SUDAN Multiple Indicator Cluster Survey 2014

Publication date: 2014

MINISTRY OF CABINET CENTRAL BUREAU OF STATISTICS SUDAN Multiple Indicator Cluster Survey 2014 Final Report UNICEF-MICS Note that in Table RH.10, the MICS indicator 5.7 (also MDG Indicator 5.2) “Delivery assisted by any skilled attendant” is presented as 77.7 percent and the indicator value has been calculated by treating the category ‘certified midwife’ as ‘skilled birth attendant’. In previous Sudan MICS 2010 final report, this indicator value was shown as 72.5 percent while the corresponding category considered as ‘skilled birth attendant’ was labeled as ‘village midwife’. In Sudan, it is reported that the Certified Midwife/Village Midwife are trained and capacitated by the MoH and therefore considered as skilled to provide adequate assistance for birth delivery. Please also note the following changes (compared to the final report that was disseminated in March 2016): As a result of a problem noticed and then corrected in the dataset, education tables ED.2 to ED.9 have been reproduced. The updated tables are attached to the end of this report. The MICS indicator references in above mentioned updated education tables (except ED.2) have been removed and an additional table, Table ED.10 (ISCED), is attached to the end of this report with corrected MICS indicator values. This table is expected to be produced in survey reports when education systems do not follow the ISCED classification and where education tables (ED3-ED.9) therefore are produced according to national standards without any reference to the MICS indicators. The table is necessary in order to present easy access to indicators for global reporting. 23 May 2016 – MICS Team UNICEF-MICS Sticky Note Note that correction has been made in Table ED.10(ISCED), column "Secondary school (ISCED 2+3)". The Sudan Multiple Indicator Cluster Survey (MICS) was carried out in 2014 by the Central Bureau of Statistics (CBS) Sudan in collaboration with the Ministry of Health as part of the global MICS programme, round 5. Technical support was provided by the United Nations Children’s Fund (UNICEF) at national, regional and headquarter levels for quality assurance. A large partnership has been established for the conduct of MICS Sudan involving UNICEF, World Health Organization (WHO), United Nations Population Fund (UNFPA), World Food Program (WFP), and the Department for International Development (DfID) UK who provided financial support. The global MICS programme was developed by UNICEF in the 1990s as an international household survey programme to support countries in the collection of internationally comparable data on a wide range of indicators on the situation of children and women. MICS surveys measure key indicators that allow countries to generate data for use in policies and programmes, and to monitor progress towards the Millennium Development Goals (MDGs) and other internationally agreed upon commitments. The specific objectives of the survey is to: x Update information for assessing the situation of children and women in Sudan based on MICS5 modules and geographical coverage of the 18 States in Sudan. x Measure the trend towards achievement of the MDGs and the goals of a World Fit For Children Plan of Action and other internationally agreed upon indicators related to children and women. x Furnish data needed for the indicators as per the global review of the Millennium Development Goals. x Contribute to the improvement of data and monitoring systems in Sudan and to strengthen technical expertise, national capacity building in the design, implementation, and analysis of such systems. x Update Census indicators and provide solid evidence for decentralization (planning and measure of progress). x Provide key evidence for social sector programming and the Poverty Reduction Strategy Paper (PRSP) under development and accountabilities for sector strategic plans and UNDAF 2013-2016. Citation: Central Bureau of Statistics (CBS), UNICEF Sudan. 2016, Multiple Indicator Cluster Survey 2014 of Sudan, Final Report. Khartoum, Sudan: UNICEF and Central Bureau of Statistics (CBS), February 2016. iii Summary Table of Survey Implementation and the Survey Population, Sudan MICS, 2014 Survey implementation Sample frame - Household Listing Sudan Population Census 2008 July, 2014 Questionnaires Household Women (age 15-49) Children under five Interviewer training July, 2014 Fieldwork 10th September – 30th October 2014 Survey sample Households - Sampled - Occupied - Interviewed - Response rate (Percent) 18,000 17,142 16,801 98.0 Children under five - Eligible - Mothers/caretakers interviewed - Response rate (Percent) 14,751 14,081 95.5 Women - Eligible for interviews - Interviewed - Response rate (Percent) 20,327 18,302 90.0 Survey population Average household size 5.9 Percentage of population living in - Urban area - Rural area States - Northern - River Nile - Red Sea - Kassala - Gadarif - Khartoum - Gezira - White Nile - Sinnar - Blue Nile - North Kordofan - South Kordofan - West Kordofan - North Darfur - West Darfur - South Darfur - Central Darfur - East Darfur 29.8 70.2 2.5 4.0 3.1 4.3 5.1 13.8 15.6 5.2 3.9 3.9 6.7 2.8 6.0 7.4 3.3 7.6 1.8 3.0 Percentage of population under: - Age 5 - Age 18 15.2 50.6 Percentage of women age 15-49 years with at least one live birth in the last 2 years 30.7 iv Housing characteristics Household or personal assets Percentage of households with - Electricity - Finished floor - Finished roofing - Finished walls 44.9 14.0 25.0 28.1 Percentage of households that own - A television - A refrigerator - Agricultural land - Farm animals/livestock 39.6 25.9 39.5 51.0 Mean number of persons per room used for sleeping 3.2 Percentage of households where at least a member has or owns a - Mobile phone - Car or truck 73.8 6.4 Summary Table of Findings1 Multiple Indicator Cluster Surveys (MICS) and Millennium Development Goals (MDG) Indicators, Sudan MICS, 2014 CHILD MORTALITY Early childhood mortalitya MICS Indicator Indicator Description Value 1.1 Neonatal mortality rate Probability of dying within the first month of life 33 1.2 MDG 4.2 Infant mortality rate Probability of dying between birth and the first birthday 52 1.3 Post-neonatal mortality rate Difference between infant and neonatal mortality rates 19 1.4 Child mortality rate Probability of dying between the first and the fifth birthdays 17 1.5 MDG 4.1 Under-five mortality rate Probability of dying between birth and the fifth birthday 68 a Indicator values are per 1,000 live births and refer to the five-year period before the survey NUTRITION Nutritional status MICS Indicator Indicator Description Value 2.1a 2.1b MDG 1.8 Underweight prevalence (a) Moderate and severe (b) Severe Percentage of children under age 5 who fall below (a) minus two standard deviations (moderate and severe) (b) minus three standard deviations (severe) of the median weight for age of the WHO standard 33.0 12.0 2.2a 2.2b Stunting prevalence (a) Moderate and severe (b) Severe Percentage of children under age 5 who fall below (a) minus two standard deviations (moderate and severe) (b) minus three standard deviations (severe) of the median height for age of the WHO standard 38.2 18.2 2.3a 2.3b Wasting prevalence (a) Moderate and severe (b) Severe Percentage of children under age 5 who fall below (a) minus two standard deviations (moderate and severe) (b) minus three standard deviations (severe) of the median weight for height of the WHO standard 16.3 4.5 1 See Appendix E for a detailed description of MICS indicators v NUTRITION Nutritional status MICS Indicator Indicator Description Value 2.4 Overweight prevalence Percentage of children under age 5 who are above two standard deviations of the median weight for height of the WHO standard 3.0 Breastfeeding and infant feeding 2.5 Children ever breastfed Percentage of women with a live birth in the last 2 years who breastfed their last live-born child at any time 95.6 2.6 Early initiation of breastfeeding Percentage of women with a live birth in the last 2 years who put their last new-born to the breast within one hour of birth 68.7 2.7 Exclusive breastfeeding under 6 months Percentage of infants under 6 months of age who are exclusively breastfed 55.4 2.8 Predominant breastfeeding under 6 months Percentage of infants under 6 months of age who received breast milk as the predominant source of nourishment during the previous day 80.8 2.9 Continued breastfeeding at 1 year Percentage of children age 12-15 months who received breast milk during the previous day 89.4 2.10 Continued breastfeeding at 2 years Percentage of children age 20-23 months who received breast milk during the previous day 48.8 2.11 Median duration of breastfeeding The age in months when 50 percent of children age 0-35 months did not receive breast milk during the previous day 21.2 2.12 Age-appropriate breastfeeding Percentage of children age 0-23 months appropriately fed during the previous day 63.1 2.13 Introduction of solid, semi-solid or soft foods Percentage of infants age 6-8 months who received solid, semi-solid or soft foods during the previous day 61.2 2.14 Milk feeding frequency for non-breastfed children Percentage of non-breastfed children age 6-23 months who received at least 2 milk feedings during the previous day 57.5 2.15 Minimum meal frequency Percentage of children age 6-23 months who received solid, semi-solid and soft foods (plus milk feeds for non- breastfed children) the minimum number of times or more during the previous day 40.7 2.16 Minimum dietary diversity Percentage of children age 6–23 months who received foods from 4 or more food groups during the previous day 28.0 2.17a 2.17b Minimum acceptable diet (a) Percentage of breastfed children age 6–23 months who had at least the minimum dietary diversity and the minimum meal frequency during the previous day (b) Percentage of non-breastfed children age 6–23 months who received at least 2 milk feedings and had at least the minimum dietary diversity not including milk feeds and the minimum meal frequency during the previous day 25.0 37.0 2.18 Bottle feeding Percentage of children age 0-23 months who were fed with a bottle during the previous day 7.3 Salt iodization 2.19 Iodized salt consumption Percentage of households with salt testing 15 parts per million or more of iodide/iodate 7.6 Low-birthweight 2.20 Low-birthweight infants Percentage of most recent live births in the last 2 years weighing below 2,500 grams at birth 32.3 2.21 Infants weighed at birth Percentage of most recent live births in the last 2 years who were weighed at birth 16.3 vi CHILD HEALTH Vaccinations MICS Indicator Indicator Description Value 3.1 Tuberculosis immunization coverage Percentage of children age 12-23 months who received BCG vaccine by their first birthday 78.5 3.2 Polio immunization coverage Percentage of children age 12-23 months who received the third dose of OPV vaccine (OPV3) by their first birthday 65.3 3.3 3.5 3.6 Pentavalanet DPT+HepB+Hib) immunization coverage Percentage of children age 12-23 months who received the third dose of Pentavalent (DPT+HepB+Hib) vaccine by their first birthday 63.9 3.4 MDG 4.3 Measles immunization coverage Percentage of children age 12-23 months who received measles vaccine by their first birthday 60.9 3.8 Full immunization coverage Percentage of children age 12-23 months who received all vaccinations recommended in the national immunization schedule by their first birthday 42.8 Tetanus toxoid 3.9 Neonatal tetanus protection Percentage of women age 15-49 years with a live birth in the last 2 years who were given at least two doses of tetanus toxoid vaccine within the appropriate interval prior to the most recent birth 58.2 Diarrhoea - Children with diarrhoea Percentage of children under age 5 with diarrhoea in the last 2 weeks 29.0 3.10 Care-seeking for diarrhoea Percentage of children under age 5 with diarrhoea in the last 2 weeks for whom advice or treatment was sought from a health facility or provider 42.7 3.11 Diarrhoea treatment with oral rehydration salts (ORS) and zinc Percentage of children under age 5 with diarrhoea in the last 2 weeks who received ORS and zinc 28.9 3.12 Diarrhoea treatment with oral rehydration therapy (ORT) and continued feeding Percentage of children under age 5 with diarrhoea in the last 2 weeks who received ORT (ORS packet, pre-packaged ORS fluid, recommended homemade fluid or increased fluids) and continued feeding during the episode of diarrhoea 59.3 Acute Respiratory Infection (ARI) symptoms - Children with ARI symptoms Percentage of children under age 5 with ARI symptoms in the last 2 weeks 17.8 3.13 Care-seeking for children with ARI symptoms Percentage of children under age 5 with ARI symptoms in the last 2 weeks for whom advice or treatment was sought from a health facility or provider 48.3 3.14 Antibiotic treatment for children with ARI symptoms Percentage of children under age 5 with ARI symptoms in the last 2 weeks who received antibiotics 59.0 Solid fuel use 3.15 Use of solid fuels for cooking Percentage of household members in households that use solid fuels as the primary source of domestic energy to cook 58.2 vii WATER AND SANITATION MICS Indicator Indicator Description Value 4.1 MDG 7.8 Use of improved drinking water sources Percentage of household members using improved sources of drinking water 68.0 4.2 Water treatment Percentage of household members in households using unimproved drinking water who use an appropriate treatment method 4.1 4.3 MDG 7.9 Use of improved sanitation Percentage of household members using improved sanitation facilities which are not shared 32.9 4.4 Safe disposal of child’s faeces Percentage of children age 0-2 years whose last stools were disposed of safely 53.0 4.5 Place for handwashing Percentage of households with a specific place for hand washing where water and soap or other cleansing agent are present 25.8 4.6 Availability of soap or other cleansing agent Percentage of households with soap or other cleansing agent 55.4 REPRODUCTIVE HEALTH Contraception and unmet need MICS Indicator Indicator Description Value - Total fertility rate Total fertility rateA for women age 15-49 years 5.2 5.1 MDG 5.4 Adolescent birth rate Age-specific fertility rateA for women age 15-19 years 87 5.2 Early childbearing Percentage of women age 20-24 years who had at least one live birth before age 18 21.5 5.3 MDG 5.3 Contraceptive prevalence rate Percentage of women age 15-49 years currently married who are using (or whose partner is using) a (modern or traditional) contraceptive method 12.2 5.4 MDG 5.6 Unmet need Percentage of women age 15-49 years who are currently married who are fecund and want to space their births or limit the number of children they have and who are not currently using contraception 26.6 A The age-specific fertility rate is defined as the number of live births to women in a specific age group during a specified period, divided by the average number of women in that age group during the same period, expressed per 1,000 women. The age-specific fertility rate for women age 15-19 years is also termed as the adolescent birth rate. The total fertility rate (TFR) is calculated by summing the age-specific fertility rates calculated for each of the 5-year age groups of women, from age 15 through to age 49. The TFR denotes the average number of children to which a woman will have given birth by the end of her reproductive years (by age 50) if current fertility rates prevailed. Maternal and newborn health 5.5a 5.5b MDG 5.5 MDG 5.5 Antenatal care coverage Percentage of women age 15-49 years with a live birth in the last 2 years who were attended during their last pregnancy that led to a live birth (a) at least once by skilled health personnel (b) at least four times by any provider 79.1 50.7 5.6 Content of antenatal care Percentage of women age 15-49 years with a live birth in the last 2 years who had their blood pressure measured and gave urine and blood samples during the last pregnancy that led to a live birth 62.8 5.7 MDG 5.2 Skilled attendant at delivery Percentage of women age 15-49 years with a live birth in the last 2 years who were attended by skilled health personnel during their most recent live birth 77.5 5.8 Institutional deliveries Percentage of women age 15-49 years with a live birth in the last 2 years whose most recent live birth was delivered in a health facility 27.7 viii 5.9 Caesarean section Percentage of women age 15-49 years whose most recent live birth in the last 2 years was delivered by caesarean section 9.1 Post-natal health checks 5.10 Post-partum stay in health facility Percentage of women age 15-49 years who stayed in the health facility for 12 hours or more after the delivery of their most recent live birth in the last 2 years 51.5 5.11 Post-natal health check for the newborn Percentage of last live births in the last 2 years who received a health check while in facility or at home following delivery, or a post-natal care visit within 2 days after delivery 27.7 5.12 Post-natal health check for the mother Percentage of women age 15-49 years who received a health check while in facility or at home following delivery, or a post-natal care visit within 2 days after delivery of their most recent live birth in the last 2 years 26.6 CHILD DEVELOPMENT MICS Indicator Indicator Description Value 6.1 Attendance to early childhood education Percentage of children age 36-59 months who are attending an early childhood education programme 22.3 6.5 Availability of children’s books Percentage of children under age 5 who have three or more children’s books 1.5 6.6 Availability of playthings Percentage of children under age 5 who play with two or more types of playthings 45.5 LITERACY AND EDUCATION MICS Indicator Indicator Description Value 7.1 MDG 2.3 Literacy rate among young people Percentage of young people age 15-24 years who are able to read a short simple statement about everyday life or who attended secondary or higher education (a) women 59.8 7.2 School readiness Percentage of children in first grade of primary school who attended pre-school during the previous school year 69.7 7.3 Net intake rate in primary education Percentage of children of school-entry age who enter the first grade of primary school 36.8 7.4 MDG 2.1 Primary school net attendance ratio (adjusted) Percentage of children of primary school age currently attending primary or secondary school 76.4 7.5 Secondary school net attendance ratio (adjusted) Percentage of children of secondary school age currently attending secondary school or higher 28.4 7.6 MDG 2.2 Children reaching last grade of primary Percentage of children entering the first grade of primary school who eventually reach last grade 80.4 7.7 Primary completion rate Number of children attending the last grade of primary school (excluding repeaters) divided by number of children of primary school completion age (age appropriate to final grade of primary school) 79.3 7.8 Transition rate to secondary school Number of children attending the last grade of primary school during the previous school year who are in the first grade of secondary school during the current school year divided by number of children attending the last grade of primary school during the previous school year 90.7 7.9 MDG 3.1 Gender parity index (primary school) Primary school net attendance ratio (adjusted) for girls divided by primary school net attendance ratio (adjusted) for boys 0.98 ix 7.10 MDG 3.1 Gender parity index (secondary school) Secondary school net attendance ratio (adjusted) for girls divided by secondary school net attendance ratio (adjusted) for boys 1.07 CHILD PROTECTION Birth registration MICS Indicator Indicator Description Value 8.1 Birth registration Percentage of children under age 5 whose births are reported registered 67.3 Child labour 8.2 Child labour Percentage of children age 5-17 years who are involved in child labour 24.9 Child discipline 8.3 Violent discipline Percentage of children age 1-14 years who experienced psychological aggression or physical punishment during the last one month 63.9 Early marriage and polygyny 8.4 Marriage before age 15 Percentage of people age 15-49 years who were first married before age 15 (a) Women 11.9 8.5 Marriage before age 18 Percentage of people age 20-49 years who were first married before age 18 (a) Women 38.0 8.6 Young people age 15-19 years currently married Percentage of young people age 15-19 years who are married (a) Women 21.2 8.7 Polygyny Percentage of people age 15-49 years who are in a polygynous union (a) Women 21.7 8.8a 8.8b Spousal age difference Percentage of young women who are married and whose spouse is 10 or more years older, (a) among women age 15-19 years, (b) among women age 20-24 years 7.9 23.0 Female genital mutilation/cutting 8.9 Approval for female genital mutilation/cutting (FGM/C) Percentage of women age 15-49 years who state that FGM/C should be continued 40.9 8.10 Prevalence of FGM/C among women Percentage of women age 15-49 years who report to have undergone any form of FGM/C 86.6 8.11 Prevalence of FGM/C among girls Percentage of daughters age 0-14 years who have undergone any form of FGM/C, as reported by mothers age 15-49 years 31.5 Attitudes towards domestic violence 8.12 Attitudes towards domestic violence Percentage of people age 15-49 years who state that a husband is justified in hitting or beating his wife in at least one of the following circumstances: (1) she goes out without telling him, (2) she neglects the children, (3) she argues with him, (4) she refuses sex with him, (5) she burns the food (a) Women 34.0 Children’s living arrangements 8.13 Children’s living arrangements Percentage of children age 0-17 years living with neither biological parent 3.4 x 8.14 Prevalence of children with one or both parents dead Percentage of children age 0-17 years with one or both biological parents dead 5.3 8.15 Children with at least one parent living abroad Percentage of children 0-17 years with at least one biological parent living abroad 1.8 HIV/AIDS AND SEXUAL BEHAVIOUR HIV/AIDS knowledge and attitudes MICS Indicator Indicator Description Value - Have heard of AIDS Percentage of people age 15-49 years who have heard of AIDS (a) Women 74.8 9.1 MDG 6.3 Knowledge about HIV prevention among young people Percentage of young people age 15-24 years who correctly identify ways of preventing the sexual transmission of HIV, and who reject major misconceptions about HIV transmission (a) Women 8.5 9.2 Knowledge of mother-to- child transmission of HIV Percentage of people age 15-49 years who correctly identify all three means of mother-to-child transmission of HIV (a) Women 28.4 9.3 Accepting attitudes towards people living with HIV Percentage of people age 15-49 years expressing accepting attitudes on all four questions toward people living with HIV (a) Women 7.9 HIV testing 9.4 People who know where to be tested for HIV Percentage of people age 15-49 years who state knowledge of a place to be tested for HIV (a) Women 17.0 9.5 People who have been tested for HIV and know the results Percentage of people age 15-49 years who have been tested for HIV in the last 12 months and who know their results (a) Women 1.6 9.6 Sexually active young people who have been tested for HIV and know the results Percentage of young people age 15-24 years who have had sex in the last 12 months, who have been tested for HIV in the last 12 months and who know their results (a) Women 1.2 9.7 HIV counselling during antenatal care Percentage of women age 15-49 years who had a live birth in the last 2 years and received antenatal care during the pregnancy of their most recent birth, reporting that they received counselling on HIV during antenatal care 4.2 9.8 HIV testing during antenatal care Percentage of women age 15-49 years who had a live birth in the last 2 years and received antenatal care during the pregnancy of their most recent birth, reporting that they were offered and accepted an HIV test during antenatal care and received their results 3.6 Orphans 9.16 MDG 6.4 Ratio of school attendance of orphans to school attendance of non-orphans Proportion attending school among children age 10-14 years who have lost both parents divided by proportion attending school among children age 10-14 years whose parents are alive and who are living with one or both parents 0.82 xi Table of Contents SUMMARY TABLE OF SURVEY IMPLEMENTATION AND THE SURVEY POPULATION, SSSUDAN MICS, 2014 . III SUMMARY TABLE OF FINDINGS . IV LIST OF TABLES . XIV LIST OF FIGURES . XVIII LIST OF ABBREVIATIONS . XXIV FOREWORD . XXVI ACKNOWLEDGEMENTS . XXVII EXECUTIVE SUMMARY . XXVIII I. INTRODUCTION . 1 1.1 Background . 1 1.2 Survey Objectives . 2 II. SAMPLE AND SURVEY METHODOLOGY. 3 2.1 Sample Design . 3 2.2 Questionnaires . 3 2.3 Training . 4 2.4 Pre-test . 4 2.5 Field work . 4 2.6 Data Processing . 5 III. Sample Coverage and the Characteristics of Households and Respondents . 6 3.1 Sample Coverage. 6 3.2 Characteristics of Households . 8 3.3 Characteristics of Female Respondents 15-49 Years of Age and Children Under-5 . 11 3.4 Housing Characteristics, Asset Ownership, and Wealth Quintiles . 15 3.5 Household Assets . 18 IV. Child Mortality . 23 4.2. Status of Child Mortality at national level . 24 4.3 Geographic Disparity in Childhood Mortality . 25 4.4 Disparity in Childhood mortality by socioeconomic and demographic patterns . 28 4.5 Trend in Childhood mortality rate using different sources. 30 V. Nutrition . 33 5.1 Low Birth Weight . 33 5.2 Nutritional Status . 36 5.2.1 Overall Status of Child Malnutrition . 40 xii 5.2.2 Geographic Inequity in Child Malnutrition . 41 5.2.3 Disparity of Child Malnutrition by Wealth Index Quintile . 43 5.2.4 Disparity in Child Malnutrition by Mother’s Education . 44 5.2.5 Trends in Under-five Nutritional Status from 2006 to 2014 . 45 5.3 Breastfeeding and Infant and Young Child Feeding . 47 5.3.1 Initial Breastfeeding . 49 5.3.2 Young Child Feeding . 51 5.4 Salt Iodization . 64 5.5 Children’s Vitamin A supplementation . 67 VI. Child Health . 69 6.1 Vaccinations . 69 6.2 Neonatal Tetanus Protection . 76 6.3 Care of Illness . 78 6.3.1 Diarrhoea . 80 6.3.2 Acute Respiratory Infections . 95 6.3.3 Solid Fuel Use . 98 VII. WATER AND SANITATION . 103 7.1 Use of Improved Water Sources . 103 7.2 Use of Improved Sanitation . 113 7.3 Handwashing . 125 VIII. REPRODUCTIVE HEALTH . 130 8.1 Fertility . 130 8.2 Contraception . 136 8.3 Unmet Need . 140 8.4 Antenatal Care (ANC) . 142 8.5 Assistance at Delivery . 150 8.6 Place of Delivery . 153 8.7 Post-natal Health Checks . 155 IX. Child Development . 169 9.1 Early Childhood Care and Education . 169 9.2 Quality of Care . 171 X. Literacy and Education . 173 10.1 Literacy among Young Women . 173 10.2 School Readiness . 174 10.3 Primary and Secondary School Participation . 176 XI. Child Protection . 192 xiii 11.1 Birth Registration . 192 11.2 Child Labour . 194 11.3 Child Discipline . 200 11.4 Early Marriage and Polygamy . 206 11.5 Female Genital Mutilation/Cutting . 214 11.6 ATTITUDES TOWARD DOMESTIC VIOLENCE . 219 11.7 Children’s Living Arrangements . 221 XII. HIV/AIDS and Sexual Behaviour . 226 12.1 Knowledge about HIV Transmission and Misconceptions about HIV . 226 12.2 Accepting Attitudes toward People Living with HIV . 231 12.3 Knowledge of a Place for HIV Testing, Counselling and Testing during Antenatal Care. 233 12.4 HIV Indicators for Young Women . 237 XIII: Household Food Security . 240 13.1 Household Food Consumption . 242 13.2 Food Coping Strategies . 248 Appendix A: Sample Design . 253 Sample Size and Sample Allocation . 253 Sampling Frame and Selection of Clusters. 255 Listing Activities . 255 Selection of Households . 255 Calculation of Sample Weights . 255 Appendix B: List of Personnel Involved in the Survey. 258 Appendix C: Estimates of Sampling Errors . 266 Appendix D: Data Quality Tables . 290 APPENDIX E: SUDAN MICS 2014INDICATORS: NUMERATORS AND DENOMINATORS . 311 Appendix F1: Household Questionnaire . 322 Appendix F2: Questionnaire for Individual Women . 349 Appendix F3: Questionnaire for Children Under-Five . 381 xiv List of Tables Table HH.1: Results of household, women's, and under-5 interviews . 7 Table HH.2: Age distribution of household population by sex . 8 Table HH.3: Household composition . 10 Table HH.4: Women's background characteristics . 12 Table HH.5: Under-5's background characteristics. 13 Table HH.6: Housing characteristics . 16 Table HH.7: Household and personal assets . 20 Table HH.8: Wealth quintiles . 22 Table CM.1: Early childhood mortality rates . 24 Table CM.2: Early childhood mortality rates by socioeconomic characteristics . 26 Table CM.3: Early childhood mortality rates by demographic characteristics. 29 Table NU.1: Low birth weight infants.……………………………….……………………………….36 Table NU.2: Nutritional status of children . 39 Table NU.3: Initial breastfeeding . 51 Table NU.4: Breastfeeding . 53 Table NU.5: Duration of breastfeeding . 56 Table NU.6: Age-appropriate breastfeeding . 58 Table NU.7: Introduction of solid, semi-solid, or soft foods . 60 Table NU.8: Infant and young child feeding (IYCF) practices . 61 Table NU.9: Bottle feeding . 64 Table NU.10: Iodized salt consumption . 67 Table NU.11: Children’s Vitamin A Supplementation . 68 Table CH.1: Vaccinations in the first years of life . 72 Table CH.2: Vaccinations by background characteristics . 75 Table CH.3: Neonatal tetanus protection . 78 Table CH.4: Reported disease episodes . 80 Table CH.5: Care-seeking during diarrhoea . 82 Table CH.6: Feeding practices during diarrhoea . 84 Table CH.7: Oral rehydration solutions, recommended homemade fluids, and zinc . 87 Table CH.8: Oral rehydration therapy with continued feeding and other treatments . 90 Table CH.9: Source of ORS and zinc . 94 Table CH.10: Care-seeking for and antibiotic treatment of symptoms of acute respiratory infection (ARI) . 96 Table CH.11: Knowledge of the two danger signs of pneumonia . 98 Table CH.12: Solid fuel use . 100 Table CH.13: Solid fuel use by place of cooking . 102 Table WS.1: Use of improved water sources . 107 Table WS.2: Household water treatment . 109 Table WS.3: Time to source of drinking water . 111 Table WS.4: Person collecting water . 113 Table WS.5: Types of sanitation facilities . 116 Table WS.6: Use and sharing of sanitation facilities . 119 Table WS.7: Drinking water and sanitation ladders . 123 Table WS.8: Disposal of child's faeces . 125 xv Table WS.9: Water and soap at place for handwashing . 128 Table WS.10: Availability of soap or other cleansing agent . 130 Table RH.1: Fertility rates . 132 Table RH.2: Adolescent birth rate and total fertility rate . 134 Table RH.3: Early childbearing . 135 Table RH.4: Trends in early childbearing . 136 Table RH.5: Use of contraception . 138 Table RH.6: Unmet need for contraception . 142 Table RH.7: Antenatal care coverage . 145 Table RH.8: Number of antenatal care visits and timing of first visit . 148 Table RH.9: Content of antenatal care . 150 Table RH.10: Assistance during delivery and caesarean section . 153 Table RH.11: Place of delivery . 155 Table RH.12: Post-partum stay in health facility . 157 Table RH.13: Post-natal health checks for new-borns . 159 Table RH.14: Post-natal care visits for new-borns within one week of birth . 161 Table RH.15: Post-natal health checks for mothers . 164 Table RH.16: Post-natal care visits for mothers within one week of birth . 166 Table RH.17: Post-natal health checks for mothers and new-borns . 168 Table CD.1: Early childhood education. 171 Table CD.3: Learning materials . 172 Table ED.1: Literacy among young women . 174 Table ED.2: School readiness . 176 Table ED.3: Primary school entry . 177 Table ED.4: Primary school attendance and out of school children . 180 Table ED.5: Secondary school attendance and out of school children . 184 Table ED.6: Children reaching last grade of primary school . 185 Table ED.7: Primary school completion and transition to secondary school. 187 Table ED.8: Education gender parity . 188 Table ED.9: Out of school gender parity . 190 Table CP.1: Birth registration . 193 Table CP.2: Children's involvement in economic activities . 197 Table CP.3: Children's involvement in household chores . 198 Table CP.4: Child labour . 200 Table CP.5: Child discipline . 204 Table CP.6: Attitudes toward physical punishment . 206 Table CP.7: Early marriage and polygyny among women . 210 Table CP.8: Trends in early marriage among women . 212 Table CP.9: Spousal age difference . 214 Table CP.10: Female genital mutilation/cutting (FGM/C) among women . 215 Table CP.11: Female genital mutilation/cutting (FGM/C) among girls . 217 Table CP.12: Approval of female genital mutilation/cutting (FGM/C) . 219 Table CP.13: Attitudes toward domestic violence among women . 221 Table CP.14: Children's living arrangements and orphanhood . 223 Table CP.15: Children with parents living abroad . 225 xvi Table HA.1: Knowledge about HIV transmission, misconceptions about HIV, and comprehensive knowledge about HIV transmission among women . 227 Table HA.2: Knowledge of mother-to-child HIV transmission among women . 231 Table HA.3: Accepting attitudes toward people living with HIV among women . 232 Table HA.4: Knowledge of a place for HIV testing among women . 235 Table HA.5: HIV counselling and testing during antenatal care . 237 Table HA.7: Key HIV and AIDS indicators among young women………….………………………………….239 Table HA.9: School attendance of orphans and non-orphans.…………….…………………………………240 Table HFS.1: Proportion of households with poor, borderline and acceptable food consumption. . 243 Table HFS.2: Proportion of househlds who employ food coping strategies . 250 Appendices: Table SD.1: Allocation of Sample Clusters (Primary Sampling Units) to Sampling Strata . 255 Table SE1: Indicators selected for sampling error calculations . 269 Table SE2: Sampling errors: Total Sample - Sudan . 270 Table SE3: Sampling errors: Urban . 271 Table SE4: Sampling errors: Rural . 272 Table SE5: Sampling errors: Northern state . 273 Table SE6: Sampling errors: River Nile state. 274 Table SE7: Sampling errors: Red Sea state . 275 Table SE8: Sampling errors: Kasala state . 276 Table SE9: Sampling errors: Gadarif state . 277 Table SE10: Sampling errors: Kharoum state . 278 Table SE11: Sampling errors: Gizera state . 279 Table SE12: Sampling errors: White Nile state . 280 Table SE13: Sampling errors: Sinnar state . 281 Table SE14: Sampling errors: Blue Nile state . 282 Table SE15: Sampling errors: North Kordofan state . 283 Table SE16: Sampling errors: South Kordofan state . 284 Table SE17: Sampling errors: West Kordofan state . 285 Table SE18: Sampling errors: North Darfur state . 286 Table SE19: Sampling errors: West Darfur state . 287 Table SE20: Sampling errors: South Darfur state . 288 Table SE21: Sampling errors: Central Darfur state . 289 Table SE22: Sampling errors: East Darfur state . 290 Table DQ.1: Age distribution of household population . 291 Table DQ.2: Age distribution of eligible and interviewed women . 294 Table DQ.4: Age distribution of children in household and under-5 questionnaires . 294 Table DQ.5: Birth date reporting: Household population . 295 Table DQ.6: Birth date and age reporting: Women . 296 Table DQ.8: Birth date and age reporting: Under-5s . 297 Table DQ.9: Birth date reporting: Children, adolescents and young people . 298 Table DQ.10: Birth date reporting: First and last births. 299 xvii Table DQ.11: Completeness of reporting . 299 Table DQ.12: Completeness of information for anthropometric indicators: Underweight . 300 Table DQ.13: Completeness of information for anthropometric indicators: Stunting . 301 Table DQ.14: Completeness of information for anthropometric indicators: Wasting . 301 Table DQ.15: Heaping in anthropometric measurements . 302 Table DQ.16: Observation of birth certificates . 303 Table DQ.17: Observation of vaccination cards . 304 Table DQ.18: Observation of women's health cards . 305 Table DQ.20: Respondent to the under-5 questionnaire . 306 Table DQ.21: Selection of children age 1-17 years for the child labour and child discipline modules . 306 Table DQ.22: School attendance by single age . 307 Table DQ.23: Sex ratio at birth among children ever born and living . 309 Table DQ.24: Births by periods preceding the survey . 309 Table DQ.25: Reporting of age at death in days . 310 Table DQ.26: Reporting of age at death in months . 311 xviii List of Figures Figure HH.1: Age and sex distribution of household population . 9 Figure CM.1: Early childhood mortality rates …………………………………….………………………………………25 Figure CM.2: Under-5 mortality rates by state, . 27 Figure CM.2a: Under-5 mortality rates by geographich area . 28 Figure CM.2b: Under-5 mortality rates by sex of child and wealth quintile . 28 Figure CM.2c: Under-5 mortality rates by mother’s education . 29 Figure CM.3: Trend in under-5 mortality rates. 31 Figure CM.3a: Trend in under-5 mortality rates by sex of child and wealth quintile as estimated at SHHS 2010 and MICS 2014 . 33 Figure NU.1a: Underweight, stunted and wasted children under-five years………. . 41 Figure NU.1: Under-five children underweight (moderate and severe) by state . 42 Figure NU.1b: Under-five children stunted (moderate and severe) by state . 43 Figure NU.1c: Under-five children wasted (moderate and severe) by state . 44 Figure NU.1d: Under-five children underweight, stunted or wasted by household wealth quintile . 45 Figure NU.1e: Trend in percentage of children under-5 underweight, stunted and wasted (moderate and severe) from SHHS 2006, SHHS, 2010 and MICS . 46 Figure NU.1f: Trend in inequality of poorest and riches under5 children underweight, stunted or wated in Sudan from SHHS 2010 to MICS 2014 . 47 Figure NU.1g: Trend in under-5 children stunted (moderate and severe) from SHHS 2010 to MICS 2014. 48 Figure NU.2: Initiation of breastfeeding . 50 Figure NU.3: Exclusive breastfeeding . 54 Figure NU.4: Infant feeding patterns by age . 55 Figure NU.5: Consumption of iodized salt . 66 Figure NU.6: Percentage of children who received Vitamin A in last six months . 69 Figure CH.1: Vaccinations by age 12 months (measles by 24 months) . 73 Figure CH.1a: Measles vaccination coverage by states: Children age 12-23 months and 24-35 months currently vaccinated against measles………………………………….……………………74 Figure CH.2: Children under-5 with diarrhoea who received ORS or recommended homemade liquids . 89 Figure CH.3: Children under-5 with diarrhoea receiving oral rehydration therapy (ORT) and continued feeding . 92 Figure CH.3a: Sources of ORS and zinc . 93 Figure WS.1: Household members access to drinking water by source . 105 Figure WS.1a: Household members with access to improved water sources by State . 106 Figure WS.1b: Household members with access to improved water sources by urban/rural and wealth index quintile . 106 Figure WS.2a: Households using Improved sanitation facility. 115 Figure WS.2: Household members by use and sharing of sanitation facilities . 121 Figure WS.2b: Household members practicing open defecation by urban and rural residence xix and by state………………………………………………………………………………….…………………….121 Figure WS.3: Household members using improved sanitation, by wealth . 124 Figure RH.1: Age-specific fertility rates by area . 133 Figure RH.2: Differentials in contraceptive use . 140 Figure RH.3a: Antenatal care service providers . 146 Figure RH.3b: Women age 15-49 years with a live birth in the last two years who made 4 or more antenatal care visits, by state, area and mother’s education . 147 Figure RH.3: Person assisting at delivery . 152 Figure ED.1a: Children of primary school age attending primary (adjusted net attendance ratio) for boys and girls by state and by urban/rural area . 179 Figure ED.1b: Children of secondary school age attending secondary school (adjusted net attendance ratio) for boys and girls by state and by urban/rural area . 183 Figure ED.1c: Girls out of school in primary and secondary by wealth index quintiles . 190 Figure ED.1: Education indicators by sex . 192 Figure CP.1: Children under age five whose births are registered . 195 Figure CP.2a: Children age 1-14 years experiencing any violent discipline method by sex, state and rural/urban disaggregation . 203 Figure CP.2: Child disciplining methods, children age 1-14 years . 205 igure CP.3a: Women age 20-49 years who first married or entered a maritial union before their 18th birthday.………………………………………………………………………………………….….209 Figure CP.3: Early marriage before ages 15 and 18 by age group of women 15-49 years . 213 Figure CP.3b: Women age 15-49 years and girls age 0-14 years by FGM/C status and by education of the woman or mother of the child . 218 Figure HA.1: Women age 15-49 years who have comprehensive knowledge of HIV transmission . 230 Figure HA.2: Accepting attitudes toward people living with HIV/AIDS . 234 Figure HFS.1: Household food consumption score by states . 244 Figure HFS.2a: Household food consumption, by urban and rural (part one) ….………….………245 Figure HFS.2b: Household food consumption, by urban and rural (part two) . 246 Figure HFS.3a: Number of days foods are consumed (part one)….…….……….….……….…….247 Figure HFS.3b: Number of days foods are consumed (part two).……….……………….……….248 Figure HFS.3c: Number of days foods are consumed (part three) . 248 Figure HFS.3d: Number of days foods are consumed (part four) . 249 Figure HFS.4a: Food coping strategies (part one) . 251 Figure HFS.4b: Food coping strategies (part two) . 251 Figure HFS.4c: Food coping strategies (part three) . 252 Figure HFS.4d: Food coping strategies (part four) . 253 Appendix: Figure DQ.1: Number of household population by single ages . 293 Figure DQ.2: Weight and height/length measurements by digits reported for the decimal points. 302 xxiv List of Abbreviations AIDS Acquired Immune Deficiency Syndrome ANC Antenatal Care ARI Acute Respiratory Infection BCG Bacillis-Calmette-Geuerin (Tuberculosis) CBS Central Bureau of Statistics CPR Contraceptive Prevalence Rate CRC Convention on the Rights of the Child CSPro Census and Survey Processing System DHS Demographic and Health Survey DPT Diphtheria Pertussis Tetanus EPI Expanded Programme on Immunization FGM/C Female Genital Mutilation/Cutting FMoH Federal Ministry of Health FP Family Planning GPI Gender Parity Index HB Hepatitis B HIB Haemophilus Influenza type B HIV Human Immunodeficiency Virus ICPD International Conference on Population and Development IDD Iodine Deficiency Disorders IGME Inter-Agency Group on Mortality Estimation IMR Infant Mortality Rate ITN Insecticide Treated Net IUD Intrauterine Device JICA Japan International Cooperation Agency JMP Joint Monitoring Programme LAM Lactational Amenorrhea Method MD Millennium Declaration MDG Millennium Development Goals MICS Multiple Indicator Cluster Survey MICS4 Multiple Indicator Cluster Survey Round 4 MICS5 Fifth global round of Multiple Indicator Clusters Surveys programme MMR Measles, Mumps, and Rubella NAR Net Attendance Rate NCCW National Council for Child Welfare NIDs National Immunisation Days NMR Neonatal Mortality Rate ORT Oral Rehydration Treatment PAPFAM Pan Arab Project for Family Health PRSP Poverty Reduction Strategy Paper RH Reproductive Health SHHS Sudan Household Health Survey SHHS2 Sudan Household Health Survey - Second Round xxv SPSS Statistical Package for Social Sciences STI Sexually Transmitted Infections TBA Traditional Birth Attendant TT Tetanus Toxoid USMR Under 5 Mortality Rate UNAIDS United Nations Programme on HIV/ AIDS UNDP United Nations Development Programme UNFPA United Nations Population Fund UNGASS United Nations General Assembly Special Session on HIV/AIDS UNICEF United Nations Children's Fund USAID United States Agency for International Development Vit. A Vitamin A WFFC World Fit for Children WFP World Food Programme WHO World Health Organization xxvi Foreword The Government of Sudan represented by the Ministry of Cabinet Affairs and UNICEF Representative in Sudan are pleased to launch this Multiple Indicator Cluster Survey (2014) Final Report for Sudan. This report of statistically sound and internationally comparable data source provides a credible evidence for informing policies and programmes, and for monitoring Sudan’s progress toward national development plan and the Sustainable Development Goals (SDGs). Under the leadership of the Director General of the Central Bureau of Statistics (CBS), a steering committee comprising of representatives from national and international institutions that contribute to the goals of the survey worked tirelessly for the past year to present a coherent and nationally validated information related to nutrition, education, child health, maternal health, HIV/AIDS, water and sanitation and child protection. The availability of accurate and current nationwide data provided by MICS 2014 represents a key assest for Sudan after the separation of South Sudan in 2011. We are grateful for the role played by a wide range of partnerships during the implementation of this survey with special reference to the Government of Sudan including all relevant line ministries, states, and local authorities. We are also grateful for the technical and financial support provided by UNICEF, WFP, UNFPA, WHO and DFID for this exercise. In the light of the above we encourage all policy makers, humanitarian and development partners, academic institutions, and indeed the people of Sudan to make effective use of this report to plan, monitor and evaluate relevant goals and objectives addressing the survival, development and protection rights of children in the country. Signed on 03rd March 2016, by: xxvii Acknowledgements The fourth Sudan Multiple Indicator Cluster Survey (MICS5), was conducted from August to December 2014 at national level covering asll eighteen states. The MICS was designed to collect information on a variety of socioeconomic and health indicators required to inform the planning, implementation and monitoring of national policies and programmes for the enhancement of the welfare of women and children. The MICS plays a critical role in informing national policies such as the Sudan Strategic Plan (2012-2016); and the sector strategic plans of health, education, and water and sanitation. It also serves as an instrument to measure progress towards the achievement of national and international committements for children and women wellbeing (MDG2015, SDG 2030). The Central Bureau of Statistics (CBS) wishes to express sincere gratitude to the various institutions and individuals who worked tirelessly to make the survey a success. Their commitment and dedication to this exercise ensured quality information for data analysis and report writing.This survey was made possible through financial and technical support from the United Nations Children’s Fund (UNICEF), the United Nations Population Fund (UNFPA), the World Food Programme (WFP), the Department for International Development (DFID). In addition, the expertise provided by various consultants (at global, regional and national levels) in the areas of sampling, training, fieldwork, data processing and report writing, and input from various stakeholders who participated in MICS workshops cannot be overemphasized. CBS is very grateful to the technical guidance, capacity building and quality assurance guaranteed by UNICEF’s experts in Sudan’s Office, Regional Office and HQ during all steps of the MICS design and implementation. This survey would not have been possible without the sustained commitment of the Survey Management Team (SMT), field and data entry and processing personnel, and patience and cooperation of respondents. CBS is thankfull to the team of Analyst and Report writers who have been devoted in the completion of statistical and demographic data analysis and writing of 13 Chapters. CBS would like to acknowledge the following institutions who were members of the MICS Steering and Technical Committees for their invaluable contributions towards the accomplishment of the survey: x Director General Central Bureau of Statistics Chairperson x Survey Technical Coordinator Reporter x Under Secretary, Federal Ministry of Health Member x Under Secretary Ministry of Education Member x Under Secretary Ministry of Welfare and S. Security Member x Under Secretary, Ministry of Environment and Public Member x UNICEF Representative Member x UNFPA Representative Member x WHO Representative Member x WFP Representative Member x Secretary General of National population Council Member xxviii Executive Summary This Sudan Multiple Indicator Cluster Survey (MICS5) is a nationally representative survey of households, women, and children with fieldwork conducted from August to November 2014. The survey was conducted by the central bureau of statistics (CBS) in collaboration with the ministries of health, welfare, general education, national environment, and national water cooperation. The survey provides statistically sound and internationally comparable data essential for developing evidence- based policies and programmes, and for monitoring progress toward national goals and global commitments. Among these global commitments are those emanating from the World Fit for Children Declaration and Plan of Action, the goals of the United Nations General Assembly Special Session on HIV/AIDS, the Education for All Declaration and the Millennium Development Goals (MDGs). Interviews were successfully completed in 15,801 households drawn from a sample 18,000 households all 18 states of Sudan with an overall response rate of 98 percent. The main results from the survey are summarized below. Child Mortality Child mortality was measured in this survey through a methodology that produced retrospective estimates (for the year 2012) of the infant mortality rate (IMR) and under-five mortality rate (U5MR). The survey estimated the IMR as 52 per 1000 live births and the U5MR as 68 per 1000 live births indicating that 76.5 percent of under-five deaths are infant deaths. Findings reveal that there is inequality of probabilities of dying between urban and rural areas: under- five mortality and infant mortality rates are respectively 56.5 and 11.8 deaths for 1,000 live births in urban area, 72.8 and 19.3 in rural area. Also the risk of dying of under-five children before the five birthday widely varies among states with East Darfur (111.7/1,000 live births) the highest and Northern state (29.9/1,000 live births) the lowest. There is also disparity in child mortality in Sudan by wealth index quintile: U5MR is estimated at 84/1,000 live births and 39/1,000 live births for the poorest and richest quintile respectively. Nutrition The survey indicated that there is high prevalence of child malnutrition is high in Sudan: one-third (33 percent) of under-five children are underweight, nearly two in five (38.2 percent) children under-five years are stunted (too short for their age), and one in six (16.3 percent) children is wasted (too thin for their height). The prevalence of underweight is 23.2 percent in urban area as compared to 37.1 percent in rural area; there is a very wide gap in child stunting between rural areas (43 percent) and urban areas (27.1 percent). Breastfeeding There is a high breastfeeding practice in Sudan with approximately 96 percent of children ever breastfed. However only 69 percent of the babies are breastfed for the first time within one hour of birth, 28 percent of newborns are given pre-lacteal feeds birth. Fifty-five (55.4 percent) of children 0- 5 months are exclusively breastfed, nearly 90 percent aged 12-15 months are having continued breastfeeding at year of age and nearly half (48.8 percent) of the children aged 20-23 months are receiving continued breastfeeding at 2 years of age. xxix Salt Iodization Sudan does not have a national law on salt iodization and as a consequence only 7.6 percent of households have adequately iodized salt (which contains 15 parts per million ppm or more of iodine). Use of adequately iodized salt is lowest in States of West Kordofan (2.9 percent), Blue Nile (3.1 percent), Red Sea (3.2 percent) and Khartoum (3.3 percent) and relatively highest use is recorded in East Darfur (18.1 percent), Central Darfur (14.8 percent) and Sinnar (15.6 percent). There is no difference of iodized salt consumption between the richest (8.8 percent) and poorest households (8.0 percent). Vitamin A Supplementation There is high coverage of vitamin A supplementation in Sudan; 78 percent of children under five years receive Vitamin A during the last 6 months preceding the survey. The coverage of Vitamin A varies by State, age of children, mother’s education and wealth index quintile. Low Birth Weight Weight at birth is an excellent indicator of both a mother's health and nutritional status and also a newborn's chances for survival, growth, long-term health and psychosocial development. The Sudan’s 2014 MICS states that 16.3 percent of births were weighed at birth. Approximately 32.3 percent of infants born during the last two years were estimated to weigh less than 2,500 grams at birth. The prevalence of low birth weight varies by urban 27.9 percent and rural area 33.9 percent and by mother’s education from 33.7 percent among children for whose mothers are not educated to 23.7 percent for children whose mothers have higher level of education The highest prevalence of low birth weight was observed in states of North Darfur (47.5 percent), East Darfur (46.9percent), North Kordofan (41.4percent) and West Kordofan (36percent) in comparison to the low prevalence observed in states of River Nile (17.2 percent), Khartoum (22.2 percent), Gadarif (23.9 percent) and Blue Nile (25.7 percent). Child Health Immunization Approximately 78.5 percent of children age 12-23 months received a BCG vaccination by the age of 12 by their first birthday. About sixty-four (63.9 percent) of the children received the third dose of Pentavalent (DPT+HepB+Hib). Similarly, 65.3 percent by the third dose of Polio vaccination, 58.9 percent for the first dose of measles vaccine by 12-23 months by 12 months of age. Overall, the percentage of children who had all the recommended vaccinations by their first birthday is low at only 42.8 percent. Tetanus Toxoid Thirty-two (32.1 percent) of surveyed women aged 15-49 years who gave birth during the year prior to the MICS5 survey received at least two doses of tetanus toxoid (TT) vaccine during their pregnancy and 58.2 percent of the women were protected against neonatal tetanus due to previous TT vaccinations. The data also showed a higher percentage of women aged 15-49 years in urban areas with a live birth in the last two years prior to the survey were protected against neonatal tetanus (65.9 percent) than their counterparts in rural areas (55.4 percent). xxx Oral Rehydration Treatment Approximately 34 percent of the children age 0-59 months with diarrhoea received ORS or increased fluids. Nearly sixty (59.3 percent) of children received ORT with continued feeding as recommended. There are notable differences in ORT and continued feeding during diarrhoea among the states ranging from percent 16.9 percent in River Nile State to 31.3 percent in West Kordofam. Care Seeking and Antibiotic Treatment of Pneumonia Approximately half (48.3 percent) of children age 0-59 months with symptoms of ARI were taken to a qualified provider. While 59 percent of the children received antibiotics during the two weeks prior to the survey. The percentage was considerably higher in urban than in rural areas, and ranged from 49 percent in South Darfur state to 78 percent in River Nile state. Antibiotic treatment of ARI symptoms is low among the poorest households and among children whose mothers/caretakers have less than secondary education. Only about five (4.5 percent) of the children with symptoms of ARI received treatment from community health workers. Mothers’ knowledge of danger signs is an important determinant of care-seeking behaviour. In the Sudan MICS 2014, 26.9 percent of women knew at least one of the two danger signs of pneumonia – fast and/or difficult breathing. The most commonly identified symptom for taking a child to a health facility is fever accounting for more than 80 percent of respondents. About 11.7 percent and 20.9 percent of mothers identified fast breathing and difficult breathing respectively as symptoms for taking children immediately to a health care provider. Solid Fuel Use Overall, more than 58.2 percent of the household population in Sudan of use solid fuels for cooking, consisting mainly of wood (40.7 percent). Use of solid fuels is low in urban areas (40.7 percent), but high in rural areas, used by two-thirds (66 percent) of household members. Very big difference between the states as use of solid fuels ranges from 99.9 percent in Central Darfur and to 13.3 percent in River Nile State Water and Sanitation The MICS5 estimates of the Sudan population’s access to improved sources of drinking water (68 percent). Overall, more than two-fifths (41.4 percent) of the household members used drinking water that was piped into their dwelling or into their compound, yard or plot or into public tap/standpipe. Nearly 41 percent of the population are living in households using improved sanitation facilities. Access to improved sanitation facilities widely varies between urban areas (39.3 percent) as compared with 28.2 percent rural areas. About 30 percent of the households in Sudan practiced open defecation (no facility, bush field). Use of open defecation as a method faecal disposal ranged from 1.7 percent in Khartoum State to 44.9 percent in Kassala State. Overall 28 percent of the households in Sudan have access to both improved sources of drinking water and improved sources of sanitation. This figure greatly varies among households along the wealth index status ladder; 3 percent in households in the poorest quintile compared to 75 percent in households in the richest quintile xxxi Reproductive Health Fertility The Total Fertility Rate (FTR) for the three years preceding the MICS5 survey is 5.2 births per woman. Fertility is considerably higher in rural areas (5.6 births per woman) than in the urban areas (4.4 births per woman). The urban-rural difference in fertility is most pronounced for women in the 20-24 age group: 167 births per 1,000 women in urban areas versus 225 births per 1,000 women in rural areas. The overall age pattern of fertility, as reflected in the ASFRs, indicates that childbearing begins early. Fertility is low among adolescents, increases to a peak of 259 births per 1,000 among women age 25-29 Contraception Current use of contraception in Sudan MICS5 was reported as 12.2 percent of women currently married 2 . The most popular method was the pill which is used by about one in ten married women in Sudan (9.0 percent). Almost 87.8 percent of the married women reported that they are not using any form of contraception. The survey results show that contraceptive prevalence ranges from 2.9 percent in Central Darfur to 26.5 percent in Khartoum State. About 20.1 percent of married women in urban and 9.0 percent in rural areas use a method of contraception. Women’s level of education is strongly associated with contraceptive prevalence; prevalence rising from 4.4 percent among those with no education to 13.3 percent among those with primary education, and to 21 percent and 27.6 percent among those with secondary and higher education respectively. About 27 percent of women 15-49 years reported for unmet need in the Sudan MICS5. Antenatal Care Overall, the proportion of women who received ANC from any skilled provider (i.e., a doctor, nurse, or midwife) was 79.1 percent while those women who did not receive ANC was 19.9 percent. There exists rural-urban differentials in favour of women who received antenatal care in urban areas (90.8 percent) compared to women in rural areas (74.9 percent). There was also significant differences among the states for women who received ANC from any provider; ranging from 61.8 percent of women in South Darfur state to 97.1 percent of the women in Khartoum state. Assistance at Delivery About 80 percent of births in Sudan that occurred in the two years preceding the MICS 2014 survey were delivered by the assistance of skilled personnel. This percentage is higher in urban areas with 92.9 percent of the deliveries by skilled personnel than 71.9 percent in rural areas. Deliveries by skilled personnel varied widely in the States ranging from 37.5 percent in Central Darfur state 99 percent in Northern State. Also delivery by skilled personnel is found to be strongly influenced by the level of education; assistance by skilled delivery attendant for women with no education was 58.5 percent, while among 2 All references to “married women” in this chapter include women in marital union as well. xxxii those with primary education it was 86.7 percent, and among women with secondary and higher education levels it was 95.7 percent and 97.6 percent respectively. More than half of the births (55 percent) in the two years preceding the MICS survey were delivered with the assistance of a certified midwife. Medical doctors assisted with the delivery of 19.2 percent of births and the births delivered by assistance of Traditional Birth Attendants (TBAs) with is 18 percent. Place of Delivery Slightly more than a quarter (27.7 percent) of births in Sudan are delivered in a health facility; of which 26.1 percent occur in public sector facilities while only 1.6 percent of the deliveries occur in private sector facilities. The MICS results also indicate that 71.3 percent of the deliveries takes place at home. Women in urban areas (45.2 percent) are more than twice as likely to deliver in a health facility as their rural counterparts (21.5 percent). Women with higher levels of educational attainment are more likely to deliver in a health facility than women with less education or no education. Specifically; 11.5 percent of women who had delivered in a health facility no education compared to 25.8 percent of the women with primary education, to 49.8 percent of the women with secondary education, and to 75.5 percent of the women with higher level of education. Post-natal checks Overall, 51.5 percent of women who gave birth in a health facility stay 12 hours or more in the facility after delivery. Across the country, the percentage of women who stay 12 hours or more varies from 29.3 percent in Central Darfur to 73.2 percent in White Nile State. The survey results indicated small difference between proportions of those delivering in public and private facilities and who stay 12 hours or more in the facility. Child Development About 22.3 percent of children aged 36-59 months are attending an organised early childhood education programme in Sudan. Urban-rural and statestate differentials are notable – the figure is as high as 44.6 percent in urban areas, compared to 13.9 percent in rural areas. Among children aged 36-59 months, attendance to early childhood education programmes is more prevalent in Khartoum state (44.3 percent), and lowest in the West Kordofan (4.3 percent). There are also significant differences among children living in different socioeconomic backgrounds; 59.4 percent of children living in the richest (20 percent) households attend such programmes, while the figure drops to 6.9 percent among children in the poorest households. Literacy and Education Adult Literacy The MICS5 indicates that about six out of ten ( 59.8 percent) young women in Sudan are literate and that literacy status varies greatly by area (79.8 percent in urban areas and 50 percent in rural areas). Of women who stated that primary school was their highest level of education, just 43.7 percent were actually able to read a simple statement shown to them. xxxiii The proportion of women who were literate was higher at 63.4 percent among women aged 15-19 years than that among women age 20-24 years (55.6 percent).The proportion of literate women (aged 15-24 years) also varied by their household wealth. The proportion of literate women was much higher among those belonging to households in the richest quintile (92.2 percent) than those belonging to households in the poorest quintile (31.2 percent). Pre-School Attendance and School Readiness Approximately seventy (69.7) percent of children who are currently attending the first grade of primary school were attending pre-school the previous year with varying proportion of children in first grade in urban areas (81.0 percent) had attended pre-school the previous year compared to 64.7 percent among children living in rural areas. State differentials are also very significant; first graders in Khartoum state have attended pre-school nearly 3 times as likely (87 percent) as their counterparts in Central Darfur State (30.5 percent). Socioeconomic status appears to have a positive correlation with school readiness – while the indicator is only 50.6 percent among the poorest households, it increases to 86.9 percent among children living in the richest households. Primary and Secondary School Participation Less than forty (36.8) percent children who are of primary school entry age in Sudan are attending the first grade of primary school. Sex differentials do not exist; however, significant differentials are present by state and urban-rural areas. In Northern state, for instance, percentage of children entering grade one is 73.6 percent, while those entering at grade one in Western Kordofan state is 13.4 percent. Those entering grade one in urban areas (56.6 percent) is nearly twice as those in rural areas (29.5 percent). A positive correlation with socioeconomic status is observed for children aged 6 who were attending the first grade. In richest households, the proportion is around 77.6 percent, while it is 14.5 percent among children living in the poorest households. Over three-fourths (76.4 percent) of children of primary school age are attending school while only (28.4 percent) of the children of secondary school age are attending secondary school. Child Protection Birth Registration The births of 67.3 percent of children under five years in Sudan have been registered; 23.4 percent of the registration certificates have been seen by the interviewers, 26.4 percent have not been seen by the interviewers, and 17.5 were reported to have no birth certificate. Children in Central Darfur State (30.9 percent) were the least to have their births registered than children in other states with Northern states (98.3 percent) registering the highest number of children under five at birth. While only 37.0 percent of the children in the poorest households were registered, nearly all children (97.9 percent) of under five children who belong to richest households were registered. Overall, only 49.8 of the children possess a birth certificate. Child Labour According to the definition of “child labour” that was used in MICS5, a child aged 5-11 years was considered to be involved in child labour activities if s/he, during the week preceding the survey, performed at least one hour of economic work or 28 hours or more of domestic work per week. For a child aged 12-14 years the cut-off points to be considered a “child labourer” were at least 14 hours of economic work or 28 hours or more of domestic work per week. xxxiv While 41.2 percent of children age 12-14 are engaged in some forms of economic activities, 9 percent are performing such tasks for fourteen or more hours. The involvement in economic activities change with age: 21 percent of children aged 5-11 years is engaged in economic activities, compared to 39.1 percent of children aged 12-14 years, and 41.2 percent of children aged 15-17 years. It is also clear from the MICS5 results that engagement in economic activities increases with movement from wealthiest to poorest households. For instance, among children aged 5 – 11 years engaged in economic activity, 9.2 percent of them belong to the wealthiest households while 35.0 percent of them fall in the poorest category. The involvement in economic activities by children varies by State ranging from 4.9 percent in Khartoum to 46.8 percent in South Darfur Child Discipline In MICS 2014 for Sudan, 63.9 percent of children age 1-14 years was subjected to at least one form of psychological or physical punishment by household members during the past month prior to the survey. Generally, the households employed a combination of violent disciplinary practices, reflecting caregivers’ motivation to control children’s behaviour by any means possible. While 52.8 percent of children experienced psychological aggression, about 47.7 percent experienced physical punishment. The most severe forms of physical punishment (hitting the child on the head, ears or face or hitting the child hard and repeatedly) are overall less common: 13.6 percent of children were subjected to severe punishment. Overall, 52.8 percent of children in the aged group 1-14 years experienced psychological aggression in the month preceding the survey. River Nile state was reported of having the highest proportion (69.6 percent) and Central Darfur state (12.6 percent) the lowest of the children aged 1-14 years who experienced psychological aggression. Early Marriage and Polygyny Early marriage, polygyny, and large spousal age differences are common in Sudan. About 21.2 percent of young women age 15-19 years are currently married. This proportion is significantly different between young women in urban areas (11.2 percent) and those in rural areas (26.0 percent). Wide variations between states are also observed; for example in Khartoum state it is 12 percent, while it is 29.9 percent in Blue Nile state. It is strongly related to the level of education, for example, 27.5 percent for women with primary education compared to only 2.4 percent for those with higher education. The percentage of women in a polygynous union is also provided in Table CP.7. Among all women age 15- 49 years who are in union, 21.7 percent are in polygynous unions. Polygynous unions are more common among rural women 23.6 percent compared to 16.9 percent for urban women. Polygynous relationships are more prevalent among older women age 45-49 years 30.8 percent compared to only 7.7 percent among younger women age 15-19 years. Among currently married women age 20-24 years, about (41.8 percent) are married to a man who is older by ten years or more. For currently married women age 15-19 years, the corresponding figure is (39.5 percent). Female Genital Mutilation/Cutting The practice of female genital mutilation /cutting (FGM/C) is highly prevalent in Sudan. Approximately 87 percent of women aged 15-49 years had had some form of female genital mutilation. The percentages rise from 76.8 percent for women without formal education to 91.8 percent for women with higher education. The practice appears more common in rural areas, the highest percentage is in North Darfur state (97.6 percent) and lowest for Central Darfur state (45.4 percent). Surprisingly the practice is highly prevalent among women in wealthy households with population in the richest and xxxv fourth richest quintiles recording 90.0 percent and 91.6 percent respectively. The prevalence of FGM is higher among older women 45-49 years with a percentage of 91.8 percent compared to 81.7 percent for women in the 15-19 years age group. Domestic Violence Women aged 15-49 years were asked whether husbands are justified in hitting or beating their wives or partners according to five different scenarios. Researchers have found that women who agree that their partners are justified in beating them tend to themselves be victims of domestic violence. Overall, 34 percent of women in the survey feel that a husband is justified in hitting or beating his wife in at least one of the five situations (If she goes out without telling him, If she neglects the children, If she argues with him, If she refuses sex with him, and If she burns the food). Women who justify a husband’s violence, in most cases agree and justify violence in instances when a wife neglects the children (24.2 percent), or if she demonstrates her autonomy, demonstrated by going out without telling her husband or arguing with him (19.5 percent). Nearly one-fifth (18.2 percent) of women believe that wife-beating is justified if the wife refuses to have sex with the husband. Justification in any of the five situations is more common among those living in poorest households, less educated, and also currently married women. Among the states, East Darfur with 77.4 percent of women approve wife beating reported the highest while River Nile with 9.6 percent reported the lowest. HIV/AIDS and Orphanhood Knowledge of HIV Transmission and Utilization of HIV Testing Services In Sudan, about three-quarters (74.8 percent) of the women age 15-49 years have heard of HIV and AIDS. However, the percentage of those who know of both main ways of preventing HIV transmission – having only one faithful uninfected partner and using a condom every time – is only about one in ten (8.9 percent). About sixty (59.8 percent) of the women know of having one faithful uninfected sex partner and 26.7 percent know of using a condom every time as main ways of preventing HIV transmission. Correct identification of misconceptions about HIV is based on the two most common and relevant misconceptions in the survey, that HIV can be transmitted by sharing food with someone with HIV (50.5 percent) and by mosquito bites (53.1 percent). Overall, 19.2 percent of the respondents reject the two most common misconceptions and know that a healthy-looking person can be HIV-positive. People who have comprehensive knowledge about HIV prevention include those who know of the two main ways of HIV prevention (having only one faithful uninfected partner and using a condom every time), who know that a healthy looking person can be HIV-positive, and who reject the two most common misconceptions. Comprehensive knowledge of HIV prevention methods and transmission is fairly low although there are differences by area; 6.9 percent and 13.1 percent in rural and urban areas respectively. Comprehensive knowledge about HIV transmission greatly varies with women’s education (48.3 percent) in women with higher level of education compared to women with no education (2.1 percent) and with wealth index level of the household; (20.4 percent) in the richest quintile compared with (2.1 percent) in the poorest quintile of the households. xxxvi Seventeen percent of women know a place where to be tested, while 5.2 percent, have actually been tested, fewer, 4.3 percent of the women, know the result of their most recent test. A very small proportion has been tested within the last 12 months prior to the survey (1.9 percent), while a somewhat smaller proportion has been tested within the last 12 months and know the result (1.6 percent). Orphanhood Less than one (0.3 percent) of children age 10-14 years in Sudan are orphans. Of these, 66.1 percent are attending school, as compared with a 80.2 percent attendance amongst non-orphan children of the same age group who are living with at least one parent. This results in an orphans to non-orphans school attendance ratio of 0.82 which suggests that orphans are not disadvantaged in relation to non- orphans. The ratio is 0.71 for girls and 1.0 for boys. The ratio is 0.92 for children in urban areas compared to 0.78 for children in rural areas. Household Food Security Data was collected on two important proxy measures of household food security: the household food consumption score (FCS) and the coping strategies that households use when they don’t have enough food or money to buy food. The food consumption groups can be described as follows: x Poor food consumption: Households that are consuming only cereals and vegetables every day and never or very seldom are consuming protein rich food such as meat and dairy. x Borderline food consumption: Households that are consuming cereals and vegetables every day, accompanied by oil and pulses a few times a week. x Acceptable food consumption: Households that are consuming cereals and vegetables every day, frequently accompanied by oil and pulses and occasionally meat and dairy. Overall, 81 percent of the households were having acceptable food consumption score. There is wide variation of food security among the states with North Darfur state having the poorest food consumption score of 16 percent 1 I. Introduction 1.1 Background This report is based on the Sudan Multiple Indicator Cluster Survey (MICS5), conducted in 2014 fieldwork August-November by the central bureau of statistics (CBS), ministry of health, ministry welfare, ministry of general education, national environment, national water cooperation The survey provides statistically sound and internationally comparable data essential for developing evidence- based policies and programmes, and for monitoring progress toward national goals and global commitments. Among these global commitments are those emanating from the World Fit for Children Declaration and Plan of Action, the goals of the United Nations General Assembly Special Session on HIV/AIDS, the Education for All Declaration and the Millennium Development Goals (MDGs). A Commitment to Action: National and International Reporting Responsibilities The governments that signed the Millennium Declaration and the World Fit for Children Declaration and Plan of Action also committed themselves to monitoring progress towards the goals and objectives they contained: “We will monitor regularly at the national level and, where appropriate, at the statelevel and assess progress towards the goals and targets of the present Plan of Action at the national, state and global levels. Accordingly, we will strengthen our national statistical capacity to collect, analyse and disaggregate data, including by sex, age and other relevant factors that may lead to disparities, and support a wide range of child-focused research. We will enhance international cooperation to support statistical capacity-building efforts and build community capacity for monitoring, assessment and planning.” (A World Fit for Children, paragraph 60) “…We will conduct periodic reviews at the national and subnational levels of progress in order to address obstacles more effectively and accelerate actions.…” (A World Fit for Children, paragraph 61) The Plan of Action of the World Fit for Children (paragraph 61) also calls for the specific involvement of UNICEF in the preparation of periodic progress reports: “… As the world’s lead agency for children, the United Nations Children’s Fund is requested to continue to prepare and disseminate, in close collaboration with Governments, relevant funds, programmes and the specialized agencies of the United Nations system, and all other relevant actors, as appropriate, information on the progress made in the implementation of the Declaration and the Plan of Action.” Similarly, the Millennium Declaration (paragraph 31) calls for periodic reporting on progress: “…We request the General Assembly to review on a regular basis the progress made in implementing the provisions of this Declaration, and ask the Secretary-General to issue periodic reports for consideration by the General Assembly and as a basis for further action.” 2 The MICS 2014 results will be critically important for final MDG reporting in 2015, and are expected to form part of the baseline data for the post-2015 era. MICS 2014 is expected to contribute to the evidence base of several other important initiatives, including Committing to Child Survival: A Promise Renewed, a global movement to end child deaths from preventable causes, and the accountability framework proposed by the Commission on Information and Accountability for the Global Strategy for Women's and Children's Health. This final report presents the results of the indicators and topics covered in the survey. 1.2 Survey Objectives The Sudan MICS 2014 has as its primary objectives: x Measure the trend towards achievement of the MDGs and the goals of a World Fit for Children Plan of Action and other internationally agreed upon indicators related to children and women. x Furnish data needed for the indicators as per the global review of the Millennium Development Goals. x Contribute to the improvement of data and monitoring systems in Sudan and to strengthen technical expertise, national capacity building in the design, implementation, and analysis of such systems. x Update Census indicators and provide solid evidence for decentralization (planning and measure of progress). x Provide key evidence for social sector programming and the Poverty Reduction Strategy Paper (PRSP) under development and accountabilities for sector strategic plans and UNDAF 2013-2016. x To provide up-to-date information for assessing the situation of children and women in Sudan x To generate data for the critical assessment of the progress made in various areas, and to put additional efforts in those areas that require more attention; x To collect disaggregated data for the identification of disparities, to allow for evidence based policy-making aimed at social inclusion of the most vulnerable; x To contribute to the generation of baseline data for the post-2015 agenda; In 2014, the population of Sudan was estimated at 36.2 million based on the 2008 population census. About 8 percent of the population (2.7 million) are nomads and pastoralists. The population of Sudan is growing very rapidly—2.5 percent annually—with an average fertility rate of 5.5. The average household size is 6.4 persons. Life Expectancy at birth is estimated at 54 years. Overall, Sudan is experiencing a major demographic shift to an increasingly young, urbanized population. There are 15 million children below the age of 18 years and 4.5 million below the age of five years. In some states, children under the age of 16 years constitute 52 percent of the population. Agriculture and livestock are essential to Sudan’s economic diversification (away from oil) and could contribute to medium-term macroeconomic stability. While these sectors presently contribute approximately 35 percent of gross domestic product (GDP), they could contribute significantly more with greater investment and better governance. Sudan now recognizes the need for greater attention to agriculture and livestock, as reflected in its Interim Poverty Reduction Strategy and the five- year program for economic reform. 3 II. Sample and Survey Methodology 2.1 Sample Design The sample for Round Five of the Sudan Multiple Indicator Cluster Survey (MICS5) was designed to provide estimates for a large number of indicators that describe the situation of children and women at the national level, in urban and rural areas, and in the 18 States of Sudan. In order to produce State- level estimates of moderate precision, a minimum of 40 enumeration areas (EAs) were selected in each State, resulting in a sample that was not self-weighting. The urban and rural areas within each state were identified as the main sampling strata and the sample was selected in two stages. In the first stage, within each stratum, a specified number of EAs were selected systematically with probability proportional to size. In the second stage, after a household listing was carried out within the selected enumeration areas, a systematic sample of 25 households was drawn in each selected EA. All of the selected EAs were visited during the fieldwork period. The sample was thus stratified by state and then by urban / rural areas. For reporting national and state-level results, sample weights are used. A more detailed description of the sample design can be found in Appendix A. 2.2 Questionnaires Three types of questionnaires were used in the survey: 1) a household questionnaire was used to collect information on all de jure household members, the household, and the dwelling; 2) a women’s questionnaire administered in each household to all women aged 15-49 years; and 3) an under-5 questionnaire, administered to mothers or caretakers of all children under 5 years living in the household. The questionnaires included the following: 9 Household Questionnaire, including the following modules: 1. Household Information Panel 2. List of Household Members 3. Education 4. Child Labour 5. Child Discipline 6. Water and Sanitation 7. Hand washing 8. Salt Iodization 9. Food Consumption & Sources3 10. Coping Strategies3 9 Individual Women questionnaire, including the following modules: 1. Woman’s Information Panel 2. Woman’s Background 3. Fertility/Birth History 4. Desire for Last Birth 5. Maternal and New-born Health 6. Post-Natal Health Checks 7. Contraception 8. Unmet Need 9. Female Genital Mutilation/Cutting 10. Attitudes toward Domestic Violence 11. HIV/AIDS 3 Survey-specific module 4 12. Mid Upper Arm Circumference(Muac)4 13. Haemoglobin Testing (Anaemia)4 9 Children under Five questionnaire, administered to mothers or caretakers of children under- five years of age5 living in the households. The questionnaire included the following modules: 1. Under Five Child Information Panel 2. Age 3. Birth Registration 4. Early Childhood Development 5. Breastfeeding and Dietary Intake 6. Immunization 7. Care Of Illness 8. Anthropometry 9. Haemoglobin Testing (Anaemia)4 2.3 Training Training of Trainers (TOT) was conducted in Khartoum during the period 24th May 2014 – 5th June 2014. The training was facilitated by three HH survey consultants (Housni Elarabi, Manar Abdel- Rahman and Achraf Mrabet). 18 State directors, 18 National Supervisor, 54 team supervisor and 18 measurers from Ministry of Health attended the TOT. Training of interviewers and measurers was conducted in the States the period 8th -17th July 2014. 2.4 Pre-test Pre-test conducted in Khartoum states covering two clusters urban/ rural with one day workshop convened for questionnaire finalization. The exercise was to test the language, the clarity of questions, coding, skipping, the translation, test areas of senility and the overall do-ability within the country context and specifics. 2.5 Field work The field work wasapplied by central bureau of statistics and states ministries of health. Overall, there are 54 teams for the 18 States. Each team consist of 6 members: 3 female interviewers, one supervisor, one editor and one measures. Therefore, the total field staff are 54 teams 6 members for each team. Each State is supported with the State CBS director and the National state supervisor. The table below outlines the schedule of the start and completion dates of the field work in the States: Completion date of data collection Starting Date of data collection State 2014/10/30 10/9/2014 Northern 1. 28/10/2014 10/9/2014 River Nile 2. 28/10/2014 10/9/2014 Red Sea 3. 01/11/2014 13/9/2014 Kassala 4. 01/11/2014 13/9/2014 Gadarif 5. 27/10/2014 11/9/2014 Gezira 6. 28/09/2014 11/8/2014 Khartoum 7. 31/10/2014 16/9/2014 White Nile 8. 06/11/2014 18/9/2014 Sinnar 9. 05/11/2014 18/9/2014 Blue Nile 10. 27/10/2014 17/9/2014 North Kordofan 11. 4 Survey specific module 5 Completion date of data collection Starting Date of data collection State 30/10/2014 12/9/2014 South Kordofan 12. 27/10/2014 16/9/2014 West Kordofan 13. 20/10/2014 01/9/2014 North Darfur 14. 29/10/2014 09/9/2014 East Darfur 15. 05/11/2014 08/9/2014 Central Darfur 16. 30/10/2014 11/9/2014 West Darfur 17. 30/10/2014 01/9/2014 South Darfur 18. 2.6 Data Processing Data were entered into the computers using the Census and Surveys Processing System (CSPro) software package, Version 5.0. The data were entered on 32 desktop computers by 40 data entry operators and 9 data entry supervisors. For quality assurance purposes, all questionnaires were double-entered and internal consistency checks were performed. Procedures and standard programmes developed under the global MICS programme and adapted to the Sudan questionnaires were used throughout. Data of entry started 14th of September and was completed in 27th of November 2014. Data were analyzed using the Statistical Package for Social Sciences (SPSS) software, Version 21. Model syntax and tabulation plans developed by the Global MICS team were customized and used for this purpose. 6 III. Sample Coverage and the Characteristics of Households and Respondents 3.1 Sample Coverage Of the 18,000 households selected in the sample, 17,142 were found to be occupied. Of these, 16,801 were successfully interviewed for a household response rate of 98 percent. In the interviewed households, 20,327 women (age 15-49 years) were identified. Of these, 18,302 were successfully interviewed, yielding a response rate of 90 percent. In addition to the women, 14,751 children under the age of five years were listed in the household questionnaires. Questionnaires were completed for 14,081 of these children, corresponding to Under-5s response rate of 95.5 percent within the interviewed households. The highest response rate at state level for households was in south Darfur at 99.3 percent, while the lowest response rate was in West Kordofan at 93.4 percent. Response rate was slightly higher in rural areas at 98.5 percent than in urban areas at 96.8 percent. The highest response rate among eligible women 15-49 years was 96.6 percent in Giezera State while the lowest response rate of 78.1 percent was in North Durfur. Similarly, the highest respond rate among eligible children under-5’s was recorded for Giezera was 96.9 percent and the lowest response rate was also in North Darfur at 87.9 percent (Table HH.1). 7 Table HH.1: Results of household, women's, and under-5 interviews Number of households, women, and children under 5 by results of the household, women's, and under-5's interviews, and household, women's and under-5's response rates, Sudan MICS, 2014 Background Charactristics Total Area State Urban Rural North- ern River Nile Red Sea Kassala Gadarif K/toum Gezira White Nile Sinnar Blue Nile North Kordo- fan South Kordo- fan West Kordo- fan North Darfur West Darfur South Darfur Central Darfur East Darfur Households Sampled 18,000 5,275 12,725 1,000 1,000 1,000 1,000 1,000 1,000 1,000 1,000 1,000 1,000 1,000 1,000 1,000 1,000 1,000 1,000 1,000 1,000 Occupied 17,142 4,984 12,158 963 938 946 932 966 945 992 925 969 961 960 971 934 943 925 953 963 956 Interviewed 16,801 4825 11,976 957 928 928 899 947 921 988 912 955 954 928 961 872 914 904 946 955 932 response rate 98.0 96.8 98.5 99.4 98.9 98.1 96.5 98.0 97.5 99.6 98.6 98.6 99.3 96.7 99.0 93.4 96.9 97.7 99.3 99.2 97.5 Women Eligible 20,327 6,692 13,635 1,191 1,115 969 1,036 1,110 1,274 1,395 1,074 1,158 1,181 1,096 1,264 969 1,153 1,035 1,176 988 1,143 Interviewed 18,302 5,979 12,323 1,083 1,027 826 946 1,012 1,171 1,347 1,027 1,057 1,079 949 1,171 863 901 918 1,065 878 982 Response rate 90.0 89.3 90.4 90.9 92.1 85.2 91.3 91.2 91.9 96.6 95.6 91.3 91.4 86.6 92.6 89.1 78.1 88.7 90.6 88.9 85.9 Overall response rate 88.2 86.5 89.0 90.4 91.1 83.6 88.1 89.4 89.6 96.2 94.3 90.0 90.7 83.7 91.7 83.1 75.7 86.7 89.9 88.1 83.8 Children under 5 Eligible 14,751 3,998 10,753 559 600 443 681 881 717 822 785 859 1,052 799 1,120 763 976 860 1,017 875 942 Mothers/ caretakers interviewed 14,081 3,811 10,270 532 565 404 655 858 699 800 754 814 1,006 750 1,092 741 885 843 975 837 871 Response rate 95.5 95.3 95.5 95.2 94.2 91.2 96.2 97.4 97.5 97.3 96.1 94.8 95.6 93.9 97.5 97.1 90.7 98.0 95.9 95.7 92.5 Overall response rate 93.6 92.3 94.1 94.6 93.2 89.5 92.8 95.5 95.0 96.9 94.7 93.4 94.9 90.7 96.5 90.7 87.9 95.8 95.2 94.9 90.1 8 3.2 Characteristics of Households The weighted stratified age and sex distribution of the survey population is provided in Table HH.2. The distribution is also used to produce the population pyramid in Figure HH.1. In the 16,801 households successfully interviewed in the survey, 98,883 household members were listed. Of these, 49,286 were males, 49,577 were females and 21 of them were of unknown gender. Table HH.2: Age distribution of household population by sex Percent and frequency distribution of the household population by five-year age groups, dependency age groups, and by child (age 0-17 years) and adult populations (age 18 or more), by sex, Sudan MICS, 2014 Background charateristics Total Males Females Missing Number Percent Number Percent Number Percent Number Percent Sudan 98,883 100.0 49,286 100.0 49,577 100.0 21 (100.0) Age 0-4 15,050 15.2 7611 15.4 7,439 15.0 0 * 5-9 16,071 16.3 8,036 16.3 8,035 16.2 0 * 10-14 13,447 13.6 6,540 13.3 6,905 13.9 1 * 15-19 9,161 9.3 4,711 9.6 4,451 9.0 0 * 20-24 7,134 7.2 3,463 7.0 3,670 7.4 1 * 25-29 6,690 6.8 2,925 5.9 3,765 7.6 0 * 30-34 5,519 5.6 2,665 5.4 2,854 5.8 0 * 35-39 5,418 5.5 2,598 5.3 2,820 5.7 0 * 40-44 3,877 3.9 2,065 4.2 1,812 3.7 0 * 45-49 3,315 3.4 1,789 3.6 1,526 3.1 0 * 50-54 4,112 4.2 1,641 3.3 2,471 5.0 0 * 55-59 2,462 2.5 1,356 2.8 1,106 2.2 0 * 60-64 2,166 2.2 1,274 2.6 892 1.8 0 * 65-69 1,350 1.4 808 1.6 542 1.1 0 * 70-74 1,455 1.5 851 1.7 604 1.2 0 * 75-79 659 0.7 404 0.8 256 0.5 0 * 80-84 523 0.5 299 0.6 224 0.5 0 * 85+ 421 0.4 229 0.5 192 0.4 0 * Missing/DK 53 0.1 24 * 12 * 17 * Dependency age groups 0-14 44,568 45.1 22,187 45.0 22,380 45.1 1 * 15-64 49,855 50.4 24,485 49.7 25,368 51.2 2 * 65+ 4,408 4.5 2,590 5.3 1,817 3.7 0 * Missing/DK 53 0.1 24 * 12 * 17 * Children and adult populations Children age 0-17 years 50,054 50.6 25,074 50.9 24,979 50.4 1 * Adults age 18+ years 48,777 49.3 24,188 49.1 24,586 49.6 2 * Missing/DK 53 0.1 24 * 12 * 17 * [*] Based on less than 25 unweighted cases and percentages have been suppressed. ( ) Figures that are based on 25-49 unweighted cases 9 Children aged 0-17 years comprise 47.73 percent of the MICS4 survey population, indicating the young nature of the population in Sierra Leone. Comparing the age distribution of MICS5 (table HH.2 ) with result from household survey 2010 no significant differences are observed for example the percentage of population aged 0-14 was 45.1 percent in MICS5 as compared to 45.6 percent for household survey 2010, percentage of population 15-64 was 50.4 percent and 50.5 percent respectively while population 65 + was 4.5 percent in MICS5 compare with 3.9 percent in 2010 household survey, comparing children aged 0-17 the percentage was 50.6 percent in MICS5 comparing with 50.8 percent in the 2010 Household Health survey the adult population 18+was 49.3 percent in MICS 5 and 49.1 percent in the 2010 Household Health survey. Data from Table HH.2 are used to create the population pyramid in Figure HH.1. Examination of this figure reveals that the population pyramid is as the same as expected; it took bell shape. Except for the female population in the age group 50-54 compared to the neighbouring age groups where there was an over representation which could have been related to interviewers bias to reduce number of eligible women in the data collection. Figure HH.1: Age and sex distribution of household population, Sudan MICS, 2014 Tables HH.3, HH.4 and HH.5 provide basic information on the households, female respondents age 15- 49, male respondents 15-49, and children under-5. Both unweight and weighted numbers are presented. Such information is essential for the interpretation of findings presented later in this report 10 8 6 4 2 0 2 4 6 8 10 0-4 5-9 10-14 15-19 20-24 25-29 30-34 35-39 40-44 45-49 50-54 55-59 60-64 65-69 70-74 75-79 80-84 85+ Per cent Age Males Females Note: # household members with missing age and/or sex are 10 and provide background information on the representativeness of the survey sample. The remaining tables in this report are presented only with weighted numbers.5 Table HH.3 provides basic background information on the households, including the sex of the household head, State, area, number of household members, and education of household head6 shown in the table. These background characteristics are used in subsequent tables in this report; the figures in the table are also intended to show the numbers of observations by major categories of analysis in the report. 1. Select the cell or cells whose contents you want aligned. 2. Click repeatedly on the tab stop marker at the left edge of the ruler, stopping when you see the symbol for a decimal tab. 3. Click on the ruler above the selected cells, at the location where you want the numbers aligned. Table HH.3: Household composition Percent and frequency distribution of households by selected characteristics Sudan MICS, 2014 Background characteristics Weighted percent Number of households Weighted Unweighted Sudan 100.0 16,801 16,801 Sex of household head Male 85.8 14,414 14,513 Female 14.2 2,387 2,288 State Northern 2.5 423 957 River Nile 4.0 666 928 Red Sea 3.1 519 928 Kassala 4.3 722 899 Gadarif 5.1 858 947 Khartoum 13.8 2,317 921 Gezira 15.6 2,629 988 White Nile 5.2 874 912 Sinnar 3.9 661 955 Blue Nile 3.9 656 954 North Kordofan 6.7 1,125 928 South Kordofan 2.8 462 961 West Kordofan 6.0 1,003 872 North Darfur 7.4 1,243 914 West Darfur 3.3 553 904 South Darfur 7.6 1,282 946 Central Darfur 1.8 299 955 East Darfur 3.0 508 932 Area Urban 29.8 5,000 4,825 Rural 70.2 11,801 11,976 5 See Appendix A: Sample Design, for more details on sample weights. 6 This was determined by asking the questions used for the construction of the background variables; typical questions asked in MICS surveys are mother tongue, ethnic background and/or religion. 11 Number of household members 1 1.6 268 314 2 7.8 1,303 1,394 3 10.6 1,773 1,867 4 13.3 2,236 2,288 5 14.5 2,443 2,447 6 14.0 2,359 2,347 7 12.5 2,108 2,030 8 9.7 1,624 1,573 9 7.1 1,190 1,095 10+ 8.9 1,498 1,446 Education of household head None 46.4 7,799 8,418 Primary 28.2 4,730 4,452 Secondary 18.7 3,137 2,885 Higher 6.0 1,013 915 Missing/DK 0.7 122 131 The weighted and unweighted Sudan number of households are equal, since sample weights were normalized.5 The table also shows the weighted mean household size estimated by the survey. The head of household in the survey was predominantly male in 85.8 percent of surveyed household members. The most populated States in the survey were Gezira, 15.6 percent and Khartoum, 13.8 percent respectively. Approximately one-third of the population was urbanized (29.8percent) while 70.2 percent were Rural. 3.3 Characteristics of Female Respondents 15-49 Years of Age and Children Under-5 TableHH.4 and Table HH.5 provide information on the background characteristics of female respondents 15-49 years of age and of children under 5 years of age. In both tables, the Sudan numbers of weighted and unweighted observations are equal, since sample weights have been normalized (standardized).5 In addition to providing useful information on the background characteristics of women, and children under age five, the tables are also intended to show the numbers of observations in each background category. These categories are used in the subsequent tabulations of this report. Mean household size 5.9 16,801 16,801 12 Table HH.4: Women's background characteristics Percent and frequency distribution of women age 15-49 years by selected background characteristics, Sudan MICS 2014 Background characteristics Weighted percent Number of women Weighted Unweighted Sudan 100.0 18,302 18,302 State Northern 2.5 457 1,083 River Nile 3.8 701 1,027 Red Sea 2.7 493 826 Kassala 4.1 747 946 Gadarif 4.8 879 1,012 Khartoum 15.4 2,821 1,171 Gezira 17.4 3,176 1,347 White Nile 4.9 889 1,027 Sinnar 3.8 698 1,057 Blue Nile 4.0 729 1,079 North Kordofan 6.4 1,173 949 South Kordofan 2.9 525 1,171 West Kordofan 5.3 965 863 North Darfur 7.2 1,317 901 West Darfur 3.0 555 918 South Darfur 7.4 1,363 1,065 Central Darfur 1.5 272 878 East Darfur 3.0 542 982 Area Urban 32.9 6,029 5,979 Rural 67.1 12,273 12,323 Age 15-19 20.3 3,709 3,655 20-24 17.3 3,162 3,150 25-29 18.4 3,359 3,415 30-34 14.0 2,558 2,593 35-39 13.9 2,542 2,527 40-44 8.9 1,633 1,639 45-49 7.3 1,339 1,323 Marital status Currently married 64.8 11,867 12,023 Widowed 1.5 278 286 Divorced 3.1 564 588 Separated 0.2 45 45 Never married 30.3 5,547 5,359 Missing * 1 1 Motherhood and recent births Never gave birth 37.1 6,798 6,601 Ever gave birth 62.9 11,504 11,701 13 Background characteristics Weighted percent Number of women Weighted Unweighted Gave birth in last two years 30.7 5,622 5,684 No birth in last two years 32.2 5,895 6,024 Education None 31.9 5,843 6,462 Primary 33.5 6,128 5,988 Secondary 23.8 4,361 4,132 Higher 10.7 1,965 1,715 Missing/DK * 5 5 Wealth index quintile Poorest 17.7 3,246 3,345 Second 18.5 3,380 4,074 Middle 19.9 3,646 3,929 Fourth 20.5 3,759 3,363 Richest 23.3 4,271 3,591 [*] Based on less than 25 unweighted cases and percentages have been suppressed. Sixty-five percent of sampled women are married and 63 percent have given birth to at least one child. Thirty-two percent of MICS5 respondents are uneducated while 34 and 24 percent have completed primary and secondary education respectively. The large differences between weighted and unweighted numbers for state are due to the oversampling of smaller states as described in Chapter Two. We observe that there is a significant variation between weight and un-weighted in number of women especially by state level also in HHs 2010 the same variation Some background characteristics of children under 5 are presented in Table HH.5. These include the distribution of children by several attributes: sex, State and area, age, mother’s or caretaker’s education**, and wealth of household head. 49.2 percent of the children represented in the MICS5 survey are female. Only 16 percent of children live in households in the wealthiest quintile while 23 percent of children live in households in the least wealthy quintile. Table HH.5: Under-5's background characteristics Percent and frequency distribution of children under five years of age by selected characteristics, Sudan MICS, 2014 Background characteristics Weighted percent Number of children Weighted Unweighted Sudan 100.0 14,081 14,081 Sex Male 50.8 7,157 7,190 Female 49.2 6,924 6,891 State Northern 1.7 236 532 14 Background characteristics Weighted percent Number of children Weighted Unweighted River Nile 2.8 393 565 Red Sea 1.7 244 404 Kassala 3.5 498 655 Gadarif 5.4 765 858 Khartoum 12.3 1,736 699 Gezira 15.3 2,149 800 White Nile 5.0 711 754 Sinnar 3.9 555 814 Blue Nile 4.9 691 1,006 North Kordofan 6.4 907 750 South Kordofan 3.8 529 1,092 West Kordofan 6.3 893 741 North Darfur 8.6 1,211 885 West Darfur 3.5 487 843 South Darfur 9.4 1,326 975 Central Darfur 1.8 254 837 East Darfur 3.5 495 871 Area Urban 27.4 3,862 3,811 Rural 72.6 10,219 10,270 Age 0-5 months 10.8 1,516 1,543 6-11 months 10.3 1,448 1,423 12-23 months 19.0 2,672 2,641 24-35 months 18.6 2,618 2,647 36-47 months 23.2 3,268 3,217 48-59 months 18.2 2,559 2,610 Respondent to the under-5 questionnaire Mother 98.5 13,810 13,810 Other primary caretaker 1.5 213 214 Mother’s education** None 42.6 5,994 6,587 Primary 35.1 4,936 4,666 Secondary 15.3 2,152 2,018 Higher 7.0 982 794 Missing/DK * 17 16 Wealth index quintile Poorest 22.6 3,188 3,248 Second 21.4 3,015 3,734 Middle 21.0 2,956 3,088 Fourth 19.1 2,684 2,212 Richest 15.9 2,238 1,799 15 Background characteristics Weighted percent Number of children Weighted Unweighted [*] Based on less than 25 unweighted cases and percentages have been suppressed. ** In this table and throughout the report, mother's education refers to educational attainment of mothers as well as caretakers of children under 5, who are the respondents to the under-5 questionnaire if the mother is deceased or is living elsewhere. 3.4 Housing Characteristics, Asset Ownership, and Wealth Quintiles Tables HH.6, HH.7 and HH.8 provide further details on household level characteristics. HH.6 presents characteristics of housing, disaggregated by area and state, distributed by whether the dwelling has electricity, the main materials of the flooring, roof, and exterior walls, as well as the number of rooms used for sleeping. Only about 45 percent of the households in Sudan have access to electricity. Availability of electricity widely varies among the States: while 94.4 percent of the households in the Northern State has of access to electricity, less than 20 percent of the Darfur and Kordofan States have access to electricity. North Darfur has the least percentage, 8.7 access to electricity. Seventy-six percent of households with access to electricity are in urban areas Main shelter materials in Sudan are made of natural floors, natural roofing and natural walls. About 30 percent of the houses have single rooms for sleeping, 42 percent of the houses have 2 rooms for sleeping, and 28 percent of them have 3 or more rooms for sleeping. The mean number of persons per room used for sleeping is 3.23. 16 Table HH.6: Housing characteristics Percent distribution of households by selected housing characteristics, according to area of residence and states, Sudan MICS, 2014 Background characteristic s Sudan Area State Urba n Rural North ern River Nile Red Sea Kass ala Gadari f Khart oum Gezira Whit e Nile Sinna r Blue Nile North Kordo fan South Kordo- fan West Kordo- fan N. Darfu r West Darfu r Sout h Darfu r Centr al Darfu r East Darfu r Electricity Yes 44.9 76.3 31.7 94.4 79.1 39.6 38.0 39.5 81.6 72.9 40.1 57.9 48.6 17.7 19.6 12.0 8.7 15.5 19.9 11.4 11.0 No 55.0 23.6 68.3 5.6 20.7 60.4 62.0 60.4 18.4 27.0 59.8 41.9 51.4 82.3 80.4 87.9 91.3 84.5 80.1 88.5 89.0 Missing 0.0 0.1 0.0 0.0 0.1 0.0 0.0 0.1 0.0 0.1 0.1 0.3 0.0 0.0 0.0 0.1 0.0 0.0 0.0 0.1 0.0 Flooring Natural floor 85.4 68.9 92.4 64.4 80.6 74.7 91.5 96.0 62.6 77.5 90.6 86.4 92.2 96.4 93.1 95.5 94.8 96.0 97.9 95.3 94.6 Rudimentary floor 0.1 0.2 0.0 0.0 0.0 0.8 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.1 0.3 0.2 0.0 0.3 0.2 0.0 0.0 Finished floor 14.0 30.2 7.2 35.4 19.2 22.5 7.9 2.9 36.9 22.3 9.2 13.2 7.8 2.6 6.2 4.0 4.4 2.7 1.3 4.0 4.7 Other 0.3 0.3 0.2 0.2 0.1 1.7 0.0 0.4 0.3 0.2 0.0 0.1 0.0 0.4 0.1 0.0 0.4 0.1 0.3 0.0 0.3 Missing/DK 0.3 0.4 0.2 0.0 0.0 0.4 0.6 0.8 0.1 0.0 0.2 0.3 0.1 0.5 0.3 0.3 0.3 0.9 0.3 0.7 0.3 Roof Natural roofing 38.7 14.2 49.1 20.1 7.2 5.3 53.2 84.8 1.5 5.6 1.7 16.1 30.4 63.3 35.3 77.8 87.2 69.7 72.1 80.7 84.7 Rudimentary roofing 34.7 34.3 34.8 61.0 84.2 28.7 30.2 2.6 49.5 76.6 77.7 46.7 4.0 10.6 6.2 9.6 1.7 6.9 9.0 5.9 0.7 Finished roofing 25.0 50.5 14.2 18.7 8.1 50.8 11.7 12.6 48.4 17.1 20.5 36.7 62.9 25.1 54.4 12.4 10.4 21.7 18.1 11.5 5.8 Other 1.6 1.0 1.9 0.2 0.5 15.1 4.5 0.1 0.6 0.6 0.1 0.1 2.7 0.8 4.2 0.1 0.7 1.6 0.7 1.9 8.8 Missing/DK 0.0 0.0 0.0 0.0 0.0 0.1 0.3 0.0 0.0 0.0 0.0 0.3 0.0 0.2 0.0 0.1 0.0 0.0 0.0 0.1 0.0 Exterior walls Natural walls 60.6 36.3 70.8 63.6 65.2 34.1 79.9 64.0 36.8 43.7 80.1 53.2 30.2 79.4 36.3 85.4 81.3 68.3 75.4 72.0 83.8 Rudimentary walls 4.9 7.5 3.8 11.4 8.8 13.9 6.7 1.5 4.7 5.0 1.6 2.0 1.5 4.4 4.8 3.4 5.9 3.8 6.7 7.8 .3 Finished walls 28.1 50.8 18.5 24.9 25.8 42.7 11.2 2.3 56.7 51.2 17.9 43.4 20.2 10.0 39.7 7.0 7.9 19.7 17.7 18.7 6.1 Other 6.3 5.3 6.8 0.1 0.1 9.2 1.6 32.2 1.8 0.2 0.4 1.1 48.0 6.1 19.1 4.1 4.7 8.0 0.3 1.5 9.8 Missing/DK 0.1 0.0 0.1 0.0 0.0 0.0 0.6 0.0 0.0 0.0 0.0 0.3 0.1 0.1 0.0 0.1 0.2 0.2 0.0 0.1 0.0 17 Background characteristic s Sudan Area State Urba n Rural North ern River Nile Red Sea Kass ala Gadari f Khart oum Gezira Whit e Nile Sinna r Blue Nile North Kordo fan South Kordo- fan West Kordo- fan N. Darfu r West Darfu r Sout h Darfu r Centr al Darfu r East Darfu r Rooms used for sleeping 1 29.7 22.3 32.8 17.6 23.6 52.4 36.4 24.7 22.1 25.7 21.0 34.1 33.6 29.4 37.0 29.0 33.5 35.2 34.9 34.9 46.5 2 41.8 40.5 42.3 49.8 48.1 28.9 35.9 49.4 38.1 41.5 46.8 42.4 48.4 42.7 37.5 43.5 44.0 42.9 38.2 39.7 37.7 3 or more 28.2 36.5 24.6 32.6 28.0 18.6 27.1 25.6 39.4 32.7 31.4 23.3 17.9 27.2 25.6 26.2 22.5 20.9 26.3 24.8 15.9 Missing/DK 0.4 0.6 0.3 0.0 0.3 0.1 0.6 0.3 0.3 0.1 0.8 0.1 0.1 0.7 0.0 1.3 0.1 1.0 0.5 0.6 0.0 Sudan 100.0 100.0 100.0 100.0 100.0 100.0 100.0 100.0 100.0 100.0 100.0 100.0 100.0 100.0 100.0 100.0 100.0 100.0 100.0 100.0 100.0 Number of households 16,801 5,000 11,801 423 666 519 722 858 2,317 2,629 874 661 656 1,125 462 1,003 1,243 553 1,282 299 508 Mean number of persons per room used for sleeping 3.23 3.06 3.30 2.61 2.94 3.28 3.35 3.13 2.98 3.26 2.87 3.22 3.56 3.11 3.87 3.17 3.58 3.13 3.38 3.16 4.00 18 3.5 Household Assets MICS5 2014 collected information on households, ownership of selected assets that are in themselves believed to have a strong association with poverty levels. Some of these can be used to measure household welfare when combined with other indicators to generate wealth index. Information was collected on household ownership of television , radio as a measure of access to mass media ; non – mobile phone telephones as an indicator of access to an efficient means of communication ; refrigerators as indication of capacity for hygienic storage of foods; digital receiver flat TV screen ,internet ,computer and washing machine. Information was also collected from households with regard to ownership of the following: means of transportation (bicycle, motorcycle, animal-drawn cart, car or truck, boat with motor), smart mobile, laptop, Thira mobile and bank account. Table HH.7 shows the percentage distribution of households by ownership of selected household and personal assets, and percent distribution by ownership of dwelling, according to area of residence and states. Access to non-mobile phones was the least at 1.8 percent while approximately 40 percent of the households have access to Television. About 74 percent of households had a least a household member possessing a mobile telephone with Northern, Khartoun, Blue Nile, Gezira, and River Nile having access at 96.6, 91.3, 87.5, 87.3, and 84.6 percent respectively. Central Darfur had the least access to mobile phones at 47.3 percent. Almost all the mobile phones are likely to be owned by urban households 87.3 percent own mobile phone compared to 68.1 percent ownership in rural areas. Access to Internet and computer were minimal at 3.8 and 3.7 percent respectively. Table HH.7 shows that 35.2 percent of the households own a radio; urban households are more likely than rural households to own television 71.1 percent compared with 26.3 percent respectively. Overall, 25.9 percent of all households own a refrigerator and as expected, urban households are more likely than rural households to own a refrigerator 50.1 percent compared with 15.7 percent respectively. Access to Agricultural land and Farm animals/livestock was highest in rural households at 51 and 64 percent respectively. Such access unfavourably compares to urban households at 12 and 20 percent respectively. With regard to access to transport, table HH.7 shows that access to car or truck transportation was 6.4 percent of households ranging from 4.4 percent in rural households to 11.0 percent in urban households. In contrast access to animal drawn transportation was 17.9 percent of rural households compared to 8.1 percent in urban households. Most of the people surveyed did not own personal bank accounts. Ownership of personal bank account was 2.4 percent in rural households and 11.1 percent in urban households. Ownership of personal bank account was highest in Khartoun and Northern States respectively at 12.6 and 9.6 19 percent and lowest in Central Darfur and West Kordofan/North Darfur at 1.0 and 1.6 percent respectively. Most of the dwellings were owned by a household member. The highest ownership was in households in North Darfur at 94.4 percent, West Kordofan at 93.5 percent, North Kordofan at 92.2 percent, Blue Nile at 92.2 percent, South Kordofan at 91.3 percent, and White Nile at 91.0 percent. 20 Table HH.7: Household and personal assets Percentage of households by ownership of selected household and personal assets, and percent distribution by ownership of dwelling, according to area of residence and states, Sudan MICS, 2014 Background characteristics Sudan Area State Urban Rural Northern River Nile Red Sea Kassala Gadarif Khartoum Gezira White Nile Sinnar Blue Nile North Kordofan South Kordofan West Kordofan North Darfur West Darfur South Darfur Central Darfur East Darfur Percentage of households that own a Radio 35.2 41.5 32.6 30.5 37.1 27.7 21.2 30.5 42.3 35.1 41.2 36.5 44.0 41.9 47.0 29.4 30.7 20.9 37.5 22.2 31.7 Television 39.6 71.1 26.3 86.0 75.3 41.2 29.0 28.8 77.0 60.5 42.0 41.5 30.4 17.4 20.2 12.4 7.6 13.8 18.2 8.0 12.5 Non-mobile phone 1.8 3.6 1.1 2.6 3.3 2.7 2.7 0.9 3.1 2.1 1.6 2.7 1.0 1.2 1.0 1.5 0.8 1.1 0.6 1.3 1.2 Refrigerator 25.9 50.1 15.7 75.7 63.1 26.7 17.8 11.0 63.2 39.8 25.1 23.1 8.7 7.7 5.0 3.5 2.7 4.5 5.9 1.8 5.9 Digital receiver 33.8 62.5 21.6 81.8 71.0 36.3 24.3 20.3 71.6 52.8 32.6 37.4 22.8 10.1 13.6 3.8 5.5 10.6 14.1 3.9 10.7 Flat TV Screen 2.3 5.7 .9 3.6 2.3 2.1 2.0 0.8 7.1 2.8 2.2 1.7 1.1 0.6 0.3 0.3 0.8 1.7 1.6 0.6 0.2 Internet 3.8 10.2 1.1 3.3 2.3 6.8 1.7 1.8 16.4 2.7 1.1 5.7 0.2 1.0 0.6 0.3 0.4 0.5 1.6 0.9 0.2 Computer 3.7 8.9 1.4 5.8 5.0 4.6 2.9 0.9 12.0 4.2 1.6 3.4 0.8 1.2 1.4 .7 1.4 1.2 1.4 1.0 0.6 Wash Machine 11.1 22.5 6.2 43.6 31.7 15.4 7.8 2.8 30.8 15.5 5.8 7.1 2.7 2.6 0.6 0.8 0.6 0.8 0.6 1.3 0.8 Percentage of households that own Agricultural land 39.5 12.0 51.1 31.3 22.7 30.3 28.0 43.4 7.0 24.0 30.2 42.7 48.0 55.6 52.0 43.2 83.4 69.4 63.3 48.8 55.7 Farm animals/ Livestock 51.0 20.3 64.0 65.1 51.9 44.0 44.9 51.0 13.8 45.4 54.8 51.7 62.9 62.3 52.7 55.1 83.1 54.4 66.5 54.2 71.7 Percentage of households where at least one member owns or has a Mobile telephone 73.8 87.3 68.1 96.4 84.6 58.9 54.9 72.1 91.3 87.3 69.4 74.7 87.5 66.5 73.0 66.1 60.6 57.9 59.2 47.3 60.0 Bicycle 13.3 17.8 11.4 12.0 12.4 5.5 14.8 10.0 13.9 18.4 10.0 22.5 30.8 2.9 35.5 13.1 3.5 5.6 11.8 21.7 4.3 Motorcycle or scooter 4.4 6.6 3.5 2.5 4.4 2.9 6.1 3.5 4.2 2.8 2.3 6.2 15.8 1.1 10.4 7.0 1.1 3.4 7.0 6.2 1.9 Animal-drawn cart 15.0 8.1 17.9 16.4 11.8 1.9 9.0 16.3 5.6 14.8 24.3 21.7 14.2 16.5 24.1 28.0 4.5 8.2 19.8 16.4 39.1 Car or truck 6.4 11.0 4.4 12.7 10.8 6.1 6.0 3.1 16.4 7.8 6.0 6.2 4.1 4.2 1.4 0.7 1.4 1.9 2.6 0.8 2.4 Boat with motor 0.5 0.3 0.6 1.0 1.4 0.5 0.2 0.0 0.1 0.3 4.8 0.6 0.2 0.2 0.2 0.0 0.0 0.1 0.2 0.6 0.0 21 Background characteristics Sudan Area State Urban Rural Northern River Nile Red Sea Kassala Gadarif Khartoum Gezira White Nile Sinnar Blue Nile North Kordofan South Kordofan West Kordofan North Darfur West Darfur South Darfur Central Darfur East Darfur Raksha 1.3 3.4 .4 2.0 2.8 2.7 0.1 0.5 3.6 1.0 1.8 1.6 0.5 0.2 1.3 0.3 0.0 0.2 1.4 0.8 0.1 Smart Mobile 8.9 17.8 5.1 33.4 15.3 10.3 12.4 2.9 22.1 9.8 11.0 6.7 2.9 2.8 2.5 1.0 1.5 1.8 3.1 6.1 2.7 Labtop/Tablet 3.8 9.4 1.4 7.2 4.8 4.4 2.0 .9 11.9 4.4 2.2 3.6 2.0 1.4 1.0 .4 1.0 2.2 2.3 1.4 1.2 Thria mobile 0.4 0.5 0.3 0.3 0.3 0.3 0.4 0.2 0.0 0.2 3.4 0.7 0.2 0.2 0.3 0.0 0.0 0.6 0.3 0.1 0.4 Bank account 5.0 11.1 2.4 9.6 4.4 8.2 2.1 4.5 12.6 4.9 2.3 5.4 5.6 1.7 4.3 1.6 1.6 3.3 3.4 1.0 2.9 Ownership of dwelling Owned by a household member 85.5 67.3 93.3 75.5 84.4 81.4 91.1 89.1 69.3 87.2 91.0 82.6 92.2 92.2 91.3 93.5 94.4 85.8 83.5 83.2 86.3 Not owned 14.4 32.5 6.7 24.5 15.4 18.5 8.8 10.9 30.7 12.8 8.8 17.1 7.8 7.7 8.6 6.2 5.5 14.2 16.5 16.7 13.7 Rented 7.0 19.1 1.9 6.3 6.2 9.0 4.9 3.1 21.4 3.8 5.0 3.1 4.0 3.0 4.5 4.5 1.7 6.0 9.2 6.5 4.2 Other 7.4 13.4 4.8 18.3 9.2 9.6 3.9 7.8 9.4 9.0 3.7 14.0 3.8 4.6 4.1 1.7 3.7 8.2 7.3 10.2 9.5 Missing/DK 0.1 0.1 0.0 0.0 0.2 0.1 0.1 0.0 0.0 0.0 0.2 0.3 0.0 0.1 0.1 0.2 0.2 0.0 0.0 0.1 0.0 Number of households 16,801 5,000 11,801 423 666 519 722 858 2,317 2,629 874 661 656 1,125 462 1,003 1,243 553 1,282 299 508 [*] Based on less than 25 unweighted cases and has been suppressed. 22 Table HH.8 shows how the household populations in Areas and States are distributed according to household wealth quintiles. Table HH.8: Wealth quintiles Percent distribution of the household population by wealth index quintiles, according to area of residence and states, Sudan MICS, 2014 Background characteristics Wealth index quintile Sudan Number of household members Poorest Second Middle Fourth Richest Sudan 20.0 20.0 20.0 20.0 20.0 100.0 98,883 Area Urban 2.8 7.2 21.0 26.9 42.0 100.0 30,476 Rural 27.7 25.7 19.6 16.9 10.2 100.0 68,407 State Northern 0.0 0.8 10.5 39.3 49.5 100.0 2,181 River Nile 3.6 1.9 10.4 38.3 45.8 100.0 3,715 Red Sea 9.1 22.5 26 21.2 21.3 100.0 2,489 Kassala 19.5 28.4 25.3 13.6 13.1 100.0 4,117 Gadarif 16.7 35.5 30.7 12.8 4.3 100.0 5,005 Khartoum 0.2 2.8 12.5 26.0 58.4 100.0 13,830 Gezira 0.6 4.7 21.3 44.5 28.8 100.0 16,270 White Nile 2.0 22.5 38.3 21.3 15.9 100.0 5,016 Sinnar 1.2 21.2 36.7 21.8 19.1 100.0 3,763 Blue Nile 2.3 26.4 45.5 18.5 7.3 100.0 4,094 North Kordofan 37.4 28.1 21.3 8.1 5.1 100.0 6,359 South Kordofan 9.9 51.0 28.4 8.5 2.2 100.0 2,983 West Kordofan 41.6 40.9 14 2.9 0.6 100.0 5,745 North Darfur 59.9 26.8 8.0 2.8 2.5 100.0 7,776 West Darfur 40.5 30.0 13.7 11.0 4.8 100.0 3,023 South Darfur 52.0 22.3 14.8 7.9 2.9 100.0 7,712 Central Darfur 32.1 49.5 12.7 4.0 1.7 100.0 1,646 East Darfur 60.8 26.0 5.9 3.4 3.9 100.0 3,158 23 IV. Child Mortality 4.1 Introduction One of the overarching goals of the Millennium Development Goals (MDGs) is to reduce infant and under-five mortality. Specifically, the MDGs call for the reduction of under-five mortality by two-thirds between 1990 and 2015. The Goal of the Sudan Health Sector Strategic Plan (HSSP 2012-2016) was to “improve health status and outcomes, especially for poor, underserved, disadvantaged and vulnerable populations” expecting the reduction of under-five mortality rate from 83 thousands life births estimated by SHHS 2010 to 53 thousands life births and the reduction of infant mortality rate from 57 to 43 at the end of the health strategic plan in 2016. This national commitment is part of the Government’s National Development Plan 2012-2016 compatible with the 25-year National Strategic Plan for Health (2003-2027) and the National Health Policy (2007). Monitoring progress towards those global and national goals is an important but difficult objective. MICS 2014 offers an opportunity to generate accurate evidence on the status of child survival in Sudan at national level and by state following the separation of the South Sudan with Sudan in 2011 which resulted to structural economic challenges of limited fiscal space (the loose of 65percent of oil revenue) for capital investment on social sector. The persistent humanitarian responses to vulnerable population affected by natural disasters, conflicts and displacements represent also major challenges for development results. The gap of human resources capacities and health financing, the limited geographic coverage of PHC (11.3 percent of population don’t have access to health services within 5km), the financial barriers of use of health services by poorest families because of the requirement of users fees and the prevailing social norms and behaviours issues represent major bottlenecks for the acceleration of progress to achieve MDG4 and MDG5 in Sudan as mentioned in 2012 by the SHSS 2012-2016. Despite those challenges and bottlenecks, it is important to recognise that in Sudan health infrastructures and skilled manpower are in place and efforts have been made to operationalize strategies and innovative high impact interventions as agreed within HSSP and the Health Sector COMPACT in a very large partnerships of Government, Donors, Civil Society, Local Authorities with engagement of communities and family participation. Mortality rates presented in this chapter are calculated from information collected in the birth histories of the Women’s Questionnaires. All interviewed women were asked whether they had ever given birth, and if yes, they were asked to report the number of sons and daughters who live with them, the number who live elsewhere, and the number who have died. In addition, they were asked to provide a detailed birth history of live births of children in chronological order starting with the firstborn. Women were asked whether births were single or multiple, the sex of the children, the date of birth (month and year), and survival status. Further, for children still alive, they were asked the current age of the child and, if not alive, the age at death. Childhood mortality rates are expressed by conventional age categories and are defined as follows: • Neonatal mortality (NN): probability of dying within the first month of life • Post-neonatal mortality (PNN): difference between infant and neonatal mortality rates • Infant mortality (1q0): probability of dying between birth and the first birthday 24 • Child mortality (4q1): probability of dying between the first and the fifth birthdays • Under-five mortality (5q0): the probability of dying between birth and the fifth birthday Rates are expressed as deaths per 1,000 live births, except in the case of child mortality, which is expressed as deaths per 1,000 children surviving to age one, and post-neonatal mortality, which is the difference between infant and neonatal mortality rates. 4.2. Status of Child Mortality at national level Table CM.1 and Figure CM.1 present neonatal, post-neonatal, infant, child, and under-five mortality rates for the three most recent five-year periods before the survey. In Sudan, the under-five mortality is estimated by MICS 2014 at 68 deaths per 1,000 live births for the period of five years preceding the survey (2010-2014) and the infant mortality rate is 52 per 1,000 live births for the same period indicating that 76.5 percent of under-five deaths are infant deaths. Neonatal mortality in the most recent 5-year period is estimated at 33 per 1,000 live births, while the post-neonatal mortality rate is estimated at 19 per 1,000 live births. Table CM.1: Early childhood mortality rates Neonatal, post-neonatal, infant, child and under-five mortality rates for five year periods preceding the survey, Sudan MICS, 2014 Years preceding the survey Neonatal mortality rate (1) Post neonatal mortality(2) Infant mortality(3) Child mortality (4) Under five mortality(5) 0-4 32.6 19.4 52.0 17.3 68.4 5-9 28.2 19.7 47.9 23.0 69.8 10-14 28.3 26.5 54.9 32.1 85.2 1MICS indicator 1.1 – Neonatal mortality 2 MICS indicator 1.3 – Post neonatal mortality rate 3 MICS indicator 1.2 – MDG indicator 4.2 – infant mortality rate 4 MICS indicator 1.4 – Child Mortality Rate 5 MICS indicator 1.5 - MDG indicator 4.1 – Under-five mortality rate Post neonatal mortality rates are computed as the difference between the infant and neonatal mortality rate The birth history method enables to calculate early child mortality rates for different years preceding the survey. The table and figure also show a declining trend at the national level, during the last 15 years, with under-five mortality at 85 per 1,000 live births during the 10-14 year period preceding the survey, and 69.8 per 1,000 live births during the most recent 5-year period, roughly referring to the years indicate period. A similar pattern is observed in all other indicators. However, there has been stagnation of neonatal mortality rate during the period 10-14 years (28.3) and 5-9 years (28.2) preceding the MICS 2014. 25 F i g u r e C M . 1 : E a r l y c h i l d h o o d m o r t a l i t y r a t e s , S u d a n M I C S , 2 0 1 4 4.3 Geographic Disparity in Childhood Mortality Tables CM.2 and figure CM.2 provide estimates of child mortality by area and by states. Findings reveal that there is inequality of probabilities of dying between urban and rural areas: under-five mortality and infant mortality rates are respectively 56.5 and 11.8 deaths for 1,000 live births in urban area, 72.8 and 19.3 in rural area. The risk of dying of under-five children before the five birthday is very high in the states of East Darfur (111.7), South Kordofan (95.4), West Darfur (91.4), North Darfur (90.3); however the lowest under- five mortality rates are measured in Northern (29.9), River Nile (35.1), North Kordofan (41.9) and Khartoum (49.8) states. Figure CM.2 provides a graphical presentation of these differences. 28 27 55 32 85 28 20 48 23 70 33 19 52 17 68 Neonatal mortality rate Post-neonatal mortality rate Infant mortality rate Child mortality rate Under-five mortality rate Years preceding the survey Note: Indicator values are per 1,000 live births 10-14 5-9 0-4 26 Table CM.2: Early Childhood Mortality Neonatal, post-neonatal, infant, child and under-five mortality rates for five year periods preceding the survey by Area and State, Sudan MICS, 2014 Geographic area Neonatal mortality1 Post neonatal mortality2 Infant mortality3 Child mortality4 Under five mortality5 Sudan 32.6 19.4 52.0 17.3 68.4 Area Urban 30.3 14.8 45.1 11.8 56.5 Rural 33.4 21.1 54.5 19.3 72.8 State Northern 23.0 6.9 30.0 0.0 29.9 River Nile 25.8 2.3 28.1 7.2 35.1 Red Sea 18.6 25.6 44.2 17.9 61.3 Kassala 47.2 15.0 62.1 19.7 80.5 Gadarif 32.6 20.8 53.4 24.6 76.7 Khartoum 30.5 14.6 45.1 4.9 49.8 Gezira 26.2 15.2 41.4 12.6 53.5 White Nile 30.3 16.5 46.8 20.0 65.8 Sinnar 18.0 16.1 34.1 18.1 51.6 Blue Nile 26.0 20.8 46.8 38.9 83.9 North Kordofan 23.0 12.7 35.6 6.5 41.9 South Kordofan 32.5 37.6 70.2 27.1 95.4 West Kordofan 43.4 24.8 68.2 15.0 82.1 North Darfur 43.9 24.6 68.5 23.4 90.3 West Darfur 39.2 32.0 71.2 21.8 91.4 South Darfur 35.2 17.5 52.6 20.4 71.9 Central Darfur 24.7 19.8 44.5 34.4 77.4 East Darfur 51.8 36.7 88.5 25.5 111.7 1 MICS indicator 1.1 - Neonatal mortality rate 2 MICS indicator 1.3 - Post-neonatal mortality rate 3 MICS indicator 1.2; MDG indicator 4.2 - Infant mortality rate 4 MICS indicator 1.4 - Child mortality rate 5 MICS indicator 1.5; MDG indicator 4.1 - Under-five mortality rate 27 Graph below reveals the 3.7 times gap of equity in child survival between Northern state (the lowest U5MR of 30 deaths per 1,000 live births) and East Darfur (the highest under-five mortality rate of 111.7 deaths for 1,000 live births). F i g u r e C M . 2 : U n d e r f i v e M o r t a l i t y R a t e s b y S t a t e , S u d a n M I C S , 2 0 1 4 The gap of equity of child survival between urban and rural area is high in Sudan as indicated below. 0 20 40 60 80 100 120 Northern River Nile North Kordofan Khartoum Sinnar Gezira Red Sea White Nile Sudan South Darfur Gadarif Central Darfur Kassala West Kordofan Blue Nile North Darfur West Darfur South Kordofan East Darfur 29.9 35.1 41.9 49.8 51.6 53.5 61.3 65.8 68.0 71.9 76.7 77.4 80.5 82.1 83.9 90.3 91.4 95.4 111.7 28 Figure CM.2a: Underfive Mortality Rates by geographic area, Sudan MICS, 2014 4.4 Disparity in Childhood mortality by socioeconomic and demographic patterns Tables CM.2b and figures CM.2c-CM.2d provide estimates of child mortality by socioeconomic and demographic characteristics. There is difference between the probabilities of dying among boys (78.7) and girls (57.6). Inequity for child survival is very high in Sudan: children living in poorest families are double times at risk of dying before their firth birthday (U5MR of 84.2) in comparison to children from richest household (U5MR of 39.4). There is also differences in mortality in terms of mothers’ education, age-group, birth order and interval of birth as indicated in figures and tables below. Figure CM.2b: Under Five Mortality Rates by sex of child and wealth quintile, Sudan MICS, 2014 56.5 72.8 68 0 10 20 30 40 50 60 70 80 Urban Rural Sudan 84.2 79.9 67.7 59.6 39.4 78.7 57.6 68 0 10 20 30 40 50 60 70 80 90 Poorest Second Middle Fourth Richest Boys Girls Sudan 29 Figure CM.2c: Underfive mortality rates by mother's education, Sudan MICS, 2014 Table CM.3: Early Childhood Mortality Neonatal, post-neonatal, infant, child and under-five mortality rates for five year periods, preceding the survey by demographic characteristics, Sudan MICS, 2014 Background characteristics Neonatal mortality Post neonatal mortality Infant mortality Child mortality Under five mortality Sudan 32.6 19.4 52.0 17.3 68.4 Sex of child Boys 38.4 21.1 59.4 20.5 78.7 Girls 26.5 17.7 44.2 14.1 57.6 Birth order 1 37.9 10.2 48.0 12.5 60.0 2-3 22.8 20.5 43.3 14.8 57.5 4-6 28.3 19.6 47.9 18.9 65.9 7+ 53.4 25.8 79.2 24.4 101.7 Previous birth interval < 2 years 52.7 30.2 82.9 27.1 107.8 2 years 23.8 19.8 43.7 18.4 61.3 3 years 13.7 11.6 25.3 7.3 32.4 4+ years 30.5 15.8 46.3 8.7 54.6 Mother’s education None 34.6 20.6 55.3 24.6 78.4 Primary 32.5 20.7 53.2 14.5 66.9 Secondary 35.0 13.0 48.0 6.1 53.8 Higher 14.6 20.2 34.8 3.8 38.4 Wealth index quintile Poorest 41.1 23.8 64.9 20.6 84.2 Second 36.0 24.3 60.3 20.9 79.9 Middle 31.2 19.2 50.3 18.2 67.7 Fourth 25.0 17.7 42.7 17.7 59.6 78.4 66.9 53.8 38.4 68.4 0 10 20 30 40 50 60 70 80 90 None Primary Secondary Higher Sudan 30 Richest 25.7 8.2 33.9 5.7 39.4 1 MICS indicator 1.1 - Neonatal mortality rate 2 MICS indicator 1.3 - Post-neonatal mortality rate 3 MICS indicator 1.2; MDG indicator 4.2 - Infant mortality rate 4 MICS indicator 1.4 - Child mortality rate 5 MICS indicator 1.5; MDG indicator 4.1 - Under-five mortality rate a Post-neonatal mortality rates are computed as the difference between the infant and neonatal mortality rates (*) Rates based on fewer than 250 unweighted exposed persons ( ) Rates based on 250 to 499 unweighted exposed persons 4.5 Trend in Childhood mortality rate using different sources As part of an effort to recap the overall evolution of child mortality measurement done in Sudan, this section presents data related to the estimation of under-five mortality as officially approved and published within national household survey full report completed in Sudan since 2000. In addition, reference to the estimation performed by the United Nations inter agency estimation group (IGME) is also presented in the graph for information. This trend analysis will cover the evolution of under-five mortality at national level, by state and by wealth quintile. Those data must be considered with caution taking into account the difference of sampling, the variance of indicator, method used and variation of geographic area (variation from 15 states in 2010 to 18 states in 2014). Despite, the limitations of different surveys in statistical view, those recap of estimation from previous surveys provide an indication of potential evolution of the situation of child survival in Sudan (decrease or increase by state and wealth quintile). 4.5.1 Trend at national level Figure CM.3 compares the findings of MICS 2014 on under-5 mortality rates with those from other data sources like SHHS 2010, SHSS 2006 and SHSS 2000. The MICS estimates indicate a decline in mortality during the last 20 years. Further secondary data analysis will provide explanation related to probable factors determinants of the acceleration or not of decline of U5MR during the two periods (1995-2006 and 2006-2014). 31 F i g u r e C M . 3 : Trends in Under-Five Mortality and Infant Mortality in Sudan as estimated by SHHS 2000, SHHS 2006, SHHS2 2010 and MICS 2014 4.5.3 Trend by wealth index quintile from SHHS 2010 and MICS 2014 data sources Figure CM.3a below seems to indicate that the reduction of under-five mortality during the last five years greatest among the middle wealth quintile than the poorest and richest quintiles. 104 102 83 68 68 71 60 52 0 20 40 60 80 100 120 1995-2000 2001-2005 2006-2010 2010-2014 U5MR-All MICS InfMR-All MICS 32 Figure CM.3a: Trend in Under Five Mortality Rates by sex of child and wealth quintile in Sudan, SHHS 2010 and Sudan MICS, 2014 86 97 95 77 42 89 76 83 84.2 79.9 67.7 59.6 39.4 78.7 57.6 68 0 20 40 60 80 100 120 Poorest Second Middle Fourth Richest Boys Girls Sudan U5MR SHHS 2010 U5MR MICS 2014 33 V. Nutrition Sudan has been committed to the 2015 Millennium Development Goals aiming to eradicate the extreme poverty and hunger. The reduction of child malnutrition is one of the goals of Sudan’s National Health Sector Strategic Plan (NHSSP) 2012-2016 which intended to reduce the prevalence of moderate malnutrition (underweight) from 32 percent to 16 percent. According to the Ministry of Health’s annual statistical reports, pneumonia, malaria, diarrhoea and malnutrition are the major causes of under-five illness and hospital admission. With reference to the global evidence of studies conducted by the World Bank (2010) and Horton and Steckel (2013) which estimated that investing in nutrition can increase a country’s GDP by at least 3 percent annually, the Investment in Nutrition Case Document developed for Sudan in 2014 has estimated that investing in nutrition can increase Sudan’s 2013 GDP by US$66.55 billions, equaling to a gain of US$2 billion per annum. Sudan has a National Nutrition Policy which supports many of the interventions that are considered to be high impact and evidence based. Within the SHSSP 2012-2016, efforts have been made by Government and Donors in order to strengthen institutional capacity of coordination and management of nutrition services at federal, state and periphery levels and to increase financial investment for addressing the prevention and treatment of acute malnutrition: the coverage of health-based services for treatment of severe acute malnutrition has reached 28 percent in 2014 and government has allocated in 2015 a Sudan amount of US$ 8 million for therapeutic foods. MICS 2014 offers an opportunity to assess the status of child malnutrition in Sudan vis-à-vis MDG 2015 and the NHSSP 2012-2016 targets and to provide baseline evidence-based prioritization of child malnutrition within the full Poverty Reduction Strategic Paper in process, the development of a national multi-sector nutrition strategy and better targeting and investment of humanitarian responses to reduce child acute malnutrition. This chapter presents findings related to low birth weight, nutritional status of children under-five years, breastfeeding and Infant and Young Child Feeding, the use of salt iodization at household level, and the coverage of child’s Vitamin A supplementation. 5.1 Low Birth Weight Weight at birth is a good indicator not only of a mother's health and nutritional status but also the newborn's chances for survival, growth, long-term health and psychosocial development. Low birth weight (defined as less than 2,500 grams) carries a range of grave health risks for children. Babies who were undernourished during pregnancy face a greatly increased risk of dying during their early stages of life up to five years of age. Those who survive may have impaired immune function and increased risk of disease; they are likely to remain undernourished, with reduced muscle strength, throughout their lives, and suffer a higher incidence of diabetes and heart disease in later life. Children born with low birth weight also have a risk of lower IQ and cognitive disabilities, affecting their performance in school and their job opportunities as adults. In developing countries, low birth weight stems primarily from the mother's poor health and nutrition. Three factors have the most impact: the mother's poor nutritional status before conception, short stature (due mostly to under nutrition and infections during her childhood), and poor nutrition during pregnancy. Inadequate weight gain during pregnancy is particularly important since it accounts for a 34 large proportion of foetal growth retardation. Moreover, diseases such as diarrhoea and malaria, which are common in many developing countries, can significantly impair foetal growth if the pregnant mother becomes infected Cigarette smoking during pregnancy is a leading cause of low birth weight. In addition, teenagers who give birth when their own bodies have yet to finish growing run a higher risk of bearing low birth weight babies. One of the major challenges in measuring the incidence of low birth weight is that more than half of infants are not weighed at birth. In the past, most estimates of low birth weight for developing countries were based on data compiled from health facilities. However, these estimates are biased for most developing countries because the majority of new-borns are not delivered in facilities, and those who are represent only a selected sample of all births. Because many infants are not weighed at birth and those who are weighed may be a biased sample of all births, the reported birth weights usually cannot be used to estimate the prevalence of low birth weight among all children. The percentage of births weighing below 2500 grams is estimated from two items in the questionnaire: the mother’s own assessment of the child’s size at birth (i.e., very small, smaller than average, average, larger than average, very large) and the mother’s recall of the child’s weight or the weight as recorded on a health card if the child was weighed at birth.7 Sudan’s 2014 MICS report states that 16.3 percent of births were weighed at birth. Approximately 32.3 percent of infants born during the last two years were estimated to weigh less than 2,500 grams at birth (Table NU.1). The prevalence of low birth weight varies by urban 27.9 percent and rural area 33.9 percent and by mother’s education from 33.7 percent among children for whose mothers are not educated to 23.7 percent for children whose mothers have higher level of education. The highest prevalence of low birth weight was observed in states of North Darfur (47.5 percent), East Darfur (46.9 percent), North Kordofan (41.4 percent) and West Kordofan (36 percent) in comparison to the low prevalence observed in states of River Nile (17.2 percent), Khartoum (22.2 percent), Gadarif (23.9 percent) and Blue Nile (25.7 percent). There is inequality of the prevalence of low birth weight among children in the wealth index quintiles of the population; 39 percent among children living in the poorest household to 22.2 percent for children of richest household category. 7 For a detailed description of the methodology, see Boerma, JT et al. 1996. Data on Birth Weight in Developing Countries: Can Surveys Help? Bulletin of the World Health Organization 74(2): 209-16. 35 Table NU.1: Low birth weight infants Percentage of last live-born children in the last two years that are estimated to have weighed below 2,500 grams at birth and percentage of live births weighed at birth, Sudan MICS, 2014 Background Characteristics Percent distribution of births by mother's assessment of size at birth Sudan Percentage of live births: Number of last live- born children in the last two years Very small Smaller than average Average Larger than average or very large DK Below 2,500 grams [1] Weighed at birth [2] Sudan 18.6 15.2 51.5 12.9 1.8 100.0 32.3 16.3 5,622 Mother's age at birth Less than 20 years 19.7 20.2 47.2 11.3 1.5 100.0 36.2 11.6 640 20-34 years 18.8 14.9 51.5 13.1 1.8 100.0 32.2 16.4 4,001 35-49 years 17.4 13.3 54.0 13.4 1.8 100.0 30.3 19.2 981 Birth order 1 16.6 16.8 53.7 11.7 1.1 100.0 31.9 21.9 910 2-3 16.2 14.8 54.0 13.0 2.0 100.0 30.5 19.3 1,669 4-5 18.8 16.1 51.0 12.2 1.9 100.0 33.1 13.5 1,428 6+ 22.1 14.0 48.0 14.1 1.8 100.0 33.8 12.7 1,614 State Northern 16.3 9.0 67.9 5.8 1.1 100.0 27.1 27.3 92 River Nile 2.7 7.5 81.2 8.6 .0 100.0 17.2 26.5 151 Red Sea 15.4 9.1 53.0 6.2 16.2 100.0 29.3 26.2 92 Kassala 16.2 7.8 62.3 12.4 1.3 100.0 26.0 13.7 199 Gadarif 9.0 11.6 70.9 7.8 0.6 100.0 23.9 7.2 307 Khartoum 7.8 10.5 69.5 11.4 0.8 100.0 22.2 56.3 684 Gezira 13.3 19.5 60.8 6.0 0.3 100.0 31.6 15.2 852 White Nile 24.6 13.4 50.0 8.7 3.3 100.0 35.6 13.6 273 Sinnar 18.2 15.4 55.6 9.9 0.9 100.0 32.1 13.1 226 Blue Nile 15.2 9.9 43.9 30.9 0.1 100.0 25.7 12.4 287 North Kordofan 23.8 23.9 36.5 13.2 2.5 100.0 41.4 10.9 352 South Kordofan 20.4 14.0 51.2 12.1 2.2 100.0 32.9 7.9 194 West Kordofan 26.6 12.9 48.2 10.8 1.5 100.0 36.0 4.3 341 North Darfur 29.5 26.9 34.6 6.0 3.0 100.0 47.5 5.3 525 West Darfur 14.4 17.3 37.0 27.0 4.2 100.0 30.7 12.7 179 South Darfur 26.6 11.2 37.1 23.2 1.9 100.0 34.5 5.1 556 Central Darfur 11.2 11.8 42.9 33.3 0.9 100.0 24.3 5.7 99 East Darfur 38.8 17.5 21.6 19.4 2.6 100.0 46.9 4.2 211 Area Urban 15.2 11.7 56.4 14.6 2.1 100.0 27.9 33.6 1,488 Rural 19.9 16.5 49.7 12.3 1.7 100.0 33.9 10.1 4,134 Mother’s education None 20.2 15.8 46.4 15.2 2.4 100.0 33.7 5.8 2,247 Primary 19.4 16.9 50.0 12.5 1.2 100.0 33.8 13.2 2,022 Secondary 16.6 12.9 58.6 10.0 2.0 100.0 29.7 31.3 942 Higher 10.9 9.5 69.9 8.9 0.8 100.0 23.7 54.7 410 Wealth index quintile 36 Background Characteristics Percent distribution of births by mother's assessment of size at birth Sudan Percentage of live births: Number of last live- born children in the last two years Very small Smaller than average Average Larger than average or very large DK Below 2,500 grams [1] Weighed at birth [2] Poorest 25.3 19.2 39.2 14.7 1.7 100.0 39.0 3.7 1,251 Second 22.7 15.3 44.9 14.7 2.4 100.0 35.1 7.4 1,232 Middle 17.7 14.7 52.8 13.0 1.8 100.0 31.4 10.9 1,192 Fourth 15.2 16.0 55.9 11.5 1.5 100.0 30.6 21.0 1,096 Richest 8.9 9.0 71.3 9.5 1.3 100.0 22.2 49.3 851 [1] MICS indicator 2.20 - Low-birthweight infants [2] MICS indicator 2.21 - Infants weighed at birth 5.2 Nutritional Status Children’s nutritional status is a reflection of their overall health. When children have access to an adequate food supply, are not exposed to repeated illness, and are well cared for, they reach their growth potential and are considered well nourished. Malnutrition is associated with more than half of all child deaths worldwide. Undernourished children are more likely to die from common childhood ailments, and for those who survive, have recurring sicknesses and faltering growth. Three-quarters of children who die from causes related to malnutrition were only mildly or moderately malnourished – showing no outward sign of their vulnerability. The Millennium Development Goal target is to reduce by half the proportion of people who suffer from hunger between 1990 and 2015. A reduction in the prevalence of malnutrition will also assist in the goal to reduce child mortality. In a well-nourished population, there is a reference distribution of height and weight for children under age five. Under-nourishment in a population can be gauged by comparing children to a reference population. The reference population used in this report is based on the WHO growth standards8. Each of the three nutritional status indicators – weight-for-age, height-for-age, and weight-for-height - can be expressed in standard deviation units (z-scores) from the median of the reference population. Weight-for-age is a measure of both acute and chronic malnutrition. Children whose weight-for-age is more than two standard deviations below the median of the reference population are considered moderately or severely underweight while those whose weight-for-age is more than three standard deviations below the median are classified as severely underweight. Height-for-age is a measure of linear growth. Children whose height-for-age is more than two standard deviations below the median of the reference population are considered short for their age and are classified as moderately or severely stunted. Those whose height-for-age is more than three standard deviations below the median are classified as severely stunted. Stunting is a reflection of chronic malnutrition as a result of failure to receive adequate nutrition over a long period and recurrent or chronic illness. 8 http://www.who.int/childgrowth/standards/technical_report 37 Weight-for-height can be used to assess wasting and overweight status. Children whose weight-for- height is more than two standard deviations below the median of the reference population are classified as moderately or severely wasted, while those who fall more than three standard deviations below the median are classified as severely wasted. Wasting is usually the result of a recent nutritional deficiency. The indicator of wasting may exhibit significant seasonal shifts associated with changes in the availability of food or disease prevalence. Children whose weight-for-height is more than two standard deviations above the median reference population are classified as moderately or severely overweight. In MICS, weights and heights of all children under 5 years of age were measured using the anthropometric equipment recommended9 by UNICEF. Findings in this section are based on the results of these measurements. Table NU.2 shows percentages of children classified into each of the above described categories, based on the anthropometric measurements that were taken during fieldwork. Additionally, the table includes mean z-scores for all three anthropometric indicators. Regarding the quality of nutrition’s indicators, children whose full birth date (month and year) were not obtained and children whose measurements are outside a plausible range are excluded from Table NU.2. Children are excluded from one or more of the anthropometric indicators when their weights and heights have not been measured, whichever applicable. For example, if a child has been weighed but his/her height has not been measured, the child is included in underweight calculations, but not in the calculations for stunting and wasting. Percentages of children by age and reasons for exclusion are shown in the data quality Tables DQ.12, DQ.13, and DQ.14 in Appendix D. The tables show that due to incomplete dates of birth, implausible measurements, missing weight and/or height and possible particular situation in Sudan, 19.3 percent of children have been excluded from calculations of the weight-for-age indicator, 21.8 percent from the height-for-age indicator, and 11.9 percent for the weight-for-height indicator. 9 See MICS Supply Procurement Instructions: http://www.childinfo.org/mics5_planning.html 38 Table NU.2: Nutritional status of children Percentage of children under age 5 by nutritional status according to three anthropometric indices: weight for age, height for age, and weight for height, Sudan MICS, 2014 Background characteristics Weight for age Number of children under age 5 Height for age Number of children under age 5 Weight for height Number of children under age 5 Underweight Mean Z- Score (SD) Stunted Mean Z- Score (SD) Wasted Overweight Mean Z- Score (SD) Percent below Percent below Percent below Percent above - 2 SD [1] - 3 SD [2] - 2 SD [3] - 3 SD [4] - 2 SD [5] - 3 SD [6] + 2 SD [7] Sudan 33.0 12.0 -1.5 11,713 38.2 18.2 -1.6 11,333 16.3 4.5 3.0 -.8 12,550 Sex Male 34.6 12.8 -1.5 5,975 40.3 20.5 -1.6 5,778 16.9 5.1 3.2 -.9 6,375 Female 31.5 11.2 -1.4 5,737 36.1 15.8 -1.5 5,556 15.7 3.8 2.8 -.8 6,175 State Northern 21.9 4.5 -1.1 214 22.6 7.2 -1.1 208 11.4 2.6 2.7 -.7 206 River Nile 32.2 11.0 -1.5 338 29.5 12.1 -1.2 336 20.1 6.1 2.0 -1.0 346 Red Sea 33.6 15.9 -1.6 182 45.4 27.1 -1.9 178 14.0 2.3 4.1 -.6 184 Kassala 42.0 15.5 -1.7 409 48.8 25.7 -1.8 400 18.5 5.1 1.7 -1.0 414 Gadarif 37.7 15.5 -1.6 666 46.0 24.3 -1.9 658 15.4 5.4 4.6 -.7 698 Khartoum 23.2 6.4 -1.2 1,603 21.9 8.4 -1.0 1,593 14.5 3.8 .5 -.8 1,632 Gezira 32.4 12.3 -1.3 2,084 41.6 21.1 -1.7 2,046 14.0 3.7 8.5 -.5 2,050 White Nile 29.8 11.1 -1.4 572 36.6 17.4 -1.5 562 14.4 3.5 2.2 -.7 622 Sinnar 36.4 14.6 -1.6 471 38.1 17.9 -1.5 465 16.0 4.5 1.6 -1.0 477 Blue Nile 35.3 10.7 -1.5 668 46.7 22.6 -1.9 656 11.1 2.7 2.2 -.6 666 North Kordofan 32.4 11.5 -1.5 752 40.8 17.5 -1.7 731 14.8 4.5 2.5 -.8 764 South Kordofan 34.8 14.5 -1.6 431 40.6 23.7 -1.6 413 16.3 3.8 2.6 -.8 452 West Kordofan 38.7 14.8 -1.5 388 42.5 22.4 -1.5 383 18.7 5.1 1.5 -1.0 781 North Darfur 44.9 16.9 -1.9 861 45.9 21.6 -1.8 759 27.9 8.6 .9 -1.4 959 West Darfur 29.4 9.9 -1.3 223 35.2 13.7 -1.2 218 19.1 6.7 4.7 -0.9 455 South Darfur 29.4 9.9 -1.4 1,231 34.2 12.8 -1.4 1,120 15.9 3.5 .3 -1.0 1,164 Central Darfur 41.0 18.5 -1.6 163 47.5 25.5 -1.8 156 17.8 4.3 5.9 -0.7 221 East Darfur 40.2 16.6 -1.7 457 46.6 24.7 -1.8 452 15.3 4.2 .9 -0.9 460 Area Urban 23.2 7.6 -1.2 3,405 27.1 10.8 -1.2 3,327 13.4 3.6 2.5 -0.7 3,494 39 Background characteristics Weight for age Number of children under age 5 Height for age Number of children under age 5 Weight for height Number of children under age 5 Underweight Mean Z- Score (SD) Stunted Mean Z- Score (SD) Wasted Overweight Mean Z- Score (SD) Percent below Percent below Percent below Percent above - 2 SD [1] - 3 SD [2] - 2 SD [3] - 3 SD [4] - 2 SD [5] - 3 SD [6] + 2 SD [7] Rural 37.1 13.8 -1.6 8,308 42.9 21.2 -1.7 8,006 17.4 4.8 3.2 -0.9 9,056 Age 0-5 months 12.4 4.3 -0.5 1,296 12.2 5.3 -0.3 1,100 12.2 4.1 7.2 -0.3 1,158 6-11 months 24.1 9.1 -1.1 1,308 18.6 6.4 -0.8 1,274 18.3 6.1 3.3 -0.8 1,319 12-17 months 34.8 12.7 -1.4 1,290 36.1 14.8 -1.4 1,274 22.6 6.6 2.4 -1.1 1,361 18-23 months 36.3 15.1 -1.7 1,034 46.0 23.5 -1.9 1,014 19.5 5.2 0.9 -0.9 1,083 24-35 months 39.4 16.6 -1.8 2,216 49.8 25.2 -2.0 2,166 17.1 4.9 2.3 -0.9 2,391 36-47 months 37.9 13.3 -1.6 2,555 47.2 23.9 -1.9 2,519 13.2 3.0 3.0 -0.8 2,928 48-59 months 36.2 10.2 -1.6 2,014 38.8 17.5 -1.7 1,987 15.2 3.7 2.7 -0.9 2,310 Mother's education None 40.8 17.2 -1.7 4,683 46.8 24.3 -1.9 4,504 18.1 5.2 2.0 -1.0 5,278 Primary 32.3 11.1 -1.4 4,179 37.8 17.1 -1.5 4,055 16.3 4.5 3.4 -0.8 4,430 Secondary 23.8 5.4 -1.1 1,930 27.6 10.1 -1.2 1,883 13.5 2.9 4.1 -0.7 1,934 Higher 16.8 3.7 -0.9 907 19.7 9.2 -1.0 877 12.1 3.2 4.5 -0.5 891 Missing/DK * * -1.0 14 * * -0.9 13 * * * -1.0 16 Wealth index quintile Poorest 39.5 14.9 -1.7 2,277 44.0 22.2 -1.8 2,127 20.1 5.7 1.4 -1.1 2,720 Second 39.8 16.4 -1.7 2,321 47.3 23.9 -1.8 2,235 17.8 4.9 2.0 -0.9 2,657 Middle 35.4 13.6 -1.6 2,548 43.6 20.9 -1.7 2,481 15.4 5.3 3.4 -0.8 2,641 Fourth 31.1 9.9 -1.4 2,493 33.8 14.9 -1.4 2,462 15.4 3.3 3.8 -0.7 2,482 Richest 17.8 4.6 -1.0 2,072 21.1 8.4 -1.0 2,027 11.7 2.6 4.8 -0.6 2,050 1 MICS indicator 2.1a and MDG indicator 1.8 - Underweight prevalence (moderate and severe) 2 MICS indicator 2.1b - Underweight prevalence (severe) 3 MICS indicator 2.2a - Stunting prevalence (moderate and severe) 4 MICS indicator 2.2b - Stunting prevalence (severe) 5 MICS indicator 2.3a - Wasting prevalence (moderate and severe) 6 MICS indicator 2.3b - Wasting prevalence (severe) 7 MICS indicator 2.4 - Overweight prevalence 40 5.2.1 Overall Status of Child Malnutrition In Sudan, as indicated by the graph below, the overall prevalence of child malnutrition is high: one- third (33 percent) of under-five children are underweight, approximately two in five children (38.2 percent) under-five years are stunted (too short for their age), and one in six (16.3 percent) children is wasted (too thin for their height). Figure NU.1a: Percentage of underweight, stunted and wasted children under-five years in Sudan MICS, 2014 With regard to gender variation in undernutrition, boys were reported to be slightly more underweight, stunted, and wasted than girls. The age pattern shows that a higher percentage of children in the age group 12-23 months are undernourished according to all three indices in comparison to children who are in the younger and older age groups (Figure NU.1b). This pattern is expected and is related to the age group at which many children cease to be breastfed and are exposed to contamination in water, food, and environment. 33 38.2 16.3 12 18.2 4.5 0 5 10 15 20 25 30 35 40 45 Underweight Stunting Wasting Moderate & Severe (-2SD) Severe (-3SD) 41 Figure NU.1: Underweight, stunted, wasted and overweight children under age 5 (moderate and severe), Sudan MICS, 2014 5.2.2 Geographic Inequity in Child Malnutrition Table NU.2 shows that children living in the rural area are the most affected by child malnutrition. The prevalence of underweight is 23.2 percent in urban area in comparison to 37.1 percent in rural area; 17.4 percent of children living in rural area are affected by acute malnutrition in comparison to 13.4 percent for urban area. The gap is very high regarding child stunting between rural area (43 percent) and urban area (27.1 percent). In Sudan, children are mostly affected by malnutrition in the states affected by conflicts and displacements of populations; Darfur and Kordofan, and in Kassala state as indicated below: x Very high prevalence of child underweight in the states of North Darfur (44.9 percent), Central Darfur (41.0 percent), East Darfur (40.2 percent), West Kordofan (38.7 percent) and Kassala (42.0 percent) in comparison to the lowest prevalence in Northern (21.9 percent), Khartoum (23.2 percent) and White Nile (29.8 percent). x High stunting prevalence among children in the states of Kassala (48.8 percent), Blue Nile (46.7 percent), Central Darfur (47.5 percent), North Darfur (45.9 percent) and East Darfur (46.6 percent). x Severe wasting prevalence, children are likely to be affected in the states of North Darfur (8.6 percent), West Darfur (6.7 percent), Central Darfur (4.3 percent) and Kassala (5.1 percent). Underweight Stunted Wasted Overweight 0 10 20 30 40 50 60 0 12 24 36 48 60 P E R C E N T AGE IN MONTHS 42 Figure NU.1b: Percentage of underfive children stunted (moderate and severe) by State, Sudan MICS, 2014 0.0 5.0 10.0 15.0 20.0 25.0 30.0 35.0 40.0 45.0 50.0 Khartoum Northern River Nile South Darfor West Darfor White Nile Sinnar Sudan South Kordofan North Kordofan Gezira West Kordofan Red Sea North Darfor Gadarif East Darfor Blue Nile Central Darfor Kassala 21.9 22.6 29.5 34.2 35.2 36.6 38.1 38.2 40.6 40.8 41.6 42.5 45.4 45.9 46.0 46.6 46.7 47.5 48.8 43 Figure NU.1.c: Percentage of underfive children wasted (moderate and severe acute malnutrition) by State, Sudan MICS, 2014 5.2.3 Disparity of Child Malnutrition by Wealth Index Quintile Figure NU.1d below shows the disparity in child malnutrition by household poverty conditions measured through the wealth index calculated using household assets. The prevalence of underweight, stunting and wasting is highest among children living in poorest household respectively 39.5 percent, 44.0 percent and 20.1 percent in comparison to low prevalence of malnutrition among children living in the richest household respectively 17.8 percent, 21.1percent and 11.7percent. 0.0 5.0 10.0 15.0 20.0 25.0 30.0 Blue Nile Northern Red Sea Gezira White Nile Khartoum North Kordofan East Darfor Gadarif South Darfor Sinnar South Kordofan Sudan Central Darfor Kassala West Kordofan West Darfor River Nile North Darfor 11.1 11.4 14.0 14.0 14.4 14.5 14.8 15.3 15.4 15.9 16.0 16.3 16.3 17.8 18.5 18.7 19.1 20.1 27.9 44 Figure NU.1d: Percentage of children under five years underweight, stunted or wasted by household wealth quintile, Sudan MICS, 2014 5.2.4 Disparity in Child Malnutrition by Mother’s Education Children whose mothers have secondary or higher education are the least likely to be underweight and stunted compared to children of mothers with no education as indicated by table NU.2. 0.0 5.0 10.0 15.0 20.0 25.0 30.0 35.0 40.0 45.0 50.0 Underweight Stunting Wasting 39.5 44.0 20.1 17.8 21.1 11.7 Poorest Second Middle Fourth Richest 45 5.2.5 Trends in Under-five Nutritional Status from 2006 to 2014 Since 2006, the nutritional status of children in Sudan remains as very challenging issues for child survival. Using the same WHO standard reference, the figure NU1.f below indicates that there has not been any change in the prevalence of acute malnutrition. The prevalence is still over the WHO emergency threshold of 15 percent. The percentage of underweight children remains also high at the same level of approximately one-third of under-five children as estimated by all three national surveys; SHHS 2006, SHHS 2010 and MICS 2014. The prevalence of stunting has increased from 32.5 percent in 2006 to 35 percent in 2010 and to 38.2 percent in 2014. With reference to the literature, gap of knowledge of mothers of child malnutrition, the gap of capacities of health facilities, the low effective use of health services due to limited geographic access and financial barriers (poverty issue and health policy of cost recovery), low coverage of use of improved sanitation facilities (33 percent), the high prevalence of diarrhoea among children (29percent) and the continuous influx of displaced populations and refugees represent key determinant factors for increased child malnutrition in Sudan. Figure NU.1e: Trend in percentage of children underfive years that are underweight, stunted and wasted (moderate and severe), SHHS 2006, SHHS 2010 and Sudan MICS 2014 In view of equity, figure NU.1g below shows that there is an important increase of stunting (from 15 percent in 2010 to 21.1) among children living in richest household conditions in comparison to low increase affecting poorest children. However, regarding the acute malnutrition, there has been a tendency of increase of prevalence of wasting among poorest children in comparison to a decrease trend for children living in richest family conditions. 0.0 5.0 10.0 15.0 20.0 25.0 30.0 35.0 40.0 Underweight Stunting Wasting 31.0 32.5 14.8 32.2 35.0 16.4 33.0 38.2 16.3 SHHS 2006 SHHS 2010 MICS 2014 46 Figure NU.1f: Trend in inequality of Poorest and Richest under five children underweight, stunted or wasted, SHHS 2010 and Sudan MICS, 2014 Figure NU.1g below indicates that the prevalence of stunting has increased in the states of Darfur, Kordofan, Blue Nile and Gadarif. However, the prevalence of stunting has decreased in River Nile, Read Sea, Sinnar and Northern. The prevalence of acute malnutrition has increased in Darfur from 24.4 percent in 2010 to 28 percent in 2014. 0.0 5.0 10.0 15.0 20.0 25.0 30.0 35.0 40.0 45.0 18.8 12.7 42.1 15.0 40.0 16.5 20.1 11.7 44.0 21.1 39.5 17.8 SHHS 2010 MICS 2014 47 Figure NU.1g: Trend in Stunted Children underfive years (moderate and severe) from SHHS 2010 to Sudan MICS 2014 5.3 Breastfeeding and Infant and Young Child Feeding Proper feeding of infants and young children can increase their chances of survival; it can also promote optimal growth and development, especially in the critical window from birth to 2 years of age. Breastfeeding for the first few years of life protects children from infection, provides an ideal source of nutrients, and is economical and safe. However, many mothers don’t start to breastfeed early enough, do not breastfeed exclusively for the recommended 6 months or stop breastfeeding too soon. There are often pressures to switch to infant formula, which can contribute to growth faltering and micronutrient malnutrition and can be unsafe if hygienic conditions, including safe drinking water are not readily available. Studies have shown that, in addition to continued breastfeeding, consumption of appropriate, adequate and safe solid, semi-solid and soft foods from the age of 6 months onwards, leads to better health and growth outcomes, with potential to reduce stunting during the first two years of life.10 10 Bhuta, Z. et al. 2013. Evidence-based interventions for improvement of maternal and child nutrition: what can be done and at what cost? The Lancet June 6, 2013. 0.0 10.0 20.0 30.0 40.0 50.0 60.0 Khartoum Northern River Nile South Darfor West Darfor White Nile Sinnar Sudan South Kordofan North Kordofan Gezira West Kordofan Red Sea North Darfor Gadarif East Darfor Blue Nile Central Darfor Kassala SHHS 2010 MICS 2014 48 UNICEF and WHO recommend that infants be breastfed within one hour of birth, breastfed exclusively for the first six months of life and continue to be breastfed up to 2 years of age and beyond.11 Starting at 6 months, breastfeeding should be combined with safe, age-appropriate feeding of solid, semi-solid and soft foods.12 A summary of key guiding principles13, 14 for feeding 6-23 month olds is provided in the table below along with proximate measures for these guidelines collected in this survey. The guiding principles for which proximate measures and indicators exist are: (i) continued breastfeeding; (ii) appropriate frequency of meals (but not energy density); and (iii) appropriate nutrient content of food Feeding frequency is used as proxy for energy intake, requiring children to receive a minimum number of meals/snacks (and milk feeds for non-breastfed children) for their age. Dietary diversity is used to ascertain the adequacy of the nutrient content of the food (not including iron) consumed. For dietary diversity, seven food groups were created for which a child consuming at least four of these is considered to have a better quality diet. In most populations, consumption of at least four food groups means that the child has a high likelihood of consuming at least one animal-source food and at least one fruit or vegetable, in addition to a staple food (grain, root or tuber).15 These three dimensions of child feeding are combined into an assessment of the children who received appropriate feeding, using the indicator of “minimum acceptable diet”. To have a minimum acceptable diet in the previous day, a child must have received: (i) the appropriate number of meals/snacks/milk feeds; (ii) food items form at least 4 food groups; and (iii) breastmilk or at least 2 milk feeds (for non-breastfed children). Guiding Principle (age 6-23 months) Proximate measures Table Continue frequent, on-demand breastfeeding for two years and beyond Breastfed in the last 24 hours NU.4 Appropriate frequency and energy density of meals Breastfed children Depending on age, two or three meals/snacks provided in the last 24 hours Non-breastfed children Four meals/snacks and/or milk feeds provided in the last 24 hours NU.6 Appropriate nutrient content of food Four food groups16 eaten in the last 24 hours NU.6 Appropriate amount of food No standard indicator exists na Appropriate consistency of food No standard indicator exists na Use of vitamin-mineral supplements or fortified products for infant and mother No standard indicator exists na 11 WHO. 2003. Implementing the Global Strategy for Infant and Young Child Feeding. Meeting Report Geneva, 3-5 February, 2003. 12 WHO. 2003. Global Strategy for Infant and Young Child Feeding. 13 PAHO. 2003. Guiding principles for complementary feeding of the breastfed child. 14 WHO. 2005. Guiding principles for feeding non-breastfed children 6-24 months of age. 15 WHO. 2008. Indicators for assessing infant and young child feeding practices. Part 1: Definitions. 16 Food groups used for assessment of this indicator are 1) Grains, roots and tubers, 2) legumes and nuts, 3) dairy products (milk, yogurt, cheese), 4) flesh foods (meat, fish, poultry and liver/organ meats), 5) eggs, 6) vitamin-A rich fruits and vegetables, and 7) other fruits and vegetables. 49 Practice good hygiene and proper food handling While it was not possible to develop indicators to fully capture programme guidance, one standard indicator does cover part of the principle: Not feeding with a bottle with a nipple NU.9 Practice responsive feeding, applying the principles of psycho-social care No standard indicator exists na 5.3.1 Initial Breastfeeding Table NU.3 is based on mothers’ reports of what their last-born child, born in the last two years, was fed in the first few days of life. It indicates the proportion who were ever breastfed, those who were first breastfed within one hour and one day of birth, and those who received a prelacteal feed.17 In Sudan, 95.6 percent of children ever breastfed. Although a very important step in management of lactation and establishment of a physical and emotional relationship between the baby and the mother, only 68.7 percent of babies are breastfed for the first time within one hour of birth, while 87.2 percent of new-borns in Sudan start breastfeeding within one day of birth. The findings are presented in Figure NU.2 by state and area. The relative low percentage of initial breastfed children within one hour is observed in Central Darfur (48.6percent) and South Darfur (51.0percent). Figure NU.2: Initiation of breastfeeding, Sudan MICS, 2014 17 Prelacteal feed refers to the provision any liquid or food, other than breastmilk, to a newborn during the period when breastmilk flow is generally being established (estimated here as the first 3 days of life). 93 93 84 86 95 92 92 90 88 90 76 83 73 87 89 83 88 87 89 86 87 37 74 74 77 90 74 69 75 68 70 63 76 60 77 68 51 49 66 71 68 69 0 20 40 60 80 100 P er c en t Within one day Within one hour 50 Table NU.3 shows that early breastfeeding of children by mothers within one hour of birth represents a universal practice of mothers in Sudan irrespective of their socio-economic status, education level, location of delivery or assistance at delivery by skilled health worker. Table NU.3: Initial breastfeeding Percentage of last live-born children in the last two years who were ever breastfed, breastfed within one hour of birth, and within one day of birth, and percentage who received a pre-lacteal feed, Sudan MICS, 2014 Background characteristics Percentage who were ever breastfed [1] Percentage who were first breastfed: Percentage who received a pre- lacteal feed Number of last live-born children in the last two years Within one hour of birth [2] Within one day of birth Sudan 95.6 68.7 87.2 28.3 5,622 State Northern 99.2 36.7 93.1 44.2 92 River Nile 97.3 74.1 93.5 43.6 151 Red Sea 87.3 74.2 84.4 16.9 92 Kassala 94.9 76.6 85.5 19.5 199 Gadarif 96.8 90.2 94.6 25.7 307 Khartoum 96.9 73.7 91.9 35.9 684 Gezira 95.2 68.8 91.8 35.2 852 White Nile 97.4 74.6 89.9 42.1 273 Sinnar 97.9 68.0 87.7 32.6 226 Blue Nile 98.8 70.1 90.2 25.1 287 North Kordofan 96.9 62.8 76.0 38.6 352 South Kordofan 96.2 75.7 82.8 30.7 194 West Kordofan 88.6 59.9 72.7 11.8 341 North Darfur 95.9 77.2 86.9 10.2 525 West Darfur 93.4 68.3 89.1 3.6 179 South Darfur 95.2 51.0 82.7 28.8 556 Central Darfur 95.8 48.6 87.6 14.9 99 East Darfur 95.7 65.5 86.8 33.9 211 Area Urban 96.0 71.0 89.1 30.1 1,488 Rural 95.5 67.9 86.5 27.6 4,134 Months since last birth 0-11 months 95.5 68.9 86.2 27.0 3,001 12-23 months 95.8 68.5 88.3 29.7 2,620 Assistance at delivery Skilled attendant 96.4 70.2 88.8 28.4 4,370 Traditional birth attendant/Daya habil 96.2 65.8 84.2 26.8 1,014 Other 93.7 67.4 84.9 28.7 144 No one/Missing 57.9 33.2 48.9 35.7 94 Place of delivery Home 96.4 71.5 87.8 26.3 4,006 Health facility: Public 96.3 63.4 88.1 34.0 1,468 Health facility: Private 96.7 65.1 86.6 37.1 91 Other/Missing 22.9 16.7 18.6 1.6 57 Mother's education None 95.5 68.0 85.1 27.7 2,247 51 Background characteristics Percentage who were ever breastfed [1] Percentage who were first breastfed: Percentage who received a pre- lacteal feed Number of last live-born children in the last two years Within one hour of birth [2] Within one day of birth Primary 95.9 67.5 87.3 29.4 2,022 Secondary 94.9 73.1 89.8 25.4 942 Higher 97.3 68.8 92.0 32.5 410 Wealth index quintile Poorest 94.4 62.1 81.2 23.9 1,251 Second 95.5 69.8 86.1 22.3 1,232 Middle 97.5 73.1 89.6 30.4 1,192 Fourth 94.6 68.2 89.5 34.3 1,096 Richest 96.4 71.3 91.1 32.5 851 [1] MICS indicator 2.5 - Children ever breastfed [2] MICS indicator 2.6 - Early initiation of breastfeeding 5.3.2 Young Child Feeding The set of Infant and Young Child Feeding indicators reported in tables NU.4 through NU.8 are based on the mother’s report of children’s consumption of food and fluids during the day or night prior to being interviewed. Data are subject to a number of limitations, some related to the respondent’s ability to provide a full report on the child’s liquid and food intake due to recall errors as well as lack of knowledge in cases where the child was fed by other individuals. In Table NU.4, breastfeeding status is presented for both exclusively breastfed and predominantly breastfed. Exclusively breastfed refers to children age less than 6 months who received only breast milk (and vitamins, mineral supplements, or medicine), distinguished by the predominantly breastfed allowing also plain water and non-milk liquids. The table also shows continued breastfeeding of children at 12-15 and 20-23 months of age. In Sudan, overall 55.4 percent of children age less than six months are exclusively breastfed with limited disparity between girls (54.3 percent) and boys (56.7 percent) and between urban (53.1 percent) and rural area (56.3 percent). With 80.8 percent predominantly breastfed, it is evident that water-based liquids are displacing feeding of breastmilk to the greatest degree. 52 Table NU.4: Breastfeeding Percentage of living children according to breastfeeding status at selected age groups, Sudan MICS, 2014 Background characteristics Children age 0-5 months Children age 12-15 months Children age 20-23 months Percent exclusively breastfed [1] Percent pre- dominantly breastfed [2] Number of children Percent breastfed (Continued breastfeeding at 1 year) [3] Number of children Percent breastfed (Continued breastfeeding at 2 years) [4] Number of children Sudan 55.4 80.8 1,516 89.4 1,019 48.8 799 Sex Male 56.7 80.4 735 88.5 496 50.7 425 Female 54.3 81.2 781 90.1 523 46.6 375 State Northern (34.7) (79.5) 21 (93.7) 19 (48.6) 13 River Nile (38.2) (81.0) 39 (95.7) 32 (74.6) 17 Red Sea * * 17 * 14 * 21 Kassala 61.3 79.5 56 (74.9) 27 (39.8) 23 Gadarif 67.3 86.7 96 85.2 51 (37.7) 38 Khartoum 55.9 81.0 160 98.7 146 49.1 133 Gezira 50.0 83.0 226 87.7 142 52.1 154 White Nile 59.4 84.3 74 94.2 56 (58.7) 31 Sinnar 43.1 83.3 58 91.0 37 (42.1) 30 Blue Nile 54.9 90.4 70 92.1 56 40.5 48 North Kordofan 69.6 87.4 92 (92.7) 56 (36.6) 57 South kordofan 51.3 71.2 56 87.2 31 61.9 25 West Kordofan 43.5 64.2 126 83.9 68 (65.6) 35 North Darfur 75.6 90.3 121 87.0 96 (43.7) 42 West Darfur 57.0 66.7 50 82.7 25 (40.8) 22 South Darfur 50.4 84.7 155 83.4 108 41.9 79 Central Darfur 44.5 65.4 34 84.9 23 * 7 East Darfur 60.3 75.8 65 89.0 35 (54.0) 23 Area Urban 53.1 78.9 399 90.4 253 46.7 260 Rural 56.3 81.5 1,117 89.0 767 49.8 539 Mother's education None 51.6 80.0 648 85.2 447 55.2 265 Primary 57.2 81.4 581 90.6 322 42.5 302 Secondary 61.3 87.2 193 95.2 183 54.2 154 Higher 59.2 69.8 92 95.0 68 41.0 78 Missing/DK * * 1 * 0 * 0 Wealth index quintile Poorest 58.4 81.8 364 84.7 231 45.7 124 Second 55.9 77.9 350 90.5 226 49.0 158 Middle 52.4 85.2 332 91.6 229 55.2 163 Fourth 53.4 84.1 274 86.7 179 48.2 212 Richest 57.0 72.1 196 94.5 155 44.7 142 [1] MICS indicator 2.7 - Exclusive breastfeeding under 6 months [2] MICS indicator 2.8 - Predominant breastfeeding under 6 months [3] MICS indicator 2.9 - Continued breastfeeding at 1 year [4] MICS indicator 2.10 - Continued breastfeeding at 2 years ( ) Figures that are based on 25-49 unweighted cases; (*) Figures that are based on fewer than 25 unweighted cases 53 Figure NU.3: Exclusive Breastfeeding (per cent), Sudan MICS, 2014 Figure NU.4 shows the detailed pattern of breastfeeding by the child’s age in months. Even at the earliest ages, the majority of children are receiving liquids or foods other than breast milk, with local soup named “Salega/Maraga” being of highest prevalence, even at the early age of 0-1 months. At age 4-5 months old, the percentage of children exclusively breastfed is below 20 percent. Only about 0.7 percent of children are receiving breast milk at age 2 years. 75.6 69.6 67.3 61.3 60.3 59.4 57 55.9 54.9 51.3 50.4 50 43.5 43.1 53.1 56.3 55.4 0 10 20 30 40 50 60 70 80 North Darfor North Kordofan Gadarif Kassala East Darfor White Nile West Darfor Khartoum Blue Nile South Kordofan South Darfor Gezira West Kordofan Sinnar Urban Rural Sudan 54 Figure NU.4: Infant feeding patterns by age, Sudan MICS, 2014 Table NU.5 shows the median duration of breastfeeding by selected background characteristics. Among children under age 36 months, the median duration is 21.2 months for any breastfeeding, 3.1 months for exclusive breastfeeding, and 5.8 months for predominant breastfeeding. There is no significant difference of duration of breastfeeding by geographic area, mother’s education and wealth index quintile. However specific cases of very low duration of exclusive breastfeeding of children is observed in Northern and West Kordofan (0.7 months), River Nile (1.4 months) and Central Darfur (1.9 months). Exclusively breastfed Breastfed and complementary foods Weaned (not breastfed) 0% 10% 20% 30% 40% 50% 60% 70% 80% 90% 100% 0-1 2-3 4-5 6-7 8-9 10-11 12-13 14-15 16-17 18-19 20-21 22-23 Age in months Exclusively breastfed Breastfed and plain water only Breastfed and non-milk liquids Breastfed and other milk / formula Breastfed and complementary foods Weaned (not breastfed) 55 Table NU.5: Duration of breastfeeding Median duration of any breastfeeding, exclusive breastfeeding, and predominant breastfeeding among children age 0-35 months, Sudan MICS, 2014 Background characteristics Median duration (in months) of Number of children age 0-35 months Any breastfeeding [1] Exclusive breastfeeding Predominant breastfeeding Median 21.2 3.1 5.8 8,254 Sex Male 21.3 3.1 5.7 4,200 Female 21.0 3.0 6.0 4,054 State Northern 21.2 .7 4.6 141 River Nile 23.4 1.4 6.1 224 Red Sea 23.5 3.1 4.8 145 Kassala 21.1 4.1 7.1 298 Gadarif 20.1 4.4 6.2 470 Khartoum 21.5 2.9 5.3 1,015 Gezira 21.5 2.5 5.4 1,257 White Nile 21.7 3.2 5.8 435 Sinnar 20.0 2.1 5.4 333 Blue Nile 20.1 3.1 6.7 422 North Kordofan 20.0 4.3 6.0 501 South Kordofan 21.7 2.6 5.8 302 West Kordofan 22.4 .7 5.3 499 North Darfur 20.5 4.8 6.2 682 West Darfur 20.9 4.5 7.0 276 South Darfur 20.7 2.5 6.7 823 Central Darfur 21.5 1.9 6.8 141 East Darfur 21.6 3.5 5.5 288 Area Urban 21.0 2.8 5.6 2,268 Rural 21.2 3.2 5.9 5,986 Mother's education None 21.4 2.7 6.6 3,358 Primary 20.8 3.2 5.8 2,971 Secondary 21.7 3.3 5.1 1,308 Higher 19.9 3.4 4.2 607 Wealth index quintile Poorest 21.0 3.4 6.7 1,794 Second 21.4 3.2 6.0 1,784 Middle 21.5 2.8 6.0 1,773 Fourth 21.1 2.8 5.7 1,608 Richest 20.9 3.2 4.5 1,295 Mean 21.0 3.8 6.4 8,254 [1] MICS indicator 2.11 - Duration of breastfeeding 56 The age-appropriateness of breastfeeding of children under age 24 months is provided in Table NU.6. Different criteria of feeding are used depending on the age of the child. For infants age 0-5 months, exclusive breastfeeding is considered as age-appropriate feeding, while children age 6-23 months are considered to be appropriately fed if they are receiving breastmilk and solid, semi-solid or soft food. Overall 66.0 percent of children age 6-23 months are being appropriately breastfed. Among children age 0-23 months, 63.1 percent are age-appropriate breastfeeding. There is disparity of appropriately breastfeeding practices of children aged 0-23 months by state: low level of practice is observed in Central (50.9 percent) andWest Darfur (51.2 percent), South Darfur (57.9 percent) and in West Kordofan (54.6 percent). Children from mothers of secondary or high education level and those living in richest households are the most appropriately breastfed in comparison to other groups. 57 Table NU.6: Age-appropriate breastfeeding Percentage of children age 0-23 months who were appropriately breastfed during the previous day, Sudan MICS, 2014 Background characteristics Children age 0-5 months Children age 6-23 months Children age 0-23 months Percent exclusively breastfed [1] Number of children Percent currently breastfeeding and receiving solid, semi- solid or soft foods Number of children Percent appropriately breastfed [2] Number of children Sudan 55.4 1,516 66.0 4,120 63.1 5,636 Sex Male 56.7 735 66.4 2,118 63.9 2,853 Female 54.3 781 65.4 2,002 62.3 2,782 State Northern (34.7) 21 83.0 74 72.4 95 River Nile 38.2 39 82.7 109 71.0 148 Red Sea (54.8) 17 69.2 72 66.4 89 Kassala 61.3 56 39.4 134 45.8 190 Gadarif 67.3 96 65.4 213 66.0 309 Khartoum 55.9 160 71.1 534 67.6 694 Gezira 50.0 226 70.9 689 65.8 915 White Nile 59.4 74 72.4 210 69.0 284 Sinnar 43.1 58 63.1 169 58.0 227 Blue Nile 54.9 70 68.3 218 65.1 288 North Kordofan 69.6 92 64.0 253 65.5 345 South Kordofan 51.3 56 65.7 132 61.4 189 West Kordofan 43.5 126 60.4 245 54.6 371 North Darfur 75.6 121 65.5 342 68.1 463 West Darfur 57.0 50 49.0 131 51.2 180 South Darfur 50.4 155 60.9 392 57.9 547 Central Darfur 44.5 34 54.1 67 50.9 101 East Darfur 60.3 65 65.0 136 63.5 202 Area 58 Background characteristics Children age 0-5 months Children age 6-23 months Children age 0-23 months Percent exclusively breastfed [1] Number of children Percent currently breastfeeding and receiving solid, semi- solid or soft foods Number of children Percent appropriately breastfed [2] Number of children Urban 53.1 399 68.7 1,104 64.6 1,503 Rural 56.3 1,117 64.9 3,016 62.6 4,133 Mother's education None 51.6 648 60.6 1,577 57.9 2,225 Primary 57.2 581 66.0 1,478 63.5 2,059 Secondary 61.3 193 74.9 734 72.1 927 Higher 59.2 92 72.0 329 69.2 421 Missing/DK * 1 * 1 * 2 Wealth index quintile Poorest 58.4 364 59.6 848 59.2 1,212 Second 55.9 350 62.7 876 60.7 1,225 Middle 52.4 332 66.2 867 62.4 1,199 Fourth 53.4 274 68.0 867 64.5 1,142 Richest 57.0 196 75.5 661 71.3 858 [1] MICS indicator 2.7 - Exclusive breastfeeding under 6 months [2] MICS indicator 2.12 - Age-appropriate breastfeeding ( ) Figures that are based on 25-49 unweighted cases [*] Based on less than 25 unweighted cases and has been suppressed. 59 Overall, 61.2 percent of infant’s age 6-8 months received solid, semi-solid, or soft foods at least once during the previous day (Table NU.7). Among currently breastfeeding infants this percentage is 61.1 percent while it is 63.4 percent among infants currently not breastfeeding. The practice of introduction of solid, semi-solid and soft foods to children aged of 6-8 months currently breastfeeding, varies by sex of children (62.4 percent for boys and 59.7 percent for girls) and by urban (67.9percent) and rural (58.9 percent). Table NU.7: Introduction of solid, semi-solid, or soft foods Percentage of infants age 6-8 months who received solid, semi-solid, or soft foods during the previous day, Sudan MICS, 2014 Background characteristics Currently breastfeeding Currently not breastfeeding All Percent receiving solid, semi-solid or soft foods Number of children age 6-8 months Percent receiving solid, semi-solid or soft foods Number of children age 6-8 months Percent receiving solid, semi-solid or soft foods [1] Number of children age 6-8 months Sudan 61.1 798 * 19 61.2 817 Sex Male 62.4 427 * 9 62.0 436 Female 59.7 371 * 10 60.2 381 Area Urban 67.9 192 * 5 68.1 198 Rural 58.9 605 * 14 59.0 619 [1] MICS indicator 2.13 - Introduction of solid, semi-solid or soft foods [*] Based on less than 25 unweighted cases and has been suppressed. Table NU.8 in next page indicates that more than one-fourth of the children age 6-23 months (40.7 percent) were receiving solid, semi-solid and soft foods the minimum number of times. There is no difference of practices for boys (40.7 percent) and girls (40.7 percent) in achieving the minimum meal frequency. The proportion of children receiving the minimum dietary diversity, or foods from at least 4 food groups (28.0 percent), was much lower than that for minimum meal frequency (40.7 percent), indicating the need to focus on improving diet quality and nutrient intake among this vulnerable group. A slightly higher proportion of older (18-23 month, old) children (37.2 percent) were achieving the minimum dietary diversity compared to younger (6-8 month old) children (9.2 percent). The overall assessment using the indicator of minimum acceptable diet revealed that only 15.1 percent of children were benefitting from a diet sufficient in both diversity and frequency. A very few percentage of children are benefiting from a diet sufficient in both diversity and frequency in the states of Kassala (3.4 percent), South Darfur (6.0 percent), North Darfur (6.6 percent), Central Darfur (6.9 percent) and North Kordofan (9.0 percent). These figures unfavourably compare to the high percentages of diet sufficiency in both diversity and frequency in Northern (48.4 percent), River Nile (29.4 percent) and Sinnar (21.5 percent) states. Children from uneducated mothers/caretakers are less covered (10.8 percent) than children from higher educated mothers (30.1 percent). Children of poorest household are less benefiting from a diet sufficient in both diversity and frequency (6.4 percent) in comparison to children living in richest household conditions (29.6 percent). 60 Table NU.8: Infant and young child feeding (IYCF) practices Percentage of children age 6-23 months who received appropriate liquids and solid, semi-solid, or soft foods the minimum number of times or more during the previous day, by breastfeeding status, Sudan MICS, 2014 Background characteristics Currently breastfeeding Currently not breastfeeding All Percent of children who received: Number of children age 6-23 months Percent of children who received: Number of children age 6-23 months Percent of children who received: Number of children age 6-23 months Minimum dietary diversity [a] Minimum meal frequency [b] Minimum acceptable diet [1], [c] Minimum dietary diversity [a] Minimum meal frequency [b] Minimum acceptable diet [2], [c] At least 2 milk feeds [3] Minimum dietary diversity [4], [a] Minimum meal frequency [5], [b] Minimum acceptable diet [c] Sudan 25.0 37.0 15.0 3,325 42.0 57.7 15.3 57.5 718 28.0 40.7 15.1 4,120 Sex Male 25.2 36.9 15.2 1,722 42.7 59.3 15.8 58.6 353 28.1 40.7 15.3 2,118 Female 24.9 37.1 14.8 1,603 41.3 56.1 14.7 56.5 365 27.9 40.7 14.8 2,002 Age 6-8 months 8.9 38.8 6.6 798 * * * * 12 9.2 38.7 6.6 817 9-11 months 25.8 34.5 15.1 589 (38.2) (48.3) (13.3) (46.3) 36 26.3 35.3 15.0 631 12-17 months 31.6 37.3 18.1 1,271 33.0 61.1 12.6 64.7 190 31.8 40.4 17.4 1,486 18-23 months 31.2 36.5 19.1 667 46.1 57.8 16.7 56.1 480 37.2 45.4 18.1 1,186 State Northern 63.3 72.8 49.8 62 (76.1) (72.2) (41.1) (56.7) 12 65.4 72.7 48.4 74 River Nile 41.5 52.1 27.8 100 * * * * 9 44.5 52.8 29.4 109 Red Sea 36.1 27.1 12.8 64 * * * * 8 36.7 30.3 13.2 72 Kassala 5.4 12.4 .3 100 (30.4) (52.1) (14.5) (72.6) 28 11.6 21.0 3.4 134 Gadarif 29.2 40.2 20.0 166 (43.7) (57.2) (19.6) (58.8) 45 32.3 43.9 19.9 213 Khartoum 39.9 26.4 12.1 435 (65.7) (51.1) (20.3) (69.2) 88 44.0 30.6 13.5 534 Gezira 23.5 50.1 19.4 559 (45.7) (68.2) (11.8) (51.8) 117 27.7 53.2 18.1 689 White Nile 31.3 39.0 19.4 178 (60.7) (72.6) (23.6) (79.0) 29 36.0 43.8 20.0 210 Sinnar 26.5 50.8 24.3 133 43.1 68.1 10.2 50.5 33 29.8 54.2 21.5 169 Blue Nile 34.4 43.6 22.3 176 71.0 61.5 21.4 59.0 41 41.7 47.0 22.1 218 61 Background characteristics Currently breastfeeding Currently not breastfeeding All Percent of children who received: Number of children age 6-23 months Percent of children who received: Number of children age 6-23 months Percent of children who received: Number of children age 6-23 months Minimum dietary diversity [a] Minimum meal frequency [b] Minimum acceptable diet [1], [c] Minimum dietary diversity [a] Minimum meal frequency [b] Minimum acceptable diet [2], [c] At least 2 milk feeds [3] Minimum dietary diversity [4], [a] Minimum meal frequency [5], [b] Minimum acceptable diet [c] North Kordofan 16.1 37.7 10.4 201 (24.1) (37.3) (2.4) (37.1) 42 17.8 37.6 9.0 253 South Kordofan 21.4 40.5 13.6 109 34.6 59.2 15.3 42.9 22 23.5 43.6 13.9 132 West Kordofan 27.9 37.0 20.6 197 (21.0) (52.6) (12.6) (69.8) 42 26.1 39.8 19.2 245 North Darfur 7.4 30.5 6.1 266 15.0 47.4 8.5 40.4 69 8.8 34.0 6.6 342 West Darfur 22.0 25.3 12.3 107 59.3 (55.6) (25.9) (64.6) 23 28.4 30.7 14.7 131 South Darfur 13.8 22.1 4.3 309 28.0 61.5 13.2 65.2 75 16.5 29.8 6.0 392 Central Darfur 11.9 29.7 5.7 52 (25.7) (30.4) (13.2) (34.8) 10 13.8 29.8 6.9 67 East Darfur 14.1 38.8 9.0 112 (27.7) (65.8) (11.0) (47.7) 23 16.3 43.5 9.3 136 Area Urban 36.1 34.9 16.5 877 58.8 59.4 26.7 65.0 201 40.1 39.5 18.4 1,104 Rural 21.1 37.8 14.5 2,448 35.5 57.0 10.8 54.6 517 23.6 41.1 13.9 3,016 Mother's education None 16.2 31.3 10.7 1,276 27.1 55.2 11.4 57.8 271 18.4 35.5 10.8 1,577 Primary 20.4 37.5 11.0 1,186 41.3 57.4 14.7 50.0 266 24.1 41.2 11.7 1,478 Secondary 42.2 44.0 24.8 608 65.7 60.4 21.6 67.2 114 45.2 46.6 24.3 734 Higher 49.9 46.4 32.0 254 (65.7) (64.5) (22.6) (69.4) 66 53.2 50.2 30.1 329 Missing/DK * * * 0 * * * * 1 * * * 1 Wealth index quintile Poorest 10.7 28.8 6.6 680 12.4 55.5 5.4 57.3 154 11.0 33.8 6.4 848 Second 17.4 31.6 11.5 712 27.5 46.5 9.3 48.3 144 18.9 34.1 11.1 876 Middle 23.2 40.3 13.9 703 49.6 56.0 16.1 57.4 153 28.2 43.1 14.3 867 Fourth 27.6 41.3 17.2 688 52.2 68.1 17.8 58.3 159 32.3 46.3 17.3 867 62 Background characteristics Currently breastfeeding Currently not breastfeeding All Percent of children who received: Number of children age 6-23 months Percent of children who received: Number of children age 6-23 months Percent of children who received: Number of children age 6-23 months Minimum dietary diversity [a] Minimum meal frequency [b] Minimum acceptable diet [1], [c] Minimum dietary diversity [a] Minimum meal frequency [b] Minimum acceptable diet [2], [c] At least 2 milk feeds [3] Minimum dietary diversity [4], [a] Minimum meal frequency [5], [b] Minimum acceptable diet [c] Richest 52.1 44.8 29.0 541 78.3 63.0 32.6 69.4 107 56.1 47.8 29.6 661 [1] MICS indicator 2.17a - Minimum acceptable diet (breastfed) [2] MICS indicator 2.17b - Minimum acceptable diet (non-breastfed) [3] MICS indicator 2.14 - Milk feeding frequency for non-breastfed children [4] MICS indicator 2.16 - Minimum dietary diversity [5] MICS indicator 2.15 - Minimum meal frequency [a] Minimum dietary diversity is defined as receiving foods from at least 4 of 7 food groups: 1) Grains, roots and tubers, 2) legumes and nuts, 3) dairy products (milk, yogurt, cheese), 4) flesh foods (meat, fish, poultry and liver/organ meats), 5) eggs, 6) vitamin-A rich fruits and vegetables, and 7) other fruits and vegetables [b] Minimum meal frequency among currently breastfeeding children is defined as children who also received solid, semi-solid, or soft foods 2 times or more daily for children age 6-8 months and 3 times or more daily for children age 9-23 months. For non-breastfeeding children age 6-23 months it is defined as receiving solid, semi-solid or soft foods, or milk feeds, at least 4 times [c] The minimum acceptable diet for breastfed children age 6-23 months is defined as receiving the minimum dietary diversity and the minimum meal frequency, while it for non-breastfed children further requires at least 2 milk feedings and that the minimum dietary diversity is achieved without counting milk feeds ( ) Figures that are based on 25-49 unweighted cases [*] Based on less than 25 unweighted cases and has been suppressed. 63 The continued practice of bottle-feeding is a concern because of the possible contamination due to unsafe water and lack of appropriate hygiene practices during preparation. Table NU.9 shows that 7.3 percent of infants Sudan are bottle fed. About 7.4 percent of children under 6 months are fed using a bottle with a nipple. Bottle-feeding of children is very prevalent in Red Sea (20.7 percent), Northern (16.7 percent) and Central Darfur (16.2 percent) states of Sudan. This practice is more common in urban areas, among richest households and in households with higher educated mothers. Table NU.9: Bottle feeding Percentage of children age 0-23 months who were fed with a bottle with a nipple during the previous day, Sudan MICS, 2014 Background characteristics Percentage of children age 0-23 months fed with a bottle with a nipple [1] Number of children age 0-23 months: Sudan 7.3 5,636 Sex Male 6.9 2,853 Female 7.8 2,782 Age 0-5 months 7.4 1,516 6-11 months 9.0 1,448 12-23 months 6.4 2,672 State Northern 16.7 95 River Nile 10.3 148 Red Sea 20.7 89 Kassala 14.5 190 Gadarif 4.7 309 Khartoum 13.8 694 Gezira 5.9 915 White Nile 8.6 284 Sinnar 5.6 227 Blue Nile 1.6 288 North Kordofan 4.4 345 South Kordofan 7.4 189 West Kordofan 5.6 371 North Darfur 2.6 463 West Darfur 8.1 180 South Darfur 5.0 547 Central Darfur 16.2 101 East Darfur 5.1 202 Area Urban 10.6 1,503 Rural 6.2 4,133 Mother's education 6.0 2,225 None 5.3 2,059 Primary 9.7 927 Secondary 19.0 421 64 Background characteristics Percentage of children age 0-23 months fed with a bottle with a nipple [1] Number of children age 0-23 months: Higher * 2 Wealth index quintile Poorest 4.0 1,212 Second 5.8 1,225 Middle 5.5 1,199 Fourth 8.3 1,142 Richest 15.7 858 [1] MICS indicator 2.18 - Bottle feeding [*] Based on less than 25 unweighted cases and has been suppressed. 5.4 Salt Iodization Iodine Deficiency Disorders (IDD) is the world’s leading cause of preventable mental retardation and impaired psychomotor development in young children. In its most extreme form, iodine deficiency causes cretinism. It also increases the risks of stillbirth and miscarriage in pregnant women. Iodine deficiency is most commonly and visibly associated with goitre. IDD takes its greatest toll in impaired mental growth and development, contributing in turn to poor school performance, reduced intellectual ability, and impaired work performance. The indicator is the percentage of households consuming adequately iodized salt (>15 parts per million). National laws required to support key nutrition interventions such as food fortification, salt iodisation and the breast milk substitute code are absent or are not been enforced. During 2014 MICS field data collection, salt used for cooking was tested for iodine content by using salt test kits and testing for the presence of indicate whether salt was tested for potassium iodide or potassium iodate content or both. Table NU.10 shows that cooking salt was tested in 93.9 percent of households surveyed. The table also shows that in 4.8 percent of households, there was no salt available. These households are included in the denominator of the indicator. As a result of absence of national law, in Sudan, only 7.6 percent of households have adequately iodized salt (which contains 15 parts per million ppm or more of iodine). Use of adequately iodized salt is lowest in States of West Kordofan (2.9 percent), Blue Nile (3.1 percent), Red Sea (3.2 percent) and Khartoum (3.3 percent) and relatively highest use in recorded in East Darfur (18.1 percent), Central Darfur (14.8 percent) and Sinnar (15.6 percent). Disparity is very low between Urban (9.0 percent) and rural area (7.0 percent). There is no difference of iodized salt consumption between the richest (8.8 percent) and poorest households (8.1 percent). Figure NU.5 below presents the percentage of adequately iodized salt and also salt containing less 15 ppm. 65 Figure NU.5: Consumption of iodized salt: Percentage of households consuming adequately iodized salt, Sudan MICS, 2014 55 42 33 35 41 29 32 25 23 28 20 24 18 22 17 19 17 14 34 35 32 36 33 36 35 34 70 54 51 45 44 44 43 36 35 32 29 27 27 26 24 23 22 17 9 7 8 8 7 7 9 8 10 30 50 70 90 110 130 P er c en t 15+ PPM of iodine Any iodine 66 Table NU.10: Iodized salt consumption Percent distribution of households by consumption of iodized salt, Sudan MICS, 2014 Background characteristics Percent of households in which salt was tested Number of households Percent of households with salt test result Number of households in which salt was tested or with no salt Percent of households with no salt Not iodized 0 PPM >0 and <15 PPM 15+ PPM [1] Sudan 93.9 16,801 4.8 60.7 26.8 7.6 16,574 State Northern 96.5 423 1.1 72.6 22.3 4.0 413 River Nile 98.6 666 0.9 56.0 31.5 11.5 663 Red Sea 94.6 519 3.3 79.4 14.1 3.2 508 Kassala 94.6 722 5.2 50.2 34.6 10.0 721 Gadarif 92.7 858 6.0 39.6 42.3 12.2 847 Khartoum 95.5 2,317 2.5 74.8 19.4 3.3 2,270 Gezira 96.3 2,629 3.6 63.9 27.6 4.8 2,626 White Nile 93.7 874 5.8 72.3 17.1 4.9 869 Sinnar 91.4 661 7.7 22.1 54.6 15.6 654 Blue Nile 93.4 656 6.4 66.5 24.0 3.1 654 North Kordofan 93.6 1,125 2.8 70.5 17.7 9.0 1,084 South Kordofan 94.9 462 3.5 67.2 20.2 9.1 455 West Kordofan 94.2 1,003 4.5 51.5 41.2 2.9 990 North Darfur 90.6 1,243 6.7 57.7 25.2 10.4 1,208 West Darfur 95.6 553 2.9 73.2 17.3 6.6 545 South Darfur 88.7 1,282 10.8 54.1 23.2 11.9 1,274 Central Darfur 92.5 299 5.2 51.3 28.8 14.8 292 East Darfur 89.2 508 9.8 39.5 32.6 18.1 502 Area Urban 94.9 5,000 3.6 62.8 24.6 9.0 4,921 Rural 93.5 11,801 5.4 59.9 27.7 7.0 11,652 Wealth index quintile Poorest 90.7 3,368 7.7 60.0 24.1 8.1 3,310 Second 92.2 3,592 6.2 57.5 28.3 8.0 3,534 Middle 93.2 3,339 5.5 61.2 26.6 6.7 3,293 Fourth 95.7 3,209 3.5 61.0 29.1 6.5 3,181 Richest 97.8 3,293 1.1 64.3 25.8 8.8 3,256 [1] MICS indicator 2.18 - Bottle feeding 67 5.5 Children’s Vitamin A supplementation Tables Nu.11 and Figure NU.6 below show that 78. percent of children in Sudan have received the Vitamin A during the last 6 months preceding the survey. The coverage of Vitamin A varies by State, age of children, mother’s education and wealth index quintile. Table NU.11: Children's vitamin A supplementation Percent distribution of children age 6-59 months by receipt of a high dose vitamin A supplement in the last 6 months, Sudan MICS, 2014 Background characteristics Percentage of children who received Vitamin A during the last 6 months [1] Number of children age 6-59 months Sudan 78.1 12,565 Child’s Sex Male 78.5 6,422 Female 77.6 6,143 State Northern 83.2 215 River Nile 85.2 355 Red Sea 79.0 226 Kassala 74.3 442 Gadarif 82.3 668 Khartoum 87.1 1,576 Gezira 83.3 1,924 White Nile 83.5 636 Sinnar 83.6 497 Blue Nile 83.2 621 North Kordofan 73.6 816 South Kordofan 79.1 472 West Kordofan 55.1 767 North Darfur 81.0 1,090 West Darfur 81.2 438 South Darfur 68.4 1,171 Central Darfur 58.1 220 East Darfur 62.0 430 Area Urban 84.5 3,463 Rural 75.6 9,102 Child’s age in month 6-11 30.0 1,448 12-23 78.4 2,672 24-35 85.8 2,618 36-47 85.8 3,268 48-59 87.1 2,559 Mother's education None 73.8 5,346 Primary 80.0 4,355 Secondary 82.6 1,959 Higher 83.9 890 Wealth index quintile Poorest 67.7 2,824 68 Background characteristics Percentage of children who received Vitamin A during the last 6 months [1] Number of children age 6-59 months Second 74.6 2,666 Middle 81.4 2,624 Fourth 84.7 2,410 Richest 84.8 2,042 Figure NU.6. Percentage of children who received Vitamin A during the last 6 months in Sudan MICS, 2014 55.1 58.1 62 68.4 73.6 74.3 78.1 79 79.1 81 81.2 82.3 83.2 83.2 83.3 83.5 83.6 85.2 87.1 0 10 20 30 40 50 60 70 80 90 100 West Kordofan Central Darfor East Darfor South Darfor North Kordofan Kassala Sudan Red Sea South Kordofan North Darfor West Darfor Gadarif Northern Blue Nile Gezira White Nile Sinnar River Nile Khartoum 69 VI. Child Health 6.1 Vaccinations Providing a safe and healthy start in life for all children and avoiding child deaths due to preventable diseases are critical to the task of reducing infant and under-five mortality rates. Immunization plays a key part towards achieving the goal of reducing infant and under-five mortality rates. The Millennium Development Goal (MDG) 4 is to reduce child mortality by two thirds between 1990 and 2015.In addition, the Global Vaccine Action Plan (GVAP) was endorsed by the 194 Member States of the World Health Assembly in May 2012 to achieve the Decade of Vaccines vision by delivering universal access to immunization. Immunization has saved the lives of millions of children in the four decades since the launch of the Expanded Programme on Immunization (EPI) in 1974. Worldwide there are still millions of children not reached by routine immunization and as a result, vaccine- preventable diseases account for more than 2 million child deaths every year. The WHO Recommended Routine Immunizations for Children18 recommends all children to be vaccinated against tuberculosis, diphtheria, pertussis, tetanus, polio, measles, hepatitis B, haemophilus influenza type b, pneumonia/meningitis, rotavirus, and rubella. All doses in the primary series are recommended to be completed before the child’s first birthday, although depending on the epidemiology of disease in a country, the first doses of measles and rubella containing vaccines may be recommended at 12 months or later. The recommended number and timing of most other doses also vary slightly with local epidemiology and may include booster doses later in childhood. The vaccination schedule followed by the Sudan National Immunization Programme provides all the above mentioned vaccinations with birth doses of BCG, Polio, and Hepatitis B vaccines (within 24 hours of birth), three doses of the Pentavalent vaccine containing DPT, Hepatitis B, and Haemophilus influenza type b (Hib) antigens, three doses of Polio vaccine, and measles. All vaccinations should be received during the first year of life. Taking into consideration this vaccination schedule, the estimates for full immunization coverage from the Sudan MICS 2014 are based on children aged 12-23/24-35 months. 18http://www.who.int/immunization/diseases/en.Table 2 includes recommendations for all children and additional antigens recommended only for children residing in certain regions of the world or living in certain high-risk population groups. 70 Vaccination Schedule for Sudan as of 2014 Age Vaccination Type Birth/First contact BCG International 6 weeks OPV1, Pentavalent1 , Oral drops, IM right, IM left, Thigh, oral drops 10 weeks OPV2, Pentavalent2 Oral drops, IM right, IM left, Thigh, oral drops 14 weeks OPV3, Pentavalent3 Oral drops, IM right, IM left, Thigh 9 months Measles Subcutaneously 18 months OPV Booster, DPT booster Oral Drops, IM right Thigh Information on vaccination coverage was collected for all children under three years of age. All mothers or caretakers were asked to provide vaccination cards. If the vaccination card for a child was available, interviewers copied vaccination information from the cards onto the MICS questionnaire. If no vaccination card was available for the child, the interviewer proceeded to ask the mother to recall whether or not the child had received each of the vaccinations, and for Polio, DPT and Hepatitis B, how many doses were received. Information was also obtained from vaccination records at health facilities. The final vaccination coverage estimates are based on information obtained from the vaccination card and the mother’s report of vaccinations received by the child. The percentage of children age 12-23 months and 24-35 months who have received each of the specific vaccinations by source of information (vaccination card or vaccination records at health facilities and mother’s recall) is shown in Table CH.1 above and Figure CH.1 below. The denominators for the table are comprised of children age 12-23 months and 24-35 months so that only children who are old enough to be fully vaccinated are counted. In the first three columns in each panel of the table, the numerator includes all children who were vaccinated at any time before the survey according to the vaccination card or the vaccination records at health facilities or the mother’s report. In the last column in each panel, only those children who were vaccinated before their first birthday, as recommended, are included. For children without vaccination cards/records, the proportion of vaccinations given before the first birthday is assumed to be the same as for children with vaccination cards/records. 71 Table CH.1: Vaccinations in the first years of life Percentage of children age 12-23 months and 24-35 months vaccinated against vaccine preventable childhood diseases at any time before the survey and by their first birthday, Sudan MICS, 2014 Background characteristics Children Age 12-23 months: Children Age 24-35 months: Vaccinated at any time feore the survey according to: Vaccinated by 12 months of agea Vaccinated at any time feore the survey according to: Vaccinated by 12 months of agea Child health card Mother's report Either Child health card Mother's report Either BCG [1] 43.7 41.6 85.3 78.5 27.3 56.7 84.0 72.1 Polio 0 42.2 45.3 87.4 30.4 26.4 60.1 86.4 29.7 Polio 1 43.8 43.7 87.5 83.7 27.4 59.1 86.5 80.2 Polio 2 43.5 38.6 82 75.7 27.4 54.0 81.3 73.0 Polio 3 [2] 42.9 32.2 75.1 65.3 27.3 45.0 72.3 59.3 Pentavalent 1 44.2 40.4 84.6 81.1 27.7 56.1 83.8 76.7 Pentavalent 2 43.9 36.7 80.6 74.5 27.6 51.9 79.5 70.7 Pentavalent 3 [3][4][5] 43.4 30.5 73.9 63.9 27.4 43.6 71.0 58.1 Measles 1 [7] 41.7 38.2 79.9 60.9 26.9 53.9 80.8 58.9 Measles 2 36.6 39 75.6 8.8 25.2 54.6 79.8 8.3 Fully vaccinatedb [8] 42.2 25.3 67.5 42.8 26.3 36.4 62.7 23.1 No vaccinations .0 11.8 11.8 12.8 .0 12.6 12.6 14.9 Number of children 2,672 2,672 2,672 2,672 2,618 2,618 2,618 2,618 [1] MICS indicator 3.1 - Tuberculosis immunization coverage [2] MICS indicator 3.2 - Polio immunization coverage [3] MICS indicator 3.3 - Diphtheria, pertussis and tetanus (DPT) immunization coverage [4] MICS indicator 3.5 - Hepatitis B immunization coverage [5] MICS indicator 3.6 - Haemophilus influenzae type B (Hib) immunization coverage [7] MICS indicator 3.4; MDG indicator 4.3 - Measles immunization coverage [8] MICS indicator 3.8 - Full immunization coverage [a] MICS indicators 3.1, 3.2, 3.3, 3.5, 3.6, and 3.7 refer to results of this column in the left panel; MICS indicators 3.4 and 3.8 refer to this column in the right panel [b] Includes: BCG, Polio3, Pentavalent3 and Measles 1 (MCV1) as per the vaccination schedule in Sudan Approximately 78.5 percent of children age 12-23 months received a BCG vaccination by the age of 12 months and the first dose of Pentavalent vaccine was given to 81.1 percent. The percentage declines to 74.5 percent for the second dose of Pentavalent, and 63.9 percent for the third dose. Similarly, 83.7 percent of children received Polio 1 by age 12 months and this declines to 65.3 percent by the third dose. The coverage for the first dose of measles vaccine by 12-23 months is lower than for the other vaccines at 60.9 percent. Overall, the percentage of children who had all the recommended vaccinations by their first birthday is low at only 42.8 percent. 72 F i g u r e C H . 1 : V a c c i n a t i o n s b y a g e 1 2 m o n t h s , S u d a n M I C S , 2 0 1 4 Table CH.2 presents vaccination coverage estimates among children age 12-23 and 24-35 months by background characteristics. The figures indicate children receiving the vaccinations at any time up to the date of the survey, and are based on information from both the vaccination cards or health facility records and mothers’/caretakers’ reports. Vaccination cards have been seen by the interviewer for only 43.7 percent of children age 12-23 months. The survey data indicated that 85.3 percent of children age 12-23 months had received BCG vaccination at any time up to the date of the survey. There was only a slight difference in BCG vaccination coverage rate by gender, the BCG vaccination coverage for males and females respectively being 83.7 percent and 86.9 percent. The BCG vaccination coverage was higher for children in urban areas (92.0 percent) than among children in rural areas (82.8 percent). The BCG vaccination coverage rate, as expected, seems to have a close link with the level of mothers’ education. The BCG vaccination coverage ranged from 76.6 percent for children of mothers with no education to 88.9 percent for children of mothers with primary education, and to 94.1 percent for children of mothers with secondary or and 92.5 percent of mothers with higher education. The BCG vaccination coverage rate also has a high association with the economic status of the household. The BCG vaccination coverage was 68.0 percent in the case of children belonging to households in the poorest quintile compared to 94.6 percent for children from households in the richest quintile. The BCG vaccination coverage rate ranged from 64.5 percent in South Darfur to 97.4 percent in Blue Nile State. The vaccination coverage rate was more than 80 percent in eleven states and below 80 percent in seven states. 79 30 84 76 65 81 75 64 61 43 13 BCG Polio at birth Polio1 Polio2 Polio3 Pentavalent 1 Pentavalent 2 Pentavalent 3 Measles Fully vaccinated No vaccinations Per cent Children Age 12-23 months 72 30 80 73 59 77 71 58 59 63 15 BCG Polio at birth Polio1 Polio2 Polio3 Pentavalent 1 Pentavalent 2 Pentavalent 3 Measles Fully vaccinated No vaccinations Children Age 24-35 months 73 Figure CH.1a: Measles Vaccination Coverage by States Percentage of children age 24-35 months currently vaccinated against Measles, Sudan MICS, 2014 58.9 67.3 67.5 67.5 72.1 73.0 74.5 75.2 77.8 80.8 83.4 86.4 87.4 89.1 89.7 90.6 95.5 96.7 97.1 .0 20.0 40.0 60.0 80.0 100.0 120.0 South Darfor Red Sea North Darfor West Kordofan East Darfor Kassala North Kordofan South Kordofan Central Darfor Sudan West Darfor Gadarif Sinnar White Nile Khartoum Blue Nile River Nile Gezira Northern 74 Table CH.2: Vaccinations by background characteristics Percentage of children age 12-23 months and 24-35 months currently vaccinated against vaccine preventable childhood diseases, Sudan MICS, 2014 Background characteristics Percentage of children age 12-23 months who received: Percentwit h vaccinatio n card seen Numbe r of childre n age 12-23 month s Percentage of children age 24- 35 months who received: With Card BCG Polio 0 Polio 1 Polio 2 Polio 3 Pentavale nt 1 Pentavale nt 2 Pentavale nt 3 Measles 1 Measles 2 Full [a] Percentwit h vaccinatio n card seen Numb er of childre n age 24-35 month s Sudan 85.3 87.4 87.5 82.0 75.1 84.6 80.6 73.9 43.7 2,672 80.8 79.8 62.7 27.3 2,618 Sex Male 83.7 86.3 86.5 81.3 74.0 84.0 79.9 72.6 42.4 1,337 79.2 77.7 60.4 26.7 1,347 Female 86.9 88.5 88.5 82.8 76.2 85.1 81.2 75.2 44.9 1,335 82.5 82.1 65.2 27.9 1,272 State Northern 93.3 96.2 96.2 94.6 90.9 94.5 94.0 89.6 50.0 48 97.1 96.0 87.2 44.2 47 River Nile 92.8 93.4 93.4 90.6 82.2 92.8 91.3 88.5 39.6 74 95.5 95.5 86.5 20.5 76 Red Sea 65.7 71.3 71.3 65.2 60.2 62.5 62.5 53.3 22.5 46 67.3 67.3 42.0 15.2 56 Kassala 78.4 79.8 79.8 71.0 64.0 77.6 67.9 62.8 38.6 93 73.0 73.0 56.6 22.3 108 Gadarif 94.4 95.3 95.3 92.8 87.5 95.2 93.7 87.2 43.5 132 86.4 85.8 66.7 21.2 161 Khartoum 95.4 96.0 96.0 92.3 89.7 94.5 92.4 89.9 52.1 364 89.7 88.6 74.1 31.6 320 Gezira 94.8 96.4 96.4 91.6 88.8 95.7 93.5 91.4 55.2 430 96.7 94.0 85.8 39.7 342 White Nile 89.9 93.6 93.6 87.4 77.2 91.2 87.1 79.6 37.1 131 89.1 88.3 67.0 24.2 151 Sinnar 80.2 82.2 82.2 75.8 68.6 79.8 73.1 60.7 42.6 102 87.4 86.6 63.9 38.3 105 Blue Nile 97.4 98.3 98.3 98.0 95.0 97.7 97.4 96.1 72.6 148 90.6 90.3 86.2 46.1 135 North Kordofan 82.9 83.6 85.1 78.5 74.9 81.6 78.5 73.5 38.4 157 74.5 74.5 54.7 24.5 156 South Kordofan 77.3 82.3 82.3 79.0 70.2 80.3 75.4 69.0 46.4 85 75.2 75.2 48.4 16.2 113 West Kordofan 72.2 74.4 74.4 63.4 49.8 66.6 59.5 46.5 11.3 156 67.5 66.8 39.1 8.3 129 North Darfur 81.6 83.1 83.1 79.8 71.3 80.4 76.8 67.3 47.3 223 67.5 67.0 52.5 27.7 219 75 Background characteristics Percentage of children age 12-23 months who received: Percentwit h vaccinatio n card seen Numbe r of childre n age 12-23 month s Percentage of children age 24- 35 months who received: With Card BCG Polio 0 Polio 1 Polio 2 Polio 3 Pentavale nt 1 Pentavale nt 2 Pentavale nt 3 Measles 1 Measles 2 Full [a] Percentwit h vaccinatio n card seen Numb er of childre n age 24-35 month s West Darfur 90.9 96.1 96.1 83.2 70.2 87.1 83.3 68.6 26.2 76 83.4 83.4 53.9 15.4 96 South Darfur 64.5 67.7 68.2 61.1 49.5 63.4 54.9 42.9 29.3 266 58.9 57.2 41.7 20.7 276 Central Darfur 75.9 74.9 74.2 66.3 51.5 71.3 61.5 49.1 43.1 51 (77.8) (76.8) (44.6) (37.9) 40 East Darfur 77.6 86.2 86.2 74.8 60.2 74.4 67.6 57.7 44.9 91 72.1 69.8 38.6 22.2 87 Area Urban 92.0 93.4 93.4 89.1 82.9 91.3 88.4 82.1 47.2 726 86.7 85.4 68.5 34.6 766 Rural 82.8 85.2 85.3 79.4 72.2 82.0 77.6 70.8 42.3 1,946 78.4 77.5 60.3 24.2 1,853 Mother's education None 76.6 80.2 80.6 73.8 64.9 76.0 70.8 63.2 38.1 1,049 72.3 71.1 53.1 21.5 1,132 Primary 88.9 90.6 90.6 85.1 78.5 87.6 84.0 77.6 46.1 929 86.8 86.0 68.7 34.5 912 Secondary 94.1 95.0 95.0 92.4 87.2 93.7 91.7 85.9 50.2 481 87.1 86.2 69.0 28.8 381 Higher 92.5 92.1 92.1 86.2 83.1 92.3 88.0 82.9 45.8 211 92.7 91.5 80.0 24.9 186 Wealth index quintile Poorest 68.0 72.8 73.5 64.5 53.8 66.9 59.3 50.3 29.6 536 61.6 61.0 43.5 17.2 583 Second 79.8 82.4 82.4 76.4 67.0 78.4 73.4 63.2 37.1 591 77.4 76.7 51.5 19.9 558 Middle 91.6 93.3 93.3 88.2 82.5 90.9 87.9 83.1 50.7 560 86.8 85.1 70.6 34.6 574 Fourth 94.0 94.4 94.4 90.5 85.5 93.3 90.9 86.7 49.8 553 90.9 90.5 76.1 31.3 466 Richest 94.6 95.4 95.4 92.3 89.2 94.8 93.3 88.7 53.0 432 91.5 90.0 76.9 36.1 437 [a] Includes: BCG, Polio3, Pentavalent3 and Measles (MCV1) as per the vaccination schedule in Sudan ( ) Figures that are based on 25-49 unweighted cases [*] Based on less than 25 unweighted cases and has been suppressed. 76 6.2 Neonatal Tetanus Protection MDG 5 aims to reduce by three quarters the maternal mortality ratio, with one of its strategies to eliminate maternal tetanus. Following on the 42nd and 44th World Health Assembly calling for elimination of neonatal tetanus, the global community continues to work to reduce the incidence of neonatal tetanus to less than 1 case of neonatal tetanus per 1,000 live births in every state by 2015. Prevention of maternal and neonatal tetanus can be ensured if all pregnant women receive at least two doses of tetanus toxoid vaccine. If a woman has received at least two doses of tetanus toxoid during a particular pregnancy, she (and her new born) are also considered to be protected against tetanus. Other conditions for neonatal Tetanus Protection are when the woman: x Received at least two doses of tetanus toxoid vaccine, the last within the previous 3 years; x Received at least 3 doses, the last within the previous 5 years; x Received at least 4 doses, the last within the previous 10 years; x Received 5 or more doses anytime during her life. 19 To assess the status of tetanus vaccination coverage, women who had a live birth during the two years before the survey were asked if they had received tetanus toxoid injections during the pregnancy and if so, they were asked for the number of such injections received. Women who did not receive two or more tetanus toxoid vaccinations during this recent pregnancy were then asked about tetanus toxoid vaccinations they may have previously received. Interviewers also asked the women to present their vaccination cards on which dates of tetanus toxoid are recorded and referred to information from the cards when available. Table CH.3 shows the status of women’s protection from tetanus among women aged 15-49 years who have had a live birth within the last 2 years prior to the survey. Overall, the table shows that 58.2 percent of the women with a live birth in the last two years were protected against neonatal tetanus. Also only 32.1 percent of the women received at least two doses of tetanus toxoid (TT) vaccine during last pregnancy. The data also showed a higher percentage of women aged 15-49 years in urban areas with a live birth in the last two years prior to the survey were protected against neonatal tetanus (65.9 percent) than their counterparts in rural areas (55.4 percent). However, there was only a marginal difference in the percentage of women who received at least two doses of tetanus toxoid (TT) vaccine during last pregnancy between those living in urban areas (32.7 percent) and those living in rural areas (31.8 percent). The data also shows that the level of education of woman in Sudan is highly related to the likelihood of neonatal tetanus protection. For instance, the percentage of women aged 15-49 years who were protected against neonatal tetanus was only 46.7 percent for women with no education, compared to 79.0 percent for women with secondary and higher levels of education. Similar differences were shown among women with varying economic status; percentage of neonatal tetanus protection among women in the richest quintile was 74.2 percent compared with the women from the poorest quintile (44.4 percent) 19 Deming, M.S. et al. 2002. Tetanus toxoid coverage as an indicator of serological protection against neonatal tetanus. Bulletin of the World Health Organization 80(9):696-703 77 Table CH.3: Neonatal tetanus protection Percentage of women age 15-49 years with a live birth in the last 2 years protected against neonatal tetanus, Sudan MICS, 2014 Background characteristics Percentage of women who received at least 2 doses during last pregnancy Percentage of women who did not receive two or more doses during last pregnancy but received: Protected against tetanus [1] Number of women with a live birth in the last 2 years 2 doses, the last within prior 3 years 3 doses, the last within prior 5 years 4 doses, the last within prior 10 years 5 or more doses during lifetime Sudan 32.1 19.3 3.8 2.3 .7 58.2 5,622 State Northern 41.9 15.0 1.6 .7 1.7 60.9 92 River Nile 42.1 25.7 3.0 2.1 .0 73.0 151 Red Sea 27.6 11.0 0.8 3.0 0.0 42.3 92 Kassala 27.5 9.8 2.2 .8 0.0 40.3 199 Gadarif 27.5 20.3 4.0 3.0 0.4 55.2 307 Khartoum 28.8 33.8 4.1 4.0 2.7 73.4 684 Gezira 36.5 18.0 5.5 2.6 0.7 63.4 852 White Nile 33.2 16.8 5.6 1.6 0.2 57.6 273 Sinnar 31.1 20.0 5.5 3.3 0.2 60.1 226 Blue Nile 31.7 12.4 2.2 4.4 0.3 50.9 287 North Kordofan 34.2 19.4 3.5 1.5 0.5 59.2 352 South Kordofan 32.3 21.7 4.2 1.4 0.0 59.6 194 West Kordofan 33.1 10.2 0.1 0.6 0.0 44.0 341 North Darfur 26.0 23.1 5.1 2.8 0.4 57.4 525 West Darfur 38.5 20.9 3.0 0.9 0.6 64.0 179 South Darfur 28.1 16.0 3.1 2.0 0.6 49.8 556 Central Darfur 51.1 7.7 1.2 0.0 0.0 60.0 99 East Darfur 31.7 13.8 4.5 1.1 0.2 51.3 211 Area Urban 32.7 23.3 3.9 4.4 1.6 65.9 1,488 Rural 31.8 17.9 3.7 1.6 0.3 55.4 4,134 Mother's education None 26.1 14.3 3.5 2.4 0.5 46.7 2,247 Primary 33.5 20.3 4.1 2.2 1.0 61.1 2,022 Secondary 38.8 23.9 4.0 2.7 0.8 70.3 942 Higher 42.5 30.9 3.4 2.1 0.1 79.0 410 Wealth index quintile Poorest 25.3 14.1 3.6 1.0 0.3 44.4 1,251 Second 31.5 17.5 2.7 1.8 0.2 53.7 1,232 Middle 35.2 16.4 3.0 1.7 0.6 56.8 1,192 Fourth 34.4 22.0 6.5 3.7 1.3 68.0 1,096 Richest 35.6 30.0 3.2 4.3 1.2 74.2 851 [1] MICS indicator 3.9 - Neonatal tetanus protection 78 6.3 Care of Illness A key strategy for accelerating progress toward MDG 4 is to tackle the diseases that are the leading killers of children under 5. Diarrhoea and pneumonia are two such diseases. The Global Action Plan for the Prevention and Control of Pneumonia and Diarrhoea (GAPPD) aims to end preventable pneumonia and diarrhoea death by reducing mortality from pneumonia to 3 deaths per 1000 live births and mortality from diarrhoea to 1 death per 1000 live births by 2025. Table CH.4 presents the percentage of children under 5 years of age who were reported to have had an episode of diarrhoea, and symptoms of acute respiratory infection (ARI). These results are not measures of true prevalence, and should not be used as such, but rather the period-prevalence of those illnesses over a two-week time window. The definition of a case of diarrhoea in this survey, was the mother’s (or caretaker’s) report that the child had such symptoms over the specified period; no other evidence were sought beside the opinion of the mother. A child was considered to have had an episode of ARI if the mother or caretaker reported that the child had, over the specified period, an illness with a cough with rapid or difficult breathing, and whose symptoms were perceived to be due to a problem in the chest or both a problem in the chest and a blocked nose. While this approach is reasonable in the context 0f a MICS survey, these basically simple case definitions must be kept in mind when interpreting the results, as well as the potential for reporting and recall biases. Further, diarrhoea, fever and ARI are not only seasonal but are also characterized by the often rapid spread of localized outbreaks from one area to another at different points in time. The timing of the survey and the location of the teams might thus considerably affect the results, which must consequently be interpreted with caution. For these reasons, although the period-prevalence over a two-week time window is reported, these data should not be used to assess the epidemiological characteristics of these diseases but rather to obtain denominators for the indicators related to use of health services and treatment. Overall, 29.0 percent of under five children were reported to have had diarrhoea in the two weeks preceding the survey, 17percent symptoms of ARI, (Table CH.4). Period-prevalence of diarrhoea ranges from 19.3 percent in the age group 48-59 months to 38.5 percent in the age group 12-23 months. In the case of ARI, the period prevalence ranges from 15.1 percent in the age group 0-11 months to 19.8 percent in the age group 24-35 months. There are minor differences in the prevalence of diarrhoea/ARI between urban and rural areas, and male and female populations. The prevalence of diarrhoea among children widely varies between states, ranging from the lowest in West Kordofan (7.6 percent) to the highest in Khartoum (42.7 percent). In the case of ARI, the prevalence ranges from the lowest in West Kordofan (5.0 percent) to the highest in North Darfur (30.8 percent). 79 Table CH.4: Reported disease episodes Percentage of children age 0-59 months for whom the mother/caretaker reported an episode of diarrhoea, and/or symptoms of acute respiratory infection (ARI) in the last two weeks, Sudan MICS, 2014 Background characteristics Percentage of children who in the last two weeks had: Number of children age 0-59 months An episode of diarrhoea Symptoms of ARI [a] Sudan 29.0 17.8 14,081 Sex Male 29.7 18.4 7,157 Female 28.3 17.1 6,924 State Northern 23.9 12.2 236 River Nile 22.5 11.2 393 Red Sea 9.6 5.9 244 Kassala 32.9 15.1 498 Gadarif 22.0 10.5 765 Khartoum 42.7 13.2 1,736 Gezira 34.8 16.8 2,149 White Nile 36.2 25.3 711 Sinnar 28.2 23.4 555 Blue Nile 20.3 12.9 691 North Kordofan 17.4 15.8 907 South Kordofan 25.0 24.3 529 West Kordofan 7.6 5.0 893 North Darfur 37.2 30.8 1,211 West Darfur 23.9 9.0 487 South Darfur 27.2 25.8 1,326 Central Darfur 31.1 14.9 254 East Darfur 35.9 31.1 495 Area Urban 31.5 17.5 3,862 Rural 28.1 17.8 10,219 Age 0-11 31.5 15.1 2,964 12-23 38.5 18.3 2,672 24-35 33.2 19.8 2,618 36-47 23.3 18.6 3,268 48-59 19.3 17.1 2,559 Mother's education None 27.0 17.6 5,994 Primary 30.9 18.4 4,936 Secondary 30.1 18.3 2,152 Higher 30.0 14.7 982 Missing/DK * * 17 Wealth index quintile Poorest 26.5 19.7 3,188 Second 24.9 19.2 3,015 Middle 28.2 18.8 2,956 Fourth 37.1 15.1 2,684 80 Background characteristics Percentage of children who in the last two weeks had: Number of children age 0-59 months An episode of diarrhoea Symptoms of ARI [a] Richest 29.6 14.8 2,238 [a] Children with symptoms of ARI are those who had an illness with a cough accompanied by a rapid or difficult breathing Sudan MICS did not include question on symptoms due to a problem in the chest, or both a problem in the chest and a blocked nose [*] Based on less than 25 unweighted cases and has been suppressed. 6.3.1 Diarrhoea Diarrhoea is a leading cause of death among children under five worldwide. Most diarrhoea-related deaths in children are due to dehydration from loss of large quantities of water and electrolytes from the body in liquid stools. Management of diarrhoea – either through oral rehydration salts (ORS) or a recommended home fluid (RHF) – can prevent many of these deaths. In addition, provision of zinc supplements has been shown to reduce the duration and severity of the illness as well as the risk of future episodes within the next two or three months. Preventing dehydration and malnutrition by increasing fluid intake and continuing to feed the child are also important strategies for managing diarrhoea. In the MICS 2014, mothers or caretakers were asked whether their child under age five years had an episode of diarrhoea in the two weeks prior to the survey. In cases where mothers reported that the child had diarrhoea, a series of questions were asked about the treatment of the illness, including what the child had been given to drink and eat during the episode and whether this was more or less than what was usually given to the child. The overall period-prevalence of diarrhoea in children under 5 years of age is 29.0 percent (Table CH.4) and ranges from 9.0 percent in West Darfur state to 42.7 percent in Khartoum state . The highest period-prevalence is seen among children age 12-23 months which grossly corresponds to the weaning period. Table CH.5 shows the percentage of children with diarrhoea in the two weeks preceding the survey for and from whom advice or treatment was sought. Overall, a health facility or provider was seen in 42.7 percent of the cases, and predominantly in the public sector at 37.3 percent and only 3.2 percent from a community health provider. Generally the proportion of those seeking advice is similar between male and female children; 42.7 percent for both sexes. There was significant difference between urban (46.1 percent) and rural (41.3 percent) respondents. Approximately 40.8 percent of children with diarrhoea in the last two weeks did not seek advice for treatment. There were notable differences between mothers’/caretakers’ education levels on seeking advice was observed in the data. 81 Table CH.5: Care-seeking during diarrhoea Percentage of children age 0-59 months with diarrhoea in the last two weeks for whom advice or treatment was sought, by source of advice or treatment, Sudan MICS, 2014 Background characteristics Percentage of children with diarrhoea for whom: Number of children age 0-59 months with diarrhoea in the last two weeks Advice or treatment was sought from: No advice or treatment sought Health facilities or providers Other source A health facility or provider [1] [b] Public Private Community health provider [a] Sudan 37.3 13.1 3.2 9.9 42.7 40.8 4,088 Sex Male 37.4 14.0 2.7 10.5 42.7 39.2 2,125 Female 37.3 12.1 3.6 9.3 42.7 42.5 1,963 State Northern 48.3 8.8 .7 10.6 53.6 33.6 56 River Nile 48.5 9.7 3.6 9.0 53.6 33.7 88 Red Sea (48.7) (9.4) (3.2) (17.2) (53.3) (26.6) 23 Kassala 55.5 4.1 2.7 3.8 57.5 36.6 164 Gadarif 44.8 15.3 3.1 5.5 52.8 36.2 168 Khartoum 39.2 18.4 .3 8.1 46.4 35.3 742 Gezira 36.6 12.7 6.0 5.5 43.8 45.2 749 White Nile 41.8 7.4 3.4 18.9 46.3 34.2 257 Sinnar 46.8 12.7 1.0 7.5 51.2 33.3 156 Blue Nile 46.1 11.1 0.0 14.6 46.5 29.8 141 North Kordofan 40.8 8.9 8.8 2.8 46.2 47.8 158 South Kordofan 35.7 5.4 1.7 8.6 36.6 51.0 132 West Kordofan 30.9 7.6 4.5 10.9 35.2 51.4 68 North Darfur 30.7 15.8 2.7 10.2 32.6 43.9 450 West Darfur 56.2 7.7 2.5 7.2 58.6 29.4 117 South Darfur 18.5 17.6 5.2 17.4 29.1 50.4 360 Central Darfur 38.7 6.1 2.1 20.8 40.1 36.4 79 East Darfur 19.6 14.5 2.0 19.3 22.2 49.9 178 Area Urban 38.4 18.2 .7 9.1 46.1 36.5 1,216 Rural 36.9 10.9 4.2 10.3 41.3 42.6 2,872 Age 0-11 37.6 10.4 1.9 5.3 42.1 47.3 933 12-23 40.6 15.0 4.0 10.7 48.4 35.5 1,028 24-35 36.2 13.1 3.7 10.2 42.0 42.0 870 36-47 31.3 14.1 3.2 11.7 35.4 42.9 763 48-59 41.5 12.6 2.7 14.0 44.5 34.2 494 Mother's education None 33.7 13.1 2.9 12.4 38.1 42.3 1,618 Primary 38.0 11.7 4.1 9.3 42.8 42.1 1,525 Secondary 47.4 13.8 2.8 6.7 53.8 32.7 648 Higher 32.1 18.6 .8 6.7 43.4 44.0 295 Missing/DK * * * * * * 2 Wealth index quintile 82 Background characteristics Percentage of children with diarrhoea for whom: Number of children age 0-59 months with diarrhoea in the last two weeks Advice or treatment was sought from: No advice or treatment sought Health facilities or providers Other source A health facility or provider [1] [b] Public Private Community health provider [a] Poorest 24.3 13.7 3.5 15.8 29.2 47.7 845 Second 39.2 10.8 5.0 9.0 42.5 41.8 750 Middle 46.7 10.9 2.6 10.1 50.8 34.0 834 Fourth 39.0 13.3 2.8 8.2 44.8 40.9 995 Richest 37.6 17.4 1.9 5.9 46.7 39.2 662 [1] MICS indicator 3.10 - Care-seeking for diarrhoea [a] Community health providers includes both public (Community health worker and Mobile/Outreach clinic) and private (Mobile clinic) health facilities [b] Includes all public and private health facilities and providers, but excludes private pharmacy [*] Based on less than 25 unweighted cases and has been suppressed. ( ) Figures that are based on 25-49 unweighted cases Table CH.6 provides statistics on drinking and feeding practices during diarrhoea. Only 19.0 percent of under five children with diarrhoea were given more than usual while 27.3 percent were given the same or less. About 26.7 percent were given somewhat less, same or more (continued feeding), but 18.4 percent were given much less or almost nothing. The proportion of female children who were given less to drink was 15.7 percent and 20.8 percent were given much less or somewhat less for males. The proportion of children under 5 years of age who had an episode of diarrhoea in the 2 weeks preceding the survey and who were given less to drink ranged from 18.7 percent in Central Darfur and Northern states to 37.6 percent in West Kordofan. The proportion of children under 5 years of age who had an episode of diarrhea in the 2 weeks preceding the survey who were given no food to eat was 18.2 percent in urban areas compared to 17.9 percent in rural areas; 18.3 percent for male children compared to 17.6 percent for female children; and 14.4 percent for children in the poorest quintile compared 16.3 percent for children in the richest quintile 83 Table CH.6: Feeding practices during diarrhoea Percent distribution of children age 0-59 months with diarrhoea in the last two weeks by amount of liquids and food given during episode of diarrhoea, Sudan MICS, 2014 Background characteristics Drinking practices during diarrhoea: Eating practices during diarrhoea: Number of children aged 0-59 months with diarrhoea Child was given to drink: Much less Child was given to drink: Somewhat less Child was given to drink: About the same Child was given to drink: More Child was given to drink: Nothing Missing/ DK Sudan Child was given to eat: Much less Child was given to eat: Somewhat less Child was given to eat: About the same Child was given to eat: More Child was given to eat: Nothing Missing/ DK Sudan Sudan 18.4 26.7 27.3 19.0 7.7 1.0 100.0 18.3 32.0 24.3 6.0 18.0 1.5 100.0 4,088 Sex Male 20.8 25.5 26.9 18.9 7.0 0.8 100.0 19.6 32.2 23.2 5.4 18.3 1.3 100.0 2,125 Female 15.7 27.9 27.7 19.1 8.3 1.2 100.0 16.9 31.7 25.5 6.7 17.6 1.7 100.0 1,963 State Northern 6.7 18.7 45.0 25.1 4.6 0.0 100.0 10.5 33.4 28.4 2.6 25.1 0.0 100.0 56 River Nile 10.9 21.1 28.5 30.0 9.6 0.0 100.0 6.8 29.0 23.1 11.4 29.6 0.0 100.0 88 Red Sea (10.9) (32.5) (17.0) (20.1) (19.5) (0.0) (100.0) (24.6) (28.3) (9.8) (9.1) (25.9) (2.3) (100.0) 23 Kassala 26.3 34.4 18.3 13.7 5.5 1.7 100.0 24.0 33.4 18.2 9.1 13.9 1.3 100.0 164 Gadarif 16.9 31.3 21.4 24.6 5.2 0.6 100.0 12.5 41.8 28.5 8.3 8.2 0.6 100.0 168 Khartoum 26.9 22.1 27.7 21.1 2.2 0.0 100.0 18.5 32.1 23.0 6.8 18.9 0.7 100.0 742 Gezira 8.9 33.8 25.1 16.7 15.0 0.6 100.0 12.0 33.8 22.4 4.1 26.9 0.8 100.0 749 White Nile 13.7 15.7 38.3 20.0 11.4 0.9 100.0 15.9 23.5 35.2 10.4 14.4 0.6 100.0 257 Sinnar 18.6 23.2 25.3 28.3 4.7 0.0 100.0 24.6 29.8 26.3 4.5 14.7 0.0 100.0 156 Blue Nile 22.9 26.2 21.8 21.5 7.6 0.0 100.0 21.8 29.1 28.0 7.7 12.9 0.5 100.0 141 North Kordofan 19.2 29.1 29.0 16.2 6.4 0.0 100.0 26.1 28.3 29.1 1.6 14.9 0.0 100.0 158 South Kordofan 12.8 37.9 35.4 9.1 4.4 0.5 100.0 15.3 38.8 30.6 6.2 8.9 0.2 100.0 132 West Kordofan 37.6 26.2 17.4 3.3 10.8 4.7 100.0 33.0 31.5 20.5 3.1 8.4 3.5 100.0 68 North Darfur 19.7 32.5 25.6 12.1 7.4 2.8 100.0 21.0 37.7 19.2 3.7 13.3 5.0 100.0 450 West Darfur 25.2 33.3 19.4 12.5 9.4 0.3 100.0 18.2 34.5 20.6 10.6 15.7 0.5 100.0 117 South Darfur 16.8 15.4 38.3 26.2 2.6 0.7 100.0 24.7 24.1 27.0 7.4 15.1 1.7 100.0 360 84 Background characteristics Drinking practices during diarrhoea: Eating practices during diarrhoea: Number of children aged 0-59 months with diarrhoea Child was given to drink: Much less Child was given to drink: Somewhat less Child was given to drink: About the same Child was given to drink: More Child was given to drink: Nothing Missing/ DK Sudan Child was given to eat: Much less Child was given to eat: Somewhat less Child was given to eat: About the same Child was given to eat: More Child was given to eat: Nothing Missing/ DK Sudan Central Darfur 18.7 19.2 29.4 8.3 17.1 7.4 100.0 14.2 21.4 33.2 6.3 19.3 5.6 100.0 79 East Darfur 19.0 24.7 17.0 28.5 7.6 3.3 100.0 18.6 33.7 17.8 2.3 24.2 3.6 100.0 178 Area Urban 22.3 22.7 29.6 21.0 3.9 0.4 100.0 19.9 30.4 24.2 6.5 18.2 0.7 100.0 1,216 Rural 16.7 28.3 26.3 18.1 9.2 1.3 100.0 17.6 32.6 24.3 5.8 17.9 1.8 100.0 2,872 Age 0-11 18.2 22.8 27.7 10.1 20.1 1.1 100.0 14.6 19.0 13.3 3.7 47.6 1.8 100.0 933 12-23 20.3 30.5 23.6 20.1 4.9 0.6 100.0 20.4 34.1 25.7 5.0 13.4 1.4 100.0 1,028 24-35 18.3 26.0 31.8 19.5 3.1 1.3 100.0 18.7 33.5 30.8 6.4 9.1 1.5 100.0 870 36-47 17.3 29.0 27.4 22.0 3.4 0.9 100.0 19.4 39.7 24.5 8.7 6.2 1.4 100.0 763 48-59 16.4 23.5 26.3 27.9 4.6 1.3 100.0 18.4 37.3 30.4 7.8 5.1 1.0 100.0 494 Mother's education None 17.9 26.0 28.4 18.7 7.7 1.3 100.0 18.9 31.7 24.7 5.9 16.9 1.9 100.0 1,618 Primary 17.5 29.5 24.9 18.1 9.3 0.8 100.0 17.7 32.8 23.4 5.3 19.7 1.1 100.0 1,525 Secondary 24.2 23.1 27.6 20.4 4.1 0.6 100.0 19.7 29.8 25.1 6.8 17.5 1.1 100.0 648 Higher 12.7 23.7 33.2 22.1 7.0 1.3 100.0 15.1 33.9 24.6 8.9 16.1 1.5 100.0 295 Missing/DK * * * * * * 100.0 * * * * * * 100.0 2 Wealth index quintile Poorest 19.3 24.8 27.8 19.6 6.3 2.3 100.0 22.3 33.6 20.3 5.9 14.4 3.5 100.0 845 Second 17.1 31.0 27.6 15.5 7.5 1.4 100.0 16.0 33.8 27.0 4.9 16.8 1.5 100.0 750 Middle 22.7 24.6 22.8 20.2 9.1 0.7 100.0 20.8 28.2 23.9 6.0 20.4 0.7 100.0 834 Fourth 15.2 26.8 28.4 18.4 10.7 0.5 100.0 14.9 31.4 25.9 5.8 20.8 1.1 100.0 995 Richest 18.0 26.6 30.3 21.6 3.3 0.1 100.0 17.7 33.4 24.3 7.7 16.3 0.5 100.0 662 [*] Based on less than 25 unweighted cases and has been suppressed ( ) Figures that are based on 25-49 unweighted cases 85 Table CH.7 shows the percentage of children receiving ORS, various types of recommended homemade fluids, and zinc during an episode of diarrhoea. Since children were likely to be given more than one type of liquid, the percentages do not necessarily add to 100. Of the children with diarrhoea in the two weeks prior to the survey, about 14.5 percent of them received fluids from ORS packets or pre-packaged ORS fluids, and 88.9 percent received recommended homemade fluids (fresh juice and rice with water), 15.2 percent received zinc in one form or another. Over ninety (90.4 percent) of children with diarrhoea received one or more of the recommended home treatments (i.e., were treated with ORS or any recommended homemade fluid). Percentage of children who received the recommended homemade fluid in form of fresh juice, rice with water and water were 48.0 percent, 47.7 percent and 85.8 respectively. Treatment with ORS (fluid from packet) during diarrhoea episodes varies from urban to rural area; 20.7 percent in urban compared to 11.8 percent in rural areas. However there was no noticeable difference between children in urban and rural areas for the reception of ORS or any recommended homemade fluid. 86 Table CH.7: Oral rehydration solutions, recommended homemade fluids, and zinc Percentage of children age 0-59 months with diarrhoea in the last two weeks, and treatment with oral rehydration salts (ORS), recommended homemade fluids, and zinc, Sudan MICS, 2014 Background characteristics Percentage of children with diarrhoea who received: ORS or zinc [1] Number of children aged 0-59 months with diarrhoea Oral rehydration salts (ORS) Recommended homemade fluids ORS or any recommend ed homemade fluid Zinc Fluid from packers Pre- packaged fluid Any ORS Fresh juice Rice water or starch Water Any recommend ed homemade fluid Tablet Syrup Any zinc Sudan 14.5 9.1 19.6 48.0 47.7 85.8 88.9 90.4 3.7 14.4 15.2 28.9 4,088 Sex Male 14.5 9.0 19.8 48.6 48.7 85.6 88.9 90.2 3.6 14.1 15.1 28.8 2,125 Female 14.4 9.3 19.5 47.4 46.8 86.0 88.9 90.5 3.7 14.7 15.4 29.0 1,963 State Northern 11.3 1.4 11.3 72.7 46.0 92.3 95.1 96.1 .7 7.0 7.0 17.6 56 River Nile 21.9 12.3 27.4 60.7 49.4 88.0 94.4 94.4 1.2 10.8 10.8 30.8 88 Red Sea (34.6) (23.7) (37.5) (68.6) (59.8) (81.6) (90.1) (95.2) (17.0) (19.8) (27.9) (53.0) 23 Kassala 34.8 14.4 41.8 40.7 42.1 77.6 82.5 86.4 2.7 21.2 22.5 51.8 164 Gadarif 11.9 10.9 19.8 53.6 50.5 89.8 92.3 92.3 1.7 22.4 22.4 37.3 168 Khartoum 19.8 9.5 22.3 73.2 64.3 88.1 93.0 94.6 2.2 14.5 14.5 30.6 742 Gezira 4.0 11.7 15.2 39.1 37.2 85.9 86.5 87.4 .8 8.9 8.9 22.4 749 White Nile 11.1 6.3 15.7 52.1 52.9 89.5 91.8 93.0 3.1 13.0 13.4 24.8 257 Sinnar 8.8 7.8 13.9 59.6 42.1 91.1 93.2 93.8 2.2 12.5 13.9 24.0 156 Blue Nile 22.7 6.4 27.6 54.7 70.0 93.7 94.2 95.5 2.4 9.9 11.0 31.8 141 North Kordofan 10.1 1.9 11.4 56.6 51.2 83.4 89.7 89.7 7.4 25.1 27.2 35.3 158 South Kordofan 10.2 9.7 15.9 40.8 53.5 88.7 91.9 93.4 9.9 17.2 17.9 27.4 132 West Kordofan 5.5 11.1 13.6 50.8 38.8 77.8 84.1 85.7 .8 9.9 10.7 14.4 68 North Darfor 17.6 8.7 20.2 36.1 41.1 84.7 87.9 90.6 5.6 13.4 13.7 25.1 450 87 Background characteristics Percentage of children with diarrhoea who received: ORS or zinc [1] Number of children aged 0-59 months with diarrhoea Oral rehydration salts (ORS) Recommended homemade fluids ORS or any recommend ed homemade fluid Zinc Fluid from packers Pre- packaged fluid Any ORS Fresh juice Rice water or starch Water Any recommend ed homemade fluid Tablet Syrup Any zinc West Darfor 29.3 10.3 32.8 39.2 65.4 84.2 87.1 89.9 14.6 22.0 26.6 46.6 117 South Darfor 10.6 6.3 15.5 28.9 38.1 86.6 89.6 90.4 5.2 19.3 22.3 28.2 360 Central Darfor 23.7 16.8 26.4 27.3 41.7 69.4 73.4 76.0 11.4 29.4 31.9 47.5 79 East Darfor 14.3 4.5 15.2 25.2 27.3 73.6 76.4 77.7 2.3 4.6 5.4 18.1 178 Area Urban 20.7 10.3 24.8 62.7 58.8 87.8 91.6 93.1 4.9 19.5 20.1 35.6 1,216 Rural 11.8 8.6 17.5 41.9 43.1 85.0 87.8 89.2 3.1 12.2 13.2 26.0 2,872 Age 0-11 12.2 7.7 16.7 27.5 29.1 67.0 69.6 73.2 3.8 15.5 16.1 26.8 933 12-23 16.7 8.8 21.6 55.8 52.8 90.2 94.0 95.2 2.5 15.1 15.8 30.8 1,028 24-35 15.0 10.9 20.9 52.9 52.6 91.6 95.4 96.1 3.8 14.1 14.7 29.9 870 36-47 14.5 10.2 20.6 52.4 53.7 92.3 94.0 94.9 4.7 12.7 14.0 28.5 763 48-59 13.1 7.9 17.5 55.4 54.8 91.9 95.4 95.5 3.7 13.9 15.1 27.3 494 Wealth index quintile Poorest 12.6 7.5 15.9 27.1 37.1 83.0 85.8 87.1 4.7 12.6 14.2 24.2 845 Second 15.7 7.3 19.1 38.8 45.1 83.7 88.1 89.4 5.2 17.7 19.0 30.9 750 Middle 16.1 9.0 21.1 49.1 54.0 87.2 89.2 91.7 4.4 12.7 13.6 28.9 834 Fourth 13.7 11.2 21.2 53.5 49.8 85.7 89.2 89.9 2.2 14.6 15.0 30.0 995 Richest 14.4 10.4 20.7 75.7 53.4 90.1 93.0 94.6 1.8 14.6 14.6 30.7 662 1 MICS indicator 3.11 - Diarrhoea treatment with oral rehydration salts (ORS) and zinc ( ) Figures that are based on 25-49 unweighted cases 88 The figure below shows the distribution of children under age 5 with diarrhoea who received ORS or recommended homemade fluids. Figure CH.2: Children under age 5 with diarrhoea who received ORS or recommended homemade fluids, Sudan MICS, 2014 Table CH.8 provides the proportion of children age 0-59 months with diarrhoea in the last two weeks who received oral rehydration therapy with continued feeding, and who received other treatments. Overall, 33.7 percent of children with diarrhoea received ORS or increased fluids, 91.0 percent received ORT (ORS or recommended homemade fluids or increased fluids). Combining the information in Table CH.6 with that of Table CH.7 on oral rehydration therapy, it is observed that 59.3 percent of children received ORT with continued feeding as recommended. There are notable differences in the home management of diarrhoea by background characteristics. The figures for ORT and continued feeding in table CH.8 range from 47.2 percent in Red Sea State to 74.9 percent in Gadarif State. There is also a notable difference among children from poorest homes with 55.5 percent and those from richest homes with 63.9 percent for ORT and continued feeding. 76 78 86 86 87 90 90 90 91 92 93 93 94 94 95 95 96 96 93 89 90 0 20 40 60 80 100 120 P er c en t 89 Table CH.8: Oral rehydration therapy with continued feeding and other treatments Percentage of children age 0-59 months with diarrhoea in the last two weeks who were given oral rehydration therapy with continued feeding and percentage who were given other treatments, Sudan MICS, 2014 Background characteristics Children with diarrhoea who were given: Not given any treatme nt or drug Number of children age 0- 59 months with diarrhoe a in the last two weeks Zinc ORS or increas ed fluids ORT (ORS or recomm ended homem ade fluids or increase d fluids) ORT with continue d feeding [1] Other treatment: Pill or syrup: Antibioti c Pill or syrup: Antimotilit y Pill or syrup : Other Pill or syrup: Unknow n Injection : Antibioti c Injectio n: Non- antibioti c Injectio n: Unknow n Intrav e- nous Home remedy, herbal medicin e Othe r Sudan 15.2 33.7 91.0 59.3 15.0 13.8 0.8 5.0 1.3 0.1 0.3 0.3 5.9 5.6 5.6 4,088 Sex Male 15.1 33.7 90.9 57.7 17.3 15.0 0.7 5.4 1.6 0.0 0.4 0.3 5.3 5.5 5.8 2,125 Female 15.4 33.8 91.1 61.1 12.6 12.4 0.9 4.7 0.9 0.2 0.1 0.3 6.6 5.7 5.4 1,963 State Northern 7.0 33.6 97.1 64.4 13.0 22.2 0.0 4.5 0.0.0 0.0 0.0 2.8 22.5 4.4 .9 56 River Nile 10.8 47.9 97.2 62.3 30.1 13.6 0.3 1.9 3.4 0.0 0.0 0.0 6.7 3.9 2.0 88 Red Sea (27.9) (45.8) (95.2) (47.2) (16.3) (26.2) (1.8) (6.2) (0.0) (0.0) (0.0) (0.0) (22.2) (5.1) (2.7) 23 Kassala 22.5 45.8 86.4 54.0 8.0 16.8 1.5 1.4 0.0 0.0 0.0 0.0 7.5 1.4 8.3 164 Gadarif 22.4 35.6 92.3 74.9 33.2 13.0 1.2 1.6 2.3 0.0 .4 0.0 6.7 6.7 3.2 168 Khartoum 14.5 36.8 94.8 59.7 25.4 26.5 0.6 2.8 2.3 0.2 .0 .6 5.5 .8 2.8 742 Gezira 8.9 29.2 89.0 58.0 8.5 10.4 0.3 4.4 0.9 0.3 1.3 .2 3.4 8.4 7.6 749 White Nile 13.4 31.3 93.0 66.6 16.4 17.5 0.0 1.9 0.9 0.0 .4 1.2 7.0 3.0 4.4 257 Sinnar 13.9 39.8 95.7 59.8 14.6 21.0 0.0 4.1 0.3 0.0 0.0 .7 2.5 2.6 1.7 156 Blue Nile 11.0 41.1 95.8 63.7 15.6 19.7 0.5 21.5 0.0 0.0 0.0 0.0 3.0 8.7 1.3 141 North Kordofan 27.2 25.4 89.7 56.3 18.5 3.6 2.4 .6 2.7 0.0 0.0 0.0 4.6 3.7 5.5 158 South Kordofan 17.9 22.4 93.7 72.1 6.4 15.5 6.0 8.1 2.1 0.0 0.0 0.0 6.3 8.5 3.3 132 West Kordofan 10.7 16.9 85.7 53.8 23.7 7.6 .7 .0 4.3 0.0 0.0 0.0 4.3 10.5 8.9 68 North Darfur 13.7 28.3 90.9 57.2 11.9 5.8 1.0 7.7 .4 0.0 0.0 0.0 2.0 4.5 7.4 450 West Darfur 26.6 41.4 90.3 61.4 12.4 5.1 0.0 1.8 1.6 0.0 0.0 0.0 9.5 4.4 5.1 117 90 Background characteristics Children with diarrhoea who were given: Not given any treatme nt or drug Number of children age 0- 59 months with diarrhoe a in the last two weeks Zinc ORS or increas ed fluids ORT (ORS or recomm ended homem ade fluids or increase d fluids) ORT with continue d feeding [1] Other treatment: Pill or syrup: Antibioti c Pill or syrup: Antimotilit y Pill or syrup : Other Pill or syrup: Unknow n Injection : Antibioti c Injectio n: Non- antibioti c Injectio n: Unknow n Intrav e- nous Home remedy, herbal medicin e Othe r South Darfur 22.3 37.5 91.1 56.8 7.8 9.5 0.0 7.7 0.9 0.0 0.0 0.0 12.8 10.1 6.2 360 Central Darfur 31.9 31.1 76.2 49.0 7.7 4.8 1.1 11.1 0.6 0.4 0.0 0.0 6.3 7.4 11.0 79 East Darfur 5.4 35.4 78.8 47.2 7.4 1.0 0.0 8.6 0.3 0.0 0.0 0.0 7.8 14.5 13.6 178 Area Urban 20.1 38.8 93.4 58.4 16.9 20.3 0.7 3.6 1.5 0.2 0.1 .5 6.0 3.5 3.7 1,216 Rural 13.2 31.6 90.0 59.7 14.2 11.0 0.8 5.7 1.2 0.1 0.4 .2 5.9 6.6 6.4 2,872 Age 0-11 16.1 24.3 74.1 30.8 13.0 11.5 0.4 4.2 0.7 0.0 1.0 .2 4.8 4.1 16.6 933 12-23 15.8 35.5 95.2 62.2 18.5 14.8 0.6 5.3 1.7 0.0 0.1 .5 5.7 6.2 3.1 1,028 24-35 14.7 34.9 96.7 69.2 14.8 15.7 0.7 5.0 1.3 0.0 0.2 .1 5.7 5.4 2.4 870 36-47 14.0 37.6 95.6 69.9 13.1 12.4 1.6 6.3 1.4 0.0 0.0 .4 6.8 7.0 2.2 763 48-59 15.1 39.9 97.3 73.5 15.1 14.5 0.5 4.2 1.2 0.0 0.0 .1 7.7 5.5 0.8 494 Wealth index quintile 0.0 Poorest 14.2 31.3 87.7 55.5 13.0 5.7 0.8 6.6 0.7 0.0 0.0 0.0 7.4 6.5 8.2 845 Second 19.0 30.1 89.9 61.8 11.5 10.3 1.0 6.7 1.2 0.0 0.2 0.0 7.5 7.8 6.2 750 Middle 13.6 35.8 92.3 56.0 18.4 17.0 0.6 7.2 .9 0.3 1.1 .5 4.2 6.7 3.4 834 Fourth 15.0 34.9 90.9 60.5 13.4 15.7 1.0 2.7 2.1 0.2 0.0 .4 4.8 4.3 6.1 995 Richest 14.6 36.6 95.1 63.9 19.8 20.9 0.2 2.0 1.1 0.0 0.1 .5 6.4 2.7 3.6 662 [1] MICS indicator 3.12 - Diarrhoea treatment with oral rehydration therapy (ORT) and continued feeding ( ) Figures that are based on 25-49 unweighted cases 91 Figure CH.3 shows slight difference between urban and rural in case of the children under five with diarrhoea who received the distribution of children under age 5 with diarrhoea who received ORT (ORS, RHF, or increased fluids) and continued feeding. A higher percentage of children in urban areas (58.4 percent) received ORT with continued feeding than those in rural areas with (59.7 percent). The apparent minimal difference among the children along the wealth index spectrum on ORT with continued feeding treatment of children with diarrhoea can be attributed to the free access to ORT in public health facilities by all the families. Figure CH.3: Children under age 5 with diarrhoea who received ORT (ORS, RHF, or increased fluids) and continued feeding, Sudan MICS, 2014 0 75 72 67 64 64 62 61 60 60 58 57 57 56 54 54 49 47 47 58 60 56 62 56 60 64 59 0 10 20 30 40 50 60 70 80 States Gadarif South Kordofan White Nile Northern Blue Nile River Nile West Darfor Sinnar Khartoum Gezira North Darfor South Darfor North Kordofan Kassala West Kordofan Central Darfor Red Sea East Darfor Area Urban Rural Wealth Index Quintile Poorest Second Middle Fourth Richest Sudan Per cent 92 Table CH.9 provides information on the source of ORS and zinc for children who benefitted from these treatments;ORS (63.8 percent) and zinc (59.5 percent). The percentage of children who were given ORS and zinc as treatment for diarrhoea were 19.6 percent, 15.2 percent respectively. For both ORS and zinc, the main source is from providers in the public health facilities. The source of ORS is 25.1 percent in public health facilities as compared to 3.6 percent from private service providers. Similar observations were reported for the source of zinc supply as treatment for diarrhoea. Figure CH.3a: Source of ORS and ZINC, Sudan MICS, 2014 63.8 25.1 3.6 8.0 59.5 31.4 4.9 8.5 P U B L I C P R I V A T E C O MMU N I T Y H E A L T H P R O V I D E R [ A ] O T H E R S O U R C E % o children when the soruce is ZINK % children when the source is ORS 93 Table CH.9: Source of ORS and zinc Percentage of children age 0-59 months with diarrhoea in the last two weeks who were given ORS, and percentage given zinc, by the source of ORS and zinc, Sudan MICS, 2014 Background characteristics Percentage of children who were given as treatment for diarrhoea: Number of children age 0-59 months Percentage of children for whom the source of ORS was: Numby er of childre n age 0-59 months Percentage of children for whom the source of zinc was: Numbe r of childre n age 0-59 months ORS Zinc Health facilities or providers A health facility or provide r [b] Health facilities or providers A health facility or provider [b] Public Private Commun ity health provider [a] Other source DK/ Missing Public Private Commu nity health provide r [a] Other sourc e DK/ Missin g Sudan 19.6 15.2 4,088 63.8 25.1 3.6 8.0 3.1 88.9 803 59.5 31.4 4.9 8.5 0.7 90.9 622 Sex Male 19.8 15.1 2,125 61.4 26.3 3.0 9.9 2.4 87.6 421 58.1 32.1 4.9 9.1 0.8 90.1 321 Female 19.5 15.4 1,963 66.4 23.8 4.3 6.0 3.8 90.2 382 61.0 30.6 5.0 7.9 0.5 91.6 301 State Northern 11.3 7.0 56 * * * * * * 6 * * * * * * 4 River Nile 27.4 10.8 88 (68.5) (23.7) (3.4) (3.8) (3.9) (92.2) 24 * * * * * * 10 Red Sea 37.5 27.9 23 * * * * * * 9 * * * * * * 7 Kassala 41.8 22.5 164 90.9 4.5 4.2 3.7 .9 95.4 68 (73.8) (21.5) (.0) (4.7) (0.0) (95.3) 37 Gadarif 19.8 22.4 168 (64.5) (16.4) (1.2) (17.5) (1.6) (80.9) 33 (76.4) (23.6) (2.5) (.0) (0.0) (100.0) 38 Khartoum 22.3 14.5 742 54.0 31.5 .0 9.6 4.9 85.5 165 58.6 41.4 5.4 0.0 0.0 100.0 108 Gezira 15.2 8.9 749 (46.8) (51.8) (4.5) (1.4) (0.0) (98.6) 114 (41.7) (45.1) (0.0) (13.2) (0.0) (86.8) 66 White Nile 15.7 13.4 257 (71.8) (22.1) (3.0) (6.1) (0.0) (93.9) 40 (72.2) (21.7) (.0) (3.5) (2.6) (93.9) 35 Sinnar 13.9 13.9 156 (67.5) (4.2) (0.0) (11.2) (17.0) (71.8) 22 (58.6) (37.6) (3.8) (3.9) (0.0) (96.1) 22 Blue Nile 27.6 11.0 141 (91.2) (3.9) (0.0) (4.9) (0.0) (95.1) 39 (80.1) (15.5) (0.0) (4.5) (0.0) (95.5) 15 North Kordofan 11.4 27.2 158 * * * * * * 18 (56.1) (37.6) (10.6) (6.3) (0.0) (93.7) 43 South Kordofan 15.9 17.9 132 (73.3) (12.1) (11.6) (6.4) (8.3) (85.3) 21 (75.6) (23.1) (2.2) (0.0) (1.3) (98.7) 24 West Kordofan 13.6 10.7 68 * * * * * * 9 * * * * * * 7 North Darfur 20.2 13.7 450 61.4 15.7 8.1 18.6 4.3 77.1 91 66.0 16.7 7.2 13.6 3.7 82.7 62 West Darfur 32.8 26.6 117 84.2 12.6 0.0 0.9 2.3 96.8 38 79.6 18.0 5.7 2.4) 0.0 97.6 31 South Darfur 15.5 22.3 360 39.7 47.5 10.1 8.1 4.7 87.2 56 26.1 44.4 12.6 29.4 .0 70.6 80 94 Background characteristics Percentage of children who were given as treatment for diarrhoea: Number of children age 0-59 months Percentage of children for whom the source of ORS was: Numby er of childre n age 0-59 months Percentage of children for whom the source of zinc was: Numbe r of childre n age 0-59 months ORS Zinc Health facilities or providers A health facility or provide r [b] Health facilities or providers A health facility or provider [b] Public Private Commun ity health provider [a] Other source DK/ Missing Public Private Commu nity health provide r [a] Other sourc e DK/ Missin g Central Darfur 26.4 31.9 79 84.1 3.7 0.0 8.7 3.4 87.9 21 73.7 12.4 2.3 11.6 2.3 86.1 25 East Darfur 15.2 5.4 178 69.4 (26.1) (3.7) (4.5) (.0) (95.5) 27 * * * * * * 10 Area Urban 24.8 20.1 1,216 63.9 25.7 .2 7.3 3.1 89.7 302 63.1 35.9 .7 .4 .7 98.9 244 Rural 17.5 13.2 2,872 63.7 24.7 5.6 8.5 3.1 88.4 501 57.2 28.5 7.7 13.7 .6 85.6 378 Age 0-11 16.7 16.1 933 72.4 18.3 2.4 6.3 3.0 90.7 156 67.8 25.2 4.4 6.4 .6 93.0 150 12-23 21.6 15.8 1,028 65.4 23.6 4.7 7.8 3.2 89.0 222 58.4 36.1 2.0 4.3 1.2 94.5 163 24-35 20.9 14.7 870 57.8 32.3 5.4 6.2 3.7 90.1 182 47.0 39.2 7.6 13.7 .1 86.2 127 36-47 20.6 14.0 763 52.2 32.1 .6 14.3 1.4 84.3 157 56.7 34.1 6.9 9.3 .0 90.7 107 48-59 17.5 15.1 494 77.7 13.3 4.3 4.4 4.5 91.0 86 70.4 16.3 5.2 11.7 1.5 86.8 75 Wealth index quintile Poorest 15.9 14.2 845 66.2 17.6 10.7 12.9 3.3 83.8 135 46.2 25.4 10.0 26.5 1.9 71.6 120 Second 19.1 19.0 750 71.0 20.7 6.9 6.8 1.5 91.7 143 69.6 24.8 7.4 4.6 1.0 94.3 143 Middle 21.1 13.6 834 67.4 16.3 1.9 14.0 2.3 83.7 176 69.0 26.2 1.4 4.5 .3 95.2 114 Fourth 21.2 15.0 995 60.3 35.3 .3 3.4 1.1 95.6 211 62.2 31.9 .6 5.9 .0 94.1 149 Richest 20.7 14.6 662 54.6 32.7 .4 4.2 8.6 87.3 137 45.8 53.7 6.0 .5 .0 99.5 97 [a] Community health provider includes both public (Community health worker and Mobile/Outreach clinic) and private (Mobile clinic) health facilities [b] Includes all public and private health facilities and providers [*] Based on less than 25 unweighted cases and has been suppressed ( ) Figures that are based on 25-49 unweighted cases 95 6.3.2 Acute Respiratory Infections Symptoms of ARI are collected during the Sudan MICS to capture pneumonia disease, the leading cause of death in children under five. Once diagnosed, pneumonia is treated effectively with antibiotics. Studies have shown a limitation in the survey approach of measuring pneumonia because many of the suspecte(d cases identified through surveys are in fact, not true pneumonia.20 While this limitation does not affect the level and patterns of care-seeking for suspected pneumonia, it limits the validity of the level of treatment of pneumonia with antibiotics, as reported through household surveys. The treatment indicator described in this report must therefore be taken with caution, keeping in mind that the accurate level is likely higher. Table CH.10: Care-seeking for and antibiotic treatment of symptoms of acute respiratory infection ARI Percentage of children age 0-59 months with symptoms of ARI in the last two weeks for whom advice or treatment was sought, by source of advice or treatment, and percentage of children with symptoms who were given antibiotics, Sudan MICS, 2014 Background characteristics Percentage of children with symptoms of ARI for whom: No advice or treatment sought Percentage of children with symptoms of ARI in the last two weeks who were given antibiotics [2] Number of children age 0-59 months with symptoms of ARI in the last two weeks [d] Advice or treatment was sought from: Other source A health facility or provider [1], [b] Health facilities or providers: Public Health facilities or providers: Private Health facilities or providers: Community health provider [a] Sudan 42.1 15.1 4.5 9.2 48.3 34.8 59.0 2,500 Sex Male 41.5 16.2 4.1 9.8 48.1 33.9 59.5 1,316 Female 42.8 13.8 4.9 8.6 48.5 35.8 58.4 1,185 State Northern 55.5 17.8 .0 1.7 64.3 26.7 71.6 29 River Nile 62.3 16.3 5.2 (4.5 74.4 15.4 78.0 44 Red Sea * * * * * * * 14 Kassala 51.6 7.7 5.0 2.6 56.0 38.0 63.4 75 Gadarif 60.8 11.7 5.3 3.8 69.6 27.7 72.8 81 Khartoum 41.1 20.4 .0 10.4 49.0 29.0 61.4 229 Gezira 58.8 11.9 4.6 3.9 63.6 25.4 65.5 361 White Nile 54.6 13.7 5.5 12.4 64.0 22.2 75.4 180 Sinnar 52.3 9.1 2.1 13.7 56.3 25.8 60.8 130 Blue Nile 58.6 8.7 .4 6.4 59.5 28.5 62.6 89 North Kordofan 49.6 11.5 9.4 7.8 54.9 31.1 66.7 144 South Kordofan 42.5 8.7 1.7 8.0 43.3 39.7 68.0 129 West Kordofan 52.6 15.8 14.4 7.5 60.2 27.6 59.2 45 North Darfur 25.3 15.5 2.6 5.1 29.2 54.2 46.5 373 West Darfur 63.1 12.2 2.5 8.5 67.8 21.6 54.2 44 South Darfur 21.7 23.4 10.1 11.1 34.8 45.1 49.0 342 Central Darfur 45.7 5.2 0.5 17.8 46.5 33.6 54.1 38 East Darfur 17.1 21.7 3.1 30.1 19.5 37.2 42.0 154 Area Urban 42.7 24.4 1.2 8.1 54.7 26.8 64.3 677 Rural 41.9 11.6 5.7 9.7 45.9 37.8 57.0 1,823 Age 0-11 43.7 13.4 3.8 11.5 49.9 32.9 60.7 447 12-23 44.0 17.0 4.7 8.4 52.3 32.2 58.4 488 24-35 43.2 12.6 4.6 6.4 48.6 38.3 58.8 518 36-47 39.1 17.0 4.2 10.1 46.1 35.0 61.3 609 48-59 41.3 14.8 5.1 10.1 44.7 35.5 54.9 438 Wealth index quintile Poorest 21.9 14.0 7.3 13.7 27.2 51.4 43.3 627 Second 39.3 16.6 6.0 10.7 45.4 35.6 58.5 580 Middle 58.3 9.3 3.1 5.7 61.9 27.2 65.2 556 Fourth 49.1 13.4 1.5 7.4 54.1 30.8 61.0 406 20Campbell, H. et al. 2013.Measuring Coverage in MNCH: Challenges in Monitoring the Proportion of Young Children with Pneumonia Who Receive Antibiotic Treatment. PLoS Med 10(5): e1001421. doi:10.1371/journal.pmed.1001421 96 Background characteristics Percentage of children with symptoms of ARI for whom: No advice or treatment sought Percentage of children with symptoms of ARI in the last two weeks who were given antibiotics [2] Number of children age 0-59 months with symptoms of ARI in the last two weeks [d] Advice or treatment was sought from: Other source A health facility or provider [1], [b] Health facilities or providers: Public Health facilities or providers: Private Health facilities or providers: Community health provider [a] Richest 49.6 26.0 2.4 6.6 63.3 19.9 76.6 331 [1] MICS indicator 3.13 - Care-seeking for children with acute respiratory infection (ARI) symptoms [2] MICS indicator 3.14 - Antibiotic treatment for children with ARI symptoms [a] Community health providers includes both public (Community health worker and Mobile/Outreach clinic) and private (Mobile clinic) health facilities [b] Includes all public and private health facilities and providers, but excludes private pharmacy [c] Includes all public and private health facilities and providers [d] Children with symptoms of ARI are those who had an illness with a cough accompanied by a rapid or difficult breathing Sudan MICS did not include question on symptoms due to a problem in the chest, or both a problem in the chest and a blocked nose ( ) Figures that are based on 25-49 unweighted cases [*] Based on less than 25 unweighted cases and has been suppressed Table CH.10 presents the percentage of children with symptoms of ARI in the two weeks preceding the survey for whom care was sought, by source of care and the percentage who received antibiotics. Approximately half (48.3 percent) of children age 0-59 months with symptoms of ARI were taken to a qualified provider. Table CH.10 also presents the use of antibiotics for the treatment of children under 5 years with symptoms of ARI by sex, age, state, area, age, and socioeconomic factors. In Sudan, 59.0 percent of under-5 children with symptoms of ARI received antibiotics during the two weeks prior to the survey. The percentage was considerably higher in urban (64.3 percent) than in rural areas (57.0 percent, and ranged from 49.0 percent in South Darfur state to 78.0 percent in River Nile state. The table also shows that antibiotic treatment of ARI symptoms is low among the poorest households and among children whose mothers/caretakers have less than secondary education. The use of antibiotics increases with the age of the child. With regard to the point of treatment among children with symptoms of ARI who were treated with antibiotics, Table CH. 10 shows treatment was mostly received from public health facilities (42.1 percent). Treatment was received in 4.5 percent of cases from community health workers. Mothers’ knowledge of danger signs is an important determinant of care-seeking behaviour. In the Sudan MICS 2014, mothers or caretakers were asked to report symptoms that would cause them to take a child under-five for care immediately at a health facility. Issues related to knowledge of danger signs of pneumonia are presented in Table CH.11. Knowledge of at least the two danger signs of pneumonia, i.e. fast and/or difficult breathing would cause women aged 15-49 years who are mothers or caretakers of under 5 children to take them immediately to a health facility for treatment. 97 Table CH.11: Knowledge of the two danger signs of pneumonia Percentage of women age 15-49 years who are mothers or caretakers of children under age 5 by symptoms that would cause them to take a child under age 5 immediately to a health facility, and percentage of mothers who recognize fast or difficult breathing as signs for seeking care immediately, Sudan MICS, 2014 Background characteristics Percentage of mothers / caretakers who think that a child should be taken immediately to a health facility if the child: Mothers/ caretakers who recognize at least one of the two danger signs of pneumonia (fast and/or difficult breathing) Number of mothers / caretaker s of children age 0-59 months Is not able to drink or breastfee d Become s sicker Develop s a fever Has fast breathin g Has difficulty breathing Has blood in stool Drinking poorly Has other symptoms Sudan 11.2 21.3 80.8 11.7 20.9 8.0 7.5 64.8 26.9 8,715 State Northern 7.2 7.6 85.6 6.0 17.6 5.5 4.8 84.1 21.5 164 River Nile 13.2 21.2 86.6 20.4 28.3 2.7 6.2 64.8 44.3 258 Red Sea 7.0 19.6 85.0 18.7 19.1 3.9 9.3 48.2 33.9 167 Kassala 6.1 14.2 82.8 6.0 17.7 5.6 3.2 43.7 20.7 328 Gadarif 20.7 28.4 92.9 13.3 25.2 13.9 15.0 63.4 27.2 476 Khartoum 36.2 32.5 89.1 29.4 43.0 31.8 21.5 71.3 51.3 1,113 Gezira 5.2 27.4 74.4 5.2 19.1 1.0 1.1 75.6 21.8 1,311 White Nile 3.6 4.7 84.6 8.3 23.4 1.6 1.2 65.4 29.6 420 Sinnar 2.7 34.2 73.8 13.0 29.4 2.9 .4 59.6 34.3 331 Blue Nile 5.0 6.8 94.0 4.8 9.4 2.7 1.2 79.6 13.9 405 North Kordofan 3.6 10.9 77.2 7.6 20.4 1.0 6.0 62.7 23.5 587 South Kordofan 4.6 14.7 80.7 6.4 9.9 1.8 1.9 51.1 14.3 297 West Kordofan 20.3 33.3 72.4 20.3 24.6 9.1 24.8 44.9 40.1 541 North Darfur 1.1 11.8 73.0 2.8 7.7 1.1 2.9 83.6 10.4 756 West Darfur 17.1 23.3 82.6 15.1 18.7 12.4 7.6 67.8 28.7 314 South Darfur 9.0 19.8 81.9 12.2 15.5 10.5 4.9 39.7 23.5 787 Central Darfur 4.5 12.6 77.9 4.4 14.1 5.0 3.9 71.2 17.8 151 East Darfur 1.1 21.9 71.4 2.2 2.3 .4 1.3 66.7 4.3 308 Area Urban 17.7 22.1 85.5 19.2 29.1 14.9 11.2 63.3 37.5 2,430 Rural 8.7 21.0 79.0 8.8 17.7 5.4 6.1 65.3 22.8 6,284 Mother's education None 8.4 21.6 79.7 9.3 14.7 5.8 6.4 60.6 20.8 3,611 Primary 11.8 20.3 81.0 11.2 22.0 7.5 7.2 66.5 27.8 2,999 Secondary 14.3 20.8 82.7 15.8 28.0 12.1 8.5 69.8 33.9 1,443 Higher 17.1 25.0 82.7 18.5 34.7 14.0 13.1 68.6 41.0 658 Missing/DK * * * * * * * * * 3 [*] Based on less than 25 unweighted cases and has been suppressed 98 Overall, 26.9 percent of women knew at least one of the two danger signs of pneumonia – fast and/or difficult breathing. The most commonly identified symptom for taking a child to a health facility is fever accounting for more than 80 percent of respondents. About 11.7 percent and 20.9 percent of mothers identified fast breathing and difficult breathing respectively as symptoms for taking children immediately to a health care provider. The percentage of mothers/caretakers who recognised the two danger signs of pneumonia was higher among mothers with higher education (41.0 percent) compared to the low percentage (20.8 percent) for mothers with no education. The percentage of mothers/caretakers who recognized the two danger signs of pneumonia was highest in Khartoum State (51.3 percent) and lowest in East Darfur state (4.3 percent). Also there was higher percentage recognition of the two danger of signs of pneumonia among urban (37.5 percent) respondents than rural (22.8 percent) respondents. 6.3.3 Solid Fuel Use More than 3 billion people around the world rely on solid fuels for their basic energy needs, including cooking and heating. Solid fuels include biomass fuels, such as wood, charcoal, crops or other agricultural waste, dung, shrubs and straw, and coal. Cooking and heating with solid fuels leads to high levels of indoor smoke which contains a complex mix of health-damaging pollutants. The main problem with the use of solid fuels is their incomplete combustion, which produces toxic elements such as carbon monoxide, polyaromatic hydrocarbons, and sulphur dioxide (SO2), among others. Use of solid fuels increases the risks of incurring acute respiratory illness, pneumonia, chronic obstructive lung disease, cancer, and possibly tuberculosis, asthma, or cataracts, and may contribute to low birth weight of babies born to pregnant women exposed to smoke. The primary indicator for monitoring use of solid fuels is the proportion of the population using solid fuels as the primary source of domestic energy for cooking, shown in Table CH.12. Solid fuel use. Percent distribution of household members according to type of cooking fuel mainly used by the household, and percentage of household members living in households using solid fuels for cooking, Sudan MICS, 2014 Overall, 58.2 percent of the household population in Sudan use solid fuels for cooking, consisting mainly of wood (40.7 percent). Use of solid fuels is low in urban areas (40.7 percent), but high in rural areas, where they are used by two third of households members (66.1 percent). Differentials with respect to household wealth and the educational level of the houshold head need more attention. Very big difference between the poorest and richest which is related very much to ability and purchasing power for the options other than access wood. The findings show that use of solid fuels ranges from 99.9 percent in Central Darfur and to 12.5 percent in Khartoum State. 99 Table CH.12: Solid fuel use by place of cooking Percent distribution of household members in households using solid fuels by place of cooking, Sudan MICS, 2014 Background characteristics Percentage of household members in households using: Solid fuels for cookin g [1] Number of household members Electricit y Liquefie d Petroleu m Gas (LPG) Kerosi ne Solid fuels: Coal / Lignite Solid fuels: Charco al Solid fuels: Wood Solid fuels: Straw / Shrubs / Grass Solid fuels: Animal dung Solid fuels: Agricultur al crop residue Solar No food cooked in househ old Other Missi ng Total Sudan 0.4 41.3 0.0 1.2 15.7 40.7 0.5 0.1 0.0 0.0 0.0 0.0 0.0 100.0 58.2 98,883 State Northern 2.1 81.3 0.1 0.9 1.2 14.4 0.0 0.0 0.0 0.0 0.1 0.0 0.0 100.0 16.4 2,181 River Nile 3.2 83.1 0.4 0.1 1.7 10.8 0.7 0.0 0.0 0.0 0.0 0.1 0.0 100.0 13.3 3,715 Red Sea 0.6 42.1 0.0 8.2 28.4 20.6 0.0 0.0 0.0 0.0 0.0 0.0 0.0 100.0 57.2 2,489 Kassala 0.0 25.3 0.0 0.7 35.3 37.7 0.9 0.0 0.0 0.0 0.0 0.0 0.0 100.0 74.7 4,117 Gadarif 0.1 29.8 .2 4.2 32.5 31.8 0.7 0.0 0.3 0.1 0.2 0.0 0.0 100.0 69.6 5,005 Khartoum 0.5 87.0 0.0 1.6 7.6 3.2 0.0 0.1 0.0 0.0 0.0 0.0 0.0 100.0 12.5 13,830 Gezira 0.4 83.3 0.0 0.2 7.1 8.8 0.0 0.1 0.0 0.0 0.0 0.0 0.0 100.0 16.2 16,270 White Nile0 0.1 61.7 0.0 3.3 13.3 19.7 0.8 1.0 0.0 0.0 0.1 0.0 0.0 100.0 38.2 5,016 Sinnar 0.0 42.0 0.0 0.4 18.9 37.8 0.3 0.1 0.0 0.1 0.2 0.0 0.3 100.0 57.4 3,763 Blue Nile 0.1 11.3 0.0 1.8 35.7 50.8 0.2 0.0 0.0 0.0 0.1 0.0 0.0 100.0 88.5 4,094 North Kordofan 0.1 17.2 0.0 0.2 22.0 60.0 0.4 0.0 0.0 0.0 0.1 0.1 0.0 100.0 82.5 6,359 South Kordofan .0 2.5 0.0 3.8 24.9 66.2 2.4 0.0 0.1 0.0 0.0 0.0 0.0 100.0 97.5 2,983 West Kordofan 0.1 1.6 0.0 0.1 15.0 82.9 0.4 0.0 0.0 0.0 0.0 0.0 0.0 100.0 98.3 5,745 North Darfur 0.1 2.5 0.0 0.2 7.2 86.8 3.2 0.0 0.0 0.0 0.0 0.0 0.1 100.0 97.4 7,776 West Darfur 0.1 0.1 0.0 0.0 20.2 79.5 0.0 0.0 0.0 0.0 0.1 0.0 0.0 100.0 99.7 3,023 South Darfur 0.4 1.8 0.0 1.0 23.2 73.3 0.1 0.0 0.1 0.0 0.0 0.0 0.0 100.0 97.7 7,712 Central Darfur 0.0 .0 0.0 1.0 11.9 86.8 0.2 .0 0.0 0.0 0.0 0.0 0.1 100.0 99.9 1,646 East Darfur 0.0 1.1 0.0 0.1 13.1 85.6 0.1 .0 0.0 0.0 0.0 0.0 0.0 100.0 98.9 3,158 100 Background characteristics Percentage of household members in households using: Solid fuels for cookin g [1] Number of household members Electricit y Liquefie d Petroleu m Gas (LPG) Kerosi ne Solid fuels: Coal / Lignite Solid fuels: Charco al Solid fuels: Wood Solid fuels: Straw / Shrubs / Grass Solid fuels: Animal dung Solid fuels: Agricultur al crop residue Solar No food cooked in househ old Other Missi ng Total Area Urban 0.4 58.8 0.0 2.5 26.0 12.0 0.0 0.1 0.0 0.0 0.0 0.0 0.1 100.0 40.7 30,476 Rural 0.4 33.5 0.0 .6 11.1 53.4 0.8 0.1 0.0 0.0 0.0 0.0 0.0 100.0 66.1 68,407 Education of the household head None 0.2 23.8 0.0 1.2 16.8 57.0 0.8 0.1 0.0 0.0 0.0 0.0 0.0 100.0 76.0 45,740 Primary 0.7 46.7 0.1 1.2 16.2 34.7 0.3 0.1 0.1 0.0 0.1 0.0 0.0 100.0 52.5 28,007 Secondary 0.3 64.9 0.1 1.3 14.2 18.8 0.3 0.0 0.0 0.0 0.0 0.0 0.0 100.0 34.7 18,812 Higher 0.6 79.6 0.0 1.2 9.4 9.1 0.0 0.0 0.0 0.0 0.0 0.0 0.0 100.0 19.8 5,564 Missing/DK 0.6 30.3 0.0 6.7 11.6 50.6 0.0 0.0 0.0 0.0 0.2 0.0 0.0 100.0 68.9 761 Wealth index quintile Poorest 0.0 0.0 0.0 0.0 2.9 96.0 1.1 0.0 0.0 0.0 0.0 0.0 0.0 100.0 99.9 19,775 Second 0.0 3.0 0.0 1.5 19.1 74.6 1.4 .3 0.1 0.0 0.1 0.0 0.0 100.0 96.9 19,776 Middle 0.3 33.6 0.1 2.9 35.4 27.2 0.2 .1 0.1 0.0 0.1 0.0 0.0 100.0 65.9 19,779 Fourth 1.0 74.5 0.1 1.2 17.9 5.1 0.0 0.0 0.0 0.0 0.0 0.0 0.1 100.0 24.3 19,773 Richest 0.6 95.1 0.0 .5 3.1 .6 0.0 0.0 0.0 0.0 0.0 0.0 0.0 100.0 4.2 19,781 [1] MICS indicator 3.15 - Use of solid fuels for cooking 101 Solid fuel use by place of cooking is shown in Table CH.13. The presence and extent of indoor pollution are dependent on cooking practices, places used for cooking, as well as types of fuel used. According to the Sudan MICS, 67.8 percent of the population living in households using solid fuels for cooking, cooking food in a separate room that is used as a kitchen. The percentage of households that cook food within the dwelling unit is slightly higher in urban areas (69.8 percent) than in rural areas (67.3 percent). Percentage of households using separate rooms as kitchen are correlated positively with the level of education and with the level of income. Table CH.13: Solid fuel use by place of cooking Percent distribution of household members in households using solid fuels by place of cooking, Sudan MICS, 2014 Background characteristics Place of cooking: Number of household members in households using solid fuels for cooking In the house: In a separate room used as kitchen In the house: Else- where in the house In a separate building Outdoors Other place Missing Sudan 67.8 18.8 4.7 5.6 2.7 0.3 57,587 State Northern 83.8 13.7 1.4 0.3 0.3 0.5 358 River Nile 78.1 21.1 0.0 0.7 .2 0.0 493 Red Sea 43.0 38.5 1.8 13.0 1.8 1.8 1,425 Kassala 31.1 43.8 4.1 17.4 3.2 0.4 3,076 Gadarif 54.7 29.3 0.5 8.7 6.7 0.1 3,481 Khartoum 60.3 28.6 1.0 7.3 2.8 0.0 1,726 Gezira 54.5 34.7 0.8 3.3 5.1 1.6 2,633 White Nile0 41.1 52.1 4.0 1.4 0.3 1.1 1,915 Sinnar 48.0 40.3 1.2 10.3 0.1 0.0 2,161 Blue Nile 51.1 26.4 3.2 18.4 0.8 0.1 3,623 North Kordofan 77.6 9.5 10.1 0.9 1.9 0.1 5,249 South Kordofan 46.0 27.8 17.1 6.6 2.1 0.4 2,909 West Kordofan 86.4 5.2 2.5 5.1 0.5 0.3 5,648 North Darfur 87.4 2.2 6.5 0.7 3.1 0.1 7,571 West Darfur 67.0 11.5 18.1 2.3 0.9 0.2 3,014 South Darfur 82.4 10.5 0.4 2.0 4.2 0.5 7,538 Central Darfur 68.6 14.8 1.9 9.7 4.8 0.3 1,645 East Darfur 79.6 10.9 0.8 3.7 4.8 0.2 3,123 Area Urban 69.8 18.8 3.6 4.0 3.2 0.6 12,402 Rural 67.3 18.8 5.0 6.1 2.6 0.3 45,185 Education of household head None 63.7 21.1 4.6 7.4 3.0 0.3 34,745 Primary 72.3 16.5 4.7 3.3 2.9 0.3 14,694 Secondary 76.3 12.6 6.1 2.5 1.7 0.7 6,523 Higher 83.5 12.2 3.0 0.8 0.5 0.0 1,101 Missing/DK 77.5 18.3 3.5 0.3 0.3 0.0 525 Wealth index quintile Poorest 73.1 14.3 4.8 4.3 3.4 0.1 19,761 102 Background characteristics Place of cooking: Number of household members in households using solid fuels for cooking In the house: In a separate room used as kitchen In the house: Else- where in the house In a separate building Outdoors Other place Missing Second 63.3 21.0 5.5 7.3 2.6 0.3 19,167 Middle 63.2 23.5 4.1 6.5 2.4 0.3 13,032 Fourth 74.2 16.9 3.5 2.4 2.1 0.8 4,798 Richest 83.8 8.5 1.6 1.1 0.0 4.9 829 103 VII. Water and Sanitation Safe drinking water is a basic necessity for good health. Unsafe drinking water can be a significant determinant of diseases such as cholera, typhoid, and schistosomiasis. Drinking water can also be contaminated with chemical and physical contaminants with harmful effects on human health. In addition to preventing disease, improved access to drinking water may be particularly important for women and children, especially in rural areas, who bear the primary responsibility for carrying water, often for long distances.21 Inadequate disposal of human excreta and personal hygiene are associated with a range of diseases including diarrhoeal diseases, polio, and are important determinants of malnutrition such as stunting. Improved sanitation can reduce diarrhoeal disease by more than a third22, and can substantially lessen the adverse health impacts of other disorders among millions of children in many countries. The MDG target (7, C) is to reduce by half, between 1990 and 2015, the proportion of people without sustainable access to safe drinking water and basic sanitation. For more details on water and sanitation and to access some reference documents, please visit data.unicef.org23 or the website of the WHO/UNICEF Joint Monitoring Programme for Water Supply and Sanitation24. 7.1 Use of Improved Water Sources The water and sanitation module was adapted and customized to observe the water sources in Sudan. The population using improved sources of drinking water are those using any of the following types of supply: piped water (into dwelling, compound, yard or plot, to neighbour, public tap/standpipe), tube well/borehole, protected well, protected spring and rainwater collection. Bottled water is considered as an improved water source only if the household is using an improved water source for handwashing and cooking. The rain water collection source is not part of Sudan’s MICS 2014 questionnaire (reference to questionnaire in page 340). The distribution of the population by main source of drinking water is shown in Table WS.1. with the indicator: percent distribution of household population according to main sources of drinking water and percentage of household population using improved drinking water sources. Table WS.1 shows use of improved water sources. Overall, 68.0 percent of the population uses an improved source of drinking water. The situation in Gadarif State is considerably worse than in other states; only 27.7 percent of the population in this state gets its drinking water from an improved source. The table also shows that 10.2 percent of the household population used drinking water that was piped into dwelling while 26.7 percent used drinking water that was piped into their compound Overall, more than two-fifths (41.4 percent) of the household members used drinking water that was piped into their dwelling or into their compound, yard or plot or into public tap/standpipe. Other improved sources of drinking water used by the household members include water yard/hand pump 21 WHO/UNICEF. 2012. Progress on Drinking water and Sanitation: 2012 update. 22 Cairncross, S. 2010. Water, sanitation and hygiene for the prevention of diarrhoea. Int. J. Epidemiology 39: i193-i205. 23 http://data.unicef.org/water-sanitation 24 http:// www.wssinfo.org 104 (22.4 percent), protected/covered well (3.1 percent), and protected spring (0.1 percent) and bottled water (0.1 percent). See also Figure WS.1 Figure WS.1: Distribution of household members by source of drinking water, Sudan MICS, 2014 Access to improved water sources by state is shown in Figure WS.1a). Differences exist between access to improved water sources by urban households 78.3 percent compared 63.5 percent of households in rural areas. Among wealth index quintiles, significant differences were observed; ranging from 45.5 percent in poorest households to 96.0 percent in the richest households (WS. Figure 1b). Piped into dwelling, yard or plot 37% Public tap/standpipe 3% Tubewell/ borehole 4% Protected well or spring 3% Unprotected well or spring 7% Surface water 24% Other unimproved 1% 105 F i g u r e W S . 1 a : H o u s e h o l d m e m b e r s w i t h a c c e s s t o i m p r o v e d w a t e r s o u r c e s b y S t a t e , Su d a n M I C S , 2 0 1 4 F i g u r e W S . 1 b : H o u s e h o l d m e m b e r s w i t h a c c e s s t o i m p r o v e d w a t e r s o u r c e s b y u r b a n a n d r u r a l r e s i d e n c e a n d b y w e a l t h i n d e x q u i n t i l e s , S u d a n M I C S , 2 0 1 4 27.7 32.7 33.2 45.1 46.6 50.6 50.6 57.2 60.1 67.5 68.0 69.8 71.3 86.0 86.9 88.3 88.7 88.9 93.8 .0 10.0 20.0 30.0 40.0 50.0 60.0 70.0 80.0 90.0 100.0 Gadarif White Nile Red Sea East Darfor South Darfor Central Darfor North Darfor Kassala South Kordofan West Darfor Sudan North Kordofan Blue Nile West Kordofan Khartoum River Nile Sinnar Gezira Northern 68.0 78.3 63.5 45.5 53.4 60.0 85.3 96.0 .0 20.0 40.0 60.0 80.0 100.0 120.0 Sudan Urban Rural Poorest Second Middle Fourth Richest 106 Table WS.1: Use of improved water sources Percent distribution of household population according to main source of drinking water and percentage of household population using improved drinking water sources, Sudan MICS, 2014 Backgroun d characteri stics Main source of drinking water Percent age using improve d sources of drinking water [1] Number of househol d members Improved sources Unimproved sources Piped into dwellin g Piped into compo und, yard or plot Pipe d to neig hbo ur Public tap / stand pipe Elevat ed tank, hand pump (Kharj aka) Protec ted well Protec ted spring Bottle d water [a] Un- prote cted well Un- protect ed spring Filtere d Surfac e water Un- Filtere d Surfac e water Tanker- truck from protecte d sources Tanker- truck from un- protecte d sources Tanker -truck from un- known source s Bottled water [a] Other Miss ing Sudan 10.2 26.7 2.9 2.6 22.4 3.1 0.1 0.0 5.3 1.3 2.4 8.3 11.5 1.9 0.3 0.0 0.9 0.2 68.0 98,883 State Northern 12.7 59.2 1.4 1.6 17.9 1.1 0.0 0.0 0.1 0.0 0.7 2.2 2.2 0.3 0.0 0.0 0.8 0.0 93.8 2,181 River Nile 40.3 33.8 2.9 0.8 8.9 1.6 0.0 0.0 0.6 0.0 0.3 5.8 3.3 1.7 0.0 0.0 0.0 0.0 88.3 3,715 Red Sea 7.3 4.8 1.4 1.5 14.9 2.9 0.0 0.4 0.8 0.3 0.0 0.2 55.8 0.0 7.9 1.2 0.3 0.4 33.2 2,489 Kassala 2.9 25.3 6.2 9.9 7.3 5.6 0.0 0.0 0.5 0.3 6.4 19.6 12.8 2.6 0.0 0.0 0.7 0.0 57.2 4,117 Gadarif 1.8 4.3 .2 13.5 6.4 1.4 0.0 0.0 1.7 0.0 4.3 20.7 35.7 8.8 0.6 0.0 0.0 0.5 27.7 5,005 hartoum 22.3 57.3 2.4 0.8 4.0 0.0 0.0 0.1 0.0 0.0 0.0 0.0 9.5 0.2 0.0 0.0 3.4 0.0 86.9 13,830 Gezira 18.1 62.7 5.3 0.2 2.3 0.2 0.0 0.1 0.1 0.0 2.2 1.6 6.2 0.9 0.0 0.0 0.1 0.0 88.9 16,270 White Nile 8.4 15.6 3.1 4.5 0.3 0.5 0.4 0.0 4.9 2.0 8.0 23.9 23.0 5.0 0.1 0.0 0.5 0.0 32.7 5,016 Sinnar 5.0 31.9 9.2 5.5 36.0 1.0 0.2 0.0 0.0 0.3 2.0 2.7 3.6 2.3 0.0 0.0 0.0 0.3 88.7 3,763 Blue Nile 5.8 31.0 6.0 0.7 27.7 0.0 0.1 0.0 0.7 1.0 1.1 20.0 4.4 1.5 0.0 0.0 0.0 0.0 71.3 4,094 North Kordofan 2.0 10.3 4.0 4.4 38.2 11.0 0.0 0.0 6.0 0.0 1.8 6.2 15.7 0.5 0.0 0.0 0.0 0.0 69.8 6,359 South Kordofan 1.0 1.2 0.6 0.3 49.5 7.4 0.0 0.0 4.4 1.2 1.2 8.2 24.6 0.0 0.0 0.0 0.1 0.2 60.1 2,983 West Kordofan 0.1 0.2 0.0 0.9 83.3 1.5 0.0 0.0 6.4 0.7 2.8 1.0 1.2 0.1 0.4 0.0 0.1 1.3 86.0 5,745 North Darfur 2.6 0.2 0.6 0.1 38.9 8.3 0.0 0.0 15.2 3.7 4.8 19.0 5.6 0.7 0.1 0.0 0.0 0.2 50.6 7,776 West Darfur 8.1 7.2 1.8 5.0 36.5 8.9 0.1 0.0 19.8 9.2 00.4 1.4 1.0 0.2 0.0 0.0 0.1 0.3 67.5 3,023 107 Backgroun d characteri stics Main source of drinking water Percent age using improve d sources of drinking water [1] Number of househol d members Improved sources Unimproved sources Piped into dwellin g Piped into compo und, yard or plot Pipe d to neig hbo ur Public tap / stand pipe Elevat ed tank, hand pump (Kharj aka) Protec ted well Protec ted spring Bottle d water [a] Un- prote cted well Un- protect ed spring Filtere d Surfac e water Un- Filtere d Surfac e water Tanker- truck from protecte d sources Tanker- truck from un- protecte d sources Tanker -truck from un- known source s Bottled water [a] Other Miss ing South Darfur 4.3 .4 0.7 2.7 32.9 5.3 0.2 0.1 24.6 5.4 1.9 8.4 8.0 4.4 0.3 0.0 0.2 0.2 46.6 7,712 Central Darfur 1.4 1.3 0.7 1.5 33.4 11.1 1.4 0.0 12.3 5.9 0.3 17.1 .2 0.0 0.0 0.0 13.1 0.4 50.6 1,646 East Darfur 1.7 4.9 1.5 1.2 35.7 0.1 0.0 0.0 0.4 0.0 3.9 16.6 25.2 6.9 0.0 0.0 2.0 0.0 45.1 3,158 Area Urban 19.8 37.6 4.7 3.3 11.4 1.4 0.0 0.1 0.8 0.0 .4 0.7 16.1 1.0 0.7 0.1 1.7 0.1 78.3 30,476 Rural 5.9 21.9 2.1 2.3 27.3 3.9 0.1 0.0 7.3 1.9 3.3 11.6 9.4 2.2 0.1 0.0 0.5 0.2 63.5 68,407 Education of the househol d head None 4.3 17.6 2.7 2.8 28.3 3.8 0.1 0.1 6.9 2.3 3.0 11.9 12.5 2.3 0.2 0.0 1.0 0.2 59.7 45,740 Primary 9.1 31.0 3.8 2.9 21.2 2.9 0.1 0.0 4.7 0.7 2.2 6.7 11.7 1.7 0.3 0.0 0.7 0.3 71.0 28,007 Secondary 19.9 38.2 2.5 2.0 14.1 2.1 0.0 0.0 3.2 0.4 1.7 3.6 9.3 1.4 0.4 0.1 1.1 0.0 78.8 18,812 Higher 30.9 43.5 1.9 1.3 7.1 1.7 0.0 0.2 1.2 0.0 0.6 2.0 7.8 0.5 0.5 0.1 0.4 0.4 86.5 5,564 Missing/ DK 8.3 12.8 0.6 2.6 30.8 2.3 0.0 0.0 7.5 1.4 0.7 8.3 22.8 1.9 0.0 0.0 0.0 0.1 57.4 761 Wealth index quintile Poorest 0.0 0.0 0.0 1.2 38.2 5.8 0.2 0.0 17.4 4.8 3.7 17.0 8.1 2.7 0.0 0.0 0.7 0.2 45.5 19,775 Second 0.2 0.0 0.6 4.7 42.5 5.2 0.2 0.0 6.3 1.7 4.1 13.9 15.4 3.8 0.2 0.0 0.9 0.4 53.4 19,776 Middle 2.6 17.0 7.3 5.1 24.5 3.4 0.0 0.1 2.4 0.2 3.6 8.2 22.1 1.8 0.4 0.0 1.0 0.3 60.0 19,779 Fourth 12.9 58.7 5.4 1.4 5.8 1.0 0.0 0.0 0.1 0.0 0.7 1.7 9.3 0.8 0.6 0.0 1.4 0.0 85.3 19,773 Richest 35.2 58.0 1.2 .4 1.0 0.1 0.0 0.2 0.1 0.0 0.0 0.4 2.5 0.2 0.3 0.2 0.3 0.0 96.0 19,781 1 MICS indicator 4.1; MDG indicator 7.8 - Use of improved drinking water sources 108 Use of household water treatment is presented in Table WS.2. Households were asked about ways they may be treating water at home to make it safer to drink. Boiling water, adding bleach or chlorine, using a water filter, and using solar disinfection are considered as effective treatment of drinking water. The table shows water treatment by all household members and the percentage of those living in households using unimproved water sources but using appropriate water treatment methods. The data indicate no significant variation between urban and rural areas in terms of water treatment for drinking; the percentage of urban households using unimproved sources of drinking water and reporting treatment of drinking water was 3.7 percent compared with 4.2 percent of rural households. The overall percent of the households in the country who are treating water from unimproved sources is 4.1 percent with wide disparities among the states. Gezira state reported the highest treatment of water for drinking purposes at 11.5 percent of households using unimproved sources, followed by Red Sea state at 8.5. Households in South Kordofan state reported almost zero percent for water treatment. There was not much variation between wealth quintiles for this indicator with 2.9 percent of households using unimproved sources in the poorest quintilereporting an appropriate water treatment method compared to 7.0 percent of households in the richest quintile. Table WS.2: Household water treatment Percentage of household population by drinking water treatment method used in the household, and for household members living in households where an unimproved drinking water source is used, the percentage who are using an appropriate treatment method, Sudan MICS, 2014 Background characteristics Water treatment method used in the household Number of househol d members Percent of househld’ members in househol ds using unimprov ed drinking water sources and using an appropria te water treatment method [1] Numbe r of househ old membe rs in househ olds using unimpr oved drinking water sources None Boil Add bleach / chlorin e Strain through a cloth Use wate r filter Solar dis- infectio n Let it stand and settle Other Don't know Sudan 70.9 2.2 1.3 4.0 0.8 0.2 22.4 1.4 0.1 98,883 4.1 31,603 State Northern 36.7 0.1 0.8 0.9 1.9 0.1 58.7 4.5 0.0 2,181 7.7 135 River Nile 6.6 1.1 2.8 1.1 0.6 0.2 92.2 4.6 0.0 3,715 1.2 435 Red Sea 64.3 4.7 4.0 20.7 0.4 0.0 16.0 0.0 0.2 2,489 8.5 1,663 Kassala 96.7 0.0 1.1 0.4 1.2 0.0 0.6 0.1 0.0 4,117 3.2 1,762 Gadarif 80.5 0.1 6.1 1.4 0.0 0.2 11.8 0.7 0.0 5,005 8.0 3,618 Khartoum 73.0 1.1 0.7 0.4 2.3 0.5 21.1 1.5 0.1 13,830 1.1 1,810 Gezira 40.9 10.2 0.0 2.4 1.1 0.2 54.4 1.7 0.0 16,270 11.5 1,806 White Nile 66.1 0.9 4.4 25.5 0.2 0.4 7.3 1.4 0.0 5,016 4.9 3,374 Sinnar 85.6 0.5 0.4 2.6 0.3 0.0 10.0 1.9 0.0 3,763 2.8 426 Blue Nile 85.3 0.0 0.5 1.7 0.1 0.0 12.5 3.1 0.0 4,094 1.0 1,176 North Kordofan 85.8 0.1 0.7 2.7 0.0 0.4 10.1 0.8 0.0 6,359 1.7 1,922 109 Background characteristics Water treatment method used in the household Number of househol d members Percent of househld’ members in househol ds using unimprov ed drinking water sources and using an appropria te water treatment method [1] Numbe r of househ old membe rs in househ olds using unimpr oved drinking water sources None Boil Add bleach / chlorin e Strain through a cloth Use wate r filter Solar dis- infectio n Let it stand and settle Other Don't know South Kordofan 71.5 0.0 1.1 4.5 0.0 0.1 21.5 1.2 0.5 2,983 0.1 1,191 West Kordofan 97.2 0.1 0.0 0.9 0.0 0.1 0.9 0.3 0.4 5,745 0.0 803 North Darfur 85.6 0.2 2.2 7.7 0.0 0.1 3.3 0.8 0.1 7,776 4.3 3,838 West Darfur 51.0 0.0 0.0 3.6 2.8 0.5 42.7 0.6 0.0 3,023 1.6 982 South Darfur 90.4 0.8 0.9 2.8 0.0 0.1 6.1 0.0 0.0 7,712 1.9 4,115 Central Darfur 94.8 0.0 0.9 3.0 0.1 0.0 0.8 0.4 0.0 1,646 0.7 814 East Darfur 89.0 0.4 2.3 2.7 0.6 0.1 0.2 5.1 0.1 3,158 5.2 1,735 Area Urban 74.7 1.3 1.6 3.0 1.3 0.2 19.0 1.0 0.1 30,476 3.7 6,612 Rural 69.3 2.6 1.2 4.5 0.5 0.2 23.9 1.6 0.0 68,407 4.2 24,991 Main source of drinking water Improved 69.8 2.6 0.8 1.4 1.0 0.2 26.4 1.0 0.1 67,280 . . Unimproved 73.3 1.1 2.5 9.6 0.3 0.2 13.9 2.3 0.1 31,603 4.1 31,603 Education of household head None 75.0 1.7 1.4 4.8 0.4 0.1 17.9 1.4 0.1 45,740 4.0 18,414 Primary 68.8 2.4 1.3 3.4 0.4 0.5 25.1 1.4 0.1 28,007 5.1 8,128 Secondary 65.4 2.8 1.2 3.7 1.2 0.1 28.8 1.3 0.1 18,812 3.0 3,984 Higher 65.0 2.8 2.2 2.1 3.6 0.0 25.5 2.3 0.0 5,564 5.1 753 Missing/DK 84.9 0.0 0.0 2.0 0.0 0.0 10.6 1.9 0.0 761 0.0 324 Wealth index quintile Poorest 84.4 0.3 1.3 4.4 0.2 0.1 8.3 1.4 0.0 19,775 2.9 10,786 Second 80.9 1.0 1.5 5.0 0.4 0.1 11.6 1.4 0.2 19,776 4.4 9,213 Middle 71.6 2.0 1.3 6.2 0.4 0.2 20.6 1.3 0.1 19,779 4.3 7,914 Fourth 58.1 3.2 1.1 2.9 0.4 0.3 37.3 1.4 0.0 19,773 6.4 2,898 Richest 59.6 4.4 1.6 1.6 2.5 0.3 34.0 1.6 0.0 19,781 7.0 792 [1] MICS indicator 4.2 - Water treatment na: not applicable The amount of time it takes household members to obtain water in Sudan is presented in Table WS.3. The person who usually collects the water is presented in Table WS.4. Note that in Table WS.3, household members using water on premises are also shown and for Table WS.4, the results refer to 110 one roundtrip from the household to the drinking water source and that information on the number of trips made in one day was not collected. Table WS.3 shows that for 41.1 percent of the household population, the drinking water source is on premises. The availability of water on premises is associated with greater use, better family hygiene practices and better health outcomes. For a water collection round trip of 30 minutes or more it has been observed that households carry progressively less water and are likely to compromise on the minimal basic drinking water needs of the household.25 For almost a third (31.4 percent) of the household population, it takes the household more than 30 minutes to get to the water source and bring water, on the other hand only 14.5 percent of those using an improved drinking water source spend 30 minutes or more per round trip to get water into their households. In rural areas a higher percentage of household members live in households that spend more time in collecting water compared to those in urban areas; 63 percent of members in urban households have improved drinking water sources on their premises versus 31 percent of members of rural households having access to improved drinking water sources on their premises. One striking finding is that households in Northern (90.6 percent), Gezira (86.1 percent), River Nile (84.4 percent), and Khartoum (82.3 percent) states have greater access to improved water sources on their premises than the other states. Households in the West Kordofan State (1.1 percent) have the least access to improved water sources for drinking on the premises of their households. Table WS.3 indicates that the percent of household with improved water on premises increased with the level education of the household head. The percent of household heads with no education who have improved water on premises is 25.5 percent compared to 77.5 percent for household head with higher education. Similarly the wealth index analysis validated the correlation between water on premises and weealth; households in the richest quintile, 95.5 percent of them had improved water on their premises, compared with 0.3 percent of households in the poorest quintile. Table WS.3: Time to source of drinking water Percent distribution of household population according to time to go to source of drinking water, get water and return, for users of improved and unimproved drinking water sources, Sudan MICS, 2014 Background characteristics Time to source of drinking water Number of household members Users of improved drinking water sources Users of unimproved drinking water sources Water on premises Less than 30 minutes 30 minutes or more Missing / DK Water on premises Less than 30 minutes 30 minutes or more Missing/ DK Sudan 41.1 10.7 14.5 1.7 2.3 8.3 16.9 4.5 98,883 State Northern 90.6 1.2 1.3 0.7 2.1 1.1 2.3 0.7 2,181 River Nile 84.4 0.6 2.7 .6 5.7 0.7 4.7 0.7 3,715 Red Sea 14.3 5.0 11.5 2.8 .2 8.9 14.3 43.0 2,489 Kassala 34.8 9.9 9.7 2.8 0.3 11.9 20.3 10.4 4,117 Gadarif 8.9 13.4 3.4 2.0 35.4 15.0 17.6 4.3 5,005 Khartoum 82.3 2.4 1.2 1.0 0.2 2.6 2.3 8.0 13,830 Gezira 86.1 0.8 1.8 0.1 0.6 5.4 4.9 0.1 16,270 25 Cairncross, S and Cliff, JL. 1987. Water use and Health in Mueda, Mozambique. Transactions of the Royal Society of ,Tropical Medicine and Hygiene 81: 51-4. 111 Background characteristics Time to source of drinking water Number of household members Users of improved drinking water sources Users of unimproved drinking water sources Water on premises Less than 30 minutes 30 minutes or more Missing / DK Water on premises Less than 30 minutes 30 minutes or more Missing/ DK White Nile 27.7 2.7 1.9 0.4 0.0 24.4 31.7 11.1 5,016 Sinnar 46.0 12.8 29.7 0.2 0.1 2.0 8.7 0.5 3,763 Blue Nile 43.0 9.2 18.9 0.2 0.1 6.8 21.3 0.5 4,094 North Kordofan 16.9 25.0 18.1 9.9 0.2 13.8 14.4 1.8 6,359 South Kordofan 2.9 28.2 24.3 4.6 0.1 18.2 20.8 0.8 2,983 West Kordofan 1.1 33.5 48.7 2.7 0.0 4.3 7.7 2.0 5,745 North Darfur 3.6 10.2 34.7 2.2 0.7 6.5 38.7 3.5 7,776 West Darfur 17.1 20.2 28.7 1.5 0.0 7.5 24.1 0.9 3,023 South Darfur 8.6 14.6 23.1 0.4 0.3 9.2 41.0 2.9 7,712 Central Darfur 4.0 23.4 22.5 0.7 0.1 14.7 32.7 1.9 1,646 East Darfur 8.2 19.3 16.8 0.8 0.1 15.6 33.9 5.3 3,158 Area Urban 63.1 5.5 7.0 2.7 3.1 3.9 5.6 9.1 30,476 Rural 31.3 13.0 17.9 1.3 2.0 10.2 21.9 2.4 68,407 Education of household head None 25.5 13.6 18.9 1.7 2.2 10.3 22.8 4.9 45,740 Primary 45.3 10.0 13.8 1.9 2.4 7.7 14.7 4.3 28,007 Secondary 62.7 7.0 7.5 1.7 2.4 5.3 9.2 4.2 18,812 Higher 77.5 3.8 4.4 0.9 1.5 3.2 5.4 3.3 5,564 Missing/DK 23.1 6.2 27.2 1.0 8.1 15.5 14.7 4.3 761 Wealth index quintile Poorest .3 13.8 30.7 .7 0.2 10.8 41.8 1.8 19,775 Second 2.0 23.6 25.5 2.4 3.4 15.7 22.8 4.7 19,776 Middle 28.3 13.7 14.0 4.0 4.4 11.6 14.7 9.3 19,779 Fourth 79.3 2.2 2.2 1.6 3.0 2.6 4.1 5.0 19,773 Richest 95.6 0.2 0.2 0.0 0.6 0.6 0.9 1.7 19,781 Table WS.4 shows that more than half of the household (57.7 percent) are without water on premises, with 33.7 percent in the urban areas and 67.9 percent in rural areas. The survey findings indicated that 36.0 percent of households had an adult female primarily responsible for collecting drinking water for the household when the source of drinking water is not on the premises. There was no significant difference between adult men (35.5 percent) on this indicator. Similarly, responsibility of children less than 15 years of age for collecting drinking water for the households was 10.8 percent and 11.3 percent for female and male children respectively. The proportion of adult women collecting drinking water for the household was significantly lower (21.3 percent) than adult males (46.7 percent) in households where the head of the household had higher educational level collecting drinking water for the household. 112 Table WS.4: Persons collecting water: Percentage of households without drinking water on premises, and percent distribution of households without drinking water on premises according to the person usually collecting drinking water used in the household, Sudan MICS, 2014 Background characteristic s Percentag e of household s without drinking water on premises Number of household s Person usually collecting drinking water Number of household s without drinking water on premises Adult woman (age 15+ years) Adult man (age 15+ years) Female child (under 15) Male child (under 15) DK Miss- ing Sudan 57.7 16,801 36.0 35.5 10.8 11.3 5.4 1.0 9,696 State Northern 6.3 423 56.0 38.2 2.4 3.4 0.0 0.0 27 River Nile 11.1 666 42.8 28.2 10.8 13.6 3.3 1.3 74 Red Sea 85.2 519 5.6 63.5 .9 4.4 21.1 4.5 443 Kassala 66.8 722 16.5 55.0 8.3 12.2 6.5 1.4 482 Gadarif 56.7 858 24.0 47.8 14.2 12.7 0.4 0.9 487 Khartoum 18.4 2,317 11.7 38.1 4.3 28.3 15.8 1.8 427 Gezira 14.1 2,629 42.2 34.0 7.8 14.3 0.4 1.2 370 White Nile 73.5 874 16.0 32.2 11.5 16.9 22.2 1.1 642 Sinnar 54.8 661 47.9 25.7 12.9 12.4 0.7 0.5 362 Blue Nile 59.0 656 29.4 39.7 15.2 15.1 0.3 0.3 387 North Kordofan 84.5 1,125 28.5 47.1 9.2 10.9 3.5 0.8 951 South Kordofan 96.5 462 58.6 23.4 8.3 5.5 3.8 0.4 446 West Kordofan 99.0 1,003 32.2 44.0 10.1 7.9 4.2 1.6 993 North Darfur 96.0 1,243 46.7 32.3 9.8 9.5 1.4 0.3 1,193 West Darfur 87.0 553 61.8 11.4 14.9 9.1 2.3 0.6 482 South Darfur 91.5 1,282 48.1 26.8 14.3 8.0 2.2 0.6 1,173 Central Darfur 96.5 299 65.0 11.7 15.7 5.6 1.4 0.5 289 East Darfur 92.3 508 36.7 24.5 15.8 17.2 5.7 0.0 469 Area Urban 33.7 5,000 19.4 46.7 5.5 9.0 16.9 2.6 1,683 Rural 67.9 11,801 39.6 33.2 11.9 11.7 3.0 0.6 8,013 Education of household head None 74.4 7,799 38.8 32.6 12.7 11.0 4.1 0.8 5,806 Primary 52.8 4,730 34.7 38.5 9.0 11.5 5.1 1.1 2,499 Secondary 35.0 3,137 27.4 42.4 6.3 11.8 11.0 1.1 1,099 Higher 20.8 1,013 21.3 46.7 3.9 12.4 12.9 2.7 211 Missing/DK 67.6 122 34.0 29.2 12.3 14.7 8.4 1.4 82 Wealth index quintile Poorest 99.6 3,368 46.0 29.0 13.2 10.6 0.9 0.2 3,354 Second 95.0 3,592 39.4 34.5 11.7 10.3 3.3 0.7 3,411 Middle 67.2 3,339 23.7 42.0 8.5 14.3 9.6 1.9 2,243 113 Background characteristic s Percentag e of household s without drinking water on premises Number of household s Person usually collecting drinking water Number of household s without drinking water on premises Adult woman (age 15+ years) Adult man (age 15+ years) Female child (under 15) Male child (under 15) DK Miss- ing Fourth 17.7 3,209 12.2 50.9 2.4 10.2 22.1 2.1 568 Richest 3.6 3,293 4.0 53.4 1.4 4.9 30.6 5.8 120 [1] MICS indicator 4.1; MDG indicator 7.8 - Use of improved drinking water sources [a] Households using bottled water as the main source of drinking water are classified into improved or unimproved drinking water users according to the water source used for other purposes such as cooking and handwashing. 7.2 Use of Improved Sanitation An improved sanitation facility is defined as one that hygienically separates human excreta from human contact. Improved sanitation facilities include flush or pour flush to a piped sewer system, septic tank, or pit latrine; ventilated improved pit latrine, pit latrine with slab, and use of a composting toilet. The data on the use of improved sanitation facilities in the country are provided in Figure WS.2 and Table WS.5. 114 Figure WS.2a: Households using Improved sanitation facility by state, Sudan MICS, 2014 11.6 12.6 13.8 17.0 18.3 19.1 20.9 28.9 29.0 30.0 34.1 38.8 40.9 42.8 49.9 56.0 61.9 85.4 95 28.2 69.3 0.0 10.0 20.0 30.0 40.0 50.0 60.0 70.0 80.0 90.0 100.0 West Kordofan Gadarif North Darfur East Darfur West Darfur Central Darfur South Kordofan Sinnar South Darfur North Kordofan Kassala White Nile Sudan Blue Nile Gezira Red Sea River Nile Khartoum Northern Rural Urban Percent 115 Table WS.5: Types of sanitation facilities Percent distribution of household population according to type of toilet facility used by the household, Sudan MICS, 2014 Background characteristics Type of toilet facility used by household Number of household members Improved sanitation facility Unimproved sanitation facility Open defecation (no facility, bush field) Flush to piped sewer system Flush to septic tank Flush to pit latrine Flush to some- where else Flush to unknown place / Not sure / DK where Ventilated Improved Pit latrine (VIP) Pit latrine with slab Composting toilet Pit latrine without slab / Open pit Bucket Other Missing/DK Sudan 0.8 4.9 1.9 0.2 0.1 11.7 21.0 0.3 27.6 0.0 2.0 0.2 29.2 98,883 State Northern 0.0 9.8 2.5 0.3 0.0 27.9 54.5 0.0 0.9 0.0 1.8 0.0 2.2 2,181 River Nile 0.5 2.9 1.6 0.0 0.0 6.6 50.3 0.0 26.6 0.0 0.4 0.1 11.0 3,715 Red Sea 1.0 11.5 4.1 0.3 0.0 31.5 7.6 0.0 6.6 0.0 2.0 0.6 35.0 2,489 Kassala 0.0 8.1 2.0 0.0 0.0 9.8 11.9 2.3 20.4 0.0 0.5 0.1 44.9 4,117 Gadarif 0.0 0.1 0.8 0.1 0.0 3.3 8.3 0.0 43.8 0.0 0.3 0.2 43.0 5,005 Khartoum 2.8 16.0 2.1 0.5 0.0 16.5 47.4 0.1 10.4 0.0 2.3 0.2 1.7 13,830 Gezira 0.8 3.2 2.3 0.0 0.0 13.1 30.5 0.0 14.0 0.2 3.6 0.1 32.4 16,270 White Nile 2.5 4.9 1.9 0.1 0.1 16.2 13.1 0.0 15.9 0.0 2.0 0.2 43.0 5,016 Sinnar 0.5 3.2 1.9 0.0 0.0 4.5 16.9 1.9 33.1 0.0 3.0 0.3 34.6 3,763 Blue Nile 0.0 2.1 3.6 0.0 0.0 1.7 35.4 0.0 45.0 0.0 0.8 0.0 11.4 4,094 North Kordofan 0.0 3.6 2.2 0.0 0.0 12.3 11.9 0.0 22.3 0.0 2.9 0.4 44.5 6,359 South Kordofan 0.8 1.1 3.3 0.0 0.2 9.3 5.7 0.5 37.5 0.0 0.8 0.0 40.7 2,983 West Kordofan 0.3 0.1 0.7 0.1 0.0 4.4 5.6 0.4 67.2 0.0 0.2 1.3 19.7 5,745 North Darfur 0.0 0.4 0.7 0.0 0.0 3.3 7.9 1.5 40.1 0.1 4.5 0.4 41.1 7,776 West Darfur 0.0 3.2 2.0 0.0 0.0 7.8 5.3 0.0 48.6 0.0 1.3 0.0 31.8 3,023 South Darfur 0.6 3.5 2.0 0.8 0.7 20.1 1.2 0.1 28.7 0.0 0.9 0.0 41.3 7,712 Central Darfur 2.0 0.3 1.7 0.0 0.0 9.7 5.4 0.0 35.2 0.0 1.0 0.2 44.6 1,646 116 Background characteristics Type of toilet facility used by household Number of household members Improved sanitation facility Unimproved sanitation facility Open defecation (no facility, bush field) Flush to piped sewer system Flush to septic tank Flush to pit latrine Flush to some- where else Flush to unknown place / Not sure / DK where Ventilated Improved Pit latrine (VIP) Pit latrine with slab Composting toilet Pit latrine without slab / Open pit Bucket Other Missing/DK East Darfur 0.1 1.0 0.7 0.0 0.0 11.9 3.2 0.1 55.4 0.0 0.7 0.2 26.6 3,158 Area Urban 2.4 14.0 4.6 0.5 0.2 17.6 29.7 0.3 23.6 0.0 1.9 0.2 5.0 30,476 Rural 0.1 0.8 0.7 0.0 0.0 9.1 17.1 0.4 29.5 .1 2.1 0.2 40.0 68,407 Education of household head None 0.5 1.5 0.8 0.1 0.0 9.7 13.7 0.3 31.1 0.0 1.7 0.2 40.4 45,740 Primary 0.4 3.7 1.8 0.1 0.0 12.3 21.7 0.5 28.0 .1 3.1 0.4 28.1 28,007 Secondary 1.9 8.7 4.1 0.4 0.2 15.5 33.2 0.3 23.1 0.0 1.4 0.2 11.1 18,812 Higher 2.8 26.2 4.6 0.3 0.4 12.3 36.1 0.1 12.5 0.0 0.8 0.3 3.6 5,564 Missing/DK 0.8 2.9 0.5 0.0 0.0 11.2 14.0 0.0 31.5 0.0 8.5 0.0 30.5 761 Wealth index quintile Poorest 0.0 0.0 0.0 0.0 0.0 4.6 1.2 0.5 30.2 0.0 1.8 0.1 61.6 19,775 Second 0.1 0.1 0.3 0.0 0.0 7.4 3.5 0.5 40.6 0.0 1.8 0.5 45.1 19,776 Middle 0.2 0.7 0.8 0.2 0.0 12.2 17.3 0.2 39.4 0.0 3.5 0.2 25.4 19,779 Fourth 0.6 2.8 2.0 0.1 0.1 18.8 38.1 0.2 21.1 .1 2.5 0.2 13.4 19,773 Richest 3.4 20.9 6.5 0.5 0.2 15.5 44.6 0.4 6.8 0.0 0.6 0.2 0.5 19,781 117 Over two-fifths (40.9 percent) of the population are living in households using improved sanitation facilities (Table WS.5), 69.3 percent of the households live in urban areas while 28.2 percent live in rural areas. Use of improved sanitation facilities varies across states ranging from residents of West Kordofan state (11.6 percent) to residents in the Norther state (95.0 percent). The table also indicates that use of improved sanitation facilities is strongly correlated with wealth with 6.2 percent access in poorest quintile of the population, followed by the second poorest (12.0 percent), the middle quintile (31.5 percent), fourth richest at (62.7 percent), and the richest at (91.9 percent). Access to improved sanitation is also positively associated with living in urban areas (69.3 percent) compared with residence in rural areas (28.2 percent). In rural areas, the population primarily uses pit latrines without slabs, or simply have no facilities. In contrast, the most common facilities in urban areas are flush toilets with connection to a sewage system or septic tank. use of ventilated Improved Pit (VIP) latrine widely varied across states with Red sea (31.5 percent) followed by Northern State (27.9 percent), and Blue Nile state (1.7) percent recording the least for use of VIP as an improved sanitation facility. About one in three of the households in Sudan practiced open defecation (no facility, bush field). Use The practice of open defecation ranged from 1.7 percent in Khartoum State to 44.9 percent in Kassala State. The MDGs and the WHO / UNICEF Joint Monitoring Programme (JMP) for Water Supply and Sanitation classify otherwise acceptable sanitation facilities which are public or shared between two or more households as unimproved. Therefore, “use of improved sanitation” is used both in the context of this report and as an MDG indicator to refer to improved sanitation facilities, which are not public or shared. Data on the use of improved sanitation are presented in Tables WS.6 and WS.7. As shown in Table WS.6, 32.9 percent of the household population is using an improved sanitation facility that is not shared. . Only 7.6 percent of households use an improved sanitation facility that is public or shared with other households. Urban households were more likely to share an improved sanitation facility than rural households (11.6 percent and 5.8 percent, respectively). Khartoum State recorded the highest percentage (15.6 percent) of households who use shared improved toilet facility compared with West Kordofan State (0.7 percent Use of an improved sanitation facility that is not shared is positively associated with the level of economic status of the household; ranging from 5.4 percent in the poorest quintile to 78.1 percent in the highest quintile 118 Table WS.6: Use and sharing of sanitation facilities Percent distribution of household population by use of private and public sanitation facilities and use of shared facilities, by users of improved and unimproved sanitation facilities, Sudan MICS, 2014 Background characteristics Users of improved sanitation facilities Users of unimproved sanitation facilities Open defecation (no facility, bush field) Number of household members Not shared [1] Public facility Shared by: 5 households or less Shared by: More than 5 households Missing/ DK Not shared Public facility Shared by: 5 households or less Shared by: More than 5 households Missing/ DK Sudan 32.9 0.4 6.2 1.0 0.4 23.8 0.7 4.6 0.6 0.3 29.2 98,883 State Northern 79.4 0.8 12.7 2.1 0.1 1.0 0.0 1.7 0.1 0.0 2.2 2,181 River Nile 49.8 1.2 9.2 1.1 0.5 23.5 0.1 3.3 0.1 0.0 11.0 3,715 Red Sea 52.4 0.2 1.5 1.1 0.7 8.1 0.2 .6 0.1 0.1 35.0 2,489 Kassala 29.3 0.1 2.7 1.2 0.7 19.9 0.1 1.0 0.1 0.0 44.9 4,117 Gadarif 9.8 0.0 1.1 0.9 0.9 36.0 0.1 5.8 0.9 1.4 43.0 5,005 Khartoum 66.4 1.7 15.5 1.3 0.4 8.8 00.6 3.3 0.1 0.1 1.7 13,830 Gezira 38.3 0.2 9.6 1.6 0.1 9.9 2.4 5.1 0.3 0.1 32.4 16,270 White Nile 29.8 0.1 7.7 0.7 0.5 12.4 0.2 4.5 1.0 0.1 43.0 5,016 Sinnar 18.6 0.1 9.1 1.1 0.0 22.2 0.1 12.5 1.4 0.2 34.6 3,763 Blue Nile 39.7 0.0 3.1 0.0 0.0 38.4 0.2 6.7 0.5 0.1 11.4 4,094 North Kordofan 25.0 0.3 3.1 1.4 0.1 15.9 0.3 7.5 1.7 0.2 44.5 6,359 South Kordofan 14.3 0.2 4.5 0.9 1.1 27.2 0.5 7.5 1.8 1.4 40.7 2,983 West Kordofan 10.4 0.1 0.4 0.2 0.5 64.7 0.3 2.3 0.8 0.6 19.7 5,745 North Darfur 12.3 0.1 0.8 0.4 0.2 43.2 0.0 1.9 0.0 0.1 41.1 7,776 West Darfur 16.0 0.1 1.4 0.4 0.3 44.9 0.8 2.4 1.4 0.5 31.8 3,023 South Darfur 24.7 0.1 2.8 1.0 0.4 21.8 0.6 6.0 0.9 0.4 41.3 7,712 Central Darfur 15.8 0.6 1.8 0.8 0.0 25.9 1.8 5.8 2.1 0.8 44.6 1,646 East Darfur 14.4 0.1 1.8 0.3 0.3 50.2 0.6 4.2 1.2 0.2 26.6 3,158 119 Background characteristics Users of improved sanitation facilities Users of unimproved sanitation facilities Open defecation (no facility, bush field) Number of household members Not shared [1] Public facility Shared by: 5 households or less Shared by: More than 5 households Missing/ DK Not shared Public facility Shared by: 5 households or less Shared by: More than 5 households Missing/ DK Area Urban 57.0 0.6 10.0 1.0 0.6 20.4 .4 4.2 0.4 0.3 5.0 30,476 Rural 22.1 0.3 4.5 1.0 0.3 25.3 .8 4.7 0.7 0.2 40.0 68,407 Education of household head None 21.3 0.3 4.0 0.8 0.3 27.0 .9 4.1 0.7 0.2 40.4 45,740 Primary 32.1 0.4 6.5 0.9 0.3 23.5 .8 6.3 0.7 0.3 28.1 28,007 Secondary 51.5 0.4 10.2 1.7 0.4 19.6 .2 3.9 0.6 0.4 11.1 18,812 Higher 69.7 1.3 10.2 0.6 1.0 11.4 .1 1.9 0.2 0.0 3.6 5,564 Missing/DK 24.6 0.0 4.9 0.0 0.0 34.0 .0 5.3 0.0 0.7 30.5 761 Wealth index quintile Poorest 5.4 0.1 .5 0.2 0.0 28.4 .3 2.8 0.5 0.2 61.6 19,775 Second 9.2 0.1 1.6 0.7 0.4 35.1 .4 6.0 1.0 0.4 45.1 19,776 Middle 24.3 0.7 4.7 1.5 0.4 31.2 2.3 7.9 1.1 0.6 25.4 19,779 Fourth 47.2 0.4 13.0 1.7 0.4 17.6 .4 5.1 0.6 0.1 13.4 19,773 Richest 78.1 0.9 11.4 0.9 0.6 6.5 .0 1.0 0.0 0.1 0.5 19,781 [1] MICS indicator 4.3; MDG indicator 7.9 - Use of improved sanitation 120 Figure WS.2: Household members by use and sharing of sanitation facilities, Sudan MICS, 2014 Figure WS.2b: Household members practicing open defecation by urban and rural residence and by state, Sudan MICS, 2014 Improved sanitation facility - not shared 33% Improved public facility 0% Improved sanitation facility - shared 7% Unimproved sanitation facility - not shared 24% Unimprove d sanitatio… Unimproved public … Open Defecation 29% 1.7 2.2 11 11.4 19.7 26.6 29.2 31.8 32.4 34.6 35 40.7 41.1 41.3 43 43 44.5 44.6 44.9 5 40 0 5 10 15 20 25 30 35 40 45 50 Khartoum Northern River Nile Blue Nile West Kordofan East Darfur Sudan West Darfur Gezira Sinnar Red Sea South Kordofan North Darfur South Darfur Gadarif White Nile North Kordofan Central Darfur Kassala Urban Rural Percent 121 Having access to both an improved drinking water source and an improved sanitation facility brings the largest public health benefits to a household.26 In its 2008 report27, the JMP developed a new way of presenting the access figures, by disaggregating and refining the data on drinking-water and sanitation and reflecting them in "ladder" format. This ladder allows a disaggregated analysis of trends in a three rung ladder for drinking-water and a four-rung ladder for sanitation. For sanitation, this gives an understanding of the proportion of population with no sanitation facilities at all – who revert to open defecation, of those reliant on technologies defined by JMP as "unimproved," of those sharing sanitation facilities of otherwise acceptable technology, and those using "improved" sanitation facilities. Table WS.7 presents the percentages of household population by these drinking water and sanitation ladders. The table also shows the percentage of household members using both improved sources of drinking water28 and an improved sanitary means of excreta disposal. In Sudan, the percentage of household population using both improved drinking water sources and improved sanitation facilities was only 28.2 percent. The percentage of household population using both improved drinking water sources and improved sanitation facilities showed an increasing trend with the educational level of the household head. In the case of households which had a household head with no education,17.2 percent used an improved drinking water source and an improved sanitation facility, wghich compares with 27.6 percent of households which had a head of households with primary education and 64.5 percentof households which had a household head with secondary or higher level of education. The percentage of household population using both improved drinking water sources and improved sanitation facilities also varied significantly with household wealth. The percentage of household population using both improved drinking water sources and improved sanitation facilities was only 3.4 percent in the case of the poorest households compared to 75.1 percent in the case of the richest households. . 26 Wolf, J et al. 2014. Systematic review: Assessing the impact of drinking water and sanitation on diarrhoeal disease in low- and middle-income settings: systematic review and meta-regression. Tropical Medicine and International Health 2014. DfID. 2013. Water, Sanitation and Hygiene: Evidence Paper. DfID: http://r4d.dfid.gov.uk/pdf/outputs/sanitation/WASH-evidence-paper-april2013.pdf 27 WHO/UNICEF JMP. 2008. MDG assessment report. http://www.wssinfo.org/fileadmin/user_upload/resources/1251794333-JMP_08_en.pdf 28 Those indicating bottled water as the main source of drinking water are distributed according to the water source used for other purposes such as cooking and handwashing. 122 Table WS.7: Drinking water and sanitation ladders: Percentage of household population by drinking water and sanitation ladders, Sudan MICS, 2014 Background characteristics Percentage of household population using: Number of household members Improved drinking water [1] [a] Un improved drinking water Improved sanitation [2] Unimproved sanitation Improved drinking water sources and improved sanitation Piped into dwelling, plot or yard Other improved Shared improved facilities Un improved facilities Open defecation Sudan 36.9 31.1 32.0 32.9 8.0 29.9 29.2 28.2 98,883 State Northern 71.9 22.0 6.2 79.4 15.7 2.7 2.2 76.3 2,181 River Nile 74.1 14.2 11.7 49.8 12.1 27.1 11.0 44.7 3,715 Red Sea 12.5 20.7 66.8 52.4 3.4 9.2 35.0 11.4 2,489 Kassala 28.2 29.0 42.8 29.3 4.6 21.1 44.9 24.8 4,117 Gadarif 6.2 21.5 72.3 9.8 2.9 44.3 43.0 4.0 5,005 Khartoum 79.7 7.2 13.1 66.4 19.0 12.9 1.7 62.7 13,830 Gezira 80.9 8.0 11.1 38.3 11.5 17.8 32.4 37.7 16,270 White Nile 23.9 8.8 67.3 29.8 9.0 18.2 43.0 20.1 5,016 Sinnar 36.8 51.8 11.3 18.6 10.4 36.4 34.6 17.5 3,763 Blue Nile 36.8 34.5 28.7 39.7 3.1 45.8 11.4 36.5 4,094 North Kordofan 12.2 57.5 30.2 25.0 4.9 25.6 44.5 22.5 6,359 South Kordofan 2.2 57.9 39.9 14.3 6.6 38.3 40.7 9.6 2,983 West Kordofan .3 85.7 14.0 10.4 1.2 68.7 19.7 9.7 5,745 North Darfur 2.8 47.8 49.4 12.3 1.5 45.1 41.1 7.9 7,776 West Darfur 15.2 52.3 32.5 16.0 2.3 50.0 31.8 14.2 3,023 South Darfur 4.8 41.8 53.4 24.7 4.3 29.6 41.3 18.9 7,712 Central Darfur 2.6 47.9 49.4 15.8 3.2 36.4 44.6 8.9 1,646 East Darfur 6.6 38.5 54.9 14.4 2.6 56.4 26.6 6.3 3,158 Area Urban 57.5 20.8 21.7 57.0 12.2 25.7 5.0 48.7 30,476 Rural 27.8 35.7 36.5 22.1 6.1 31.8 40.0 19.1 68,407 Education of household head None 22.0 37.7 40.3 21.3 5.4 32.9 40.4 17.2 45,740 Primary 40.1 30.9 29.0 32.1 8.2 31.6 28.1 27.6 28,007 Secondary 58.1 20.7 21.2 51.5 12.7 24.6 11.1 45.9 18,812 Higher 74.6 11.9 13.5 69.7 13.1 13.6 3.6 64.4 5,564 Missing/DK 21.1 36.3 42.6 24.6 4.9 40.0 30.5 13.3 761 Wealth index quintile Poorest .0 45.5 54.5 5.4 0.8 32.2 61.6 3.4 19,775 Second .2 53.2 46.6 9.2 2.7 43.0 45.1 6.5 19,776 Middle 19.6 40.4 40.0 24.3 7.3 43.1 25.4 16.3 19,779 Fourth 71.6 13.7 14.7 47.2 15.5 23.9 13.4 39.9 19,773 Richest 93.3 2.7 4.0 78.1 13.8 7.6 0.5 75.1 19,781 [1] MICS indicator 4.1; MDG indicator 7.8 - Use of improved drinking water sources [2] MICS indicator 4.3; MDG indicator 7.9 - Use of improved sanitation; [a] Those indicating bottled water as the main source of drinking water are distributed according to the water source used for other purposes such as cooking and 123 F i g u r e W S . 3 : H o u s e h o l d m e m b e r s u s i n g i m p r o v e d i m p r o v e d s a n i t a t i o n , b y w e a l t h , Su d a n M I C S , 2 0 1 4 Safe disposal of a child’s faeces is disposing of the stool, by the child using a toilet or by rinsing the stool into a toilet or latrine. Putting disposable diapers with solid waste, a very common practice throughout the world has thus far been classified as an inadequate means of disposal of child faeces for concerns about poor disposal of solid waste itself. This classification is currently under review. Disposal of faeces of children 0-2 years of age is presented in Table WS.8. Overall, the percentage of children whose stools were disposed of safely was 53.0 percent. There was a significant difference between rural and urban areas in the proportion of children whose stools were disposed of safely. The proportion of children whose stools were disposed of safely was 78.3 percent in urban areas compared to 43.4 percent in rural areas. There was also a significant difference between the proportion of children whose stools were disposed of safely among children whose mothers had no education (36.5 percent) and among children whose mothers had secondary or higher level of education (81.2 percent). Significant difference between those in households in the richest and poorest quintiles were also found in terms of the proportion of children whose stools were disposed of safely; recording 81.6 percent among those from households in the richest quintile compared to only 22.9 percent among those from households in the poorest quintile. 3 6 16 40 75 28 0 20 40 60 80 Poorest Second Middle Fourth Richest Sudan Pe rc en t Wealth Index Quintiles 124 Table WS.8: Disposal of child's faeces Percent distribution of children age 0-2 years according to place of disposal of child's faeces, and the percentage of children age 0-2 years whose stools were disposed of safely the last time the child passed stools, Sudan MICS, 2014 Background characteristics Place of disposal of child's faeces Percentage of children whose last stools were disposed of safely [1] Number of children age 0-2 years Child used toilet / latrine Put / Rinsed into toilet or latrine Put / Rinsed into drain or ditch Thrown into garbage (solid waste) Buried Left in the open Other DK Missing Sudan 3.8 49.2 7.8 11.2 9.7 12.1 3.8 0.9 1.5 53.0 8,263 Type of sanitation facility in dwelling Improved 8.2 74.1 2.8 7.4 1.3 2.5 1.8 0.7 1.3 82.3 3,022 Unimproved 2.3 62.9 12.1 8.2 5.4 4.1 2.7 0.9 1.4 65.3 2,576 Open defecation 0.4 7.7 9.4 18.5 23.3 30.7 7.2 1.0 1.8 8.1 2,665 State Northern 8.8 71.0 1.3 15.3 0.4 2.2 .9 0.0 0.0 79.8 142 River Nile 3.3 65.6 4.0 8.3 4.2 10.2 3.3 0.3 0.9 68.9 224 Red Sea 6.6 47.8 4.5 15.6 4.2 12.0 6.0 2.5 0.6 54.4 145 Kassala 1.7 26.9 5.3 14.3 10.0 39.9 .1 0.3 1.5 28.6 298 Gadarif 2.1 35.6 11.3 12.3 10.9 19.1 6.5 0.8 1.2 37.8 471 Khartoum 15.0 65.1 2.8 12.1 0.2 1.9 .7 0.6 1.6 80.0 1,016 Gezira 2.1 55.2 9.1 11.0 4.8 12.7 4.2 0.6 0.2 57.4 1,257 White Nile 3.9 37.5 5.9 12.8 4.3 21.4 11.7 0.4 2.1 41.5 435 Sinnar 1.5 55.3 5.0 22.4 5.6 6.6 2.3 0.0 1.3 56.8 333 Blue Nile 1.6 68.0 5.2 12.2 3.7 4.8 3.5 0.2 0.8 69.7 426 North Kordofan 3.4 38.4 4.0 12.2 18.9 9.6 9.1 1.8 2.7 41.8 501 South Kordofan 2.3 41.3 7.8 14.8 9.0 9.0 12.3 1.1 2.4 43.6 302 West Kordofan 0.3 63.5 11.0 4.5 7.5 11.6 0.0 0.2 1.4 63.7 499 North Darfur 0.9 30.9 18.1 19.6 7.6 16.5 1.0 1.7 3.7 31.8 684 West Darfur 0.2 59.0 2.7 3.4 19.8 7.5 2.5 1.1 3.8 59.2 278 South Darfur 3.2 37.6 3.8 4.1 32.9 12.2 3.9 1.8 0.4 40.7 823 Central Darfur 0.6 33.3 12.0 4.6 25.0 17.4 2.8 2.1 2.1 34.0 141 East Darfur 2.0 49.4 25.4 2.4 5.4 12.9 1.0 0.0 1.5 51.4 289 Area Urban 9.1 69.2 3.4 8.0 2.1 2.6 2.9 0.9 1.7 78.3 2,273 Rural 1.8 41.6 9.5 12.4 12.6 15.6 4.2 0.9 1.4 43.4 5,990 Education of household head None 1.9 34.5 9.9 12.3 15.3 18.2 5.3 0.8 1.6 36.5 3,361 Primary 4.0 52.4 8.0 10.9 8.3 10.6 3.5 1.1 1.2 56.4 2,976 Secondary 6.8 67.9 4.6 9.5 2.6 4.3 1.9 0.2 2.2 74.7 1,308 Higher 7.3 73.9 2.4 10.4 0.9 1.5 1.5 1.5 0.6 81.2 607 125 Background characteristics Place of disposal of child's faeces Percentage of children whose last stools were disposed of safely [1] Number of children age 0-2 years Child used toilet / latrine Put / Rinsed into toilet or latrine Put / Rinsed into drain or ditch Thrown into garbage (solid waste) Buried Left in the open Other DK Missing Missing/DK * * * * * * * * * * 10 Wealth index quintile Poorest 0.6 22.3 10.1 11.8 26.2 20.4 4.9 1.8 1.8 22.9 1,795 Second 1.8 37.1 11.6 14.1 10.7 17.7 5.0 0.4 1.8 38.8 1,786 Middle 2.3 55.1 8.3 12.0 5.2 10.3 4.6 0.6 1.6 57.4 1,775 Fourth 5.8 68.7 5.0 6.2 2.5 7.4 2.8 0.8 0.9 74.5 1,608 Richest 10.8 70.8 2.3 11.5 0.6 0.9 1.1 0.7 1.2 81.6 1,299 [1] MICS indicator 4.5 - Place for handwashing [*] Based on less than 25 unweighted cases and has been suppressed 7.3 Handwashing Hand washing with water and soap is the most cost effective health intervention to reduce both the incidence of diarrhoea and pneumonia in children under five29. It is most effective when done using water and soap after visiting a toilet or cleaning a child, before eating or handling food and, before feeding a child. Monitoring correct hand washing behaviour at these critical times is challenging. A reliable alternative to observations or self-reported behaviour is assessing the likelihood that correct hand washing behaviour takes place by asking if a household has a specific place where people wash their hands and, if yes, observing whether water and soap (or other local cleansing materials) are available at this place. Table WS.9 indicates that in only 40.9 percent of the households was a specific place for hand washing in the dwelling, yard or plot observed. The proportion of households where the interviewers could not observe a specific place where household members usually wash their hands was 46.1 percent. In a further 17.5 percent of households permission to see a handwashing facility was not granted. The data suggests that more than half of the population have no specific place for hand washing in the dwelling, yard or plot. In only one fourth (25.0 percent) of the households both water and soap (or another cleansing agent) were present at the specific place for hand washing while an small proportion of households had only water available at the specific place (0 .8 percent) or soap but no water (1.3 percent). The proportion of households with a specific place for hand washing with water and soap in urban areas was 34.0 percent and that of rural areas was 21.8 percent. It was observed that the availability of places for handwashing with water and soap increased with the level of education of the head of the household as the wealth index quintile of the household. Nearly 20 percentof the households were not able or refused to show the presence of any soap in the household, whereas another 26percent did not have any soap in the households, leaving the 29 Cairncross, S and Valdmanis, V. 2006. Water supply, sanitation and hygiene promotion Chapter 41 in Disease Control Priorities in Developing Countries. 2nd Edition, Edt. Jameson et al. The World Bank. 126 remaining 55.4 percent of households, in which either the soap was observed or shown to the interviewer (Table WS.10) Table WS9. Water and soap at place for handwashing Percent of household where place for handwashing was observed, percentage with no specific place for handwashing and percent distribution of households by availability of water and soap at specific place for handwashing, Sudan MICS, 2014 Table WS 10. Availability of soap or other cleansing agent. Percent distribution of households by availability of soap or other cleansing agent in dwelling, Sudan MICS, 2014 127 Table WS.9: Water and soap at place for handwashing Percentage of households where place for handwashing was observed, percentage with no specific place for handwashing, and percent distribution of households by availability of water and soap at specific place for handwashing, Sudan MICS, 2014 Percentage of households: Numbe r of househ olds Place for handw ashing observ ed: Water is availab le and: Soap present Place for handw ashing observ ed: Water is availa ble and: No soap: Ash, mud, or sand presen t Place for handwa shing observe d: Water is availabl e and: No soap: No other cleansi ng agent present Place for handw ashing observ ed: Water is not availab le and: Soap presen t Place for handw ashing observ ed: Water is not availab le and: No soap: Ash, mud, or sand presen t Place for handw ashing observ ed: Water is not availab le and: No soap: No other cleansi ng agent presen t No spec ific plac e for han dwa shin g in the dwel ling, yard , or plot Total Perce ntage of house holds with a specifi c place for handw ashing where water and soap or other cleansi ng agent are presen t [1] Numb er of house holds where place for handw ashing was observ ed or with no specifi c place for handw ashing Whe re plac e for hand wash ing was obse rved With no specifi c place for handw ashing in the dwelli ng, yard, or plot Sudan 40.9 46.1 16,801 25.0 0.8 13.5 1.3 0.2 6.3 53.0 100.0 25.8 14,625 State Northern 48.0 20.8 423 33.3 0.0 34.5 0.5 0.0 1.5 30.2 100.0 33.3 290 River Nile 64.5 33.5 666 48.0 0.0 17.2 0.2 0.0 0.4 34.2 100.0 48.0 653 Red Sea 15.9 79.3 519 12.8 0.0 0.7 2.5 0.0 0.7 83.3 100.0 12.8 494 Kassala 19.8 79.3 722 10.6 0.0 7.4 0.2 0.0 1.8 80.0 100.0 10.6 715 Gadarif 1.9 67.4 858 2.0 0.0 0.6 0.1 0.0 0.2 97.2 100.0 2.0 595 Khartoum 53.0 44.0 2,317 42.0 0.1 10.5 1.3 0.0 0.8 45.4 100.0 42.1 2,248 Gezira 57.4 40.3 2,629 18.9 0.5 31.2 0.9 0.0 7.2 41.3 100.0 19.4 2,567 White Nile 49.8 29.3 874 33.0 0.1 13.4 3.3 0.0 13.0 37.1 100.0 33.1 691 Sinnar 53.9 45.4 661 44.0 0.0 3.9 0.6 0.0 5.8 45.7 100.0 44.0 656 Blue Nile 52.3 22.5 656 17.8 9.4 30.4 1.4 0.7 10.3 30.1 100.0 27.2 491 North Kordofan 3.5 96.0 1,125 2.6 0.0 0.4 0.1 0.0 0.5 96.5 100.0 2.6 1,120 South Kordofan 61.6 24.8 462 35.5 0.0 12.1 3.2 0.0 20.5 28.7 100.0 35.5 400 West Kordofan 22.7 64.8 1,003 6.7 0.0 2.6 3.5 0.0 13.1 74.0 100.0 6.7 878 North Darfur 62.4 10.0 1,243 49.5 5.8 14.7 1.4 1.9 12.9 13.8 100.0 55.3 900 West Darfur 47.1 41.6 553 30.5 0.0 6.6 1.5 0.3 14.2 46.9 100.0 30.5 491 South Darfur 17.2 46.7 1,282 17.0 0.0 6.8 0.8 0.0 2.3 73.1 100.0 17.0 819 Central Darfur 93.3 3.3 299 22.4 0.5 32.7 2.7 0.5 37.9 3.4 100.0 22.9 289 East Darfur 8.3 55.9 508 8.3 0.9 1.8 0.4 0.0 1.6 87.0 100.0 9.2 326 Area Urban 47.3 46.9 5,000 33.8 0.2 11.2 1.5 0.0 3.4 49.8 100.0 34.0 4,711 Rural 38.2 45.8 11,801 20.7 1.1 14.6 1.1 0.2 7.7 54.5 100.0 21.8 9,913 Education of 128 Percentage of households: Numbe r of househ olds Place for handw ashing observ ed: Water is availab le and: Soap present Place for handw ashing observ ed: Water is availa ble and: No soap: Ash, mud, or sand presen t Place for handwa shing observe d: Water is availabl e and: No soap: No other cleansi ng agent present Place for handw ashing observ ed: Water is not availab le and: Soap presen t Place for handw ashing observ ed: Water is not availab le and: No soap: Ash, mud, or sand presen t Place for handw ashing observ ed: Water is not availab le and: No soap: No other cleansi ng agent presen t No spec ific plac e for han dwa shin g in the dwel ling, yard , or plot Total Perce ntage of house holds with a specifi c place for handw ashing where water and soap or other cleansi ng agent are presen t [1] Numb er of house holds where place for handw ashing was observ ed or with no specifi c place for handw ashing Whe re plac e for hand wash ing was obse rved With no specifi c place for handw ashing in the dwelli ng, yard, or plot househol d head None 34.1 50.4 7,799 17.8 1.1 12.5 0.8 0.2 7.9 59.6 100.0 18.9 6,585 Primary 39.2 48.6 4,730 22.4 0.9 14.6 1.4 0.2 5.2 55.4 100.0 23.3 4,154 Secondary 52.6 38.1 3,137 36.2 0.2 14.4 2.2 0.0 4.9 42.0 100.0 36.5 2,845 Higher 65.7 27.1 1,013 52.8 0.1 13.5 0.7 0.0 3.7 29.2 100.0 52.9 940 Missing/D K 39.8 42.9 122 18.0 2.7 11.9 1.8 0.0 13.7 51.9 100.0 20.7 101 Wealth index quintile Poorest 23.3 52.2 3,368 13.0 1.5 4.7 1.2 0.6 9.8 69.2 100.0 14.4 2,543 Second 30.6 54.1 3,592 16.4 1.0 9.3 1.1 0.1 8.2 63.9 100.0 17.5 3,041 Middle 37.7 49.9 3,339 19.1 0.8 13.5 1.4 0.1 8.1 57.0 100.0 19.9 2,925 Fourth 43.3 48.4 3,209 18.9 0.6 21.8 1.0 0.0 5.0 52.7 100.0 19.4 2,942 Richest 71.2 25.2 3,293 53.8 0.3 16.8 1.5 0.0 1.5 26.1 100.0 54.0 3,174 [1] MICS indicator 4.5 - Place for handwashing 129 Table WS.10: Availability of soap or other cleansing agent Percent distribution of households by availability of soap or other cleansing agent in the dwelling, Sudan, 2014 Background Characteristics Place for handwashing observed Place for handwashing not observed Total Percentage of households with soap or other cleansing agent anywhere in the dwelling [1] Number of households Soap or other cleansing agent observed Soap or other cleansing agent not observed: Soap or other cleansing agent shown Soap or other cleansing agent not observed at place for handwashing: No soap or other cleansing agent in household Soap or other cleansing agent not observed at place for handwashing: Not able/Does not want to show cleansing agent Missing Soap or other cleansing agent not observed: Soap or other cleansing agent shown Soap or other cleansing agent not observed at place for handwashing: No soap or other cleansing agent in household Soap or other cleansing agent not observed at place for handwashing: Not able/Does not want to show cleansing agent Missing Sudan 23.7 7.2 6.9 3.0 0.2 24.5 19.1 15.3 0.1 100.0 55.4 16,801 State Northern 23.2 19.0 1.9 3.8 0.0 33.5 5.5 13.1 0.0 100.0 75.7 423 River Nile 47.3 4.9 2.4 10.0 0.0 19.2 4.5 11.8 0.0 100.0 71.3 666 Red Sea 14.6 0.2 0.6 0.5 0.0 21.0 38.1 24.7 0.4 100.0 35.7 519 Kassala 10.7 4.7 3.0 1.5 0.0 24.1 42.1 14.0 0.0 100.0 39.4 722 Gadarif 1.4 0.4 0.1 0.1 0.0 41.4 39.3 17.3 0.0 100.0 43.2 858 Khartoum 42.1 8.1 0.9 1.5 0.5 31.7 5.6 9.5 0.2 100.0 81.9 2,317 Gezira 19.8 14.6 19.0 3.9 0.0 25.9 5.9 10.8 0.0 100.0 60.3 2,629 White Nile 28.8 4.9 7.0 8.4 0.7 12.4 27.0 10.7 0.2 100.0 46.1 874 Sinnar 44.3 1.8 2.5 5.2 0.1 11.6 19.9 14.5 0.1 100.0 57.7 661 Blue Nile 21.9 26.6 2.8 1.0 0.1 32.6 12.5 2.6 0.0 100.0 81.0 656 North Kordofan 2.6 0.6 0.0 0.2 0.0 44.0 20.6 31.6 0.3 100.0 47.3 1,125 South Kordofan 33.4 4.0 21.1 2.7 0.3 8.7 19.1 10.6 0.0 100.0 46.1 462 West Kordofan 9.0 1.9 7.6 4.2 0.0 17.8 28.5 30.5 0.4 100.0 28.8 1,003 North Darfor 42.4 8.8 7.7 3.4 0.2 6.2 10.2 21.0 0.2 100.0 57.3 1,243 West Darfor 28.6 3.1 11.3 4.1 0.0 23.6 10.2 18.6 0.6 100.0 55.3 553 South Darfor 11.3 2.7 2.1 0.8 0.3 26.4 36.9 19.5 0.1 100.0 40.4 1,282 Central Darfor 25.1 16.3 43.6 7.4 0.8 1.2 4.8 0.7 0.0 100.0 42.7 299 East Darfor 6.2 0.3 1.7 0.2 0.0 26.7 58.9 6.0 0.0 100.0 33.2 508 Area Urban 33.5 7.1 4.1 2.2 0.3 27.3 13.7 11.6 0.1 100.0 67.9 5,000 Rural 19.5 7.2 8.1 3.3 0.1 23.4 21.3 16.9 0.2 100.0 50.1 11,801 Education of household head None 16.8 6.2 8.0 2.9 0.1 23.5 25.7 16.5 0.2 100.0 46.5 7,799 Primary 21.8 7.8 6.3 3.3 0.0 27.1 16.7 16.8 0.1 100.0 56.8 4,730 Secondary 35.1 8.5 5.8 2.7 0.5 25.1 10.4 11.9 0.1 100.0 68.6 3,137 Higher 49.7 9.0 3.7 3.0 0.2 18.7 5.9 9.6 0.1 100.0 77.5 1,013 Missing/DK 18.6 2.8 16.4 1.9 0.0 20.2 20.0 20.0 0.0 100.0 41.6 122 Wealth index quintile Poorest 12.3 2.5 6.3 2.2 0.0 18.8 34.8 22.9 0.2 100.0 33.6 3,368 Second 15.8 4.6 7.5 2.6 0.1 22.3 28.7 18.2 0.2 100.0 42.7 3,592 Middle 18.8 7.8 8.1 2.7 0.1 29.4 18.3 14.5 0.1 100.0 56.0 3,339 Fourth 18.8 11.4 9.6 3.4 0.2 33.1 9.8 13.5 0.2 100.0 63.2 3,209 Richest 53.6 10.1 3.1 4.1 0.4 19.5 2.2 7.1 0.0 100.0 83.2 3,293 [1] MICS indicator 4.6 - Availability of soap or other cleansing agent 130 VIII. REPRODUCTIVE HEALTH 8.1 Fertility Measures of current fertility are presented in Table RH.1 for the three-year period preceding the survey. A three-year period was chosen for calculating these rates to provide the most current information while also allowing the rates to be calculated for a sufficient number of cases so as not to compromise the statistical precision of the estimates. Age-specific fertility rates (ASFRs), expressed as the number of births per 1,000 women in a specified age group, show the age pattern of fertility. Numerators for ASFRs are calculated by identifying live births that occurred in the three-year period preceding the survey classified according to the age of the mother (in five-year age groups) at the time of the child’s birth. The denominators of the rates represent the number of woman-years lived by the survey respondents in each of the five-year age groups during the specified period. The total fertility rate (TFR) is a synthetic measure that denotes the number of live births a woman would have if she were subject to the current age-specific fertility rates throughout her reproductive years (15-49 years). The general fertility rate (GFR) is the number of live births occurring during the specified period per 1,000 women age 15-49.The crude birth rate (CBR) is the number of live births per 1,000 population during the specified period. Measures of current fertility are presented in Table RH.1 for the three year period preceding the survey. In MICS5, age specific and Sudan fertility rates are calculated by using information on the date of last birth of each woman and are based on the one-year period (1-12 months) preceding the survey. Rates are underestimated by a very small margin due to absence of information on multiple births (twins, triplets, etc.) and on women who may have had multiple deliveries during the one year period preceding the survey. The total fertility rate (TFR) is calculated by summing the age-specific fertility rates calculated for each of the 5-year age groups of women, from age 15 through to age 49. The total fertility rate (TFR) is a synthetic measure that denotes the number of live births a woman would have if she were subject to the current age-specific fertility rates throughout her reproductive years (15-49 years). The general fertility rate (GFR) is the number of live births occurring during the specified period per 1,000 women age 15-49. The crude birth rate (CBR) is the number of live births per 1,000 population during the specified period. 131 Table RH.1: Fertility rates Adolescent birth rate, age-specific and Sudan fertility rates, the general fertility rate, and the crude birth rate for the one-year / three-year period preceding the survey, by area, Sudan MICS, 2014 Age Area Sudan Urban Rural 15-19 [1] 53 103 87 20-24 167 225 207 25-29 238 268 259 30-34 194 243 226 35-39 151 165 160 40-44 58 78 71 45-49 13 29 23 TFR [a] 4.4 5.6 5.2 GFR [b] 139.5 181.3 167.5 CBR [c] 30.6 35.7 34.2 1 MICS indicator 5.1; MDG indicator 5.4 - Adolescent birth rate [a] TFR: total fertility rate expressed per woman age 15-49 [b] GFR: General fertility rate expressed per 1,000 women age 15-49 [c] CBR: Crude birth rate expressed per 1,000 population Table RH.1 shows current fertility in Sudan at the national level and by urban-rural area. The TFR for the three years preceding the survey MICS5 is 5.2 births per woman. Fertility is considerably higher in rural areas (5.6 births per woman) than in the urban areas (4.4 births per woman). As the ASFRs show, the pattern of higher rural fertility is prevalent in all age groups. These results are shown in Figure RH.1 as well. 132 F i g u r e R H . 1 : Ag e - s p e c i f i c f e r t i l i t y r a t e s b y a r e a , S u d a n M I C S , 2 0 1 4 The urban-rural difference in fertility is most pronounced for women in the 20-24 age group: 167 births per 1,000 women in urban areas versus 225 births per 1,000 women in rural areas. The overall age pattern of fertility, as reflected in the ASFRs, indicates that childbearing begins early. Fertility is low among adolescents, increases to a peak of 259 births per 1,000 among women age 25-29, and declines thereafter. Table RH.2 shows adolescent birth rates and Sudan fertility rates. The adolescent birth rate (age- specific fertility rate for women age 15-19) is defined as the number of births to women age 15-19 years during the three year period preceding the survey, divided by the average number of women age 15-19 (number of women-years lived between ages 15 through 19, inclusive) during the same period, expressed per 1,000 women. Adolescent birth rates at national level according to Table RH.2 is 87 births per 1000 women. Considerable variations between states are observed. For example adolescent birth rates for Khartoum state is 47 compared to 125 births for South Darfur. Similar variations in TFR are also observed between the states. The highest TFR of 6.9 births is registered for South Darfur state, as compared with a rate of 3.2 births for Red Sea state as the lowest. According to Table RH.2 the level of education of the woman is inversely correlated with her fertility. Women with secondary or high education shows lower fertility compared with women with primary or no education. 0 50 100 150 200 250 300 15-191 20-24 25-29 30-34 35-39 40-44 45-49 P er 1 ,0 00 Age Urban Rural Total Rates refer to the one year/three years period preceding the survey 133 Table RH.2: Adolescent birth rate and total fertility rate Adolescent birth rates and Sudan fertility rates for the one-year / three-year period preceding the survey, Sudan MICS, 2014 Background characteristics Adolescent birth rate [1] (Age-specific fertility rate for women age 15-19) TFR [a] Sudan 87 5.2 State Northern 52 3.8 River Nile 49 3.6 Red Sea 49 3.2 Kassala 113 4.8 Gadarif 115 5.9 Khartoum 47 4.2 Gezira 65 4.3 White Nile 91 5.2 Sinnar 86 5.3 Blue Nile 114 6.7 North Kordofan 113 4.8 South Kordofan 119 5.8 West Kordofan 91 5.8 North Darfur 100 6.8 West Darfur 117 6.7 South Darfur 125 6.9 Central Darfur 113 5.7 East Darfur 112 6.2 Education None 169 6.4 Primary 112 5.4 Secondary 34 4.2 Higher 8 3.2 [1] MICS indicator 5.1; MDG indicator 5.4 - Adolescent birth rate 134 Table RH.3: Early childbearing Percentage of women age 15-19 years who have had a live birth, are pregnant with the first child, have begun childbearing, and who have had a live birth before age 15, and percentage of women age 20-24 years who have had a live birth before age 18, Sudan MICS, 2014 Background characteristics Percentage of women age 15-19 who: Number of women age 15-19 Percentage of women age 20-24 who have had a live birth before age 18 [1] Number of women age 20-24 Have had a live birth Are pregnant with first child Have begun childbearing Have had a live birth before age 15 Sudan 11.8 3.3 15.1 1.4 3,709 21.5 3,162 State Northern 4.9 3.8 8.6 0.3 81 6.3 65 River Nile 10.8 4.3 15.1 1.1 123 10.7 131 Red Sea 10.8 4.7 15.5 2.6 74 10.2 76 Kassala 19.0 3.6 22.6 2.6 147 24.4 125 Gadarif 14.7 4.1 18.8 4.2 164 25.4 163 Khartoum 6.3 3.0 9.4 1.2 583 10.5 470 Gezira 9.7 3.8 13.5 0.9 681 15.1 550 White Nile 9.5 5.0 14.5 0.0 165 21.7 147 Sinnar 10.8 2.3 13.1 1.3 124 24.1 133 Blue Nile 15.2 8.1 23.4 1.6 167 27.8 130 North Kordofan 19.1 1.8 20.9 1.8 249 23.5 222 South Kordofan 15.1 0.8 15.9 3.7 112 36.8 86 West Kordofan 12.1 1.9 14.0 1.0 168 24.8 172 North Darfur 8.5 3.3 11.8 0.1 265 30.4 214 West Darfur 11.9 2.7 14.6 2.6 125 33.8 89 South Darfur 17.2 1.9 19.1 0.8 307 33.5 260 Central Darfur 13.3 1.1 14.4 1.5 63 38.4 41 East Darfur 18.7 1.1 19.8 2.7 114 29.6 88 Area Urban 6.5 2.1 8.7 1.0 1219 12.3 1,044 Rural 14.4 3.8 18.2 1.6 2491 26.0 2,118 Education None 28.4 4.5 32.9 6.3 519 42.4 802 Primary 14.4 4.1 18.5 1.0 1622 26.4 1,040 Secondary 3.9 2.1 6.0 0.2 1409 8.0 771 Higher 1.7 0.7 2.4 0.8 160 .7 548 Wealth index quintile Poorest 15.5 2.7 18.2 1.5 629 32.4 536 Second 17.8 3.8 21.6 2.2 720 35.8 617 Middle 14.9 3.2 18.1 2.4 777 20.1 608 Fourth 7.3 3.6 11.0 0.3 753 16.8 731 Richest 5.1 2.9 8.0 0.7 831 6.2 669 1 MICS indicator 5.2 - Early childbearing 135 Table RH.4: Trends in early childbearing Percentage of women who have had a live birth, by age 15 and 18, by area and age group, Sudan MICS, 2014 Background characteristics Urban Rural All Perce nt-age of wome n with a live birth before age 15 Numb er of wome n age 15-49 years Perce nt-age of wome n with a live birth before age 18 Numb er of wome n age 20-49 years Perce nt-age of wome n with a live birth before age 15 Numb er of wome n age 15-49 years Perce nt-age of wome n with a live birth before age 18 Numb er of wome n age 20-49 years Percen t-age of wome n with a live birth before age 15 Numbe r of women age 15- 49 years Perce nt-age of wome n with a live birth before age 18 Number of women age 20- 49 years Sudan 3.6 6029 18.1 4810 6.0 12273 25.5 9783 5.2 18302 23.0 14,593 Age 15-19 1.0 1219 * 0 1.6 2491 * 0 1.4 3709 * 0 20-24 1.7 1044 12.3 1044 7.1 2118 26.0 2118 5.3 3162 21.5 3,162 25-29 4.9 1030 17.4 1030 7.9 2329 28.4 2329 7.0 3359 25.0 3,359 30-34 4.9 859 20.1 859 6.3 1698 27.6 1698 5.8 2558 25.1 2,558 35-39 4.6 834 20.9 834 6.1 1707 22.1 1707 5.6 2542 21.7 2,542 40-44 5.9 578 20.7 578 7.6 1055 22.0 1055 7.0 1633 21.6 1,633 45-49 4.6 464 20.2 464 7.8 875 22.9 875 6.7 1339 21.9 1,339 [*] Based on less than 25 unweighted cases and has been suppressed. Table RH.3 presents some early childbearing30 indicators for women age 15-19 and 20-24 while Table RH.4 presents the trends for early childbearing. As shown in Table RH.3, 11.8 percent of women age 15-19 have already had a birth, 3.3 percent are pregnant with their first child, and 1.4 percent have had a live birth before age 15. The table also shows that 21.5 percent of women age 20-24 have had a live birth before age 18. Generally speaking Table RH.3 shows some variations among the states in all the indicators. Urban women show comparatively lower indicators than the rural women. The table also shows that women with secondary or higher education show lower indicators compared with women of primary or no education. In Table RH.4 of the percentage of women who experienced child bearing before age 15 was 5.2 percent. Child bearing before age 15 is significantly higher among rural women 6 percent compared with 3.6 percent among those in urban areas. Considering child bearing before age 15 by current age of women, the table shows no clear pattern according to the age neither at national nor at urban or rural settings. Table RH4 also shows percentage distribution of women according their experience with child bearing before age 18 and their current age. The table shows that at national level 23 percent of the women 30Childbearing is the process of giving birth to children. While early childbearing is defined as having had live births before specific young ages, for the purposes of Table RH.3, women age 15-19 years who have begun childbearing includes thosewho have had a live birth as well as those who have not had a live birth but are pregnant with their first child. 136 have experienced child bearing before age 18, as compared with 18.1 percent for the urban and 25.5 percent for the rural women. Considering the child bearing before age 18 by current age of women the table shows that: x Age by age, fewer women in the urban areas experienced bearing before age 18 compared with their rural counterparts. x Child bearing before age 18 is more prevalent among older generation of urban women while in the rural areas the child bearing before age 18 is more prevalent among younger women. 8.2 Contraception Appropriate family planning is important to the health of women and children by: 1) preventing pregnancies that are too early or too late; 2) extending the period between births; and 3) limiting the Sudan number of children. Access by all couples to information and services to prevent pregnancies that are too early, too closely spaced, too late or too many is critical. 137 Table RH.5: Use of contraception Percentage of women age 15-49 years currently married who are using (or whose partner is using) a contraceptive method, Sudan MICS, 2014 Background characteristic s Percent of women currently married who are using (or whose partner is using): Any moder n method Any traditiona l method Any metho d [1] Number of women currentl y married Not metho d IUD Injecta b. Implant s Pill Male condo m Femal e condo m Diaphrag m / foam /jelly LA M Periodic abstinenc e /Rhythm Withd -rawal Othe r Missin g Sudan 87.8 0.4 1.4 0.3 9.0 0.0 0.0 0.0 0.4 0.2 0.0 0.3 0.1 11.7 0.5 12.2 11,867 State Northern 77.1 0.9 2.4 1.2 15.0 0.1 0.0 0.0 0.2 1.3 0.0 1.8 0.0 19.7 3.1 22.9 280 River Nile 78.7 0.3 2.4 0.1 15.7 0.1 0.0 0.0 1.3 0.5 0.4 0.4 0.0 19.9 1.4 21.3 409 Red Sea 90.4 0.5 1.4 0.5 7.1 0.0 0.1 0.0 0.0 0.0 0.0 0.0 0.0 9.6 0.0 9.6 323 Kassala 92.1 0.1 0.8 0.2 6.2 0.0 0.0 0.0 0.0 0.2 0.0 0.2 0.2 7.3 0.4 7.9 506 Gadarif 90.5 0.1 1.1 0.0 8.0 0.0 0.0 0.0 0.0 0.1 0.0 0.2 0.0 9.2 0.3 9.5 630 Khartoum 73.5 1.7 3.3 1.5 17.3 0.1 0.0 0.0 1.0 0.5 0.0 1.0 0.2 24.9 1.5 26.5 1,623 Gezira 87.8 0.2 1.6 0.0 9.6 0.0 0.1 0.0 0.4 0.1 0.1 0.0 0.1 11.9 0.2 12.2 1,961 White Nile 84.4 0.2 1.6 0.0 11.9 0.1 0.0 0.0 0.4 0.0 0.0 0.9 0.5 14.2 0.9 15.6 577 Sinnar 86.5 0.1 0.9 0.1 11.8 0.0 0.0 0.0 0.6 0.1 0.1 0.0 0.0 13.4 0.1 13.5 450 Blue Nile 92.9 0.1 1.1 0.3 4.5 0.0 0.0 0.0 0.9 0.0 0.0 0.2 0.0 6.9 0.2 7.1 525 North Kordofan 85.3 0.1 0.7 0.0 13.3 0.0 0.0 0.0 0.1 0.2 0.0 0.0 0.2 14.2 0.2 14.7 743 South Kordofan 91.0 0.1 1.1 0.0 7.2 0.0 0.0 0.0 0.4 0.0 0.0 0.1 0.1 8.8 0.1 9.0 355 West Kordofan 93.9 0.1 0.2 0.1 4.8 0.0 0.0 0.3 0.4 0.0 0.0 0.0 0.0 6.0 0.0 6.1 687 North Darfur 96.3 0.5 0.2 0.1 2.7 0.0 0.0 0.0 0.1 0.0 0.0 0.0 0.0 3.7 0.0 3.7 913 West Darfur 95.9 0.3 0.8 0.0 2.4 0.2 0.0 0.0 0.2 0.2 0.0 0.0 0.0 3.9 0.2 4.1 383 South Darfur 94.6 0.0 1.6 0.1 3.6 0.0 0.0 0.0 0.0 0.0 0.0 0.1 0.0 5.3 0.1 5.4 933 Central Darfur 97.1 0.0 0.2 0.0 2.4 0.0 0.2 0.0 0.0 0.2 0.0 0.0 0.0 2.7 0.2 2.9 188 East Darfur 93.8 0.4 0.5 0.1 3.8 0.0 0.0 0.0 1.0 0.0 0.0 0.2 0.1 5.8 0.2 6.2 378 Area Urban 79.9 1.0 1.9 0.8 14.5 0.1 0.0 0.0 0.7 0.3 0.1 0.7 0.0 19.0 1.0 20.1 3,437 Rural 91.0 0.2 1.2 0.1 6.8 0.0 0.0 0.0 0.3 0.1 0.0 0.1 0.1 8.7 0.3 9.0 8,430 Age 15-19 93.6 0.0 0.2 0.0 5.5 0.0 0.0 0.0 0.2 0.5 0.0 0.0 0.0 5.9 0.5 6.4 741 138 Background characteristic s Percent of women currently married who are using (or whose partner is using): Any moder n method Any traditiona l method Any metho d [1] Number of women currentl y married Not metho d IUD Injecta b. Implant s Pill Male condo m Femal e condo m Diaphrag m / foam /jelly LA M Periodic abstinenc e /Rhythm Withd -rawal Othe r Missin g 20-24 89.3 0.2 1.1 0.3 8.3 0.0 0.0 0.0 0.5 0.0 0.0 0.0 0.2 10.5 0.0 10.7 1,737 25-29 86.0 0.2 0.8 0.5 11.8 0.0 0.0 0.0 0.4 0.1 0.0 0.0 0.2 13.7 0.1 14.0 2,617 30-34 86.7 0.5 1.3 0.5 9.5 0.1 0.0 0.1 0.7 0.1 0.0 0.3 0.1 12.8 0.4 13.3 2,130 35-39 85.3 0.3 2.9 0.2 10.0 0.0 0.0 0.0 0.5 0.1 0.0 0.6 0.0 14.1 0.7 14.7 2,160 40-44 88.1 0.8 2.2 0.1 7.8 0.1 0.1 0.0 0.2 0.5 0.0 0.2 0.0 11.3 0.6 11.9 1,374 45-49 92.2 1.2 0.4 0.0 4.4 0.0 0.0 0.0 0.2 0.4 0.3 1.0 0.0 6.2 1.6 7.8 1,107 Number of living children 0 99.6 0.0 0.1 0.0 .3 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.4 0.0 .4 1,156 1 89.6 0.0 0.2 0.3 9.2 0.0 0.0 0.0 0.2 0.3 0.0 0.1 0.0 9.9 0.4 10.4 1,506 2 83.9 0.5 1.3 0.7 12.9 0.0 0.0 0.0 0.5 0.0 0.0 0.0 0.2 15.9 0.0 16.1 1,590 3 82.5 0.6 2.0 0.3 13.4 0.1 0.0 0.0 0.5 0.1 0.1 0.2 0.2 17.0 0.3 17.5 1,653 4+ 87.5 0.5 1.9 0.2 8.4 0.0 0.0 0.0 0.5 0.2 0.0 0.5 0.1 11.7 0.8 12.5 5,962 Education None 95.6 0.1 0.5 0.0 3.2 0.0 0.0 0.0 0.3 0.0 0.0 0.1 0.0 4.2 0.1 4.4 4,778 Primary 86.7 0.3 1.8 0.2 9.7 0.1 0.0 0.1 0.5 0.2 0.0 0.3 0.2 12.6 0.5 13.3 3,961 Secondary 79.0 0.8 2.6 0.5 15.4 0.0 0.1 0.0 0.6 0.4 0.2 0.4 0.0 20.0 1.0 21.0 2,228 Higher 72.4 1.4 1.9 1.8 21.1 0.1 0.0 0.0 0.3 0.2 0.1 0.5 0.1 26.6 0.9 27.6 895 Missing/DK * * * * * * * * * * * * * * * * 5 Wealth index quintile Poorest 96.2 0.1 0.2 0.0 3.3 0.0 0.0 0.0 0.2 0.0 0.0 0.0 0.0 3.8 0.0 3.8 2,341 Second 94.9 0.1 0.7 0.0 3.7 0.0 0.0 .1 0.3 0.1 0.0 0.0 0.1 4.9 0.2 5.1 2,412 Middle 90.9 0.1 1.2 0.1 7.1 0.0 0.0 0.0 0.3 0.0 0.0 0.2 0.0 8.8 0.3 9.1 2,417 Fourth 82.7 0.5 2.5 0.2 12.4 0.0 0.1 0.0 0.9 0.1 0.0 0.2 0.3 16.7 0.3 17.3 2,333 Richest 74.0 1.3 2.6 1.2 18.7 0.1 0.0 0.0 0.4 0.5 0.2 0.9 0.0 24.4 1.7 26.0 2,364 [1] MICS indicator 5.3; MDG indicator 5.3 - Contraceptive prevalence rate, [*] Based on less than 25 unweighted cases and has been suppressed. 139 Current use of contraception was reported by 12.2 percent of women currently married31 (See Table RH.5). The most popular method was the pill which is used by about one in ten married women in Sudan (9.0 percent). The next most popular method is injectable, which accounts for 1.4 percent of married women. Between 0.4 percent and 1.4 percent of married women reported the use of IUDs, and injectable. Less than 1 percent use periodic abstinence, withdrawal, female condom, male condom, implants, diaphragm/foam/jelly or the lactational amenorrhea method (LAM). Almost 87.8 percent of the married women reported that they are not using any form of contraception. The survey results show that contraceptive prevalence ranges from 2.9 percent in Central Darfur to 26.5 percent in Khartoum State. About 20.1 percent of married women in urban and 9.0 percent in rural areas use a method of contraception. The findings by state and area are shown in Figure RH.5. Adolescents are far less likely to use contraception than older women. Only 6.4 percent of women age 15-19 married currently use a method of contraception compared to 10.7 percent of 20-24 year olds, while the use of contraception among older women ranges from 7.8 percent to 14.7 percent. Women’s level of education is strongly associated with contraceptive prevalence. The percentage of married women using any method of contraception rises from 4.4 percent among those with no education to 13.3 percent among those with primary education, and to 21.0 percent and 27.6 percent among those with secondary and higher education respectively. Despite the differences in overall prevalence, the pattern of use by specific methods does not vary significantly with the level of education. F i g u r e R H . 2 : D i f f e r e n t i a l s i n c o n t r a c e p t i v e u s e , S u d a n M IC S , 2 0 1 4 31 All references to “married women” in this chapter include women in marital union as well. 27 23 21 16 15 14 12 10109 8 7 66 5 44 3 20 9 0 28 21 13 4 12 140 8.3 Unmet Need Unmet need for contraception refers to fecund women who are married and are not using any method of contraception, but who wish to postpone the next birth (spacing) or who wish to stop childbearing altogether (limiting). Unmet need is identified in MICS by using a set of questions eliciting current behaviours and preferences pertaining to contraceptive use, fecundity, and fertility preferences. Table RH.6 shows the levels of met need for contraception, unmet need, and the demand for contraception satisfied. Unmet need for spacing is defined as the percentage of women who are married and are not using a method of contraception AND x are not pregnant, and not postpartum amenorrheic32, and are fecund33, and say they want to wait two or more years for their next birth OR x are not pregnant, and not postpartum amenorrheic, and are fecund, and unsure whether they want another child OR x are pregnant, and say that pregnancy was mistimed: would have wanted to wait OR x are postpartum amenorrheic, and say that the birth was mistimed: would have wanted to wait Unmet need for limiting is defined as percentage of women who are married and are not using a method of contraception AND x are not pregnant, and not postpartum amenorrheic, and are fecund, and say they do not want any more children OR x are pregnant, and say they did not want to have a child OR x Are postpartum amenorrheic, and say that they did not want the birth. Sudan unmet need for contraception is the sum of unmet need for spacing and unmet need for limiting. This indicator is also known as unmet for family planning and is one of the indicators used to track progress towards achieving the MDG 5 of improving maternal health. This indicator is also known as unmet need for family planning and is one of the indicators used to track progress toward the Millennium Development Goal 5 of improving maternal health. Met need for limiting includes women married who are using (or whose partner is using) a contraceptive method34, and who want no more children, are using male or female sterilization, or declare themselves as infecund. Met need for spacing includes women who are using (or whose partner is using) a contraceptive method, and who want to have another child, or are undecided 32 A woman is postpartum amenorrheic if she had a birth in last two years and is not currently pregnant, and her menstrual period has not returned since the birth of the last child 33 A woman is considered infecund if she is neither pregnant nor postpartum amenorrheic, and (1a) has not had menstruation for at least six months, or (1b) never menstruated, or (1c) her last menstruation occurred before her last birth, or (1d) in menopause/has had hysterectomy OR (2) She declares that she has had hysterectomy, or that she has never menstruated, or that she is menopausal, or that she has been trying to get pregnant for 2 or more years without result in response to questions on why she thinks she is not physically able to get pregnant at the time of survey OR (3) She declares she cannot get pregnant when asked about desire for future birth OR (4) She has not had a birth in the preceding 5 years, is currently not using contraception and is currently married and was continuously married during the last 5 years preceding the survey. 34 In this chapter, whenever reference is made to the use of a contraceptive by a woman, this may refer to her partner using a contraceptive method (such as male condom). 141 whether to have another child. The Sudan of met need for spacing and limiting ads up to the Sudan met need for contraception. Using information on contraception and unmet need, the percentage of demand for contraception satisfied is also estimated from the MICS data. The percentage of demand satisfied is defined as the proportion of women currently married who are currently using contraception, over the Sudan demand for contraception. The Sudan demand for contraception includes women who currently have an unmet need (for spacing or limiting), plus those who are currently using contraception. Table RH.6 shows that the Sudan met need (13.4 percent) is higher than the Sudan unmet need (26.6 percent) for family planning. Unmet need is also highest among rural (27.5 percent) compared to urban women (24.4 percent); and is higher among women with no education 926.9 percent) or primary education (28.8 percent) compared to those with secondary (24.0 percent) and higher education (21.5 percent). The table also highlights that the Sudan demand for satifactory family planning is 33.4 percent, with some discrepancies according to location with satifactory demand in urban areas as 47.4 percent while in rural areas it is still relatively low (26.4 percent). Table RH.6: Unmet need for contraception Percentage of women age 15-49 years currently married with an unmet need for family planning and percentage of demand for contraception satisfied, Sudan MICS, 2014 Background characteristics Met need for contraception Unmet need for contraception Number of women currently married Percentage of demand for contraception satisfied Number of women currently married with need for contraception For spacing For limiting Total For spacing For limiting Total [1] Sudan 9.1 4.2 13.4 19.1 7.5 26.6 11,867 33.4 4,739 State Northern 15.1 9.5 24.6 15.6 14.3 29.9 280 45.1 153 River Nile 16.1 7.0 23.1 16.4 8.4 24.8 409 48.3 196 Red Sea 7.5 3.0 10.5 13.0 6.1 19.1 323 35.5 96 Kassala 5.0 3.8 8.8 12.0 4.7 16.7 506 34.5 129 Gadarif 7.4 2.6 10.0 19.4 4.6 24.0 630 29.4 214 Khartoum 18.4 11.1 29.5 14.6 6.6 21.3 1,623 58.2 824 Gezira 9.4 3.2 12.6 22.5 6.2 28.7 1,961 30.5 811 White Nile 11.4 5.8 17.2 19.8 9.1 28.8 577 37.4 266 Sinnar 10.6 4.1 14.7 19.7 6.5 26.1 450 36.1 184 Blue Nile 6.2 1.6 7.8 20.7 5.1 25.8 525 23.1 176 North Kordofan 11.9 4.6 16.5 19.9 12.5 32.4 743 33.7 363 South Kordofan 7.6 1.8 9.4 24.1 9.7 33.8 355 21.7 153 West Kordofan 4.6 1.7 6.2 16.0 8.0 23.9 687 20.7 207 North Darfur 3.4 0.9 4.4 21.2 8.4 29.7 913 12.8 311 West Darfur 3.2 1.2 4.4 16.1 5.1 21.2 383 17.2 98 South Darfur 4.0 2.3 6.4 22.9 8.9 31.8 933 16.7 356 Central Darfur 3.2 0.6 3.8 19.8 8.0 27.9 188 11.9 60 East Darfur 3.6 3.0 6.6 22.4 8.5 30.9 378 17.5 142 142 Background characteristics Met need for contraception Unmet need for contraception Number of women currently married Percentage of demand for contraception satisfied Number of women currently married with need for contraception For spacing For limiting Total For spacing For limiting Total [1] Area Urban 13.9 8.1 22.0 16.3 8.1 24.4 3,437 47.4 1,595 Rural 7.2 2.7 9.8 20.2 7.3 27.5 8,430 26.4 3,144 Age 15-19 6.7 0.3 6.9 23.8 1.0 24.8 741 21.9 235 20-24 10.2 1.6 11.8 23.3 1.7 25.0 1,737 32.1 641 25-29 13.1 2.6 15.7 22.9 4.9 27.8 2,617 36.1 1,137 30-34 10.7 4.2 14.9 21.6 8.6 30.2 2,130 33.1 961 35-39 9.1 6.5 15.6 17.7 9.8 27.5 2,160 36.2 932 40-44 4.4 8.1 12.5 11.3 15.3 26.6 1,374 32.0 538 45-49 2.2 6.0 8.2 7.6 11.0 18.6 1,107 30.6 297 Education None 2.8 1.9 4.7 18.4 8.5 26.9 4,778 14.9 1,509 Primary 10.2 4.4 14.5 21.5 7.2 28.8 3,961 33.6 1,716 Secondary 15.0 8.3 23.3 16.3 7.7 24.0 2,228 49.2 1,053 Higher 23.5 6.3 29.8 18.5 3.0 21.5 895 58.1 459 Missing/DK * * * * * * 5 * 2 [[1] MICS indicator 5.4; MDG indicator 5.6 - Unmet need [*] Based on less than 25 unweighted cases and has been suppressed. Table RH.6 shows that unmet need for contraception is highest (33.8 percent) among women in South Kordofan State and lowest (16.7 percent) among women in Kassala State. The results show no large differences in the unmet need of different age groups, this ranges from 24.8 percent for women in the age 15-19 to 30.2 percent among those falling in the age group 30 – 34. 8.4 Antenatal Care (ANC) The antenatal period presents important opportunities for reaching pregnant women with a number of interventions that may be vital to their health and well-being and that of their infants. Better understanding of foetal growth and development and its relationship to the mother's health has resulted in increased attention to the potential of antenatal care as an intervention to improve both maternal and new-born health. For example, antenatal care can be used to inform women and families about risks and symptoms in pregnancy and about the risks of labour and delivery, and therefore it may provide the route for ensuring that pregnant women do, in practice, deliver with the assistance of a skilled health care provider. Antenatal visits also provide an opportunity to supply information on birth spacing, which is recognized as an important factor in improving infant survival. Tetanus immunization during pregnancy can be life-saving for both the mother and the infant. The prevention and treatment of malaria among pregnant women, management of anaemia during pregnancy and treatment of sexually transmitted infections (STIs) can significantly improve foetal outcomes and improve maternal health. Adverse outcomes such as low birth weight can be reduced through a combination of interventions to improve women's nutritional status and prevent infections (e.g., malaria and STIs) during pregnancy. More recently, the potential of the antenatal care as an entry 143 point for HIV prevention and care, in particular for the prevention of HIV transmission from mother to child, has led to renewed interest in access to and use of antenatal services. WHO recommends a minimum of four antenatal visits based on a review of the effectiveness of different models of antenatal care. WHO guidelines are specific on the content on antenatal care visits, which include: x Blood pressure measurement x Urine testing for bacteriuria and proteinuria x Blood testing to detect syphilis and severe anaemia x Weight/height measurement (optional). It is of crucial importance for pregnant women to start attending antenatal care visits as early in pregnancy as possible in order to prevent and detect pregnancy conditions that could affect both the woman and her baby. Antenatal care should continue throughout the entire pregnancy. Antenatal care coverage indicators (at least one visit with a skilled provider and 4 or more visits with any providers) are used to track progress toward the Millennium Development Goal 5 of improving maternal health. The type of personnel providing antenatal care to women age 15-49 years who gave birth in the two years preceding is presented in Table RH.7. Overall, the proportion of women who received ANC from any skilled provider was 79.1 percent while those women who did not receive ANC was 19.9 percent. There exists rural-urban differentials in favour of women who received antenatal care in urban areas (90.8 percent) compared to women in rural areas (74.9 percent). There was also significant differences among the states for women who received ANC from any provider; ranging from 61.8 percent of women in South Darfur state to 97.1 percent of the women in Khartoum state. Differences also exist among women in the wealth index households who received ANC ranging from 61.7 in the poorest households to 97.2 percent in the richest households. 144 Table RH.7: Antenatal care coverage Percent distribution of women age 15-49 years with a live birth in the last two years by antenatal care provider during the pregnancy for the last birth, Sudan MICS, 2014 Background characteristics Provider of antenatal care [a] Any skilled provider [1] Number of women with a live birth in the last two years Medical doctor Nurse / Midwife Auxiliary midwife Certified midwife Medical assistant Traditional birth attendant Community health worker Other/ missing No antenatal care Sudan 55.4 1.5 2.9 17.5 1.7 0.8 0.1 0.1 19.9 79.1 5,622 State Northern 94.7 0.0 0.0 0.0 0.0 0.0 0.0 0.0 5.3 94.7 92 River Nile 88.8 0.0 1.2 4.4 0.7 0.0 0.0 0.0 4.8 95.2 151 Red Sea 64.2 1.7 1.4 5.1 0.0 0.9 0.0 0.0 26.7 72.4 92 Kassala 60.4 0.3 4.8 11.5 6.0 0.0 0.0 0.5 16.5 83.0 199 Gadarif 58.5 2.9 2.5 16.7 0.0 0.6 0.0 0.0 18.9 80.5 307 Khartoum 84.2 1.8 4.8 6.3 0.0 0.0 0.5 0.0 2.4 97.1 684 Gezira 74.9 1.0 2.4 4.9 0.0 0.0 0.0 0.0 16.7 83.3 852 White Nile 71.1 0.2 0.0 6.2 1.2 0.0 0.1 0.0 21.1 78.8 273 Sinnar 59.3 2.0 3.0 11.0 0.0 0.0 0.0 0.0 24.7 75.3 226 Blue Nile 46.9 0.5 1.0 23.0 0.4 0.2 0.0 0.0 28.0 71.8 287 North Kordofan 66.3 0.6 1.9 12.7 4.2 0.0 0.0 0.0 14.4 85.6 352 South Kordofan 38.8 1.1 7.4 36.7 0.9 0.3 0.2 1.0 13.4 85.1 194 West Kordofan 37.2 3.8 3.0 18.3 3.0 0.6 0.2 0.0 34.0 65.3 341 North Darfur 35.5 2.1 5.8 22.2 2.9 2.3 0.4 0.0 28.7 68.7 525 West Darfur 15.6 2.3 0.9 55.7 0.7 2.8 0.0 0.0 22.0 75.2 179 South Darfur 25.3 1.5 3.2 27.3 4.5 2.3 0.0 0.3 35.7 61.8 556 Central Darfur 16.1 1.2 0.5 42.1 7.9 8.1 0.0 0.4 23.6 67.9 99 East Darfur 24.3 1.8 0.0 56.4 0.5 0.6 0.2 0.0 16.3 82.9 211 Area Urban 68.3 2.4 4.9 14.9 0.2 0.3 0.0 0.1 8.9 90.8 1,488 Rural 50.8 1.2 2.2 18.5 2.2 1.0 0.2 0.1 23.9 74.9 4,134 Mother's age at birth Less than 20 56.8 0.9 1.6 19.6 2.5 0.7 0.0 0.0 17.9 81.4 640 20-34 56.2 1.3 3.2 17.2 1.6 0.9 0.2 0.1 19.5 79.4 4,001 35-49 51.4 2.9 2.9 17.6 1.7 0.6 0.1 0.0 22.9 76.4 980 Missing * * * * * * * * * * 1 Education None 35.8 1.3 2.8 23.1 2.7 1.5 0.1 0.1 32.5 65.7 2,247 Primary 59.3 2.0 3.1 18.0 1.3 0.3 0.2 0.1 15.7 83.8 2,022 Secondary 77.4 1.5 3.6 9.2 0.8 0.2 0.0 0.0 7.2 92.5 942 Higher 93.1 0.0 1.3 4.0 0.2 0.4 0.1 0.0 .9 98.6 410 Wealth index quintile Poorest 27.8 1.0 2.1 26.0 4.7 2.1 0.1 0.3 35.8 61.7 1,251 Second 41.3 2.2 2.5 25.5 2.3 1.1 0.1 0.1 24.8 73.9 1,232 Middle 53.6 1.6 4.9 17.3 0.5 0.5 0.3 0.0 21.3 78.0 1,192 Fourth 77.9 1.6 3.1 9.3 0.1 0.0 0.1 0.0 7.9 92.0 1,096 Richest 90.0 0.8 1.8 4.5 0.1 0.0 0.0 0.0 2.8 97.2 851 145 In Sudan, antenatal care is mostly provided by medical doctors (55.4 percent) while a minority of women receive care from a traditional birth attendant (0.8 percent), mostly in rural areas. Figure RH.3 below shows the distribution of people that provide antenatal care to the pregnant women F i g u r e R H . 3 a : An t e n a t a l C a r e S e r v i c e P r o v i d e r s , S u d a n M I C S , 2 0 1 4 The percentage of women who received ANC was found to be influenced by the women’s educational level and the level of household wealth: only 65.7 percent of women with no formal education received ANC at least once by skilled personnel, while 83.8 percent of women with primary education and 92.5 percent and 98.6 percent of women with secondary and higher level of education respectively; have received ANC at least once by skilled personnel. There were significant differentials among women who received ANC from households in the richest quintile (97.2 percent) and those in the poorest quintile (61.7 percent) respectively. Table RH.8 shows the number of antenatal care visits during the latest pregnancy that took place within the two years preceding the survey, regardless of provider, by selected characteristics. Almost four in five mothers (82.3 percent) received antenatal care more than once and over half of mothers received antenatal care at least four times (50.7 percent). Mothers from the poorest households and those with primary or no education are less likely than more advantaged mothers to receive antenatal care four or more times. For example, while only 35.1 percent of the women with no education have reported four or more antenatal care visits, as large as 83.1 of the women with higher education have been served four times or more. Along the same line, 31.9 percent of the women living in poorest households reported four or more antenatal care visits compared with 81.3 percent among those living in richest households. Table RH.8 also provides information about the timing of the first antenatal care visit. Overall, 59.2 percent of women with a live birth in the last two years had their first antenatal care visit during the .1 .8 1.5 1.7 2.9 17.5 55.4 .0 10.0 20.0 30.0 40.0 50.0 60.0 Community health worker Traditional birth attendant Nurse / Midwife Medical assistant Auxiliary midwife Certified midwife Medical doctor Percent 146 first trimester of their last pregnancy, with a median of 2.0 months of pregnancy at the first visit among those who received antenatal care. Figure RH.3b: Women age 15-49 years with a live birth in the last two years who made 4 or more antenatal care visits, by state, area and mother’s education, Sudan MICS, 2014 82 67 59 58 56 54 53 53 51 51 47 47 46 45 44 43 41 37 28 72 43 83 69 53 35 0 10 20 30 40 50 60 70 80 90 Kh ar to um N or th er n So ut h Ko rd of an N or th K or do fa n W es t D ar fu r Ka ss al a Re d Se a Ri ve r N ile Su da n Ge zir a Ce nt ra l D ar fu r Ea st D ar fu r W hi te N ile Ga da rif Si nn ar Bl ue N ile So ut h Da rf ur N or th D ar fu r W es t K or do fa n Ar ea U rb an Ru ra l M ot he r's E du ca tio n Hi gh er Se co nd ar y Pr im ar y N on e 147 Table RH.8: Number of antenatal care visits Percent distribution of women age 15-49 years with a live birth in the last two years by number of antenatal care visits by any provider and by the timing of first antenatal care visits, Sudan MICS, 2014 Background characteristics Percent distribution of women who had: Percent distribution of women by number of months pregnant at the time of first antenatal care visit Number of women with a live birth in the last two years Median months pregnant at first ANC visit Number of women with a live birth in the last two years who had at least one ANC visit No antenetal care visits 1 visit 2 visits 3 visits 4 or more visits [1] Missing/ DK No antenatal care visits First trimester 4-5 months 6-7 months 8+ months DK/ Missing Sudan 19.9 4.6 9.3 14.4 50.7 1.0 20.1 46.5 21.3 9.4 2.4 0.4 5,622 3 4,468 State Northern 5.6 5.2 9.3 13.5 66.5 0.0 5.3 63.1 17.8 9.4 4.1 0.3 92 2 87 River Nile 4.8 7.8 11.8 22.6 52.9 0.0 4.8 49.6 28.8 11.7 4.6 0.4 151 3 143 Red Sea 26.7 1.1 6.3 11.5 53.4 1.0 27.2 44.4 22.6 4.2 0.4 1.2 92 3 66 Kassala 16.5 6.8 8.8 13.3 54.0 0.7 17.4 44.8 22.9 11.4 2.9 0.6 199 3 164 Gadarif 18.9 5.8 12.5 16.7 44.8 1.4 18.9 43.3 27.4 7.3 1.6 1.6 307 3 244 Khartoum 2.4 1.8 5.1 8.2 81.9 0.6 2.7 65.8 22.7 7.9 0.3 0.6 684 3 661 Gezira 16.7 4.9 10.8 16.8 50.5 0.2 16.7 55.0 18.1 8.5 1.7 0.0 852 3 710 White Nile 21.1 8.7 8.3 16.1 45.5 0.4 21.1 39.8 23.6 9.2 6.0 0.3 273 3 215 Sinnar 24.7 6.2 12.2 13.5 43.5 0.0 24.7 48.5 17.9 7.5 1.5 0.0 226 3 170 Blue Nile 28.0 5.0 9.3 14.8 42.7 0.3 28.0 46.2 14.9 8.0 2.7 0.2 287 3 206 North Kordofan 14.4 1.6 6.9 15.6 57.7 3.9 14.8 54.7 18.0 10.5 2.0 0.0 352 3 300 South Kordofan 13.6 2.7 9.4 14.2 59.3 0.9 13.6 36.4 32.8 14.3 2.5 0.4 194 4 167 West Kordofan 34.0 5.7 13.7 17.9 28.1 0.6 34.1 32.7 15.1 11.8 5.2 1.0 341 3 221 North Darfur 28.8 5.8 12.9 14.8 36.9 0.8 28.7 30.8 27.7 10.7 1.8 0.3 525 4 373 148 Background characteristics Percent distribution of women who had: Percent distribution of women by number of months pregnant at the time of first antenatal care visit Number of women with a live birth in the last two years Median months pregnant at first ANC visit Number of women with a live birth in the last two years who had at least one ANC visit No antenetal care visits 1 visit 2 visits 3 visits 4 or more visits [1] Missing/ DK No antenatal care visits First trimester 4-5 months 6-7 months 8+ months DK/ Missing West Darfur 22.0 3.3 8.9 9.8 56.1 0.0 23.1 43.8 21.2 8.6 2.9 0.3 179 3 137 South Darfur 35.7 2.9 6.8 11.8 40.9 1.9 35.7 38.0 14.8 8.5 2.3 0.7 556 3 354 Central Darfur 23.6 3.6 5.7 17.7 47.1 2.3 23.6 40.5 22.8 11.0 1.9 0.2 99 3 75 East Darfur 16.3 8.8 7.2 18.9 46.8 2.1 16.8 37.4 29.8 11.6 4.3 0.2 211 4 175 Area Urban 9.0 2.4 4.8 10.5 71.8 1.5 9.2 58.3 23.4 6.8 1.6 0.7 1,488 3 1,340 Rural 23.9 5.4 10.9 15.9 43.2 0.8 24.0 42.2 20.6 10.3 2.7 0.3 4,134 3 3,128 Mother's age at birth Less than 20 17.9 6.0 9.4 16.9 49.0 0.8 18.0 52.2 19.1 7.9 2.4 0.3 640 3 523 20-34 19.5 4.4 9.8 14.7 50.7 1.0 19.7 46.5 21.7 9.3 2.4 0.4 4,001 3 3,196 35-49 22.9 4.8 7.4 12.0 52.2 0.8 23.0 42.5 21.2 10.5 2.3 0.5 980 3 750 Education None 32.5 5.6 11.6 14.3 35.1 1.0 32.6 33.8 19.6 10.2 3.0 0.7 2,247 3 1,498 Primary 15.8 4.8 10.2 15.5 53.0 0.7 15.9 47.0 24.6 10.2 2.1 0.1 2,022 3 1,698 Secondary 7.2 3.3 5.0 14.0 69.1 1.5 7.3 60.5 21.4 8.5 1.9 0.4 942 3 870 Higher 0.9 1.7 2.3 11.1 83.1 0.9 1.5 80.7 13.7 2.1 1.5 0.5 410 2 402 149 The coverage of key services that pregnant women are expected to receive during antenatal care are shown in Table RH.9 below. Among those women who had a live birth during the two years preceding the survey, 66.1 percent reported that a blood sample was taken during antenatal care visits, 66.9 percent that their blood pressure was checked, and 66.1 percent that urine specimen was taken. In general, 62.8 percent of these women reported that their blood sample and urine taken and blood pressure measured. The proportion of women who had had two samples and one measurement taken was higher for urban (81.3 percent) than rural areas (56.1 percent) and it increases with education level of the mother; with 43.4 percent for those with no education, 68.3 percent for mothers with primary, 82.7 for those with secondary, and 96.2 percent for women with higher education. Khartoum State had the highest proportion (95.6 percent) of women who received antenatal care and had their blood pressure measured, urine sample taken and blood test taken during ANC visits. The lowest proportion of women who received these services during ANC visits was in Central Darfur State (30.7 percent). The survey results indicated significant differentials according to household well-being with 38.1 percent in the poorest quintile and 92.7 percent of the women in the richest quintile had had their blood pressure measured, urine sample taken and blood test done during the ANC visit Table RH.9: Content of antenatal care Percentage of women age 15-49 years with a live birth in the last two years who, at least once, had their blood pressure measured, urine sample taken, and blood sample taken as part of antenatal care, during the pregnancy for the last birth, Sudan MICS, 2014 Background characteristics Percentage of women who, during the pregnancy of their last birth, had: Number of women with a live birth in the last two years Blood pressure measured Urine sample taken Blood sample taken Blood pressure measured, urine and blood sample taken [1] Sudan 66.9 66.1 66.1 62.8 5,622 State Northern 91.3 94.0 94.1 90.6 92 River Nile 90.2 88.7 89.9 87.3 151 Red Sea 72.6 72.0 67.6 66.1 92 Kassala 73.2 74.4 73.8 71.5 199 Gadarif 66.3 65.9 65.2 64.4 307 Khartoum 96.3 96.9 96.1 95.6 684 Gezira 74.8 72.8 74.1 68.9 852 White Nile 70.3 69.0 68.8 65.6 273 Sinnar 62.5 63.8 64.1 58.8 226 Blue Nile 50.7 54.8 53.6 46.8 287 North Kordofan 74.1 75.3 73.9 73.1 352 South Kordofan 80.4 81.6 81.1 79.5 194 West Kordofan 55.0 54.8 54.8 53.0 341 North Darfur 51.8 49.8 49.8 46.7 525 West Darfur 51.9 48.7 48.5 45.0 179 South Darfur 37.7 37.7 37.5 35.2 556 Central Darfur 47.3 35.0 42.1 30.7 99 150 Background characteristics Percentage of women who, during the pregnancy of their last birth, had: Number of women with a live birth in the last two years Blood pressure measured Urine sample taken Blood sample taken Blood pressure measured, urine and blood sample taken [1] East Darfur 58.2 48.3 49.0 38.3 211 Area Urban 83.6 84.1 83.7 81.3 1,488 Rural 60.9 59.6 59.7 56.1 4,134 Mother's age at birth Less than 20 64.4 65.4 66.3 61.2 640 20-34 67.9 67.0 66.7 63.7 4,001 35-49 64.6 63.0 63.4 60.2 980 Missing * * * * 1 Mother's education None 48.2 46.7 47.2 43.4 2,247 Primary 72.7 71.9 71.4 68.3 2,022 Secondary 85.7 86.2 86.2 82.7 942 Higher 97.2 97.8 97.0 96.2 410 Wealth index quintile Poorest 44.0 41.3 41.5 38.1 1,251 Second 55.2 55.0 54.8 51.5 1,232 Middle 66.4 66.6 66.4 63.0 1,192 Fourth 85.1 84.3 84.0 80.2 1,096 Richest 94.7 94.3 95.0 92.7 851 [1] MICS indicator 5.6 - Content of antenatal care [*] Based on less than 25 unweighted cases and has been suppressed. 8.5 Assistance at Delivery About three quarters of all maternal deaths occur due to direct obstetric causes.35 The single most critical intervention for safe motherhood is to ensure that a competent health worker with midwifery skills is present at every birth, and in case of emergency that transport is available to a referral facility for obstetric care. The skilled attendant at delivery indicator is used to track progress toward the Millennium Development Goal 5 of improving maternal health. The MICS included a number of questions to assess the proportion of births attended by a skilled attendant. A skilled attendant includes a doctor, nurse, certified midwife, Traditional Birth Attendants, nurse/midwife, and community health workers. Over seventy (77.7) percent of births occurring in the two years preceding the MICS 2014 survey were delivered by the assistance of skilled personnel (Table RH.10). This percentage is higher in urban areas with 93.2 percent of the deliveries by skilled personnel than 71.9 percent in rural areas. Deliveries by 35 Say, L et al. 2014. Global causes of maternal death: a WHO systematic analysis. The Lancet Global Health 2(6): e323-33. DOI: 10.1016/S2214-109X(14)70227-X 151 skilled personnel varied widely in the States ranging from 36.4 percent in Central Darfur state 99.6 percent in Khartoum State. Results show that delivery by skilled personnel is found to be strongly influenced by the level of education; assistance by skilled delivery attendant for women with no education was 58.5 percent, while among those with primary education it was 86.2 percent, and among women with secondary and higher education levels it was 95.7 percent and 97.6 percent respectively. More than half of the births (55.0 percent) in the two years preceding the MICS survey were delivered with the assistance of a certified midwife. Medical doctors assisted with the delivery of 19.2 percent of births and the births delivered by assistance of Traditional Birth Attendants (TBAs) with 18 percent. F i g u r e R H . 3 : P e r s o n a s s i s t i n g a t d e l i v e r y , S u d a n M I C S , 2 0 1 4 Table RH.10 also shows information on women who delivered by caesarean section (C-section) and provides additional information on the timing of the decision to conduct a C-section (before labour pains began or after) in order to better assess if such decisions are mostly driven by medical or non– medical reasons. Overall, 9.1 percent of women who delivered in the last two years had a C-section; for 6.1 percent of women, the decision was taken before the onset of labour pains and for 3 percent of them after. Mother’s age at delivery was found to considerably affect the decision for opting to C-section as shown in the data. Women who delivered and had C-section among women less than 20 years is 6.4 percent and it rises to 8.8 percent in age group 20-34, and to 11.9 percent among women in the age group 35- 49. It is clear that women who delivered in the last two years and had a C-section among urban areas (14.7 percent) doubled the percentage of the women in who had C-section in rural areas (7 percent). 0 0 1 3 18 19 55 0 10 20 30 40 50 60 Community health worker Medical Assistant Health Visitor Nurse/Midwife Traditional birth attendant Medical Doctor Certified Midwife Percent 152 Table RH.10: Assistance during delivery and caesarean section Percent distribution of women age 15-49 years with a live birth in the last two years by person providing assistance at delivery, and percentage of births delivered by C-section, Sudan MICS, 2014 Background characteristics Person assisting at delivery Deliver y assiste d by any skilled attend ant [1] Percent delivered by C- section Number of women who had a live birth in the last two years Medic al doctor Nurs e / Mid- wife Healt h visito r Certif ied mid- wife TBA Comm unity health worker Other / missi ng No atten dant Decide d before onset of labour pains Decide d after onset of labour pains C- sectio n total [2] Sudan 19.2 2.5 0.9 55.0 18.0 0.1 3.4 1.0 77.5 6.1 3.0 9.1 5,622 State Northern 49.1 8.7 0.0 41.2 0.0 0.0 1.0 0.0 99.0 23.1 12.2 35.2 92 River Nile 37.7 4.7 1.3 53.3 2.9 0.0 0.0 0.0 97.1 14.0 4.8 18.8 151 Red Sea 25.9 12.8 0.9 38.2 20.2 0.0 2.1 0.0 77.8 8.3 0.6 9.0 92 Kassala 14.3 1.4 0.7 60.3 22.3 0.0 1.0 0.0 76.8 4.7 1.0 5.6 199 Gadarif 13.8 3.8 0.0 65.1 10.1 0.0 5.8 1.4 82.7 3.6 2.9 6.5 307 Khartoum 48.0 1.6 1.7 48.3 0.4 0.0 0.0 0.0 99.6 14.4 6.4 20.7 684 Gezira 25.5 2.2 2.0 62.8 4.0 0.0 2.0 1.4 92.5 7.3 5.1 12.4 852 White Nile 25.1 2.9 0.0 64.2 6.1 0.0 1.6 0.0 92.3 11.5 5.9 17.4 273 Sinnar 16.5 7.5 0.0 65.1 2.8 0.0 6.6 1.4 89.1 3.3 4.0 7.2 226 Blue Nile 7.4 1.6 0.3 51.8 8.9 0.0 21.7 8.4 61.0 2.9 1.1 4.0 287 North Kordofan 18.9 0.7 0.3 67.0 9.6 0.0 3.1 0.3 86.9 5.9 2.2 8.1 352 South Kordofan 4.5 3.5 1.0 71.0 15.6 0.2 3.0 1.2 80.0 3.3 0.8 4.1 194 West Kordofan 6.6 1.7 0.8 57.3 29.0 0.6 3.6 0.4 66.3 1.9 0.2 2.1 341 North Darfur 6.4 1.6 1.7 51.0 38.5 0.0 0.6 0.2 60.7 2.3 1.9 4.2 525 West Darfur 6.7 0.5 0.2 50.3 36.8 0.0 5.4 0.0 57.7 1.9 0.2 2.0 179 South Darfur 9.8 1.8 0.7 36.3 47.9 0.0 2.5 0.9 48.7 2.0 0.5 2.5 556 Central Darfur 3.0 0.0 0.0 33.4 56.7 0.7 5.8 0.5 36.4 1.1 0.5 1.5 99 East Darfur 2.8 2.4 0.0 55.3 36.5 0.3 2.6 0.0 60.6 0.8 0.2 1.0 211 Area Urban 33.1 3.8 1.5 54.8 4.7 0.0 1.7 0.3 93.2 10.5 4.2 14.7 1,488 Rural 14.2 2.0 0.7 55.0 22.8 0.1 4.0 1.2 71.9 4.4 2.6 7.0 4,134 Mother's age at birth Less than 20 14.2 2.5 0.3 59.8 19.2 0.0 3.3 0.7 76.8 3.5 2.9 6.4 640 20-34 19.2 2.3 1.1 55.6 17.9 0.1 3.1 0.8 78.1 5.6 3.2 8.8 4,001 35-49 22.2 3.3 0.8 49.3 17.9 0.1 4.3 1.9 75.7 9.6 2.3 11.9 980 Missing * * * * * * * * * * * * 1 Place of delivery Home 1.5 1.6 1.0 65.8 25.1 0.1 3.6 1.3 69.9 0.0 0.0 0.0 4,006 Health facility 65.1 4.9 0.8 28.4 0.3 0.0 0.5 0.0 99.2 21.9 10.8 32.7 1,559 Public 64.8 4.7 0.7 29.0 0.4 0.0 0.5 0.0 99.1 21.1 10.9 32.0 1,468 Private 70.2 8.1 3.0 18.7 0.0 0.0 0.0 0.0 100.0 34.6 9.6 44.3 91 Other/ DK/Missing 6.1 0.0 0.0 19.5 2.8 0.0 68.6 3.0 25.6 0.0 0.0 0.0 57 Mother's education 153 Background characteristics Person assisting at delivery Deliver y assiste d by any skilled attend ant [1] Percent delivered by C- section Number of women who had a live birth in the last two years Medic al doctor Nurs e / Mid- wife Healt h visito r Certif ied mid- wife TBA Comm unity health worker Other / missi ng No atten dant Decide d before onset of labour pains Decide d after onset of labour pains C- sectio n total [2] None 7.1 2.0 0.8 48.7 33.0 0.0 6.4 2.1 58.5 1.8 1.3 3.1 2,247 Primary 16.0 2.8 0.8 66.7 11.6 0.1 1.7 0.2 86.2 4.6 2.7 7.4 2,022 Secondary 37.8 2.9 1.2 53.8 3.0 0.0 1.0 0.3 95.7 13.7 5.1 18.8 942 Higher 58.2 3.1 2.4 34.0 2.1 0.0 0.2 0.0 97.6 18.8 9.0 27.8 410 Wealth index quintile Poorest 5.0 1.1 0.2 41.6 48.9 0.0 2.4 0.8 .0 1.9 0.7 2.5 1,251 Second 9.6 1.9 0.8 58.2 23.7 0.2 4.6 1.1 47.9 2.1 1.4 3.6 1,232 Middle 13.1 2.2 0.9 68.4 6.8 0.1 6.1 2.3 70.5 4.0 3.0 6.9 1,192 Fourth 27.4 3.6 0.7 63.4 2.5 0.0 1.9 0.4 84.6 7.9 4.8 12.6 1,096 Richest 51.6 4.2 2.7 40.2 0.3 0.0 1.0 0.1 95.2 18.4 6.5 25.0 851 8.6 Place of Delivery Increasing the proportion of births that are delivered in health facilities is an important factor in reducing the health risks to both the mother and the baby. Proper medical attention and hygienic conditions during delivery can reduce the risks of complications and infection that can cause morbidity and mortality to either the mother or the baby. Table RH.11 presents the percentage distribution of women age 15-49 years who had a live birth in the two years preceding the survey by place of delivery, and the percentage of births delivered in a health facility according to their background characteristics. Slightly more than a quarter (27.7 percent) of births in Sudan are delivered in a health facility; of which 26.1 percent occured in public sector facilities while only 1.6 percent of the deliveries occured in private sector facilities. The MICS results also indicate that 71.3 percent of the deliveries takes place at home. Women in urban areas (45.2 percent) are more than twice as likely to deliver in a health facility as their rural counterparts (21.5 percent). Women with higher levels of educational attainment are more likely to deliver in a health facility than women with less education or no education. Specifically; 11.5 percent of women who had delivered in a health facility with no education compared to 25.8 percent of the women with primary education, to 49.8 percent of the women with secondary education, and to 75.5 percent of the women with higher level of education. Institutional deliveries varies from as low as 7.5 percent in West Kordofan to almost ten times (72.5 percent) in Northern state. Similarly, the proportion of births occurring in a health facility steadily increases with wealth from as low as 8.9 percent among women in the poorest households to 70.8 percent among women in the richest households. Majority of the women, 87.1 percent, who received no antenatal care services delivered at home. 154 Table RH.11: Place of delivery Percent distribution of women age 15-49 years with a live birth in the last two years by place of delivery of their last birth, Sudan MICS, 2014 Background characteristics Place of delivery Delivered in health facility [1] Number of women with a live birth in the last two years Public sector health facility Private sector health facility Home Other Missing/ DK Sudan 26.1 1.6 71.3 0.2 0.9 27.7 5,622 State Northern 69.9 2.6 27.1 0.0 0.4 72.5 92 River Nile 54.0 2.4 43.6 0.0 0.0 56.4 151 Red Sea 36.3 10.2 51.5 0.0 2.1 46.5 92 Kassala 26.0 0.9 71.5 0.5 1.1 26.9 199 Gadarif 20.2 0.0 79.5 0.1 0.2 20.2 307 Khartoum 55.5 8.6 35.7 0.0 0.2 64.1 684 Gezira 36.4 0.7 62.5 0.0 0.3 37.1 852 White Nile 33.8 1.4 63.4 0.3 1.1 35.2 273 Sinnar 24.4 0.6 73.7 0.4 0.9 25.0 226 Blue Nile 13.6 0.0 86.1 0.2 0.1 13.6 287 North Kordofan 21.8 0.4 76.1 0.0 1.7 22.2 352 South Kordofan 12.8 0.3 85.0 0.3 1.6 13.1 194 West Kordofan 7.3 0.2 91.4 0.0 1.1 7.5 341 North Darfur 10.7 0.0 88.9 0.1 0.4 10.7 525 West Darfur 12.9 0.4 82.5 0.0 4.2 13.3 179 South Darfur 10.0 0.0 88.6 0.4 1.0 10.0 556 Central Darfur 9.3 0.2 88.1 1.3 1.0 9.5 99 East Darfur 13.3 0.0 84.2 0.5 2.0 13.3 211 Area Urban 40.0 5.2 53.7 0.2 1.0 45.2 1,488 Rural 21.1 0.3 77.6 0.2 0.8 21.5 4,134 Mother's age at birth Less than 20 27.6 0.9 70.7 0.1 0.7 28.5 640 20-34 26.0 1.5 71.6 0.1 0.8 27.5 4,001 35-49 25.7 2.6 70.1 0.3 1.2 28.4 980 Missing * * * * * * 1 Percent of women who had: None 6.8 0.1 89.2 0.2 3.7 6.8 1,120 1-3 visits 18.7 0.7 80.4 0.2 0.1 19.4 1,596 4+ visits 37.9 2.7 59.1 0.1 0.1 40.6 2,852 Missing/DK 23.8 3.7 70.2 0.0 2.4 27.4 54 Mother's education None 11.4 0.1 87.1 0.3 1.2 11.5 2,247 Primary 24.6 1.2 73.6 0.1 0.6 25.8 2,022 155 Background characteristics Place of delivery Delivered in health facility [1] Number of women with a live birth in the last two years Public sector health facility Private sector health facility Home Other Missing/ DK Secondary 46.3 3.5 49.3 0.1 0.8 49.8 942 Higher 67.7 7.8 23.7 0.0 0.8 75.5 410 Wealth index quintile Poorest 8.9 0.0 90.3 0.2 0.6 8.9 1,251 Second 15.1 0.2 83.4 0.3 1.1 15.3 1,232 Middle 18.6 0.6 79.5 0.2 1.0 19.2 1,192 Fourth 37.9 1.1 60.3 0.0 0.7 39.0 1,096 Richest 62.7 8.2 28.3 0.0 0.8 70.8 851 [*] Based on less than 25 unweighted cases and has been suppressed. 8.7 Post-natal Health Checks The time of birth and immediately after is a critical window of opportunity to deliver lifesaving interventions for both the mother and new-born. Across the world, approximately 3 million new-borns annually die in the first month of life36 and the majority of these deaths occur within a day or two of birth37, which is also the time when the majority of maternal deaths occur38. Despite the importance of the first few days following birth, large-scale, nationally representative household survey programmes have not systematically included questions on the post-natal period and care for the mother and new-born. In 2008, the Countdown to 2015 initiative, which monitors progress on maternal, new-born and child health interventions, highlighted this data gap, and called not only for post-natal care (PNC) programmes to be strengthened, but also for better data availability and quality39. Following the establishment and discussions of an Inter-Agency Group on PNC and drawing on lessons learned from earlier attempts of collecting PNC data, a new questionnaire module for MICS was developed and validated. Named the Post-natal Health Checks (PNHC) module, the objective is to collect information on new-borns’ and mothers’ contact with a provider, not content of care. The rationale for this is that as PNC programmes scale up, it is important to measure the coverage of that scale up and ensure that the platform for providing essential services is in place. Content is considered more difficult to measure, particularly because the respondent is asked to recall services delivered up to two years preceding the interview. Table RH.12 below shows the percentage distribution of women age 15-49 years that gave birth in a health facility in the two years preceding the survey by duration of stay in the facility following the delivery, according to background characteristics. 36 UN Interagency Group for Child Mortality Estimation. 2013. Levels and Trends in Child Mortality: Report 2013 37 Lawn, JE et al. 2005. 4 million neonatal deaths: When? Where? Why? Lancet 2005; 365:891–900. 38 WHO, UNICEF, UNFPA, The World Bank. 2012. Trends in Maternal Mortality: 1990-2010. World Health Organization. 39 HMN, UNICEF, WHO. 2008. Countdown to 2015: Tracking Progress in Maternal, Newborn & Child Survival, The 2008 Report. UNICEF. 156 Overall, 51.5 percent of women who gave birth in a health facility stay 12 hours or more in the facility after delivery. Across the country, the percentage of women who stay 12 hours or more varies from 29.3 percent in Central Darfur to 73.2 percent in White Nile State. The survey results indicated small difference between proportions of those delivering in public and private facilities and who stay 12 hours or more in the facility. The proportion of women delivering in private facilities who stay 12 hours or more is 55.2 percent while those delivering in public facilities is 51.2 percent. The same applies to differences between women who deliver in rural areas (55.8 percent) and those who deliver in urban areas (45.8 percent). As expected, nearly all women (95.9 percent) giving birth through C-section stay 12 hours or more in the facility after giving birth. There are no clear patterns with regards to background characteristics of woman’s age at delivery and her education. Safe motherhood programmes have recently increased emphasis on the importance of post-natal care, recommending that all women and new-borns receive a health check within two days of delivery. To assess the extent of post-natal care utilization, women were asked whether they and their new- born received a health check after the delivery, the timing of the first check, and the type of health provider for the woman’s last birth in the two years preceding the survey. Table RH.12: Post-partum stay in health facility Percent distribution of women age 15-49 years with a live birth in the last two years who had their last birth delivered in a health facility by duration of stay in health facility, Sudan MICS, 2014 Background characteristic s Duration of stay in health facility: 12 hours or more [1] Number of women who had their last birth delivere d in a health facility in the last 2 years Less than 6 hours 6-11 hours 12-23 hours 1-2 days 3 days or more Missing/ DK Sudan 44.5 3.7 1.7 18.1 31.7 0.3 51.5 1,559 State Northern 35.4 5.7 0.4 15.7 42.8 0.0 58.9 67 River Nile 61.6 1.2 0.7 6.5 30.0 0.0 37.2 85 Red Sea 68.9 0.0 5.6 5.1 20.5 0.0 31.1 43 Kassala 36.6 2.4 0.0 38.6 22.4 0.0 61.0 54 Gadarif 43.3 1.1 0.0 23.5 32.2 0.0 55.7 62 Khartoum 51.4 3.9 2.3 12.2 30.3 0.0 44.8 438 Gezira 40.0 3.8 2.2 20.9 33.1 0.0 56.2 316 White Nile 23.1 3.4 3.1 21.9 48.2 0.3 73.2 96 Sinnar 46.6 2.5 1.2 22.5 27.2 0.0 50.9 56 Blue Nile (52.8) (1.8) (2.6) (25.1) (17.7) (0.0) (45.4) 39 North Kordofan 45.0 4.6 0.7 22.1 27.6 0.0 50.4 78 South Kordofan (30.7) (5.3) (0.0) (36.7) (25.8) (1.5) (62.5) 25 West Kordofan (39.9) (1.4) (0.0) (10.8) (47.9) (0.0) (58.7) 26 North Darfur (32.5) (11.8) (0.0) (15.8) (40.0) (0.0) (55.8) 56 West Darfur 33.0 2.9 - 39.2 23.7 1.2 100.0 24 157 Background characteristic s Duration of stay in health facility: 12 hours or more [1] Number of women who had their last birth delivere d in a health facility in the last 2 years Less than 6 hours 6-11 hours 12-23 hours 1-2 days 3 days or more Missing/ DK South Darfur (34.6) (1.7) (0.0) (22.0) (35.4) (6.3) (57.4) 55 Central Darfur 70.7 - - 7.2 22.1 - 100.0 9 East Darfur (58.1) (8.8) (2.8) (17.9) (10.7) (1.7) (31.4) 28 Area Urban 49.5 4.3 2.0 13.7 30.1 0.4 45.8 672 Rural 40.8 3.2 1.4 21.4 32.9 0.3 55.8 887 Mother's age at birth Less than 20 46.3 2.8 4.9 23.9 21.2 0.9 50.0 182 20-34 45.2 3.9 1.0 18.4 31.2 0.2 50.7 1,099 35-49 40.8 3.3 2.1 13.1 40.4 0.3 55.6 278 Type of health facility Public 44.7 3.7 1.8 18.3 31.2 0.3 51.2 1,468 Type of delivery 41.5 3.3 0.3 15.0 39.9 0.0 55.2 91 Vaginal birth 65.1 4.7 2.4 21.6 5.8 0.4 29.8 1,046 C-section 2.5 1.5 .1 10.9 84.8 0.1 95.9 511 Missing * * * * * * * 1 Mother's education None 45.6 2.4 1.7 21.8 27.0 1.5 50.5 259 Primary 47.2 2.9 1.3 19.9 28.7 0.1 49.9 521 Secondary 45.4 2.9 2.4 16.1 33.0 0.2 51.5 469 Higher 37.9 7.2 1.0 15.0 38.8 0.0 54.8 310 Wealth index quintile Poorest 40.8 5.5 0.0 24.5 27.8 1.3 52.3 111 Second 47.0 2.4 1.7 23.2 25.5 0.2 50.4 188 Middle 35.8 2.1 0.9 25.1 35.3 0.9 61.2 229 Fourth 45.2 2.9 1.7 18.1 32.1 0.1 51.8 428 Richest 47.3 4.9 2.3 12.7 32.7 0.1 47.7 603 ( ) Figures that are based on 25-49 unweighted cases [*] Based on less than 25 unweighted cases and has been suppressed. Table RH.13 shows the percentage of new-borns born in the last two years who received health checks and post-natal care visits from any health provider after birth. Please note that health checks following birth while in facility or at home refer to checks provided by any health provider regardless of timing (column 1), whereas post-natal care visits refer to a separate visit to check on the health of the new- born and provide preventive care services and therefore do not include health checks following birth while in facility or at home. The indicator Post-natal health checks includes any health check after birth 158 received while in the health facility and at home (column 1), regardless of timing, as well as PNC visits within two days of delivery (columns 2, 3, and 4). Overall, 23.4 percent of new-borns receive a health check following birth while in a facility or at home. With regards to PNC visits, these predominantly occur either on the first or 3 - 6 days following the delivery (2.9 percent and 3.6 percent, respectively). As a result, a Sudan of 27.7 percent of all new- borns receive a post-natal health check. This percentage varies from 12.2 percent in Central Darfur to 57.4 percent in Khartoum. Urban new-borns are more likely to receive a health check, both following birth (39.3 percent) and in Sudan including PNC visits (41.8 percent), than their rural counterparts (17.6 percent and 22.6 percent, respectively). There is a very clear correlation with both education and household wealth, with the percentage of post-natal health checks of new-borns increasing with education and wealth. For example, the percentage of post-natal health checks of new-borns is lower (15.2 percent) among those with no education than those with higher education (63.9 percent). Likewise, the percentage of post-natal health checks of new-borns is 16.6 percent among those belonging to the poorest quintile compared to 61.5 percent among those who live in the richest quintile. Generally, health checks occur following birth whether in health facility or home deliveries (77.8 percent public, 78.6 percent private). Looking only at those new-borns that did not receive a PNC visit, an expected pattern is seen. However, it is worth noting that new-borns to young women, age less than 20 years, have the highest rate of no PNC visits among age groups of women (88.7 percent). Table RH.13: Post-natal health checks for new-borns Percentage of women age 15-49 years with a live birth in the last two years whose last live birth received health checks while in facility or at home following birth, percent distribution whose last live birth received post-natal care (PNC) visits from any health provider after birth, by timing of visit, and percentage who received post-natal health checks, Sudan MICS, 2014 Background characteristics Health check followin g birth while in facility or at home [a] PNC visit for newborns [b] Post- natal health check for the newborn [1], [c] Number of last live births in the last two years Same day 1 day followin g birth 2 days following birth 3-6 days following birth After the first week following birth No post- natal care visit Missing/ DK Sudan 23.4 2.6 2.9 2.7 3.6 2.7 85.2 0.2 27.7 5,622 State Northern 47.5 1.8 0.0 2.1 3.1 5.0 88.0 0.0 48.2 92 River Nile 43.0 5.8 1.2 1.1 2.3 5.5 84.0 0.0 45.7 151 Red Sea 30.8 3.2 0.3 0.0 1.6 3.6 91.2 0.0 32.4 92 Kassala 23.4 3.5 1.3 2.5 2.7 .6 89.2 0.3 27.2 199 Gadarif 17.2 1.7 2.4 2.7 2.3 3.2 86.9 0.8 20.8 307 Khartoum 55.0 3.1 0.8 3.2 5.5 3.2 84.2 0.0 57.4 684 Gezira 27.3 .7 1.9 2.5 5.6 2.0 87.0 0.3 28.5 852 White Nile 31.3 2.3 0.0 4.1 2.8 3.2 87.4 0.2 32.7 273 Sinnar 21.7 0.7 2.3 3.4 5.0 3.7 84.7 0.2 24.5 226 Blue Nile 11.5 0.7 4.5 2.1 0.4 1.2 91.1 0.0 15.8 287 North Kordofan 21.0 4.7 6.7 4.3 4.4 4.5 74.9 0.4 31.3 352 South Kordofan 13.4 2.4 2.4 2.8 4.4 3.0 84.6 0.4 16.2 194 West Kordofan 6.9 3.6 2.5 1.4 5.0 3.0 83.6 0.9 12.4 341 159 Background characteristics Health check followin g birth while in facility or at home [a] PNC visit for newborns [b] Post- natal health check for the newborn [1], [c] Number of last live births in the last two years Same day 1 day followin g birth 2 days following birth 3-6 days following birth After the first week following birth No post- natal care visit Missing/ DK North Darfur 10.0 2.4 3.7 3.3 1.3 .9 88.4 0.0 15.8 525 West Darfur 12.4 7.4 10.7 2.1 2.8 1.7 75.1 0.3 27.1 179 South Darfur 12.1 3.8 4.7 2.7 2.2 2.6 84.0 0.0 19.0 556 Central Darfur 5.3 2.1 4.8 3.5 3.1 1.9 84.6 0.0 12.2 99 East Darfur 14.1 1.7 3.5 0.2 3.1 5.3 86.2 0.0 17.6 211 Area Urban 39.3 2.4 2.0 3.7 5.0 3.1 83.6 0.2 41.8 1,488 Rural 17.6 2.7 3.3 2.3 3.1 2.6 85.8 0.2 22.6 4,134 Mother's age at birth Less than 20 22.3 1.2 3.5 1.4 2.7 2.0 88.7 0.5 26.0 640 20-34 23.0 3.2 2.9 2.7 3.9 2.4 84.7 0.2 27.8 4,001 35-49 25.4 1.3 2.9 3.2 2.6 4.7 85.0 0.2 28.5 980 Missing * * * * * * * * * 1 Place of delivery Home 2.5 2.7 3.6 3.3 3.9 2.3 84.2 0.1 8.4 4,006 Health facility 77.8 2.7 1.5 1.2 2.8 3.9 87.4 0.6 78.2 1,559 Public 77.7 2.7 1.5 1.0 2.8 3.8 87.5 0.6 78.2 1,468 Private 78.6 2.9 .5 3.9 2.6 5.6 84.6 0.0 78.6 91 Other/DK/ Missing 0.0 0.0 0.0 0.0 0.0 0.0 100.0 0.0 0.0 57 Mother's education None 10.1 2.0 3.8 2.0 2.4 1.6 88.2 0.0 15.2 2,247 Primary 21.1 3.3 2.7 3.1 4.4 3.1 83.1 0.4 26.1 2,022 Secondary 42.7 2.5 2.7 3.1 4.8 4.1 82.7 0.1 45.3 942 Higher 62.8 2.8 .6 3.4 3.2 4.1 85.3 0.6 63.9 410 Wealth index quintile Poorest 8.3 3.5 5.8 2.6 1.8 2.4 84.0 0.0 16.6 1,251 Second 13.8 2.7 2.9 2.1 2.7 2.8 86.4 0.5 18.7 1,232 Middle 16.7 2.0 2.2 2.9 4.3 1.6 87.0 0.2 19.9 1,192 Fourth 30.3 1.7 1.7 2.7 5.8 2.4 85.7 0.1 32.6 1,096 Richest 59.8 3.4 1.6 3.5 3.6 5.2 82.3 0.4 61.5 851 [*] Based on less than 25 unweighted cases and has been suppressed. In Table RH.14, the percentage of new-borns who received the first PNC visit within one week of birth is shown by location and type of provider of service. As defined above, a visit does not include a check in the facility or at home following birth. Survey results indicated that one in ten (10.0 percent) of the first PNC visits for new-borns occur in a public facility. There exists no wide variations regarding this proportion across the different 160 background characteristics such as education and wealth of the household. However, there are large differences according to background characteristics when looking at the proportions of new-borns taking place at home or in private facilities. Note that there was minimal or almost no new-borns delivered at home that attended a private facility for PNC visit, whereas 55.8 percent of the new-borns delivered in a private facility also attended a private facility for the PNC visit. Also, it is quite clear that public facility visits are predominantly among women in the wealthiest households (20.1 percent) as well as with mothers with high education (25.5 percent). Again, in Sudan, around four in five (84.1 percent) of the first PNC visits for new-borns are provided by a Doctor, nurse or midwife and certified midwife combined. Urban-rural distribution shows that 93.7 percent and 80.1 percent of the first visits among new-borns are attended by a doctor, nurse, or mid-wife, in urban and rural areas respectively. It is interesting to observe that attendance by a traditional birth attendant (TBA) is more prevalent in Central Darfur (48.2 percent), South Darfur (42.5 percent), East Darfur (29.5 percent), Kassala (29.4 percent), and West Darfur state (26.8 percent) than in other states. The less educated or not educated a woman is, the more likely she would have delivered at home. For instance, the percentage of women who delivered at home was 30.2 percent in the case of women with no education compared to 7.1 percent among women with primary education and 2.0 percent among women with secondary level of education. The percentage of women who delivered at home was 32.7 percent among women belonging to the poorest households as compared to 0.5 percent among those living in the richest households. Table RH.14: Post-natal care visits for newborns within one week of birth Percent distribution of women age 15-49 years with a live birth in the last two years whose last live birth received a post-natal care (PNC) visit within one week of birth, by location and provider of the first PNC visit, Sudan MICS, 2014 Background characteristics Location of first PNC visit for newborns Provider of first PNC visit for newborns Number of last live births in the last two years with a PNC visit within the first week of life Home Public sector Private sector Missing Doctor/ nurse/ mid-wife /certified midwife Health visitor Medical assistant Comm- unity health worker Traditional birth attendant Sudan 88.9 10.0 0.8 0.3 84.1 1.4 .4 .4 13.7 665 State Northern * * * * * * * * * 6 River Nile (52.9) (47.1) (0.0) (0.0) (100.0) (97.1) (2.9) (0.0) (0.0) 16 Red Sea * * * * * * * * * 5 Kassala (78.6) (21.4) (0.0) (0.0) (100.0) (63.9) (4.0) (2.6) (0.0) 20 Gadarif (95.0) (5.0) (0.0) (0.0) (96.4) (0.0) (0.0) (0.0) (3.6) 28 Khartoum (79.0) (17.2) (3.7) (0.0) (100.0) (0.0) (0.0) (0.0) (0.0) 86 Gezira (95.2) (4.8) (0.0) (0.0) (90.9) (4.0) (0.0) (2.0) (3.1) 91 White Nile (90.8) (7.2) (2.0) (0.0) (93.9) (0.0) (0.0) (0.0) (6.1) 25 Sinnar (92.3) (6.6) (0.0) (1.1) (90.1) (1.1) (0.0) (0.0) (8.8) 26 Blue Nile (92.4) (7.6) (0.0) (0.0) (100.0) (89.2) (0.0) (0.0) (0.0) 22 161 Background characteristics Location of first PNC visit for newborns Provider of first PNC visit for newborns Number of last live births in the last two years with a PNC visit within the first week of life Home Public sector Private sector Missing Doctor/ nurse/ mid-wife /certified midwife Health visitor Medical assistant Comm- unity health worker Traditional birth attendant North Kordofan 96.0 2.2 1.8 0.0 94.7 0.0 1.2 0.0 4.1 71 South Kordofan 79.0 19.4 1.6 0.0 100.0 93.3 0.0 0.0 0.0 23 West Kordofan (88.0) (12.0) (0.0) (0.0) (81.2) (4.3) (0.0) (2.6) (11.9) 43 North Darfur (97.5) (2.5) (0.0) (0.0) (76.6) (2.8) (1.8) (0.0) (18.8) 56 West Darfur 91.0 9.0 0.0 0.0 72.2 1.1 0.0 0.0 26.8 41 South Darfur 88.0 9.9 0.0 2.1 57.5 0.0 0.0 0.0 42.5 74 Central Darfur (95.7) (4.3) (0.0) (0.0) (100.0) (51.8) (0.0) (0.0) (0.0) 13 East Darfur (94.1) (5.9) (0.0) (0.0) (100.0) (70.5) (0.0) (0.0) (0.0) 18 Area Urban 84.1 13.9 1.8 0.2 93.7 1.3 0.0 0.0 5.0 195 Rural 90.9 8.3 0.4 0.3 80.1 1.5 .5 0.6 17.3 469 Mother's age at birth Less than 20 88.3 11.7 0.0 0.0 85.5 0.0 0.0 0.0 14.5 56 20-34 89.0 9.9 0.8 0.4 83.1 1.6 0.3 0.6 14.4 509 35-49 89.0 9.6 1.4 0.0 88.3 1.4 0.9 0.0 9.4 99 Place of delivery Home 98.5 1.1 0.0 0.4 81.2 1.3 0.3 0.2 16.9 538 Health facility 48.2 47.5 4.2 0.0 96.4 1.8 0.4 1.4 0.0 127 Public 48.5 51.1 0.3 0.0 96.5 1.6 0.4 1.5 0.0 118 Private * * * * * * * * * 9 Mother's education None 92.4 7.6 0.0 0.0 68.6 0.5 0.2 0.5 30.2 229 Primary 91.8 6.1 1.5 0.6 91.2 1.4 0.3 0.0 7.1 271 Secondary 81.0 17.6 1.1 0.2 92.0 3.7 0.8 1.5 2.0 123 Higher (74.5) (25.5) (0.0) (0.0) (100.0) (0.0) (0.0) (0.0) (0.0) 41 Wealth index quintile Poorest 92.7 6.4 0.0 0.9 66.2 0.0 0.8 0.3 32.7 171 Second 93.6 5.3 1.0 0.0 78.3 1.2 0.8 0.4 19.3 127 Middle 90.6 9.1 0.3 0.0 91.5 2.3 0.0 0.0 6.2 134 Fourth 87.2 12.2 0.4 0.2 96.8 0.6 0.0 1.4 1.2 129 Richest 76.8 20.1 3.1 0.0 95.5 4.0 0.0 0.0 0.5 103 ( ) Figures that are based on 25-49 unweighted cases [*] Based on less than 25 unweighted cases and has been suppressed. 162 Tables RH.15 and RH.16 present information collected on post-natal health checks and visits of the mother and are identical to Tables RH.13 and RH.14 that presented the data collected for new-born. Table RH.15 presents a pattern somewhat similar to Table RH.13, but with some important differences. Overall, 23.4 percent of mothers receive a health check following birth while in a facility or at home. With regards to PNC visits, the majority take place 3-6 days following birth or after the first week following birth (3.0 percent and 3.6 percent, respectively). As a result, a Sudan of 26.6 percent of all mothers receive a post-natal health check. This percentage varies from 10.3 percent in West Kordofan State to 56.1 percent in Khartoum State. Urban mothers are much more likely to receive a health check, both following birth (39.2 percent) and PNC visits (41.7 percent), than their rural counterparts (17.7 percent and 21.2 percent, respectively). There is again a very clear correlation to both education and household wealth, with the percentage of post-natal health checks of mothers increasing with education and wealth. Health checks following birth occur mainly in health facility deliveries (77.6 percent public, 83.9 percent private), whereas for mothers delivering at home the figure is very low (2.5 percent). The main difference between the table for new-borns and the table for mothers is that the percentage with health checks, both following the birth and through a visit, is lower for mothers than for new-borns. As was the case for the new-born, the age group of mothers age less than 20, has a very low percentage receiving a health check through a timely visit. 163 Table RH.15: Post-natal health checks for mothers Percentage of women age 15-49 years with a live birth in the last two years who received health checks while in facility or at home following birth, percent distribution who received post-natal care (PNC) visits from any health provider after birth at the time of last birth, by timing of visit, and percentage who received post-natal health checks, Sudan MICS, 2014 Background characteristics Health check after birth while in facility or at home [a] PNC visit for mothers [b] Post- natal health check for the mother [1], [c] Number of women who gave birth in the two years preceding the survey Same day 1 day after birth 2 days after birth 3-6 days after birth After the first week after birth No post- natal care visit Missing/ DK Sudan 23.4 2.1 2.1 2.0 3.0 3.1 87.3 0.3 26.6 5,622 State Northern 53.8 1.0 0.0 1.0 3.8 11.4 82.2 0.6 54.4 92 River Nile 42.9 3.2 0.4 0.3 2.5 6.7 86.8 0.0 43.3 151 Red Sea 34.6 2.3 0.8 0.0 1.2 1.8 94.0 0.0 35.3 92 Kassala 23.2 1.3 1.0 1.6 2.2 1.0 92.2 0.8 24.9 199 Gadarif 16.9 1.0 2.2 2.3 2.6 3.6 88.4 0.0 19.3 307 Khartoum 54.3 2.7 0.7 1.4 2.6 5.4 86.5 0.8 56.1 684 Gezira 27.2 0.0 0.5 2.1 4.4 1.6 91.2 0.2 27.6 852 White Nile 31.5 1.0 1.1 2.5 5.3 5.5 84.6 0.0 32.7 273 Sinnar 22.0 .6 2.3 3.3 4.3 4.1 85.2 0.2 24.4 226 Blue Nile 11.7 2.2 3.8 1.6 0.9 1.2 90.3 0.0 16.8 287 North Kordofan 20.3 2.4 4.5 4.1 6.7 6.4 75.1 0.7 25.9 352 South Kordofan 13.4 1.4 0.9 2.7 2.6 2.5 89.8 0.2 15.3 194 West Kordofan 6.9 2.5 1.5 1.5 2.8 1.3 90.4 0.0 10.3 341 North Darfur 10.5 3.8 0.6 3.3 0.9 1.4 89.7 0.2 13.8 525 West Darfur 11.6 9.2 11.3 1.0 3.5 0.6 74.3 0.0 28.9 179 South Darfur 12.1 3.2 4.4 1.8 1.9 2.4 86.0 0.2 18.6 556 Central Darfur 6.0 2.1 2.7 2.5 3.4 0.6 88.7 0.0 10.8 99 East Darfur 13.2 .9 2.6 0.1 2.8 2.9 90.7 0.0 15.5 211 Area Urban 39.2 2.5 1.4 2.8 3.5 4.3 85.1 0.3 41.7 1,488 Rural 17.7 2.0 2.3 1.8 2.9 2.7 88.1 0.3 21.2 4,134 Mother's age at birth Less than 20 22.7 .6 2.9 0.9 3.0 2.6 89.9 0.1 25.6 640 20-34 23.1 2.3 2.0 2.2 3.1 2.6 87.5 0.3 26.5 4,001 35-49 25.1 2.3 1.8 2.3 2.7 5.4 85.2 0.3 27.7 980 Missing * * * * * * * * * 1 Place of delivery Home 2.5 2.1 2.6 2.5 3.0 2.0 87.4 0.3 6.9 4,006 Health facility 78.0 2.2 0.7 0.9 3.2 5.9 86.9 0.2 78.1 1,559 Public 77.6 2.0 0.7 0.9 3.4 5.8 86.9 0.2 77.7 1,468 Private 83.9 5.2 0.0 0.4 0.0 7.5 86.9 0.0 83.9 91 Other/Missing 0.0 1.0 0.0 0.0 0.9 1.1 96.9 0.0 1.0 57 Type of delivery Vaginal birth 71.2 2.2 0.9 1.2 1.9 2.4 91.3 0.1 71.4 1,047 C-section 91.7 2.3 0.3 0.4 5.8 13.0 77.8 0.4 91.7 511 Missing 2.7 0.0 0.0 0.0 1.1 1.3 97.6 0.0 2.7 49 Mother's education None 10.2 2.1 3.0 1.7 1.8 2.0 89.2 0.1 14.7 2,247 164 Background characteristics Health check after birth while in facility or at home [a] PNC visit for mothers [b] Post- natal health check for the mother [1], [c] Number of women who gave birth in the two years preceding the survey Same day 1 day after birth 2 days after birth 3-6 days after birth After the first week after birth No post- natal care visit Missing/ DK Primary 21.2 2.1 1.9 2.5 3.9 2.8 86.4 0.5 24.1 2,022 Secondary 42.5 2.5 1.3 1.9 3.9 5.1 85.1 0.2 44.5 942 Higher 62.9 1.9 0.1 2.0 3.6 6.0 86.4 0.1 63.3 410 Wealth index quintile Poorest 8.3 3.0 3.4 2.1 1.9 2.1 87.4 0.1 14.0 1,251 Second 13.7 2.4 3.2 1.8 1.9 2.4 88.1 0.2 18.4 1,232 Middle 17.3 1.1 1.4 2.7 4.2 2.3 87.9 0.4 19.0 1,192 Fourth 29.9 1.5 1.2 1.8 3.8 4.2 87.2 0.3 31.7 1,096 Richest 59.7 2.9 0.4 1.6 3.9 5.3 85.7 0.2 61.1 851 [*] Based on less than 25 unweighted cases and has been suppressed. Table RH.16 matches Table RH.14, but now deals with PNC visits for mothers by location and type of provider. As defined above, a visit does not include a check in the facility or at home following birth. Overall, 11.7 percent of the first PNC visits occur in a public facility. This proportion varies across background characteristics. The largest variation is found according to household wealth; where as high as 94.5 percent of the women belonging to the poorest households have their first PNC visit in a public facility compared to 67.4 percent of the women of the richest households who have their first PNC visit in a public facility. With regards to provider of the first PNC visit for mothers, the variations across background characteristics are not large, although there is a higher prevalence among urban women whose first PNC visit provider is Doctor/ nurse/ midwife /certified midwife at 90.7 percent against their rural counterparts at 78.9 percent. One in six (17.3 percent) of rural women are receiving their PNC by traditional birth attendants. It is expected, but nevertheless interesting, to note that almost 86.4 percent of the women giving birth by C-section are seen by a doctor/nurse/midwife at their first PNC visit. 165 Table RH.16: Post-natal care visits for mothers within one week of birth Percent distribution of women age 15-49 years with a live birth in the last two years who received a post-natal care (PNC) visit within one week of birth, by location and provider of the first PNC visit, Sudan MICS, 2014 Background characteristics Location of first PNC visit Provider of first PNC visit for newborns Number of women who gave birth in the two years preceding survey and received a PNC visit within one week of delivery Home Public Sector Private Sector Missing/ DK Doctor/ nurse/ midwife /certified midwife Health visitor Medical assistant Community health worker TBA Sudan 87.7 11.7 0.5 0.2 82.3 2.3 0.7 0.7 13.9 523 State Northern * * * * * * * * * 5 River Nile * * * * * * * * * 10 Red Sea * * * * * * * * * 4 Kassala * * * * * * * * * 12 Gadarif (87.1) (12.9) (0.0) (0.0) (100.0) (0.0) (0.0) (0.0) (0.0) 25 Khartoum * * * * * * * * * 50 Gezira * * * * * * * * * 59 White Nile (76.5) (23.5) (0.0) (0.0) (91.1) (3.2) (0.0) (0.0) (5.6) 27 Sinnar (95.0) (5.0) (0.0) (0.0) (100.0) (94.0) (0.0) (0.0) (0.0) 24 Blue Nile (94.6) (5.4) (0.0) (0.0) (100.0) (92.6) (0.0) (3.7) (0.0) 24 North Kordofan 96.3 3.7 0.0 0.0 95.9 0.0 1.4 0.0 2.8 63 South Kordofan (91.0) (9.0) (0.0) (0.0) (100.0) (73.6) (3.3) (0.0) (2.6) 15 West Kordofan (78.1) (21.9) (0.0) (0.0) (85.6) (3.3) (0.0) (2.0) (9.2) 28 North Darfur (90.0) (7.6) (2.4) (0.0) (67.2) (5.4) (2.3) (2.4) (22.7) 45 West Darfur 94.1 .9 1.0 0.0 69.1 1.0 0.0 0.0 29.9 45 South Darfur 86.9 11.6 0.0 1.5 56.5 2.5 0.0 0.0 41.0 63 Central Darfur (84.4) (15.6) (0.0) (0.0) (100.0) (70.0) (0.0) (2.5) (0.0) 11 East Darfur * * * * * * * * * 14 Area Urban 81.8 16.9 1.2 0.0 90.7 2.7 0.0 0.9 5.7 153 Rural 90.1 9.5 0.1 0.3 78.9 2.2 1.0 0.6 17.3 370 Mother's age at birth Less than 20 97.1 2.9 0.0 0.0 80.3 1.0 0.0 0.0 18.7 47 20-34 89.0 10.1 0.6 0.3 80.9 2.9 0.6 1.0 14.6 386 35-49 76.9 23.1 0.0 0.0 89.8 0.5 1.3 0.0 8.4 89 Place of delivery Home 98.8 1.2 0.0 0.0 79.5 2.1 0.7 0.2 17.5 413 Health facility 45.6 51.3 2.2 0.9 93.3 3.3 0.7 2.6 0.0 109 Public 44.6 52.6 1.9 0.9 93.0 3.5 0.7 2.8 0.0 104 Private * * * * * * * * * 5 Other/Missing * * * * * * * * * 1 Type of delivery Vaginal birth 62.0 35.8 0.7 1.5 98.1 0.7 1.2 0.0 0.0 65 C-section (22.5) (73.0) (4.4) (0.0) (86.4) (7.1) (0.0) (6.4) (0.0) 45 166 Background characteristics Location of first PNC visit Provider of first PNC visit for newborns Number of women who gave birth in the two years preceding survey and received a PNC visit within one week of delivery Home Public Sector Private Sector Missing/ DK Doctor/ nurse/ midwife /certified midwife Health visitor Medical assistant Community health worker TBA Missing * * * * * * * * * 1 Mother's education None 93.3 6.7 0.0 0.0 67.3 1.3 0.9 0.3 30.3 194 Primary 88.3 10.7 0.5 0.5 89.3 3.1 0.4 0.7 6.5 208 Secondary 78.5 21.0 0.5 0.0 92.7 3.8 1.1 2.0 0.4 90 Higher (75.1) (22.0) (2.9) (0.0) (100.0) (0.0) (0.0) (0.0) (0.0) 31 Wealth index quintile Poorest 94.5 4.7 0.0 0.7 60.7 1.2 1.0 0.4 36.6 130 Second 95.0 5.0 0.0 0.0 79.7 1.4 1.6 0.0 17.4 115 Middle 89.6 10.4 0.0 0.0 92.6 2.4 0.3 0.3 4.3 112 Fourth 83.0 15.2 1.8 0.0 95.0 1.5 0.0 3.2 0.3 91 Richest 67.4 31.5 1.1 0.0 93.3 6.7 0.0 0.0 0.0 75 ( ) Figures that are based on 25-49 unweighted cases [*] Based on less than 25 unweighted cases and has been suppressed. Table RH.17 presents the distribution of women with a live birth in the two years preceding the survey by receipt of health checks or PNC visits within 2 days of birth for the mother and the new-born, thus combining the indicators presented in Tables RH.13 and RH.15. Sudan MICS 2014 shows that for 23.7 percent of live births, both the mothers and their new-borns receive either a health check following birth or a timely PNC visit, whereas for as large as 69.4 percent of births neither receive health checks Nor timely visits. There are quite large discrepancies across the background characteristics. Births in Urban areas (37.3 percent) are twice better served with health checks or timely visits as compared to births in rural areas (18.7 percent). The figures between states vary from 8.5 percent in Central Darfur to 51.0 percent in Khartoum state. There are also very clear correlations to household wealth and the education of the woman, where increasing wealth and education tends to be associated with better coverage. As expected, the opposite is true for births without health checks or timely visits. For example, births belonging to the wealthiest households (55.0 percent) are more than four times better served with health checks or timely visits as compared to births in households in the poorest quintile (12.7 percent). The picture is less clear when it comes to patterns on health checks or timely visits for either the mother or the new-born alone, although generally a higher level of coverage for new-borns. 167 Table RH.17: Post-natal health checks for mothers and new-borns Percent distribution of women age 15-49 years with a live birth in the last two years by post-natal health checks for the mother and new-born, within two days of the most recent birth, Sudan MICS, 2014 Background characteristics Health checks or PNC visits within 2 days of birth for: Number of women age 15-49 years who gave birth in the 2 years preceding the survey Both mothers and newborns Mothers only Newborns only Neither mother nor newborn Missing Sudan 23.7 2.9 4.0 69.4 0.0 5,622 State Northern 43.8 10.6 4.3 41.3 0.0 92 River Nile 40.0 3.3 5.7 51.0 0.0 151 Red Sea 28.8 6.6 3.6 61.0 0.0 92 Kassala 21.7 3.3 5.6 69.5 0.0 199 Gadarif 18.2 1.1 2.7 78.0 0.0 307 Khartoum 51.0 5.1 6.3 37.5 0.0 684 Gezira 24.5 3.1 4.0 68.4 0.0 852 White Nile 29.9 2.7 2.8 64.6 0.0 273 Sinnar 21.9 2.2 2.4 73.3 0.2 226 Blue Nile 13.3 3.5 2.5 80.7 0.0 287 North Kordofan 22.8 3.0 8.4 65.7 0.0 352 South Kordofan 12.8 2.5 3.4 81.3 0.0 194 West Kordofan 9.3 1.0 3.0 86.6 0.0 341 North Darfur 12.6 1.2 3.2 83.0 0.0 525 West Darfur 22.7 6.2 4.4 66.7 0.0 179 South Darfur 16.6 1.9 2.4 79.1 0.0 556 Central Darfur 8.5 2.3 3.7 85.5 0.0 99 East Darfur 15.1 0.4 2.5 82.0 0.0 211 Area Urban 37.3 4.3 4.4 53.9 0.0 1,488 Rural 18.7 2.4 3.9 74.9 0.0 4,134 Mother's age at birth 22.1 3.5 3.9 70.5 0.0 640 Less than 20 23.6 2.9 4.2 69.3 0.0 4,001 20-34 24.9 2.8 3.5 68.8 0.0 980 35-49 * * * * * 1 Place of delivery Home 5.5 1.5 3.0 90.1 0.0 4,006 Health facility 71.3 6.8 6.9 15.0 0.0 1,559 Public 71.2 6.5 7.0 15.3 0.0 1,468 Private 73.2 10.7 5.4 10.7 0.0 91 Other/DK/Missing 0.0 1.0 0.0 99.0 0.0 57 Type of delivery Vaginal birth 66.0 5.4 8.7 19.8 0.0 1,047 C-section 82.0 9.6 3.0 5.2 0.1 511 Missing 2.7 0.0 0.0 97.3 0.0 49 Mother's education None 12.7 2.0 2.6 82.8 0.0 2,247 Primary 21.5 2.6 4.5 71.3 0.0 2,022 Secondary 39.7 4.8 5.5 50.0 0.0 942 Higher 57.8 5.5 6.0 30.7 0.0 410 Wealth index quintile Poorest 12.7 1.3 3.9 82.1 0.0 1,251 168 Background characteristics Health checks or PNC visits within 2 days of birth for: Number of women age 15-49 years who gave birth in the 2 years preceding the survey Both mothers and newborns Mothers only Newborns only Neither mother nor newborn Missing Second 15.6 2.7 3.1 78.5 0.0 1,232 Middle 16.6 2.4 3.3 77.7 0.0 1,192 Fourth 28.5 3.2 4.1 64.2 0.0 1,096 Richest 55.0 6.1 6.5 32.4 0.0 851 ( ) Figures that are based on 25-49 unweighted cases [*] Based on less than 25 unweighted cases and has been suppressed. 169 IX. Child Development 9.1 Early Childhood Care and Education Readiness of children for primary school can be improved through attendance to early childhood education programmes or through pre-school attendance. Early childhood education programmes include programmes for children that have organised learning components as opposed to baby-sitting and day-care which do not typically have organised education and learning. For Sudan, structural changes were introduced in the general education system in 1998 when the old system of 6+3+3 grades (adopted in the 1970s) was changed into 2+8+3 to include two years pre- school, 8 years at the basic stage and three years of secondary school. Currently Basic Education in Sudan includes pre-school education (Khalwa and kindergarten) - two consecutive years targeting children of four to five years of age at basic education level, eight consecutive years of schooling from 6 to 13 years of age, at the end of which students sit for the basic level certificate examination which qualifies them for admission to secondary school. Observing the context of Sudan and during the customization of the Child development module only the questions that will allow the production of Tables CD.1 and CD.3 were kept as part of the under- five questionnaires. Table CD.1: indicates that 22.3 percent of children aged 36-59 months are attending an organised early childhood education programme (Table CD.1). Urban-rural and state differentials are notable – the figure is as high as 44.6 percent in urban areas, compared to 13.9 percent in rural areas. Among children aged 36-59 months, attendance to early childhood education programmes is more prevalent in Khartoum state (56.2 percent), and lowest in the West Kordofan (4.3 percent). No gender differential exists, but differentials by socioeconomic status seem to be significant; 59.4 percent of children living in the richest households while the figure drops to 6.9 percent among children in the poorest households. The data indicates that there is notable variation between children attending early childhood education programmes at ages 36-47 months and 48-59 months as 13.5 percent and 33.5 percent respectively. 170 Table CD.1: Early childhood education Percentage of children age 36-59 months who are attending an organized early childhood education programme, Sudan MICS, 2014 Background characteristics Percentage of children age 36-59 months attending early childhood education [1] Number of children age 36-59 months Sudan 22.3 5,827 Sex Male 21.9 2,957 Female 22.7 2,869 State Northern 47.3 94 River Nile 36.1 169 Red Sea 37.6 98 Kassala 12.2 200 Gadarif 16.2 295 Khartoum 56.2 721 Gezira 21.0 892 White Nile 26.2 275 Sinnar 24.8 223 Blue Nile 13.3 268 North Kordofan 9.4 407 South Kordofan 21.9 227 West Kordofan 4.3 394 North Darfur 13.7 529 West Darfur 13.5 211 South Darfur 17.3 503 Central Darfur 9.1 113 East Darfur 11.8 207 Area Urban 44.6 1,594 Rural 13.9 4,233 Age of child 36-47 months 13.5 3,268 48-59 months 33.5 2,559 Mother's education None 8.8 2,636 Primary 22.7 1,965 Secondary 46.0 844 Higher 62.0 375 Missing/DK * 7 Wealth index quintile Poorest 6.9 1,393 Second 9.2 1,232 Middle 17.2 1,182 Fourth 30.0 1,076 Richest 59.4 943 [1] MICS indicator 6.1 - Attendance to early childhood education [*] Based on less than 25 unweighted cases and has been suppressed. 171 9.2 Quality of Care Exposure to books in early years not only provides the child with greater understanding of the nature of print, but may also give the child opportunities to see others reading, such as older siblings doing school work. Presence of books is important for later school performance. The mothers/caretakers of all children under 5 were asked about number of children’s books or picture books they have for the child, and the types of playthings that are available at home. In Sudan, only 1.3 percent of children age 0-59 months live in households where at least 3 children’s books are present for the child (Table CD.3). Overall, there exists very small number of households with 10 or more books children’s books. While no gender differentials are observed, a higher percentage of urban children appear to have access to children’s books than those children living in rural households. The proportion of under-5 children who have 3 or more children’s books is 4.4 percent in urban areas, compared to .4 percent in rural areas. Table CD.3: Learning materials Percentage of children under age 5 by numbers of children's books present in the household, and by playthings that child plays with, Sudan MICS, 2014 Background characteristics Percentage of children living in households that have for the child: Percentage of children who play with: Number of children under age 5 3 or more children's books [1] 10 or more children's books Home- made toys Toys from a shop/ manufactured toys Household objects/ objects found outside Two or more types of playthings [2] Sudan 1.5 0.0 41.1 39.8 54.8 45.5 14,081 Sex Male 1.6 0.0 42.1 40.9 55.0 46.2 7,157 Female 1.4 0.0 40.1 38.8 54.7 44.8 6,924 State Northern 0.8 0.2 47.6 78.0 75.3 73.1 236 River Nile 2.1 0.2 32.2 57.7 51.3 44.6 393 Red Sea 2.0 0.0 27.0 34.6 40.3 30.6 244 Kassala 0.5 0.0 15.6 22.3 38.6 18.6 498 Gadarif 0.5 0.0 37.3 43.1 69.0 49.4 765 Khartoum 7.2 0.0 30.0 72.2 42.5 45.6 1,736 Gezira 1.0 0.0 53.5 39.6 63.8 56.1 2,149 White Nile 0.9 0.0 39.8 46.3 62.7 51.8 711 Sinnar 1.3 0.1 43.5 52.2 51.6 47.7 555 Blue Nile 0.3 0.0 43.8 31.7 77.2 54.3 691 North Kordofan 0.3 0.0 46.9 34.5 47.2 44.3 907 South Kordofan 0.1 0.0 58.5 32.9 60.8 55.6 529 West Kordofan 0.6 0.1 38.4 39.5 50.6 39.4 893 North Darfur 0.4 0.0 21.8 17.7 45.2 20.7 1,211 West Darfur 0.5 0.0 53.4 26.6 46.0 44.2 487 South Darfur 0.6 0.0 59.2 31.2 60.0 57.1 1,326 172 Background characteristics Percentage of children living in households that have for the child: Percentage of children who play with: Number of children under age 5 3 or more children's books [1] 10 or more children's books Home- made toys Toys from a shop/ manufactured toys Household objects/ objects found outside Two or more types of playthings [2] Central Darfur 0.2 0.0 18.8 10.5 40.3 15.9 254 East Darfur 0.5 0.0 37.8 22.2 55.4 40.9 495 Area Urban 4.4 0.1 37.7 58.9 50.7 48.6 3,862 Rural 0.4 0.0 42.4 32.7 56.3 44.4 10,219 Age of child 36-47 months 0.4 0.0 27.0 31.3 35.7 30.0 5,636 48-59 months 2.2 0.0 50.5 45.6 67.5 55.9 8,445 Mother's education None 0.3 0.0 41.5 24.5 56.3 41.3 5,994 Primary 0.7 0.0 40.5 40.2 53.1 44.8 4,936 Secondary 3.3 0.0 41.9 64.4 55.5 55.0 2,152 Higher 8.6 0.2 40.1 78.1 53.2 55.2 982 Missing/DK * * * * * * 17 Wealth index quintile Poorest 0.2 0.0 38.1 20.1 52.5 36.2 3,188 Second 0.1 0.0 40.5 26.7 52.3 39.3 3,015 Middle 0.5 0.0 45.9 36.8 60.0 49.5 2,956 Fourth 1.1 0.0 42.3 50.0 57.0 51.1 2,684 Richest 7.0 0.1 38.5 77.6 52.0 55.3 2,238 [1] MICS indicator 6.5 - Availability of children’s books [2] MICS indicator 6.6 - Availability of playthings Table CD.3 also shows that 45.5 percent of children age 0-59 months had 2 or more types of playthings to play with in their homes. The types of playthings included in the questionnaires were homemade toys (such as dolls and cars, or other toys made at home), toys that came from a store, and household objects (such as pots and bowls) or objects and materials found outside the home (such as sticks, rocks, animal shells, or leaves). It is interesting to note that less than four out of ten (39.8 percent) of children play with toys that come from a store as compared to 54.8 percent of the toys coming from the homes. The proportion of children who have 2 or more types of playthings to play with is 46.2 percent among male children and 44.8 percent among female children. Urban-rural differentials are observed in this respect; significant differences are observed in terms of mother’s education – 55.2 percent of children whose mothers with secondary or higher education have 2 or more types of playthings as compared 41.3 percent for children whose mothers have no education. Differentials are observed by socioeconomic status of the households, in the range of 36.2 percent among the poorest households to 55.3 percent among the richest households. 173 X. Literacy and Education 10.1 Literacy among Young Women The Youth Literacy Rate reflects the outcomes of primary education over the previous 10 years or so. As a measure of the effectiveness of the primary education system, it is often seen as a proxy measure of social progress and economic achievement. In Sudan Multiple Indicator Cluster Survey (MICS 2014), since only a women’s questionnaire was administered, the results are based only on females age 15- 24. Literacy is assessed on the ability of the respondent to read a short simple statement or based on school attendance. The percent literate is presented in Table ED.1. This table indicates that 59.8 percent of young women in Sudan are literate and that literacy status varies greatly by area 79.8 percent in urban areas and 50.0 percent in rural areas). Of women who stated that primary school was their highest level of education, just 43.7 percent were actually able to read the statement shown to them. The proportion of women who were literate was higher at 63.4 percent among women age 15-19 years than that among women age 20-24 years (55.6 percent).The proportion of literate women (aged 15-24 years) also varied by their household wealth. The proportion of literate women was much higher among those belonging to households in the richest quintile (92.2 percent) than those belonging to households in the poorest quintile (31.2 percent). Table ED.1: Literacy among young women Percentage of women age 15-24 years who are literate, Sudan MICS, 2014 Background characteristics Percentage literate [1] Percentage not known Number of women age 15- 24 years Sudan 59.8 1.4 6,871 State Northern 91.5 0.2 146 River Nile 79.8 2.5 253 Red Sea 71.9 3.4 150 Kassala 48.4 0.7 272 Gadarif 42.8 0.4 327 Khartoum 82.6 1.8 1,053 Gezira 66.4 0.8 1,231 White Nile 67.5 2.5 312 Sinnar 54.0 2.3 257 Blue Nile 36.1 0.6 297 North Kordofan 58.8 1.5 471 South Kordofan 49.2 1.3 197 West Kordofan 32.9 0.6 341 North Darfur 56.0 0.9 479 West Darfur 50.1 1.8 214 South Darfur 49.3 1.1 567 Central Darfur 27.4 2.7 104 East Darfur 40.0 4.0 201 Area Urban 79.8 1.7 2,262 Rural 50.0 1.2 4,609 174 Background characteristics Percentage literate [1] Percentage not known Number of women age 15- 24 years Education None 4.2 0.7 1,321 Primary 43.7 3.2 2,662 Secondary 100.0 0.0 2,180 Higher 100.0 0.0 708 Age 15-19 63.4 1.7 3,709 20-24 55.6 1.0 3,162 Wealth index quintile Poorest 31.2 1.0 1,165 Second 38.1 1.2 1,338 Middle 55.6 1.6 1,385 Fourth 72.9 1.8 1,483 Richest 92.2 1.2 1,500 [1] MICS indicator 7.1; MDG indicator 2.3 - Literacy rate among young women 10.2 School Readiness Attendance to pre-school education is important for the readiness of children to school. Table ED.2 shows the proportion of children in the first grade of primary school (regardless of age) who attended pre-school the previous year40. Overall, 69.7 percent of children who are currently attending the first grade of primary school were attending pre-school the previous year. The proportion among males is lower (66.0 percent) than females (73.4 percent), while a higher proportion of children in first grade in urban areas (81.0 percent) had attended pre-school the previous year compared to children living in rural areas (64.7 percent). State differentials are also very significant; first graders in Khartoum state have attended pre-school nearly 3 times as likely (87.0 percent) as their counterparts in Central Darfur State (30.5 percent). Socioeconomic status appears to have a positive correlation with school readiness – while the indicator is only 50.6 percent among the poorest households, it increases to 86.9 percent among those children living in the richest households. 40 The computation of the indicator does not exclude repeaters, and therefore is inclusive of both children who are attending primary school for the first time, as well as those who were in the first grade of primary school the previous school year and are repeating. Children repeating may have attended pre-school prior to the school year during which they attended the first grade of primary school for the first time; these children are not captured in the numerator of the indicator 175 Table ED.2: School readiness Percentage of children attending first grade of primary school who attended pre-school the previous year, Sudan MICS, 2014 Background characteristics Percentage of children attending first grade who attended preschool in previous year [1] Number of children attending first grade of primary school Sudan 69.7 2,580 Sex Male 66.0 1,299 Female 73.4 1,281 State Northern 79.9 56 River Nile 86.6 94 Red Sea 66.9 57 Kassala 65.7 77 Gadarif 72.3 145 Khartoum 87.0 329 Gezira 77.0 486 White Nile 82.9 140 Sinnar 72.1 90 Blue Nile 77.0 107 North Kordofan 68.2 172 South Kordofan 64.7 84 West Kordofan 51.5 116 North Darfur 61.8 221 West Darfur 59.5 75 South Darfur 39.3 211 Central Darfur 30.5 46 East Darfur 60.2 75 Area Urban 81.0 790 Rural 64.7 1,790 Wealth index quintile Poorest 50.6 471 Second 57.7 472 Middle 69.5 573 Fourth 80.6 569 Richest 86.9 495 [1] MICS indicator 7.2 - School readiness 176 10.3 Primary and Secondary School Participation Universal access to basic education and the completion of primary education by the world’s children is one of the Millennium Development Goals. Education is a vital prerequisite for combating poverty, empowering women, protecting children from hazardous and exploitative labour and sexual exploitation, promoting human rights and democracy, protecting the environment, and influencing population growth. In Sudan, children enter primary school at age 6 and enter secondary school at age 14. There are 8 grades in primary school and 3 grades in secondary school. In primary school, grades are referred to as year 1 basic to year 8 basic. For secondary school, grades are referred to as grade 1 to grade 3. The school year typically runs from June of one year to March of the following year. Of children who are of primary school entry age in Sudan, 36.8 percent are attending the first grade of primary school (Table ED.3). Sex differentials do not exist; however, significant differentials are present by state and urban-rural areas. In Northern state, for instance, percentage of children entering grade one is 73.6 percent, while those entering at grade one in Western Kordofan state is 13.4 percent. Those entering grade one in urban urban areas (56.6 percent) is nearly twice as those in rural areas (29.5 percent). A positive correlation with socioeconomic status is observed for children age 6 who were attending the first grade. In richest households, the proportion is around 77.6 percent, while it is 14.5 percent among children living in the poorest households. Table ED.3: Primary school entry Percentage of children of primary school entry age entering grade 1 (net intake rate), Sudan MICS, 2014 Background characteristics Percentage of children of primary school entry age entering grade 1 [1] Number of children of primary school entry age Sudan 36.8 3,142 Sex Male 36.1 1,560 Female 37.5 1,582 State Northern 73.6 54 River Nile 66.5 88 Red Sea 44.1 78 Kassala 27.5 141 Gadarif 34.4 180 Khartoum 68.0 372 Gezira 46.0 456 White Nile 39.7 163 Sinnar 31.9 129 Blue Nile 28.4 141 North Kordofan 36.6 225 South Kordofan 28.5 111 West Kordofan 13.4 180 North Darfur 19.7 263 West Darfur 23.0 122 South Darfur 22.6 272 177 Background characteristics Percentage of children of primary school entry age entering grade 1 [1] Number of children of primary school entry age Central Darfur 22.9 58 East Darfur 19.6 108 Area Urban 56.6 843 Rural 29.5 2,299 Wealth index quintile Poorest 14.5 727 Second 20.3 693 Middle 33.2 704 Fourth 56.9 548 Richest 77.6 469 [1] MICS indicator 7.3 - Net intake rate in primary education Table ED.4 provides the percentage of children of primary school age (6 to 13 years) who are attending primary or secondary school41 and those who are out of school. Over three-quarters (76.4 percent) of children of primary school age are attending school. A large proportion (21.6 percent) of the children are out of school primarily due to a very low attendance rate (45.1 percent) for children age 6, who appear to be starting late in school, as seen by a relatively high percentage attending pre-school. In urban areas 91.4 percent of children attend school while 70.6 percent of them attend in rural areas. There were also considerable variations in the net primary school attendance ratios among states. The net primary school attendance ratio ranged from 54.1 percent in Western Kordofan State to 95.5 percent in Northern State . The net attendance varied among sex in states (see fig. ED.1a) The household wealth also appears to have an influence on the net primary school attendance ratio. The net primary school attendance ratio was only 57.4 percent among children belonging to households in the poorest quintile compared to 96.9 percent among children from households in the richest quintile. 41 Ratios presented in this table are "adjusted" since they include not only primary school attendance, but also secondary school attendance in the numerator. 178 Figure ED.1a: Children of primary school age attending primary (adjusted attendance ratio) for boys and girls by state and by urban/rural area, Sudan MICS, 2014 77 96 90 85 69 76 96 85 80 83 79 77 69 56 76 64 65 58 66 92 72 76 95 92 84 68 69 95 83 79 80 77 71 70 52 77 57 67 51 58 91 69 0 20 40 60 80 100 120 Male Female 179 Table ED.4: Primary school attendance and out of school children Percentage of children of primary school age attending primary or secondary school (adjusted net attendance ratio), percentage attending preschool, and percentage out of school, Sudan MICS, 2014 Background characteristic s Male Female Sudan Net attendanc e ratio (adjusted) [1] Percentage of children: Numbe r of childre n Net attendanc e ratio ( adjusted) [1] Percentage of children: Numbe r of childre n Net attendanc e ratio (adjusted) [1] Percentage of children: Numbe r of childre n Not attendin g school or pre- school Attendin g pre- school Out of school [a] Not attending school or preschoo l Attendin g preschoo l Out of school [a] Not attendin g school or pre- school Attendin g pre- school Out of school [a] Sudan 77.4 12.5 8.5 21.0 11,522 75.5 13.9 8.4 22.3 11,454 76.4 13.2 8.5 21.6 22,977 State Northern 95.7 2.8 3.1 5.8 204 95.3 2.2 3.3 5.5 200 95.5 2.5 3.2 5.7 404 River Nile 90.4 4.4 5.5 9.8 321 91.7 5.5 2.3 7.8 344 91.1 4.9 3.9 8.8 665 Red Sea 85.3 9.0 8.5 17.5 263 83.5 9.9 7.9 17.8 249 84.4 9.4 8.2 17.7 512 Kassala 68.7 14.1 11.7 25.7 547 67.9 14.9 17.5 32.4 469 68.3 14.4 14.4 28.8 1,016 Gadarif 75.9 12.9 12.1 25.0 621 68.6 16.2 10.1 26.3 600 72.3 14.5 11.1 25.6 1,220 Khartoum 95.5 3.0 7.4 10.4 1,377 95.0 2.1 6.2 8.3 1,411 95.3 2.6 6.8 9.3 2,788 Gezira 85.2 9.3 5.9 15.2 1,801 83.2 8.9 7.6 16.5 1,783 84.2 9.1 6.7 15.8 3,585 White Nile 79.7 12.8 5.5 18.3 564 79.0 12.9 5.2 18.1 584 79.3 12.9 5.3 18.2 1,148 Sinnar 83.0 10.7 14.5 25.2 408 80.2 13.0 15.6 28.6 409 81.6 11.9 15.1 26.9 816 Blue Nile 78.6 14.3 28.2 42.5 500 77.3 14.7 27.8 42.5 479 78.0 14.5 28.0 42.5 979 North Kordofan 76.8 13.1 3.8 16.9 748 71.0 17.2 2.9 20.1 758 73.9 15.2 3.3 18.5 1,506 South Kordofan 69.3 17.2 5.5 22.7 399 69.6 13.8 8.3 22.1 380 69.5 15.6 6.8 22.4 779 West Kordofan 56.0 21.6 5.0 26.7 715 52.4 27.5 8.2 35.8 769 54.1 24.7 6.7 31.4 1,483 North Darfur 76.0 15.0 9.3 24.3 989 77.4 14.1 7.6 21.7 959 76.7 14.6 8.4 23.0 1,949 West Darfur 63.5 19.1 8.4 27.5 436 56.8 28.0 5.1 33.1 405 60.3 23.4 6.8 30.2 841 South Darfur 65.0 17.2 9.6 26.7 979 67.4 18.6 8.9 27.5 996 66.2 17.9 9.2 27.1 1,975 Central Darfur 57.6 22.9 6.4 29.3 219 50.9 25.3 5.5 30.9 230 54.1 24.1 6.0 30.1 449 East Darfur 66.3 16.2 8.0 24.2 431 57.8 23.0 6.6 29.6 428 62.0 19.6 7.3 26.9 859 180 Background characteristic s Male Female Sudan Net attendanc e ratio (adjusted) [1] Percentage of children: Numbe r of childre n Net attendanc e ratio ( adjusted) [1] Percentage of children: Numbe r of childre n Net attendanc e ratio (adjusted) [1] Percentage of children: Numbe r of childre n Not attendin g school or pre- school Attendin g pre- school Out of school [a] Not attending school or preschoo l Attendin g preschoo l Out of school [a] Not attendin g school or pre- school Attendin g pre- school Out of school [a] Area Urban 91.6 5.1 6.0 11.1 3,205 91.3 4.0 5.5 9.5 3,241 91.4 4.5 5.7 10.3 6,446 Rural 71.9 15.3 9.5 24.8 8,317 69.2 17.8 9.6 27.4 8,213 70.6 16.5 9.6 26.1 16,531 Age at beginning of school year 6 62.7 20.9 24.7 45.6 1,560 64.5 19.7 24.9 44.6 1,582 63.6 20.3 24.8 45.1 3,142 7 71.8 16.1 11.3 27.4 1,605 70.7 15.1 10.7 25.8 1,706 71.2 15.6 11.0 26.6 3,311 8 76.3 12.7 7.3 20.0 1,637 76.8 12.9 7.5 20.4 1,567 76.5 12.8 7.4 20.2 3,204 9 84.2 8.3 5.3 13.5 1,357 80.9 10.7 6.1 16.8 1,284 82.6 9.4 5.7 15.1 2,640 10 79.9 10.2 4.3 14.4 1,607 80.5 10.8 4.2 15.0 1,456 80.2 10.5 4.2 14.7 3,063 11 85.6 6.5 3.6 10.1 1,127 82.3 10.9 4.1 15.0 1,161 84.0 8.7 3.9 12.6 2,289 12 83.1 10.5 5.2 15.7 1,541 76.8 13.0 2.9 15.9 1,509 80.0 11.7 4.1 15.8 3,051 13 79.5 12.4 3.1 15.4 1,088 74.7 16.8 3.5 20.3 1,189 77.0 14.7 3.3 18.0 2,277 Wealth index quintile Poorest 58.8 20.7 8.2 28.9 2,710 56.0 24.1 7.8 31.9 2,644 57.4 22.4 8.0 30.4 5,353 Second 66.5 18.7 10.2 28.9 2,473 62.1 22.0 10.6 32.6 2,469 64.3 20.4 10.4 30.8 4,942 Middle 81.6 11.5 13.5 25.0 2,462 80.0 12.5 13.0 25.6 2,326 80.8 12.0 13.3 25.3 4,788 Fourth 92.6 5.2 5.1 10.3 2,154 91.5 4.4 6.5 10.9 2,197 92.0 4.8 5.8 10.6 4,352 Richest 97.2 1.0 3.8 4.9 1,724 96.7 1.1 2.9 4.0 1,818 96.9 1.1 3.3 4.4 3,542 [1] MICS indicator 7.4; MDG indicator 2.1 - Primary school net attendance ratio (adjusted) [a] The percentage of children of primary school age out of school are those not attending school and those attending preschool 181 The secondary school net attendance ratio is presented in Table ED.542. More dramatic than in primary school, only (28.4 percent) of the children of secondary school age are attending secondary school or higher. Of those who are not attending secondary schools, some were attending primary schools while the rest were out of school. Approximately 37.0 percent of the children of secondary school age were attending primary schools while the remaining 24.2 percent out of school. The net secondary school attendance ratios were highest (38.4 percent) among children aged 16 years and lowest (20.1 percent) among those aged 14 years. In the case of boys, the net attendance rate was highest (36.1 percent) among those aged 16 years and lowest (19.3 percent) among boys aged 14 years. Net secondary school attendance ratios for girls was highest (40.9 percent) among 16 year-olds and lowest (20.7 percent) among those aged 14 years. There were variations in net secondary school attendance ratios for children living in urban and rural areas; 42.2 percent for children in urban areas compared to 22.2 percent for those in rural areas. There were also considerable variations in the net secondary school attendance ratios among States; the net secondary school attendance ratios ranged from 12.2 percent in Central Darfur State to 56.1 percent in Khartoum State. Also even within states variations exists between boys and girls in terms of the net secondary school attendance ratios for boys, ranging from 10.7 percent in Blue Nile State to 53.6 percent in Khartoum State. Noticeable variations also exist among States in net secondary school attendance ratio for girls, ranging from 11.4 percent in Central Darfur State to 58.2 percent in Khartoum State. (see figure ED.2) The household wealth also appears to have an influence on the net secondary school attendance ratio. The net secondary school attendance ratio was only 9.1 percent among children belonging to households in the poorest quintile compared to 68.5 percent among children from the households in the richest quintile. 42 Ratios presented in this table are "adjusted" since they include not only secondary school attendance, but also attendance to higher levels in the numerator. 182 Figure ED.1b: Children of secondary school age attending secondary school (adjusted net attendance ratio) for boys and girls by state and by urban/rural area, Sudan MICS, 2014 27 35 49 33 14 16 54 38 25 18 11 16 15 17 22 28 20 13 14 40 22 29 58 52 38 16 18 58 39 28 26 15 15 21 12 22 18 17 11 16 45 22 0 10 20 30 40 50 60 70 Sudan Northern River Nile Red Sea Kassala Gadarif Khartoum Gezira White Nile Sinnar Blue Nile North Kordofan South Kordofan West Kordofan North Darfor West Darfor South Darfor Central Darfor East Darfor Urban Rural Female Male 183 Table ED.5: Secondary school attendance and out of school children Percentage of children of secondary school age attending secondary school or higher (adjusted net attendance ratio), percentage attending primary school, and percentage out of school, Sudan MICS, 2014 Background characteristics Male Female Sudan Net attenda nce ratio (adjust ed) [1] Percent age of children : Attendi ng primary school Percent age of children : Out of school [a] Numb er of childre n Net attend ance ratio (adj. [1] Percent age of children : Attendin g primary school Percent age of children : Out of school [a] Numb er of childre n Net attenda nce ratio (adjust ed) [1] Percent age of children : Attendi ng primary school Percent age of children : Out of school [a] Numb er of childr en Sudan 27.4 41.6 20.8 3087 29.4 32.6 27.5 3214 28.4 37.0 24.2 6,300 State Northern 35.2 43.4 20.0 77 57.5 30.4 11.5 64 45.4 37.5 16.1 141 River Nile 49.4 29.0 17.7 118 51.6 19.3 26.4 104 50.5 24.4 21.8 222 Red Sea 33.1 45.8 13.2 79 38.1 33.3 19.8 58 35.2 40.5 16.0 137 Kassala 13.7 44.9 32.7 148 16.2 29.2 37.8 127 14.8 37.7 35.1 275 Gadarif 15.7 44.7 21.8 167 18.3 37.3 29.2 154 16.9 41.2 25.4 321 Khartoum 53.6 27.1 11.9 369 58.2 29.4 9.1 422 56.1 28.3 10.4 790 Gezira 38.4 40.3 18.3 464 39.2 17.2 32.2 567 38.9 27.5 25.9 1,031 White Nile 25.0 40.4 30.2 172 28.0 34.0 32.3 150 26.4 37.4 31.2 322 Sinnar 18.3 43.8 31.8 102 26.0 35.9 21.9 100 22.1 39.9 26.9 202 Blue Nile 10.7 34.2 29.0 137 14.5 25.9 30.6 137 12.6 30.0 29.8 274 North Kordofan 16.0 40.6 32.2 213 15.1 38.8 34.9 192 15.6 39.7 33.5 405 South Kordofan 14.9 43.6 29.1 73 20.5 31.8 35.9 92 18.0 37.0 32.9 165 West Kordofan 17.2 39.2 24.6 178 12.1 36.8 33.3 197 14.5 37.9 29.2 374 North Darfur 22.3 53.8 15.6 248 22.1 48.6 23.1 285 22.2 51.1 19.6 533 West Darfur 27.6 52.3 8.5 105 17.8 41.3 29.8 114 22.5 46.6 19.6 219 South Darfur 20.4 49.3 13.6 263 17.0 43.9 32.1 273 18.7 46.6 23.0 536 Central Darfur 13.0 47.0 20.4 63 11.4 38.2 38.3 66 12.2 42.5 29.6 130 East Darfur 14.0 51.0 23.9 112 16.3 38.5 28.6 111 15.2 44.8 26.2 224 Area Urban 39.7 42.2 12.4 959 44.6 37.6 12.3 1007 42.2 39.9 12.3 1,966 Rural 21.9 41.4 24.6 2128 22.4 30.3 34.4 2207 22.2 35.7 29.6 4,334 Age at beginning of school year 14 19.3 55.4 14.3 1094 20.7 45.2 22.4 1499 20.1 49.5 19.0 2,593 15 28.0 39.8 22.8 1025 32.9 28.2 29.4 848 30.2 34.5 25.8 1,873 16 36.1 28.1 25.9 969 40.9 15.1 34.3 866 38.4 22.0 29.9 1,835 Melevel Cannot be determined [b] 26.7 33.0 20.0 166 14.1 16.8 51.9 253 19.1 23.2 39.3 419 Missing 27.5 42.1 20.8 2921 30.7 33.9 25.4 2960 29.1 38.0 23.1 5,882 Wealth index quintile Poorest 9.6 46.5 25.1 658 8.6 36.5 39.3 679 9.1 41.4 32.3 1,337 Second 17.6 40.1 27.3 674 13.2 36.7 36.6 645 15.5 38.4 31.9 1,320 Middle 15.0 50.9 25.6 590 15.3 36.1 34.4 640 15.1 43.2 30.2 1,230 Fourth 34.6 42.3 19.1 565 40.2 34.4 18.8 645 37.6 38.1 19.0 1,210 Richest 63.6 28.2 5.5 599 73.3 18.1 6.2 604 68.5 23.1 5.8 1,204 [1] MICS indicator 7.5; MDG indicator 2.1 - Secondary school net attendance ratio (adjusted) a The percentage of children of secondary school age out of school are those who are not attending primary, secondary, or higher education 184 The percentage of children entering first grade who eventually reach the last grade of primary school is presented in Table ED.6. Of all children starting grade one, the majority (80.4 percent) will eventually reach grade 8. The MICS included only questions on school attendance in the current and previous year. Thus, the indicator is calculated synthetically by computing the cumulative probability of survival from the first to the last grade of primary school, as opposed to calculating the indicator for a real cohort which would need to be followed from the time a cohort of children entered primary school, up to the time they reached the last grade of primary school. Repeaters are excluded from the calculation of the indicator, because it is not known whether they will eventually graduate. As an example, the probability that a child will move from the first grade to the second grade is computed by dividing the number of children who moved from the first grade to the second grade (during the two consecutive school years covered by the survey) by the number of children who have moved from the first to the second grade plus the number of children who were in the first grade the previous school year, but dropped out. Both the numerator and denominator excludes children who repeated during the two school years under consideration. The percentage of children entering first grade who eventually reach grade 8 of primary school was 93.2 in urban areas compared to 73.8 in rural areas. The percentage of children entering first grade of primary school in a given year and who eventually reach grade 8 was associated with household wealth. The percentage of children reaching grade 8 was 97.4 among children from households in the richest quintile compared to 66.1 among children from households in the poorest quintile. Table ED.6: Children reaching last grade of primary school Percentage of children entering first grade of primary school who eventually reach the last grade of primary school (Survival rate to last grade of primary school), Sudan MICS, 2014 Background characteristics Percent attending grade 1 last school year who are in grade 2 this school year Percent attending grade 2 last school year who are attending grade 3 this school year Percent attending grade 3 last school year who are attending grade 4 this school year Percent attending grade 4 last school year who are attending grade 5 this school year Percent attending grade 5 last school year who are attending grade 6 this school year Percent attending grade 6 last school year who are attending grade 7 this school year Percent attending grade 7 last school year who are attending grade 8 this school year Percent who reach grade 8 of those who enter grade 1 [1] Sudan 97.3 98.5 97.6 97.4 97.4 96.4 94.0 80.4 Sex Male 96.8 98.5 98.1 97.6 97.4 95.8 93.9 80.0 Female 97.9 98.6 97.0 97.2 97.4 97.0 94.0 80.8 State Northern 100.0 99.5 99.0 98.6 95.7 95.7 92.2 81.9 River Nile 100.0 98.8 98.4 98.8 98.9 97.1 96.8 89.2 Red Sea 100.0 98.7 99.2 95.9 100.0 98.0 97.9 90.1 Kassala 99.0 98.6 100.0 99.2 100.0 98.4 96.9 92.4 Gadarif 98.3 99.5 98.0 97.4 96.0 98.9 88.8 78.8 Khartoum 100.0 100.0 98.8 98.9 99.4 97.9 99.3 94.4 Gezira 96.9 99.7 97.9 98.5 98.9 96.4 95.0 84.4 White Nile 98.3 97.9 97.5 97.7 97.6 97.3 91.8 80.0 Sinnar 100.0 98.6 97.9 98.2 98.7 97.1 86.8 78.9 185 Background characteristics Percent attending grade 1 last school year who are in grade 2 this school year Percent attending grade 2 last school year who are attending grade 3 this school year Percent attending grade 3 last school year who are attending grade 4 this school year Percent attending grade 4 last school year who are attending grade 5 this school year Percent attending grade 5 last school year who are attending grade 6 this school year Percent attending grade 6 last school year who are attending grade 7 this school year Percent attending grade 7 last school year who are attending grade 8 this school year Percent who reach grade 8 of those who enter grade 1 [1] Blue Nile 93.6 93.3 92.1 95.5 96.4 88.9 90.1 59.4 North Kordofan 99.0 99.6 98.8 100.0 97.6 93.1 86.6 76.7 South Kordofan 96.8 99.0 100.0 98.0 95.2 93.8 93.2 78.2 West Kordofan 97.8 97.1 93.2 93.5 94.4 97.6 89.7 68.3 North Darfur 98.7 98.3 98.5 95.9 96.3 95.6 92.1 77.8 West Darfur 89.5 95.2 93.5 92.2 90.5 92.2 92.0 56.4 South Darfur 91.5 96.0 95.6 95.4 95.0 97.3 93.5 69.3 Central Darfur 92.3 98.0 94.5 95.4 87.7 96.5 98.5 67.9 East Darfur 96.0 100.0 97.4 97.6 98.7 98.9 98.4 87.6 Area Urban 99.4 99.8 99.0 99.3 99.2 99.2 97.1 93.2 Rural 96.2 98.0 96.9 96.4 96.2 94.8 91.8 73.8 Wealth index quintile Poorest 94.5 98.2 96.1 93.6 94.3 94.2 89.3 66.1 Second 96.2 96.7 96.1 96.9 94.5 96.4 91.3 72.1 Middle 96.6 98.3 97.0 96.8 97.4 93.8 90.8 74.0 Fourth 99.4 99.4 98.9 99.3 99.0 97.4 97.4 91.2 Richest 100.0 100.0 99.7 100.0 99.7 99.5 98.4 97.4 1 MICS indicator 7.6; MDG indicator 2.2 - Children reaching last grade of primary The primary school completion rate and transition rate to secondary education are presented in Table ED.7. The primary completion rate is the ratio of the Sudan number of students, regardless of age, entering the last grade of primary school for the first time, to the number of children of the primary graduation age at the beginning of the current (or most recent) school year. Over nine-tenths(90.7 percent) of the children who were attending the last grade of primary school in the previous school year were found to be attending the first grade of secondary school in the school year of the survey. The table also provides “effective” transition rate which takes account of the presence of repeaters in the final grade of primary school. This indicator better reflects situations in which pupils repeat the last grade of primary education but eventually make the transition to the secondary level. The simple transition rate tends to underestimate pupils’ progression to secondary school as it assumes that the repeaters never reach secondary school. The table shows that in Sudan 97.9 percent of the children in the last grade of primary school are expected to move on transition to secondary school. At the time of the survey, the primary school completion rate was 79.3 percent (84.8 percent for boys and 74.3 percent for girls). The primary school completion rate was 111.2 percent for children in urban 186 areas compared to 65.8 percent for children in rural areas. It appears that in urban areas there exist a number of overaged children in the last grade of primary schools The primary school completion rate seems to increase with the household wealth. It was only 57.7 percent among children from households in the poorest quintile compared to 118.6 percent among children from households in the richest quintile. Table ED.7: Primary school completion and transition to secondary school Primary school completion rates and transition and effective transition rates to secondary school, Sudan MICS, 2014 Background characteristics Primary school completion rate [1] Number of children of primary school completion age Transition rate to secondary school [2] Number of children who were in the last grade of primary school the previous year Effective transition rate to secondary school Number of children who were in the last grade of primary school the previous year and are not repeating that grade in the current school year Sudan 79.3 2,277 90.7 1,161 97.9 1,075 Sex Male 84.8 1,088 90.4 587 99.5 534 Female 74.3 1,189 91.0 574 96.4 542 State Northern 95.9 45 92.4 27 92.4 27 River Nile 90.8 67 96.1 48 97.0 47 Red Sea (102.7) 41 * 15 * 14 Kassala 63.1 104 (65.8) 27 * 22 Gadarif 53.0 129 87.6 56 93.4 53 Khartoum 119.6 285 92.6 165 96.7 158 Gezira 70.2 363 90.9 249 96.7 234 White Nile 90.0 110 96.8 63 106.1 57 Sinnar 59.6 85 (90.1) 30 (105.4) 25 Blue Nile 49.1 91 (81.2) 33 (94.2) 28 North Kordofan 58.5 160 (86.7) 46 (118.2) 33 South Kordofan 78.8 64 86.9 27 91.7 26 West Kordofan 55.2 148 (83.0) 37 (83.8) 36 North Darfur 91.3 176 88.7 154 96.9 141 West Darfur 87.8 81 94.8 47 104.1 43 South Darfur 95.9 188 90.1 90 94.6 86 Central Darfur 71.1 47 93.7 17 (110.9) 14 East Darfur 69.2 91 93.7 32 97.6 31 Area Urban 111.2 677 93.9 441 100.6 411 Rural 65.8 1,600 88.7 720 96.2 664 Wealth index quintile Poorest 57.7 510 84.4 167 94.0 150 Second 57.0 489 91.3 193 98.1 180 Middle 79.0 447 87.0 194 96.6 175 Fourth 95.4 452 89.9 289 99.1 262 Richest 118.6 378 96.6 318 99.5 309 187 [1] MICS indicator 7.7 - Primary completion rate [2] MICS indicator 7.8 - Transition rate to secondary school ( ) Figures that are based on 25-49 unweighted cases [*] Based on less than 25 unweighted cases and has been suppressed. The ratio of girls to boys attending primary and secondary education is provided in Table ED.8. These ratios are better known as the Gender Parity Index (GPI). Notice that the ratios included here are obtained from net attendance ratios rather than gross attendance ratios. The latter provide an erroneous description of the GPI mainly because, in most cases, the majority of over-aged children attending primary education tend to be boys. The table shows that gender parity for primary school is (0.98) close to 1.00, indicating no difference in the attendance of girls and boys to primary school. However, the indicator increases to 1.07 for secondary education. The disadvantage of girls at the primary stage of education is particularly pronounced in Eastern Darfur state (GPI: 0.87), as well as among children living in the poorest households (GPI: 0.95). The GPI at the secondary stage for children belonging to households in the richest quintile was 1.15 compared to 0.90 for children belonging to households in the poorest quintile. The GPI at the secondary stage of education ranged between 0.64 in Western Darfur State to 1.63 in Northern state. Table ED.8: Education gender parity Ratio of adjusted net attendance ratios of girls to boys, in primary and secondary school, Sudan MICS, 2014 Background characteristics Primary school adjusted net attendance ratio (NAR), girls Primary school adjusted net attendance ratio (NAR), boys Gender parity index (GPI) for primary school adjusted NAR [1] Secondary school adjusted net attendance ratio (NAR), girls Secondary school adjusted net attendance ratio (NAR), boys Gender parity index (GPI) for secondary school adjusted NAR [2] Sudan 75.5 77.4 0.98 29.4 27.4 1.07 State Northern 95.3 95.7 1.00 57.5 35.2 1.63 River Nile 91.7 90.4 1.01 51.6 49.4 1.04 Red Sea 83.5 85.3 0.98 38.1 33.1 1.15 Kassala 67.9 68.7 0.99 16.2 13.7 1.18 Gadarif 68.6 75.9 0.90 18.3 15.7 1.17 Khartoum 95.0 95.5 1.00 58.2 53.6 1.09 Gezira 83.2 85.2 0.98 39.2 38.4 1.02 White Nile 79.0 79.7 0.99 28.0 25.0 1.12 Sinnar 80.2 83.0 0.97 26.0 18.3 1.42 Blue Nile 77.3 78.6 0.98 14.5 10.7 1.35 North Kordofan 71.0 76.8 0.92 15.1 16.0 0.94 South Kordofan 69.6 69.3 1.00 20.5 14.9 1.38 West Kordofan 52.4 56.0 0.93 12.1 17.2 0.71 North Darfur 77.4 76.0 1.02 22.1 22.3 0.99 West Darfur 56.8 63.5 0.89 17.8 27.6 0.64 South Darfur 67.4 65.0 1.04 17.0 20.4 0.83 Central Darfur 50.9 57.6 0.88 11.4 13.0 0.88 East Darfur 57.8 66.3 0.87 16.3 14.0 1.16 188 Table ED.8: Education gender parity Ratio of adjusted net attendance ratios of girls to boys, in primary and secondary school, Sudan MICS, 2014 Background characteristics Primary school adjusted net attendance ratio (NAR), girls Primary school adjusted net attendance ratio (NAR), boys Gender parity index (GPI) for primary school adjusted NAR [1] Secondary school adjusted net attendance ratio (NAR), girls Secondary school adjusted net attendance ratio (NAR), boys Gender parity index (GPI) for secondary school adjusted NAR [2] Area Urban 91.3 91.6 1.00 44.6 39.7 1.12 Rural 69.2 71.9 0.96 22.4 21.9 1.02 Wealth index quintile Poorest 56.0 58.8 0.95 8.6 9.6 0.90 Second 62.1 66.5 0.93 13.2 17.6 0.75 Middle 80.0 81.6 0.98 15.3 15.0 1.02 Fourth 91.5 92.6 0.99 40.2 34.6 1.16 Richest 96.7 97.2 0.99 73.3 63.6 1.15 [1] MICS indicator 7.9; MDG indicator 3.1 - Gender parity index (primary school) [2] MICS indicator 7.10; MDG indicator 3.1 - Gender parity index (secondary school) [a] Children age 15 or higher at the time of the interview whose mothers were not living in the household The percentage of girls in Sudan out of school population, in both primary and secondary school, are provided in Table ED.9. The table shows that at the primary level girls account for about half (51.4 percent) of the out-of-school population. Girls’ share increased to 56.4 percent, however, at the secondary level. There were also considerable variations in the out-of-school at primary level among States with West Kordofan recording up to 59.1 percent of girls of primary school age out of school. At secondary level there also exists considerable variations among states in terms of the out-of-school for girls of primary school age with south Darfur recoding up 65.8 percent. 189 Figure ED.1c: Girls out of school in primary and secondary by wealth index quintiles, Sudan MICS, 2014 Table ED.9: Out of school gender parity Percentage of girls in the Sudan out of school population, in primary and secondary school, Sudan MICS, 2014 Background characteristics Primary school Secondary school Percentag e of out of school children Number of children of primary school age Percent age of girls in the Sudan out of school populati on of primary school age Number of children of primary school age out of school Percent age of out of school children Number of children of secondar y school age Percent age of girls in the Sudan out of school populati on of second ary school age Number of children of secondary school age out of school Sudan 21.6 22,977 51.4 4,974 26.7 6,300 56.4 1,682 State Northern 5.7 404 * 23 16.3 141 * 23 River Nile 8.8 665 46.0 59 22.3 222 57.7 50 Red Sea 17.7 512 49.0 90 17.9 137 (46.6) 25 Kassala 28.8 1,016 51.9 293 39.6 275 49.9 109 Gadarif 25.6 1,220 50.3 313 30.2 321 49.6 97 Khartoum 9.3 2,788 45.0 260 12.4 790 44.3 98 Gezira 15.8 3,585 51.8 568 26.5 1,031 68.0 274 White Nile 18.2 1,148 50.5 209 32.1 322 48.9 103 Sinnar 26.9 816 53.2 220 31.7 202 44.7 64 52 53 49 52 46 59 54 59 53 51 0 10 20 30 40 50 60 70 Poorest Second Middle Fourth Richest P er ce nt Wealth Index quintile Primary Secondary 190 Background characteristics Primary school Secondary school Percentag e of out of school children Number of children of primary school age Percent age of girls in the Sudan out of school populati on of primary school age Number of children of primary school age out of school Percent age of out of school children Number of children of secondar y school age Percent age of girls in the Sudan out of school populati on of second ary school age Number of children of secondary school age out of school Blue Nile 42.5 979 48.9 416 47.7 274 52.2 131 North Kordofan 18.5 1,506 54.7 279 33.5 405 49.4 136 South Kordofan 22.4 779 48.2 175 34.5 165 61.5 57 West Kordofan 31.4 1,483 59.1 466 31.6 374 57.9 118 North Darfur 23.0 1,949 46.4 448 20.1 533 61.3 107 West Darfur 30.2 841 52.8 254 20.5 219 (76.8) 45 South Darfur 27.1 1,975 51.1 536 25.3 536 65.8 136 Central Darfur 30.1 449 52.5 135 33.5 130 (63.0) 43 East Darfur 26.9 859 54.9 231 30.3 224 51.0 68 Area Urban 10.3 6,446 46.3 662 13.2 1,966 50.5 259 Rural 26.1 16,531 52.1 4,312 32.8 4,334 57.4 1,423 Wealth index quintile Poorest 30.4 5,353 51.9 1,628 35.0 1,337 59.0 468 Second 30.8 4,942 52.9 1,521 36.0 1,320 54.0 474 Middle 25.3 4,788 49.1 1,209 34.9 1,230 59.0 429 Fourth 10.6 4,352 51.8 460 19.6 1,210 52.6 237 Richest 4.4 3,542 46.4 156 6.1 1,204 51.4 74 [a] Children age 15 or higher at the time of the interview whose mothers were not living in the household [*] Based on less than 25 unweighted cases and has been suppressed. 191 Figure ED.1 brings together all of the attendance and progression related education indicators covered in this chapter, by sex. Information on attendance to early childhood education is also included, which was covered in Chapter 9, in Table CD.1. F i g u r e E D . 1 : Ed u c a t i o n i n d i c a t o r s b y s e x , S u d a n M I C S , 2 0 1 4 School readiness 66 73 Net intake rate in primary education Primary school completion rate Transition rate to secondary school 36 38 85 74 90 91 Attendance to early childhood education Primary school attendance Secondary school attendance 22 23 77 76 27 29 Children reaching last grade of primary 80 81 Boys Girls Note: All indicator values are in per cent 192 XI. Child Protection 11.1 Birth Registration A name and nationality is every child’s right, enshrined in the Convention on the Rights of the Child (CRC) and other international treaties. Yet the births of around one in four children under the age of five worldwide have never been recorded.43 This lack of formal recognition by the State usually means that a child is unable to obtain a birth certificate. As a result, he or she may be denied health care or education. Later in life. The lack of official identification documents can mean that a child may enter into marriage or the labour market, or be conscripted into the armed forces before the legal age. In adulthood, birth certificates may be required to obtain social assistance or a job in the formal sector, to buy or prove the right to inherit property, to vote, and to obtain a passport. Registering children at birth is the first step in securing their recognition before the law, safeguarding their rights, and ensuring that any violation of these rights does not go unnoticed.44 Table CP.1: Birth registration Percentage of children under age 5 by whether birth is registered and percentage of children not registered whose mothers/caretakers know how to register birth, Sudan MICS, 2014 Background characteristics Children under age 5 whose birth is registered with civil authorities Number of children under age 5 Children under age 5 whose birth is not registered Has birth certificate No birth certificate Total registered [1] Percent of children whose mother/ caretaker knows how to register birth Number of children under age 5 without birth registration Seen Not seen Sudan 23.4 26.4 17.5 67.3 14,081 35.2 4,599 Sex Male 24.3 27.2 17.4 68.8 7,157 35.2 2,230 Female 22.5 25.6 17.7 65.8 6,924 35.3 2,369 State Northern 43.4 41.9 13.0 98.3 236 * 4 River Nile 26.1 50.6 20.2 96.8 393 * 13 Red Sea 37.8 34.0 8.8 80.5 244 28.3 47 Kassala 24.4 20.2 14.7 59.2 498 13.9 203 Gadarif 19.9 32.7 27.1 79.8 765 40.7 155 Khartoum 39.8 41.9 15.2 96.9 1736 * 55 Gezira 37.6 22.5 19.8 79.9 2149 57.1 433 White Nile 19.9 27.8 23.1 70.8 711 62.2 207 Sinnar 29.7 29.0 16.9 75.6 555 46.7 135 Blue Nile 31.2 14.9 12.9 58.9 691 36.1 284 North Kordofan 23.8 25.5 26.5 75.8 907 47.7 219 South Kordofan 17.5 17.6 26.0 61.2 529 39.3 205 West Kordofan 4.2 24.1 10.5 38.7 893 34.5 547 North Darfur 8.0 26.7 15.0 49.7 1,211 27.9 609 West Darfur 11.6 27.0 9.1 47.8 487 28.0 254 43 UNICEF. 2014. The State of the World’s Children 2015. UNICEF. 44 UNICEF. 2013. Every Child’s Birth Right: Inequities and trends in birth registration. UNICEF. 193 Background characteristics Children under age 5 whose birth is registered with civil authorities Number of children under age 5 Children under age 5 whose birth is not registered Has birth certificate No birth certificate Total registered [1] Percent of children whose mother/ caretaker knows how to register birth Number of children under age 5 without birth registration Seen Not seen South Darfur 9.9 19.4 15.4 44.7 1,326 23.7 733 Central Darfur 7.0 9.4 14.5 30.9 254 22.9 176 East Darfur 11.0 7.6 16.8 35.5 495 32.4 320 Area Urban 38.2 37.4 13.4 89.0 3,862 51.4 426 Rural 17.8 22.3 19.1 59.2 10,219 33.6 4,173 Age 0-11 16.8 19.7 25.5 62.0 2,964 40.1 1,125 12-23 21.8 25.6 21.9 69.2 2,672 36.6 822 24-35 26.4 27.2 14.9 68.4 2,618 32.0 827 36-47 25.6 30.5 12.4 68.4 3,268 31.0 1,031 48-59 26.9 29.0 13.1 69.0 2,559 35.8 794 Mother's education None 13.1 18.7 15.3 47.2 5,994 30.2 3,163 Primary 24.7 27.7 22.9 75.4 4,936 41.3 1,215 Secondary 37.3 37.4 16.1 90.8 2,152 73.2 197 Higher 48.1 42.4 7.4 97.9 982 * 21 Missing/DK * * * * 17 * 2 Wealth index quintile Poorest 5.5 17.0 14.5 37.0 3,188 26.2 2,008 Second 11.3 20.3 21.8 53.4 3,015 36.8 1,405 Middle 23.8 26.2 23.8 73.8 2,956 42.9 773 Fourth 36.0 33.2 17.1 86.4 2,684 57.3 366 Richest 49.4 40.0 8.5 97.9 2,238 (76.6) 46 [1] MICS indicator 8.1 - Birth registration ( ) Figures that are based on 25-49 unweighted cases * Based on less than 25 unweighted cases and has been suppressed. The births of 67.3 percent of children under five years in MICS 2014 have been registered; 23.4 percent of the registration certificates have been seen by the interviewers, 26.4 percent have not been seen by the interviewers, and 17.5 were reported to have no birth certificate (Table CP.1). Registration of birth becomes more likely as a child grows older. There are no significant variations in birth registration depending on the sex of the child with male children registered at 68.8 percent and females at 65.8 percent. Children in Central Darfur State (30.9 percent) were the least to have their births registered than children other states with Northern states (98.3 percent) recording the highest number of children under five whose births are registered. While only 37.0 percent of the children in the poorest households were registered, nearly all children (97.9 percent) of under five children who belong to richest households were registered. The data show significant differences between the proportion of children whose births are reported as registered and those who actually have a birth certificate. 194 Overall, only 49.8 of children possess a birth certificate. These findings are also presented in Figure CP.1. Urban-rural differentials indicated that 89.0 percent and 59.2 percent of under five children were registered in urban and rural areas respectively. Figure CP.1: Children under age five whose births are registered, Sudan MICS, 2014 The lack of adequate knowledge of how to register a child can present another major obstacle to the fulfilment of a child’s right to identity. Data show that only 35.2 percent of mothers of unregistered children report knowing how to register a child’s birth or the majority of mothers without registered children appear not to be aware of the registration process. This is further shown that while only 47.2 percent of under five children whose mothers’ have no education have been registered, as high as 97.9 percent of those whose mothers are highly educated, have been registered. 11.2 Child Labour Children around the world are routinely engaged in paid and unpaid forms of work that are not harmful to them. However, they are classified as child labourers when they are either too young to work or are involved in hazardous activities that may compromise their physical, mental, social or educational development. Article 32 (1) of the Convention on the Rights of the Child states: "States Parties recognize the right of the child to be protected from economic exploitation and from performing any work that is likely to be hazardous or to interfere with the child's education, or to be harmful to the child's health or physical, mental, spiritual, moral or social development". 13 20 9 15 27 15 20 23 17 13 26 26 10 15 9 15 15 17 13 19 15 23 16 7 18 85 77 72 45 53 82 60 48 59 46 49 35 28 35 39 29 16 19 76 40 32 52 75 90 50 State Northern River Nile Red Sea Kassala Gadarif Khartoum Gezira White Nile Sinnar Blue Nile North Kordofan South Kordofan West Kordofan North Darfor West Darfor South Darfor Central Darfor East Darfor Area Urban Rural Mother's education None Primary Secondary Higher Sudan Per cent Registered, no birth certificate Birth certificate 195 The child labour module was administered for children age 5-17 and includes questions on the type of work a child does and the number of hours he or she is engaged in it. Data are collected on both economic activities (paid or unpaid work for someone who is not a member of the household, work for a family farm or business) and domestic work (household chores such as cooking, cleaning or caring for children, as well as collecting firewood or fetching water). The module also collects information on hazardous working conditions. 45, 46 Table CP.2 presents children’s involvement in economic activities. The methodology of the MICS Indicator on Child Labour uses three age-specific thresholds for the number of hours a child can perform economic activity without it being classified as in child labour. A child that performed economic activities during the last week for more than the age-specific number of hours is classified as in child labour: i. age 5-11: 1 hour or more ii. age 12-14: 14 hours or more iii. age 15-17: 43 hours or more While 39.1 percent of children age 12-14 are engaged in some forms of economic activities, 9 percent are performing such tasks for fourteen or more hours. The involvement in economic activities change with age: 21.0 percent of children age 5-11 years is engaged in economic activities, compared to 39.1 percent of children age 12-14 years, and 41.2 percent of children age 15-17 years. It is also clear from the MICS results that engagement in economic activities increases with movement from wealthiest to poorest households. For instance, among children aged 5 – 11 years engaged in economic activity, 9.2 percent of them belong to the wealthiest households while 35.0 percent of them fall in the poorest category. Similarly, involvement in economic activities varies with State ranging from 4.9 percent in Khartoum to 46.8 percent in South Darfur among children aged 5-11. 45 UNICEF. 2012. How Sensitive Are Estimates of Child Labour to Definitions? MICS Methodological Paper No. 1. UNICEF. 46 The Child Labour module and the Child Discipline module were administered using random selection of a single child in all households with one or more children age 1-17 (See Appendix F: Questionnaires). The Child Labour module was administered if the selected child was age 5-17 and the Child Discipline module if the child was age 1-14 years old. To account for the random selection, the household sample weight is multiplied by the total number of children age 1-17 in each household. 196 Table CP.2: Children's involvement in economic activities Percentage of children by involvement in economic activities during the last week, according to age groups, Sudan MICS, 2014 Background characteristics Percentage of children age 5-11 years involved in economic activity for at least one hour Number of children age 5-11 years Percentage of children age 12-14 years involved in: Number of children age 12- 14 years Percentage of children age 15-17 years involved in: Number of children age 15- 17 years Economic activity less than 14 hours Economic activity for 14 hours or more Economic activity less than 43 hours Economic activity for 43 hours or more Sudan 21.0 20,809 30.1 9.0 7,942 38.0 3.2 5,526 Sex Male 23.6 10,457 32.1 10.4 3,916 40.5 4.8 2,881 Female 18.4 10,352 28.2 7.7 4,024 35.4 1.4 2,645 Missing * 0 * * 2 * *. 0 State Northern 12.2 348 22.5 5.1 148 20.2 1.7 137 River Nile 7.3 606 15.4 4.1 279 23.0 0.7 183 Red Sea 11.9 470 25.5 0.3 151 18.2 0.0 129 Kassala 8.0 850 11.7 0.2 346 20.4 0.0 279 Gadarif 22.2 1,024 20.0 16.3 484 34.8 4.4 276 Khartoum 4.9 2,592 13.1 2.1 930 18.7 3.1 818 Gezira 15.1 3,092 23.9 2.2 1284 31.0 3.0 877 White Nile 12.1 1,104 33.1 0.2 359 31.8 0.2 261 Sinnar 18.7 690 32.4 9.8 306 34.3 4.9 169 Blue Nile 33.9 928 31.1 16.5 334 45.1 14.8 249 North Kordofan 16.0 1,404 30.2 16.6 562 41.2 4.3 337 South Kordofan 33.0 750 50.4 9.0 235 65.6 0.3 151 West Kordofan 26.2 1,282 40.8 7.6 508 51.2 0.0 356 North Darfur 22.8 1,806 42.1 9.1 611 47.7 5.3 484 West Darfur 28.9 827 44.9 6.6 231 49.8 3.9 190 South Darfur 46.8 1,870 40.4 24.0 660 67.3 0.0 383 Central Darfur 39.4 422 64.5 8.6 151 71.5 5.6 106 East Darfur 36.0 744 46.9 23.9 364 70.3 6.1 141 Area Urban 11.0 5,777 20.7 2.8 2,473 20.9 0.9 1,695 Rural 24.9 15,032 34.4 11.8 5,469 45.6 4.2 3,831 School attendance Yes 20.5 14,961 27.6 7.5 6,235 31.4 1.0 3,349 No 22.4 5,848 39.3 14.4 1,707 48.3 6.5 2,177 melevel Cannot be determined [a] * 3 * * 8 34.9 4.4 574 Wealth index quintile Poorest 35.0 4,932 42.7 18.9 1,785 63.7 4.9 1,084 197 Background characteristics Percentage of children age 5-11 years involved in economic activity for at least one hour Number of children age 5-11 years Percentage of children age 12-14 years involved in: Number of children age 12- 14 years Percentage of children age 15-17 years involved in: Number of children age 15- 17 years Economic activity less than 14 hours Economic activity for 14 hours or more Economic activity less than 43 hours Economic activity for 43 hours or more Second 25.1 4,577 42.2 10.7 1,633 54.3 3.4 1,066 Middle 18.1 4,563 30.6 9.9 1,450 32.2 5.7 1,120 Fourth 10.6 3,732 15.2 3.2 1,616 21.7 1.3 1,073 Richest 9.2 3,006 17.4 0.6 1,459 20.2 0.7 1,184 * Based on less than 25 unweighted cases and has been suppressed. Table CP.3 presents children’s involvement in household chores. As for economic activity above, the methodology also uses age-specific thresholds for the number of hours a child can perform household chores without it being classified as child labour. A child that performed household chores during the last week for more than the age-specific number of hours is classified as in child labour: i. age 5-11 and age 12-14: 28 hours or more ii. age 15-17: 43 hours or more The survey revealed that girls are more likely to perform household chores than boys across all three age groups. The percentage of children involved seem consistently higher in rural areas than in urban areas as well as strongly correlated to mother’s education and household wealth. For example, in age group 15 – 17 years, 85.4 percent are engaged in chores less than 43 hours in urban areas; while in rural settings it is 75.4 percent with Blue Nile state recording the highest percentage (92.1 percent) and North Darfur state reporting the lowest (59.2 percent). Similarly, within the same age group, an interesting results shows that percentage of children engaged in chores less than 43 hours declines as we move from wealthiest (85.6 percent) households to the poorest ones (71.1 Percent). Table CP.3: Children's involvement in household chores Percentage of children by involvement in household chores during the last week, according to age groups, Sudan MICS, 2014 Backgound characteristics Percentage of children age 5-11 years involved in: Number of children age 5- 11 years Percentage of children age 12-14 years involved in: Number of children age 12- 14 years Percentage of children age 15-17 years involved in: Number of children age 15- 17 years Household chores less than 28 hours Household chores for 28 hours or more Household chores less than 28 hours Household chores for 28 hours or more Household chores less than 43 hours Household chores for 43 hours or more Sudan 64.3 1.5 20,809 78.2 4.0 7,942 78.4 2.3 5,526 Sex Male 60.5 1.1 10,457 76.8 2.2 3,916 70.0 2.0 2,881 Female 68.1 2.0 10,352 79.6 5.9 4,024 87.7 2.5 2,645 Missing * * 0 * * 2 * * 0 State Northern 70.8 1.6 348 82.0 6.1 148 91.0 2.7 137 River Nile 75.0 0.4 606 88.2 1.0 279 83.1 0.0 183 Red Sea 54.1 0.2 470 83.6 0.0 151 66.6 1.4 129 198 Backgound characteristics Percentage of children age 5-11 years involved in: Number of children age 5- 11 years Percentage of children age 12-14 years involved in: Number of children age 12- 14 years Percentage of children age 15-17 years involved in: Number of children age 15- 17 years Household chores less than 28 hours Household chores for 28 hours or more Household chores less than 28 hours Household chores for 28 hours or more Household chores less than 43 hours Household chores for 43 hours or more Kassala 36.6 0.2 850 52.8 0.2 346 59.5 0.3 279 Gadarif 58.8 3.1 1,024 70.4 5.2 484 77.4 5.7 276 Khartoum 72.2 0.0 2,592 85.1 0.0 930 86.1 0.0 818 Gezira 71.5 0.4 3,092 89.1 1.5 1,284 78.7 0.0 877 White Nile 66.0 0.1 1,104 82.4 0.3 359 84.1 2.1 261 Sinnar 74.8 1.1 690 84.9 2.5 306 83.5 3.6 169 Blue Nile 80.5 2.3 928 81.7 7.3 334 92.1 3.5 249 North Kordofan 60.3 2.0 1,404 79.7 1.7 562 73.7 1.0 337 South Kordofan 62.6 4.3 750 86.3 7.9 235 94.1 1.5 151 West Kordofan 54.1 2.1 1,282 76.8 6.9 508 77.9 2.5 356 North Darfur 43.4 1.1 1,806 57.5 4.3 611 59.2 0.0 484 West Darfur 63.9 4.1 827 60.9 9.5 231 71.4 6.4 190 South Darfur 73.4 3.3 1,870 76.5 11.7 660 85.6 11.0 383 Central Darfur 58.0 3.2 422 76.5 6.2 151 68.4 9.2 106 East Darfur 67.0 2.8 744 76.9 9.2 364 83.3 2.6 141 Area Urban 68.3 0.8 5,777 82.4 1.9 2,473 85.4 0.5 1,695 Rural 62.8 1.8 15,032 76.3 5.0 5,469 75.4 3.0 3,831 School attendance Yes 68.6 1.5 14,961 78.3 3.6 6,235 81.7 1.9 3,349 No 53.2 1.7 5,848 78.1 5.8 1,707 73.5 2.8 2,177 melevel Cannot be determined [a] * * 3 * * 8 68.9 3.8 574 Wealth index quintile Poorest 56.7 2.7 4,932 72.5 7.6 1,785 71.1 2.9 1,084 Second 60.0 2.0 4,577 72.9 5.0 1,633 74.0 6.2 1,066 Middle 65.7 1.3 4,563 79.6 4.2 1,450 84.1 1.5 1,120 Fourth 73.7 1.0 3,732 87.7 1.5 1,616 76.4 0.8 1,073 Richest 69.7 0.0 3,006 79.3 1.4 1,459 85.6 0.1 1,184 [a] Children age 15 or higher at the time of the interview whose mothers were not living in the household na: not applicable [*] Based on less than 25 unweighted cases and has been suppressed Table CP.4 combines the children working and performing household chores at or above and below the age-specific thresholds as detailed in the previous tables, as well as those children reported working under hazardous conditions, into the Sudan child labour indicator. The results show that there is discrepancy between those males and females at or above the age specific threshold or below the age specific threshold among all children aged 5-17 with regards to 199 economic activities; with higher percentage of males (17.5 percent) than females (13.2 percent) of those at or above the age specific threshold for household. In the contrary, there is a higher percentage of females (73.9 percent) than males (65.8 percent) among those below the age specific threshold. The MICS results indicates that working in hazardous conditions is higher among the age group 15 – 17 years (28.5 percent) with clear differentials in the proportion of children working under hazardous conditions who live in urban areas (8.1 percent) than those dwelling in rural areas (21.8 percent). State differentials also show that Khartoum state records the lowest percentage of children working under hazardous conditions (5.9 percent), while East Darfur state has the highest percentage of children working under hazardous conditions (40.4 percent). Not surprisingly, working in hazardous conditions seems to be strongly related to the well-being of household, with those higher percentages of children working under hazardous conditions among children whose families are classified among the poorest households (28.3 percent) compared to 6.8 percent of working children from the wealthiest households. Table CP.4: Child labour Percentage of children age 5-17 years by involvement in economic activities or household chores during the last week, percentage working under hazardous conditions during the last week, and percentage engaged in child labour during the last week, Sudan MICS, 2014 Background characteristics Children involved in economic activities for a total number of hours during last week: Children involved in household chores for a total number of hours during last week: Children working under hazardous conditions Total child labour [1] Number of children age 5- 17 years Below the age specific threshold At or above the age specific threshold Below the age specific threshold At or above the age specific threshold Sudan 14.3 15.4 69.8 2.2 17.8 24.9 34,278 Sex Male 15.0 17.5 65.8 1.5 20.7 27.9 17,255 Female 13.6 13.2 73.9 3.0 14.8 21.8 17,021 Missing * * * * * * 2 State Northern 13.6 8.2 77.8 2.9 9.4 15.3 634 River Nile 8.8 5.4 79.8 0.5 9.5 11.2 1,068 Red Sea 8.3 7.5 62.1 0.4 10.9 12.7 750 Kassala 7.9 4.6 44.7 0.2 7.6 9.6 1,475 Gadarif 11.1 17.9 64.8 4.1 15.2 26.7 1,784 Khartoum 7.0 4.0 77.6 0.0 5.9 7.5 4,340 Gezira 11.8 9.9 77.0 0.6 13.5 17.2 5,253 White Nile 12.7 7.8 72.1 0.4 12.4 15.9 1,724 Sinnar 14.7 14.4 78.7 1.8 17.7 25.4 1,166 Blue Nile 16.4 26.9 82.7 3.6 28.7 38.1 1,512 North Kordofan 13.7 14.5 67.0 1.8 16.5 23.4 2,303 South Kordofan 24.6 23.7 71.7 4.7 34.6 41.4 1,135 West Kordofan 18.9 17.4 63.4 3.3 24.7 31.4 2,147 North Darfur 17.7 17.0 49.0 1.6 23.2 29.4 2,902 West Darfur 19.2 21.0 64.5 5.5 17.2 29.8 1,248 200 Background characteristics Children involved in economic activities for a total number of hours during last week: Children involved in household chores for a total number of hours during last week: Children working under hazardous conditions Total child labour [1] Number of children age 5- 17 years Below the age specific threshold At or above the age specific threshold Below the age specific threshold At or above the age specific threshold South Darfur 19.0 35.5 75.7 6.2 25.4 48.2 2,913 Central Darfur 28.3 27.3 63.8 4.8 32.7 45.1 678 East Darfur 23.1 29.1 71.7 4.6 40.4 49.4 1,249 Area Urban 9.8 7.2 74.7 1.0 8.1 13.0 9,945 Rural 16.1 18.7 67.8 2.7 21.8 29.8 24,332 Age 5-11 2.0 21.0 64.3 1.5 12.3 22.2 20,809 12-14 30.1 9.0 78.2 4.0 24.7 28.7 7,942 15-17 38.0 3.2 78.4 2.3 28.5 29.7 5,526 School attendance Yes 12.4 14.5 72.9 2.1 15.7 22.6 24,544 No 19.1 17.5 62.1 2.7 23.1 30.8 9,733 melevel Cannot be determined [a] 34.2 4.5 68.4 3.7 26.6 29.2 585 Wealth index quintile Poorest 19.8 27.1 62.3 3.8 28.3 40.6 7,800 Second 18.7 18.7 64.9 3.3 25.1 32.7 7,276 Middle 12.7 14.5 71.4 1.9 17.1 23.2 7,133 Fourth 8.5 7.2 77.7 1.1 7.3 11.8 6,420 Richest 9.7 5.2 75.5 0.4 6.8 10.2 5,648 [1] MICS indicator 8.2 - Child labour [a] Children age 15 or higher at the time of the interview whose mothers were not living in the household [*] Based on less than 25 unweighted cases and has been suppressed. 11.3 Child Discipline Teaching children self-control and acceptable behavior is an integral part of child discipline in all cultures. Positive parenting practices involve providing guidance on how to handle emotions or conflicts in manners that encourage judgment and responsibility and preserve children's self-esteem, physical and psychological integrity and dignity. Too often however, children are raised through the use of punitive methods that rely on the use of physical force or verbal intimidation to obtain desired behaviors. Studies47 have found that exposing children to violent discipline have harmful consequences, which range from immediate impacts to long-term harm that children carry forward into adult life. Violence hampers children’s development, learning abilities and school performance; 47 Straus, MA and Paschall MJ. 2009. Corporal Punishment by Mothers and Development of Children’s Cognitive Ability: A longitudinal study of two nationally representative age cohorts. Journal of Aggression, Maltreatment & Trauma 18(5): 459- 83. Erickson, MF and Egeland, B. 1987. A Developmental View of the Psychological Consequences of Maltreatment. School Psychology Review 16: 156-68. Schneider, MW et al. 2005. Do Allegations of Emotional Maltreatment Predict Developmental Outcomes Beyond that of Other Forms of Maltreatment?. Child Abuse & Neglect 29(5): 513–32. 201 it inhibits positive relationships, provokes low self-esteem, emotional distress and depression; and, at times, it leads to risk taking and self-harm. In the MICS, respondents to the household questionnaire were asked a series of questions on the methods adults in the household used to discipline a selected child during the past month prior to the survey.46 In MICS Table CP.5, 63.9 percent of children age 1-14 years was subjected to at least one form of psychological or physical punishment by household members during the past month prior to the survey. Generally, households employ a combination of violent disciplinary practices, reflecting caregivers’ motivation to control children’s behaviour by any means possible. While 52.8 percent of children experienced psychological aggression, about 61.3 percent experienced physical punishment. The most severe forms of physical punishment (hitting the child on the head, ears or face or hitting the child hard and repeatedly) are overall less common: 13.6 percent of children were subjected to severe punishment. The survey reveals no variations between male and female children who were subjected to physical discipline: male (61.6 percent) and female children (60.8 percent). Differentials with respect to many of the background variables were relatively small. Children living in rural areas (62.3 percent), while those living urban areas (68.2 percent), while those living in the richest households (71.6 percent) were likely than those living in poor households (54.1 percent) of children to be subjected to any violent discipline method. Overall, 52.8 percent of children in the aged group 1-14 years experienced psychological aggression in the month preceding the survey. River Nile state was reported of having the highest proportion (69.6 percent) and Central Darfur state (12.6 percent) the lowest of the children aged 1-14 years who experienced psychological aggression. Children between 10 - 14 years were slightly more likely to experience non-violent discipline than the other age groups (23.8 percent). 202 F i g u r e C P . 2 a : C h i l d r e n a g e 1 - 1 4 y e a r s e x p e r i e n c i n g a n y v i o l e n t d i s c i p l i n i n g m e t h o d b y s e x , s t a t e a n d u r b a n / r u r a l d i s a g g r e g a t i o n , S u d a n M I C S , 2 0 1 4 64 65 63 78 75 75 74 74 73 69 69 69 68 58 58 57 55 52 47 45 18 68 62 0 10 20 30 40 50 60 70 80 90 Sudan Male Female Sinnar South Darfur River Nile Gezira Northern White Nile Gadarif Khartoum East Darfur Blue Nile Red Sea South Kordofan Kassala West Darfur West Kordofan North Kordofan North Darfur Central Darfur Urban Rural Percent 203 T a b l e C P . 5 : C h i l d d i s c i p l i n e P e r c e n t a g e o f c h i l d r e n a g e 1 - 1 4 y e a r s b y c h i l d d i s c i p l i n i n g m e t h o d s e x p e r i e n c e d d u r i n g t h e l a s t o n e m o n t h , S u d a n M I C S , 2 0 1 4 Background characteristics Percentage of children age 1-14 years who experienced: Number of children age 1-14 years Only non- violent discipline Psychological aggression Physical punishment Any violent discipline method [1] Any Severe Sudan 21.6 52.8 47.7 13.6 63.9 40,814 Sex Male 20.5 53.7 47.9 13.7 64.5 20,494 Female 22.8 52.0 47.4 13.4 63.4 20,318 Missing * * * * * 2 State Northern 22.2 61.0 61.2 8.8 73.5 699 River Nile 21.3 69.6 43.9 4.5 74.6 1,215 Red Sea 19.9 52.1 39.9 7.5 58.2 840 Kassala 27.2 46.1 42.9 14.7 56.7 1,653 Gadarif 21.7 58.3 51.6 13.6 69.4 2,114 Khartoum 19.9 61.8 46.3 11.8 69.3 4,927 Gezira 19.4 66.3 52.4 13.3 74.0 6,472 White Nile 13.0 65.5 51.9 18.9 72.7 2,027 Sinnar 17.8 67.8 66.4 21.2 78.3 1,498 Blue Nile 24.8 56.9 57.0 13.0 68.0 1,831 North Kordofan 7.6 34.1 38.6 12.0 46.9 2,649 South Kordofan 20.6 37.4 50.7 17.2 57.7 1,408 West Kordofan 33.1 39.1 38.6 17.4 52.4 2,555 North Darfur 37.7 28.5 36.5 7.3 44.8 3,535 West Darfur 39.1 36.1 47.6 19.0 54.8 1,449 South Darfur 15.3 61.7 52.7 12.4 75.1 3,617 Central Darfur 13.6 12.6 14.9 4.3 18.2 799 East Darfur 14.4 55.2 56.8 28.2 69.3 1,523 Area Urban 20.3 57.2 50.6 14.7 68.2 11,487 Rural 22.1 51.1 46.5 13.1 62.3 29,327 Age 1-2 years 19.6 42.8 40.8 8.6 54.1 5,611 3-4 years 20.9 54.4 56.1 16.4 68.5 6,452 5-9 years 20.8 54.8 52.5 15.2 67.2 15,522 10-14 years 23.8 54.0 40.8 12.3 62.1 13,229 Education of household head None 22.2 50.0 45.6 14.1 60.6 18,764 Primary 19.8 55.1 50.7 14.3 67.5 12,061 204 Background characteristics Percentage of children age 1-14 years who experienced: Number of children age 1-14 years Only non- violent discipline Psychological aggression Physical punishment Any violent discipline method [1] Any Severe Secondary 22.6 56.6 48.5 12.9 67.1 7,625 Higher 22.7 53.4 47.6 5.9 64.3 2,035 Missing/DK 23.7 44.1 36.6 14.9 51.6 330 Wealth index quintile Poorest 23.7 41.0 41.5 12.9 54.1 9,383 Second 23.5 47.0 45.1 14.8 58.9 8,797 Middle 19.0 56.8 52.3 14.6 68.8 8,438 Fourth 21.9 60.3 52.9 13.9 70.0 7,773 Richest 19.2 63.7 47.7 11.0 71.6 6,423 [1] MICS indicator 8.3 - Violent discipline [*] Based on less than 25 unweighted cases and has been suppressed. F i g u r e C P . 2 : C h i l d d i s c i p l i n i n g m e t h o d s , c h i l d r e n a g e 1 - 1 4 y e a r s , Su d a n M I C S , 2 0 1 4 While violent methods are extremely common forms of discipline, Table CP.6 reveals that only 29.7 percent of respondents believe that physical punishment is a necessary part of child-rearing. There 21 64 51 Other 34 Severe 13 Only non-violent discipline Any violent discipline Psychological aggression Physical punishment Per cent 205 are large differentials across background variables of respondents, with the percentage in rural areas higher (31.8 percent) than those in urban areas (24.6 percent). Overall, respondents with secondary education attainment are more likely to find physical punishment as necessary in disciplining children, with 45.5 percent respectively. The respondent’s relationship to the child also matters: 29.5 percent of mothers believe in the necessity of physical punishment compared to 33.2 percent of fathers and 27.4 percent among other adult household members. Table CP.6: Attitudes toward physical punishment Percentage of respondents to the child discipline module who believe that physical punishment is needed to bring up, raise, or educate a child properly, Sudan MICS, 2014 Background characteristics Respondent believes that a child needs to be physically punished Number of respondents to the child discipline module Sudan 29.7 11,848 Sex Male 33.1 2,232 Female 28.9 9,616 State Northern 30.9 246 River Nile 22.3 406 Red Sea 8.9 299 Kassala 23.0 497 Gadarif 37.9 622 Khartoum 21.7 1,552 Gezira 26.8 1,804 White Nile 16.7 596 Sinnar 45.1 452 Blue Nile 20.6 485 North Kordofan 24.8 763 South Kordofan 40.3 364 West Kordofan 34.0 733 North Darfur 46.1 948 West Darfur 33.3 418 South Darfur 36.9 1,023 Central Darfur 21.2 226 East Darfur 40.7 414 Area Urban 24.6 3,415 Rural 31.8 8,434 Age <25 30.0 1,726 25-39 30.1 6,162 40-59 28.6 3,288 60+ 31.3 672 Missing\DK * 2 206 Background characteristics Respondent believes that a child needs to be physically punished Number of respondents to the child discipline module Respondent's relationship to selected child Mother 29.5 8,088 Father 33.2 1,849 Other 27.4 1,911 Respondent's education None 31.0 9,002 Primary * 18 Secondary 45.5 115 Higher 29.2 1,108 Missing/DK 22.0 1,606 Wealth index quintile Poorest 38.5 2,558 Second 32.6 2,587 Middle 27.9 2,400 Fourth 25.7 2,236 Richest 21.8 2,068 [*] Based on less than 25 unweighted cases and has been suppressed. 11.4 Early Marriage and Polygamy Marriage48 before the age of 18 years is a reality for many young girls. In many parts of the world parents encourage the marriage of their daughters while they are still children in hopes that the marriage will benefit them both financially and socially, while also relieving financial burdens on the family. In actual fact, child marriage is a violation of human rights, compromising the development of girls and often resulting in early pregnancy and social isolation, with little education and poor vocational training reinforcing the gendered nature of poverty.49 The right to 'free and full' consent to a marriage is recognized in the Universal Declaration of Human Rights - with the recognition that consent cannot be 'free and full' when one of the parties involved is not sufficiently mature to make an informed decision about a life partner. Closely related to the issue of child marriage is the age at which girls become sexually active. Women who are married before the age of 18 tend to have more children than those who marry later in life. Pregnancy related deaths are known to be a leading cause of mortality for both married and unmarried girls between the ages of 15 and 19, particularly among the youngest of this cohort. There is evidence to suggest that girls who marry at young ages are more likely to marry older men which puts them at increased risk of HIV infection. The demand for this young wife to reproduce and the power imbalance resulting from the age differential lead to very low condom use among such couples.50 48 All references to marriage in this chapter include marital union as well. 49Bajracharya, A ND Amin, S. 2010.Poverty, marriage timing, and transitions to adulthood in Nepal: A longitudinal analysis using the Nepal living standards survey. Poverty, Gender, and Youth Working Paper No. 19. Population Council. Godha, D et al. 2011. The influence of child marriage on fertility, fertility-control, and maternal health care utilization. MEASURE/Evaluation PRH Project Working paper 11-124. 50Clark, S et al. 2006. Protecting young women from HIV/AIDS: the case againstchild and adolescentmarriage. International Family Planning Perspectives 32(2): 79-88. 207 The percentage of women married before ages of 15 and 18 years are provided in Table CP.7. Among women age 15-49 years, (11.9 percent) were married before age 15 and, among women age 20-49 years, (38.0 percent) were married before age 18. About 21.2 percent of young women age 15-19 years are currently married. This proportion is significantly different between young women in urban areas (11.2 percent) and those in rural areas (26.0 percent). Wide variations between states are also observed; for example in Khartoum state, 12.0 percent, while it is 33 percent in Gadarif state. It is strongly related to the level of education, for example, 27.5 percent for women with primary education compared to only 2.4 percent for those with higher education. The percentage of women in a polygynous union is also provided in Table CP.7. Among all women age 15-49 years who are in union, 21.7 percent are in polygynous unions. Polygynous unions are more common among rural women 23.6 percent compared to 16.9 percent for urban women. Polygynous relationships are more prevalent among older women age 45-49 years 30.8 percent compared to only 7.7 percent among younger women age 15-19 years. The wealth index quintiles in the table show that women in the richest and the fourth quintiles have consistently lower levels of early marriage and polygamy than the first, second and middle wealth quintiles. Raj, A et al. 2009. Prevalence of child marriage and its effect on fertility and fertility-control outcomes of young women in India: a cross-sectional, observational study. The Lancet 373 (9678): 1883–9. 208 Figure CP.3a: Women age 20-49 years who first married or entered a marital union before their 18th birthday, Sudan MICS, 2014 38 19 21 27 30 32 34 37 39 41 44 45 47 47 49 50 55 56 57 29 42 0 10 20 30 40 50 60 70 P er ce nt 209 Table CP.7: Early marriage and polygyny among women Percentage of women age 15-49 years who first married or entered a marital union before their 15th birthday, percentages of women age 20-49 years who first married or entered a marital union before their 15th and 18th birthdays, percentage of women age 15-19 years currently married , and the percentage of women who are in a polygynous marriage or union, Sudan MICS, 2014 Background characteristics Women age 15-49 years Women age 20-49 years Women age 15-19 years Women age 15-49 years Percent married before age 15 [1] Number of women age 15-49 years Percent married before age 15 Percent married before age 18 [2] Number of women age 20-49 years Percent currently married [3] Women age 15-19 years Percent in polygynous marriage/ union [4] Number of women age 15-49 years currently married Sudan 11.9 18,302 13.4 38.0 14,593 21.2 3,709 21.7 11,867 State Northern 5.1 457 6.0 19.0 376 13.6 81 6.4 280 River Nile 6.2 701 6.6 21.0 579 22.3 123 6.0 409 Red Sea 10.0 493 9.8 32.2 420 23.0 74 6.1 323 Kassala 18.6 747 20.0 45.1 600 29.8 147 10.7 506 Gadarif 14.9 879 16.2 49.3 715 33.1 164 19.1 630 Khartoum 6.9 2,821 7.8 26.5 2,239 12.0 583 13.9 1,623 Gezira 8.7 3,176 9.6 29.7 2,495 21.1 681 13.3 1,961 White Nile 9.1 889 10.3 36.9 724 20.8 165 11.9 577 Sinnar 12.3 698 13.6 34.0 574 19.2 124 17.8 450 Blue Nile 16.5 729 19.7 50.1 562 29.9 167 28.3 525 North Kordofan 15.6 1,173 17.5 39.1 924 27.6 249 14.3 743 South Kordofan 18.0 525 20.7 46.7 414 20.1 112 25.5 355 West Kordofan 13.5 965 15.2 40.8 796 19.6 168 33.2 687 North Darfur 12.9 1,317 15.0 47.0 1,052 16.6 265 35.2 913 West Darfur 14.1 555 15.6 43.9 430 20.5 125 52.9 383 South Darfur 17.8 1,363 22.0 55.7 1,056 23.7 307 40.9 933 Central Darfur 16.4 272 19.8 54.6 209 22.5 63 45.3 188 East Darfur 15.3 542 18.0 57.4 428 26.3 114 35.2 378 Area Urban 8.0 6,029 9.2 29.1 4,810 11.2 1219 16.9 3,437 Rural 13.7 12,273 15.5 42.3 9,783 26.0 2491 23.6 8,430 Age 15-19 5.7 3,709 0 21.2 3709 7.7 741 20-24 11.9 3,162 11.9 34.2 3,162 0 12.1 1,737 25-29 14.7 3,359 14.7 40.0 3,359 0 18.1 2,617 30-34 12.4 2,558 12.4 37.9 2,558 0 21.2 2,130 35-39 13.8 2,542 13.8 38.6 2,542 0 30.1 2,160 40-44 13.7 1,633 13.7 37.8 1,633 0 28.2 1,374 45-49 14.6 1,339 14.6 40.9 1,339 0 30.8 1,107 Education None 19.7 5,843 20.2 54.6 5,324 40.5 519 32.4 4,778 Primary 13.9 6,128 16.2 43.5 4,506 27.5 1622 16.4 3,961 Secondary 3.7 4,361 5.1 20.8 2,953 8.8 1409 12.7 2,228 Higher .2 1,965 0.1 3.1 1,805 2.4 160 9.9 895 210 Background characteristics Women age 15-49 years Women age 20-49 years Women age 15-19 years Women age 15-49 years Percent married before age 15 [1] Number of women age 15-49 years Percent married before age 15 Percent married before age 18 [2] Number of women age 20-49 years Percent currently married [3] Women age 15-19 years Percent in polygynous marriage/ union [4] Number of women age 15-49 years currently married Missing/DK * 5 0.0 49.8 5 0 40.8 5 Wealth index quintile Poorest 17.8 3,246 20.6 53.8 2,616 24.5 629 35.5 2,341 Second 17.1 3,380 19.2 50.9 2,660 30.1 720 27.2 2,412 Middle 12.7 3,646 14.1 39.6 2,870 25.5 777 21.1 2,417 Fourth 9.0 3,759 10.3 32.6 3,006 16.9 753 13.3 2,333 Richest 5.0 4,271 5.6 19.2 3,441 10.7 831 11.2 2,364 [1] MICS indicator 8.4 - Marriage before age 15 [2] MICS indicator 8.5 - Marriage before age 18 [3] MICS indicator 8.6 - Young women age 15-19 years currently married or in union [4] MICS indicator 8.7 - Polygyny Tables CP.8 presents the proportion of women who were first married before age 15 and 18 by area and age groups. Examining the percentages married before age 15 and 18 by different age groups allow for trends to be observed in early marriage over time. Data show that 40.9 percent of women age 45-49 years where first married by age 18 compared to 34.2 percent of women age 20-24 years at national level. While it is 14.6 percent and 11.9 percent for women age 45-49 and 20-24 respectivelymarrying before 15. In the rural area the percentages are 44.0 and 40.4 for women age 45-49 and 20-24 respectively marrying before age 18. In urban areas comparable figures are 35.1 and 21.6 percent respectively 211 T a b l e C P . 8 : T r e n d s i n e a r l y m a r r i a g e a m o n g w o m e n P e r c e n t a g e o f w o m e n w h o w e r e f i r s t m a r r i e d o r e n t e r e d i n t o a m a r i t a l u n i o n b e f o r e a g e 1 5 a n d 1 8 , b y a r e a a n d a g e g r o u p s , S u d a n M I C S , 2 0 1 4 Background characteristics Urban Rural All Percent of women married before age 15 Number of women age 15- 49 years Percent of women married before age 18 Number of women age 20-49 years Percent of women married before age 15 Number of women age 15-49 years Percent of women married before age 18 Number of women age 20-49 years Percent of women married before age 15 Number of women age 15-49 years Percent of women married before age 18 Number of women age 20-49 years Sudan 8.0 6,029 29.1 4,810 13.7 12,273 42.3 9,783 11.9 18,302 38.0 14,593 Age group 15-19 3.3 1,219 * 0 6.9 2,491 * 0 5.7 3,709 * 0 20-24 5.5 1,044 21.6 1,044 15.0 2,118 40.4 2,118 11.9 3,162 34.2 3,162 25-29 8.0 1,030 26.8 1,030 17.7 2,329 45.8 2,329 14.7 3,359 40.0 3,359 30-34 9.6 859 31.3 859 13.9 1,698 41.2 1,698 12.4 2,558 37.9 2,558 35-39 11.1 834 33.7 834 15.1 1,707 41.0 1,707 13.8 2,542 38.6 2,542 40-44 11.9 578 31.8 578 14.7 1,055 41.1 1,055 13.7 1,633 37.8 1,633 45-49 12.3 464 35.1 464 15.8 875 44.0 875 14.6 1,339 40.9 1,339 [*] Based on less than 25 unweighted cases and has been suppressed 212 F i g u r e C P . 3 : E a r l y m a r r i a g e b e f o r e a g e s 1 5 a n d 1 8 b y a g e g r o u p o f w o m e n 1 5 - 4 9 ye a r s , S u d a n M I C S , 2 0 1 4 Another component is the spousal age difference with the indicator being the percentage of married women 10 or more years younger than their current spouse. Table CP.9 presents percentage distribution of women currently married age 15-19 and 20-24 years according to the age difference with their husband or partner. The results show that there are some important spousal age differences in Sudan MICS, 2014. Among currently married women age 20-24 years, about (41.8 percent) are married to a man who is older by ten years or more. For currently married women age 15-19 years, the corresponding figure is (39.5 percent). The differences between states for women aged 15-19 varied between 20.2 percent for Central Darfur and 50.6 percent for Khartoum state. The corresponding figures for urban and rural areas are 48.7 percent an 37.7 percent respectively. The percentage of women who are married to men older by 10+ is inversely proportional to the level of education. For example the percentage of the women with higher education are lower than women with less or no education in both age groups 15-19 and 20-24 years. There are no discernible spousal age differences among the women according to the wealth index backgrounds. 6 12 15 12 14 14 15 na 34 40 38 39 38 41 15-19 20-24 25-29 30-34 35-39 40-44 45-49 na: not applicable Age in years Percentage married before age 15 Percentage married before age 18 213 Table CP.9: Spousal age difference Percent distribution of women currently married age 15-19 and 20-24 years according to the age difference with their husband or partner, Sudan MICS, 2014 Background characteristics Percentage of currently married women age 15- 19 years whose husband or partner is: Number of women age 15- 19 years currentl y married/ in union Percentage of currently married women age 20-24 years whose husband or partner is: Number of women age 20- 24 years currentl y married/ in union Younger 0-4 years older 5-9 years older 10+ years older [1] Husban d/ partner's age unknow n Young er 0-4 years older 5-9 years older 10+ years older [2] Husban d / partner' s age unknow n Sudan 0.1 3.3 8.0 7.9 80.7 3,709 0.6 10.5 19.1 23.0 46.8 3,162 State Northern 0.0 2.0 4.7 5.9 87.4 81 0.0 5.6 14.5 20.0 59.9 65 River Nile 0.0 1.5 8.6 10.2 79.7 123 0.0 8.1 11.7 20.5 59.6 131 Red Sea 0.0 6.2 8.8 5.8 79.2 74 0.6 9.0 12.8 19.5 58.2 76 Kassala 0.5 4.0 15.0 8.0 72.4 147 0.5 17.2 15.5 18.0 48.8 125 Gadarif 0.4 4.0 13.0 12.1 70.5 164 0.0 8.4 23.1 32.6 35.9 163 Khartoum 0.0 .4 5.5 6.1 88.0 583 0.0 6.1 13.9 18.2 61.8 470 Gezira 0.0 2.4 8.8 8.8 80.1 681 1.1 6.7 18.2 26.0 48.0 550 White Nile 0.0 3.5 7.6 7.9 80.9 165 1.0 7.3 24.7 23.3 43.6 147 Sinnar 0.0 1.9 7.6 7.1 83.4 124 0.0 10.5 20.7 23.5 45.3 133 Blue Nile 0.0 9.5 11.1 6.9 72.5 167 0.6 14.5 25.8 28.6 30.6 130 North Kordofan 0.3 2.8 8.2 12.7 76.1 249 0.4 12.2 17.4 17.5 52.5 222 South Kordofan 0.0 2.2 5.2 8.8 83.8 112 0.7 13.2 26.8 16.3 42.9 86 West Kordofan 0.0 5.8 6.3 5.9 81.9 168 1.2 18.4 21.1 16.6 42.7 172 North Darfur 0.0 4.0 7.7 3.8 84.4 265 0.5 18.0 26.2 19.6 35.8 214 West Darfur 0.0 1.9 8.1 9.5 80.5 125 0.7 13.3 21.6 31.2 33.1 89 South Darfur 0.0 5.9 6.7 8.5 78.9 307 0.7 13.0 19.4 31.2 35.8 260 Central Darfur 0.5 3.0 10.4 4.1 82.0 63 2.5 11.9 11.8 30.4 43.4 41 East Darfur 1.2 5.7 5.9 7.9 79.3 114 1.1 10.1 24.8 22.2 41.8 88 Area Urban 0.0 1.4 3.4 4.9 90.4 1,219 0.3 5.9 12.5 19.3 62.0 1,044 Rural 0.2 4.2 10.3 9.4 76.0 2,491 0.7 12.8 22.4 24.8 39.3 2,118 Age 15-19 0.1 3.3 8.0 7.9 80.7 3709 * * * * * 0 20-24 0.0 0.0 0.0 0.0 0.0 0 0.6 10.5 19.1 23.0 46.8 3162 Education None 0.2 6.7 15.9 15.0 62.2 519 0.6 18.6 23.5 29.8 27.5 802 Primary 0.2 4.6 10.8 9.3 75.1 1622 0.8 12.2 22.3 25.1 39.5 1040 Secondary 0.0 .8 2.8 4.4 92.0 1409 0.6 5.9 18.2 22.6 52.8 771 Higher 0.0 0.0 0.0 1.7 98.3 160 0.1 2.1 8.0 9.5 80.4 548 Wealth Index quintile Poorest 0.2 5.6 8.8 6.9 78.5 629 1.3 17.8 22.1 22.3 36.5 536 Second 0.1 4.2 12.9 10.8 71.9 720 0.0 14.9 25.4 25.0 34.7 617 Middle 0.2 3.8 7.8 10.8 77.4 777 0.5 10.4 19.7 22.8 46.6 608 Fourth 0.0 2.3 8.3 5.6 83.9 753 1.0 8.1 18.3 26.6 46.0 731 Richest 0.0 1.2 3.2 5.5 90.2 831 0.2 3.5 11.3 17.7 67.2 669 ( ) Figures that are based on 25-49 unweighted cases [*] Based on less than 25 unweighted cases and has been suppressed 214 11.5 Female Genital Mutilation/Cutting Female genital mutilation/cutting (FGM/C) is the partial or total removal of the female external genitalia or other injury to the female genital organs. FGM/C is always traumatic with immediate complications including excruciating pain, shock, urine retention, ulceration of the genitals and injury to adjacent tissue. Other complications include septicaemia, infertility, obstructed labour, and even death. The procedure is generally carried out on girls between the ages of 4 and 14; it is also done to infants, women who are about to be married and, sometimes, to women who are pregnant with their first child or who have just given birth. It is often performed by traditional practitioners, including midwives and barbers, without anaesthesia, using scissors, razor blades, or broken glass. FGM/C is a fundamental violation of human rights. It subjects girls and women to health risks and has life-threatening consequences. Although no international human rights instruments specifically addressed the practice, Article 25 of the Universal Declaration of Human Rights states that “everyone has the right to a standard of living adequate for health and well-being” and has been used to argue that FGM/C violates the right to health and bodily integrity. Furthermore, it could be argued that girls, i.e. children, cannot be said to give informed consent to such a potentially damaging practice as FGM/C. Table CP.10 presents the prevalence of FGM/C among women age 15-49 years and the type of procedure. The table shows that 86.6 percent of women had some form of female genital mutilation. The percentages rises from 76.8 percent for women without formal education to 91.8 percent for women with higher education. The practice appears more common in rural areas, the highest percentage is 97.7 for North Kordofan state and the lowest 45.4 for Central Darfur. Surprisingly the practice is highly prevalent among women in wealthy households with population in the richest and fourth richest quintiles recording 91.6 percent and 90.0 percent respectively. Table CP.10: Female genital mutilation/cutting (FGM/C) among women Percentage of women age 15-49 years by FGM/C status and percent distribution of women who had FGM/C by type of FGM/C, Sudan MICS, 2014 Background characteristics Percentage who had any form of FGM/C [1] Number of women age 15-49 years Percent distribution of women age 15-49 years who had FGM/C: Number of women age 15- 49 years who had FGM/C Had flesh removed Were nicked Were sewn closed Form of FGM/C not determined Sudan Sudan 86.6 18,302 16.3 2.2 77.0 4.5 100.0 15,853 State Northern 97.5 457 2.9 0.4 94.6 2.1 100.0 446 River Nile 96.4 701 11.1 2.2 74.5 12.2 100.0 676 Red Sea 89.0 493 8.8 2.4 86.6 2.2 100.0 439 Kassala 78.7 747 3.7 1.4 86.4 8.4 100.0 587 Gadarif 78.5 879 22.1 0.6 71.3 5.9 100.0 690 Khartoum 87.5 2,821 9.7 9.5 74.6 6.2 100.0 2,469 Gezira 86.9 3,176 5.0 0.7 90.0 4.3 100.0 2,759 White Nile 93.7 889 20.3 0.7 77.2 1.8 100.0 833 Sinnar 84.0 698 4.2 1.6 91.7 2.6 100.0 586 Blue Nile 68.0 729 14.3 0.7 84.1 1.0 100.0 495 North Kordofan 97.7 1,173 24.8 0.2 71.9 3.0 100.0 1,146 South Kordofan 88.8 525 20.8 1.8 68.8 8.7 100.0 467 215 Background characteristics Percentage who had any form of FGM/C [1] Number of women age 15-49 years Percent distribution of women age 15-49 years who had FGM/C: Number of women age 15- 49 years who had FGM/C Had flesh removed Were nicked Were sewn closed Form of FGM/C not determined Sudan West Kordofan 81.0 965 5.1 0.3 91.6 3.1 100.0 781 North Darfur 97.6 1,317 39.8 0.4 58.5 1.2 100.0 1,286 West Darfur 61.2 555 24.7 0.9 60.3 14.2 100.0 339 South Darfur 88.2 1,363 27.7 0.9 68.7 2.7 100.0 1,203 Central Darfur 45.4 272 47.0 0.9 36.7 15.4 100.0 124 East Darfur 97.3 542 44.3 0.0 55.4 0.3 100.0 528 Area Urban 85.5 6,029 12.4 4.7 77.9 5.0 100.0 5,153 Rural 87.2 12,273 18.2 0.9 76.6 4.3 100.0 10,700 Age 15-19 81.7 3,709 18.2 3.9 70.8 7.1 100.0 3,029 20-24 85.7 3,162 16.2 2.7 75.8 5.3 100.0 2,,709 25-29 87.6 3,359 16.4 2.2 77.5 3.9 100.0 2,943 30-34 88.0 2,558 14.4 1.7 80.1 3.7 100.0 2,250 35-39 86.6 2,542 16.5 1.2 79.3 2.9 100.0 2,201 40-44 91.4 1,633 13.6 1.0 81.7 3.7 100.0 1,493 45-49 91.8 1,339 17.9 0.8 78.2 3.0 100.0 1,229 Woman’s education None 76.8 5,843 25.3 1.0 70.1 3.7 100.0 4,487 Primary 90.4 6,128 13.9 1.3 81.2 3.7 100.0 5,541 Secondary 92.1 4,361 11.2 3.9 79.0 5.9 100.0 4,018 Higher 91.8 1,965 12.6 4.2 77.0 6.1 100.0 1,804 Missing/DK * 5 * * * * 100.0 4 Wealth index quintile Poorest 88.0 3,246 34.1 0.5 62.1 3.3 100.0 2,855 Second 81.7 3,380 20.7 1.2 74.8 3.3 100.0 2,761 Middle 80.7 3,646 12.6 1.6 82.1 3.6 100.0 2,944 Fourth 90.0 3,759 7.7 2.8 84.0 5.5 100.0 3,381 Richest 91.6 4,271 10.4 4.0 79.6 6.0 100.0 3,912 [1] MICS indicator 8.10 - Prevalence of FGM/C among women [*] Based on less than 25 unweighted cases and has been suppressed Table CP.11 presents the prevalence and extent of FGM/C performed on all daughters, age 0-14 years, of the respondents. It is important to remember that prevalence data for girls age 0-14 years reflect their current – not final – FGM/C status, since many of them may not have reached the customary age for cutting at the time of the survey .They are reported as being uncut but are still at risk of undergoing the procedure. Overall, 31.5 percent of girls have undergone FGM/C. Daughters whose mothers have no education (33.6 percent) are more likely to be exposed to the practice of FGM/C compared to daughters whose mothers have primary education (32.7 percent), secondary education (28.6 percent) and higher education (15.2 percent). 216 The practice of FGM on young girls is most prevalent in the Red Sea state with 55.6 percent compared to the West Darfur state where only 12.1 percent of the young girls have undergone the practice. The practice is slightly more common in rural areas (33.0 percent) than in urban areas (27.8 percent). The table shows that the prevalence of the FGM is 69.0 percent for girls 10-14 of age compared with 31.5 percent for 5-9 age group and only 4.3 percent among 0-4 age group. 34.6 percent of daughters of women who had experienced FGM have also under gone cutting compared with only 2.3 percent among the daughters of women who had not experienced FGM. The wealth index have no effect on the practice of FGM. Table CP.11: Female genital mutilation/cutting (FGM/C) among girls Percentage of daughters aged 0-14 years by FGM/C status and percent distribution of daughters who had FGM/C by type of FGM/C Sudan MICS, 2014 Background characteristics Percentage of daughters who had any form of FGM/C [1] Number of daughters age 0- 14 years Number of daughters age 0-14 years who had FGM/C Sudan 31.5 17,661 5,570 State Northern 43.1 323 139 River Nile 50.0 508 254 Red Sea 55.6 326 181 Kassala 46.6 674 314 Gadarif 28.9 937 271 Khartoum 29.9 2,205 658 Gezira 31.9 2,790 890 White Nile 43.8 876 384 Sinnar 27.4 652 179 Blue Nile 30.0 762 229 North Kordofan 49.1 1,196 587 South Kordofan 27.3 601 164 West Kordofan 25.6 996 255 North Darfur 27.0 1,645 443 West Darfur 12.1 633 76 South Darfur 21.2 1,609 340 Central Darfur 13.9 230 32 East Darfur 24.8 697 173 Area Urban 27.8 4,844 1,345 Rural 33.0 12,818 4,225 Age 0-4 4.3 6,481 279 5-9 31.5 6,460 2,033 10-14 69.0 4,720 3,258 Mother's education None 33.6 7,943 2,668 Primary 32.7 6,028 1,970 Secondary 28.6 2,763 789 Higher 15.2 919 140 217 Background characteristics Percentage of daughters who had any form of FGM/C [1] Number of daughters age 0- 14 years Number of daughters age 0-14 years who had FGM/C Missing/DK * 8 3 Mother's FGM/C experience No FGM/C 2.3 1,680 39 Had FGM/C 34.6 15,982 5,531 Wealth index quintile Poorest 30.2 4,029 1,216 Second 30.3 3,617 1,094 Middle 31.5 3,684 1,161 Fourth 35.6 3,418 1,217 Richest 30.3 2,913 882 [1] MICS indicator 8.11 - Prevalence of FGM/C among girls [*] Based on less than 25 unweighted cases and has been suppressed Figure CP.3b : Women age 15-49 years and girls 0-14 years who have undergone FGM/C by education of the woman or mother of the child, Sudan MICS, 2014 Table CP.12 presents the women’s attitudes towards FGM/C. In respect of whether the practice should be continued or discontinued, 40.9 percent of the women thought it should be continued while 52.8 percent of them believed it should be discontinued. Women in East Darfur state (64.4 percent) are most likely to support the continuation of the practice of FGM/C than women in other 0 10 20 30 40 50 60 70 80 90 100 None Primary Secondary Higher 77 90 92 92 33.6 32.7 28.6 15.2 P er ce nt Education of woman or mother Women age 15-49 yrs Girls 0-14 years 218 states with women in Khartoum state (24.0 percent) supporting continuation of the the practice the least. The level of education of the woman has significant effect on her attitude towards the practice of FGM; 16.9 percent of the women with higher education approved the continuation of the practice of FGM compared to 55.0 percent of the women with no education. Table CP.12 also shows that women in the poorest households are more likely to support the continuation of the practice with 61.9 percent compared to their counterparts in the richest households (23.3 percent). The continuation of the FGM is supported by 28.0 percent of the urban women compared with 47.4 percent of rural women. Table CP.12: Approval of female genital mutilation/cutting (FGM/C) Percentage of women age 15-49 years who have heard of FGM/C, and percent distribution of women according to attitudes towards whether the practice of FGM/C should be continued, Sudan MICS, 2014 Background characteristics Percentage of women who have heard of FGM/C Number of women aged 15-49 years Percent distribution of women who believe the practice of FGM/C should be: Number of women age 15-49 years who have heard of FGM/C Continued [1] Discontinued Depends Don't know/ Missing Sudan 96.3 18,302 40.9 52.8 2.3 4.0 17,620 State Northern 99.3 457 33.0 64.5 0.4 2.2 454 River Nile 99.1 701 40.8 55.0 1.5 2.8 694 Red Sea 90.6 493 51.8 46.6 0.3 1.3 447 Kassala 96.6 747 53.1 42.0 1.4 3.4 721 Gadarif 93.1 879 39.1 55.6 1.2 4.2 818 Khartoum 98.5 2,821 24.0 71.0 2.7 2.3 2,779 Gezira 97.2 3,176 31.8 55.8 5.7 6.8 3,086 White Nile 98.5 889 43.1 53.4 1.0 2.5 875 Sinnar 96.6 698 33.5 59.2 5.6 1.7 675 Blue Nile 93.7 729 36.3 59.8 0.9 3.0 683 North Kordofan 99.3 1,173 53.1 38.7 1.9 6.2 1,165 South Kordofan 96.3 525 37.6 54.0 2.3 6.1 506 West Kordofan 85.6 965 58.1 35.8 1.8 4.3 826 North Darfur 99.1 1,317 55.7 39.9 0.1 4.3 1,305 West Darfur 96.4 555 37.8 59.4 0.3 2.5 535 South Darfur 97.2 1,363 52.8 43.3 0.9 3.0 1,326 Central Darfur 71.5 272 45.7 48.0 1.1 5.2 194 East Darfur 98.0 542 64.4 30.6 0.4 4.6 531 Area Urban 97.1 6,029 28.0 67.3 2.1 2.6 5,856 Rural 95.8 12,273 47.4 45.5 2.4 4.7 11,764 Age 15-19 96.3 3,709 38.9 53.3 1.7 6.1 3,572 20-24 96.5 3,162 40.9 53.7 2.3 3.1 3,050 25-29 96.2 3,359 43.2 50.4 2.4 3.9 3,232 30-34 96.2 2,558 42.8 50.6 2.8 3.7 2,461 219 Background characteristics Percentage of women who have heard of FGM/C Number of women aged 15-49 years Percent distribution of women who believe the practice of FGM/C should be: Number of women age 15-49 years who have heard of FGM/C Continued [1] Discontinued Depends Don't know/ Missing 35-39 95.4 2,542 40.5 54.1 1.9 3.5 2,424 40-44 96.7 1,633 37.4 56.2 3.3 3.1 1,579 45-49 97.1 1,339 42.5 52.4 2.1 3.0 1,300 Woman's education None 92.3 5,843 55.0 37.3 1.6 6.1 5,394 Primary 96.9 6,128 47.3 46.3 2.3 4.1 5,939 Secondary 99.2 4,361 25.7 69.0 2.8 2.5 4,328 Higher 99.5 1,965 16.9 79.1 3.1 0.9 1,954 Missing/DK * 5 * * * * 5 FGM/C experience No FGM/C 72.1 2,449 8.0 83.0 1.3 7.8 1,767 Had FGM/C 100.0 15,853 44.6 49.4 2.4 3.6 15,853 Wealth index quintile Poorest 95.9 3,246 61.9 32.3 0.7 5.2 3,112 Second 92.6 3,380 54.9 38.8 1.7 4.6 3,130 Middle 95.2 3,646 40.6 52.8 2.1 4.5 3,473 Fourth 97.9 3,759 32.0 60.3 3.6 4.1 3,678 Richest 99.0 4,271 23.3 71.6 2.9 2.1 4,226 ( ) Figures that are based on 25-49 unweighted cases (*) Figures that are based on fewer than 25 unweighted cases 11.6 Attitudes toward Domestic Violence MICS assessed the attitudes of women age 15-49 years towards wife beating by asking the respondents whether they think that husbands are justified to hit or beat their wives in a variety of situations. The purpose of these questions was to capture the social justification of violence (in contexts where women have a lower status in society) as a disciplinary action when a woman does not comply with certain expected gender roles. The responses to these questions are presented in Table CP.13. Overall, 34.0 percent of women in the survey feel that a husband is justified in hitting or beating his wife in at least one of the five situations (If she goes out without telling him, If she neglects the children, If she argues with him, If she refuses sex with him, and If she burns the food). Women who justify a husband’s violence, in most cases agree and justify violence in instances when a wife neglects the children (24.2 percent), or if she demonstrates her autonomy, demonstrated by going out without telling her husband (21.8 percent) or arguing with him (19.5 percent). Nearly one-fifth (18.2 percent) of women believe that wife-beating is justified if the wife refuses to have sex with the husband. Justification in any of the five situations is more common among those living in poorest households, less educated, and also currently married women. Among the states, East Darfur with 77.4 percent of women can justify wife beating reported the highest while River Nile with 9.6 percent reported the lowest. The percentages for the urban and the rural areas are 25.0 percent and 38.4 percent respectively. 220 Table CP.13: Attitudes toward domestic violence among women Percentage of women age 15-49 years who believe a husband is justified in beating his wife in various circumstances, Sudan MICS, 2014 Background characteristics Percentage of women age 15-49 years who believe a husband is justified in beating his wife: Number of women age 15-49 years If she goes out without telling him If she neglects the children If she argues with him If she refuses sex with him If she burns the food For any of these five reasons [1] Sudan 21.8 24.2 19.5 18.2 15.2 34.0 18,302 State Northern 11.7 16.9 11.8 8.7 6.7 25.7 457 River Nile 5.9 6.7 5.5 6.0 5.2 9.6 701 Red Sea 3.2 6.7 4.2 3.3 1.5 10.4 493 Kassala 6.1 8.4 7.8 7.0 3.3 14.1 747 Gadarif 14.7 15.5 14.3 13.3 10.4 22.0 879 Khartoum 9.5 10.8 6.9 4.9 3.2 18.8 2,821 Gezira 9.3 10.9 6.0 5.9 5.0 17.0 3,176 White Nile 18.5 21.3 16.8 15.5 14.6 35.2 889 Sinnar 25.2 23.7 17.7 18.6 14.0 40.0 698 Blue Nile 23.9 24.7 18.7 14.8 14.8 38.8 729 North Kordofan 18.4 21.9 18.8 17.0 15.0 28.9 1,173 South Kordofan 39.0 40.1 36.4 29.6 27.5 58.1 525 West Kordofan 33.6 37.5 31.2 28.5 27.2 50.5 965 North Darfur 46.4 50.6 38.5 41.5 35.6 62.2 1,317 West Darfur 39.9 41.9 37.8 34.7 29.5 57.1 555 South Darfur 47.1 50.9 46.7 43.4 32.7 65.2 1,363 Central Darfur 44.9 44.8 39.6 40.2 33.2 63.4 272 East Darfur 51.3 62.4 55.4 54.7 45.5 77.4 542 Area Urban 13.3 15.4 11.8 11.0 7.2 25.0 6,029 Rural 25.9 28.5 23.3 21.8 19.1 38.4 12,273 Age 15-19 23.0 25.5 20.5 17.1 15.4 35.5 3,709 20-24 21.0 24.9 19.3 18.2 14.8 34.9 3,162 25-29 23.2 25.3 20.6 19.1 15.7 35.5 3,359 30-34 20.9 23.4 17.7 18.5 14.7 32.6 2,558 35-39 20.8 22.7 20.0 19.4 15.6 33.0 2,542 40-44 20.5 22.7 17.7 17.6 15.7 31.5 1,633 45-49 21.5 22.0 19.0 17.0 13.4 32.1 1,339 Marital status Currently married 23.7 25.8 21.3 20.6 16.6 36.2 11,867 Formerly married 22.2 26.0 21.3 20.0 16.6 35.8 887 Never married 17.6 20.5 15.2 12.9 11.9 29.2 5,547 Woman's education None 32.1 33.9 29.8 28.2 24.0 45.6 5,843 Primary 24.2 26.8 20.4 19.0 16.1 36.7 6,128 Secondary 12.0 15.1 11.1 9.7 7.6 23.7 4,361 Higher 5.2 7.2 4.3 4.9 3.0 14.4 1,965 221 Background characteristics Percentage of women age 15-49 years who believe a husband is justified in beating his wife: Number of women age 15-49 years If she goes out without telling him If she neglects the children If she argues with him If she refuses sex with him If she burns the food For any of these five reasons [1] Missing/DK * * * * * * 5 Wealth index quintile Poorest 43.3 47.3 41.0 40.3 35.2 58.3 3,246 Second 32.4 34.5 30.1 26.8 24.0 46.7 3,380 Middle 19.4 21.5 16.7 15.4 12.1 32.9 3,646 Fourth 13.2 14.9 9.6 8.5 6.5 22.7 3,759 Richest 6.5 8.9 5.8 5.6 3.1 16.4 4,271 [1] MICS indicator 8.12 - Attitudes towards domestic violence. [*] Based on less than 25 unweighted cases and has been suppressed (*) Figures that are based on fewer than 25 unweighted cases 11.7 Children’s Living Arrangements The CRC recognizes that “the child, for the full and harmonious development of his or her personality, should grow up in a family environment, in an atmosphere of happiness, love and understanding. Millions of children around the world grow up with or without the care of their parents for several reasons, including due to the premature death of the parents or their migration for work. In most cases, these children are cared for by members of their extended families, while in others, children may be living in households other than their own, as live-in domestic workers for instance. Understanding the children’s living arrangements, including the composition of the households where they live and the relationships with their primary caregivers, is key to design of targeted interventions aimed at promoting child’s care and wellbeing. Table CP.14 presents information on the living arrangements and orphanhood status of children under age 18. As shown on the table 81.8 percent of children aged 0-17 years in Sudan MICS, 2014 live with both their parents, 12.8 percent live with only their mothers, and 1.7 percent live with only their fathers. About two (2.4) percent of the children live with neither of their biological parents while both of them are alive. One in ten (9.4 percent) of the children live with their mothers only while the biological fathers are alive, considerably a significant difference (0.8 percent) of the children living with their fathers when their biological mothers are alive. About 5.3 percent of the children have lost one or both parents with a very small percentage (0.3 percent) have lost both parents. As expected, older children are less likely than younger children to live with both parents and slightly more likely than younger children to have lost one or both parents. Table CP.14 also shows that the percentage of children living with both parents in the richest wealth quintile (80.6 percent) and in the poorest quintile (82.9 percent). About seven (6.9 percent) of children in the poorest households live with only their mothers while their fathers are alive. The corresponding proportion of such children in the richest quintile is 11.6 percent. 222 Table CP.14: Children's living arrangements and orphanhood Percent distribution of children age 0-17 years according to living arrangements, percentage of children age 0-17 years not living with a biological parent and percentage of children who have one or both parents dead, Sudan MICS, 2014 Background characteristics Living with both parents Living with neither biological parent Living with mother only Living with father only Missing information on father/ mother Sudan Living with neither biological parent [1] One or both parents dead [2] Number of children age 0-17 years Only father alive Only mother alive Both alive Both dead Father alive Father dead Mother alive Mother dead Sudan 81.8 0.5 0.3 2.4 0.3 9.4 3.4 0.8 0.9 0.4 100.0 3.4 5.3 50,054 Sex Male 82.6 0.4 0.3 1.9 0.2 9.1 3.4 0.9 0.9 0.3 100.0 2.8 5.3 25,074 Female 81.1 0.5 0.3 3.0 0.3 9.6 3.4 0.7 0.8 0.4 100.0 4.0 5.3 24,979 State Northern 89.5 0.4 0.1 1.2 0.1 4.7 2.0 0.2 1.5 0.3 100.0 1.8 4.1 898 River Nile 88.7 0.3 0.0 1.8 0.1 5.5 2.8 0.4 0.4 0.1 100.0 2.1 3.5 1,495 Red Sea 91.8 0.4 0.5 1.8 0.1 2.1 1.6 0.3 1.1 0.4 100.0 2.8 3.7 1,024 Kassala 87.3 0.8 0.1 1.2 0.4 5.8 2.7 0.1 1.3 0.4 100.0 2.5 5.2 2,060 Gadarif 87.7 0.3 0.2 2.1 0.5 5.2 2.5 0.7 0.4 0.2 100.0 3.2 4.0 2,608 Khartoum 83.3 0.2 0.3 2.0 0.3 8.7 3.7 0.6 0.8 0.2 100.0 2.8 5.4 6,169 Gezira 71.4 0.4 0.2 2.1 0.1 21.0 2.7 0.7 1.3 0.2 100.0 2.7 4.6 7,966 White Nile 81.9 0.6 0.2 1.4 0.1 9.9 3.1 2.0 0.6 0.2 100.0 2.3 4.6 2,479 Sinnar 85.7 0.3 0.2 2.1 0.3 7.0 2.7 0.7 0.8 0.1 100.0 2.9 4.2 1,819 Blue Nile 83.1 0.5 0.3 2.2 0.4 9.0 1.9 1.5 0.6 0.5 100.0 3.4 3.6 2,248 North Kordofan 90.0 0.3 0.2 1.1 0.2 4.8 1.8 0.4 0.4 0.7 100.0 1.8 2.9 3,226 South Kordofan 85.4 0.9 0.4 2.7 0.4 4.8 2.9 1.1 0.6 0.9 100.0 4.3 5.1 1,687 West Kordofan 88.4 0.2 0.1 1.8 0.2 4.4 3.2 0.4 0.5 0.8 100.0 2.3 4.2 3,168 North Darfur 81.1 0.2 0.4 4.4 0.2 5.7 6.1 0.5 1.1 0.3 100.0 5.2 8.1 4,325 West Darfur 66.1 0.7 0.4 3.9 0.7 18.2 5.9 2.4 1.2 0.6 100.0 5.7 9.0 1,770 South Darfur 81.0 1.0 0.7 3.5 0.2 7.4 4.1 0.8 1.2 0.2 100.0 5.4 7.2 4,345 Central Darfur 70.0 1.0 0.7 3.6 0.4 16.9 4.8 1.2 1.0 0.3 100.0 5.8 8.0 969 East Darfur 83.0 0.6 0.6 3.9 0.5 4.7 4.4 1.4 0.5 0.5 100.0 5.6 6.6 1,798 Area 223 Background characteristics Living with both parents Living with neither biological parent Living with mother only Living with father only Missing information on father/ mother Sudan Living with neither biological parent [1] One or both parents dead [2] Number of children age 0-17 years Only father alive Only mother alive Both alive Both dead Father alive Father dead Mother alive Mother dead Urban 81.1 0.4 0.5 2.6 0.3 9.0 3.9 1.0 0.8 0.4 100.0 3.8 5.9 14,169 Rural 82.1 0.5 0.2 2.3 0.2 9.5 3.2 0.7 0.9 0.3 100.0 3.3 5.0 35,885 Age 0-4 85.7 0.2 0.1 1.1 0.1 10.8 1.4 0.4 0.2 0.1 100.0 1.4 1.9 15,050 5-9 82.9 0.4 0.3 2.3 0.1 9.6 2.5 0.8 0.9 0.3 100.0 3.1 4.2 16,071 10-14 79.6 0.7 0.5 3.0 0.3 8.2 5.0 1.0 1.3 0.3 100.0 4.5 7.8 13,447 15-17 73.4 1.0 0.8 4.9 0.9 7.7 7.2 1.2 1.6 1.3 100.0 7.6 11.5 5,486 Wealth index quintile Poorest 82.9 0.7 0.4 3.1 0.3 6.9 4.0 0.6 0.9 0.3 100.0 4.5 6.2 11,305 Second 83.5 0.5 0.3 2.4 0.3 7.2 3.8 0.8 0.8 0.4 100.0 3.6 5.8 10,653 Middle 82.1 0.4 0.3 2.3 0.3 9.9 2.8 0.9 0.8 0.4 100.0 3.2 4.5 10,344 Fourth 79.5 0.4 0.3 2.1 0.2 12.4 3.1 0.9 1.0 0.3 100.0 2.9 4.9 9,584 Richest 80.6 0.2 0.3 2.0 0.2 11.6 3.0 0.9 1.0 0.3 100.0 2.6 4.7 8,168 1 MICS indicator 8.13 - Children’s living arrangements 2 MICS indicator 8.14 - Prevalence of children with one or both parents dead 224 The Sudan MICS, 2014 included a simple measure of one particular aspect of migration related to what is termed children left behind, i.e. for whom one or both parents have moved abroad. While the amount of literature is growing, the long-term effects of the benefits of remittances versus the potential adverse psycho-social effects are not yet conclusive, as there is somewhat conflicting evidence available as to the effects on children. Besides presenting simple prevalence rates, the results presented in Table CP.15 of this survey is supposed to help fill the data gap on the topic of migration. As expected, only 1.8 percent of children aged 0-17 years have one or both parents living abroad. There are notable differences between groups of children by state with Gezira state (6.4 percent) having the highest percentage of children who have at least one parent living abroad compared South Darfur where no children have their parents living abroad; and among children in the richest households (4.3 percent) as compared with the poorest households (0.1 percent). Generally, the data on parents living abroad is very small to allow for detailed analysis such as shown in table CP15. Table CP.15: Children with parents living abroad Percent distribution of children age 0-17 years by residence of parents in another country, Sudan MICS, 2014 Background characteristics Percent distribution of children age 0-17 years: Percentage of children age 0-17 years with at least one parent living abroad [1] Number of children age 0-17 years With at least one parent living abroad: Only mother abroad With at least one parent living abroad: Only father abroad With at least one parent living abroad: Both mother and father abroad With neither parent living abroad Sudan Sudan 0.0 1.7 0.0 98.2 100.0 1.8 50,054 Sex Male 0.0 1.7 0.0 98.3 100.0 1.7 25,074 Female 0.0 1.8 0.0 98.2 100.0 1.8 24,979 Missing * * * * 100.0 * 1 State Northern 0.0 2.9 0.0 97.1 100.0 2.9 898 River Nile 0.0 1.7 0.0 98.3 100.0 1.7 1,495 Red Sea 0.0 0.1 0.0 99.9 100.0 0.1 1,024 Kassala 0.0 1.7 0.0 98.2 100.0 1.8 2,060 Gadarif 0.1 0.6 0.0 99.3 100.0 0.7 2,608 Khartoum 0.0 1.9 0.0 98.1 100.0 1.9 6,169 Gezira 0.0 6.4 0.0 93.6 100.0 6.4 7,966 White Nile 0.1 1.7 0.0 98.2 100.0 1.8 2,479 Sinnar 0.1 1.4 0.0 98.5 100.0 1.5 1,819 Blue Nile 0.0 0.5 0.0 99.5 100.0 0.5 2,248 North Kordofan 0.0 0.4 0.0 99.6 100.0 0.4 3,226 South Kordofan 0.0 0.1 0.0 99.9 100.0 0.1 1,687 West Kordofan 0.0 0.2 0.0 99.8 100.0 0.2 3,168 North Darfur 0.0 0.1 0.0 99.9 100.0 0.1 4,325 West Darfur 0.0 1.3 0.0 98.5 100.0 1.5 1,770 South Darfur 0.0 0.0 0.0 100.0 100.0 0.0 4,345 Central Darfur 0.1 0.5 0.0 99.3 100.0 0.7 969 225 Background characteristics Percent distribution of children age 0-17 years: Percentage of children age 0-17 years with at least one parent living abroad [1] Number of children age 0-17 years With at least one parent living abroad: Only mother abroad With at least one parent living abroad: Only father abroad With at least one parent living abroad: Both mother and father abroad With neither parent living abroad Sudan East Darfur 0.1 0.3 0.1 99.5 100.0 0.5 1,798 Area Urban 0.1 1.2 0.0 98.7 100.0 1.3 14,169 Rural 0.0 2.0 0.0 98.0 100.0 2.0 35,885 Age 0-4 0.0 2.5 0.0 97.4 100.0 2.6 15,050 5-9 0.0 2.0 0.0 98.0 100.0 2.0 16,071 10-14 0.0 1.2 0.0 98.7 100.0 1.3 13,447 15-17 0.1 0.0 0.0 99.9 100.0 0.1 5,486 Wealth index quintile Poorest 0.0 0.1 0.0 99.9 100.0 0.1 11,305 Second 0.0 0.3 0.0 99.6 100.0 0.4 10,653 Middle 0.0 1.7 0.0 98.3 100.0 1.7 10,344 Fourth 0.0 3.3 0.0 96.7 100.0 3.3 9,584 Richest 0.1 4.2 0.0 95.7 100.0 4.3 8,168 [1] MICS indicator 8.15 - Children with at least one parent living abroad [*] Based on less than 25 unweighted cases and has been suppressed 226 XII. HIV/AIDS and Sexual Behaviour 12.1 Knowledge about HIV Transmission and Misconceptions about HIV One of the most important prerequisites for reducing the rate of HIV infection is accurate knowledge of how HIV is transmitted and strategies for preventing transmission. Correct information is the first step towards raising awareness and giving adolescents and young people the tools to protect themselves from infection. Misconceptions about HIV are common and can confuse adolescents and young people and hinder prevention efforts. The UN General Assembly Special Session on HIV/AIDS (UNGASS) called on governments to improve the knowledge and skills of young people to protect themselves from HIV. The indicators to measure this goal as well as the MDG of reducing HIV infections by half include improving the level of knowledge of HIV and its prevention, and changing behaviours to prevent further spread of the disease. HIV module(s) were administered to women and men 15-49 years of age. Please note that the questions in this module often refer to “the AIDS virus”. This terminology is used strictly as a method of data collection to aid respondents, preferred over the correct terminology of “HIV” that is used here in reporting the results, where appropriate. Table HA.1: Knowledge about HIV transmission, misconceptions about HIV, and comprehensive knowledge about HIV transmission among women Percentage of women age 15-49 years who know the main ways of preventing HIV transmission, percentage who know that a healthy looking person can be HIV-positive, percentage who reject common misconceptions, and percentage who have comprehensive knowledge about HIV transmission, Sudan MICS, 2014 Background characteristics Perce nt-age who have heard of AIDS Percentage who know transmission can be prevented by: Percen t-age who know that a health y looking person can be HIV- positiv e Percentage who know that HIV cannot be transmitted by: Percent- age who reject the two most common misconce ptions and know that a healthy looking person can be HIV- positive Percent- age with compreh en-sive knowledg e [1] Number of women age 15-49 Having only one faithful uninfec ted sex partner Using a cond om every time Perce ntage of wome n who know both ways Mosq uito bites Supe r- natur al mea ns Sharing food with someon e with HIV Sudan 74.8 59.7 26.7 24.7 34.6 46.9 56.4 49.5 19.2 8.9 18,302 State Northern 88.9 75.5 42.6 39.6 52.7 60.9 69.3 65.9 32.2 17.0 457 River Nile 85.3 72.8 40.9 38.3 55.8 64.9 72.8 57.3 33.1 17.9 701 Red Sea 69.8 51.9 20.9 18.2 34.6 47.6 48.3 40.6 16.9 6.1 493 Kassala 56.7 36.0 16.7 15.0 19.8 32.8 36.6 36.5 14.1 6.5 747 Gadarif 73.0 59.2 20.0 18.7 32.0 37.8 50.6 43.6 14.9 5.8 879 Khartoum 94.8 84.2 32.5 30.7 67.4 75.3 79.8 67.2 40.3 15.3 2,821 Gezira 71.5 54.4 27.5 26.1 33.4 50.6 55.0 51.4 21.0 11.9 3,176 White Nile 80.1 64.3 25.8 23.9 28.2 41.5 59.2 59.0 12.7 4.6 889 Sinnar 68.3 62.7 32.4 31.3 34.1 40.8 53.9 48.9 18.6 8.5 698 Blue Nile 66.9 54.9 23.0 21.7 22.3 39.7 50.2 41.6 13.0 8.5 729 North Kordofan 69.8 44.8 17.4 15.3 19.2 32.6 50.6 41.9 7.4 2.9 1,173 South 73.1 55.0 28.1 25.1 31.3 38.3 48.6 52.2 16.1 9.5 525 227 Background characteristics Perce nt-age who have heard of AIDS Percentage who know transmission can be prevented by: Percen t-age who know that a health y looking person can be HIV- positiv e Percentage who know that HIV cannot be transmitted by: Percent- age who reject the two most common misconce ptions and know that a healthy looking person can be HIV- positive Percent- age with compreh en-sive knowledg e [1] Number of women age 15-49 Having only one faithful uninfec ted sex partner Using a cond om every time Perce ntage of wome n who know both ways Mosq uito bites Supe r- natur al mea ns Sharing food with someon e with HIV Kordofan West Kordofan 67.3 46.4 31.4 28.1 16.8 33.9 40.7 36.7 6.7 3.6 965 North Darfur 63.1 50.5 18.3 17.4 16.8 29.3 41.9 31.7 6.3 2.8 1,317 West Darfur 78.4 60.5 37.6 33.0 37.0 44.6 58.1 49.3 19.8 14.0 555 South Darfur 75.1 63.5 26.1 22.8 27.6 44.1 59.4 52.7 14.3 5.7 1,363 Central Darfur 48.9 29.8 12.2 10.8 15.6 16.4 27.2 22.7 6.5 2.1 272 East Darfur 71.5 54.9 17.7 15.5 17.0 32.0 49.5 39.9 4.9 2.5 542 Area Urban 90.5 76.9 34.6 32.3 52.0 64.9 73.7 65.9 30.4 13.1 6,029 Rural 67.1 51.2 22.8 21.0 26.1 38.1 47.9 41.5 13.6 6.9 12,273 Age 15-24 [1] 74.2 58.2 25.0 23.0 34.1 49.0 57.6 50.4 19.9 8.5 6,871 15-19 72.1 55.3 22.8 20.8 33.9 49.1 56.8 48.9 19.5 7.7 3,709 20-24 76.6 61.6 27.5 25.5 34.4 48.9 58.6 52.2 20.3 9.5 3,162 25-29 76.4 62.2 29.3 27.2 34.8 45.3 56.0 49.6 18.6 9.4 3,359 30-39 75.0 59.9 26.9 24.6 33.5 44.3 54.9 49.1 17.4 8.3 5,099 40-49 74.4 59.9 27.4 25.9 37.3 48.2 56.6 48.2 21.2 10.5 2,972 Marital status Ever married 73.3 58.1 25.6 23.7 32.0 42.8 53.0 46.6 16.7 8.1 12,754 Never married 78.5 63.3 29.2 27.0 40.7 56.4 64.3 56.2 24.9 10.8 5,547 Missing * * * * * * * * * * 1 Education None 52.2 35.8 12.6 11.0 15.0 22.7 30.5 26.5 5.3 2.1 5,843 Primary 74.8 57.8 24.6 22.5 29.0 41.1 53.9 46.8 13.0 5.5 6,128 Secondary 94.7 80.8 38.3 36.0 52.0 72.1 80.1 71.7 33.3 15.1 4,361 Higher 98.4 89.7 49.5 47.2 72.0 81.0 88.3 77.5 48.3 26.4 1,965 Missing/DK * * * * * * * * * * 5 Wealth index quintile Poorest 56.3 39.9 15.4 13.1 15.0 23.8 34.8 28.0 4.8 2.0 3,246 Second 62.3 44.5 17.9 16.1 17.9 29.6 40.7 34.3 7.3 3.0 3,380 Middle 69.4 54.5 21.1 19.5 27.3 39.2 49.8 44.4 12.6 4.8 3,646 Fourth 83.4 67.3 30.5 28.6 40.7 54.7 65.0 60.2 23.5 11.2 3,759 Richest 96.0 84.4 43.7 41.3 63.6 77.8 83.2 72.9 41.2 20.4 4,271 228 One indicator which is both an MDG and the Global AIDS Response Progress Reporting (GARPR; formerly UNGASS) indicator is the percentage of young people who have comprehensive and correct knowledge of HIV prevention and transmission. This is defined as 1) knowing that consistent use of a condom during sexual intercourse and having just one uninfected faithful partner can reduce the chance of getting HIV, 2) knowing that a healthy-looking person can have HIV, and 3) rejecting the two most common local misconceptions about transmission/prevention of HIV. In the Sudan MICS 2014, all women who have heard of AIDS were asked questions on all three components and the results are detailed in Tables HA.1 above. In Sudan, about three-quarters (74.8 percent) of the women age 15-49 years have heard of HIV and AIDS. However, the percentage of those who know of both main ways of preventing HIV transmission – having only one faithful uninfected partner and using a condom every time – is only about one in ten (24.7percent). About sixty (59.7 percent) of the women know of having one faithful uninfected sex partner and 26.7 percent know of using a condom every time as main ways of preventing HIV transmission. Table HA.1 also presents the percentage of women who can correctly identify misconceptions concerning HIV. The indicator is based on the two most common and relevant misconceptions in the survey, that HIV can be transmitted by sharing food with someone with HIV (49.5 percent) and by mosquito bites (46.9 percent). The table also provide information on whether women know that HIV cannot be transmitted by supernatural means (56.4 percent). Overall, 19.2 percent of the respondents reject the two most common misconceptions and know that a healthy-looking person can be HIV- positive. People who have comprehensive knowledge about HIV prevention include those who know of the two main ways of HIV prevention (having only one faithful uninfected partner and using a condom every time), who know that a healthy looking person can be HIV-positive, and who reject the two most common misconceptions. Comprehensive knowledge of HIV prevention methods and transmission is fairly low although there are differences by area; 6.9 percent and 13.1 percent in rural and urban areas respectively. Comprehensive knowledge about HIV transmission greatly varies with women’s education (26.4 percent) in women with higher level of education compared to women with no education (2.1 percent) and with wealth index level of the household; (20.4 percent) in the richest quintile compared with (2.0 percent) in the poorest quintile of the households. 229 F i g u r e H A. 1 : W o m e n a g e d 1 5 - 4 9 y e a r s w h o h a v e c o m p r e h e n s i v e k n o w l e d g e o f H I V t r a n s m i s s i o n , Su d a n M I C S , 2 0 1 4 Knowledge of mother-to-child transmission of HIV is also an important first step for women to seek HIV testing when they are pregnant to avoid infection in the baby. Women should know that HIV can be transmitted during pregnancy, during delivery, and through breastfeeding. The level of knowledge among women age 15-49 years concerning mother-to-child transmission is presented in Table HA.2. Overall, 57.0 percent of women know that HIV can be transmitted from mother to child. The percentage of women who know all three ways of mother-to-child transmission is 28.4 percent, while 17.8 percent of women did not know of any specific way. The percentage of women who know all three ways that mother-to-child transmission can take place ranges from 17.8 percent in the Kassala State to 38.7 percent in River Nile State. Increasing levels of this indicator are associated with urban residence, never-married status and higher levels of women’s education (secondary and above) and household wealth. 32 30 13 21 14 7 Knows 2 ways to prevent HIV Identify 2 most common misconceptions and know that a healthy looking person can be HIV- positive Comprehensive knowledge PercentUrban Rural 230 Table HA.2: Knowledge of mother-to-child HIV transmission among women Percentage of women age 15-49 years who correctly identify means of HIV transmission from mother to child, Sudan MICS, 2014 Background characteristics Percentage of women age 15-49 who have heard of AIDS and: Number of women age 15-49 Know HIV can be transmitted from mother to child: Do not know any of the specific means of HIV transmission from mother to child During pregnancy During delivery By breast- feeding By at least one of the three means By all three means [1] Sudan 46.7 47.0 36.9 57.0 28.4 17.8 18,302 State Northern 63.7 51.1 52.3 73.6 33.8 15.2 457 River Nile 55.9 58.7 46.0 67.3 38.7 18.0 701 Red Sea 41.4 43.5 27.7 51.9 22.2 17.9 493 Kassala 29.0 25.8 23.8 36.3 17.8 20.3 747 Gadarif 41.9 43.2 35.7 49.6 30.2 23.4 879 Khartoum 69.8 70.3 42.6 82.3 35.3 12.5 2,821 Gezira 46.0 46.6 28.4 55.2 23.2 16.3 3,176 White Nile 54.4 49.4 47.2 65.4 34.0 14.7 889 Sinnar 41.1 40.6 33.7 53.9 22.5 14.4 698 Blue Nile 38.5 41.9 32.7 50.7 22.6 16.2 729 North Kordofan 46.0 45.6 42.1 51.5 35.7 18.3 1,173 South Kordofan 48.0 47.2 48.1 56.5 37.8 16.5 525 West Kordofan 31.6 38.1 35.8 46.0 25.2 21.4 965 North Darfur 33.4 31.4 32.6 41.3 22.4 21.8 1,317 West Darfur 40.5 44.3 40.9 56.6 29.0 21.9 555 South Darfur 38.9 41.9 37.9 50.9 26.7 24.2 1,363 Central Darfur 30.1 29.1 27.6 33.4 23.6 15.5 272 East Darfur 40.2 38.6 42.3 51.1 28.9 20.4 542 Area Urban 62.8 62.1 45.2 75.5 35.7 15.1 6,029 Rural 38.8 39.5 32.8 48.0 24.8 19.2 12,273 Age 15-24 [1] 45.7 45.7 38.2 56.9 28.0 17.2 6,871 15-19 45.3 44.3 38.5 56.5 27.5 15.6 3,709 20-24 46.3 47.4 37.7 57.4 28.6 19.1 3,162 25-29 46.0 46.6 36.5 56.3 27.8 20.1 3,359 30-39 46.5 47.4 35.8 56.9 28.2 18.1 5,099 40-49 49.9 49.4 36.5 58.2 30.2 16.1 2,972 Marital status Ever married 44.7 45.0 35.4 54.3 27.6 19.0 12,754 Never married 51.3 51.5 40.4 63.3 30.2 15.2 5,547 Missing * * * * * * 1 Education None 25.1 25.6 23.7 31.4 18.0 20.8 5,843 Primary 45.9 46.0 40.0 56.2 30.9 18.5 6,128 231 Background characteristics Percentage of women age 15-49 who have heard of AIDS and: Number of women age 15-49 Know HIV can be transmitted from mother to child: Do not know any of the specific means of HIV transmission from mother to child During pregnancy During delivery By breast- feeding By at least one of the three means By all three means [1] Secondary 65.1 64.2 47.3 78.5 36.5 16.2 4,361 Higher 72.5 75.0 43.3 88.2 33.5 10.2 1,965 Missing/DK * * * * * * 5 Wealth index quintile Poorest 26.2 28.0 28.6 34.8 20.0 21.5 3,246 Second 33.1 33.4 31.9 41.5 24.0 20.9 3,380 Middle 42.1 42.7 36.9 50.9 29.3 18.5 3,646 Fourth 55.1 53.9 41.0 65.8 32.5 17.6 3,759 Richest 69.5 69.6 43.6 83.8 33.7 12.2 4,271 [1] MICS indicator 9.2 - Knowledge of mother-to-child transmission of HIV [*] Based on less than 25 unweighted cases and has been suppressed 12.2 Accepting Attitudes toward People Living with HIV The indicators on attitudes toward people living with HIV measure stigma and discrimination in the community. Stigma and discrimination are considered low if respondents report an accepting attitude on the following four questions: 1) would care for a family member with AIDS in own home; 2) would buy fresh vegetables from a vendor who is HIV-positive; 3) thinks that a female teacher who is HIV-positive should be allowed to teach in school; and 4) would not want to keep it a secret if a family member is HIV-positive. Table HA.3: Accepting attitudes toward people living with HIV among women Percentage of women age 15-49 years who have heard of AIDS who express an accepting attitude towards people living with HIV, Sudan MICS, 2014 Percent of women who: Number of women who have heard of AIDS Are willing to care for a family member with AIDS in own home Would buy fresh vegetables from a shopkeeper or vendor who is HIV- positive Believe that a female teacher who is HIV- positive and is not sick should be allowed to continue teaching Would not want to keep secret that a family member is HIV- positive Agree with at least one accepting attitude Express accepting attitudes on all four indicators [1] Sudan 85.9 29.2 44.1 40.2 93.9 7.9 13,698 State Northern 95.7 24.3 46.7 43.9 97.9 9.4 406 River Nile 94.2 36.2 53.0 37.3 97.3 13.8 598 Red Sea 83.6 38.4 46.9 47.6 87.9 16.9 344 Kassala 74.6 30.4 40.7 26.5 77.1 8.3 423 Gadarif 79.1 27.1 42.1 41.1 96.0 6.4 642 Khartoum 88.9 33.3 53.0 31.3 95.5 7.1 2,674 Gezira 94.3 31.0 48.8 37.6 97.0 7.7 2,271 White Nile 96.7 30.4 43.6 45.7 99.2 7.7 712 232 Percent of women who: Number of women who have heard of AIDS Are willing to care for a family member with AIDS in own home Would buy fresh vegetables from a shopkeeper or vendor who is HIV- positive Believe that a female teacher who is HIV- positive and is not sick should be allowed to continue teaching Would not want to keep secret that a family member is HIV- positive Agree with at least one accepting attitude Express accepting attitudes on all four indicators [1] Sinnar 96.0 33.3 45.3 32.8 99.2 8.9 477 Blue Nile 89.2 23.9 40.0 39.1 96.1 5.3 488 North Kordofan 70.4 20.9 33.2 47.3 87.2 5.6 819 South Kordofan 82.2 25.1 39.1 50.4 93.1 8.1 384 West Kordofan 62.4 21.0 25.6 59.2 87.4 5.4 649 North Darfur 78.9 20.6 34.8 36.0 86.0 6.0 831 West Darfur 80.7 40.2 51.0 23.4 92.5 2.5 435 South Darfur 85.0 26.1 39.3 57.7 95.9 11.9 1,024 Central Darfur 68.6 13.4 20.9 52.8 89.5 2.3 133 East Darfur 88.2 31.9 40.1 46.9 97.1 10.1 388 Area Urban 89.5 34.7 51.9 38.2 95.9 9.4 5,457 Rural 83.6 25.5 39.0 41.6 92.6 6.9 8,240 Age 15-24 [1] 86.6 30.2 47.0 40.4 94.2 8.7 5,095 15-19 86.6 29.8 46.4 40.8 94.4 8.9 2,674 20-24 86.7 30.7 47.6 40.1 94.0 8.5 2,421 25-29 83.4 29.5 42.6 41.9 93.5 8.9 2,567 30-39 85.6 27.5 41.7 40.3 93.6 6.6 3,825 40-49 87.8 29.0 43.5 37.6 94.2 6.9 2,211 Marital status Ever married 84.5 27.6 40.7 40.8 93.1 7.3 9,344 Never married 89.0 32.5 51.4 38.9 95.6 9.0 4,354 Education None 74.9 18.3 26.6 40.7 87.6 4.1 3,050 Primary 84.0 25.3 38.0 41.4 92.7 6.7 4,582 Secondary 91.8 35.0 54.9 41.1 97.5 10.5 4,128 Higher 95.3 42.8 63.4 34.9 99.1 11.1 1,933 Missing/DK * * * * * * 4 Wealth index quintile Poorest 72.6 17.6 26.8 45.7 86.9 5.1 1,828 Second 76.0 22.1 30.8 43.1 88.6 5.1 2,107 Middle 84.5 26.8 39.1 43.8 94.4 7.6 2,529 Fourth 90.5 31.7 49.4 38.9 95.9 8.9 3,136 Richest 94.3 37.5 57.8 35.2 97.9 9.9 4,099 [1] MICS indicator 9.3 - Accepting attitudes towards people living with HIV [*] Based on less than 25 unweighted cases and has been suppressed 233 Table HA.3 presents the attitudes of women towards people living with HIV. Interestingly, 93.9 percent of women who have heard of AIDS agree with at least one accepting statement in Sudan. The most common accepting attitude is willing to care for a family member with AIDS in own home (85.9 percent). However, only 29.2 percent of the women would buy fresh vegetables from a shopkeeper or vendor who is HIV-positive. Higher educated individuals (99.1 percent) and those from richest households (97.9 percent) have more accepting attitudes (i.e., agree with at least one accepting attitude) than the ones with no education (87.6 percent) and poorest households (86.9 percent). Figure HA.2: Accepting attitudes toward people living with HIV/AIDS in Sudan MICS, 2014 12.3 Knowledge of a Place for HIV Testing, Counselling and Testing during Antenatal Care Another important indicator is the knowledge of where to be tested for HIV and use of such services. In order to protect themselves and to prevent infecting others, it is important for individuals to know their HIV status. Knowledge of own status is also a critical factor in the decision to seek treatment. Questions related to knowledge of a facility for HIV testing and whether a person has ever been tested are presented in Tables HA.4. Would buy fresh vegetables from a shopkeeper or vendor who is HIV-positive Would not want to keep secret if a family member is HIV- positive Are willing to care for a family member with AIDS in own home Believe that a female teacher who is HIV- positive and is not sick should be allowed to continue teaching 0.0 10.0 20.0 30.0 40.0 50.0 60.0 70.0 80.0 90.0 100.0 15-19 25-29 40-49 15-19 25-29 40-49 15-19 25-29 40-49 15-19 25-29 40-49 Pe rc en t Age 234 Table HA.4: Knowledge of a place for HIV testing among women Percentage of women age 15-49 years who know where to get an HIV test, percentage who have ever been tested, percentage who have ever been tested and know the result of the most recent test, percentage who have been tested in the last 12 months, and percentage who have been tested in the last 12 months and know the result, Sudan MICS, 2014 Background characteristics Percent of women who: Number of women age 15-49 Know a place to get tested [1] Have ever been tested Have ever been tested and know the result of the most recent test Have been tested in the last 12 months Have been tested in the last 12 months and know the result [2, 3] Sudan 17.0 5.2 4.3 1.9 1.6 18,302 State Northern 19.2 4.1 3.2 1.8 1.3 457 River Nile 18.1 6.7 6.0 2.7 2.3 701 Red Sea 24.9 6.7 5.4 2.5 2.3 493 Kassala 9.0 3.6 2.6 1.4 1.2 747 Gadarif 14.2 3.7 3.0 1.1 0.8 879 Khartoum 35.3 10.5 9.2 2.6 2.3 2,821 Gezira 7.1 1.2 1.0 0.7 0.5 3,176 White Nile 12.6 4.7 4.0 1.7 1.5 889 Sinnar 21.8 6.2 5.0 2.0 1.9 698 Blue Nile 26.0 5.8 4.1 2.3 1.6 729 North Kordofan 14.9 5.3 4.4 1.9 1.8 1,173 South Kordofan 21.1 6.8 4.6 3.2 2.2 525 West Kordofan 9.3 2.8 1.8 0.7 0.4 965 North Darfur 9.6 3.3 2.5 1.7 1.3 1,317 West Darfur 25.7 14.2 11.9 8.2 7.2 555 South Darfur 13.3 4.6 3.6 1.6 1.3 1,363 Central Darfur 13.5 5.1 4.0 2.6 2.4 272 East Darfur 9.9 2.4 2.2 0.7 0.7 542 Area Urban 31.2 10.4 8.8 3.6 3.2 6,029 Rural 10.1 2.7 2.1 1.1 0.8 12,273 Age 15-24 [1] 15.2 3.3 2.7 1.4 1.2 6,871 15-19 13.0 2.1 1.5 0.9 0.6 3,709 20-24 17.8 4.8 4.1 2.0 1.8 3,162 25-29 17.4 7.3 5.9 3.1 2.6 3,359 30-39 18.9 6.7 5.6 2.2 1.9 5,099 40-49 17.7 4.8 3.8 1.1 0.9 2,972 Marital status Ever married 16.4 6.1 5.1 2.1 1.8 12,754 Never married 18.5 3.3 2.5 1.4 1.2 5,547 Missing * * * * * 1 Education None 6.0 2.1 1.6 1.0 0.8 5,843 Primary 13.8 4.6 3.8 1.8 1.6 6,128 Secondary 25.3 7.7 6.5 2.5 2.1 4,361 Higher 41.6 11.1 9.0 3.5 2.9 1,965 235 Background characteristics Percent of women who: Number of women age 15-49 Know a place to get tested [1] Have ever been tested Have ever been tested and know the result of the most recent test Have been tested in the last 12 months Have been tested in the last 12 months and know the result [2, 3] Missing/DK * * * * * 5 Wealth index quintile Poorest 5.4 1.4 .9 0.6 0.3 3,246 Second 9.2 2.9 2.4 1.4 1.3 3,380 Middle 14.5 5.4 4.4 2.3 1.9 3,646 Fourth 20.6 6.5 5.5 2.6 2.2 3,759 Richest 31.2 8.7 7.2 2.4 2.1 4,271 [1] MICS indicator 9.4 - Women who know where to be tested for HIV [2] MICS indicator 9.5 - Women who have been tested for HIV and know the results [3] MICS indicator 9.6 - Sexually active young women who have been tested for HIV and know the results [*] Based on less than 25 unweighted cases and has been suppressed Seventeen percent of women know a place where to be tested, while 5.2 percent, have actually been tested, fewer, 4.3 percent of the women, know the result of their most recent test. A very small proportion has been tested within the last 12 months prior to the survey (1.9 percent), while a somewhat smaller proportion has been tested within the last 12 months and know the result (1.6 percent). Knowledge of a place to be tested is higher among women from wealthier households, fourth quintile (20.6 percent) and richest quintile (31.2 percent); among women with secondary (25.3 percent) and higher education (41.6 percent) levels; among women resident in urban areas (31.2 percent) than among women who live in rural areas (10.1 percent); and among women in Khartoum (35.3 percent), Blue Nile (26.0 percent), West Darfur ( 25.7 percent), Red Sea (24.9 percent), Sinnar (21.8 percent), and South Kordofan (21.1 percent) states. Table HA.5 presents the percentage distribution of women who had given birth within the two years preceding the survey and who received counselling and HIV testing during antenatal care. About sixty (59.9 percent) received antenatal care from a health professional but only 4.2 percent received HIV counselling during antenatal care while 3.6 percent were offered an HIV test and were tested for HIV during antenatal care and received the results. The percentage of women who were offered an HIV test and were tested for HIV during antenatal care and received the results is much higher in the West Darfur state (12.8 percent) than in the next highest state (7.6 percent in Khartoum). Higher levels of this indicator are associated with urban residence (9.2 percent) and higher levels of women’s education (9.0 percent). 236 Table HA.5: HIV counselling and testing during antenatal care Percentage of women age 15-49 with a live birth in the last 2 years who received antenatal care from a health professional during the last pregnancy, percentage who received HIV counselling, percentage who were offered and tested for HIV, percentage who were offered, tested and received the results of the HIV test, and percentage who received counselling and were offered, accepted and received the results of the HIV test, Sudan MICS, 2014 Background characteristics Percentage of women who: Number of women age 15-49 with a live birth in the last 2 years Received antenatal care from a health care professional for last pregnancy Received HIV counselling during antenatal care [1] Were offered an HIV test and were tested for HIV during antenatal care Were offered an HIV test and were tested for HIV during antenatal care, and received the results [2] Received HIV counselling, were offered an HIV test, accepted and received the results Sudan 59.9 4.2 4.1 3.6 2.6 5,622 State Northern 94.7 0.4 0.7 0.7 0.4 92 River Nile 90.0 5.2 3.5 3.5 3.2 151 Red Sea 67.3 7.5 6.6 5.9 4.3 92 Kassala 65.6 4.2 4.0 4.0 3.6 199 Gadarif 63.9 2.6 2.5 2.5 1.9 307 Khartoum 90.8 8.4 9.5 7.6 4.7 684 Gezira 78.3 0.3 0.9 0.9 0.3 852 White Nile 71.3 2.1 2.8 2.8 1.6 273 Sinnar 64.4 1.5 1.0 0.8 0.6 226 Blue Nile 48.4 3.6 4.1 3.3 2.8 287 North Kordofan 68.8 7.1 7.4 6.9 5.2 352 South Kordofan 47.4 9.8 7.1 5.5 3.6 194 West Kordofan 44.0 2.1 0.7 0.7 0.7 341 North Darfur 43.5 3.1 3.2 2.5 2.2 525 West Darfur 18.8 13.7 13.8 12.8 10.8 179 South Darfur 29.9 5.1 2.9 2.7 2.0 556 Central Darfur 17.9 4.0 4.9 4.1 2.8 99 East Darfur 26.1 0.8 0.7 0.7 0.5 211 Area Urban 75.7 10.4 10.5 9.2 6.5 1,488 Rural 54.2 2.0 1.8 1.5 1.1 4,134 Age 15-24 [1] 61.7 2.8 3.4 3.2 2.1 1,515 15-19 62.0 1.3 1.9 1.7 0.7 385 20-24 61.6 3.3 3.9 3.8 2.6 1,130 25-29 61.2 4.6 4.7 3.9 2.8 1,608 30-39 59.0 4.9 4.1 3.7 2.9 2,108 40-49 51.9 4.7 3.7 2.7 1.8 390 Marital status Ever married/union 59.9 4.2 4.1 3.6 2.6 5,620 Missing 100.0 0.0 0.0 0.0 0.0 1 Education None 39.9 1.8 1.7 1.4 1.1 2,247 Primary 64.5 3.9 3.3 3.0 2.5 2,022 Secondary 82.6 8.7 8.5 7.6 5.5 942 237 Background characteristics Percentage of women who: Number of women age 15-49 with a live birth in the last 2 years Received antenatal care from a health care professional for last pregnancy Received HIV counselling during antenatal care [1] Were offered an HIV test and were tested for HIV during antenatal care Were offered an HIV test and were tested for HIV during antenatal care, and received the results [2] Received HIV counselling, were offered an HIV test, accepted and received the results Higher 94.4 8.9 10.5 9.0 4.3 410 Wealth index quintile Poorest 31.0 1.3 0.9 0.6 0.6 1,251 Second 46.1 2.7 2.0 1.7 1.1 1,232 Middle 60.1 4.7 5.3 4.7 3.6 1,192 Fourth 82.7 6.3 6.2 5.4 4.4 1,096 Richest 92.6 7.3 7.3 6.6 3.8 851 [1] MICS indicator 9.7 - HIV counselling during antenatal care [2] MICS indicator 9.8 - HIV testing during antenatal care [*] Based on less than 25 unweighted cases and has been suppressed 12.4 HIV Indicators for Young Women In many countries, over half of new adult HIV infections are among young people age 15-24 years thus a change in behaviour among members of this age group is especially important to reduce new infections. The next tables present specific information on this age group. Table HA.7 summarizes information on key HIV indicators for young women. Results with respect to comprehensive knowledge (8.5 percent of young women), knowledge of mother to child transmission (28.0 percent of young women), and knowledge of a place to get tested (15.2 percent of young women) are generally worse in this age group than the population age 15-49 years as a whole. Accepting attitudes towards people living with HIV with respect to the same four indicators that were previously discussed are fairly similar in this age group (8.7 percent of young women compared to 7.9 percent in the general population of women 15-49 years). Overall, 2.7 percent of young women in this age group, who are sexually active, have been tested for HIV in the last 12 months and know the result. Higher levels on this indicator are found among young women who are from the top two wealth quintile households (3.4 and 3.9 percent respectively);;; secondary and higher levels of education (4.1 percent and 4.9 percent respectively); women ever married (3.6 percent); and in West Darfur (10.9 percent), River Nile (6.7 percent), Sinnar (5.4 percent), Northern (5.0 percent), and South Kordofan (4.0 percent) 238 Table HA.7: Key HIV and AIDS indicators among young women Percentage of women age 15-24 years by key HIV and AIDS indicators, Sudan MICS, 2014 Background characteristics Percentage of women age 15-24 years who: Number of women age 15- 24 years Percentage who express accepting attitudes towards people living with HIV on all four indicators [a] Number of women age 15- 24 years who have heard of AIDS Have comprehensive knowledge [1] Know all three means of HIV transmission from mother to child Know a place to get tested for HIV Have been tested for HIV in the last 12 months and know the result Have been tested in the last 12 months and know the result Sudan 8.5 28.0 15.2 2.7 1.2 6,871 8.7 5,095 State Northern 14.7 32.1 18.3 5.0 3.5 146 10.1 129 River Nile 16.7 44.8 17.7 6.7 2.9 253 14.3 219 Red Sea 5.3 20.2 25.3 2.1 1.5 150 21.6 113 Kassala 6.9 17.8 3.8 1.1 0.6 272 10.6 157 Gadarif 5.7 31.0 12.3 1.9 0.8 327 6.2 243 Khartoum 15.6 31.2 27.7 3.0 0.4 1,053 7.5 986 Gezira 9.4 21.0 7.0 0.9 0.4 1,231 7.0 837 White Nile 3.6 33.4 10.8 1.6 1.3 312 10.3 247 Sinnar 9.6 21.9 24.4 5.4 2.4 257 11.2 180 Blue Nile 9.0 24.2 25.4 1.9 0.6 297 7.3 201 North Kordofan 2.2 36.8 14.5 3.2 2.1 471 6.1 314 South Kordofan 9.9 35.8 22.6 4.0 1.9 197 7.3 143 West Kordofan 4.4 25.7 6.7 0.6 0.0 341 5.3 219 North Darfur 3.5 26.2 8.7 2.4 1.2 479 8.7 314 West Darfur 15.9 30.0 26.9 10.9 6.3 214 3.6 179 South Darfur 5.5 27.3 11.6 2.4 0.5 567 14.0 416 Central Darfur 2.5 26.3 16.4 2.7 2.6 104 2.0 53 East Darfur 1.4 29.4 10.0 2.3 0.5 201 11.2 145 Area Urban 12.3 35.3 26.1 4.6 2.0 2,262 10.3 2,041 Rural 6.6 24.4 9.9 1.7 0.8 4,609 7.7 3,054 Age 15-19 7.7 27.5 13.0 1.5 0.6 3,709 8.9 2,674 15-17 6.7 26.9 12.1 1.4 0.6 2,152 9.3 1,524 18-19 9.1 28.3 14.3 1.5 0.6 1,558 8.5 1,150 20-24 9.5 28.6 17.8 4.1 1.8 3,162 8.5 2,421 20-22 8.2 29.3 16.5 3.4 1.5 2,175 8.5 1,641 23-24 12.3 26.9 20.8 5.7 2.5 987 8.4 780 Marital status Ever married 7.1 25.0 12.7 3.6 1.6 2,636 7.4 1,829 Never married 9.4 29.8 16.8 2.1 0.9 4,236 9.5 3,266 Education None 1.6 13.0 4.0 0.9 0.3 1,321 5.8 559 Primary 4.7 26.5 11.0 1.8 0.8 2,662 5.6 1,799 239 Background characteristics Percentage of women age 15-24 years who: Number of women age 15- 24 years Percentage who express accepting attitudes towards people living with HIV on all four indicators [a] Number of women age 15- 24 years who have heard of AIDS Have comprehensive knowledge [1] Know all three means of HIV transmission from mother to child Know a place to get tested for HIV Have been tested for HIV in the last 12 months and know the result Have been tested in the last 12 months and know the result Secondary 11.9 36.9 20.0 4.1 1.6 2,180 11.4 2,044 Higher 25.3 34.2 37.4 4.9 2.6 708 10.9 693 Wealth index quintile Poorest 2.2 19.6 5.5 0.9 0.3 1,165 7.6 625 Second 3.3 23.8 8.8 1.8 1.0 1,338 6.0 839 Middle 4.9 29.2 13.3 2.9 1.7 1,385 8.7 972 Fourth 10.9 31.1 21.5 3.4 1.4 1,483 9.4 1,224 Richest 19.1 34.0 24.0 3.9 1.4 1,500 10.1 1,434 [1] MICS indicator 9.1; MDG indicator 6.3 - Knowledge about HIV prevention among young women [a] Refer to Table HA.3 for the four indicators Table HA.9 presents information on the orphanhood status of children age 10-14 years, and their school attendance. Less than one (0.3 percent) of children age 10-14 years in Sudan are orphans. Of these, 66.1 percent are attending school, as compared with a 80.2 percent attendance amongst non- orphan children of the same age group who are living with at least one parent. This results in an orphans to non-orphans school attendance ratio of 0.82 which suggests that orphans are not disadvantaged in relation to non-orphans. The ratio is 0.71 for girls and 1.0 for boys. The ratio is 0.92 for children in urban areas compared to 0.78 for children in rural areas. Table HA.9: School attendance of orphans and non-orphans School attendance of children age 10-14 years by orphanhood, Sudan MICS, 2014 Background characteristics Percentage of children whose mother and father have died (orphans) Percentage of children whose parents are still alive and who are living with at least one parent (non- orphans) Number of children age 10- 14 years Percentage of children whose mother and father have died (orphans) and are attending school Sudan number of orphan children age 10-14 years Percentage of children whose parents are still alive, who are living with at least one parent (non- orphans), and who are attending school Sudan number of non- orphan children age 10- 14 years Orphans to non- orphans school attendance ratio [1] Sudan 0.3 88.9 13,447 66.1 46 80.2 11,949 .82 Sex Male 0.3 89.6 6,540 82.9 18 82.5 5,862 1.00 Female 0.4 88.1 6,905 55.7 28 78.0 6,086 .71 Missing * * 1 * 1 Area Urban 0.3 87.4 3,947 86.4 13 93.5 3,450 .92 Rural 0.3 89.5 9,499 58.1 33 74.8 8,499 .78 [1] MICS indicator 9.16; MDG indicator 6.4 - Ratio of school attendance of orphans to school attendance of non-orphans See Table CP.14 for further overall results related to children's living arrangements and orphanhood [*] Based on less than 25 unweighted cases and has been suppressed 240 XIII: Household Food Security Sudan continues to struggle with the macro-economic after-effects of the 2011 separation of South Sudan. Sudan’s Gross Domestic Product (GDP) contracted significantly as a result of the loss of 75 percent of oil output and 60 percent of fiscal revenue51, but returned to growth in 2013 and 2014, with a real growth rate of 2.1 and 3.6 percent, respectively. Concerns remain around declining oil production, spill-over effects of state crises, inflation, subsidiary reform and high external debt.52 Inflation slowed in recent months, from an annualized rate of approximately 40 percent in the first three quarters of 2014, to between 20 to 25 percent in the first few months of 2015. The expectation of a good agricultural season helped bring the rate of inflation down, helped by the stabilization of macro-economic conditions. The Sudanese Pound was devalued considerably during 2014 and 2015, but the informal market’s exchange rate of 9 SDG continues to be far above the official exchange rate 6 SDG (to 1 USD). Household food security in Sudan is strongly linked with the performance of the agricultural sector of the economy. Directly, the agricultural sector provides household-level food production for domestic consumption and wage labour opportunities on farms. According to Sudan Central Bureau of Statistics, the agricultural sector account for 27 percent of the active labour force. Indirectly, the level of agricultural production influences the price of food, which helps determine household economic access, as most households are net consumer of food, relying on markets as their main food source. In the 2014/2015 agricultural season, the quantity and distribution of rainfall was generally good, resulting in a high level of national production of sorghum and other cash and food crops such as millet, groundnut and sesame. According to the 2014/2015 Annual Crop and Food Supply Assessment Mission (A-CFSAM) of the Food Security Technical Secretariat (FSTS), the national cereal production in 2014/15 was estimated at a record level of 7.84 million tons. A total of 6.3 million tons of sorghum, 1.1 million tons of millet and 0.5 million tons of wheat was expected to be harvested. Production was about 176 percent above the previous season’s poor harvest and 86 percent above the 5-years average (2008/09 to 2012/13) Cash crop production in the 2014 summer season improved as a results of high food prices at the beginning of 2014, stimulating supply creation. Sesame recovered from last year’s low production levels, mainly due to a significant increase in the extent of area planted. The production was estimated to increase by 231 percent compared to the previous year. Groundnut production followed a similar pattern: As a result of the sharp increased groundnut prices during early 2014, the area planted with groundnut had doubled compared to the previous year and the 5 years average. Measuring food security The 2014 MICS 2014 survey included a module on two important proxy measures of household food security: the household food consumption score (FCS) and the coping strategies that households use when they don’t have enough food or money to buy food. 51 Ibid. 52 IMF 2014, April. World Economic Outlook 2014. 241 Household food consumption score (FCS) The Household Food Consumption Score (FCS) is a food consumption indicator that is used as a proxy for household food security. Food consumption indicators are designed to reflect the quantity and quality of people’s diet. The FCS is a measure of dietary diversity, food frequency and the relative nutritional importance of the food consumed. A high food consumption score increases the possibility that a household achieves nutrient adequacy. Data are collected at household level on the number of days in the past week the household members have consumed any of 8 food or food groups. The score is calculated by multiplying the number of days by the weight assigned to the food/food group, based upon its relative nutritional importance. The food consumption score is used to classify households into three groups: poor, borderline or acceptable food consumption. The food consumption groups put together households (HH) that have similar dietary patterns and access to food. The food consumption groups can be described as follows: x Poor food consumption: Households that are consuming only cereals and vegetables every day and never or very seldom are consuming protein rich food such as meat and dairy. x Borderline food consumption: Households that are consuming cereals and vegetables every day, accompanied by oil and pulses a few times a week. x Acceptable food consumption: Households that are consuming cereals and vegetables every day, frequently accompanied by oil and pulses and occasionally meat and dairy. The table below outlines the weights and their justification for each food/food group used to calculate the food consumption score. Weights and justification for food consumption score Food group Weight Justification Main staples 2 Energy dense, protein content lower and poorer quality than legumes, micronutrients, including sorghum, millet, wheat, bread and maize. Pulses 3 Energy dense, high amounts of protein but of lower quality than meats, micronutrients, low fat, including groundnuts, pulses, beans and lentils. Vegetables 1 Low energy, low protein, no fat, micronutrients. Dried vegetables constitute an important part of the diet in Sudan, especially okra, tomatoes and kawal (fermented leaves), but fresh vegetables are also consumed (tomatoes, cucumber, onions, chili, okra, salad leaves). Fruit 1 Low energy, low protein, no fat, micronutrients. Meat and fish 4 Highest quality protein, easily absorbable micronutrients, energy dense, fat. Even when consumed in small quantities, improvements to the quality of diet are large. Commonly eaten meats in Sudan in include beef, chicken, fish, bush meat and dried meat (sharmout). Eggs are also included in this category. Milk 4 Highest quality protein, micronutrients, vitamin A, energy. Dairy products eaten in Sudan includes milk powder, fresh milk, yoghurt and cheese. Sugar 0.5 Empty calories. Usually consumed in small quantities. Oil 0.5 Energy dense but usually no other micronutrients. 242 This section will include the percentage of households in each consumption category, by state, plus the median number of days per week each food is consumed, by state. Coping strategies The module on coping strategies was added to measure behavior of households when they have difficulties covering their food needs. Households were first asked if they had experienced difficulties accessing enough food or money to buy food in the previous week. Then they were asked which coping strategies they used to manage the shortage and the number of days in the past week each coping strategy was used. Below are the six strategies included in the survey: 1. How often does your household rely on less preferred and less expensive foods? 2. How often does your household eat borrowed food or borrow money to purchase food? 3. How often does your household rely on help from friends or relatives? 4. How often does your household limit portion size at mealtimes? 5. How often does your household restrict consumption for adults in order for small children to eat? 6. How often does your household reduce number of meals eaten in a day? In the analysis and reporting for MICS 2014, the findings are presented according to the percentage of households that reported using each of the strategies by state. 13.1 Household Food Consumption Table HFS.1 shows the result of the analysis of the household food consumption data from MICS5. Overall, over eighty percent (81.5 percent) of households have acceptable food consumption levels. In Sudan, 18.5% of households are in food consumption insecurity. The table shows that households in Central Darfur are the least to have acceptable consumption (50.4 percent), followed by North Darfur (59.4 percent), West Darfur (62.7 percent) in terms of dietary diversity and food frequency. Very good levels of acceptable food consumption are found in River Nile (97.6 percent), Northern (97.1 perceent) and Red sea (91.5 percent). Poor levels of food consumption are especially found in Central Darfur (15.8 percent), North Darfur (12.6 percent), and West Kordofan (12.6 percent) states. Table HFS.1: Houshold Food Consumption Score Percentage of households with poor, borderline and acceptable food consumption, Sudan MICS, 2014 Background characteristics Household food consumption score Poor Borderline Acceptable Total Sudan 5.4% 13.1% 81.5% 100% State Northern 0.5% 2.4% 97.1% 100% River Nile 0.4% 1.9% 97.6% 100% Red Sea 2.9% 5.5% 91.5% 100% Kassala 5.4% 9.7% 84.9% 100% Gadarif 3.1% 8.2% 88.7% 100% Khartoum 1.1% 6.6% 92.2% 100% Gezira 3.2% 9.4% 87.4% 100% White Nile 3.3% 12.0% 84.7% 100% Sinnar 4.0% 13.3% 82.7% 100% Blue Nile 0.3% 6.9% 92.8% 100% North Kordofan 5.5% 16.0% 78.5% 100% 243 Background characteristics Household food consumption score Poor Borderline Acceptable Total South Kordofan 5.7% 19.9% 74.5% 100% West Kordofan 12.6% 21.6% 65.8% 100% North Darfur 15.4% 25.0% 59.6% 100% West Darfur 9.2% 28.1% 62.7% 100% South Darfur 8.8% 18.1% 73.2% 100% Central Darfur 15.8% 33.8% 50.4% 100% East Darfur 7.5% 15.0% 77.5% 100% Area Urban 2.4% 8.5% 89.1% 100% Rural 6.7% 15.0% 78.3% 100% Education of household head None 7.9% 16.6% 75.5% 100% Primary 4.5% 12.0% 83.5% 100% Secondary 2.2% 8.7% 89.1% 100% Higher 0.4% 4.0% 95.7% 100% Missing/DK 6.3% 18.2% 75.5% 100% Wealth index quintile Poorest 11.9% 21.3% 66.8% 100% Second 8.6% 19.2% 72.3% 100% Middle 3.7% 13.3% 83.0% 100% Fourth 2.1% 8.3% 89.6% 100% Richest 0.2% 2.4% 97.4% 100% Figure HFS.1: Household food consumption score, by states, Sudan MICS, 2014 0% 0% 3% 5% 3% 1% 3% 3% 4% 0% 6% 6% 13% 15% 9% 9% 16% 8% 5%2% 2% 6% 10% 8% 7% 9% 12% 13% 7% 16% 20% 22% 25% 28% 18% 34% 15% 13% 97% 98% 92% 85% 89% 92% 87% 85% 83% 93% 78% 74% 66% 60% 63% 73% 50% 77% 82% 0% 25% 50% 75% 100% P ro pr tio n of h ou se ho ld s Poor Borderline Acceptable 244 Household food consumption – urban and rural differences The data were also analysed to compare the food consumption of households in urban areas to those in rural areas. There was a lot of variation between states but in general, the states with better food consumption tend to have less of a difference between rural and urban households. The findings are presented in the following two graphs. Figure HFS. 2a shows that for households in Northern, River Nile, Garadif, and Gezira there was little or no difference in consumption between urban and rural households. Urban households in Red Sea and Kassala states have slightly better consumption that those in rural areas while those in Khartoum and Kassala have slightly worse consumption compared to rural households. However, in both White Nile and Sennar states, the consumption of urban households is quite a bit better than rural households. Figure HFS.2a: Household food consumption, by urban and rural (part one), Sudan MICS, 2014 The urban/rural comparisons for households in Central and Western Sudan are quite different as shown in the below graph. For the Kordofan and Darfur regions, rural households are less likely to have acceptable consumption than households in urban areas. The difference is greatest in Central Darfur where only 48 percent of the rural households have acceptable consumption, compared to 75 percent of urban households. In South Kordofan, 69 percent of rural households have acceptable consumption compared to 83 percent of those in urban areas. 7% 5% 5%3% 2% 2% 2% 5% 7% 7% 7% 8% 8% 7% 4% 8% 9% 5% 14% 8% 15% 9% 7% 97% 97% 99% 97% 93% 89% 90% 87% 89% 90% 92% 95% 90% 89% 94% 81% 89% 81% 91% 93% 0% 25% 50% 75% 100% U rb an R ur al U rb an R ur al U rb an R ur al U rb an R ur al U rb an R ur al U rb an R ur al U rb an R ur al U rb an R ur al U rb an R ur al U rb an R ur al Northern River Nile Red Sea Kassala Gadarif Khartoum Gezira White Nile Sennar Blue Nile Pr op or tio n of h ou se ho ld s Poor Borderline Acceptable 245 Figure HFS.2b: Household food consumption, by urban and rural (part two), Sudan MICS, 2014 As is evident from table HFS.1, households’ food consumption is positively correlated both with the level of education of the household head and with household wealth. Twenty-four percent of households whose head has no education has either poor or borderline food consumption, compared to only 11 percent for those whose head had completed secondary education. The corresponding percentages for households in the bottom wealth quintile is 33 percent, compared to 3 percent in the top wealth quintile. Comparison of household consumption habits The 7-day recall data were used to determine the ‘typical’ weekly household consumption for each state and the following graphs are used to show the differences and similarities across the country. Households in Northern state typically consume wheat/bread, legumes, meat, oil/fat, dairy, sugar and dried vegetables on a daily basis with consumption of eggs, fresh vegetables, fruit, sorghum and millet occasionally. Households in River Nile state consume sorghum, wheat/bread, oil/fat, dairy, sugar and dried vegetables on a daily basis with regular consumption of legumes, meat and fresh vegetables and occasional consumption of millet, fruits and eggs. In Red Sea state, household consumption is characterized by daily consumption of sorghum, wheat/bread, oil/fat, dairy, and sugar with regular consumption of dried vegetables and occasional consumption of millet, legumes, meat, fruit, eggs and fresh vegetables. Consumption in Khartoum state is characterized by daily consumption of wheat/bread, oil, dairy and sugar with regular consumption of meat, fresh vegetables and dried vegetables and occasional consumption of sorghum, millet, legumes, fruits and eggs. 1% 7% 3% 6% 9% 13% 10% 16% 6% 10% 4% 11% 4% 17% 2% 8% 2% 7% 12% 17% 12% 23% 17% 23% 20% 26% 17% 32% 11% 21% 14% 36% 8% 16% 8% 15% 87% 76% 85% 71% 74% 64% 70% 58% 77% 57% 85% 68% 82% 47% 90% 75% 89% 78% 0% 25% 50% 75% 100% U rb an R ur al U rb an R ur al U rb an R ur al U rb an R ur al U rb an R ur al U rb an R ur al U rb an R ur al U rb an R ur al U rb an R ur al North Kordofan South Kordofan West Kordofan North Darfor West Darfor South Darfor Central Darfor East Darfor Total P ro po rti on o f h ou se ho ld s Poor Borderline Acceptable 246 Figure HFS.3a: Number of days foods are consumed (part one), Sudan MICS, 2014 Consumption for households in Gadarif state is characterized by daily consumption of sorghum, oil/fat, dairy, sugar and dried vegetables with regular consumption of wheat/bread and meat and occasional consumption of millet, legumes, fruits, eggs and fresh vegetables. In Gezira state, households consume sorghum, wheat/bread, oil/fat, dairy, sugar and dried vegetables on a daily basis with regular consumption of fresh vegetables and only occasional consumption of millet, legumes, fruits and eggs. Households in White Nile consume sorghum, oil/fat, dairy, sugar and dried vegetables on a daily basis accompanied with wheat/bread and meat on a regular basis and occasional consumption of millet, legumes, fruits, eggs and fresh vegetables. In Sinnar state, household food consumption is characterized by daily consumption of sorghum, wheat/bread, oil/fat, dairy, sugar and dried vegetables, as well as regular consumption of meat and occasional consumption of millet, legumes, fruit, eggs and fresh vegetables. Blue Nile households have daily consumption of sorghum, wheat/bread, meat, oil/fat, dairy, sugar and dried vegetables and regular consumption of fresh vegetables and occasionally consume millet, legumes, fruits and eggs. 2 2 7 7 7 7 2 7 7 3 3 77 2 7 5 4 7 2 7 7 3 4 77 3 7 3 3 7 2 7 7 3 3 5 7 7 7 3 3 7 3 7 7 3 3 7 2 2 7 3 4 7 2 7 7 3 4 5 0 1 2 3 4 5 6 7 N um be r o f d ay s pe r w ee k Northern River Nile Red Sea Kassala Khartoum 247 Figure HFS.3b: Number of days foods are consumed (part two), Sudan MICS, 2014 Household food consumption across the Kordofan states is similar and is characterized by daily consumption of sorghum, millet (except South Kordofan), oil/fat, dairy, sugar and dried vegetables, and occasional consumption of wheat, legumes, meat, fruits, eggs and fresh vegetables. Figure HFS.3c: Number of days foods are consumed (part three), Sudan MICS, 2014 Consumption for households in the Darfur region is characterized by daily consumption of sorghum and millet (except South and Central Darfur), oils/fats, dairy, sugar and dried vegetables, with occasional consumption of wheat/bread, legumes, meat, fruits, eggs and fresh vegetables. 7 3 5 3 6 7 2 7 7 2 3 77 2 7 2 7 7 2 7 7 2 5 77 2 6 2 5 7 2 7 7 2 3 77 3 7 2 5 7 2 7 7 2 3 77 3 7 3 7 7 3 7 7 2 4 7 0 1 2 3 4 5 6 7 N um be r o fd ay s pe r w ee k Gadarif Gezira White Nile Sinnar Blue Nile 7 7 4 3 3 7 2 7 7 2 3 77 2 3 2 3 7 2 7 7 2 3 77 7 3 3 3 7 1 7 7 3 2 7 0 1 2 3 4 5 6 7 N um be r o f d ay s pe r w ee k North Kordofan South Kordofan West Kordofan 248 Figure HFS.3d: Number of days foods are consumed (part four), Sudan MICS, 2014 13.2 Food Coping Strategies The following section presents by state the percentage of households using different coping strategies when they don’t have enough food or money to buy food for their families. Households in Northern state rarely need to use food coping strategies but when they do, they will borrow food or money to buy food or rely on less preferred or less expensive foods. When faced with food shortages, households in River Nile state will rely on less preferred or less expensive foods or borrowing money or food. This is the same for households in Red Sea and Kassala states. Households in Khartoum state were much more likely to report difficulties in accessing enough food or money to buy food compared to the other states. To cope, they mostly rely on less preferred or less expensive foods or on borrowing money or food. They also will rely on friends and relatives or reduce the number of meals. 7 7 2 2 2 7 2 7 7 2 2 77 7 2 2 3 7 2 7 7 2 3 77 5 3 3 3 7 2 7 7 2 3 77 5 1 3 2 7 2 7 7 2 3 77 7 2 3 2 7 2 7 7 2 4 7 0 1 2 3 4 5 6 7 N um be r o f d ay s pe r w ee k North Darfor West Darfor South Darfor Central Darfor East Darfor 249 Table HFS.2: Food Coping Strategies Background characteristics Rely on less preferred and less expensive food Eat borrowed food or borrowed money to purchase food Rely on help from friends or relatives Limit portion size at mealtimes Restrict consumption for adults in order for small children to eat Reduce number of meals eaten in a day Sudan 15.1% 16.1% 6.4% 3.4% 1.3% 4.8% State Northern 3.9% 6.5% 1.1% 1.3% 0.7% 2.1% River Nile 11.8% 5.2% 2.6% 1.5% 0.7% 2.7% Red Sea 9.5% 8.3% 2.0% 2.3% 0.0% 2.8% Kassala 6.4% 4.2% 3.2% 2.4% 1.4% 2.6% Gadarif 28.4% 23.3% 8.5% 3.4% 0.7% 9.1% Khartoum 7.2% 8.6% 3.1% 1.0% 0.4% 2.3% Gezira 14.0% 19.6% 8.0% 4.3% 1.2% 5.1% White Nile 19.3% 21.6% 4.5% 3.9% 1.3% 3.4% Sinnar 23.2% 19.9% 4.3% 2.7% 0.6% 2.4% Blue Nile 20.1% 19.2% 4.8% 3.9% 0.5% 4.9% North Kordofan 11.8% 22.7% 5.1% 4.4% 1.6% 4.6% South Kordofan 12.8% 14.2% 4.6% 1.9% 1.7% 4.6% West Kordofan 6.3% 12.4% 7.5% 2.9% 2.6% 5.2% North Darfur 12.8% 11.7% 9.3% 2.1% 1.8% 3.6% West Darfur 6.4% 7.8% 6.0% 3.5% 1.8% 3.6% South Darfur 16.7% 13.4% 6.8% 5.3% 1.4% 5.0% Central Darfur 22.0% 17.8% 11.7% 7.8% 3.4% 7.4% East Darfur 16.3% 26.2% 10.9% 4.4% 1.8% 5.4% Area Urban 20.2% 17.8% 6.2% 3.6% 1.0% 6.2% Rural 13.0% 15.4% 6.4% 3.3% 1.4% 4.2% Education of household head None 15.5% 15.9% 7.4% 4.0% 1.3% 4.8% Primary 15.2% 16.3% 5.9% 3.4% 1.5% 5.6% Secondary 15.6% 17.1% 5.1% 2.4% 1.0% 4.4% Higher 11.2% 12.6% 4.3% 1.6% 0.5% 2.7% Missing/DK 11.3% 18.6% 5.8% 1.3% 1.3% 3.1% Wealth index quintile Poorest 12.6% 14.7% 7.6% 3.4% 1.6% 4.1% Second 13.9% 16.5% 6.4% 3.7% 1.5% 5.1% Middle 17.2% 18.0% 6.5% 3.7% 1.2% 4.8% Fourth 16.9% 17.8% 6.6% 3.8% 1.4% 5.3% Richest 15.3% 13.5% 4.6% 2.3% 0.5% 4.7% 250 Figure HFS.4a: Food coping strategies (Part one), Sudan MICS, 2014 Households in Gadarif were also not likely to face difficulties in accessing enough food for their families but if necessary will borrow money or food or rely on less preferred or expensive foods. The situation was similar for households in Gezira, White Nile, Sinnar and Blue Nile states where 20- 25 percent reported facing difficulties in accessing enough food for their needs and then relying on borrowing or consuming less preferred or less expensive foods. Figure HFS.4b: Food coping strategies (Part two), Sudan MICS, 2014 Households in the Kordofan region have similar levels of difficulties accessing enough food or money to buy food with those in North Kordofan most likely to face these difficulties. The primary responses 4% 7% 1% 1% 1% 2% 12% 5% 3% 2% 1% 3% 9% 8% 2% 2% 0% 3% 6% 4% 3% 2% 1% 3% 28% 23% 8% 3% 1% 9% 0% 10% 20% 30% Rely on less preferred and less expensive food Eat borrowed food or borrowed money to purchase food Rely on help from friends or relatives Limit portion size at mealtimes Restrict consumption for adults in order for small children to eat Reduce number of meals eaten in a day P ro po rti on o f h ou se ho ld s Northern River Nile Red Sea Kassala Khartoum 7% 9% 3% 1% 0% 2% 14% 20% 8% 4% 1% 5% 19% 22% 5% 4% 1% 3% 23% 20% 4% 3% 1% 2% 20% 19% 5% 4% 1% 5% 0% 10% 20% 30% Rely on less preferred and less expensive food Eat borrowed food or borrowed money to purchase food Rely on help from friends or relatives Limit portion size at mealtimes Restrict consumption for adults in order for small children to eat Reduce number of meals eaten in a day P ro po rti on o f h ou se ho ld s Gadarif Gezira White Nile Sinnar Blue Nile 251 are similar with borrowing or changing consumption to less preferred or less expensive foods with those in West Kordofan slightly more likely to rely on help from friends or relatives. Figure HFS.4c: Food coping strategies (Part three), Sudan MICS, 2014 Households in the Darfur region face similar challenges in accessing enough food or money to buy food with those in East and Central Darfur the most likely to borrow money or food or to rely on less preferred or expensive foods. The Darfur households are more likely to rely on help from friends or relatives than households in the other states and slightly more likely in South and Central Darfur to limit portion size at mealtimes. 12% 23% 5% 4% 2% 5% 13% 14% 5% 2% 2% 5% 6% 12% 8% 3% 3% 5% 0% 10% 20% 30% Rely on less preferred and less expensive food Eat borrowed food or borrowed money to purchase food Rely on help from friends or relatives Limit portion size at mealtimes Restrict consumption for adults in order for small children to eat Reduce number of meals eaten in a day P ro po rti on o f h ou se ho ld s North Kordofan South Kordofan West Kordofan 252 Figure HFS.4d: Food coping strategies (Part four), Sudan MICS, 2014 Several of the food coping strategies do not correlate significantly with the level of education of the head of household, nor with the household wealth status, arguably illustrating the relative nature of the perception of coping with food access problems. Households whose head is better educated was found to be less likely to rely on help from friends and relatives, and to limit portion size at mealtimes. 13% 12% 9% 2% 2% 4% 6% 8% 6% 3% 2% 4% 17% 13% 7% 5% 1% 5% 22% 18% 12% 8% 3% 7% 16% 26% 11% 4% 2% 5% 15% 16% 6% 3% 1% 5% 0% 10% 20% 30% Rely on less preferred and less expensive food Eat borrowed food or borrowed money to purchase food Rely on help from friends or relatives Limit portion size at mealtimes Restrict consumption for adults in order for small children to eat Reduce number of meals eaten in a day P ro po rti on o f h ou se ho ld s North Darfor West Darfor South Darfor Central Darfor East Darfor Country average 253 Appendix A: Sample Design The major features of the sample design are described in this appendix. Sample design features include target sample size, sample allocation, sampling frame and listing, choice of domains, sampling stages, stratification, and the calculation of sample weights. The primary objective of the sample design for the Sudan MICS 2014 was to produce statistically reliable estimates for a large number of indicators, at the national level, for urban and rural areas, and for the eighteen states of the country: Northern, River Nile, Red Sea, Kassala, Gadaraf, Khartoum, Gezira, Sinnar, Blue Nile, White Nile, North Kordofan, South Kordofan, North Darfur, West Darfur, South Darfur, and the recent established West Kordofan, Eastern Darfur and Central Darfu. In order to produce State-level estimates of moderate precision, a minimum of 30 enumeration areas (EAs) were selected in each State, resulting in a sample that was not self-weighting. Urban and rural areas in each of the eighteen states were defined as the sampling strata and a multitwo-stage, stratified cluster sampling approach was used for the selection of the survey sample. In the first stage, within each stratum, a specified number of EAs were selected systematically with probability proportional to size. In the second stage, after a household listing was carried out within the selected enumeration areas, a systematic sample of 25 households was drawn in each selected EA. Sample Size and Sample Allocation The sample size for the Sudan MICS 2014 was calculated as 18,000 households. For the calculation of the sample size, the key indicator used was the breast feeding. The following formula was used to estimate the required sample size for this indicator: z2 * r * (1-r) * deff n = --------------------------------------------- (RME * r)2 * pb * AveSize * RR where: n = the required sample size, (number of HHs) z = the value in the normal distribution that gives level of confidence 95% (z = 2) r=predicted value of indicator (in target/base population), (r=0.41) deff = the design effect, ( deff = 1.7) RME=relative margin of error at 95% confidence (RME=0.11). pb = proportion of target/base population in total population, (pb = 0.16). AveSize=Average household size (AveSize=6). RR = response rate (RR =0.9) By substitution: n = 22*(0.41) (1-0.41) *1.7 (0.11*0.41)2 *(0.16)*6*0.9 n = 936 = 1000 HHs from each state. Total sample for all Sudan = 1000*18=18000 HHs. 254 For the calculation, r (underweight prevalence) was assumed to be 25 percent. The value of deff (design effect) was taken as 1.5 based on estimates from previous surveys, pb (percentage of children age 0-4 years in the total population) was taken as 13 percent, AveSize (average household size) was taken as 6.2 households, and the response rate was assumed to be 90 percent, based on experience from previous surveys. The resulting number of households from this exercise was 1,000 households which is the sample size needed in each state – thus yielding 18,000 in total. The number of households selected per cluster for the Sudan MICS 2014 was determined as 25 households, based on a number of considerations, including the design effect, the budget available, and the time that would be needed per team to complete one cluster. Dividing the total number of households by the number of sample households per cluster, it was calculated that 86 sample clusters would need to be selected in each state. Equal allocation of the total sample size to the eighteen states was used. Therefore, 40 clusters were allocated to each state, with the final sample size calculated as 18,000 households (40 clusters * 18 states * 25 sample households per cluster). In each state, the clusters (primary sampling units) were distributed to the urban and rural domains proportionally to the size of urban and rural populations in that state. The table below shows the allocation of clusters to the sampling strata. Table SD.1: Allocation of Sample households and Clusters (Primary Sampling Units) to Sampling Strata Number Households Number of Clusters Total Urban Rural Total Urban Rural Sudan 18,000 5,125 12,875 720 205 515 No. State 1 Northern 1,000 200 800 40 8 32 2 River Nile 1,000 300 700 40 12 28 3 Red Sea 1,000 500 500 40 20 20 4 Kassala 1,000 325 675 40 13 27 5 Gadarif 1,000 250 750 40 10 30 6 Khartoum 1,000 800 200 40 32 8 7 Gezira 1,000 175 825 40 7 33 8 White Nile 1,000 300 700 40 12 28 9 Sinnar 1,000 225 775 40 9 31 10 Blue Nile 1,000 225 775 40 9 31 11 North Kordofan 1,000 200 800 40 8 32 12 South Kordofan 1,000 250 750 40 10 30 13 West Kordofan 1,000 250 750 40 10 30 14 North Darfur 1,000 175 825 40 7 33 15 West Darfur 1,000 100 900 40 4 36 16 South Darfur 1,000 375 625 40 15 25 17 Central Darfur 1,000 175 825 40 7 33 18 East Darfur 1,000 300 700 40 12 28 255 Sampling Frame and Selection of Clusters The 2008 census frame was used for the selection of clusters. Census enumeration areas were defined as primary sampling units (PSUs), and were selected from each of the sampling strata by using systematic pps (probability proportional to size) sampling procedures, based on the number of households in each enumeration area from the 2008 Population and Housing Census frame. The first stage of sampling was thus completed by selecting the required number of enumeration areas from each of the eighteen states, separately for the urban and rural strata. Listing Activities Since the sampling frame (the 2008 census) was not up-to-date, a new listing of households was conducted in all the sample enumeration areas prior to the selection of households. For this purpose, listing teams were formed who visited all of the selected enumeration areas and listed all households in the enumeration areas. A separate manual was provided that described the listing organization, dates, teams, procedures of the listing exercise that was to be carried out. This manual was written in Arabic. Selection of Households Lists of households were prepared by the listing teams in the field for each enumeration area. The households were then sequentially numbered from 1 to n (the total number of households in each enumeration area) at the Central Bureau of Statitics Office, where the selection of 25 households in each enumeration area was carried out using random systematic selection procedures. Calculation of Sample Weights The Sudan MICS 2014 sample is not self-weighting. Essentially, by allocating equal numbers of households to each of the states, different sampling fractions were used in each state since the sizes of the states varied. For this reason, sample weights were calculated and these were used in the subsequent analyses of the survey data. The major component of the weight is the reciprocal of the sampling fraction employed in selecting the number of sample households in that particular sampling stratum (h) and PSU (i): hi hi fW 1 The term fhi, the overall probability for selecting the sample households in the i-th sample PSU in the h-th stratum, is the product of probabilities of selection at every stage in each sampling stratum: hihihihi pppf 321 uu where pshi is the probability of selection of the sampling unit at stage s for the i-th sample PSU in the h-th sampling stratum. Based on the sample design, these probabilities were calculated as follows: 256 p1hi = h hih M Mn u , nh = number of sample PSUs selected in stratum h Mhi = number of households in the 2008 Census frame for the i-th sample PSU in stratum h Mh = total number of households in the 2008 Census frame for stratum h p2hi = proportion of the PSU listed for the i-th sample PSU in stratum h (in the case of PSUs that were segmented); for non-segmented PSUs, p2hi = 1 p3hi = hiM ' 25 M'hi = number of households listed in the i-th sample PSU in stratum h Since the number of households in each enumeration area (PSU) from the 2008 Census frame used for the first stage selection and the updated number of households in the enumeration area from the listing are generally different, individual overall probabilities of selection for households in each sample enumeration area (cluster) were calculated. A final component in the calculation of sample weights takes into account the level of non-response for the household and individual interviews. The adjustment for household non-response in each stratum is equal to: hRR 1 where RRh is the response rate for the sample households in stratum h, defined as the proportion of the number of interviewed households in stratum h out of the number of selected households found to be occupied during the fieldwork in stratum h. Similarly, adjustment for non-response at the individual level (women, men, and under-5 children) for each stratum is equal to: hRR 1 where RRh is the response rate for the individual questionnaires in stratum h, defined as the proportion of eligible individuals (women, men, and under-5 children) in the sample households in stratum h who were successfully interviewed. After the completion of the fieldwork, response rates were calculated for each sampling stratum. These were used to adjust the sample weights calculated for each cluster. Response rates in the Sudan MICS 2014 are shown in Table HH.1 in this report. The non-response adjustment factors for the individual women, men, and under-5 questionnaires were applied to the adjusted household weights. Numbers of eligible women, men, and under-5 257 children were obtained from the roster of household members in the Household Questionnaire for households where interviews were completed. The design weights for the households were calculated by multiplying the inverse of the probabilities of selection by the non-response adjustment factor for each enumeration area. These weights were then standardized (or normalized), one purpose of which is to make the weighted sum of the interviewed sample units equal to the unweighted number of observations the national level. Normalization is achieved by dividing the full sample weights (adjusted for nonresponse) by the average of these weights across all households at the national level. This is performed by multiplying the sample weights by a constant factor equal to the unweighted number of households at the national level divided by the weighted total number of households (using the full sample weights adjusted for nonresponse). A similar standardization procedure was followed in obtaining standardized weights for the individual women, men, and under-5 questionnaires. Adjusted (normalized) weights varied between lowest weight and highest weight in the 720 sample enumeration areas (clusters). Sample weights were appended to all data sets and analyses were performed by weighting households, women, men, or under-5s with these sample weights. 258 Appendix B: List of Personnel Involved in the Survey A. Steering committee members: Director General Central Bureau of Statistics Chairperson Survey Technical Coordinator Reporter Under Secretary, Federal Ministry of Health Member Under Secretary Ministry of Education Member Under Secretary Ministry of Welfare and S. Security Member Under Secretary, Ministry of Environment and Public Member UNICEF Representative Member UNFPA Representative Member WHO Representative Member WFP Representative Member Secretary General of National population Council Member B. Technical Committee Members Director General Central Bureau of Statistics - Chairman Representatives from: – Federal Ministry of Health – Ministry of Welfare and Social Security – Ministry Education – National population Council – National Council for Child Welfare – Ministry of Environment and Urban Development – Ministry of Human Resources Development and Labour – Public Water Corporation – UNFPA – UNICEF – WHO – WFP Survey Administrative Coordinator Survey National Consultants (4) Experts and Technical persons from CBS C. National Survey Team Members Dr. Yassin El-haj Abdin National survey coordinator Kamal Ahmed Ismael National survey technical coordinator El-Tag Awad Aburas Administrative Coordinator Somia Khalid El-Khier Field Work coordinator Amin Ahmed Doud Data processing coordinator Intsar El-hadi Administrative assistant Maha Elhaj Administrative assistant Amani Abdelwhaab Accountant Amira Gaber) Administrative assistant Isam Idriss Elkhas Assistant National Administrator 259 Hassan Morkaz Computer programmer Amin Ahmed Doud Data processing coordinator Magda Mohamed Secretary Habab Abdallah Secretary D. MICS5 National Consultants Prof Siddig Mohamed A. Shahein Sample design expert Ibrahim Abbas Household Consultant Siddig Mohamed Osman Data Processing Expert Abdel Bari Hassan Nasr MICS5 Consultant/UNICEF E. UNICEF Staff Supporting the Survey Robert Ndamobissi Chief of Section Planning, Monitoring & Evaluation Walaa Kordofani ex- Monitoring and Evaluation officer Alaa Mahmoud Monitoring and Evaluation Officer Siddig Musa Abaker F. Report Writing Team Kamal M. Ismail: Chapters 1 & 2 Robert Ndamobissi: Chapters 4 & 5 Ibrahim Abbas Seif Elnasr: Chapter 3 Abdel Bari H Nasr: Chapters 7 & 9 Siddig M. Osman: Chapter 10 Dr. Faisal: Chapters 6 & 9 Anders Petersson: Chapter 13 Alaa Mahmoud: Review/Editing Dina Ali: Review & Editing Paul A. Sengeh (UNICEF Consultant): Chapter 12 & Executive Summary G. Field Personnel State State Manager National supervisor Field supervisor Filed editors : Interviewers : Measurers Northern Houda Mohamed Gomaa Magda Khalaf Allah Mohamed Awad Mohame Awad Nagla Abdelnoor Abdelraheem Hajer Osman Yasin Noor Alhuda Goma Adel Ali Noraldein Somia Taha Abdallah Amjad Ahmed El- Haj El-Sadig Mohamed Goma Ashraf Ahmed Almogamer Hanya Mahmoud Shamat Hanan Hashim Mohamed Kawser Mohamed El-Khier Rawya Musa Mohamed Mashaaer Abdelteif Mohamed Afraa Awad Ahmed Dawla Ibrahim El- Hassan Mymona Ali Ahmed Sara Mahjoub Abdelraheem 260 State State Manager National supervisor Field supervisor Filed editors : Interviewers : Measurers River Nile Mohamed Yousif Fardos Mohamed Salih Siefeldeen Osman Idrees Rehab Ahmed Elkhalifa Sumaiah Gareeballah Amnah Ahmed Hussain Ashraf Tajelsir Bakry Omniah Alfaky Thigah Surajaldeen Hind Sallah Abdallah Nada Alnoor Ahmed Siham Gareeballah Adwa Nasr eldeen Najwa Alawad Marwa Alnoor Ayah Abdallah Magzoob Marwa Yahia Aml Ahmed Osman Ghadah Babker Altieb Hanaa Mahmoud Red Sea FATIMA SAID ALAMIN AMNA OMER FATIMA SAID ALAMIN RASHA ABDALLA IBRAHIM AMINA MHJOOB AHMED SAFYA MOHMED AHMED TAHANI OSMAN IBRAHIM KHADIGA GAFFER AL MOTALEB FATIMA MAHMUD MOHMED AMAL MOHAMED ALI FAKI OMER AHMED IBRAHIM MAHMUD MOHMED AMENA IDRES MOHMED FATIMA MOHMED ABEED SEHAM AWAD IBRAHEM TAHANI OSMAN IBRAHIM BADRIA SALAH MOHMED NADA HASSEN RAMADAN BOSINA AHMED MOHAMED NADREEN AWAD FADUL AL MOULA WEDAD SAID ALAMIN Kassala Yousif Hesein Abdelmageid Mustafa Hassan Ali Basha Rihab Mohamed Ali Nor Moahmed Osman Sara Hassan Almahel Eman Musa El-Shikh Eman Abasher El-Shiekh Huda Saad Ahmed Magda Mahjob Ibrahim Thorya Osman Hassan Abdellah El- Bokhary Osman Amel Adam Mohamed Hanan Abdellah Saad Amiera Abdein Hassan Fatima Ahmed Byerag Tayseer Tahier Nayer Arfat Hasaballah Ahmed Nawal Elsir Idries Nagla Abdelfatah Mohamed Salih Aasma Ibrahim Idriss Gadarif Um salma Gubara Ibrahim. Ali suliman ali Abd Razig Rahama Mustafa Amgad Abdalwahab Ebrahem Manahel Mahadi Musa Elham Alamin Ebrahim 261 State State Manager National supervisor Field supervisor Filed editors : Interviewers : Measurers Alzaki Altaher Ali Majda Mohammed saleh Bedour Mohammed Alhassan Khadega Adem Abd allh Faiz Mohammed Abd alrahman Saadia Mohammed Alhassan Ebetahj Mohammed Alnour Fataheia Mohammed Abdallh Hager Ahmed Abd eldin Khadega Saleh Hamed Rehab Musa Aljak Maisoun Abdalwahab Ebrahem Marem Mutasim Mohammed Thouwiba Ezz Eldin Osman Khartoum Abdelgader Mohamed Ahmed Husien Hassan Husien Tarieg Mohamed El- Hassan Sana Mohamed Sati Nadia Hassan Amer Khider Noon Mohamed Osman Faiza Mohamed Ahmed Ezdehar Mohamed Osman Bielges Suliman Suaad Dafallah Amel Eabyedi Rasha Musa Mai Samri Asrar Eshag Amal Ezeldien Alwya Ali Esia Hanan Abdallah Manal Fadul Hanan Mohamed Osman Gezira AWADELSYE D ABDALLA ADAM MUSTAFA ELJACK MUSTAFA RAJYA MUSA ELAWAD SAWSAN ABDALLA AHMED NASHWA ABDELRAHIM ADAM SALMA MAHAJOUB AWAD ELRAYAH MOHAMED ZAROUG REHAB HASSAN ABDELGADIR HOAYDA SHARAFELDEEN ELTAHIR RAJA HASSAN ABDALLA ELZAIN ABDALLA MOHAMED IHLAM MOHAMED ALI HAFIZA IBRAHIM AHMED WIGDAN OMER ABDELGAFAR HADEEL HASHIM MOHAMED LIMYA BASHIR ABDELRAZIG WISAL ABDALLA HAMID ABIR SHAMSALDINE MUSA ALZINA DAFALLAH AHMED SAFA SALA KHODLY White Nile Fadwa Sied Ahmed Mubarak Haj Musa Huda Tagelsier Mohamed Eman Rahmtallah Gomaa Habiba Bashier El- Haj 262 State State Manager National supervisor Field supervisor Filed editors : Interviewers : Measurers Hhalifa Ahmed Mohamed Musa Wageallah Alnaw Amel Mustafa Mohamed Buthaina Abdallah Aaker Afrah El-Hadi Adam Ibrahim Abaas Mohamed Sania Hamed Omer Nmareg Mahjoub Mohamed Sediga Abaker Kharief Wala Adam Abdallah Ardnos Ibrahim Ali Tagwa Ahmed Adam Rashida Younis Husien Wegdan Wageallah Alnaw Hayat Ismael Suliman Sinnar Mohamed Ahmed Asaker Mahaseen Abdelgani Mohamed Yagoup Khalifa Hanim Slman Yousif Hajer Mustafa Abeer musa Mohamed Ibrahim Ahmed Hassan Hanan Ibrahim Sulafa Hassan El- Safi Rasha Hassan mahmoud Ibtsam Omer Osman Heba El-Tayeb Abdelrazaag Zeinb Attallah Almnaan Hawa Abdelrahman Idrees Nazik Salih Samah Mohyeldaien Suhaier Adam Ahmed Shahed Abubaker Mohamed Afraa osman Intsar Omer Mohamed Blue Nile Idres Omer Idres Hanan Ali El-Shikh Khalid Osman Ahmed Mariam Mohamed Abaker Malka Mohamed Adam Rogaya Osman Hassan Mustafa Khalid Mustafa Amani Ibrahim Nada Hassan Koko Heba Mohyeldain Ahmed Khalied Yousif El-Awad Hekmat Hamaad Hala Mohamed Mustafa Huda Hamed Mohamed Awadia Abu Elhassan Elham Abdelgader Suliman Hajwa Abdelaziz Mubark Manahel El-haj Muser Ayat Omer Mariam Mohamed Abakar North Kordofan Ali Turo Mosa Hanan Abass Sediq Izaldeen Altigani Hamad Shaza Tarig Alshazaly Fatuma Osman Dgash Amna Abdalla Ahmed Adil Manal Mohammed Abdalla Fatima Gamar Alasha Emam Ilham Farah Abdalrhman Zehra Gibril Mohammed Mehasin Alsmani Altaib Albagir Kamal Albagir Rihab Aljaily zian Alabdeen Halima Ibrahim Alddy 263 State State Manager National supervisor Field supervisor Filed editors : Interviewers : Measurers Rihab Omer Idriss Marim Babekr Abusara Eatizaz Ali Gesm Alla Mwahib Alsmani Rahma Reem Altaj Mohammed Rania Ibrahim Bakhit South Kordofan Abaas Mohamdeen Hamouda Abugamah Omer Osman Mohamed Ayoub Faisal Mohamed Elamin Gaidum arees omer Hua Ibrahim Hamed Hajer Ismael Fadellah Faisal Mohamed Adam Romya mohammdny ebrahim Myada Abdelaziz Omer Bedoor Hasien El- balabi Basher konona abdellah Nemaat Musa Bringi Zamzam El-haj Mohamed Aaisha Gomaa Obied Egbal rodwan Mohamed Fathia abdelmotaleb Malak haggar Mohamed Mariam Abdallah trtoor Siham Fathi Mohamed Latifa Hamed Ibrahim West Kordofan ELTAYEB GOMMA MOHAMED KHEIRALLA H MOHAMM ED KHAMEI KHEIRALLAH MOHAMMED KHAMEI ISLAM JABER ALMAKI HANAN ABDALRAHMAN SELIMAN MONIRA AHMED IBRAHIM AHMED ANKOSH AHMED MARIAM SOBAHI ELIAN NAGWA MERGANI AHMED AWDIA AHMED MOHAMMED ALI AHMED EISA SOMIA IBRAHIM OMER MONA AHMED HAMDAN SAHAR ADAM SELIMAN WAFA ALI HAMED EHLAM SAEED ADAM ALTOUMA IBRAHIM HOMIDAN SHAZA AHMED ALDAW YASMIN MOHAMMED HOMIDAN SALMA YOSEF MAHADI North Darfur Khalda Abdallah Imam Mahasin Ibrahim El-Haj Suha Gaber Atem Najla Hamed Mohamed 264 State State Manager National supervisor Field supervisor Filed editors : Interviewers : Measurers Somia Abdallah Ibrahim Abdelrahm an El- Khalifa Husien Mahmoud Badawi Nagat Abdallah Ibraim Aasha Abelmaged Mohamed Hawa Adam Diego Mohamed Musa Ibraim Ayda Ali Adam Nada Gebril Goma Safa Aibraim Adam Madina Adam ibrahim Israa Adam El-Haj Mstora Musa ali Mahaa Ahmed Syada Abdallah Ahmed Najwa Salih Ahmed West Darfur Wafa Hassan Mansour Salah Abdelrahm an Maged Hasim Husien Togol El-Tayeb Musa Hasab Allah Rawda Mohamed Adam Mariam Yahya Ismael Mubark Mohamed Abdallah Gada Musa Abdallah Shama Suliman Abdelkarem Asma Abdelrahman Hamed Mohamed Ahmed Bader Rania Adam Abdallah Zeinab Hashim Ibrahim Sadeya Adam Yagoub Egbal Hassan Ramdan Manal Mohamed Bader Mahasin Musa Abdallah Tagreed Adam Haroun Amani Fadul Hassan Nagat Hassan Mansour South Darfur El-Magboul Abdallah aAbaker Eisaa Ali Abaker Tarieg Hesabo Adam Muna Moahmed Ahmed Dalia Salaheldien Abubaker Hassan Ibrahim Ahmed Abdallah Abugoula Nemaat Moahmed Ahmed Muna Mohamed Adam El-Hafez Musa Suliman Mustafa Abdelrahman Yagoub Amani Eisaa ali Haja Gameel Allah Ahmed Ahmed Adam Mohamed Tasabieh Mohamed Adam Eman Mohamed Abugola Sara Mubarak Mohamed Muzdalefa Omer Abaker Munera Yahya Abdelrahman Intsar Adam Senien Central Darfur El-Hafez Ibrahim Ahmed Ismael Abaker Banda Mohamed Mustafa Ogal Zubida Adam Hamed Hanan Musa Badallh Nagat Abuker Mohamed Hayder Ides Yahya Siham Idres Arbab Manahel Abdallah Ishag Tsabih Mohamed Aldoma 265 State State Manager National supervisor Field supervisor Filed editors : Interviewers : Measurers Zien El-Abdein Osman Amani Abelmutalib Salih Zuhal Salih Madani Magboula Abdelshafea Muna Logman Abaker Ibtehal Salih Mohamed Mahasin Salih Osman Kawser Idres Mohamed Salma Mohamed Osman East Darfur Mohamed Ahmed Asim Markhni Mohamed Osman Aseel Abdalwahab Adam Rihab El-Sadig Mohammed Namarig Abdallah Mohammed Haja Mohammed Hassan Basher Easa Ali Omar Om Salama Ahmed Fadlla Yusuf Masin Abdalrahman Mohammed Harm Husian Ahmed Abdelmajied Ahmed Samsedin Osman Zahra Hammad Dogoush Ali Taiseer Ahmed Beniamen Anas Adam Ahmed Hawa Ibrahim Ahmed Abdalla Ibrahim Mohammed Mazaher Mohammed Khalefa Howida Daw El- bietn Mahmoud Taiseer Adam Haroun Korsi Insaf Guam Khamis Awatif Omda Bakhet Wade 266 Appendix C: Estimates of Sampling Errors C1. Replacement of Clusters in Conflict affected areas MICS 2014 have been realized in a very challenging context of ongoing long term armed conflicts and many displacements of populations prevailing in Darfur and Kordofan estates Sudan in addition to the outstanding high risk mining areas. A very large sample design has been defined for MICS 2014 in Sudan which comprises 720 Clusters (40 per state), 18,000 Households (1,000 per state) in order to ensure adequate representativity of statistical estimation by each State. During the implementation of the field data collection, the Central Bureau of Statistics (CBS) has been constrained to proceed to the replacement of 22 clusters (enumeration area) among 720 sampled for the survey (which represent 3%). The maximum number of clusters that have been replaced within state is four (4) clusters in Red Sea; West Kordofan; East Darfur; central Darfur. This in addition to two Clusters in Kassala ; and one cluster in each of South Darfur; West Darfur; Khartoum and Gedaref. The main reason of replacement of clusters are as follow: i) insecurity in Darfur states, ii) Mine area in Kassala state, iii) the displacements of population in Red Sea and iv) the Rainy Season in Gadaref state. The Central Bureau of Statistics benefiting of solid expertise of Consultant in Sampling has developed adequate technical measures by providing to the field work team leader (technical expert), clear instructions that has enabled to perform the replacement in close compliance to the statistical practice of replacement of enumeration area by choosing the nearest accessible area using list of frame in respect of urban and rural areas. Taking into account the provisional measure of sample design which has included 10% of “non-respondents rate” and the expansion of initial calculated required sample from 930 clusters to 1,000, any anticipated error which may merge from the replacements has been fully absorbed. Indicators measured for MICS 2014 in Sudan is not affected by the replacement of 22 clusters (from 1 to maximum 4 into some states). Table below indicates the geographic distribution of replaced 22 samples of cluster implemented during the survey. State Area Locality Name AU Cluster No. PAU_Name HHS RED SEA RURAL GANIB El Aoleeb 201 Giadet 83 RURAL GANIB El Aoleeb 202 Ashtake 100 RURAL SAWAKIN Rifi Sawakin 202 Merkeb 150 RURAL HAYA Rifi Haya 201 Rahedet 367 KASSALA RURAL HAMASHKORAIB Hamashkoraib 202 Teshaier I 99 RURAL TALKOOK Talkook 201 Tm Kafar 239 GADAREF RURAL RAHAD Wad El Shaair 201 Barbar 131 KHARTOUM URBAN JEBEL AULIA Nasr 101 Al mansora Moraba wahed 223 WEST KORDOFAN RURAL LAGAWA Rifi Sinoot 201 Algasabo 124 RURAL ESSALAM Rifi Kigaira 201 Bagara 149 RURAL ABIAE Rifi Muglad 203 Om Al bashar 123 RURAL ABIAE Rifi Mairam 202 Abo betek 137 267 State Area Locality Name AU Cluster No. PAU_Name HHS CENTRAL DARFUR RURAL AZOOM Um Shalaya 201 Muaskr Lagen 150 RURAL WADI SALIH Rifi Um Khair 201 Helat Al goz 163 RURAL WADI SALIH Rifi Bendisi 203 Gander 45 RURAL WADI SALIH Rifi Bendisi 204 Batat Rasol 113 SOUTH DARFUR RURAL RIHAID BURDI Um Dagoog 201 Al mased 114 EAST DARFUR RURAL SHIAIRIYA Rifi Yassin 201 Kelal Mogo 186 RURAL ADILA Abu Karinka 201 Baket Hai al wehda 138 RURAL ADILA Rifi Sharif 201 Om Nalala 297 RURAL ADILA Rifi Sharif 201 Al Gora 256 WEST DARFUR URBAN GINAINA Ginaina Town 123 Hai Al Kobre 146 Benefiting of the international expertise of the Global MICS Consultant of Sampling, the probabibility of selection of the 22 replaced clusters have been recalculated taking into account the initial population size from 2008 population census and the enumerated population in 2014. This has been integrated into the calculation of weight factor of measurement of indicators. Test has been performed to compare indicators generated without or including the revised probability which resulted to the positive conclusion of no difference of estimations: the replacement of 22 clusters due to the conflicts did’nt affect the accuracy of indicators. C2. Sampling Errors The sample of respondents selected in the Sudan Multiple Indicator Cluster Survey (MICS5) is only one of the samples that could have been selected from the same population, using the same design and size. Each of these samples would yield results that differ somewhat from the results of the actual sample selected. Sampling errors are a measure of the variability between the estimates from all possible samples. The extent of variability is not known exactly, but can be estimated statistically from the survey data. The following sampling error measures are presented in this appendix for each of the selected indicators: ƒ Standard error (se): Standard error is the square root of the variance of the estimate. For survey indicators that are means, proportions or ratios, the Taylor series linearization method is used for the estimation of standard errors. For more complex statistics, such as fertility and mortality rates, the Jackknife repeated replication method is used for standard error estimation. ƒ Coefficient of variation (se/r) is the ratio of the standard error to the value (r) of the indicator, and is a measure of the relative sampling error. ƒ Design effect (deff) is the ratio of the actual variance of an indicator, under the sampling method used in the survey, to the variance calculated under the assumption of simple random sampling based on the same sample size. The square root of the design effect (deft) is used to show the efficiency of the sample design in relation to the precision. A deft value of 1.0 indicates that the sample design of the survey is as efficient as a simple random sample for a particular indicator, 268 while a deft value above 1.0 indicates an increase in the standard error due to the use of a more complex sample design. ƒ Confidence limits are calculated to show the interval within which the true value for the population can be reasonably assumed to fall, with a specified level of confidence. For any given statistic calculated from the survey, the value of that statistic will fall within a range of plus or minus two times the standard error (r + 2.se or r – 2.se) of the statistic in 95 percent of all possible samples of identical size and design. For the calculation of sampling errors from MICS data, programs developed in CSPro Version 5.0, SPSS Version 21 Complex Samples module and CMRJack53 have been used. The results are shown in the tables that follow. In addition to the sampling error measures described above, the tables also include weighted and unweighted counts of denominators for each indicator. Given the use of normalized weights, by comparing the weighted and unweighted counts it is possible to determine whether a particular domain has been under-sampled or over-sampled compared to the average sampling rate. If the weighted count is smaller than the unweighted count, this means that the particular domain had been over-sampled. As explained later in the footnote of Table SE.1, there is an exception in the case of indicators 4.1 and 4.3, for which the unweighted count represents the number of sample households, and the weighted counts reflect the total population. Sampling errors are calculated for indicators of primary interest, for the national level. Three of the selected indicators are based on households members, 7 are based on women, and 2 are based on children under 5. Table SE.1 shows the list of indicators for which sampling errors are calculated, including the base population (denominator) for each indicator. Table SE.1: Indicators selected for sampling error calculations List of indicators selected for sampling error calculations, and base populations (denominators) for each indicator, Sudan MICS, 2014 MICS5 Indicator Base Population Household members 4.1 Use of improved drinking water sources All household membersa 4.3 Use of improved sanitation All household membersa 7.4 Primary school net attendance ratio (adjusted) Children of primary school age Women 5.3 Contraceptive prevalence rate Women age 15-49 years who are currently married 5.4 Unmet need Women age 15-49 years who are currently married 5.5a Antenatal care coverage (1+ times, skilled provider) Women age 15-49 years with a live birth in the last 2 years 5.5b Antenatal care coverage (4+ times, any provider) Women age 15-49 years with a live birth in the last 2 years 5.7 Skilled attendant at delivery Women age 15-49 years with a live birth in the last 2 years 7.1 Literacy rate (young women) Women age 15-24 years 9.1 Knowledge about HIV prevention (young women) Women age 15-24 years Under-5s 2.1a Underweight prevalence (moderate and severe) Children under age 5 years 2.1b Underweight prevalence (severe) Children under age 5 years a To calculate the weighted results of MICS Indicators 4.1 and 4.3, the household weight is multiplied by the number of household members in each household. Therefore the unweighted base population presented in the SE tables reflect the unweighted number of households, whereas the weighted numbers reflect the household population 53 CMRJack is a software developed by FAFO, an independent and multidisciplinary research foundation. CMRJack produces mortality estimates and standard errors for surveys with complete birth histories or summary birth histories. See http://www.fafo.no/ais/child_mortality/index.html 269 Table SE.2: Sampling errors: Total Sample - Sudan Standard errors, coefficients of variation, design effects (deff), square root of design effects (deft) and confidence intervals for selected indicators, Sudan, 2014 Table Value (r) Stand ard error (se) Coeffici ent of variatio n (se/r) Design effect (deff) Square root of design effect (deft) Weight ed count Unweight ed count Confidence limits r - 2se r + 2se Household members Use of improved drinking water sources WS.1 .6804 .01432 .021 15.846 3.981 98,883 16,801 0.652 0.709 Use of improved sanitation WS.5 .3286 .01206 .037 11.070 3.327 98,883 16,801 0.304 0.353 Primary school net attendance ratio (adjusted) ED.4 .7642 .00796 .010 8.065 2.840 22,977 22,924 0.748 0.780 Women Contraceptive prevalence rate RH.5 .1223 .00562 .046 3.533 1.880 11,867 12,023 0.111 0.134 Unmet need RH.6 .2658 .00579 .022 2.068 1.438 11,867 12,023 0.254 0.277 Antenatal care coverage (1+ times, skilled provider) RH.7 .7909 .01034 .013 3.673 1.917 5,622 5,684 0.770 0.812 Antenatal care coverage (4+ times, any provider) RH.8 .5073 .01132 .022 2.912 1.706 5,622 5,684 0.485 0.530 Skilled attendant at delivery RH.10 .7773 .01278 .016 5.363 2.316 5,622 5,684 0.752 0.803 Literacy rate (young women) ED.1 .5978 .01344 .022 5.111 2.261 6,871 6,805 0.571 0.625 Knowledge about HIV prevention (young women) HA.1 .0851 .00752 .088 4.949 2.225 6,871 6,805 0.070 0.100 Under-5s Underweight prevalence (moderate and severe) NU.2 .3305 .00870 .026 3.885 1.971 11,713 11,367 0.313 0.348 Underweight prevalence (severe) NU.2 .1202 .00561 .047 3.388 1.841 11,713 11,367 0.109 0.131 270 Table SE.3: Sampling errors: Urban Standard errors, coefficients of variation, design effects (deff), square root of design effects (deft) and confidence intervals for selected indicators, Sudan, 2014 Table Value (r) Standa rd error (se) Coeffici ent of variatio n (se/r) Design effect (deff) Square root of design effect (deft) Weighte d count Unweig hted count Confidence limits r - 2se r + 2se Household members Use of improved drinking water sources WS.1 .7830 .01843 .024 9.647 3.106 30,476 4825 0.746 0.820 Use of improved sanitation WS.5 .5704 .01595 .028 5.011 2.239 30,476 4825 0.538 0.602 Primary school net attendance ratio (adjusted) ED.4 .9141 .00623 .007 3.132 1.770 6,446 6,340 0.902 0.927 Women Contraceptive prevalence rate RH.5 .2005 .00960 .048 1.967 1.403 3,437 3420 0.181 0.220 Unmet need RH.6 .2443 .01075 .044 2.141 1.463 3,437 3420 0.223 0.266 Antenatal care coverage (1+ times, skilled provider) RH.7 .9077 .00993 .011 1.768 1.330 1,488 1503 0.888 0.928 Antenatal care coverage (4+ times, any provider) RH.8 .7178 .01547 .022 1.774 1.332 1,488 1503 0.687 0.749 Skilled attendant at delivery RH.10 .9322 .01242 .013 3.667 1.915 1,488 1503 0.907 0.957 Literacy rate (young women) ED.1 .7975 .01818 .023 4.607 1.589 2,262 2,253 0.761 0.834 Knowledge about HIV prevention (young women) HA.1 .1231 .01381 .112 3.978 1.995 2,262 2253 0.095 0.151 Under-5s Underweight prevalence (moderate and severe) NU.2 .2324 .01116 .048 2.249 1.500 3,405 3224 0.210 0.255 Underweight prevalence (severe) NU.2 .0756 .00626 .083 1.807 1.344 3,405 3224 0.063 0.088 271 Table SE.4: Sampling errors: Rural Standard errors, coefficients of variation, design effects (deff), square root of design effects (deft) and confidence intervals for selected indicators, Sudan, 2014 Table Value (r) Standa rd error (se) Coeffici ent of variatio n (se/r) Design effect (deff) Square root of design effect (deft) Weighte d count Unweigh ted count Confidence limits r - 2se r + 2se Household members Use of improved drinking water sources WS.1 .6347 .01935 .030 19.340 4.398 68,407 11,976 0.596 0.673 Use of improved sanitation WS.5 .2209 .01596 .072 17.720 4.209 68,407 11,976 0.189 0.253 Primary school net attendance ratio (adjusted) ED.4 .7058 .01052 .015 8.844 2.974 16,531 16,584 0.685 0.727 Women Contraceptive prevalence rate RH.5 .0905 .00679 .075 4.817 2.195 8,430 8,603 0.077 0.104 Unmet need RH.6 .2745 .00683 .025 2.013 1.419 8,430 8,603 0.261 0.288 Antenatal care coverage (1+ times, skilled provider) RH.7 .7489 .01357 .018 4.094 2.023 4,134 4,181 0.722 0.776 Antenatal care coverage (4+ times, any provider) RH.8 .4315 .01358 .031 3.144 1.773 4,134 4,181 0.404 0.459 Skilled attendant at delivery RH.10 .7216 .01700 .024 6.014 2.452 4,134 4,181 0.688 0.756 Literacy rate (young women) ED.1 .4997 .01769 .035 5.695 2.386 4,609 4,552 0.464 0.535 Knowledge about HIV prevention (young women) HA.1 .0664 .00890 .134 5.811 2.411 4,609 4,552 0.049 0.084 Under-5s Underweight prevalence (moderate and severe) NU.2 .3706 .01064 .029 3.954 1.988 8,308 8,143 0.349 0.392 Underweight prevalence (severe) NU.2 .1385 .00725 .052 3.586 1.894 8,308 8,143 0.124 0.153 272 Table SE.5: Sampling errors: Northern state Standard errors, coefficients of variation, design effects (deff), square root of design effects (deft) and confidence intervals for selected indicators, Sudan, 2014 Table Value (r) Standar d error (se) Coeffici ent of variatio n (se/r) Design effect (deff) Square root of design effect (deft) Weighted count Unwei ghted count Confidence limits r - 2se r + 2se Household members Use of improved drinking water sources WS.1 .9381 .03308 .035 18.022 4.245 2,181 957 0.872 1.000 Use of improved sanitation WS.5 .7938 .04120 .052 9.915 3.149 2,181 957 0.711 0.876 Primary school net attendance ratio (adjusted) ED.4 .9549 .01090 .011 2.482 1.576 404 900 0.933 0.977 Women Contraceptive prevalence rate RH.5 .2289 .02817 .123 2.953 1.718 280 658 0.173 0.285 Unmet need RH.6 .2993 .02244 .075 1.577 1.256 280 658 0.254 0.344 Antenatal care coverage (1+ times, skilled provider) RH.7 .9465 .01569 .017 1.046 1.023 92 216 0.915 0.978 Antenatal care coverage (4+ times, any provider) RH.8 .6646 .03704 .056 1.323 1.150 92 216 0.590 0.739 Skilled attendant at delivery RH.10 .9903 .00568 .006 .720 .849 92 216 0.979 1.000 Literacy rate (young women) ED.1 .9149 .02162 .024 2.052 1.432 1.432 343 0.872 0.958 Knowledge about HIV prevention (young women) HA.1 .1469 .01503 .102 .616 .785 146 343 0.117 0.177 Under-5s Underweight prevalence (moderate and severe) NU.2 .2194 .02467 .112 1.720 1.311 214 485 0.170 0.269 Underweight prevalence (severe) NU.2 .0453 .01471 .325 2.424 1.557 214 485 0.016 0.075 273 Table SE.6: Sampling errors: River Nile state Standard errors, coefficients of variation, design effects (deff), square root of design effects (deft) and confidence intervals for selected indicators, Sudan, 2014 Table Value (r) Standa rd error (se) Coeffici ent of variatio n (se/r) Design effect (deff) Square root of design effect (deft) Weighted count Unwei ghted count Confidence limits r - 2se r + 2se Household members Use of improved drinking water sources WS.1 .8829 .03686 .042 12.181 3.490 3,715 928 0.809 0.957 Use of improved sanitation WS.5 .4981 .03861 .078 5.529 2.351 3,715 928 0.421 0.575 Primary school net attendance ratio (adjusted) ED.4 .9108 .02986 .033 10.600 3.256 665 967 0.851 0.971 Women Contraceptive prevalence rate RH.5 .2133 .02120 .099 1.638 1.280 409 613 0.171 0.256 Unmet need RH.6 .2476 .02182 .088 1.564 1.251 409 613 0.204 0.291 Antenatal care coverage (1+ times, skilled provider) RH.7 .9516 .01566 .016 1.231 1.109 151 232 0.920 0.983 Antenatal care coverage (4+ times, any provider) RH.8 .5292 .04388 .083 1.785 1.336 151 232 0.441 0.617 Skilled attendant at delivery RH.10 .9710 .01907 .020 2.985 1.728 151 232 0.933 1.000 Literacy rate (young women) ED.1 .7984 .03635 .046 3.013 1.736 253 368 0.726 0.871 Knowledge about HIV prevention (young women) HA.1 .1666 .02541 .152 1.706 1.306 253 368 0.116 0.217 Under-5s Underweight prevalence (moderate and severe) NU.2 .3217 .03003 .093 2.028 1.424 338 492 0.262 0.382 Underweight prevalence (severe) NU.2 .1102 .01304 .118 .851 .923 338 492 0.084 0.136 274 Table SE.7: Sampling errors: Red Sea state Standard errors, coefficients of variation, design effects (deff), square root of design effects (deft) and confidence intervals for selected indicators, Sudan, 2014 Table Value (r) Standa rd error (se) Coeffici ent of variatio n (se/r) Design effect (deff) Square root of design effect (deft) Weighted count Unwe ighte d count Confidence limits r - 2se r + 2se Household members Use of improved drinking water sources WS.1 .3319 .05621 .169 13.208 3.634 2,489 928 0.219 0.444 Use of improved sanitation WS.5 .5243 .03454 .066 4.435 2.106 2,489 928 0.455 0.593 Primary school net attendance ratio (adjusted) ED.4 .8443 .02707 .032 5.000 2.236 512 898 0.790 0.898 Women Contraceptive prevalence rate RH.5 .0960 .01300 .135 1.097 1.047 323 564 0.070 0.122 Unmet need RH.6 .1913 .02213 .116 1.783 1.335 323 564 0.147 0.236 Antenatal care coverage (1+ times, skilled provider) RH.7 .7237 .03614 .050 .967 .983 92 149 0.651 0.796 Antenatal care coverage (4+ times, any provider) RH.8 .5342 .03805 .071 .861 .928 92 149 0.458 0.610 Skilled attendant at delivery RH.10 .7778 .03773 .049 1.219 1.104 92 149 0.702 0.853 Literacy rate (young women) ED.1 .7190 .04422 .062 2.420 1.555 150 251 0.631 0.807 Knowledge about HIV prevention (young women) HA.1 .0534 .01620 .304 1.299 1.140 150 251 0.021 0.086 Under-5s Underweight prevalence (moderate and severe) NU.2 .3363 .02908 .086 1.122 1.059 182 297 0.278 0.395 Underweight prevalence (severe) NU.2 .1586 .02327 .147 1.201 1.096 182 297 0.112 0.205 275 Table SE.8: Sampling errors: Kassala state Standard errors, coefficients of variation, design effects (deff), square root of design effects (deft) and confidence intervals for selected indicators, Sudan, 2014 Table Value (r) Standar d error (se) Coeffic ient of variati on (se/r) Design effect (deff) Squar e root of desig n effect (deft) Weighted count Unweig hted count Confidence limits r - 2se r + 2se Household members Use of improved drinking water sources WS.1 .5721 .07354 .129 19.840 4.454 4,117 899 0.425 0.719 Use of improved sanitation WS.5 .2934 .06413 .219 17.816 4.221 4,117 899 0.165 0.422 Primary school net attendance ratio (adjusted) ED.4 .6833 .06772 .099 26.509 5.149 1,016 1,252 0.548 0.819 Women Contraceptive prevalence rate RH.5 .0791 .02388 .302 5.263 2.294 506 673 0.031 0.127 Unmet need RH.6 .1666 .01408 .085 .959 .979 506 673 0.138 0.195 Antenatal care coverage (1+ times, skilled provider) RH.7 .8305 .02294 .028 1.010 1.005 199 271 0.785 0.876 Antenatal care coverage (4+ times, any provider) RH.8 .5395 .05229 .097 2.972 1.724 199 271 0.435 0.644 Skilled attendant at delivery RH.10 .7704 .03911 .051 2.335 1.528 199 271 0.692 0.849 Literacy rate (young women) ED.1 .4842 .05434 .112 3.902 1.975 272 331 0.376 0.593 Knowledge about HIV prevention (young women) HA.1 .0695 .01968 .283 1.978 1.407 272 331 0.030 0.109 Under-5s Underweight prevalence (moderate and severe) NU.2 .4195 .03545 .085 2.772 1.665 409 538 0.349 0.490 Underweight prevalence (severe) NU.2 .1554 .02106 .135 1.814 1.347 409 538 0.113 0.198 276 Table SE.9: Sampling errors: Gadarif state Standard errors, coefficients of variation, design effects (deff), square root of design effects (deft) and confidence intervals for selected indicators, Sudan, 2014 Table Value (r) Stand ard error (se) Coefficient of variation (se/r) Design effect (deff) Square root of design effect (deft) Weighted count Unwei ghted count Confidence limits r - 2se r + 2se Household members Use of improved drinking water sources WS.1 .2771 .04833 .174 11.030 3.321 5,005 947 0.180 0.374 Use of improved sanitation WS.5 .0979 .02025 .207 4.393 2.096 5,005 947 0.057 0.138 Primary school net attendance ratio (adjusted) ED.4 .7232 .03414 .047 7.848 2.801 1,220 1,349 0.655 0.792 Women Contraceptive prevalence rate RH.5 .0949 .01654 .174 2.283 1.511 630 718 0.062 0.128 Unmet need RH.6 .2400 .02466 .103 2.390 1.546 630 718 0.191 0.289 Antenatal care coverage (1+ times, skilled provider) RH.7 .8054 .04011 .050 3.552 1.885 307 347 0.725 0.886 Antenatal care coverage (4+ times, any provider) RH.8 .4479 .03753 .084 1.970 1.404 307 347 0.373 0.523 Skilled attendant at delivery RH.10 .8267 .04960 .060 5.943 2.438 307 347 0.728 0.926 Literacy rate (young women) ED.1 .4276 .05778 .135 5.170 2.274 327 380 0.312 0.543 Knowledge about HIV prevention (young women) HA.1 .0574 .01425 .248 1.422 1.193 327 380 0.029 0.086 Under-5s Underweight prevalence (moderate and severe) NU.2 .3766 .03366 .089 3.567 1.889 666 740 0.309 0.444 Underweight prevalence (severe) NU.2 .1555 .01967 .127 2.178 1.476 666 740 0.116 0.195 277 Table SE.10: Sampling errors: Khartoum state Standard errors, coefficients of variation, design effects (deff), square root of design effects (deft) and confidence intervals for selected indicators, Sudan, 2014 Table Value (r) Standar d error (se) Coefficient of variation (se/r) Desig n effect (deff) Square root of design effect (deft) Weighted count Unweig hted count Confidence limits r - 2se r + 2se Household members Use of improved drinking water sources WS.1 .8691 .03497 .040 9.894 3.145 13,830 921 0.799 0.939 Use of improved sanitation WS.5 .6641 .02698 .041 3.003 1.733 13,830 921 0.610 0.718 Primary school net attendance ratio (adjusted) ED.4 .9527 .00981 .010 2.312 1.520 2,788 1,083 0.933 0.972 Women Contraceptive prevalence rate RH.5 .2651 .01809 .068 1.117 1.057 1,623 666 0.229 0.301 Unmet need RH.6 .2125 .01665 .078 1.102 1.050 1,623 666 0.179 0.246 Antenatal care coverage (1+ times, skilled provider) RH.7 .9715 .01177 .012 1.364 1.168 684 274 0.948 0.995 Antenatal care coverage (4+ times, any provider) RH.8 .8187 .03116 .038 1.786 1.336 684 274 0.756 0.881 Skilled attendant at delivery RH.10 .9956 .00441 .004 1.213 1.101 684 274 0.987 1.000 Literacy rate (young women) ED.1 .8257 .03025 .037 2.747 1.657 1,053 433 0.765 0.886 Knowledge about HIV prevention (young women) HA.1 .1563 .03122 .200 3.192 1.787 1,053 433 0.094 0.219 Under-5s Underweight prevalence (moderate and severe) NU.2 .2319 .02027 .087 1.487 1.220 1,603 646 0.191 0.272 Underweight prevalence (severe) NU.2 .0645 .01026 .159 1.126 1.061 1,603 646 0.044 0.085 278 Table SE.11: Sampling errors: Gizera state Standard errors, coefficients of variation, design effects (deff), square root of design effects (deft) and confidence intervals for selected indicators, Sudan, 2014 Table Value (r) Standar d error (se) Coefficie nt of variation (se/r) Design effect (deff) Square root of design effect (deft) Weighted count Unwei ghted count Confidence limits r - 2se r + 2se Household members Use of improved drinking water sources WS.1 .8890 .04486 .050 20.121 4.486 16,270 988 0.799 0.979 Use of improved sanitation WS.5 .3828 .05045 .132 10.633 3.261 16,270 988 0.282 0.484 Primary school net attendance ratio (adjusted) ED.4 .7935 .02476 .031 4.437 2.106 1,148 1,187 0.744 0.843 Women Contraceptive prevalence rate RH.5 .1222 .02204 .180 3.627 1.904 1,961 802 0.078 0.166 Unmet need RH.6 .2872 .01982 .069 1.537 1.240 1,961 802 0.248 0.327 Antenatal care coverage (1+ times, skilled rovider) RH.7 .8325 .02779 .033 1.844 1.358 852 334 0.777 0.888 Antenatal care coverage (4+ times, any provider) RH.8 .5049 .03393 .067 1.533 1.238 852 334 0.437 0.573 Skilled attendant at delivery RH.10 .9251 .02595 .028 3.234 1.798 852 334 0.873 0.977 Literacy rate (young women) ED.1 .6639 .04508 .068 4.744 2.178 1,231 522 0.574 0.754 Knowledge about HIV prevention (young women) HA.1 .0942 .02607 .277 4.152 2.038 1,231 522 0.042 0.146 Under-5s Underweight prevalence (moderate and severe) NU.2 .3236 .03568 .110 4.491 2.119 2,084 773 0.252 0.395 Underweight prevalence (severe) NU.2 .1232 .02454 .199 4.302 2.074 2,084 773 0.074 0.172 279 Table SE.12: Sampling errors: White Nile state Standard errors, coefficients of variation, design effects (deff), square root of design effects (deft) and confidence intervals for selected indicators, Sudan, 2014 Table Value (r) Stand ard error (se) Coefficie nt of variation (se/r) Design effect (deff) Square root of design effect (deft) Weighted count Unwei ghted count Confidence limits r - 2se r + 2se Household members Use of improved drinking water sources WS.1 .3274 .04966 .152 10.203 3.194 5,016 912 0.228 0.427 Use of improved sanitation WS.5 .2979 .03504 .118 5.348 2.313 5,016 912 0.228 0.368 Primary school net attendance ratio (adjusted) ED.4 .7935 .02476 .031 4.437 2.106 1,148 1,187 0.744 0.843 Women Contraceptive prevalence rate RH.5 .1561 .01671 .107 1.406 1.186 577 664 0.123 0.190 Unmet need RH.6 .2885 .01906 .066 1.174 1.083 577 664 0.250 0.327 Antenatal care coverage (1+ times, skilled provider) RH.7 .7880 .02719 .035 1.372 1.171 273 311 0.734 0.842 Antenatal care coverage (4+ times, any provider) RH.8 .4549 .03547 .078 1.573 1.254 273 311 0.384 0.526 Skilled attendant at delivery RH.10 .9233 .01677 .018 1.231 1.110 273 311 0.890 0.957 Literacy rate (young women) ED.1 .6754 .03812 .056 2.399 1.549 312 363 0.599 0.752 Knowledge about HIV prevention (young women) HA.1 .0361 .01093 .303 1.243 1.115 312 363 0.014 0.058 Under-5s Underweight prevalence (moderate and severe) NU.2 .2979 .02380 .080 1.666 1.291 572 616 0.250 0.346 Underweight prevalence (severe) NU.2 .1111 .01432 .129 1.276 1.130 572 616 0.083 0.140 280 Table SE.13: Sampling errors: Sinnar state Standard errors, coefficients of variation, design effects (deff), square root of design effects (deft) and confidence intervals for selected indicators, Sudan, 2014 Table Value (r) Standar d error (se) Coeffic ient of variati on (se/r) Design effect (deff) Square root of design effect (deft) Weighted count Unwei ghted count Confidence limits r - 2se r + 2se Household members Use of improved drinking water sources WS.1 .8868 .02618 .030 6.512 2.552 3,763 955 0.834 0.939 Use of improved sanitation WS.5 .1858 .02464 .133 3.827 1.956 3,763 955 0.137 0.235 Primary school net attendance ratio (adjusted) ED.4 .8159 .03312 .041 8.675 2.945 816 1,189 0.750 0.882 Women Contraceptive prevalence rate RH.5 .1354 .01993 .147 2.303 1.517 450 680 0.096 0.175 Unmet need RH.6 .2615 .01874 .072 1.235 1.111 450 680 0.224 0.299 Antenatal care coverage (1+ times, skilled rovider) RH.7 .7531 .03499 .046 2.219 1.490 226 338 0.683 0.823 Antenatal care coverage (4+ times, any provider) RH.8 .4350 .02942 .068 1.187 1.089 226 338 0.376 0.494 Skilled attendant at delivery RH.10 .8915 .04175 .047 6.071 2.464 226 338 0.808 0.975 Literacy rate (young women) ED.1 .5404 .03961 .073 2.394 1.547 257 380 0.461 0.620 Knowledge about HIV prevention (young women) HA.1 .0963 .01930 .200 1.622 1.274 257 380 0.058 0.135 Under-5s Underweight prevalence (moderate and severe) NU.2 .3639 .03956 .109 4.719 2.172 471 699 0.285 0.443 Underweight prevalence (severe) NU.2 .1463 .01982 .135 2.196 1.482 471 699 0.107 0.186 281 Table SE.14: Sampling errors: Blue Nile state Standard errors, coefficients of variation, design effects (deff), square root of design effects (deft) and confidence intervals for selected indicators, Sudan, 2014 Table Value (r) Stand ard error (se) Coefficient of variation (se/r) Design effect (deff) Square root of design effect (deft) Weighted count Unweig hted count Confidence limits r - 2se r + 2se Household members Use of improved drinking water sources WS.1 .7129 .04713 .066 10.342 3.216 4,094 954 0.619 0.807 Use of improved sanitation WS.5 .3967 .07000 .176 19.512 4.417 4,094 954 0.257 0.537 Primary school net attendance ratio (adjusted) ED.4 .7797 .02373 .030 4.489 2.119 979 1,370 0.732 0.827 Women Contraceptive prevalence rate RH.5 .0710 .01313 .185 1.997 1.413 525 765 0.045 0.097 Unmet need RH.6 .2584 .02514 .097 2.519 1.587 525 765 0.208 0.309 Antenatal care coverage (1+ times, skilled provider) RH.7 .7181 .05337 .074 5.938 2.437 287 423 0.611 0.825 Antenatal care coverage (4+ times, any provider) RH.8 .4268 .03984 .093 2.737 1.655 287 423 0.347 0.506 Skilled attendant at delivery RH.10 .6099 .07716 .127 10.560 3.250 287 423 0.456 0.764 Literacy rate (young women) ED.1 .3607 .03833 .106 2.810 1.676 297 442 0.284 0.437 Knowledge about HIV prevention (young women) HA.1 .0897 .02489 .277 3.346 1.829 297 442 0.040 0.139 Under-5s Underweight prevalence (moderate and severe) NU.2 .3526 .02004 .057 1.707 1.306 668 971 0.313 0.393 Underweight prevalence (severe) NU.2 .1070 .01120 .105 1.273 1.128 668 971 0.085 0.129 282 Table SE.15: Sampling errors: North Kordofan state Standard errors, coefficients of variation, design effects (deff), square root of design effects (deft) and confidence intervals for selected indicators, Sudan, 2014 Table Value (r) Standar d error (se) Coefficie nt of variation (se/r) Design effect (deff) Square root of design effect (deft) Weighted count Unweight ed count Confidence limits r - 2se r + 2se Household members Use of improved drinking water sources WS.1 .6978 .05574 .080 13.658 3.696 6,359 928 0.586 0.809 Use of improved sanitation WS.5 .2503 .03373 .135 5.620 2.371 6,359 928 0.183 0.318 Primary school net attendance ratio (adjusted) ED.4 .7385 .03716 .050 8.651 2.941 1,506 1,211 0.664 0.813 Women Contraceptive prevalence rate RH.5 .1467 .02179 .149 2.276 1.509 743 601 0.103 0.190 Unmet need RH.6 .3241 .02052 .063 1.153 1.074 743 601 0.283 0.365 Antenatal care coverage (1+ times, skilled provider) RH.7 .8559 .02484 .029 1.466 1.211 352 294 0.806 0.906 Antenatal care coverage (4+ times, any provider) RH.8 .5771 .03680 .064 1.626 1.275 352 294 0.503 0.651 Skilled attendant at delivery RH.10 .8846 .03664 .041 3.852 1.963 352 294 0.811 0.958 Literacy rate (young women) ED.1 .5879 .05185 .088 4.328 2.080 471 391 0.484 0.692 Knowledge about HIV prevention (young women) HA.1 .0223 .00693 .311 .859 .927 471 391 0.008 0.036 Under-5s Underweight prevalence (moderate and severe) NU.2 .3241 .02068 .064 1.212 1.101 752 622 0.283 0.365 Underweight prevalence (severe) NU.2 .1150 .01358 .118 1.125 1.061 752 622 0.088 0.142 283 Table SE.16: Sampling errors: South Kordofan state Standard errors, coefficients of variation, design effects (deff), square root of design effects (deft) and confidence intervals for selected indicators, Sudan, 2014 Table Value (r) Standar d error (se) Coeffici ent of variatio n (se/r) Design effect (deff) Square root of design effect (deft) Weighted count Unwei ghted count Confidence limits r - 2se r + 2se Household members Use of improved drinking water sources WS.1 .6008 .06134 .102 15.058 3.880 2,983 961 0.478 0.723 Use of improved sanitation WS.5 .1432 .02996 .209 7.020 2.649 2,983 961 0.083 0.203 Primary school net attendance ratio (adjusted) ED.4 .6945 .05417 .078 21.698 4.658 779 1,570 0.586 0.803 Women Contraceptive prevalence rate RH.5 .0899 .01489 .166 2.094 1.447 355 774 0.060 0.120 Unmet need RH.6 .3379 .03182 .094 3.498 1.870 355 774 0.274 0.402 Antenatal care coverage (1+ times, skilled provider) RH.7 .8506 .02691 .032 2.559 1.600 194 450 0.797 0.904 Antenatal care coverage (4+ times, any provider) RH.8 .5926 .03231 .055 1.941 1.393 194 450 0.528 0.657 Skilled attendant at delivery RH.10 .8020 .05731 .071 9.287 3.047 194 450 0.687 0.917 Literacy rate (young women) ED.1 .4917 .04650 .095 4.006 2.002 197 464 0.399 0.585 Knowledge about HIV prevention (young women) HA.1 .0948 .02539 .268 3.479 1.865 197 464 0.044 0.146 Under-5s Underweight prevalence (moderate and severe) NU.2 .3483 .02906 .083 3.299 1.816 431 888 0.290 0.406 Underweight prevalence (severe) NU.2 .1446 .01504 .104 1.622 1.274 431 888 0.115 0.175 284 Table SE.17: Sampling errors: West Kordofan state Standard errors, coefficients of variation, design effects (deff), square root of design effects (deft) and confidence intervals for selected indicators, Sudan, 2014 Table Value (r) Standar d error (se) Coeffici ent of variatio n (se/r) Design effect (deff) Square root of design effect (deft) Weighted count Unwei ghted count Confidence limits r - 2se r + 2se Household members Use of improved drinking water sources WS.1 .8603 .03154 .037 7.208 2.685 5,745 872 0.797 0.923 Use of improved sanitation WS.5 .1038 .02301 .222 4.958 2.227 5,745 872 0.058 0.150 Primary school net attendance ratio (adjusted) ED.4 .5413 .03653 .067 6.940 2.634 1,483 1,292 0.468 0.614 Women Contraceptive prevalence rate RH.5 .0606 .01180 .195 1.473 1.214 687 603 0.037 0.084 Unmet need RH.6 .2394 .01839 .077 1.118 1.058 687 603 0.203 0.276 Antenatal care coverage (1+ times, skilled provider) RH.7 .6528 .04488 .069 2.497 1.580 341 282 0.563 0.743 Antenatal care coverage (4+ times, any provider) RH.8 .2814 .03469 .123 1.673 1.293 341 282 0.212 0.351 Skilled attendant at delivery RH.10 .6734 .05485 .081 3.843 1.960 341 282 0.564 0.783 Literacy rate (young women) ED.1 .3287 .04861 .148 3.288 1.813 341 308 0.231 0.426 Knowledge about HIV prevention (young women) HA.1 .0436 .01619 .371 1.928 1.389 341 308 0.011 0.076 Under-5s Underweight prevalence (moderate and severe) NU.2 .3870 .03407 .088 1.708 1.307 388 350 0.319 0.455 Underweight prevalence (severe) NU.2 .1475 .01668 .113 .772 .879 388 350 0.114 0.181 285 Table SE.18: Sampling errors: North Darfor state Standard errors, coefficients of variation, design effects (deff), square root of design effects (deft) and confidence intervals for selected indicators, Sudan, 2014 Table Value (r) Standar d error (se) Coeffici ent of variatio n (se/r) Design effect (deff) Square root of design effect (deft) Weighted count Unwei ghted count Confidence limits r - 2se r + 2se Household members Use of improved drinking water sources WS.1 .5064 .03806 .075 5.292 2.300 7,776 914 0.430 0.583 Use of improved sanitation WS.5 .1227 .02094 .171 3.719 1.928 7,776 914 0.081 0.165 Primary school net attendance ratio (adjusted) ED.4 .7669 .01693 .022 2.332 1.527 1,949 1,455 0.733 0.801 Women Contraceptive prevalence rate RH.5 .0369 .00742 .201 .964 .982 913 623 0.022 0.052 Unmet need RH.6 .2967 .01880 .063 1.054 1.027 913 623 0.259 0.334 Antenatal care coverage (1+ times, skilled provider) RH.7 .6866 .03150 .046 1.627 1.276 525 354 0.624 0.750 Antenatal care coverage (4+ times, any provider) RH.8 .3688 .02850 .077 1.232 1.110 525 354 0.312 0.426 Skilled attendant at delivery RH.10 .6071 .05101 .084 3.850 1.962 525 354 0.505 0.709 Literacy rate (young women) ED.1 .5602 .05055 .090 3.444 1.856 479 333 0.459 0.661 Knowledge about HIV prevention (young women) HA.1 .0351 .01243 .355 1.516 1.231 479 333 0.010 0.060 Under-5s Underweight prevalence (moderate and severe) NU.2 .4486 .01842 .041 .867 .931 861 633 0.412 0.485 Underweight prevalence (severe) NU.2 .1691 .01586 .094 1.132 1.064 861 633 0.137 0.201 286 Table SE.19: Sampling errors: West Darfor state Standard errors, coefficients of variation, design effects (deff), square root of design effects (deft) and confidence intervals for selected indicators, Sudan, 2014 Table Value (r) Stand ard error (se) Coefficie nt of variation (se/r) Design effect (deff) Square root of design effect (deft) Weighted count Unwei ghted count Confidence limits r - 2se r + 2se Household members Use of improved drinking water sources WS.1 .6753 .04993 .074 10.269 3.205 3,023 904 0.575 0.775 Use of improved sanitation WS.5 .1598 .04546 .284 13.899 3.728 3,023 904 0.069 0.251 Primary school net attendance ratio (adjusted) ED.4 .6027 .03358 .056 6.490 2.548 841 1,379 0.536 0.670 Women Contraceptive prevalence rate RH.5 .0411 .01053 .256 1.780 1.334 383 634 0.020 0.062 Unmet need RH.6 .2116 .01755 .083 1.168 1.081 383 634 0.176 0.247 Antenatal care coverage (1+ times, skilled provider) RH.7 .7523 .04653 .062 3.450 1.857 179 298 0.659 0.845 Antenatal care coverage (4+ times, any provider) RH.8 .5611 .05271 .094 3.350 1.830 179 298 0.456 0.666 Skilled attendant at delivery RH.10 .5775 .05597 .097 3.813 1.953 179 298 0.466 0.689 Literacy rate (young women) ED.1 .5006 .05521 .110 4.304 2.075 214 354 0.390 0.611 Knowledge about HIV prevention (young women) HA.1 .1593 .03605 .226 3.425 1.851 214 354 0.087 0.231 Under-5s Underweight prevalence (moderate and severe) NU.2 .2937 .02680 .091 1.264 1.124 223 366 0.240 0.347 Underweight prevalence (severe) NU.2 .0988 .01884 .191 1.455 1.206 223 366 0.061 0.136 287 Table SE.20: Sampling errors: South Darfur state Standard errors, coefficients of variation, design effects (deff), square root of design effects (deft) and confidence intervals for selected indicators, Sudan, 2014 Table Value (r) Standar d error (se) Coeffici ent of variatio n (se/r) Design effect (deff) Square root of design effect (deft) Weighted count Unweig hted count Confidence limits r - 2se r + 2se Household members Use of improved drinking water sources WS.1 .4664 .04692 .101 8.359 2.891 7,712 946 0.373 0.560 Use of improved sanitation WS.5 .2472 .03434 .139 5.990 2.448 7,712 946 0.178 0.316 Primary school net attendance ratio (adjusted) ED.4 .6620 .03067 .046 6.087 2.467 1,975 1,449 0.601 0.723 Women Contraceptive prevalence rate RH.5 .0543 .01614 .297 3.605 1.899 933 712 0.022 0.087 Unmet need RH.6 .3181 .01978 .062 1.283 1.133 933 712 0.278 0.358 Antenatal care coverage (1+ times, skilled provider) RH.7 .6179 .05115 .083 4.555 2.134 556 412 0.516 0.720 Antenatal care coverage (4+ times, any provider) RH.8 .4087 .03777 .092 2.426 1.557 556 412 0.333 0.484 Skilled attendant at delivery RH.10 .4869 .04648 .095 3.555 1.885 556 412 0.394 0.580 Literacy rate (young women) ED.1 .4929 .04974 .101 4.375 2.092 567 443 0.393 0.592 Knowledge about HIV prevention (young women) HA.1 .0547 .01276 .233 1.391 1.179 567 443 0.029 0.080 Under-5s Underweight prevalence (moderate and severe) NU.2 .2936 .02398 .082 2.499 1.581 1,231 902 0.246 0.342 Underweight prevalence (severe) NU.2 .0986 .01350 .137 1.848 1.359 1,231 902 0.072 0.126 288 Table SE.21: Sampling errors: Central Darfur state Standard errors, coefficients of variation, design effects (deff), square root of design effects (deft) and confidence intervals for selected indicators, Sudan, 2014 Table Value (r) Stand ard error (se) Coeffic ient of variati on (se/r) Design effect (deff) Square root of design effect (deft) Weighted count Unweig hted count Confidence limits r - 2se r + 2se Household members Use of improved drinking water sources WS.1 .5059 .07838 .155 23.444 4.842 1,646 955 0.349 0.663 Use of improved sanitation WS.5 .1580 .02303 .146 3.803 1.950 1,646 955 0.112 0.204 Primary school net attendance ratio (adjusted) ED.4 .5415 .05304 .098 16.361 4.045 449 1,445 0.435 0.648 Women Contraceptive prevalence rate RH.5 .0290 .00843 .291 1.532 1.238 188 608 0.012 0.046 Unmet need RH.6 .2785 .02653 .095 2.126 1.458 188 608 0.225 0.332 Antenatal care coverage (1+ times, skilled provider) RH.7 .6790 .03503 .052 1.841 1.357 99 328 0.609 0.749 Antenatal care coverage (4+ times, any provider) RH.8 .4714 .04635 .098 2.819 1.679 99 328 0.379 0.564 Skilled attendant at delivery RH.10 .3748 .05416 .145 4.094 2.023 99 328 0.266 0.483 Literacy rate (young women) ED.1 .2742 .04225 .154 2.897 1.702 104 324 0.190 0.359 Knowledge about HIV prevention (young women) HA.1 .0249 .01168 .470 1.816 1.348 104 324 0.002 0.048 Under-5s Underweight prevalence (moderate and severe) NU.2 .4102 .04413 .108 4.412 2.100 163 549 0.322 0.499 Underweight prevalence (severe) NU.2 .1848 .03031 .164 3.343 1.828 163 549 0.124 0.245 289 Table SE.22: Sampling errors: East Darfur state Standard errors, coefficients of variation, design effects (deff), square root of design effects (deft) and confidence intervals for selected indicators, Sudan, 2014 Table Value (r) Standar d error (se) Coeffici ent of variatio n (se/r) Design effect (deff) Square root of design effect (deft) Weight ed count Unweig hted count Confidence limits r - 2se r + 2se Household members Use of improved drinking water sources WS.1 .4507 .03377 .075 4.290 2.071 3,158 932 0.383 0.518 Use of improved sanitation WS.5 .1444 .03515 .243 9.307 3.051 3,158 932 0.074 0.215 Primary school net attendance ratio (adjusted) ED.4 .6205 .03775 .061 9.579 3.095 859 1,584 0.545 0.696 Women Contraceptive prevalence rate RH.5 .0616 .01289 .209 1.909 1.382 378 665 0.036 0.087 Unmet need RH.6 .3092 .01968 .064 1.204 1.097 378 665 0.270 0.349 Antenatal care coverage (1+ times, skilled provider) RH.7 .8293 .03000 .036 2.353 1.534 211 371 0.769 0.889 Antenatal care coverage (4+ times, any provider) RH.8 .4680 .04603 .098 3.149 1.774 211 371 0.376 0.560 Skilled attendant at delivery RH.10 .6055 .04941 .082 3.781 1.945 211 371 0.507 0.704 Literacy rate (young women) ED.1 .3998 .03829 .096 2.285 1.512 201 375 0.323 0.476 Knowledge about HIV prevention (young women) HA.1 .0138 .00802 .579 1.761 1.327 201 375 0.000 0.030 Under-5s Underweight prevalence (moderate and severe) NU.2 .4024 .02869 .071 2.734 1.654 457 800 0.345 0.460 Underweight prevalence (severe) NU.2 .1658 .01973 .119 2.249 1.500 457 800 0.126 0.205 290 Appendix D: Data Quality Tables Table DQ.1: Age distribution of household population Single-year age distribution of household population by sex, Sudan MICS, 2014 Age (Years) Males Females Missing Number Percent Number Percent Number Percent 0 1,632 3.3 1568 3.2 0 0.0 1 1,406 2.9 1427 2.9 0 0.0 2 1,436 2.9 1390 2.8 0 0.0 3 1,742 3.5 1757 3.5 0 0.0 4 1,395 2.8 1297 2.6 0 0.0 5 1,847 3.7 1837 3.7 0 0.0 6 1,581 3.2 1622 3.3 0 0.0 7 1,626 3.3 1758 3.5 0 0.0 8 1,647 3.3 1548 3.1 0 0.0 9 1,334 2.7 1270 2.6 0 0.0 10 1,657 3.4 1522 3.1 0 0.0 11 1,128 2.3 1141 2.3 0 0.0 12 1,578 3.2 1524 3.1 1 5.4 13 1,081 2.2 1156 2.3 0 0.0 14 1,097 2.2 1562 3.2 0 0.0 15 1,059 2.1 848 1.7 0 0.0 16 964 2.0 860 1.7 0 0.0 17 864 1.8 891 1.8 0 0.0 18 1,184 2.4 1159 2.3 0 0.0 19 639 1.3 693 1.4 0 0.0 20 1,094 2.2 1202 2.4 1 4.2 21 491 1.0 567 1.1 0 0.0 22 764 1.5 760 1.5 0 2.4 23 566 1.1 540 1.1 0 0.0 24 548 1.1 601 1.2 0 0.0 25 985 2.0 1221 2.5 0 0.0 26 483 1.0 625 1.3 0 0.0 27 502 1.0 708 1.4 0 0.0 28 593 1.2 662 1.3 0 0.0 29 362 0.7 549 1.1 0 0.0 30 1,162 2.4 1266 2.6 0 0.0 31 313 0.6 343 0.7 0 0.0 32 519 1.1 551 1.1 0 0.0 33 313 0.6 318 0.6 0 0.0 34 358 0.7 375 0.8 0 0.0 35 1,172 2.4 1160 2.3 0 0.0 36 312 0.6 319 0.6 0 0.0 291 Age (Years) Males Females Missing Number Percent Number Percent Number Percent 37 403 0.8 532 1.1 0 0.0 38 375 0.8 443 0.9 0 0.0 39 336 0.7 366 0.7 0 0.0 40 1,142 2.3 843 1.7 0 0.0 41 222 0.5 229 0.5 0 0.0 42 328 0.7 309 0.6 0 0.0 43 154 0.3 204 0.4 0 0.0 44 219 0.4 228 0.5 0 0.0 45 946 1.9 725 1.5 0 0.0 46 222 0.4 188 0.4 0 0.0 47 192 0.4 228 0.5 0 0.0 48 222 0.5 192 0.4 0 0.0 49 208 0.4 193 0.4 0 0.0 50 852 1.7 1379 2.8 0 2.1 51 164 0.3 298 0.6 0 0.0 52 266 0.5 405 0.8 0 0.0 53 145 0.3 147 0.3 0 0.0 54 213 0.4 242 0.5 0 0.0 55 583 1.2 646 1.3 0 0.0 56 214 0.4 133 0.3 0 0.0 57 164 0.3 97 0.2 0 0.0 58 224 0.5 116 0.2 0 0.0 59 171 0.3 115 0.2 0 0.0 60 845 1.7 663 1.3 0 0.0 61 75 0.2 42 0.1 0 0.0 62 140 0.3 83 0.2 0 0.0 63 87 0.2 31 0.1 0 0.0 64 126 0.3 74 0.1 0 0.0 65 479 1.0 388 0.8 0 1.6 66 73 0.1 46 0.1 0 0.0 67 78 0.2 29 0.1 0 0.0 68 83 0.2 37 0.1 0 0.0 69 94 0.2 42 0.1 0 0.0 70 643 1.3 457 0.9 0 0.0 71 51 0.1 19 0.0 0 0.0 72 56 0.1 47 0.1 0 0.0 73 33 0.1 31 0.1 0 0.0 74 68 0.1 49 0.1 0 0.0 75 292 0.6 199 0.4 0 0.0 76 40 0.1 9 0.0 0 0.0 77 27 0.1 21 0.0 0 0.0 292 Age (Years) Males Females Missing Number Percent Number Percent Number Percent 78 25 0.1 11 0.0 0 0.0 79 19 0.0 17 0.0 0 0.0 80 225 0.5 182 0.4 0 0.0 81 19 0.0 3 0.0 0 0.0 82 17 0.0 12 0.0 0 0.0 83 12 0.0 12 0.0 0 0.0 84 26 0.1 14 0.0 0 0.0 85+ 229 0.5 192 0.4 0 0.0 DK/missing 24 0.0 12 0.0 17 84.3 Sudan 49,286 100.0 49577 100.0 21 100.0 Figure DQ.1: Household population by single ages, Sudan MICS, 2014 Note: The figure excludes 36 household members with unknown age and/or sex 0 200 400 600 800 1,000 1,200 1,400 1,600 1,800 2,000 0 5 10 15 20 25 30 35 40 45 50 55 60 65 70 75 80 85+ Number Age Males Females 293 Table DQ.2: Age distribution of eligible and interviewed women Household population of women age 10-54 years, interviewed women age 15-49 years, and percentage of eligible women who were interviewed, by five-year age groups, Sudan MICS, 2014 Age group (yrs) Household population of women age 10-54 years Interviewed women age 15-49 years Percentage of eligible women interviewed (Completion rate) Number Number Percent 10-14 6,905 . . . 15-19 4,451 3,842 20.3 86.3 20-24 3,670 3,274 17.3 89.2 25-29 3,765 3,467 18.3 92.1 30-34 2,854 2,645 14.0 92.7 35-39 2,820 2,631 13.9 93.3 40-44 1,812 1,694 8.9 93.4 45-49 1,526 1,389 7.3 91.0 50-54 2,471 . . . Total (15-49) 20,898 18,941 100.0 90.6 DQ.4: Age distribution of children in household and under-5 questionnaires Household population of children age 0-7 years, children age 0-4 years whose mothers/caretakers were interviewed, and percentage of under-5 children whose mothers/caretakers were interviewed, by single years of age, Sudan MICS, 2014 Single years age Household population of children 0-7 years Under-5s with completed interviews Percentage of eligible under- 5s interviewed (Completion rate) Number Number Percent 0 3,200 3,046 21.2 95.2 1 2,833 2,724 18.9 96.1 2 2,826 2,673 18.6 94.6 3 3,499 3,362 23.4 96.1 4 2,692 2,584 18.0 96.0 5 3,684 . . . 6 3,203 . . . 7 3,384 . . . Total (0-4) 15,050 14,388 100.0 95.6 Ratio of 5 to 4 1.37 294 DQ.5: Birth date reporting: Household population Percent distribution of household population by completeness of date of birth information, Sudan MICS, 2014 Background characteristics Completeness of reporting of month and year of birth Total Number of household members Year and month of birth Year of birth only Month of birth only Both missing Sudan 53.3 30.6 0.1 16.0 100.0 97,049 Age 0-4 84.9 12.9 0.1 2.2 100.0 14,752 5-14 65.4 25.7 0.1 8.8 100.0 29,332 15-24 54.4 31.7 0.1 13.9 100.0 15,853 25-49 36.5 40.5 0.1 22.9 100.0 24,480 50-64 22.1 43.5 0.2 34.1 100.0 8,496 65-84 15.3 40.7 0.2 43.8 100.0 3,708 85+ 8.4 40.0 0.0 51.6 100.0 370 DK/missing 0.0 24.1 0.0 75.9 100.0 58 State Northern 76.1 15.0 0.0 8.9 100.0 4,914 River Nile 73.0 26.3 0.0 0.7 100.0 5,202 Red Sea 57.0 25.6 0.1 17.3 100.0 4,351 Kassala 66.5 32.9 0.0 0.6 100.0 5,026 Gadarif 36.5 19.4 0.1 44.0 100.0 5,522 Khartoum 75.5 17.4 0.1 7.0 100.0 5,452 Gezira 75.6 11.7 0.1 12.6 100.0 6,096 White Nile 42.9 19.1 0.2 37.8 100.0 5,233 Sinnar 50.2 17.1 0.2 32.6 100.0 5,479 Blue Nile 79.0 19.0 0.0 2.0 100.0 5,837 North Kordofan 47.8 51.3 0.0 0.8 100.0 5,220 South Kordofan 61.8 29.8 0.2 8.2 100.0 6,144 West Kordofan 23.4 30.7 0.5 45.5 100.0 5,017 North Darfur 28.9 48.5 0.0 22.6 100.0 5,793 West Darfur 20.6 61.7 0.1 17.7 100.0 4,942 South Darfur 62.4 30.8 0.0 6.8 100.0 5,732 Central Darfur 18.1 81.2 0.0 0.7 100.0 5,244 East Darfur 57.4 19.8 0.1 22.8 100.0 5,845 Area Urban 60.7 25.7 0.1 13.5 100.0 29,481 Rural 50.1 32.8 0.1 17.0 100.0 67,568 295 DQ.6: Birth date and age reporting: Women Percent distribution of women age 15-49 years by completeness of date of birth/age information, Sudan MICS, 2014 Background characteristics Completeness of reporting of date of birth and age Total Number of women age 15- 49 years Year and month of birth Year of birth and age Year of birth only Age only Other/DK/ Missing Sudan 45.0 36.4 0.0 18.3 0.3 100.0 18,302 State Northern 80.7 15.9 0.0 3.4 0.0 100.0 1,083 River Nile 76.0 23.8 0.0 .1 0.1 100.0 1,027 Red Sea 56.7 31.0 0.0 12.1 0.2 100.0 826 Kassala 49.9 48.5 0.0 1.2 0.4 100.0 946 Gadarif 20.0 28.7 0.0 51.2 0.2 100.0 1,012 Khartoum 82.2 15.1 0.0 2.6 0.1 100.0 1,171 Gezira 75.9 14.4 0.0 9.4 0.2 100.0 1,347 White Nile 29.8 25.9 0.0 43.6 0.7 100.0 1,027 Sinnar 30.7 20.6 0.0 47.5 1.2 100.0 1,057 Blue Nile 65.8 32.5 0.0 1.6 0.1 100.0 1,079 North Kordofan 35.8 63.2 0.0 .3 0.6 100.0 949 South Kordofan 47.7 44.6 0.0 7.2 0.5 100.0 1,171 West Kordofan 13.1 25.4 0.0 61.0 0.6 100.0 863 North Darfur 15.5 56.2 0.0 28.2 0.1 100.0 901 West Darfur 13.9 62.9 0.0 23.0 0.2 100.0 918 South Darfur 49.1 41.9 0.0 9.0 0.0 100.0 1,065 Central Darfur 4.9 93.5 0.0 1.3 0.3 100.0 878 East Darfur 27.0 34.2 0.0 38.7 0.1 100.0 982 Area Urban 59.1 28.7 0.0 11.9 0.3 100.0 5,979 Rural 38.1 40.1 0.0 21.5 0.3 100.0 12,323 296 DQ.8: Birth date and age reporting: Under-5s Percent distribution children under 5 by completeness of date of birth/age information, Sudan MICS, 2014 Background characteristics Completeness of reporting of date of birth and age Total Number of under-5 children Year and month of birth Year of birth and age Year of birth only Age only Other/DK/ Missing Sudan 88.2 11.8 0.0 0.0 .0 100.0 14,081 State Northern 99.6 0.4 0.0 0.0 0.0 100.0 532 River Nile 95.6 4.4 0.0 0.0 0.0 100.0 565 Red Sea 94.6 5.2 0.0 0.2 0.0 100.0 404 Kassala 97.9 2.1 0.0 0.0 0.0 100.0 655 Gadarif 92.9 7.1 0.0 0.0 0.0 100.0 858 Khartoum 97.0 3.0 0.0 0.0 0.0 100.0 699 Gezira 98.8 1.3 0.0 0.0 0.0 100.0 800 White Nile 90.8 9.2 0.0 0.0 0.0 100.0 754 Sinnar 96.6 3.3 0.0 0.1 0.0 100.0 814 Blue Nile 99.3 .7 0.0 0.0 0.0 100.0 1,006 North Kordofan 95.5 4.5 0.0 0.0 0.0 100.0 750 South Kordofan 94.0 6.0 0.0 0.0 0.0 100.0 1,092 West Kordofan 49.4 50.6 0.0 0.0 0.0 100.0 741 North Darfur 80.1 19.9 0.0 0.0 0.0 100.0 885 West Darfur 45.4 54.4 0.0 0.1 0.0 100.0 843 South Darfur 96.7 3.3 0.0 0.0 0.0 100.0 975 Central Darfur 71.3 28.7 0.0 0.0 0.0 100.0 837 East Darfur 97.2 2.8 0.0 0.0 0.0 100.0 871 Area Urban 92.4 7.6 0.0 0.0 0.0 100.0 3,811 Rural 86.6 13.4 0.0 0.0 0.0 100.0 10,270 297 DQ.9: Birth date reporting: Children, adolescents and young people Percent distribution of children, adolescents and young people age 5-24 years by completeness of date of birth information, Sudan MICS, 2014 Background characteristics Completeness of reporting of month and year of birth Total Number of children, adolescents and young people age 5- 24 years Year and month of birth Year of birth only Month of birth only Both missing Sudan 61.5 27.8 0.1 10.6 100.0 45,185 State Northern 92.5 6.0 0.0 1.5 100.0 2,013 River Nile 85.2 14.8 0.0 0.0 100.0 2,169 Red Sea 74.7 17.4 0.0 7.9 100.0 1,795 Kassala 80.1 19.9 0.0 0.0 100.0 2,387 Gadarif 38.6 21.1 0.2 40.2 100.0 2,622 Khartoum 88.0 10.0 0.0 2.0 100.0 2,363 Gezira 85.6 7.5 0.0 6.8 100.0 2,797 White Nile 55.3 22.1 0.2 22.4 100.0 2,338 Sinnar 62.6 21.8 0.2 15.5 100.0 2,406 Blue Nile 92.6 7.0 0.0 0.4 100.0 2,773 North Kordofan 56.3 43.7 0.0 0.0 100.0 2,420 South Kordofan 71.1 24.7 0.1 4.0 100.0 2,917 West Kordofan 27.0 31.7 0.6 40.7 100.0 2,434 North Darfur 30.2 50.9 0.0 18.9 100.0 2,857 West Darfur 21.4 62.8 0.0 15.7 100.0 2,495 South Darfur 70.2 26.8 0.0 3.0 100.0 2,815 Central Darfur 13.7 86.2 0.0 0.2 100.0 2,645 East Darfur 73.4 16.8 0.0 9.8 100.0 2,939 Area Urban 70.9 20.8 0.1 8.2 100.0 13,434 Rural 57.5 30.8 0.1 11.6 100.0 31,751 298 DQ.10: Birth date reporting: First and last births Percent distribution of first and last births to women age 15-49 years by completeness of date of birth, Sudan MICS, 2014 Background characteristic s Completeness of reporting of date of birth Date of first birth Total Number of first births Date of last birth Total Number of last births Year and month of birth Year of birth only Complete d years since first birth only Other/ DK/ Missing Both month and year Year only Other/ DK/ Missing Sudan 76.1 19.1 4.7 0.0 100.0 11,701 84.5 13.0 2.5 100.0 10,075 State Northern 99.3 .7 0.0 0.0 100.0 607 99.0 1.0 0.0 100.0 501 River Nile 91.8 8.2 0.0 0.0 100.0 558 94.1 5.9 0.0 100.0 459 Red Sea 83.7 13.7 2.6 0.0 100.0 502 89.8 8.1 2.1 100.0 422 Kassala 92.5 7.5 0.0 0.0 100.0 636 95.7 4.3 0.0 100.0 540 Gadarif 56.5 16.7 26.8 0.0 100.0 701 81.1 9.2 9.7 100.0 597 Khartoum 94.0 5.8 0.2 0.0 100.0 651 95.8 4.0 0.2 100.0 552 Gezira 98.2 1.6 0.1 0.0 100.0 733 99.0 1.0 0.0 100.0 605 White Nile 77.8 17.1 5.1 0.0 100.0 643 87.0 10.0 3.0 100.0 532 Sinnar 73.0 17.7 8.9 0.5 100.0 666 90.1 8.1 1.8 100.0 565 Blue Nile 98.5 1.5 0.0 0.0 100.0 733 99.7 0.3 0.0 100.0 631 North Kordofan 73.4 26.2 0.2 0.2 100.0 602 88.5 11.5 0.0 100.0 521 South Kordofan 94.7 5.1 0.3 0.0 100.0 789 96.3 3.3 0.4 100.0 697 West Kordofan 42.1 29.7 28.2 0.0 100.0 582 49.4 35.4 15.1 100.0 522 North Darfur 54.7 43.5 1.8 0.0 100.0 623 73.4 25.0 1.6 100.0 563 West Darfur 27.1 62.3 10.5 0.2 100.0 657 38.6 51.5 10.0 100.0 581 South Darfur 82.8 17.1 0.1 0.0 100.0 721 93.4 6.1 0.5 100.0 622 Central Darfur 23.4 76.0 0.6 0.0 100.0 624 50.4 49.0 0.5 100.0 569 East Darfur 96.6 2.4 1.0 0.0 100.0 673 97.5 1.5 1.0 100.0 596 Area Urban 83.6 12.5 3.9 0.1 100.0 3,398 88.9 8.3 2.8 100.0 2,926 Rural 73.0 21.8 5.1 0.0 100.0 8,303 82.7 14.9 2.4 100.0 7,149 Table DQ.11: Completeness of reporting Percentage of observations that are missing information for selected questions and indicators, Sudan MICS, 2014 Household Missing Information Percent with missing/incomplete information* Number of cases Salt test result 0.6 16,801 Starting time of interview 2.0 16,801 Ending time of interview 1.7 16,801 299 Table DQ.11: Completeness of reporting Percentage of observations that are missing information for selected questions and indicators, Sudan MICS, 2014 Women (Missing Information) Percent with missing/incomplete information* Number of cases Date of first marriage/union: Only month 30.4 12,755 Date of first marriage/union: Both month and year 25.1 12,755 Age at first marriage/union 0.0 12,755 Starting time of interview 0.0 18,302 Ending time of interview 0.0 18,302 DQ.12: Completeness of information for anthropometric indicators: Underweight Percent distribution of children under 5 by completeness of information on date of birth and weight, Sudan MICS, 2014 Background characteristics Valid weight and date of birth Reason for exclusion from analysis Total Percent of children excluded from analysis Number of children under 5 Weight not measured Incomplete date of birth Weight not measured, incomplete date of birth Flagged cases (outliers) Sudan 80.7 7.0 10.6 1.2 0.4 100.0 19.3 14,081 Weight by age <6 months 83.3 8.6 5.8 0.3 1.9 100.0 16.7 1,543 6-11 months 88.9 6.7 3.9 0.2 0.3 100.0 11.1 1,423 12-23 months 85.1 5.9 7.5 0.8 0.7 100.0 14.9 2,641 24-35 months 81.6 6.9 10.5 0.8 0.1 100.0 18.4 2,647 36-47 months 75.6 7.4 14.7 2.3 0.0 100.0 24.4 3,217 48-59 months 75.6 7.0 15.3 1.8 0.2 100.0 24.4 2,610 300 DQ.13: Completeness of information for anthropometric indicators: Stunting Percent distribution of children under 5 by completeness of information on date of birth and length or height, Sudan MICS, 2014 Background characteristics Valid length/height and date of birth Reason for exclusion from analysis Total Percent of children excluded from analysis Number of children under 5 Length/ Height not measured Incomplete date of birth Length/Height not measured, incomplete date of birth Flagged cases (outliers) Sudan 78.2 8.4 10.5 1.3 1.6 100.0 21.8 14,081 Age <6 months 73.8 17.0 5.8 0.4 3.0 100.0 26.2 1,543 6-11 months 86.6 7.2 3.9 0.3 2.0 100.0 13.4 1,423 12-23 months 83.6 6.4 7.5 0.8 1.7 100.0 16.4 2,641 24-35 months 79.7 7.7 10.4 0.9 1.2 100.0 20.3 2,647 36-47 months 74.0 7.7 14.6 2.4 1.2 100.0 26.0 3,217 48-59 months 74.3 7.3 15.1 2.0 1.3 100.0 25.7 2,610 DQ.14: Completeness of information for anthropometric indicators: Wasting Percent distribution of children under 5 by completeness of information on weight and length or height, Sudan MICS, 2014 Background characteristics Valid weight and length/ height Reason for exclusion from analysis Total Percent of children excluded from analysis Number of children under 5 Weight not measured Length/ Height not measured Weight and length/ height not measured Flagged cases (outliers) Sudan 88.1 0.2 1.7 8.0 2.0 100.0 11.9 14,081 Age <6 months 77.7 0.3 8.9 8.6 4.5 100.0 22.3 1,543 6-11 months 90.0 0.4 1.1 6.5 2.1 100.0 10.0 1,423 12-23 months 90.3 0.1 0.6 6.6 2.4 100.0 9.7 2,641 24-35 months 89.8 0.3 1.2 7.5 1.2 100.0 10.2 2,647 36-47 months 88.5 0.2 0.7 9.4 1.2 100.0 11.5 3,217 48-59 months 88.7 0.2 0.7 8.6 1.8 100.0 11.3 2,610 301 DQ.15: Heaping in anthropometric measurements Distribution of weight and height/length measurements by digits reported for the decimal points, Sudan MICS, 2014 Digits Weight Height Number Percent Number Percent Sudan 12,924 100.0 12,959 100.0 0 1,431 11.1 3,657 28.2 1 1,247 9.6 970 7.5 2 1,357 10.5 1,511 11.7 3 1,261 9.8 1,348 10.4 4 1,265 9.8 1,063 8.2 5 1,366 10.6 1,195 9.2 6 1,296 10.0 852 6.6 7 1,291 10.0 899 6.9 8 1,214 9.4 692 5.3 9 1,196 9.3 772 6.0 0 or 5 14,290 110.6 14,154 109.2 Figure DQ.2: Weight and height/length measurements by digits reported for the decimal points, Sudan MICS, 2014 11 10 11 10 10 11 10 10 9 9 28 8 12 10 8 9 7 7 5 6 0 5 10 15 20 25 30 0 1 2 3 4 5 6 7 8 9 P er c en t Digits reported Weight Height or length 302 DQ: 16: Observation of birth certificates Percent distribution of children under 5 by presence of birth certificates, and percentage of birth certificates seen, Sudan MICS, 2014 Background characteristics Child has birth certificate Child does not have birth certificate Missing/ DK Total Percentage of birth certificates seen by the interviewer (1)/(1+2)*100 Number of children under age 5 Seen by the interviewer (1) Not seen by the interviewer (2) Sudan 21.6 25.9 52.1 0.5 100.0 45.5 14,081 State Northern 43.8 41.5 14.7 0.0 100.0 51.3 532 River Nile 26.5 50.4 23.0 0.0 100.0 34.5 565 Red Sea 32.9 33.2 33.7 0.2 100.0 49.8 404 Kassala 23.2 22.7 53.1 0.9 100.0 50.5 655 Gadarif 20.3 32.4 46.9 0.5 100.0 38.5 858 Khartoum 40.3 42.2 17.5 0.0 100.0 48.9 699 Gezira 40.9 24.1 34.6 0.4 100.0 62.9 800 White Nile 21.8 28.8 48.8 0.7 100.0 43.0 754 Sinnar 30.8 28.7 40.4 0.0 100.0 51.8 814 Blue Nile 30.6 14.4 54.6 0.4 100.0 68.0 1,006 North Kordofan 23.9 24.9 51.1 0.1 100.0 48.9 750 South Kordofan 17.6 20.9 61.0 0.5 100.0 45.7 1,092 West Kordofan 5.0 27.9 66.0 1.1 100.0 15.2 741 North Darfur 9.8 27.2 62.4 0.6 100.0 26.5 885 West Darfur 10.9 27.6 61.2 0.2 100.0 28.3 843 South Darfur 12.1 22.1 65.3 0.5 100.0 35.4 975 Central Darfur 7.5 12.2 79.5 0.8 100.0 38.2 837 East Darfur 10.9 9.0 79.1 1.0 100.0 54.9 871 Area Urban 37.6 35.8 26.2 0.3 100.0 51.2 3,811 Rural 15.6 22.2 61.7 0.5 100.0 41.3 10,270 Child's age 0-5 months 10.8 15.6 73.2 0.5 100.0 41.0 1,543 6-11 months 21.8 22.6 55.4 0.2 100.0 49.1 1,423 12-23 months 19.5 25.3 54.7 0.5 100.0 43.6 2,641 24-35 months 24.9 27.2 47.3 0.6 100.0 47.9 2,647 36-47 months 23.3 29.3 46.8 0.6 100.0 44.4 3,217 48-59 months 24.3 28.9 46.5 0.3 100.0 45.7 2,610 303 DQ.17: Observation of vaccination cards Percent distribution of children age 0-35 months by presence of a vaccination card, and the percentage of vaccination cards seen by the interviewers, Sudan MICS, 2014 Background characteristics Child does not have vaccination card Child has vaccination card Missing /DK Total Percent of vaccination cards seen by the interviewer (1)/(1+2)*100 Number of children age 0-35 months Had vaccination card previously Never had vaccinatio n card Seen by the interviewer (1) Not seen by the interviewer (2) Sudan 2.7 20.0 36.7 39.4 1.2 100.0 48.2 8,254 State Northern 1.3 7.2 53.1 38.4 0.0 100.0 58.0 320 River Nile 2.5 11.1 29.7 56.7 0.0 100.0 34.4 323 Red Sea 1.7 30.5 17.6 48.1 2.1 100.0 26.8 233 Kassala 3.1 28.4 33.2 34.8 0.5 100.0 48.9 391 Gadarif 5.7 14.8 36.1 43.0 0.4 100.0 45.7 526 Khartoum 0.7 5.1 47.4 46.2 0.5 100.0 50.7 409 Gezira 2.6 20.6 42.8 34.0 0.0 100.0 55.7 470 White Nile 1.7 16.6 29.1 50.9 1.7 100.0 36.4 464 Sinnar 2.7 12.8 44.1 39.8 .6 100.0 52.6 483 Blue Nile 1.8 7.6 65.4 25.0 .2 100.0 72.4 616 North Kordofan 3.6 19.2 32.9 42.0 2.6 100.0 43.9 417 South Kordofan 4.0 15.7 37.5 40.6 2.2 100.0 48.1 626 West Kordofan 1.9 36.0 14.6 46.2 1.4 100.0 24.0 431 North Darfur 3.6 19.0 39.0 35.4 3.0 100.0 52.4 505 West Darfur 2.5 23.7 19.7 51.9 2.3 100.0 27.5 472 South Darfur 2.9 32.6 27.5 36.1 1.0 100.0 43.3 596 Central Darfur 1.5 33.7 39.9 23.2 2.1 100.0 63.3 466 East Darfur 2.4 27.5 36.2 33.4 0.8 100.0 52.0 506 Area Urban 1.8 11.1 44.2 41.4 1.5 100.0 51.6 2,252 Rural 3.0 23.4 33.9 38.7 1.1 100.0 46.7 6,002 Child's age 0-5 months 0.9 47.3 33.8 17.3 0.8 100.0 66.2 1,543 6-11 months 1.5 14.9 48.6 34.6 0.4 100.0 58.4 1,423 12-23 months 2.2 14.1 42.5 40.7 0.6 100.0 51.1 2,641 24-35 months 4.7 12.8 26.3 53.7 2.5 100.0 32.8 2,647 304 DQ.18: Observation of women's health cards Percent distribution of women with a live birth in the last 2 years by presence of a health card, and the percentage of health cards seen by the interviewers, Sudan MICS, 2014 Background characteristics Woman does not have health card Woman has health card Missing/ DK Total Percent of health cards seen by the interviewer (1)/(1+2)*100 Number of women with a live birth in the last two years Seen by the interviewer (1) Not seen by the interviewer (2) Sudan 53.3 9.2 35.6 1.9 100.0 20.6 5,684 State Northern 44.9 8.3 46.3 0.5 100.0 15.3 216 River Nile 30.2 6.9 61.2 1.7 100.0 10.1 232 Red Sea 54.4 11.4 30.9 3.4 100.0 27.0 149 Kassala 62.0 9.2 27.3 1.5 100.0 25.3 271 Gadarif 63.7 4.6 30.8 0.9 100.0 13.0 347 Khartoum 45.6 5.1 47.8 1.5 100.0 9.7 274 Gezira 56.3 13.5 29.6 0.6 100.0 31.3 334 White Nile 59.5 5.5 34.1 1.0 100.0 13.8 311 Sinnar 53.3 6.5 39.3 0.9 100.0 14.2 338 Blue Nile 60.5 13.0 25.1 1.4 100.0 34.2 423 North Kordofan 58.5 5.8 32.3 3.4 100.0 15.2 294 South Kordofan 53.1 9.8 35.8 1.3 100.0 21.5 450 West Kordofan 68.8 6.0 21.3 3.9 100.0 22.1 282 North Darfur 46.6 8.2 43.2 2.0 100.0 15.9 354 West Darfur 47.0 8.4 41.3 3.4 100.0 16.9 298 South Darfur 47.8 9.5 40.0 2.7 100.0 19.1 412 Central Darfur 39.0 22.0 36.9 2.1 100.0 37.3 328 East Darfur 60.6 9.7 27.2 2.4 100.0 26.3 371 Area Urban 40.2 12.7 45.1 2.0 100.0 22.0 1,503 Rural 58.0 8.0 32.2 1.8 100.0 19.8 4,181 305 DQ.20: Respondent to the under-5 questionnaire Distribution of children under five by whether the mother lives in the same household, and the person who was interviewed for the under-5 questionnaire, Sudan MICS, 2014 Age of children Mother in the household Mother not in the household and primary caretaker identified: Total Number of children under 5 Father Other adult female Other adult male Sudan 98.0 0.1 1.9 0.0 100.0 15,050 Age (yrs) 0 99.5 0.0 0.5 0.0 100.0 3,200 1 98.6 0.0 1.4 0.0 100.0 2,833 2 97.6 0.2 2.2 0.0 100.0 2,826 3 97.2 0.0 2.7 0.1 100.0 3,499 4 97.2 0.1 2.6 0.0 100.0 2,692 DQ.21: Selection of children age 1-17 years for the child labour and child discipline modules Percent distribution of households by the number of children age 1-17 years, and the percentage of households with at least two children age 1-17 years where correct selection of one child for the child labour and child discipline modules was performed, Sudan MICS, 2014 Background characteristics Number of children age 1-17 years Number of households Percent of households where correct selection was performed Number of households with 2 or more children age 1-17 years None One Two or more Total Sudan 18.8 15.1 66.1 100.0 16,801 94.5 11,100 State Northern 30.6 17.6 51.8 100.0 957 98.6 496 River Nile 27.2 17.3 55.5 100.0 928 95.9 515 Red Sea 32.5 18.2 49.2 100.0 928 95.6 457 Kassala 19.4 17.0 63.6 100.0 899 95.8 572 Gadarif 17.8 14.7 67.5 100.0 947 94.7 639 Khartoum 21.4 15.9 62.8 100.0 921 96.7 578 Gezira 19.5 12.9 67.6 100.0 988 97.2 668 White Nile 20.6 17.8 61.6 100.0 912 94.7 562 Sinnar 22.5 15.3 62.2 100.0 955 95.1 594 Blue Nile 15.5 13.8 70.6 100.0 954 96.9 674 North Kordofan 21.6 13.6 64.9 100.0 928 90.7 602 South Kordofan 12.9 13.4 73.7 100.0 961 92.9 708 West Kordofan 17.8 15.1 67.1 100.0 872 90.8 585 North Darfur 11.3 12.0 76.7 100.0 914 95.3 701 West Darfur 13.6 15.7 70.7 100.0 904 93.3 639 South Darfur 10.8 15.9 73.4 100.0 946 95.4 694 Central Darfur 13.8 13.5 72.7 100.0 955 89.5 694 East Darfur 10.2 12.3 77.5 100.0 932 94.3 722 Area Urban 19.9 14.8 65.3 100.0 4,825 94.4 3,151 306 Background characteristics Number of children age 1-17 years Number of households Percent of households where correct selection was performed Number of households with 2 or more children age 1-17 years None One Two or more Total Rural 18.4 15.2 66.4 100.0 11,976 94.6 7,949 Wealth index quintile Poorest 14.1 13.7 72.2 100.0 3,543 94.2 2,557 Second 18.2 15.8 66.0 100.0 4,304 93.3 2,841 Middle 18.8 14.4 66.8 100.0 3,502 94.5 2,340 Fourth 21.0 14.8 64.3 100.0 2,750 95.6 1,767 Richest 24.0 17.0 59.0 100.0 2,702 96.1 1,595 DQ.22: School attendance by single age Distribution of household population age 5-24 years by educational level and and grade attended in the current (or most recent) school year, Sudan MICS, 2014 Single age (yrs) Not attend ing school Khalw a Assas vocati onal trainin g Univer sity Above Univer sity Not able to deter mine DK/ Missin g Missin g Total Number of household members Age at beginning of school year 5 65.0 9.2 25.2 0.0 - 0.0 - 0.4 0.3 100.0 3,561 6 32.2 7.4 60.0 0.0 - 0.0 - 0.3 0.0 100.0 3,142 7 19.8 5.4 74.6 0.0 - 0.0 - 0.0 0.1 100.0 3,311 8 15.2 5.5 79.1 0.0 - .0 - 0.0 0.2 100.0 3,204 9 10.6 5.3 83.9 0.0 - 0.0 - 0.0 0.1 100.0 2,640 10 11.8 4.4 83.8 0.0 - 0.0 - 0.1 0.0 100.0 3,063 11 9.5 4.0 86.3 0.0 0 0.0 - 0.1 0.1 100.0 2,289 12 12.9 4.4 81.6 0.0 0 0.0 - 1.0 0.0 100.0 3,051 13 16.1 3.6 73.1 0.0 - .0 - 7.2 0.0 100.0 2,277 14 20.8 3.4 53.9 0.1 0 0.0 - 21.6 0.0 100.0 2,593 15 28.1 2.4 37.0 0.2 1 0.0 - 31.6 0.0 100.0 1,873 16 34.4 2.1 23.7 0.3 1 0.0 - 37.8 0.1 100.0 1,835 17 41.3 1.8 14.9 0.8 4 0.0 - 36.9 0.0 100.0 1,790 18 51.4 2.1 9.6 0.3 8 0.0 - 28.3 0.1 100.0 2,230 19 54.4 1.5 5.0 0.1 16 0.0 - 22.8 0.0 100.0 1,415 20 70.0 1.0 3.9 0.1 14 0.0 - 10.9 0.3 100.0 2,201 21 65.5 .8 1.7 0.2 21 0.2 - 10.7 0.1 100.0 1,094 22 77.3 .7 2.2 0.0 12 0.3 - 7.9 0.0 100.0 1,491 23 78.8 .8 1.8 0.1 14 0.0 - 4.9 0.0 100.0 1,106 24 76.3 1.0 1.6 0.2 6 0.1 9.3 5.4 0.0 100.0 1,165 307 DQ.23: Sex ratio at birth among children ever born and living Sex ratio (number of males per 100 females) among children ever born (at birth), children living, and deceased children, by age of women, Sudan MICS, 2014 Age group Children Ever Born Children Living Children Deceased Number of women Sons Daughters Sex ratio at birth Sons Daughters Sex ratio Sons Daughters Sex ratio Sudan 27,074 25,171 1.08 24,425 23,134 1.06 2,649 2037 1.30 18,302 Age 15-19 317 307 1.03 296 294 1.01 21 13 1.62 3,655 20-24 1,773 1,596 1.11 1,652 1,505 1.10 121 91 1.33 3,150 25-29 4,487 4,201 1.07 4,133 3,925 1.05 354 276 1.28 3,415 30-34 5,166 4,931 1.05 4,740 4,572 1.04 426 359 1.19 2,593 35-39 6,575 6,107 1.08 5,921 5,621 1.05 654 486 1.35 2,527 40-44 4,651 4,227 1.10 4,133 3,830 1.08 518 397 1.30 1,639 45-49 4,105 3,802 1.08 3,550 3,387 1.05 555 415 1.34 1,323 308 DQ.24: Births by periods preceding the survey Number of births, percentage with complete birth date, sex ratio at birth, and calendar year ratio by calendar year, according to living, deceased, and total children (weighted, imputed), as reported in the birth histories, Sudan MICS, 2014 Background characteristics Number of births Percent with complete birth date [a] Sex ratio at birth [b] Period ratio [c] Living Dead Total Living Dead Total Living Dead Total Living Dead Total Sudan 46,821 4,245 51,066 78.3 64.4 77.2 104.4 131.2 106.3 na na na Years 0 2,935 147 3,082 93.3 79.2 92.6 105.3 157.2 107.3 na na na 1 2,601 161 2,762 91.7 77.9 90.9 101.5 113.1 102.2 95.2 102.7 95.6 2 2,528 167 2,695 89.0 64.4 87.5 105.7 139.3 107.5 88.4 90.9 88.6 3 3,116 206 3,323 83.3 69.0 82.4 98.7 117.7 99.8 124.2 118.4 123.8 4 2,490 182 2,671 83.4 68.1 82.3 105.5 204.5 110.1 78.8 89.6 79.4 5 3,205 199 3,404 78.6 68.8 78.1 98.9 138.6 100.8 121.6 102.8 120.3 6 2,781 205 2,986 80.1 70.1 79.4 98.4 139.5 100.8 92.1 102.0 92.7 7 2,836 203 3,039 75.3 66.3 74.7 94.4 178.5 98.4 104.9 100.1 104.5 8 2,628 201 2,829 73.5 65.8 72.9 108.0 96.1 107.1 105.5 96.1 104.7 9 2,147 215 2,362 77.2 65.8 76.2 103.4 99.2 103.0 19.4 16.8 19.1 10+ 19,555 2,358 21,913 72.4 60.5 71.1 108.2 129.7 110.3 na na na Five year periods 0-4 13,670 864 14,533 88.1 71.3 87.1 103.1 141.8 105.1 na na na 5-9 13,596 1,023 14,619 77.0 67.4 76.4 100.2 126.2 101.8 na na na 10-14 9,829 932 10,761 73.9 61.4 72.8 98.3 118.7 99.9 na na na 15-19 5,386 658 6,044 72.4 60.9 71.2 115.3 142.7 118.0 na na na 20+ 4,341 767 5,108 68.9 59.1 67.4 124.4 133.2 125.7 na na na na: not applicable [a] Both month and year of birth given. The inverse of the percent reported is the percent with incomplete and therefore imputed date of birth [b] (Bm/Bf) x 100, where Bm and Bf are the numbers of male and female births, respectively [c] (2 x Bt/(Bt-1 + Bt+1)) x 100, where Bt is the number of births in year t preceding the survey 309 DQ.25: Reporting of age at death in days Distribution of reported deaths under one month of age by age at death in days and the percentage of neonatal deaths reported to occur at ages 0-6 days, by 5-year periods preceding the survey (weighted, imputed), Sudan MICS, 2014 Age at death (days) Number of years preceding the survey Total 0-19 0-4 5-9 10-14 15-19 0 49 32 20 11 112 1 170 147 99 73 488 2 39 46 28 17 130 3 46 43 44 23 155 4 28 28 18 15 89 5 14 12 6 8 40 6 21 3 6 5 36 7 35 44 40 36 154 8 8 10 5 4 27 9 11 7 2 3 23 10 4 6 7 2 19 11 2 2 1 4 10 12 7 5 8 4 24 13 3 2 2 0 7 14 6 4 3 4 17 15 16 7 3 4 30 16 0 0 2 0 2 17 0 0 1 1 3 18 0 0 0 2 2 19 0 0 1 0 1 20 5 1 3 4 13 21 2 1 2 0 6 22 0 4 1 3 8 23 1 0 0 0 1 24 3 2 0 1 6 25 1 1 0 3 5 26 0 2 0 0 2 27 1 2 0 0 2 29 1 0 0 0 1 30 0 0 0 0 1 Total 0-30 476 410 301 228 1,415 Percent early neonatal* 77.2 75.5 73.5 67.0 74.3 * Deaths during the first 7 days (0-6), divided by deaths during the first month (0-30 days) 310 DQ.26: Reporting of age at death in months Distribution of reported deaths under two years of age by age at death in months and the percentage of infant deaths reported to occur at age under one month, by 5-year periods preceding the survey (weighted, imputed), Sudan MICS, 2014 Age at death (months) Number of years preceding the survey Total 0-19 0-4 5-9 10-14 15-19 0 476 410 301 228 1,415 1 62 35 37 25 159 2 28 29 27 16 101 3 28 32 27 19 107 4 22 19 24 6 71 5 29 35 17 11 92 6 23 32 24 9 87 7 20 42 25 23 110 8 21 18 30 11 81 9 15 25 52 8 100 10 4 6 9 7 26 11 4 7 3 2 17 12 68 124 118 80 390 13 3 1 2 0 6 14 2 3 2 0 8 15 0 0 3 3 6 16 2 2 1 2 6 17 0 3 0 2 5 18 2 6 7 8 24 19 3 0 0 0 4 20 3 0 3 0 5 21 0 2 1 0 2 23 1 1 - 0 2 Reported as 1 year 0 0 1 0 1 Total 0-11 684 660 552 340 2,236 Percent neonatal [b] 65.0 59.4 52.0 62.3 60.0 a] Includes deaths under one month reported in days [b] Deaths under one month, divided by deaths under one year 311 Appendix E: Sudan MICS 2014Indicators: Numerators and Denominators MICS INDICATOR Module54 Numerator Denominator MDG Indicator Reference55 MORTALITY 1.1 Neonatal mortality rate BH Probability of dying within the first month of life 1.2 Infant mortality rate BH Probability of dying between birth and the first birthday MDG 4.2 1.3 Post-neonatal mortality rate BH Difference between infant and neonatal mortality rates 1.4 Child mortality rate BH Probability of dying between the first and the fifth birthdays 1.5 Under-five mortality rate BH Probability of dying between birth and the fifth birthday MDG 4.1 NUTRITION 2.1a 2.1b Underweight prevalence AN Number of children under age 5 who fall below (a) minus two standard deviations (moderate and severe) (b) minus three standard deviations (severe) of the median weight for age of the WHO standard Total number of children under age 5 MDG 1.8 2.2a 2.2b Stunting prevalence AN Number of children under age 5 who fall below (a) minus two standard deviations (moderate and severe) (b) below minus three standard deviations (severe) of the median height for age of the WHO standard Total number of children under age 5 2.3a 2.3b Wasting prevalence AN Number of children under age 5 who fall below (a) minus two standard deviations (moderate and severe) (b) minus three standard deviations (severe) of the median weight for height of the WHO standard Total number of children under age 5 54Some indicators are constructed by using questions in several modules in the MICS questionnaires. In such cases, only the module(s) which contains most of the necessary information is indicated. 55Millennium Development Goals (MDG) indicators, effective 15 January 2008 - http://mdgs.un.org/unsd/mdg/Host.aspx?Content=Indicators/OfficialList.htm, accessed 10 June 2013. 312 MICS INDICATOR Module54 Numerator Denominator MDG Indicator Reference55 2.4 Overweight prevalence AN Number of children under age 5 who are above two standard deviations of the median weight for height of the WHO standard Total number of children under age 5 2.5 Children ever breastfed MN Number of women with a live birth in the last 2 years who breastfed theirlast live-born child at any time Total number of women with a live birth in the last 2 years 2.6 Early initiation of breastfeeding MN Number of women with a live birth in the last 2 yearswho put their last newborn to the breast within one hour of birth Total number of women with a live birth in the last 2 years 2.7 Exclusive breastfeeding under 6 months BD Number of infants under 6 months of age who are exclusively breastfed56 Total number of infants under 6 months of age 2.8 Predominant breastfeeding under 6 months BD Number of infants under 6 months of age who received breast milk as the predominant source of nourishment57 during the previous day Total number of infants under 6 months of age 2.9 Continued breastfeeding at 1 year BD Number of children age 12-15 months who received breast milk during the previous day Total number of children age 12-15 months 2.10 Continued breastfeeding at 2 years BD Number of children age 20-23 months who received breast milk during the previous day Total number of children age 20-23 months 2.11 Duration of breastfeeding BD The age in months when 50 percent of children age 0-35 months did not receive breast milk during the previous day 2.12 Age-appropriate breastfeeding BD Number of children age 0-23 months appropriately fed 58 during the previous day Total number of children age 0-23 months 2.13 Introduction of solid, semi-solid or soft foods BD Number of infants age 6-8 months who received solid, semi- solid or soft foods during the previous day Total number of infants age 6-8 months 2.14 Milk feeding frequency for non-breastfed children BD Number of non-breastfed children age 6-23 months who received at least 2 milk feedings during the previous day Total number of non-breastfed children age 6-23 months 56Infants receiving breast milk, and not receiving any other fluids or foods, with the exception of oral rehydration solution, vitamins, mineral supplements and medicines 57Infants who receive breast milk and certain fluids (water and water-based drinks, fruit juice, ritual fluids, oral rehydration solution, drops, vitamins, minerals, and medicines), but do not receive anything else (in particular, non-human milk and food-based fluids) 58Infants age 0-5 months who are exclusively breastfed, and children age 6-23 months who are breastfed and ate solid, semi-solid or soft foods 313 MICS INDICATOR Module54 Numerator Denominator MDG Indicator Reference55 2.15 Minimum meal frequency BD Number of children age 6-23 months who received solid, semi- solid and soft foods (plus milk feeds for non-breastfed children) the minimum number of times59 or more during the previous day Total number of children age 6-23 months 59Breastfeeding children: Solid, semi-solid, or soft foods, two times for infants age 6-8 months, and three times for children 9-23 months; Non-breastfeeding children: Solid, semi-solid, or soft foods, or milk feeds, four times for children age 6-23 months 314 MICS INDICATOR Module54 Numerator Denominator MDG Indicator Reference55 2.16 Minimum dietary diversity BD Number of children age 6–23 months who received foods from 4 or more food groups60 during the previous day Total number of children age 6–23 months 2.17a 2.17b Minimum acceptable diet BD (a) Number of breastfed children age 6–23 months who had at least the minimum dietary diversity and the minimum meal frequency during the previous day (b) Number of non-breastfed children age 6–23 months who received at least 2 milk feedings and had at least the minimum dietary diversity not including milk feeds and the minimum meal frequency during the previous day (a) Number of breastfed children age 6–23 months (b) Number of non-breastfed children age 6–23 months 2.18 Bottle feeding BD Number of children age 0-23 months who were fed with a bottle during the previous day Total number of children age 0-23 months 2.19 Iodized salt consumption SI Number of households with salt testing 15 parts per million or more of iodide/iodate Total number of households in which salt was tested or where there was no salt 2.20 Low-birthweight infants MN Number of most recent live births in the last 2 yearsweighing below 2,500 grams at birth Total number of most recent live births in the last 2 years 2.21 Infants weighed at birth MN Number ofmost recent live births in the last 2 years who were weighed at birth Total number of most recent live births in the last 2 years CHILD HEALTH 3.1 Tuberculosis immunization coverage IM Number of children age 12-23 months who received BCG vaccine by their first birthday Total number of children age 12-23 months 3.2 Polio immunization coverage IM Number of children age 12-23 months who received the third dose of OPV vaccine (OPV3) by their first birthday Total number of children age 12-23 months 3.3 3.5 3.6 Pentavalent (DPT+HepB+Hib) immunization coverage IM Number of children age 12-23 months who received the third dose of Pentavalent (DPT+HepB+Hib) vaccine by their first birthday Total number of children age 12-23 months 3.4 Measles immunization coverage61 IM Number of children age 12-23 months who received measles vaccine by their first birthday Total number of children age 12-23 months MDG 4.3 60The indicator is based on consumption of any amount of food from at least 4 out of the 7 following food groups: 1) grains, roots and tubers, 2) legumes and nuts, 3) dairy products (milk, yogurt, cheese), 4) flesh foods (meat, fish, poultry and liver/organ meats), 5) eggs, 6) vitamin-A rich fruits and vegetables, and 7) other fruits and vegetables 61In countries where measles vaccination is administered at or after 12 months of age according to the vaccination schedule, the indicator is calculated as the proportion of children age 24-35 months who received the measles vaccine by 24 months of age 315 MICS INDICATOR Module54 Numerator Denominator MDG Indicator Reference55 3.8 Full immunization coverage IM Number of children age 12-23 months who received all vaccinations recommended in the national immunization schedule by their first birthday Total number of children age 12-23 months 3.9 Neonatal tetanus protection MN Number of women age 15-49 years with a live birth in the last 2 years who were given at least two doses of tetanus toxoid vaccine within the appropriate interval62 prior to the most recent birth Total number of women age 15-49 years with a live birth in the last2 years 3.10 Care-seeking for diarrhoea CA Number of children under age 5 with diarrhoea in the last 2 weeks for whom advice or treatment was sought from a health facility or provider Total number of children under age 5 with diarrhoea in the last 2 weeks 3.11 Diarrhoea treatment with oral rehydration salts (ORS) and zinc CA Number of children under age 5 with diarrhoea in the last 2 weeks who received ORS and zinc Total number of children under age 5 with diarrhoea in the last 2 weeks 3.12 Diarrhoea treatment with oral rehydration therapy (ORT) and continued feeding CA Number of children under age 5 with diarrhoea in the last 2 weeks who received ORT (ORS packet, pre-packaged ORS fluid, recommended homemade fluid or increased fluids) and continued feeding during the episode of diarrhoea Total number of children under age 5 with diarrhoea in the last 2 weeks 3.13 Care-seeking for children with acute respiratory infection (ARI) symptoms CA Number of children under age 5 with ARI symptoms in the last 2 weeks for whom advice or treatment was sought from a health facility or provider Total number of children under age 5 with ARI symptoms in the last 2 weeks 3.14 Antibiotic treatment for children with ARI symptoms CA Number of children under age 5 with ARI symptoms in the last 2 weeks who received antibiotics Total number of children under age 5 withARI symptoms in the last 2 weeks 3.15 Use of solid fuels for cooking HC Number of household members in households that use solid fuels as the primary source of domestic energy to cook Total number of household members 62See the MICS tabulation plan for a detailed description 316 MICS INDICATOR Module54 Numerator Denominator MDG Indicator Reference55 WATER AND SANITATION 4.1 Use of improved drinking water sources WS Number of household members using improved sources of drinking water Total number of household members MDG 7.8 4.2 Water treatment WS Number of household members in households using unimproved drinking water who use an appropriate treatment method Total number of household members in households using unimproved drinking water sources 4.3 Use of improved sanitation WS Number of household members using improved sanitation facilities which are not shared Total number of household members MDG 7.9 4.4 Safe disposal of child’s faeces CA Number of children age 0-2 years whose last stools were disposed of safely Total number of children age 0-2 years 4.5 Place for handwashing HW Number of households with a specific place for hand washing where water and soap or other cleansing agent are present Total number of households 4.6 Availability of soap or other cleansing agent HW Number of households with soap or other cleansing agent Total number of households REPRODUCTIVE HEALTH 5.1 Adolescent birth rate63 BH Age-specific fertility rate for women age 15-19 years MDG 5.4 5.2 Early childbearing BH Number of women age 20-24 years who had at least one live birth before age 18 Total number of women age 20-24 years 5.3 Contraceptive prevalence rate CP Number of women age 15-49 years currently married or in union who are using (or whose partner is using) a (modern or traditional) contraceptive method Total number of women age 15-49 years who are currently married or in union MDG 5.3 5.4 Unmet need64 UN Number of women age 15-49 years who are currently married or in union who are fecund and want to space their births or limit the number of children they have and who are not currently using contraception Total number of women age 15-49 years who are currently married or in union MDG 5.6 63The indicator is calculated for the last 3-year period. 64See the MICS tabulation plan for a detailed description http://mics.unicef.org/tools#analysis 317 MICS INDICATOR Module54 Numerator Denominator MDG Indicator Reference55 5.5a 5.5b Antenatal care coverage MN Number of women age 15-49 years with a live birth in the last 2 years who were attended during their last pregnancy that led to a live birth (a) at least once by skilled health personnel (b) at least four times by any provider Total number of women age 15-49 years with a live birth in the last 2 years MDG 5.5 5.6 Content of antenatal care MN Number of women age 15-49 years with a live birth in the last 2 years who had their blood pressure measured and gave urine and blood samples during the last pregnancy that led to a live birth Total number of women age 15-49 years with a live birth in the last 2 years 5.7 Skilled attendant at delivery MN Number of women age 15-49 years with a live birth in the last 2 years who were attended by skilled health personnel during their most recent live birth Total number of women age 15-49 years with a live birth in the last 2 years MDG 5.2 5.8 Institutional deliveries MN Number of women age 15-49 years with a live birth in the last 2 years whose most recent live birth was delivered in a health facility Total number of women age 15-49 years with a live birth in the last 2 years 5.9 Caesarean section MN Number of women age 15-49 years whose most recent live birth in the last 2 years was delivered by caesarean section Total number of women age 15-49 years with a live birth in the last 2 years 5.10 Post-partum stay in health facility PN Number of women age 15-49 years who stayed in the health facility for 12 hours or more after the delivery of their most recent live birth in the last 2 years Total number of women age 15-49 years with a live birth in the last 2 years 5.11 Post-natal health check for the newborn PN Number of last live births in the last 2 yearswho received a health check while in facility or at home following delivery, or a post-natal care visit within 2 days after delivery Total number of last live births in the last 2 years 5.12 Post-natal health check for the mother PN Number of women age 15-49 years who received a health check while in facility or at home following delivery, or a post- natal care visit within 2 days after delivery of their most recent live birth in the last 2 years Total number of women age 15-49 years with a live birth in the last 2 years CHILD DEVELOPMENT 6.1 Attendance to early childhood education EC Number of children age 36-59 months who are attending an early childhood education programme Total number of children age 36-59 months 318 MICS INDICATOR Module54 Numerator Denominator MDG Indicator Reference55 6.5 Availability of children’s books EC Number of children under age 5 who have three or more children’s books Total number of children under age 5 6.6 Availability of playthings EC Number of children under age 5 with two or more types of playthings Total number of children under age 5 LITERACY AND EDUCATION 7.1 Literacy rate among young women [M] WB Number of women age 15-24 years who are able to read a short simple statement about everyday life or who attended secondary or higher education Total number of women age 15-24 years MDG 2.3 7.2 School readiness ED Number of children in first grade of primary school who attended pre-school during the previous school year Total number of children attending the first grade of primary school 7.3 Net intake rate in primary education ED Number of children of school-entry age who enter the first grade of primary school Total number of children of school-entry age 7.4 Primary school net attendance ratio (adjusted) ED Number of children of primary school age currently attending primary or secondary school Total number of children of primary school age MDG 2.1 7.5 Secondary school net attendance ratio (adjusted) ED Number of children of secondary school age currently attending secondary school or higher Total number of children of secondaryschool age 7.6 Children reaching last grade of primary ED Proportion of children entering the first grade of primary school who eventually reach last grade MDG 2.2 7.7 Primary completion rate ED Number of children attending the last grade of primary school (excluding repeaters) Total number of children of primary school completion age (age appropriate to final grade of primary school) 7.8 Transition rate to secondary school ED Number of children attending the last grade of primary school during the previous school year who are in the first grade of secondary school during the current school year Total number of children attending the last grade of primary school during the previous school year 7.9 Gender parity index (primary school) ED Primary school net attendance ratio (adjusted) for girls Primary school net attendance ratio (adjusted) for boys MDG 3.1 7.10 Gender parity index (secondary school) ED Secondary school net attendance ratio (adjusted) for girls Secondary school net attendance ratio (adjusted) for boys MDG 3.1 CHILD PROTECTION 319 MICS INDICATOR Module54 Numerator Denominator MDG Indicator Reference55 8.1 Birth registration BR Number of children under age 5 whose births are reported registered Total number of children under age 5 8.2 Child labour CL Number of children age 5-17 years who are involved in child labour65 Total number of children age 5-17 years 8.3 Violent discipline CD Number of children age 1-14 years who experienced psychological aggression or physical punishment during the last one month Total number of children age 1-14 years 8.4 Marriage before age 15[M] MA Number of women age 15-49 years who were first married before age 15 Total number of women age 15-49 years 8.5 Marriage before age 18[M] MA Number of women age 20-49 years who were first married before age 18 Total number of women age 20-49 years 8.6 Young women age 15-19 years currently married MA Number of women age 15-19 years who are married Total number of women age 15-19 years 8.7 Polygyny[M] MA Number of women age 15-49 years who are in a polygynous Total number of women age 15-49 years who are married or in union 8.8a 8.8b Spousal age difference MA Number of women who are married and whose spouse is 10 or more years older, (a) among women age 15-19 years, (b) among women age 20-24 years Total number of women who are married or in union (a) age 15-19 years, (b) age 20-24 years 8.9 Approval for female genital mutilation/cutting (FGM/C) FG Number of women age 15-49 years who state that FGM/C should be continued Total number of women age 15-49 years who have heard of FGM/C 8.10 Prevalence of FGM/C among women FG Number of women age 15-49 years who report to have undergone any form of FGM/C Total number of women age 15-49 years 8.11 Prevalence of FGM/C among girls FG Number of daughters age 0-14 years who have undergone any form of FGM/C, as reported by mothers age 15-49 years Total number of daughters age 0-14 yearsof mothers age 15-49 years 8.12 Attitudes towards domestic violence[M] DV Number of women who state that a husband is justified in hitting or beating his wife in at least one of the following circumstances: (1) she goes out without telling him, (2) she neglects the children, (3) she argues with him, (4) she refuses sex with him, (5) she burns the food Total number of women age 15-49 years 65Children involved in child labour are defined as children involved in economic activities above the age-specific thresholds, children involved in household chores above the age-specific thresholds, and children involved in hazardous work. See the MICS tabulation plan for more detailed information on thresholds and classifications 320 MICS INDICATOR Module54 Numerator Denominator MDG Indicator Reference55 8.13 Children’s living arrangements HL Number of children age 0-17 years living with neither biological parent Total number of children age 0-17 years 8.14 Prevalence of children with one or both parents dead HL Number of children age 0-17 years with one or both biologicalparents dead Total number of children age 0-17 years 8.15 Children with at least one parent living abroad HL Number of children 0-17 years with at least one biologicalparent living abroad Total number of children 0-17 years HIV/AIDS 9.1 Knowledge about HIV prevention among young women[M] HA Number of women age 15-24 years who correctly identify ways of preventing the sexual transmission of HIV66, and who reject major misconceptions about HIV transmission Total number of women age 15-24 years MDG 6.3 9.2 Knowledge of mother-to-child transmission of HIV[M] HA Number of women age 15-49 years who correctly identify all three means67 of mother-to-child transmission of HIV Total number of women age 15-49 years 9.3 Accepting attitudes towards people living with HIV[M] HA Number of women age 15-49 years expressing accepting attitudes on all four questions68 toward people living with HIV Total number of women age 15-49 years who have heard of HIV 9.4 Women who know where to be tested for HIV[M] HA Number of women age 15-49 years who state knowledge of a place to be tested for HIV Total number of women age 15-49 years 9.5 Women who have been tested for HIV and know the results [M] HA Number of women age 15-49 years who have been tested for HIV in the last 12 months and who know their results Total number of womenage 15-49 years 9.6 Sexually active young women who have been tested for HIV and know the results [M] HA Number of women age 15-24 years who have had sex in the last 12 months, who have been tested for HIV in the last 12 monthsand who know their results Total number of women age 15-24 years who have had sex in the last 12 months 9.7 HIV counselling during antenatal care HA Number of women age 15-49 years who had a live birth in the last 2 years and received antenatal care during the pregnancy of their most recent birth, reporting that they received counselling on HIV during antenatal care Total number of women age 15-49 years who had a live birth in the last 2 years 66Using condoms and limiting sex to one faithful, uninfected partner 67Transmission during pregnancy, during delivery, and by breastfeeding 68Women (1) who think that a female teacher with the AIDS virus should be allowed to teach in school, (2) who would buy fresh vegetables from a shopkeeper or vendor who has the AIDS virus, (3) who would not want to keep it as a secret if a family member became infected with the AIDS virus, and (4) who would be willing to care for a family member who became sick with the AIDS virus 321 MICS INDICATOR Module54 Numerator Denominator MDG Indicator Reference55 9.8 HIV testing during antenatal care HA Number of women age 15-49 years who had a live birth in the last 2 yearsand received antenatal care during the pregnancy of their most recent birth, reporting that they were offered and accepted an HIV test during antenatal care and received their results Total number of women age 15-49 years whohad a live birth in the last 2 years 9.16 Ratio of school attendance of orphans to school attendance of non-orphans HL - ED Proportion attending school among children age 10-14 years who have lost both parents Proportion attending school among children age 10-14 years whose parents are alive and who are living with one or both parents MDG 6.4 FOOD SECURITY CS.1 Food Consumption Score FS Number of households with poor/borderline/acceptable food consumption Total number of households CS.2 Dietary Diversity Score FS Number of household with average dietary diversity score (calculated on the entire population and on sub-groups) Total number of households CS.3 Coping strategy index FS Number of households using negative coping strategy Total number of households 322 Appendix F1: Household Questionnaire HOUSEHOLD QUESTIONNAIRE Sudan Multiple Indicator Survey 2014 HOUSEHOLD INFORMATION PANEL HH HH0.state code HH1. Cluster number: ___ ___ HH2. Household number: ___ ___ HH3. Interviewer’s name and number: HH4. Supervisor’s name and number: Name _________________________ ___ ___ Name__________________________ ___ ___ HH5. Day / Month / Year of interview: ___ ___ /___ ___ / 2 0 1 4 HH6. AREA: Urban . 1 Rural . 2 WE ARE FROM THE Central Bureau of Statistics. WE ARE CONDUCTING A SURVEY ABOUT THE SITUATION OF CHILDREN, FAMILIES AND HOUSEHOLDS. I WOULD LIKE TO TALK TO YOU ABOUT THESE SUBJECTS. THE INTERVIEW WILL TAKE ABOUT 35 MINUTES. ALL THE INFORMATION WE OBTAIN WILL REMAIN STRICTLY CONFIDENTIAL AND ANONYMOUS. MAY I START NOW? … Yes, permission is given Ö Go to HH18 to record the time and then begin the interview. … No, permission is not given Ö Circle 04 in HH9. Discuss this result with your supervisor. 323 HH9. Result of household interview: Completed . 01 No household member or no competent respondent at home at time of visit . 02 Entire household absent for extended period of time . 03 Refused . 04 Dwelling vacant / Address not a dwelling . 05 Dwelling destroyed . 06 Dwelling not found . 07 Other (specify) ________________________________________________________________ 96 After the household questionnaire has been completed, fill in the following information: HH10. Respondent to Household Questionnaire: Name _______________________ ___ ___ HH11. Total number of household members: ___ ___ After all questionnaires for the household have been completed, fill in the following information: HH12. Number of women age 15-49 years: ___ ___ HH13. Number of women’s questionnaires completed: ___ ___ HH14. Number of children under age 5: ___ ___ HH15. Number of under-5 questionnaires completed: ___ ___ HH16. Field editor’s name and number: Name______________________________ __ __ HH17. Main data entry clerk’s name and number: Name________________________________ __ __ Respondent mobile __ ___ __ ___ __ __ __ __ __ Researcher mobile __ __ __ __ __ __ __ __ __ __ 324 HH18. Record the time. Morning . 1 Afternoon . 2 Hour . __ __ Minutes . __ __ LIST OF HOUSEHOLD MEMBERS HL FIRST, PLEASE TELL ME THE NAME OF EACH PERSON WHO USUALLY LIVES HERE, STARTING WITH THE HEAD OF THE HOUSEHOLD. List the head of the household in line 01. List all household members (HL2), their relationship to the household head (HL3), and their sex (HL4) Then ask: ARE THERE ANY OTHERS WHO LIVE HERE, EVEN IF THEY ARE NOT AT HOME NOW? If yes, complete listing for questions HL2-HL4. Then, ask questions starting with HL5 for each person at a time. Use an additional questionnaire if all rows in the List of Household Members have been used. For women age 15-49 For children age 0-4 For children age 0-17 years For Children age 0-14 HL1 . Line no. HL2. Name HL3. WHAT IS THE RELATIO N-SHIP OF (name) TO THE HEAD OF HOUSE- HOLD? HL4. IS (name) MALE OR FEMALE? 1 Male 2 Female HL5. WHAT IS (name)’S DATE OF BIRTH? HL6. HOW OLD IS (name)? Record in completed years. If age is 95 or above, record ‘00’. HL7. Circle line no. if woman age 15-49. HL7B. Circle line no. if age 0-4. HL11. IS (name)’S NATURAL MOTHER ALIVE? 1 Yes 2 NoÞ HL13 8 DKÞ HL13 HL12. DOES (name)’S NATURAL MOTHER LIVE IN THIS HOUSE- HOLD? If “Yes”, record line no. of mother and go to HL13. If “No”, record 00. HL12A. WHERE DOES (ame)’S NATURAL MOTHER LIVE? 1 In another househol d in this country 2 Institution in this country 3 Abroad 8 DK HL13. IS (name)’S NATURAL FATHER ALIVE? 1 Yes 2 NoÞ HL15 8 DKÞ HL15 HL14. DOES (name)’S NATURAL FATHER LIVE IN THIS HOUSE- HOLD? If “Yes”, record line no. of father and go to HL15. If “No”, record 00. HL14A. WHERE DOES (name)’S NATURAL FATHER LIVE? 1 In another househol d in this country 2 Institutio n in this country 3 Abroad 8 DK HL15. Record line no. of mother from HL12 if indicated. If HL12 is blank or ‘00’ ask: WHO IS THE PRIMARY CARETAKER OF (name)? 98 DK 9998 DK Line Name Relatio n* M F Month Year Age 15-49 0-4 Y N DK Mother Y N DK Y N DK Father Mother 01 0 1 1 2 __ __ __ __ __ __ __ __ 01 01 1 2 8 ___ ___ 1 2 3 8 1 2 8 ___ ___ 1 2 3 8 ___ ___ 02 ___ ___ 1 2 __ __ __ __ __ __ __ __ 02 02 1 2 8 ___ ___ 1 2 3 8 1 2 8 ___ ___ 1 2 3 8 ___ ___ 03 ___ ___ 1 2 __ __ __ __ __ __ __ __ 03 03 1 2 8 ___ ___ 1 2 3 8 1 2 8 ___ ___ 1 2 3 8 ___ ___ 04 ___ ___ 1 2 __ __ __ __ __ __ __ __ 04 04 1 2 8 ___ ___ 1 2 3 8 1 2 8 ___ ___ 1 2 3 8 ___ ___ 05 ___ ___ 1 2 __ __ __ __ __ __ __ __ 05 05 1 2 8 ___ ___ 1 2 3 8 1 2 8 ___ ___ 1 2 3 8 ___ ___ 325 For women age 15-49 For children age 0-4 For children age 0-17 years For Children age 0-14 HL1 . Line no. HL2. Name HL3. WHAT IS THE RELATIO N-SHIP OF (name) TO THE HEAD OF HOUSE- HOLD? HL4. IS (name) MALE OR FEMALE? 1 Male 2 Female HL5. WHAT IS (name)’S DATE OF BIRTH? HL6. HOW OLD IS (name)? Record in completed years. If age is 95 or above, record ‘00’. HL7. Circle line no. if woman age 15-49. HL7B. Circle line no. if age 0-4. HL11. IS (name)’S NATURAL MOTHER ALIVE? 1 Yes 2 NoÞ HL13 8 DKÞ HL13 HL12. DOES (name)’S NATURAL MOTHER LIVE IN THIS HOUSE- HOLD? If “Yes”, record line no. of mother and go to HL13. If “No”, record 00. HL12A. WHERE DOES (ame)’S NATURAL MOTHER LIVE? 1 In another househol d in this country 2 Institution in this country 3 Abroad 8 DK HL13. IS (name)’S NATURAL FATHER ALIVE? 1 Yes 2 NoÞ HL15 8 DKÞ HL15 HL14. DOES (name)’S NATURAL FATHER LIVE IN THIS HOUSE- HOLD? If “Yes”, record line no. of father and go to HL15. If “No”, record 00. HL14A. WHERE DOES (name)’S NATURAL FATHER LIVE? 1 In another househol d in this country 2 Institutio n in this country 3 Abroad 8 DK HL15. Record line no. of mother from HL12 if indicated. If HL12 is blank or ‘00’ ask: WHO IS THE PRIMARY CARETAKER OF (name)? 98 DK 9998 DK Line Name Relatio n* M F Month Year Age 15-49 0-4 Y N DK Mother Y N DK Y N DK Father Mother 06 ___ ___ 1 2 __ __ __ __ __ __ __ __ 06 06 1 2 8 ___ ___ 1 2 3 8 1 2 8 ___ ___ 1 2 3 8 ___ ___ 07 ___ ___ 1 2 __ __ __ __ __ __ __ __ 07 07 1 2 8 ___ ___ 1 2 3 8 1 2 8 ___ ___ 1 2 3 8 ___ ___ 08 ___ ___ 1 2 __ __ __ __ __ __ __ __ 08 08 1 2 8 ___ ___ 1 2 3 8 1 2 8 ___ ___ 1 2 3 8 ___ ___ 09 ___ ___ 1 2 __ __ __ __ __ __ __ __ 09 09 1 2 8 ___ ___ 1 2 3 8 1 2 8 ___ ___ 1 2 3 8 ___ ___ 10 ___ ___ 1 2 __ __ __ __ __ __ __ __ 10 10 1 2 8 ___ ___ 1 2 3 8 1 2 8 ___ ___ 1 2 3 8 ___ ___ 11 ___ ___ 1 2 __ __ __ __ __ __ __ __ 11 11 1 2 8 ___ ___ 1 2 3 8 1 2 8 ___ ___ 1 2 3 8 ___ ___ 12 ___ ___ 1 2 __ __ __ __ __ __ __ __ 12 12 1 2 8 ___ ___ 1 2 3 8 1 2 8 ___ ___ 1 2 3 8 ___ ___ 13 ___ ___ 1 2 __ __ __ __ __ __ __ __ 13 13 1 2 8 ___ ___ 1 2 3 8 1 2 8 ___ ___ 1 2 3 8 ___ ___ Tick here if additional questionnaire used … 326 Probe for additional household members. Probe especially for any infants or small children not listed, and others who may not be members of the family (such as servants, friends) but who usually live in the household. Insert names of additional members in the household list and complete form accordingly. Now for each woman age 15-49 years, write her name and line number and other identifying information in the information panel of a separate Individual Women’s Questionnaire. For each child under age 5, write his/her name and line number AND the line number of his/her mother or caretaker in the information panel of a separate Under-5 Questionnaire. You should now have a separate questionnaire for each eligible woman, each eligible man, and each child under five in the household. * Codes for HL3: Relationship to head of household: 01 Head 02 Spouse / Partner 03 Son / Daughter 04 Son-In-Law / Daughter-In- Law 05 Grandchild 06 Parent 07 Parent-In-Law 08 Brother / Sister 09 Brother-In-Law / Sister-In- Law 10 Uncle / Aunt 11 Niece / Nephew 12 Other relative 13 Adopted / Foster/ Stepchild 14 Other (Not related) 98 DK 327 EDUCATIO N ED For household members age 4 and above For household members age 4-24 years ED1. Line numb er ED2. Name and age Copy from HL2 and HL6. ED3. HAS (name) EVER ATTENDE D SCHOOL OR PRE- SCHOOL OR KHALWA ? 1 Yes Þ ED4A 2 NO : a. If the age 25 years or more Ö Next line. b. If age 4 -24 years continu e to ED3A. ED3.A WHAT WAS THE MAIN REASON FOR NOT ATTENDING SCHOOL? ED4A. WHAT IS THE HIGHEST EDUCATIONAL LEVEL (name) HAS ATTENDED? LEVEL: 00 KHALWA 01 PRESCHOOL 02 PRELIMINARY 03 PRIMARY 04 BASIC 05 VOCATIONAL TRAINING 06 INTERMEDIATE 07 SECONDARY 08 HIGH SCHOOL (3 YEARS) 09 HIGH SCHOOL (4 YEARS) 10 INTERMEDIA TE DIPLOMA 11 UNIVERSITY 12 POST GRADUATE 98 DON’T KNOW ED4B. WHAT IS THE HIGHEST GRADE (name) COMPLET ED AT THIS LEVEL? Grade: 98 DK If the first grade at this level is not completed , enter “00”. ED5. DURING THE CURRENT SCHOOL YEAR, THAT IS 2014- 2015, DID (name) ATTEND SCHOOL OR PRESCHOOL OR KHALWA AT ANY TIME? 1 Yes:ED6 2 No Þ ED5A ED5A WHAT WAS THE MAIN REASON FOR NOT ATTENDING SCHOOL? ED6. DURING THIS/THAT SCHOOL YEAR, WHICH LEVEL AND GRADE IS/WAS (name) ATTENDING? ED7. DURING THE PREVIOUS SCHOOL YEAR, THAT IS 2013- 2014, DID (name) ATTEND SCHOOL OR PRESCHOOL OR KHALWA AT ANY TIME? 1 Yes 2 No Þ Next Line 8 DK Þ Next Line ED8. DURING THAT PREVIOUS SCHOOL YEAR, WHICH LEVEL AND GRADE DID (name) ATTEND? 1 FINANCIAL BURDEN OF SCHOOL EXPENSES 2 UNAVAILABILI TY OF EDUCATION SERVICES 3 DISABILITY/ ILLNESS 4 WORK TO SUPPORT FAMILY 5 SCHOOL TOO FAR AWAY 6 MIXED EDUCATION 7 OTHER 8 DK Þ Next Line 1 FINANCIAL BURDEN OF SCHOOL EXPENSES 2 UNAVAILABILITY OF EDUCATION SERVICES 3 DISABILITY/ ILLNESS 4 WORK TO SUPPORT FAMILY 5 SCHOOL TOO FAR AWAY 6 MIXED EDUCATION 7 UNAVAILABILITY OF DRINKING WATER AND TOILET. 8 EARLY MARRIAGE 96 OTHERS AFTER EACH ANSWER GO TO ED7 LEVEL: 00 KHALWA 01 PRESCHOOL 04 BASIC 05 VOCATIONAL TRAINING 08 HIGH SCHOOL . 11 UNIVERSITY 12 POST GRADUATE 98 DON’T KNOW If level=00,01 or 12 go to ED7 LEVEL: 00 KHALWA 01 PRESCHOOL 04 BASIC 05 VOCATIONAL TRAINING 08 HIGH SCHOOL 11 UNIVERSITY 12 POST GRADUATE 98 DON’T KNOW If level=00 or 01,12 go to next line. Grade : 98 DK 328 If level=00,01 or 12, skip to ED5. Line Name Age Ye s No Level Grade Yes No Level Grade Yes No DK Level Grade 01 ___ ___ 1 2 ___ ___ ___ ___ 1 2 ___ ___ ___ ___ 1 2 8 ___ ___ ___ ___ 02 ___ ___ 1 2 ___ ___ ___ ___ 1 2 ___ ___ ___ ___ 1 2 8 ___ ___ ___ ___ 03 ___ ___ 1 2 ___ ___ ___ ___ 1 2 ___ ___ ___ ___ 1 2 8 ___ ___ ___ ___ 04 ___ ___ 1 2 ___ ___ ___ ___ 1 2 ___ ___ ___ ___ 1 2 8 ___ ___ ___ ___ 05 ___ ___ 1 2 ___ ___ ___ ___ 1 2 ___ ___ ___ ___ 1 2 8 ___ ___ ___ ___ 06 ___ ___ 1 2 ___ ___ ___ ___ 1 2 ___ ___ ___ ___ 1 2 8 ___ ___ ___ ___ 07 ___ ___ 1 2 ___ ___ ___ ___ 1 2 ___ ___ ___ ___ 1 2 8 ___ ___ ___ ___ For household members age 4 and above For household members age 4-24 years 329 ED1. Line numb er ED2. Name and age Copy from HL2 and HL6. ED3. HAS (name) EVER ATTENDE D SCHOOL OR PRE- SCHOOL OR KHALWA ? 1 Yes Þ ED4A 2 NO : a. If the age 25 years or more Ö next line. 3. If age 4 -24 years continu e ED3.A WHAT WAS THE MAIN REASON FOR NOT ATTENDING SCHOOL? ED4A. WHAT IS THE HIGHEST EDUCATIONAL LEVEL (name) HAS ATTENDED? LEVEL: 00 KHALWA 01 PRESCHOOL 02 PRELIMINARY 03 PRIMARY 04 BASIC 05 VOCATIONAL TRAINING 06 INTERMEDIATE 07 SECONDARY 08 HIGH SCHOOL (3 YEARS) 09 HIGH SCHOOL (4 YEARS) 10INTERMEDIA TE DIPLOMA 11 UNIVERSITY 12 POST GRADUATE 98 DON’T KNOW If level=00,01 or 12, skip to ED5 ED4B. WHAT IS THE HIGHEST GRADE (name) COMPLET ED AT THIS LEVEL? Grade: 98 DK If the first grade at this level is not completed , enter “00”. ED5. DURING THE CURRENT SCHOOL YEAR, THAT IS 2014- 2015, DID (name) ATTEND SCHOOL OR PRESCHOOL OR KHALWA AT ANY TIME? 1 Yes:ED6 2 No Þ ED5A WHAT WAS THE MAIN REASON FOR NOT ATTENDING SCHOOL? ED6. DURING THIS/THAT SCHOOL YEAR, WHICH LEVEL AND GRADE IS/WAS (name) ATTENDING? : ED7. DURING THE PREVIOUS SCHOOL YEAR, THAT IS 2012- 2013, DID (name) ATTEND SCHOOL OR PRESCHOOL OR KHALWA AT ANY TIME? 1 Yes 2 No Þ Next Line 8 DK Þ Next Line ED8. DURING THAT PREVIOUS SCHOOL YEAR, WHICH LEVEL AND GRADE DID (name) ATTEND? 0 NOT OF SCHOOL AGE 1 FINANCIAL BURDEN OF SCHOOL EXPENSES 2 UNAVAILABILI TY OF EDUCATION SERVICES 3 DISABILITY/ ILLNESS 4 WORK TO SUPPORT FAMILY 5 SCHOOL TOO FAR AWAY 6 MIXED EDUCATION 7 OTHER 9 DK Þ Next Line 1 FINANCIAL BURDEN OF SCHOOL EXPENSES 2 UNAVAILABILITY OF EDUCATION SERVICES 3 DISABILITY/ ILLNESS 4 WORK TO SUPPORT FAMILY 5 SCHOOL TOO FAR AWAY 6 MIXED EDUCATION 7 UNAVAILABILITY OF DRINKING WATER AND TOILET. 8 EARLY MARRIAGE 9 OTHERS LEVEL: 00 KHALWA 01 PRESCHOOL 04 BASIC 05 VOCATIONAL TRAINING 08 HIGH SCHOOL 11 UNIVERSITY 12 POST GRADUATE 98 DON’T KNOW If level=00,01 or 12 go to ED7 If level=00 or 01, skip to ED7. Grade: 98 DK LEVEL: 00 KHALWA 01 PRESCHOOL 04 BASIC 05 VOCATIONAL TRAINING 08 HIGH SCHOOL. 11 UNIVERSITY 12 POST GRADUATE 98 DON’T KNOW If level=00,01 or 12 go to ED7 Grade : 98 DK Line Name Age Ye s No Level Grade Yes No Level Grade Yes s No DK Level Grade 330 08 ___ ___ 1 2 ___ ___ ___ ___ 1 2 ___ ___ ___ ___ 1 2 8 ___ ___ ___ ___ 09 ___ ___ 1 2 ___ ___ ___ ___ 1 2 ___ ___ ___ ___ 1 2 8 ___ ___ ___ ___ 10 ___ ___ 1 2 ___ ___ ___ ___ 1 2 ___ ___ ___ ___ 1 2 8 ___ ___ ___ ___ 11 ___ ___ 1 2 ___ ___ ___ ___ 1 2 ___ ___ ___ ___ 1 2 8 ___ ___ ___ ___ 12 ___ ___ 1 2 ___ ___ ___ ___ 1 2 ___ ___ ___ ___ 1 2 8 ___ ___ ___ ___ 13 ___ ___ 1 2 ___ ___ ___ ___ 1 2 ___ ___ ___ ___ 1 2 8 ___ ___ ___ ___ 331 SELECTION OF ONE CHILD FOR CHILD LABOUR/CHILD DISCIPLINE SL SL1. Check HL6 in the List of Household Members and write the total number of children age 1-17 years. Total number . __ SL2. Check the number of children age 1-17 years in SL1: … Zero Ö Go to HOUSEHOLD CHARACTERISTICS module. … One Ö Go to SL9 and record the rank number as ‘1’, enter the line number, child’s name and age. … Two or more Ö Continue with SL2A. SL2A. List each of the children age 1-17 years below in the order they appear in the List of Household Members. Do not include other household members outside of the age range 1-17 years. Record the line number, name, sex, and age for each child. SL3. Rank number SL4. Line number from HL1 SL5. Name from HL2 SL6. Sex from HL4 SL7. Age from HL6 Rank Line Name M F Age 1 __ __ 1 2 ___ ___ 2 __ __ 1 2 ___ ___ 3 __ __ 1 2 ___ ___ 4 __ __ 1 2 ___ ___ 5 __ __ 1 2 ___ ___ 6 __ __ 1 2 ___ ___ 7 __ __ 1 2 ___ ___ o SL8. Check the last digit of the household number (HH2) from the cover page. This is the number of the row you should go to in the table below. Check the total number of children age 1-17 years in SL1 above. This is the number of the column you should go to in the table below. Find the box where the row and the column meet and circle the number that appears in the box. This is the rank number (SL3) of the selected child. Total Number of Eligible Children in the Household (from SL1) Last Digit of Household Number (from HH2) 2 3 4 5 6 7 8+ 0 2 2 4 3 6 5 4 1 1 3 1 4 1 6 5 2 2 1 2 5 2 7 6 3 1 2 3 1 3 1 7 4 2 3 4 2 4 2 8 5 1 1 1 3 5 3 1 6 2 2 2 4 6 4 2 7 1 3 3 5 1 5 3 8 2 1 4 1 2 6 4 9 1 2 1 2 3 7 5 SL9. Record the rank number (SL3), line number (SL4), name (SL5) and age (SL7) of the selected child. Rank number __ Line number __ __ Name_______________________________ Age __ __ 332 CHILD LABOUR CL CL1. Check selected child’s age from SL9: … 1-4 years Ö Go to Next Module (Child discipline) … 5-17 years Ö Continue with CL2. CL2. NOW I WOULD LIKE TO ASK ABOUT ANY WORK CHILDREN IN THIS HOUSEHOLD MAY DO. SINCE LAST (day of the week), DID (name) DO ANY OF THE FOLLOWING ACTIVITIES, EVEN FOR ONLY ONE HOUR? [A] DID (name) DO ANY WORK OR HELP ON HIS/HER OWN OR THE HOUSEHOLD’S PLOT/FARM/FOOD GARDEN OR LOOKED AFTER ANIMALS? FOR EXAMPLE, GROWING FARM PRODUCE, HARVESTING, OR FEEDING, GRAZING, MILKING ANIMALS? [B] DID (name) HELP IN FAMILY BUSINESS OR RELATIVE’S BUSINESS WITH OR WITHOUT PAY, OR RUN HIS/HER OWN BUSINESS? [C] DID (name) PRODUCE OR SELL ARTICLES, HANDICRAFTS, CLOTHES, FOOD OR AGRICULTURAL PRODUCTS? [D] SINCE LAST (day of the week), DID (name) ENGAGE IN ANY OTHER ACTIVITY IN RETURN FOR INCOME IN CASH OR IN KIND, EVEN FOR ONLY ONE HOUR? If “No”, Probe: PLEASE INCLUDE ANY ACTIVITY (name) PERFORMED AS A REGULAR OR CASUAL EMPLOYEE, SELF-EMPLOYED OR EMPLOYER; OR AS AN UNPAID FAMILY WORKER HELPING OUT IN HOUSEHOLD BUSINESS OR FARM. Yes No Worked on plot / farm / food garden / looked after animals . 1 2 Helped in family / relative’s business/ran own business . 1 2 Produce / sell articles / handicrafts / clothes / food or agricultural products . 1 2 Any other activity . 1 2 CL3. Check CL2, A to D … There is at least one ‘Yes’ Ö continue with CL4 … All answers are ‘No Ö Go to CL8 CL4. SINCE LAST (day of the week) ABOUT HOW MANY HOURS DID (name) ENGAGE IN THIS ACTIVITY/THESE ACTIVITIES, IN TOTAL? If less than one hour, record “00” Number of hours . __ __ CL5. DOES THE ACTIVITY/DO THESE ACTIVITIES REQUIRE CARRYING HEAVY LOADS? Yes . 1 No . 2 1Ö CL8 CL6. DOES THE ACTIVITY/DO THESE ACTIVITIES REQUIRE WORKING WITH DANGEROUS TOOLS (KNIVES ETC.) OR OPERATING HEAVY MACHINERY? Yes . 1 No . 2 1Ö CL8 333 CL7. HOW WOULD YOU DESCRIBE THE WORK ENVIRONMENT OF (name)? [A] IS (name) EXPOSED TO DUST, FUMES OR GAS? [B] IS (name) EXPOSED TO EXTREME COLD, HEAT OR HUMIDITY? [C] IS (name) EXPOSED TO LOUD NOISE OR VIBRATION? [D] IS (name) REQUIRED TO WORK AT HEIGHTS? [E] IS (name) REQUIRED TO WORK WITH CHEMICALS (PESTICIDES, GLUES, ETC.) OR EXPLOSIVES? [F] IS (name) EXPOSED TO OTHER THINGS, PROCESSES OR CONDITIONS BAD FOR (name)’S HEALTH OR SAFETY? Yes . 1 No . 2 Yes . 1 No . 2 Yes . 1 No . 2 Yes . 1 No . 2 Yes . 1 No . 2 Yes . 1 No . 2 CL8. SINCE LAST (day of the week), DID (name) FETCH WATER OR COLLECT FIREWOOD FOR HOUSEHOLD USE? Yes . 1 No . 2 2Ö CL10 CL9. IN TOTAL, HOW MANY HOURS DID (name) SPEND ON FETCHING WATER OR COLLECTING FIREWOOD FOR HOUSEHOLD USE, SINCE LAST (day of the week)? If less than one hour, record “00” Number of hours . __ __ CL10. SINCE LAST (day of the week), DID (name) DO ANY OF THE FOLLOWING FOR THIS HOUSEHOLD? [A] SHOPPING FOR HOUSEHOLD? [B] REPAIR ANY HOUSEHOLD EQUIPMENT? [C] COOKING OR CLEANING UTENSILS OR THE HOUSE? [D] WASHING CLOTHES? [E] CARING FOR CHILDREN? [F] CARING FOR THE OLD OR SICK? [G] OTHER HOUSEHOLD TASKS? Yes No Shopping for household . 1 2 Repair household equipment . 1 2 Cooking / cleaning utensils /house . 1 2 Washing clothes . 1 2 Caring for children . 1 2 Caring for old / sick . 1 2 Other household tasks . 1 2 CL11. Check CL10, A to G … There is at least one ‘Yes’ Ö Continue with CL12 … All answers are ‘No’ Ö Go to Next Module CL12. SINCE LAST (day of the week), ABOUT HOW MANY HOURS DID (name) ENGAGE IN THIS ACTIVITY/THESE ACTIVITIES, IN TOTAL? Number of hours . __ __ 334 If less than one hour, record “00” 335 CHILD DISCIPLINE CD CD1. Check selected child’s age from SL9: … 1-14 years Ö Continue with CD2 … 15-17 years Ö Go to Next Module CD2. Write the line number and name of the child from SL9. Line number __ __ Name _____________________________ CD3. ADULTS USE CERTAIN WAYS TO TEACH CHILDREN THE RIGHT BEHAVIOUR OR TO ADDRESS A BEHAVIOUR PROBLEM. I WILL READ VARIOUS METHODS THAT ARE USED. PLEASE TELL ME IF YOU OR ANYONE ELSE IN YOUR HOUSEHOLD HAS USED THIS METHOD WITH (name) IN THE PAST MONTH. [A] TOOK AWAY PRIVILEGES, FORBADE SOMETHING (name) LIKED OR DID NOT ALLOW HIM/HER TO LEAVE THE HOUSE. [B] EXPLAINED WHY (name)’S BEHAVIOUR WAS WRONG. [C] SHOOK HIM/HER. [D] SHOUTED, YELLED AT OR SCREAMED AT HIM/HER. [E] GAVE HIM/HER SOMETHING ELSE TO DO. [F] SPANKED, HIT OR SLAPPED HIM/HER ON THE BOTTOM WITH BARE HAND. [G] HIT HIM/HER ON THE BOTTOM OR ELSEWHERE ON THE BODY WITH SOMETHING LIKE A BELT, HAIRBRUSH, STICK, SLIPPER OR OTHER HARD OBJECT. [H] CALLED HIM/HER DUMB, LAZY, OR ANOTHER NAME LIKE THAT. [I] HIT OR SLAPPED HIM/HER ON THE FACE, HEAD OR EARS. [J] HIT OR SLAPPED HIM/HER ON THE HAND, ARM, OR LEG. [K] BEAT HIM/HER UP, THAT IS HIT HIM/HER OVER AND OVER AS HARD AS ONE COULD. Yes No Took away privileges . 1 2 Explained wrong behaviour . 1 2 Shook him/her . 1 2 Shouted, yelled, screamed . 1 2 Gave something else to do . 1 2 Spanked, hit, slapped on bottom with bare hand . 1 2 Hit with belt, hairbrush, stick, slipper or other hard object . 1 2 Called dumb, lazy, or another name . 1 2 Hit / slapped on the face, head or ears . 1 2 Hit / slapped on hand, arm or leg . 1 2 Beat up, hit over and over as hard as one could . 1 2 CD4. DO YOU BELIEVE THAT IN ORDER TO BRING UP, RAISE, OR EDUCATE A CHILD PROPERLY, THE CHILD NEEDS TO BE PHYSICALLY PUNISHED? Yes . 1 No . 2 DK/ No opinion………………………….….8 336 HOUSEHOLD CHARACTERISTICS HC HC2. HOW MANY ROOMS IN THIS HOUSEHOLD ARE USED FOR SLEEPING? Number of rooms __ __ HC3. Main material of the dwelling floor. Record observation. Natural floor Earth / Sand 11 Dung 12 Rudimentary floor Wood planks 21 Ganaa (Palm / Bamboo) 22 Finished floor Parquet or polished wood 31 Vinyl or asphalt strips 32 Ceramic tiles 33 Cement/ Dafra (bricks+cement) 34 Carpet 35 Concrete 36 Marble……………………….………37 Other (specify) _____________________ 96 HC4. Main material of the roof. Record observation. Natural roofing No Roof 11 Thatch / Palm leaf 12 Sod 13 Rudimentary roofing Rustic mat 21 Ganaa (Palm / Bamboo) 22 Wood planks 23 Cardboard 24 Traditional roof (mat+wood planks) 25 Finished roofing Metal / Tin (Zinc) 31 Wood 32 Ceramic tiles 34 Cement / concrete 35 Other (specify) _____________________ 96 HC5. Main material of the exterior walls. Record observation. Natural walls No walls 11 Cane / Palm / Trunks 12 Dirt (jaloos) 13 Rudimentary walls Bamboo (Ganaa) with mud 21 Stone with mud 22 Uncovered adobe 23 Plywood 24 Cardboard 25 Reused wood 26 Finished walls 337 Stone with lime / cement 32 Bricks 33 Cement blocks 34 Covered adobe (Bayad) 35 Wood planks / shingles 36 Other (specify) _____________________ 96 HC6. WHAT TYPE OF FUEL DOES YOUR HOUSEHOLD MAINLY USE FOR COOKING? Electricity 01 Liquefied Petroleum Gas (LPG) 02 Kerosene 05 Coal / Lignite 06 Charcoal 07 Wood 08 Straw / Shrubs / Grass 09 Animal dung 10 Agricultural crop residue 11 Solar energy…………………………. …………………………………,,,….….12 Wood dust………….…………………,,.…….13 No food cooked in household………….95 Other (specify) _____________________ 96 01ÖHC8 02ÖHC8 05ÖHC8 95ÖHC8 HC7. IS THE COOKING USUALLY DONE IN THE HOUSE, IN A SEPARATE BUILDING, OR OUTDOORS? If ‘In the house’, probe: IS IT DONE IN A SEPARATE ROOM USED AS A KITCHEN? In the house In a separate room used as kitchen/tukul 1 Elsewhere in the house 2 In a separate building 3 Outdoors 4 Other (specify) ______________________ 6 HC8. DOES YOUR HOUSEHOLD HAVE: [A] ELECTRICITY? [B] A RADIO? [C] A TELEVISION? [D] A NON-MOBILE TELEPHONE? [E] A REFRIGERATOR? [F] A DIGITAL RECEIVER? [G] A FLAT SCREEN TV [H] AN INTERNET CONNECTION? [I] DESKTOP COMPUTER [J] Washing machine Yes No Electricity . 1 2 Radio . 1 2 Television . 1 2 Non-mobile telephone . 1 2 Refrigerator . 1 2 Digital receiver . 1 2 Flat screen TV . 1 2 Internet connection . 1 2 Desktop computer . 1 2 Washing machine . 1 2 338 HC9. DOES ANY MEMBER OF YOUR HOUSEHOLD OWN: [B] A MOBILE PHONE? [C] A BICYCLE? [D] A MOTORCYCLE OR SCOOTER? [E] AN ANIMAL-DRAWN CART (KARO)? [F] A CAR OR TRUCK? [G] A BOAT WITH A MOTOR? [H] A RAKSHA [I] A SMART PHONE [J] A LAPTOP COMPUTER/ TABLET [K ] THORAYA PHONE Yes No Mobile telephone . 1 2 Bicycle . 1 2 Motorcycle / Scooter . 1 2 Animal-drawn cart (Karo) . 1 2 Car / Truck . 1 2 Boat with motor . 1 2 Raksha . 1 2 Smart phone . 1 2 Laptop/ tablet . 1 2 Thoraya phone.1 2 HC10. DO YOU OR SOMEONE LIVING IN THIS HOUSEHOLD OWN THIS DWELLING? If “No”, then ask: DO YOU RENT THIS DWELLING FROM SOMEONE NOT LIVING IN THIS HOUSEHOLD? If “Rented from someone else”, circle “2”. For other responses, circle “6”. Own 1 Rent 2 Other (specify)______________________6 HC11. DOES ANY MEMBER OF THIS HOUSEHOLD OWN ANY LAND THAT CAN BE USED FOR AGRICULTURE? Yes 1 No 2 2ÖHC13 HC12. HOW MANY FEDDANS OF AGRICULTURAL LAND DO MEMBERS OF THIS HOUSEHOLD OWN? If less than 1, record “00”. If 95 or more, record “95”. If unknown, record “98”. Feddans ___ ___ HC13. DOES THIS HOUSEHOLD OWN ANY LIVESTOCK, HERDS, OTHER FARM ANIMALS, OR POULTRY? Yes 1 No 2 2ÖHC15 HC14. HOW MANY OF THE FOLLOWING ANIMALS DOES THIS HOUSEHOLD HAVE? [A] CATTLE, MILK COWS, OR BULLS? [B] HORSES, DONKEYS, OR MULES? [C] GOATS? [D] SHEEP? [E] CHICKENS? Cattle, milk cows, or bulls ___ ___ Horses, donkeys, or mules ___ ___ Goats ___ ___ Sheep ___ ___ 339 [F] PIGS? [G] CAMELS? If none, record “00”. If 95 or more, record “95”. If unknown, record “98”. Chickens ___ ___ Pigs ___ ___ Camels ___ ___ HC15. DOES ANY MEMBER OF THIS HOUSEHOLD HAVE A BANK ACCOUNT? Yes 1 No 2 340 WATER AND SANITATION WS WS1. WHAT IS THE MAIN SOURCE OF DRINKING WATER FOR MEMBERS OF YOUR HOUSEHOLD? Piped water Piped into dwelling 11 Piped into compound, yard or plot 12 Piped to neighbour 13 Public tap / standpipe 14 Elevated tank, handpump (Kharjaka) 15 Dug well Protected well 31 Unprotected well 32 Water from spring Protected spring 41 Unprotected spring 42 Surface water (river, stream, dam, hafeer, lake, pond, canal, irrigation channel) filtered 52 Surface water (river, stream, dam, hafeer, lake, pond, canal, irrigation channel) unfiltered 53 Tanker-truck/ Cart with tank Transported from sources ( 11, 12,13, 14, 15,31, 41,52) 61 Transported from sources ( 32, 42, 53) 62 Unknown source 63 Bottled water 91 Other (specify) 96 11ÖWS6 12ÖWS6 13ÖWS6 14ÖWS3 15ÖWS3 31ÖWS3 32ÖWS3 41ÖWS3 42ÖWS3 52ÖWS3 53ÖWS3 61ÖWS3 62ÖWS3 63ÖWS3 96ÖWS3 WS2. WHAT IS THE MAIN SOURCE OF WATER USED BY YOUR HOUSEHOLD FOR OTHER PURPOSES SUCH AS COOKING AND HANDWASHING? Piped water Piped into dwelling 11 Piped into compound, yard or plot 12 Piped to neighbour 13 Public tap / standpipe 14 Elevated tank, handpump (Kharjaka) 15 Dug well Protected well 31 Unprotected well 32 Water from spring Protected spring 41 Unprotected spring 42 Surface water (river, stream, dam, hafeer, lake, pond, canal, irrigation channel) filtered 52 Surface water (river, stream, dam, hafeer, lake, pond, canal, irrigation channel) unfiltered 53 11ÖWS6 12ÖWS6 13ÖWS6 61ÖWS6 62ÖWS 63ÖWS6 341 Tanker-truck/ Cart with tank Transported from sources ( 11, 12,13, 14, 15,31, 41,52)…………………………………61 Transported from sources ( 32, 42, 53) 62 Unknown source……………………… 63 Other (specify)_____________________96 WS3. WHERE IS THAT WATER SOURCE LOCATED? In own dwelling 1 In own yard / plot 2 Elsewhere 3 1ÖWS6 2ÖWS6 WS4. HOW LONG DOES IT TAKE TO GO THERE, GET WATER, AND COME BACK? Number of minutes __ __ __ DK 998 WS5. WHO USUALLY GOES TO THIS SOURCE TO COLLECT THE WATER FOR YOUR HOUSEHOLD? Probe: IS THIS PERSON UNDER AGE 15? WHAT SEX? Adult woman (age 15+ years) 1 Adult man (age 15+ years) 2 Female child (under 15) 3 Male child (under 15) 4 DK 8 WS6. DO YOU DO ANYTHING TO THE WATER TO MAKE IT SAFER TO DRINK? Yes 1 No 2 DK 8 2ÖWS8 8ÖWS8 WS7. WHAT DO YOU USUALLY DO TO MAKE THE WATER SAFER TO DRINK? Probe: ANYTHING ELSE? Record all items mentioned. Boil A Add bleach / chlorine B Strain it through a cloth C Use water filter (ceramic, sand, composite, etc.) D Solar disinfection E Let it stand and settle (e.g. zeer) F Other (specify)_____________________X DK Z WS8. WHAT KIND OF TOILET FACILITY DO MEMBERS OF YOUR HOUSEHOLD USUALLY USE? If “flush” or “pour flush”, probe: WHERE DOES IT FLUSH TO? If not possible to determine, ask permission to observe the facility. Flush / Pour flush Flush to piped sewer system 11 Flush to septic tank 12 Flush to pit (latrine) 13 Flush to somewhere else 14 Flush to unknown place / Not sure / DK where 15 Pit latrine Ventilated Improved Pit latrine (VIP) 21 Pit latrine with slab 22 Pit latrine without slab / Open pit 23 342 Composting toilet 31 Bucket 41 No facility, Bush, Field 95 Other (specify) _____________________ 96 95ÖWS11A WS9. DO YOU SHARE THIS FACILITY WITH OTHERS WHO ARE NOT MEMBERS OF YOUR HOUSEHOLD? Yes 1 No 2 2ÖWS11 A WS10. DO YOU SHARE THIS FACILITY ONLY WITH MEMBERS OF OTHER HOUSEHOLDS THAT YOU KNOW, OR IS THE FACILITY OPEN TO THE USE OF THE GENERAL PUBLIC? Other households only (not public) 1 Public facility 2 2ÖWS11 A WS11. HOW MANY HOUSEHOLDS IN TOTAL USE THIS TOILET FACILITY, INCLUDING YOUR OWN HOUSEHOLD? Number of households (if less than 10) 0 __ Ten or more households 10 DK 98 WS11A. WHAT IS THE MAIN METHOD USED FOR DISPOSING GARBAGE? Removed by garbage vehicles 1 Thrown away from living areas 2 Thrown out of the house 3 Burned 4 Buried 5 Others (specify)____________________6 343 HANDWASHING HW HW1. WE WOULD LIKE TO LEARN ABOUT THE PLACES THAT HOUSEHOLDS USE TO WASH THEIR HANDS. CAN YOU PLEASE SHOW ME WHERE MEMBERS OF YOUR HOUSEHOLD MOST OFTEN WASH THEIR HANDS? Observed 1 Not observed Not in dwelling / plot / yard 2 No permission to see 3 /Other reason (specify) ________________________ 6 2 ÖHW4 3 ÖHW4 6 ÖHW4 HW2. Observe presence of water at the place for handwashing. Verify by checking the tap/pump, or basin, bucket, water container or similar objects for presence of water. Water is available 1 Water is not available 2 HW3A. Is soap, detergent or mud/sand present at the place for handwashing? Yes, present . 1 No, not present . 2 2ÖHW4 HW3B. Record your observation. Circle all that apply. Bar soap A Detergent (Powder / Liquid / Paste) B Liquid soap C Mud / Sand D AÖ next module BÖ next module CÖ next module DÖ next module HW4. DO YOU HAVE ANY SOAP OR DETERGENT OR MUD/SAND IN YOUR HOUSE FOR WASHING HANDS? Yes . 1 No . 2 2Ö next module HW5A. CAN YOU PLEASE SHOW IT TO ME? Yes, shown . 1 No, not shown……….…………………… ….2 2ÖNEXT MODULE HW5B. Record your observation. Circle all that apply. Bar soap A Detergent (Powder / Liquid / Paste) B Liquid soap C Ash / Mud / Sand D 344 FOOD CONSUMPTION & SOURCES FC FC1: NOW I WOULD LIKE TO TALK ABOUT YOUR FOOD ITEMS & CONSUMPTION; ?DAYS 7IN THE LAST )FOOD ITEM(UME DID YOUR FAMILY CONS 2ÖFC1[B] Yes………………….….1 No……………………….2 [A] SORGHUM? Number of days…….___ Main source………….___ HOW MANY DAYS DID YOUR FAMILY EAT THIS FOOD ITEM? WHAT WAS THE MAIN SOURCE? Use codes below for the food sources - If there are several sources for a same food, indicate the main source 2Ö FC1[C] Yes………………….….1 No……………………….2 [B] MILLET? Number of days…….___ Main source…………___ HOW MANY DAYS DID YOUR FAMILY EAT THIS FOOD ITEM? WHAT WAS THE MAIN SOURCE? Use codes below for the food sources - If there are several sources for a same food, indicate the main source 2Ö FC1[D] Yes………………….….1 No……………………….2 [C] WHEAT/ BREAD? Number of days…….___ Main source…………___ HOW MANY DAYS DID YOUR FAMILY EAT THIS FOOD ITEM? WHAT WAS THE MAIN SOURCE? Use codes below for the food sources - If there are several sources for a same food, indicate the main source 2Ö FC1[E] Yes………………….….1 No……………………….2 [D] GROUNDNUTS, PULSES (BEANS, LENTILS)? Number of days…….___ Main source…………___ HOW MANY DAYS DID YOUR FAMILY EAT THIS FOOD ITEM? WHAT WAS THE MAIN SOURCE? Use codes below for the food sources - If there are several sources for a same food, indicate the main source 2Ö FC1[F] Yes………………….….1 No……………………….2 [E] MEAT/CHICKEN, BUSH MEAT, ETC. Number of days…….___ Main source…………___ HOW MANY DAYS DID YOUR FAMILY EAT THIS FOOD ITEM? WHAT WAS THE MAIN SOURCE? Use codes below for the food sources - If there are several sources for a same food, indicate the main source 2Ö FC1[G] Yes………………….….1 No……………………….2 [F] COOKING OIL/FATS Number of days…….___ Main source…………___ HOW MANY DAYS DID YOUR FAMILY EAT THIS FOOD ITEM? WHAT WAS THE MAIN SOURCE? Use codes below for the food sources - If there are several sources for a same food, indicate the main source 5 Borrowed 6 Gift from family/ friends / relatives 7 Food aid (NGOs, WFP) Food source codes 1 Own production (crops, animals) 2 Purchased on market, shop etc. 3 Hunting, fishing, gathering 4 Received in-kind against labour or other items 345 2Ö FC1[H] Yes………………….….1 No……………………….2 [G] FRUITS? Number of days…….___ Main source………….___ HOW MANY DAYS DID YOUR FAMILY EAT THIS FOOD ITEM? WHAT WAS THE MAIN SOURCE? Use codes below for the food sources - If there are several sources for a same food, indicate the main source 2Ö FC1[I] Yes………………….….1 No……………………….2 [H] MILK, YOGHURT, CHEESE, ETC ? Number of days…….___ Main source…………___ HOW MANY DAYS DID YOUR FAMILY EAT THIS FOOD ITEM? WHAT WAS THE MAIN SOURCE? Use codes below for the food sources - If there are several sources for a same food, indicate the main source 2Ö FC1[J] Yes………………….….1 No……………………….2 [I] SUGAR? Number of days…….___ Main source…………___ HOW MANY DAYS DID YOUR FAMILY EAT THIS FOOD ITEM? WHAT WAS THE MAIN SOURCE? Use codes below for the food sources - If there are several sources for a same food, indicate the main source 2Ö FC1[K] Yes………………….….1 No……………………….2 [J] EGG? Number of days…….___ Main source…………___ HOW MANY DAYS DID YOUR FAMILY EAT THIS FOOD ITEM? WHAT WAS THE MAIN SOURCE? Use codes below for the food sources - If there are several sources for a same food, indicate the main source 2Ö FC1[L] Yes………………….….1 No……………………….2 [K] FRESH VEGETABLES? Number of days…….___ Main source…………___ HOW MANY DAYS DID YOUR FAMILY EAT THIS FOOD ITEM? WHAT WAS THE MAIN SOURCE? Use codes below for the food sources - If there are several sources for a same food, indicate the main source 2Önext module Yes………………….….1 No……………………….2 [L] DRY VEGETABLES (OKRA, TOMATOES, ONION , ETC? Number of days…….___ Main source…………___ HOW MANY DAYS DID YOUR FAMILY EAT THIS FOOD ITEM? WHAT WAS THE MAIN SOURCE? Use codes below for the food sources - If there are several sources for a same food, indicate the main source 5 Borrowed 6 Gift from family/ friends / relatives 7 Food aid (NGOs, WFP) Food source codes 1 Own production (crops, animals) 2 2 Purchased on market, shop etc. 3 Hunting, fishing, gathering 4 Received in-kind against labour or other items COPING STRATEGIES CS .CS1: IN THE PAST 7 DAYS, WERE THERE TIMES WHEN YOU DID NOT HAVE ENOUGH FOOD OR MONEY TO BUY FOOD FOR YOUR FAMILY? Yes…………………………………………………. 1 No……………………………………………………. 2 2ÖHH19 346 CS2: WHAT WAS THE COPING STRATEGY THAT YOU ADOPTED DURING THAT TIMES? Probe (Don’t read answers) Rely on less preferred and less expensive food [A] IF If the respondent mentioned this option ask: HOW MANY DAYS DID YOU ADOPT THAT STRATEGY? Number of days… …___ Eat borrowed food or borrow money to purchase food . [B] IF If the respondent mentioned this option ask; HOW MANY DAYS DID YOU ADOPT THAT STRATEGY? Number of days…….__ _ Rely on help from friends or relatives (musaada) .…………….[C] If If the respondent mentioned this option ask; HOW MANY DAYS DID YOU ADOPT THAT STRATEGY? Number of days………. ___ Limit portion size at mealtimes . [D] IF If the respondent mentioned this option ask; HOW MANY DAYS DID YOU ADOPT THAT STRATEGY? Number of days…….__ _ Restrict consumption for adults in order for small children to eat . [E] If If the respondent mentioned this option ask; HOW MANY DAYS DID YOU ADOPT THAT STRATEGY? Number of days………. ___ Reduce number of meals eaten in a day . [F] If the respondent mentioned this option ask: HOW MANY DAY DID YOU ADOPT THAT STRATEGY? Number of days…….__ _ 347 HH19. Record the time. Morning . 1 Afternoon . 2 Hour and minutes . __ __ : __ __ SALT IODIZATION SI SI1. THERE ARE TYPES OF SALT THAT CONTAIN IODINE WHICH IS AN IMPORTANT NUTRIENT. WE WOULD LIKE TO CHECK WHETHER THE SALT USED IN YOUR HOUSEHOLD IS IODIZED. MAY I HAVE A SAMPLE OF THE SALT USED TO COOK MEALS IN YOUR HOUSEHOLD? If salt not tested, please mention the reasons. Not iodized - 0 PPM 1 More than 0 PPM & less than 15 PPM 2 15 PPM or more 3 No salt in the house 4 Salt not tested (specify reason)_____________________5 HH20. Thank the respondent for his/her cooperation and check the List of Household Members: … A separate QUESTIONNAIRE FOR INDIVIDUAL WOMEN has been issued for each woman age 15-49 years in the List of Household Members (HL7). … A separate QUESTIONNAIRE FOR CHILDREN UNDER FIVE has been issued for each child under age 5 years in the List of Household Members (HL7B). Return to the cover page and make sure that the result of the household interview (HH9), the name and line number of the respondent to the household questionnaire (HH10), and the number of eligible women (HH12), and under-5s (HH14) are entered. Make arrangements for the administration of the remaining questionnaire(s) in this household. 348 Interviewer’s Observations Field Editor’s Observations Supervisor’s Observations 349 Appendix F2: Questionnaire for Individual Women QUESTIONNAIRE FOR INDIVIDUAL WOMEN Sudan Multiple Indicator Survey 2014 WOMAN’S INFORMATION PANEL WM This questionnaire is to be administered to all women age 15 through 49 (see List of Household Members, column HL7). A separate questionnaire should be used for each eligible woman. WM0 State code ___ ___ WM1. Cluster number: WM2. Household number: ___ ___ ___ ___ WM3. Woman’s name: WM4. Woman’s line number: Name ___ ___ WM5. Interviewer’s name and number: WM6. Day / Month / Year of interview: Name ___ ___ ___ ___ /___ ___ / 2 0 1 4 Repeat greeting if not already read to this woman: WE ARE FROM THE CENTRAL BUREAU OF STATISTICS. WE ARE CONDUCTING A SURVEY ABOUT THE SITUATION OF CHILDREN, FAMILIES AND HOUSEHOLDS. I WOULD LIKE TO TALK TO YOU ABOUT THESE SUBJECTS. THE INTERVIEW WILL TAKE ABOUT 45 MINUTES. ALL THE INFORMATION WE OBTAIN WILL REMAIN STRICTLY CONFIDENTIAL AND ANONYMOUS. If greeting at the beginning of the household questionnaire has already been read to this woman, then read the following: NOW I WOULD LIKE TO TALK TO YOU MORE ABOUT YOUR HEALTH AND OTHER TOPICS. THIS INTERVIEW WILL TAKE ABOUT 45 MINUTES. AGAIN, ALL THE INFORMATION WE OBTAIN WILL REMAIN STRICTLY CONFIDENTIAL AND ANONYMOUS. MAY I START NOW? … Yes, permission is given Ö Go to WM10 to record the time and then begin the interview. … No, permission is not given Ö Circle “03” in WM7. Discuss this result with your supervisor. WM7. Result of woman’s interview Completed . 01 Not at home . 02 Refused . 03 Partly completed . 04 Incapacitated . 05 Other (specify) ____________________________ 96 WM8. Field editor’s name and number: Name___________________________ __ __ WM9. Main data entry clerk’s name and number: Name__________________________________ __ __ 350 WM10. Record the time. Morning . 1 Afternoon . 2 Hour and minutes . __ __ : __ __ WOMAN’S BACKGROUND WB WB1. IN WHAT MONTH AND YEAR WERE YOU BORN? Date of birth Month . __ __ DK month . 98 Year . __ __ __ __ DK year . 9998 WB2. HOW OLD ARE YOU? Probe: HOW OLD WERE YOU AT YOUR LAST BIRTHDAY? Compare and correct WB1 and/or WB2 if inconsistent. Age (in completed years) . __ __ WB3. HAVE YOU EVER ATTENDED SCHOOL OR KHALWA OR PRESCHOOL? Yes . 1 No . 2 2ÖWB7 WB4. WHAT IS THE HIGHEST LEVEL OF EDUCATION YOU ATTAINED? KHALWA………………………………….00 PRESCHOOL……………………………….01 PRELIMINARY……………………………….02 PRIMARY………………………………… 03 BASIC……………………………………….04 VOCATIONAL TRAINING…………………….05 INTERMEDIATE………………………………….06 SECONDARY……………………………….07 HIGH SCHOOL (3 YEARS) ………………….08 HIGH SCHOOL…(4 YEARS)………………………….09 INTERMEDIATE DIPLOMA ……………………10 UNIVERSITY……………………………….11 POST GRADUATE……………………………12 00ÖWB7 01ÖWB7 12ÖNEXT MODULE WB5. WHAT IS THE HIGHEST GRADE YOU COMPLETED AT THAT LEVEL? If the first grade at this level is not completed, enter “00”. Grade . __ __ WB6. Check WB4: … Vocational training or higher (WB4=05, 06, 07, 08,09,10,11) Ö Go to Next Module. … Primary (WB4=02, 03 or 04) Ö Continue with WB7. 351 WB7. NOW I WOULD LIKE YOU TO READ THIS SENTENCE TO ME. Show sentence on the card to the respondent. If respondent cannot read whole sentence, probe: CAN YOU READ PART OF THE SENTENCE TO ME? Cannot read at all . 1 Able to read only parts of sentence . 2 Able to read whole sentence . 3 No sentence in required language __________________4 (specify language) Blind / visually impaired . 5 352 MARRIAGE MA MA1. ARE YOU CURRENTLY MARRIED? Yes, currently married . 1 Not currently married . 2 2ÖMA5 MA2. HOW OLD IS YOUR HUSBAND? Probe: HOW OLD WAS YOUR HUSBAND ON HIS LAST BIRTHDAY? Age in years . __ __ DK . 98 MA3. BESIDES YOURSELF, DOES YOUR HUSBAND HAVE ANY OTHER WIVES? Yes . 1 No . 2 2ÖMA7 MA4. HOW MANY OTHER WIVES DOES HE HAVE CURRENTLY? Number . __ __ DK . 98 ÖMA7 98ÖMA7 MA5. HAVE YOU EVER BEEN MARRIED? Yes, formerly married . 1 No . 2 2ÖFGM module MA6. WHAT IS YOUR MARITAL STATUS NOW: ARE YOU WIDOWED, DIVORCED OR SEPARATED? Widowed . 1 Divorced . 2 Separated. 3 MA7. HAVE YOU BEEN MARRIED ONLY ONCE OR MORE THAN ONCE? Only once . 1 More than once . 2 1ÖMA8A 2ÖMA8B MA8A. IN WHAT MONTH AND YEAR DID YOU MARRY? MA8B. IN WHAT MONTH AND YEAR DID YOU FIRST MARRY? Date of (first) marriage Month . __ __ DK month . 98 Year . __ __ __ __ DK year . 9998 ÖNext Module MA9. HOW OLD WERE YOU WHEN YOU FIRST STARTED LIVING WITH YOUR (FIRST) HUSBAND? Age in years . __ __ 353 FERTILITY/BIRTH HISTORY CM CM1. NOW I WOULD LIKE TO ASK ABOUT ALL THE BIRTHS YOU HAVE HAD DURING YOUR LIFE. HAVE YOU EVER GIVEN BIRTH? Yes . 1 No . 2 2ÖCM8 CM4. DO YOU HAVE ANY SONS OR DAUGHTERS TO WHOM YOU HAVE GIVEN BIRTH WHO ARE NOW LIVING WITH YOU? Yes . 1 No . 2 2ÖCM6 CM5. HOW MANY SONS LIVE WITH YOU? HOW MANY DAUGHTERS LIVE WITH YOU? If none, record “00”. Sons at home . __ __ Daughters at home . __ __ CM6. DO YOU HAVE ANY SONS OR DAUGHTERS TO WHOM YOU HAVE GIVEN BIRTH WHO ARE ALIVE BUT DO NOT LIVE WITH YOU? Yes . 1 No . 2 2ÖCM8 CM7. HOW MANY SONS ARE ALIVE BUT DO NOT LIVE WITH YOU? HOW MANY DAUGHTERS ARE ALIVE BUT DO NOT LIVE WITH YOU? If none, record “00”. Sons elsewhere . __ __ Daughters elsewhere . __ __ CM8. HAVE YOU EVER GIVEN BIRTH TO A BOY OR GIRL WHO WAS BORN ALIVE BUT LATER DIED? If “No” probe by asking: I MEAN, TO A CHILD WHO EVER BREATHED OR CRIED OR SHOWED OTHER SIGNS OF LIFE – EVEN IF HE OR SHE LIVED ONLY A FEW MINUTES OR HOURS? Yes . 1 No . 2 2ÖCM10 CM9. HOW MANY BOYS HAVE DIED? HOW MANY GIRLS HAVE DIED? If none, record “00”. Boys dead . __ __ Girls dead . __ __ CM10. Sum answers to CM5, CM7, and CM9. Sum . __ __ CM11. JUST TO MAKE SURE THAT I HAVE THIS RIGHT, YOU HAVE HAD IN TOTAL (total number in CM10) LIVE BIRTHS DURING YOUR LIFE. IS THIS CORRECT? … Yes. Check below: … No live births Ö Go to ILLNESS SYMPTOMS Module. … One or more live births Ö Continue with the BIRTH HISTORY module. … No. Ö Check responses to CM1-CM10 and make corrections as necessary before proceeding to the BIRTH HISTORY Module or ILLNESS SYMPTOMS Module. 354 BIRTH HISTORY BH NOW I WOULD LIKE TO RECORD THE NAMES OF ALL OF YOUR BIRTHS, WHETHER STILL ALIVE OR NOT, STARTING WITH THE FIRST ONE YOU HAD. Record names of all of the births in BH1.Record twins and triplets on separate lines. If there are more than 14 births, use an additional questionnaire. BH Line No. BH1. WHAT NAME WAS GIVEN TO YOUR (first/next) BABY? BH2. WERE ANY OF THESE BIRTHS TWINS? 1 Single 2 Multiple BH3. IS (name) A BOY OR A GIRL? 1 Boy 2 Girl BH4. IN WHAT MONTH AND YEAR WAS (name) BORN? Probe: WHAT IS HIS/HER BIRTHDAY? BH5. IS (name) STILL ALIVE? 1 Yes 2 No BH6. HOW OLD WAS (name) AT HIS/HER LAST BIRTHDAY? Record age in completed years. BH7. IS (name) LIVING WITH YOU? 1 Yes 2 No BH8. Record household line number of child (from HL1) Record “00” if child is not listed. BH9. If dead: HOW OLD WAS (name) WHEN HE/SHE DIED? Record days if less than 1 month; record months if less than 2 years; or years BH10. WERE THERE ANY OTHER LIVE BIRTHS BETWEEN (name of previous birth) AND (name), INCLUDING ANY CHILDREN WHO DIED AFTER BIRTH? 1 Yes 2 No S M B G Month Year Y N Age Y N Line No Unit Number Y N 01 1 2 1 2 ___ ___ ___ ___ ___ ___ 1 2 ___ ___ 1 2 ___ ___ Ö Next Line Days . 1 Months . 2 Years . 3 ___ ___ Ö BH9 02 1 2 1 2 ___ ___ ___ ___ ___ ___ 1 2 ___ ___ 1 2 ___ ___ Ö BH10 Days . 1 Months . 2 Years . 3 ___ ___ 1 2 Ö BH9 03 1 2 1 2 ___ ___ ___ ___ ___ ___ 1 2 ___ ___ 1 2 ___ ___ Ö BH10 Days . 1 Months . 2 Years . 3 ___ ___ 1 2 Ö BH9 04 1 2 1 2 ___ ___ ___ ___ ___ ___ 1 2 ___ ___ 1 2 ___ ___ Ö BH10 Days . 1 Months . 2 Years . 3 ___ ___ 1 2 Ö BH9 05 1 2 1 2 ___ ___ ___ ___ ___ ___ 1 2 ___ ___ 1 2 ___ ___ Ö BH10 Days . 1 Months . 2 Years . 3 ___ ___ 1 2 Ö BH9 06 1 2 1 2 ___ ___ ___ ___ ___ ___ 1 2 ___ ___ 1 2 ___ ___ Ö BH10 Days . 1 Months . 2 Years . 3 ___ ___ 1 2 Ö BH9 07 1 2 1 2 ___ ___ ___ ___ ___ ___ 1 2 ___ ___ 1 2 ___ ___ Ö BH10 Days . 1 Months . 2 Years . 3 ___ ___ 1 2 Ö BH9 355 BH Line No. BH1. WHAT NAME WAS GIVEN TO YOUR (first/next) BABY? BH2. WERE ANY OF THESE BIRTHS TWINS? 1 Single 2 Multiple BH3. IS (name) A BOY OR A GIRL? 1 Boy 2 Girl BH4. IN WHAT MONTH AND YEAR WAS (name) BORN? Probe: WHAT IS HIS/HER BIRTHDAY? BH5. IS (name) STILL ALIVE? 1 Yes 2 No BH6. HOW OLD WAS (name) AT HIS/HER LAST BIRTHDAY? Record age in completed years. BH7. IS (name) LIVING WITH YOU? 1 Yes 2 No BH8. Record household line number of child (from HL1) Record “00” if child is not listed. BH9. If dead: HOW OLD WAS (name) WHEN HE/SHE DIED? Record days if less than 1 month; record months if less than 2 years; or years BH10. WERE THERE ANY OTHER LIVE BIRTHS BETWEEN (name of previous birth) AND (name), INCLUDING ANY CHILDREN WHO DIED AFTER BIRTH? 1 Yes 2 No S M B G Month Year Y N Age Y N Line No Unit Number Y N 08 1 2 1 2 ___ ___ ___ ___ ___ ___ 1 2 ___ ___ 1 2 ___ ___ Ö BH10 Days . 1 Months . 2 Years . 3 ___ ___ 1 2 Ö BH9 09 1 2 1 2 ___ ___ ___ ___ ___ ___ 1 2 ___ ___ 1 2 ___ ___ Ö BH10 Days . 1 Months . 2 Years . 3 ___ ___ 1 2 Ö BH9 10 1 2 1 2 ___ ___ ___ ___ ___ ___ 1 2 ___ ___ 1 2 ___ ___ Ö BH10 Days . 1 Months . 2 Years . 3 ___ ___ 1 2 Ö BH9 11 1 2 1 2 ___ ___ ___ ___ ___ ___ 1 2 ___ ___ 1 2 ___ ___ Ö BH10 Days . 1 Months . 2 Years . 3 ___ ___ 1 2 Ö BH9 12 1 2 1 2 ___ ___ ___ ___ ___ ___ 1 2 ___ ___ 1 2 ___ ___ Ö BH10 Days . 1 Months . 2 Years . 3 ___ ___ 1 2 Ö BH9 13 1 2 1 2 ___ ___ ___ ___ ___ ___ 1 2 ___ ___ 1 2 ___ ___ Ö BH10 Days . 1 Months . 2 Years . 3 ___ ___ 1 2 Ö BH9 14 1 2 1 2 ___ ___ ___ ___ ___ ___ 1 2 ___ ___ 1 2 ___ ___ Ö BH10 Days . 1 Months . 2 Years . 3 ___ ___ 1 2 Ö BH9 356 BH Line No. BH1. WHAT NAME WAS GIVEN TO YOUR (first/next) BABY? BH2. WERE ANY OF THESE BIRTHS TWINS? 1 Single 2 Multiple BH3. IS (name) A BOY OR A GIRL? 1 Boy 2 Girl BH4. IN WHAT MONTH AND YEAR WAS (name) BORN? Probe: WHAT IS HIS/HER BIRTHDAY? BH5. IS (name) STILL ALIVE? 1 Yes 2 No BH6. HOW OLD WAS (name) AT HIS/HER LAST BIRTHDAY? Record age in completed years. BH7. IS (name) LIVING WITH YOU? 1 Yes 2 No BH8. Record household line number of child (from HL1) Record “00” if child is not listed. BH9. If dead: HOW OLD WAS (name) WHEN HE/SHE DIED? Record days if less than 1 month; record months if less than 2 years; or years BH10. WERE THERE ANY OTHER LIVE BIRTHS BETWEEN (name of previous birth) AND (name), INCLUDING ANY CHILDREN WHO DIED AFTER BIRTH? 1 Yes 2 No S M B G Month Year Y N Age Y N Line No Unit Number Y N BH11. HAVE YOU HAD ANY LIVE BIRTHS SINCE THE BIRTH OF (name of last birth in BIRTH HISTORY Module)? Yes . 1 No . 2 1ÖRecord birth(s) in Birth History 357 CM12A. Compare number in CM10 with number of births in the BIRTH HISTORY Module above and check: … Numbers are same Ö Continue with CM13. … Numbers are different Ö Probe and reconcile. CM13. Check BH4 in BIRTH HISTORY Module: Last birth occurred within the last 2 years, that is, since (month of interview) in 2012 (if the month of interview and the month of birth are the same, and the year of birth is 2012, consider this as a birth within the last 2 years) … No live birth in last 2 years. Ö Go to ILLNESS SYMPTOMS Module. … One or more live births in last 2 years. Ö Record name of last born child and continue with Next Module. Name of last-born child_______________________ If child has died, take special care when referring to this child by name in the following modules. 358 DESIRE FOR LAST BIRTH DB This module is to be administered to all women with a live birth in the 2 years preceding the date of interview. Record name of last-born child from CM13 here _____________________. Use this child’s name in the following questions, where indicated. DB1. WHEN YOU GOT PREGNANT WITH (name), DID YOU WANT TO GET PREGNANT AT THAT TIME? Yes . 1 No . 2 1ÖNext Module DB2. DID YOU WANT TO HAVE A BABY LATER ON, OR DID YOU NOT WANT ANY (MORE) CHILDREN? Later . 1 No more . 2 2ÖNext Module DB3. HOW MUCH LONGER DID YOU WANT TO WAIT? Record the answer as stated by respondent. Months . 1 __ __ Years . 2 __ __ DK. 998 359 MATERNAL AND NEWBORN HEALTH MN This module is to be administered to all women with a live birth in the 2 years preceding the date of interview. Record name of last-born child from CM13 here _____________________. Use this child’s name in the following questions, where indicated. MN1. DID YOU SEE ANYONE FOR ANTENATAL CARE DURING YOUR PREGNANCY WITH (name)? Yes . 1 No . 2 2ÖMN5 MN2. WHOM DID YOU SEE? Probe: ANYONE ELSE? Probe for the type of person seen and circle all answers given. Health professional: Doctor . A Nurse midwife . B Health visitor . C Certified midwife . D Medical assistant . E Other person Traditional birth attendant/Daya habil . F Community health worker . G Other (specify) _______________________ X MN2A. HOW MANY WEEKS OR MONTHS PREGNANT WERE YOU WHEN YOU FIRST RECEIVED ANTENATAL CARE FOR THIS PREGNANCY? Record the answer as stated by respondent. Weeks . 1 __ __ Months . 2 0 __ DK . 998 MN3. HOW MANY TIMES DID YOU RECEIVE ANTENATAL CARE DURING THIS PREGNANCY? Probe to identify the number of times antenatal care was received. If a range is given, record the minimum number of times antenatal care received. Number of times . __ __ DK . 98 MN4. AS PART OF YOUR ANTENATAL CARE DURING THIS PREGNANCY, WERE ANY OF THE FOLLOWING DONE AT LEAST ONCE: [A] WAS YOUR BLOOD PRESSURE MEASURED? [B] DID YOU GIVE A URINE SAMPLE? [C] DID YOU GIVE A BLOOD SAMPLE? Yes No Blood pressure . 1 2 Urine sample . 1 2 Blood sample . 1 2 MN4D. WHILE YOU WERE RECEIVING ANTENATAL CARE, WAS THE TYPE OF YOUR DELIVERY DISCUSSED (NORMAL OF CAESAREAN SECTION) WITH YOU? Yes . 1 No. 2 MN4E. WHILE YOU WERE RECEIVING ANTENATAL CARE, WAS THE PLACE OF YOUR DELIVERY DISCUSSED WITH YOU? Yes . 1 No. 2 MN4F. DURING YOUR PREGNANCY WITH (name) DID YOU USE IRON OR FEFOL TABLETS OR SYRUP LIKE THESE? Show the tablets Yes . 1 No. 2 DK . 8 MN5. DO YOU HAVE AN IMMUNIZATION CARD OR OTHER DOCUMENT WITH YOUR OWN IMMUNIZATIONS LISTED? MAY I SEE IT PLEASE? If a card is presented, use it to assist with answers to the following questions. Yes (card seen) . 1 Yes (card not seen) . 2 No. 3 DK . 8 360 MN6. WHEN YOU WERE PREGNANT WITH (name), DID YOU RECEIVE ANY INJECTION IN THE SHOULDER TO PREVENT THE BABY FROM GETTING TETANUS, THAT IS CONVULSIONS AFTER BIRTH? Yes . 1 No. 2 DK . 8 2ÖMN9 8ÖMN9 MN7. HOW MANY TIMES DID YOU RECEIVE THIS TETANUS INJECTION DURING YOUR PREGNANCY WITH (name)? Number of times . __ DK . 8 8ÖMN9 MN8. How many tetanus injections during last pregnancy were reported in MN7? … At least two tetanus injections during last pregnancy. Ö Go to MN17. … Only one tetanus injection during last pregnancy. Ö Continue with MN9. MN9. DID YOU RECEIVE ANY TETANUS INJECTION AT ANY TIME BEFORE YOUR PREGNANCY WITH (name), EITHER TO PROTECT YOURSELF OR ANOTHER BABY? Yes . 1 No. 2 DK . 8 2ÖMN17 8ÖMN17 MN10. HOW MANY TIMES IN YOUR LIFE DID YOU RECEIVE A TETANUS INJECTION BEFORE YOUR PREGNANCY WITH (NAME)? If 5 or more times, record ‘5’. Number of times . __ DK . 8 8ÖMN17 MN11. HOW MANY YEARS AGO DID YOU RECEIVE THE LAST TETANUS INJECTION BEFORE YOUR PREGNANCY WITH (name)? If less than 1 year, record ‘00’. Years ago . __ __ MN17. WHO ASSISTED WITH THE DELIVERY OF (name)? Probe: ANYONE ELSE? Probe for the type of person assisting and circle all answers given. If respondent says no one assisted, probe to determine whether any adults were present at the delivery. Health professional: Doctor . A Nurse midwife . B Health visitor . C Certified midwife . D Medical assistant . E Other person Traditional birth attendant/ Daya habil . F Community health worker . G Other (specify) _______________________ X No one . Y MN18. WHERE DID YOU GIVE BIRTH TO (name)? Probe to identify the type of source. If unable to determine whether public or private, write the name of the place. (Name of place) Home . Respondent’s home . 11 Other home . 12 Public sector Government hospital . 21 Government clinic / health centre . 22 Government health post . 23 Other public (specify) _____________ 26 Private medical Ssector Private hospital . 31 Private clinic . 32 Other private medical (specify) _______________ 36 Other (specify) ______________________ 96 11ÖMN20 12ÖMN20 96ÖMN20 361 MN18A. WHAT WAS THE MODE OF DELIVERY OF (name)? Vaginal delivery . 1 Assisted delivery (vacuum or forceps) . 2 Caesarean section……………………….….3 1ÖMN20 2ÖMN20 MN19A. WHEN WAS THE DECISION MADE TO HAVE THE CAESAREAN SECTION? WAS IT BEFORE OR AFTER YOUR LABOUR PAINS STARTED? Before . 1 After . 2 MN20. WHEN (name) WAS BORN, WAS HE/SHE VERY LARGE, LARGER THAN AVERAGE, AVERAGE, SMALLER THAN AVERAGE, OR VERY SMALL? Very large . 1 Larger than average . 2 Average . 3 Smaller than average . 4 Very small . 5 DK . 8 MN21. WAS (name) WEIGHED AT BIRTH? Yes . 1 No . 2 DK . 8 2ÖMN23 8ÖMN23 MN22. HOW MUCH DID (name) WEIGH? If a card is available, record weight from card. From card . 1 (kg) __ . __ __ __ From recall . 2 (kg) __ . __ __ __ DK . 99998 MN23. HAS YOUR MENSTRUAL PERIOD RETURNED SINCE THE BIRTH OF (name)? Yes . 1 No . 2 MN24. DID YOU EVER BREASTFEED (name)? Yes . 1 No . 2 2ÖNext Module (Post-natal health checks) MN25. HOW LONG AFTER BIRTH DID YOU FIRST PUT (name) TO THE BREAST? If less than 1 hour, record “00” hours. If less than 24 hours, record hours. Otherwise, record days. Immediately . 000 Hours . 1 __ __ Days . 2 __ __ DK / Don’ t remember 998 MN26. IN THE FIRST THREE DAYS AFTER DELIVERY, WAS (name) GIVEN ANYTHING TO DRINK OTHER THAN BREAST MILK? Yes . 1 No . 2 2ÖNext Module (Post-natal health checks) MN27. WHAT WAS (name) GIVEN TO DRINK? Probe: ANYTHING ELSE? Milk (other than breast milk) . A Plain water . B Sugar or glucose water . C Gripe water . D Sugar-salt-water solution . E Fruit juice . F Infant formula . G Tea / herbal Infusions . H Honey . I Other (specify) _______________________ X 362 363 POST-NATAL HEALTH CHECKS PN This module is to be administered to all women with a live birth in the 2 years preceding the date of interview. Record name of last-born child from CM13 here _____________________. Use this child’s name in the following questions, where indicated. PN1. Check MN18: Was the child delivered in a health facility? … Yes, the child was delivered in a health facility (MN18=21-26 or 31-32) Ö Continue with PN2. … No, the child was not delivered in a health facility (MN18=11-12 or 96) Ö Go to PN6. PN2. NOW I WOULD LIKE TO ASK YOU SOME QUESTIONS ABOUT WHAT HAPPENED IN THE HOURS AND DAYS AFTER THE BIRTH OF (name). YOU HAVE SAID THAT YOU GAVE BIRTH IN (name or type of facility in MN18). HOW LONG DID YOU STAY THERE AFTER THE DELIVERY? If less than one day, record hours. If less than one week, record days. Otherwise, record weeks. Hours . 1 __ __ Days . 2 __ __ Weeks . 3 __ __ DK / Don’t remember . 998 PN3. I WOULD LIKE TO TALK TO YOU ABOUT CHECKS ON (name)’S HEALTH AFTER DELIVERY – FOR EXAMPLE, SOMEONE EXAMINING (name), CHECKING THE CORD, OR SEEING IF (name) IS OK. BEFORE YOU LEFT THE (name or type of facility in MN18), DID ANYONE CHECK ON (name)’S HEALTH? Yes . 1 No . 2 PN4. AND WHAT ABOUT CHECKS ON YOUR HEALTH – I MEAN, SOMEONE ASSESSING YOUR HEALTH, FOR EXAMPLE ASKING QUESTIONS ABOUT YOUR HEALTH OR EXAMINING YOU? DID ANYONE CHECK ON YOUR HEALTH BEFORE YOU LEFT (name or type or facility in MN18)? Yes . 1 No . 2 PN5. NOW I WOULD LIKE TO TALK TO YOU ABOUT WHAT HAPPENED AFTER YOU LEFT (name or type of facility in MN18). DID ANYONE CHECK ON (name)’S HEALTH AFTER YOU LEFT (name or type of facility in MN18)? Yes . 1 No . 2 1ÖPN11 2ÖPN16 PN6. Check MN17: Did a health professional, traditional birth attendant, or community health worker assist with the delivery? … Yes, delivery assisted by a health professional, traditional birth attendant, or community health worker (MN17=A-G) Ö Continue with PN7. … No, delivery not assisted by a health professional, traditional birth attendant, or community health worker (A-G not circled in MN17) Ö Go to PN10. 364 PN7. YOU HAVE ALREADY SAID THAT (person or persons in MN17) ASSISTED WITH THE BIRTH. NOW I WOULD LIKE TO TALK TO YOU ABOUT CHECKS ON (name)’S HEALTH AFTER DELIVERY, FOR EXAMPLE EXAMINING (name), CHECKING THE CORD, OR SEEING IF (name) IS OK. AFTER THE DELIVERY WAS OVER AND BEFORE (person or persons in MN17) LEFT YOU, DID (person or persons in MN17) CHECK ON (name)’S HEALTH? Yes . 1 No . 2 PN8. AND DID (person or persons in MN17) CHECK ON YOUR HEALTH BEFORE LEAVING? BY CHECK ON YOUR HEALTH, I MEAN ASSESSING YOUR HEALTH, FOR EXAMPLE ASKING QUESTIONS ABOUT YOUR HEALTH OR EXAMINING YOU. Yes . 1 No . 2 PN9. AFTER THE (person or persons in MN17) LEFT YOU, DID ANYONE CHECK ON THE HEALTH OF (name)? Yes . 1 No . 2 1ÖPN11 2ÖPN18 PN10. I WOULD LIKE TO TALK TO YOU ABOUT CHECKS ON (name)’S HEALTH AFTER DELIVERY – FOR EXAMPLE, SOMEONE EXAMINING (name), CHECKING THE CORD, OR SEEING IF THE BABY IS OK. AFTER (name) WAS DELIVERED, DID ANYONE CHECK ON HIS/HER HEALTH? Yes . 1 No . 2 2ÖPN19 PN11. DID SUCH A CHECK HAPPEN ONLY ONCE, OR MORE THAN ONCE? Once . 1 More than once . 2 1ÖPN12A 2ÖPN12B PN12A. HOW LONG AFTER DELIVERY DID THAT CHECK HAPPEN? PN12B. HOW LONG AFTER DELIVERY DID THE FIRST OF THESE CHECKS HAPPEN? If less than one day, record hours. If less than one week, record days. Otherwise, record weeks. Hours . 1 __ __ Days . 2 __ __ Weeks . 3 __ __ DK / Don’t remember . 998 365 PN13. WHO CHECKED ON (name)’S HEALTH AT THAT TIME? Health professional Doctor . A Nurse midwife . B Health visitor . C Certified midwife . D Medical assistant . E Other person Traditional birth attendant /Dayat habel . F Community health worker . G Other (specify) _______________________ X PN14. WHERE DID THIS CHECK TAKE PLACE? Probe to identify the type of source. If unable to determine whether public or private, write the name of the place. (Name of place) Home Respondent’s home . 11 Other home . 12 Public sector Government hospital . 21 Government clinic / health centre . 22 Government health post . 23 Other public (specify) ______________ 26 Private medical sector Private hospital . 31 Private clinic . 32 Other private medical (specify) _______________ 36 Other (specify) ______________________ 96 PN15. Check MN18: Was the child delivered in a health facility? … Yes, the child was delivered in a health facility (MN18=21-26 or 31-36) Ö Continue with PN16. … No, the child was not delivered in a health facility (MN18=11-12 or 96) Ö Go to PN17. PN16. AFTER YOU LEFT (name or type of facility in MN18), DID ANYONE CHECK ON YOUR HEALTH? Yes . 1 No . 2 1ÖPN20 2ÖNext Module (Illness symptoms) PN17. Check MN17: Did a health professional, traditional birth attendant, or community health worker assist with the delivery? … Yes, delivery assisted by a health professional, traditional birth attendant, or community health worker (MN17=A-G) Ö Continue with PN18 … No, delivery not assisted by a health professional, traditional birth attendant, or community health worker (A-G not circled in MN17) Ö Go to PN19 PN18. AFTER THE DELIVERY WAS OVER AND (person or persons in MN17) LEFT, DID ANYONE CHECK ON YOUR HEALTH? Yes . 1 No . 2 1ÖPN20 2ÖNext Module (Illness symptoms) 366 PN19. AFTER THE BIRTH OF (name), DID ANYONE CHECK ON YOUR HEALTH? I MEAN SOMEONE ASSESSING YOUR HEALTH, FOR EXAMPLE ASKING QUESTIONS ABOUT YOUR HEALTH OR EXAMINING YOU. Yes . 1 No . 2 2ÖNext Module (Illness symptoms) PN20. DID SUCH A CHECK HAPPEN ONLY ONCE, OR MORE THAN ONCE? Once . 1 More than once . 2 1ÖPN21A 2ÖPN21B PN21A. HOW LONG AFTER DELIVERY DID THAT CHECK HAPPEN? PN21B. HOW LONG AFTER DELIVERY DID THE FIRST OF THESE CHECKS HAPPEN? If less than one day, record hours. If less than one week, record days. Otherwise, record weeks. Hours . 1 __ __ Days . 2 __ __ Weeks . 3 __ __ DK / Don’t remember . 998 PN22. WHO CHECKED ON YOUR HEALTH AT THAT TIME? Health professional Doctor . A Nurse midwife . B Health visitor . C Certified midwife . D Medical assistant . E Other person Traditional birth attendant (Dayat habel). F Community health worker . G Other (specify) _______________________ X PN23. WHERE DID THIS CHECK TAKE PLACE? Probe to identify the type of source. If unable to determine whether public or private, write the name of the place. (Name of place) Home Respondent’s home . 11 Other home . 12 Public sector Government hospital . 21 Government clinic / health centre . 22 Government health post . 23 Other public (specify) ______________ 26 Private medical sector Private hospital . 31 Private clinic . 32 Private maternity home . 33 Other private medical (specify) _______________ 36 Other (specify) ______________________ 96 367 ILLNESS SYMPTOMS IS IS1. Check List of Household Members, columns HL7B and HL15: Is the respondent the mother or caretaker of any child under age 5? … Yes Ö Continue with IS2. … No Ö Go to Next Module. IS2. SOMETIMES CHILDREN HAVE SEVERE ILLNESSES AND SHOULD BE TAKEN IMMEDIATELY TO A HEALTH FACILITY. WHAT TYPES OF SYMPTOMS WOULD CAUSE YOU TO TAKE A CHILD UNDER THE AGE OF 5 TO A HEALTH FACILITY RIGHT AWAY? Probe: ANY OTHER SYMPTOMS? Keep asking for more signs or symptoms until the mother/caretaker cannot recall any additional symptoms. Circle all symptoms mentioned, but do not prompt with any suggestions Child not able to drink or breastfeed . A Child becomes sicker . B Child develops a fever . C Child has fast breathing . D Child has difficulty breathing . E Child has blood in stool . F Child is drinking poorly . G Other (specify) ______________________ X Other (specify) ______________________ Y Other (specify) ______________________ Z 368 CONTRACEPTION CP CP0: Check MA1: respondent is currently married? … No, Ö Go to FGM module … Yes, currently married Ö Continue with CP1 CP1. I WOULD LIKE TO TALK WITH YOU ABOUT ANOTHER SUBJECT – FAMILY PLANNING. ARE YOU PREGNANT NOW? Yes, currently pregnant . 1 No . 2 Unsure or DK . 8 1ÖCP2A CP2. COUPLES USE VARIOUS WAYS OR METHODS TO DELAY OR AVOID A PREGNANCY. ARE YOU CURRENTLY DOING SOMETHING OR USING ANY METHOD TO DELAY OR AVOID GETTING PREGNANT? Yes . 1 No . 2 1ÖCP3 CP2A. HAVE YOU EVER DONE SOMETHING OR USED ANY METHOD TO DELAY OR AVOID GETTING PREGNANT? Yes . 1 No . 2 1ÖNext Module (Unmet need) 2ÖNext Module (Unmet need) CP3. WHAT ARE YOU DOING TO DELAY OR AVOID A PREGNANCY? Do not prompt. If more than one method is mentioned, circle each one. IUD . C Injectables . D Implants . E Pill . F Male condom . G Female condom . H Diaphragm . I Foam / Jelly . J Lactational amenorrhoea method (LAM) . K Periodic abstinence / Rhythm . L Withdrawal . M Other (specify) _______________________ X 369 UNMET NEED UN UN1. Check CP1: Currently pregnant? … Yes, currently pregnant Ö Continue with UN2. … No, unsure or DK Ö Go to UN6. UN2. NOW I WOULD LIKE TO TALK TO YOU ABOUT YOUR CURRENT PREGNANCY. WHEN YOU GOT PREGNANT, DID YOU WANT TO GET PREGNANT AT THAT TIME? Yes . 1 No . 2 1ÖUN4 UN3. DID YOU WANT TO HAVE A BABY LATER ON OR DID YOU NOT WANT ANY (MORE) CHILDREN? Later . 1 No more . 2 UN4. NOW I WOULD LIKE TO ASK SOME QUESTIONS ABOUT THE FUTURE. AFTER THE CHILD YOU ARE NOW EXPECTING, WOULD YOU LIKE TO HAVE ANOTHER CHILD, OR WOULD YOU PREFER NOT TO HAVE ANY MORE CHILDREN? Have another child . 1 No more / None . 2 Undecided / DK . 8 1ÖUN7 2ÖUN13 8ÖUN13 UN6. NOW I WOULD LIKE TO ASK YOU SOME QUESTIONS ABOUT THE FUTURE. WOULD YOU LIKE TO HAVE (A/ANOTHER) CHILD, OR WOULD YOU PREFER NOT TO HAVE ANY (MORE) CHILDREN? Have (a/another) child . 1 No more / None . 2 Says she cannot get pregnant . 3 Undecided / DK . 8 2ÖUN9 3ÖUN11 8ÖUN9 UN7. HOW LONG WOULD YOU LIKE TO WAIT BEFORE THE BIRTH OF (A/ANOTHER) CHILD? Record the answer as stated by respondent. Months . 1 __ __ Years . 2 __ __ Does not want to wait (soon/now) . 993 Says she cannot get pregnant . 994 Other . 996 DK . 998 994ÖUN11 UN8. Check CP1: Currently pregnant? … Yes, currently pregnant Ö Go to UN13. … No, unsure or DK Ö Continue with UN9. 370 UN9. Check CP2: Currently using a method? … Yes Ö Go to UN13. … No Ö Continue with UN10. UN10. DO YOU THINK YOU ARE PHYSICALLY ABLE TO GET PREGNANT AT THIS TIME? Yes . 1 No . 2 DK . 8 1 ÖUN13 8 ÖUN13 UN11. WHY DO YOU THINK YOU ARE NOT PHYSICALLY ABLE TO GET PREGNANT? Infrequent sex / No sex . A Menopausal . B Never menstruated . C Hysterectomy (surgical removal of uterus) . D Has been trying to get pregnant for 2 years or more without result . E Postpartum amenorrheic . F Breastfeeding .G Too old . H Fatalistic . I Other (specify) ______________________ X DK . Z UN12. Check UN11: “Never menstruated” mentioned? … Mentioned Ö Go to Next Module. … Not mentioned Ö Continue with UN13. UN13. WHEN DID YOUR LAST MENSTRUAL PERIOD START? Record the answer using the same unit stated by the respondent. Days ago . 1 __ __ Weeks ago . 2 __ __ Months ago . 3 __ __ Years ago . 4 __ __ In menopause / Has had hysterectomy . 994 Before last birth . 995 Never menstruated . 996 371 FEMALE GENITAL MUTILATION/CUTTING FG FG1. HAVE YOU EVER HEARD OF FEMALE CIRCUMCISION? Yes . 1 No . 2 2ÖNext Module (Domestic violence) FG3. HAVE YOU YOURSELF EVER BEEN CIRCUMCISED? Yes . 1 No . 2 2ÖFG8C FG4. NOW I WOULD LIKE TO ASK YOU WHAT WAS DONE TO YOU AT THAT TIME. WAS ANY FLESH REMOVED FROM THE GENITAL AREA? Yes . 1 No . 2 DK . 8 1ÖFG6 FG5. WAS THE GENITAL AREA JUST NICKED WITHOUT REMOVING ANY FLESH? Yes . 1 No . 2 DK . 8 FG6. WAS THE GENITAL AREA SEWN CLOSED? If necessary, probe: Was it sealed? Yes . 1 No . 2 DK . 8 FG7. HOW OLD WERE YOU WHEN YOU WERE CIRCUMCISED? If the respondent does not know the exact age, probe to get an estimate Age at circumcision . __ __ DK / Don’t remember / Not sure . 98 FG8. WHO PERFORMED THE CIRCUMCISION? Health professional Doctor . 11 Nurse Midwife . 12 Health visitor . 13 Certified midwife. 14 Medical assistant. 15 Other health professional (specify) ____________ 16 Traditional persons Traditional birth attendant . 22 Other traditional (specify) _____________ 26 DK . 98 FG8A. Check MA1 and MA5: Is the respondent currently married or ever married? … No Ö Go to FG22 … Yes Ö Continue with FG8B FG8B. DID YOU PERFORM RE CIRCUMCISION (ADAL) ? Yes . 1 No . 2 DK . 8 FG8C. Check MA1 and MA5: Is the respondent currently married or ever married? … No Ö Go to FG22 … Yes Ö Continue with FG9 FG9. Check CM5 for Number of daughters at home and CM7 for Number of daughters elsewhere, and sum the answers here Total number of living daughters . ___ ___ 372 FG10. JUST TO MAKE SURE THAT I HAVE THIS RIGHT, YOU HAVE (total number in FG9) LIVING DAUGHTERS. IS THIS CORRECT? … Yes … One or more living daughters Ö Continue with FG11 … Does not have any living daughters Ö Go to FG22 … No Ö Check responses to CM1 – CM10 and make corrections as necessary, until FG10 = Yes FG11. Ask the respondent to tell you the name(s) of her daughter(s), beginning with the youngest daughter (if more than one daughter). Write down the name of each daughter in FG12. Then, ask questions FG13 to FG20 for each daughter at a time. The total number of daughters in FG12 should be equal to the number in FG9. If more than 4 daughters, use additional questionnaires. Daughter #1 Daughter #2 Daughter #3 Daughter #4 FG12. Name of daughter ___________ ___________ ___________ ___________ FG13. HOW OLD IS (name)? Age . ___ ___ Age . ___ ___ Age . ___ ___ Age . ___ ___ FG14. IS (name) YOUNGER THAN 15 YEARS OF AGE? Yes . 1 No . 2 If “No”, go to FG13 for next daughter. If no more daughters, go to FG22. Yes . 1 No . 2 If “No”, go to FG13 for next daughter. If no more daughters, go to FG22. Yes . 1 No . 2 If “No”, go to FG13 for next daughter. If no more daughters, go to FG22. Yes. 1 No . 2 If “No”, go to FG13 for next daughter in an additional questionnaire. If no more daughters, go to FG22. FG15. IS (name) CIRCUMCISED? Yes . 1 No . 2 If “No”, go to FG13 for next daughter. If no more daughters, go to FG22. Yes . 1 No . 2 If “No”, go to FG13 for next daughter. If no more daughters, go to FG22. Yes . 1 No . 2 If “No”, go to FG13 for next daughter. If no more daughters, go to FG22. Yes. 1 No . 2 If “No”, go to FG13 for next daughter in an additional questionnaire. If no more daughters, go to FG22. FG16. HOW OLD WAS (name) WHEN THIS OCCURRED? If the respondent does not know the age, probe to get an estimate. Age . ___ ___ DK . 98 Age . ___ ___ DK . 98 Age . ___ ___ DK . 98 Age . ___ ___ DK . 98 373 FG20. WHO PERFORMED THE CIRCUMCISION? Health professional Doctor . 11 Nurse midwife . 12 Health visitor . 13 Certified midwife . . 14 Medical assistant . 15 Other health professional (specify) ____ 16 Traditional persons Traditional birth attendant . 22 Other traditional (specify) ____ 26 DK 98 Health professional Doctor . 11 Nurse midwife . 12 Health visitor . 13 Certified midwife . . 14 Medical assistant . 15 Other health professional (specify) ____ 16 Traditional persons Traditional birth attendant . 22 Other traditional (specify) ____ 26 DK . 98 Health professional Doctor . 11 Nurse midwife . 12 Health visitor . 13 Certified midwife . . 14 Medical assistant . 15 Other health professional (specify) ____ 16 Traditional persons Traditional birth attendant . 22 Other traditional (specify) ____ 26 DK . 98 Health professional Doctor . 11 Nurse midwife . 12 Health visitor . 13 Certified midwife . . 14 Medical assistant . 15 Other health professional (specify) ____ 16 Traditional persons Traditional birth attendant . 22 Other traditional (specify) ____ 26 DK . 98 FG21. Go back to FG13 for next daughter. If no more daughters, continue with FG22. Go back to FG13 for next daughter. If no more daughters, continue with FG22. Go back to FG13 for next daughter. If no more daughters, continue with FG22. Go back to FG13 in first column of additional questionnaire for next daughter. If no more daughters, continue with FG22. Tick here if additional questionnaire used. … FG22 DO YOU THINK THIS PRACTICE SHOULD BE CONTINUED OR SHOULD IT BE DISCONTINUED Continued . 1 Discontinued . 2 Depends . 3 DK. 8 FG23 WHAT DO YOU NAME GIRL WHO IS NOT CIRCUMCISED ? Not circumcised . 1 Intact (Salema) . 2 Not sanitized/unclean (Ma mutahara) . 3 Other (specify) ______________________ 8 374 ATTITUDES TOWARD DOMESTIC VIOLENCE DV DV1. SOMETIMES A HUSBAND IS ANNOYED OR ANGERED BY THINGS THAT HIS WIFE DOES. IN YOUR OPINION, IS A HUSBAND JUSTIFIED IN HITTING OR BEATING HIS WIFE IN THE FOLLOWING SITUATIONS: [A] IF SHE GOES OUT WITHOUT TELLING HIM? [B] IF SHE NEGLECTS THE CHILDREN? [C] IF SHE ARGUES WITH HIM? [D] IF SHE REFUSES TO HAVE SEX WITH HIM? [E] IF SHE BURNS THE FOOD? Yes No DK Goes out without telling . 1 2 8 Neglects children . 1 2 8 Argues with him . 1 2 8 Refuses sex . 1 2 8 Burns food . 1 2 8 375 HIV/AIDS HA HA1. NOW I WOULD LIKE TO TALK WITH YOU ABOUT SOMETHING ELSE. HAVE YOU EVER HEARD OF AN ILLNESS CALLED AIDS? Yes . 1 No . 2 2ÖWM11 HA2. CAN PEOPLE REDUCE THEIR CHANCE OF GETTING THE AIDS VIRUS BY HAVING JUST ONE UNINFECTED SEX PARTNER WHO HAS NO OTHER SEX PARTNERS? Yes . 1 No . 2 DK . 8 HA3. CAN PEOPLE GET THE AIDS VIRUS BECAUSE OF WITCHCRAFT OR OTHER SUPERNATURAL MEANS? Yes . 1 No . 2 DK . 8 HA4. CAN PEOPLE REDUCE THEIR CHANCE OF GETTING THE AIDS VIRUS BY USING A CONDOM EVERY TIME THEY HAVE SEX? Yes . 1 No . 2 DK . 8 HA5. CAN PEOPLE GET THE AIDS VIRUS FROM MOSQUITO BITES? Yes . 1 No . 2 DK . 8 HA6. CAN PEOPLE GET THE AIDS VIRUS BY SHARING FOOD WITH A PERSON WHO HAS THE AIDS VIRUS? Yes . 1 No . 2 DK . 8 HA7. IS IT POSSIBLE FOR A HEALTHY-LOOKING PERSON TO HAVE THE AIDS VIRUS? Yes . 1 No . 2 DK . 8 HA8. CAN THE VIRUS THAT CAUSES AIDS BE TRANSMITTED FROM A MOTHER TO HER BABY: [A] DURING PREGNANCY? [B] DURING DELIVERY? [C] BY BREASTFEEDING? Yes No DK During pregnancy. 1 2 8 During delivery . 1 2 8 By breastfeeding . 1 2 8 HA9. IN YOUR OPINION, IF A FEMALE TEACHER HAS THE AIDS VIRUS BUT IS NOT SICK, SHOULD SHE BE ALLOWED TO CONTINUE TEACHING IN SCHOOL? Yes . 1 No . 2 DK / Not sure / Depends . 8 HA10. WOULD YOU BUY FRESH VEGETABLES FROM A SHOPKEEPER OR VENDOR IF YOU KNEW THAT THIS PERSON HAD THE AIDS VIRUS? Yes . 1 No . 2 DK / Not sure / Depends . 8 HA11. IF A MEMBER OF YOUR FAMILY GOT INFECTED WITH THE AIDS VIRUS, WOULD YOU WANT IT TO REMAIN A SECRET? Yes . 1 No . 2 DK / Not sure / Depends . 8 HA12. IF A MEMBER OF YOUR FAMILY BECAME SICK WITH AIDS, WOULD YOU BE WILLING TO CARE FOR HER OR HIM IN YOUR OWN HOUSEHOLD? Yes . 1 No . 2 DK / Not sure / Depends . 8 376 HA13. Check CM13: Any live birth in last 2 years? … No live birth in last 2 years (CM13=”No” or blank) Ö Go to HA24. … One or more live births in last 2 years Ö Continue with HA14. HA14. Check MN1: Received antenatal care? … Received antenatal care Ö Continue with HA15. … Did not receive antenatal care Ö Go to HA24. HA15. DURING ANY OF THE ANTENATAL VISITS FOR YOUR PREGNANCY WITH (name), WERE YOU GIVEN ANY INFORMATION ABOUT: [A] BABIES GETTING THE AIDS VIRUS FROM THEIR MOTHER? [B] THINGS THAT YOU CAN DO TO PREVENT GETTING THE AIDS VIRUS? [C] GETTING TESTED FOR THE AIDS VIRUS? WERE YOU: [D] OFFERED A TEST FOR THE AIDS VIRUS? Y N DK AIDS from mother . 1 2 8 Things to do . 1 2 8 Tested for AIDS . 1 2 8 Offered a test . 1 2 8 HA16. I DON’T WANT TO KNOW THE RESULTS, BUT WERE YOU TESTED FOR THE AIDS VIRUS AS PART OF YOUR ANTENATAL CARE? Yes . 1 No . 2 DK . 8 2ÖHA19 8ÖHA19 HA17. I DON’T WANT TO KNOW THE RESULTS, BUT DID YOU GET THE RESULTS OF THE TEST? Yes . 1 No . 2 DK . 8 2ÖHA22 8ÖHA22 HA18. REGARDLESS OF THE RESULT, ALL WOMEN WHO ARE TESTED ARE SUPPOSED TO RECEIVE COUNSELLING AFTER GETTING THE RESULT. AFTER YOU WERE TESTED, DID YOU RECEIVE COUNSELLING? Yes . 1 No . 2 DK . 8 1ÖHA22 2ÖHA22 8ÖHA22 HA19. Check MN17: Birth delivered by health professional (A, B, C, D or E)? … Yes, birth delivered by health professional (MN17 = A, B, C, D or E) Ö Continue with HA20. … No, birth not delivered by health professional (MN17 = else) Ö Go to HA24. HA20. I DON’T WANT TO KNOW THE RESULTS, BUT WERE YOU TESTED FOR THE AIDS VIRUS BETWEEN THE TIME YOU WENT FOR DELIVERY BUT BEFORE THE BABY WAS BORN? Yes . 1 No . 2 2ÖHA24 HA21. I DON’T WANT TO KNOW THE RESULTS, BUT DID YOU GET THE RESULTS OF THE TEST? Yes . 1 No . 2 HA22. HAVE YOU BEEN TESTED FOR THE AIDS VIRUS SINCE THAT TIME YOU WERE TESTED DURING YOUR PREGNANCY? Yes . 1 No . 2 1ÖHA25 377 HA23. WHEN WAS THE MOST RECENT TIME YOU WERE TESTED FOR THE AIDS VIRUS? Less than 12 months ago . 1 12-23 months ago . 2 2 or more years ago . 3 1ÖWM11 2ÖWM11 3ÖWM11 HA24. I DON’T WANT TO KNOW THE RESULTS, BUT HAVE YOU EVER BEEN TESTED TO SEE IF YOU HAVE THE AIDS VIRUS? Yes . 1 No . 2 2ÖHA27 HA25. WHEN WAS THE MOST RECENT TIME YOU WERE TESTED? Less than 12 months ago . 1 12-23 months ago . 2 2 or more years ago . 3 HA26. I DON’T WANT TO KNOW THE RESULTS, BUT DID YOU GET THE RESULTS OF THE TEST? Yes . 1 No . 2 DK . 8 1ÖWM11 2ÖWM11 8ÖWM11 HA27. DO YOU KNOW OF A PLACE WHERE PEOPLE CAN GO TO GET TESTED FOR THE AIDS VIRUS? Yes . 1 No . 2 WM11. RECORD THE TIME. Morning . 1 Afternoon . 2 Hour and minutes . __ __ : __ __ WM11A. Indicate to the respondent that you will need to take a blood sample for anaemia and explain that the results will provided to her immediately. Ask the respondent for permission? … Yes, permission is given … No, permission is not given WM12. Check List of Household Members, columns HL7 and HL15: Is the respondent the mother or caretaker of any child age 0-4 living in this household? … Yes Ö Proceed to complete the result of woman’s interview (WM7) on the cover page and then go to QUESTIONNAIRE FOR CHILDREN UNDER FIVE for that child and start the interview with this respondent. … No Ö End the interview with this respondent by thanking her for her cooperation and proceed to Complete the result of woman’s interview (WM7) on the cover page. 378 MID UPPER ARM CIRCUMFERENCE(MUAC) MU After questionnaires for all women and children are complete, then measurer takes the MUAC measures from the respondent .(women and children) MU1. Measurer’s name and number: Name __________________ __ __ MU2. Mid upper arm circumference (MUAC) Circumference (cm) __ __ . __ Circumference not measured 999.9 HAEMOGLOBIN TESTING (ANAEMIA) HT After questionnaires for all women and children are complete, the measurer measuresdraws a sample of blood for testing the Haemoglobin. HT1. Check WM11A: Permission given? … Yes Ö Continue with HT2. … No Ö Go to HT4. HT2. Result of the HB measurement HB measured . 1 Women not present . 2 Other (specify) _______________________ 6 2ÖHT4 6ÖHT4 HT3. HB measurements . ___ ___ . ___ HT4. Is there another woman in the household who is eligible for the blood test? … Yes Ö Go to the Haemoglobin testing module in the next woman questionnaire. … No Ö End the testing procedure. 379 Interviewer’s Observations Field Editor’s Observations Supervisor’s Observations 380 381 Appendix F3: Questionnaire for Children Under-Five QUESTIONNAIRE FOR CHILDREN UNDER FIVE Sudan Multiple Indicator Survey 2014 UNDER-FIVE CHILD INFORMATION PANEL UF This questionnaire is to be administered to all mothers or caretakers (see List of Household Members, column HL15) who care for a child that lives with them and is under the age of 5 years (see List of Household Members, column HL7B). A separate questionnaire should be used for each eligible child. UF0. State code ___ ___ UF1. Cluster number : UF2. Household number: ___ ___ ___ ___ UF3. Child’s name: UF4. Child’s line number: Name ___ ___ UF5. Mother’s / Caretaker’s name: UF6. Mother’s / Caretaker’s line number: Name ___ ___ UF7. Interviewer’s name and number: UF8. Day / Month / Year of interview: Name ___ ___ ___ ___ /___ ___ / 2 0 14 Repeat greeting if not already read to this respondent: WE ARE FROM THE CENTRAL BUREAU OF STATISTICS. WE ARE CONDUCTING A SURVEY ABOUT THE SITUATION OF CHILDREN, FAMILIES AND HOUSEHOLDS. I WOULD LIKE TO TALK TO YOU ABOUT (child’s name from UF3)’S HEALTH AND WELL- BEING. THE INTERVIEW WILL TAKE ABOUT 35 MINUTES. ALL THE INFORMATION WE OBTAIN WILL REMAIN STRICTLY CONFIDENTIAL AND ANONYMOUS. If greeting at the beginning of the household questionnaire has already been read to this person, then read the following: NOW I WOULD LIKE TO TALK TO YOU MORE ABOUT (child’s name from UF3)’S HEALTH AND OTHER TOPICS. THIS INTERVIEW WILL TAKE ABOUT 35 MINUTES. AGAIN, ALL THE INFORMATION WE OBTAIN WILL REMAIN STRICTLY CONFIDENTIAL AND ANONYMOUS. MAY I START NOW? … Yes, permission is given Ö Go to UF12 to record the time and then begin the interview. … No, permission is not given Ö Circle 03 in UF9. Discuss this result with your supervisor. UF9. Result of interview for children under 5 Codes refer to mother/caretaker. Completed . 01 Not at home . 02 Refused . 03 Partly completed . 04 Incapacitated . 05 Other (specify) ___________________________ 96 382 UF10. Field editor’s name and number: Name______________________________ __ __ UF11. Main data entry clerk’s name and number: Name_______________________________ __ __ 383 UF12. Record the time. Morning . 1 Afternoon. 2 Hour and minutes . __ __ : __ __ AGE AG AG1. NOW I WOULD LIKE TO ASK YOU SOME QUESTIONS ABOUT THE DEVELOPMENT AND HEALTH OF (name). ON WHAT DAY, MONTH AND YEAR WAS (name) BORN? Probe: WHAT IS HIS / HER BIRTHDAY? If the mother/caretaker knows the exact birth date, also enter the day; otherwise, circle 98 for day. Month and year must be recorded. Date of birth Day . __ __ DK day . 98 Month . __ __ Year . 2 0 __ __ AG2. HOW OLD IS (name)? Probe: HOW OLD WAS (name) AT HIS / HER LAST BIRTHDAY? Record age in completed years. Record ‘0’ if less than 1 year. Compare and correct AG1 and/or AG2 if inconsistent. Age (in completed years) . __ 384 BIRTH REGISTRATION MODULE BR BR1. DOES (name) HAVE A BIRTH CERTIFICATE? If yes, ask: MAY I SEE IT? Yes, seen . 1 Yes, not seen . 2 No . 3 DK . 8 1ÖNext Module (Early Childhood development ) 2ÖNext Module (Early Childhood development ) BR2. HAS (name)’S BIRTH BEEN REGISTERED WITH THE CIVIL AUTHORITIES? Yes . 1 No . 2 DK . 8 1ÖNext Module (Early Childhood development) 8ÖBR3 BR2A. WHY WASN’T (NAME) REGISTERED? Very expensive . 1 Too far . 2 Did not know that a birth certificate is supposed to be registered . 3 Other (specify) _______________________ 6 BR3. DO YOU KNOW HOW TO REGISTER (name)’S BIRTH? Yes . 1 No . 2 385 EARLY CHILDHOOD DEVELOPMENT MODULE EC EC1. HOW MANY CHILDREN’S BOOKS OR PICTURE BOOKS DO YOU HAVE FOR (name)? None . 00 Number of children’s books . 0 __ Ten or more books . 10 EC2. I AM INTERESTED IN LEARNING ABOUT THE THINGS THAT (name) PLAYS WITH WHEN HE/SHE IS AT HOME. DOES HE/SHE PLAY WITH: [A] HOMEMADE TOYS (SUCH AS DOLLS, CARS, OR OTHER TOYS MADE AT HOME)? [B] TOYS FROM A SHOP OR MANUFACTURED TOYS? [C] HOUSEHOLD OBJECTS (SUCH AS BOWLS OR POTS) OR OBJECTS FOUND OUTSIDE (SUCH AS STICKS, ROCKS, ANIMAL SHELLS OR LEAVES)? If the respondent says “YES” to the categories above, then probe to learn specifically what the child plays with to ascertain the response. Y N DK Homemade toys . 1 2 8 Toys from a shop . 1 2 8 Household objects or outside objects . 1 2 8 EC4. Check AG2: Age of child. … Child age: Newborn (less than a year, 1 or 2 Ö Go to Next Module. … Child age 3 or 4 Ö Continue with EC5. EC5. DOES (name) ATTEND ANY ORGANIZED LEARNING OR EARLY CHILDHOOD EDUCATION PROGRAMME, SUCH AS A PRIVATE OR GOVERNMENT FACILITY, INCLUDING KINDERGARTEN OR COMMUNITY CHILD CARE? Yes . 1 No . 2 DK . 8 2ÖIM20 8ÖIM20 EC5A. DURING THE LAST SEVEN DAYS OF THE PREVIOUS SCHOOL YEAR (2013-2014), HOW MANY DAYS DID (name) ATTEND THIS PROGRAM? Number of days _____ _____ DK 8 386 BREASTFEEDING AND DIETARY INTAKE BD BD1. Check AG2: Age of child … Child age 0, 1 or 2 Ö Continue with BD2. … Child age 3 or 4 Ö Go to IM20 in the immunization module. BD2. HAS (name) EVER BEEN BREASTFED? Yes . 1 No . 2 DK . 8 2ÖBD4 8ÖBD4 BD3. IS (name) STILL BEING BREASTFED? Yes . 1 No . 2 DK . 8 BD4. YESTERDAY, DURING THE DAY OR NIGHT, DID (name) DRINK ANYTHING FROM A BOTTLE WITH A NIPPLE? Yes . 1 No . 2 DK . 8 BD5. DID (name) DRINK ORS (ORAL REHYDRATION SOLUTION) YESTERDAY, DURING THE DAY OR NIGHT? Yes . 1 No . 2 DK . 8 BD6. DID (name) DRINK OR EAT VITAMIN OR MINERAL SUPPLEMENTS OR ANY MEDICINES YESTERDAY, DURING THE DAY OR NIGHT? Yes . 1 No . 2 DK . 8 BD7. NOW I WOULD LIKE TO ASK YOU ABOUT (OTHER) LIQUIDS THAT (name) MAY HAVE HAD YESTERDAY DURING THE DAY OR THE NIGHT. I AM INTERESTED TO KNOW WHETHER (name) HAD THE ITEM EVEN IF COMBINED WITH OTHER FOODS. PLEASE INCLUDE LIQUIDS CONSUMED OUTSIDE OF YOUR HOME. DID (NAME) DRINK (NAME OF ITEM) YESTERDAY DURING THE DAY OR THE NIGHT: Yes No DK [A] PLAIN WATER? Plain water 1 2 8 [B] JUICE OR JUICE DRINKS? Juice or juice drinks 1 2 8 [C] BROTH / CLEAR SOUP (SALEGA/ MARAGA)? Soup 1 2 8 [D] MILK SUCH AS TINNED, POWDERED, OR FRESH ANIMAL MILK? Milk 1 2 8 If yes: HOW MANY TIMES DID (name) DRINK MILK? If 7 or more times, record '7'. If unknown, record ‘8’. Number of times drank milk . __ [E] INFANT FORMULA? Infant formula 1 2 8 If yes: HOW MANY TIMES DID (name) DRINK INFANT FORMULA? If 7 or more times, record '7'. If unknown, record ‘8’. Number of times drank infant formula . __ [F] ANY OTHER LIQUIDS? (Specify)_____________________________ Other liquids 1 2 8 387 BD8. NOW I WOULD LIKE TO ASK YOU ABOUT (OTHER) FOODS THAT (name) MAY HAVE HAD YESTERDAY DURING THE DAY OR THE NIGHT. AGAIN, I AM INTERESTED TO KNOW WHETHER (name) HAD THE ITEM EVEN IF COMBINED WITH OTHER FOODS. PLEASE INCLUDE FOODS CONSUMED OUTSIDE OF YOUR HOME. DID (name) EAT (Name of food) YESTERDAY DURING THE DAY OR THE NIGHT: Yes No DK [A] YOGURT? Yogurt 1 2 8 If yes: HOW MANY TIMES DID (name) DRINK OR EAT YOGURT? If 7 or more times, record '7'. If unknown, record ‘8’. Number of times drank/ate yogurt . __ [B] ANY CERELAC? Cerelac…. 1 2 8 [C] BREAD, RICE, MACARONA, PORRIDGE (ASYDA), OR OTHER FOODS MADE FROM GRAINS? Foods made from grains… 1 2 8 [D] PUMPKIN, CARROTS, SWEET POTATOES? Pumpkin, carrots.… 1 2 8 [E] POTATOES, MANIOC, CASSAVA, OR ANY OTHER FOODS MADE FROM ROOTS? Potatoes, manioc, cassava, etc.…. 1 2 8 [F] ANY GREEN, LEAFY VEGETABLES LIKE SPINACH OR MOLAOKHIYA/ WARAG/ THALIG/ ROCKET? Green, leafy vegetables… 1 2 8 [G] MANGOES, PAPAYAS OR DALEB? Mangoes…… 1 2 8 [H] ANY OTHER FRUITS OR VEGETABLES? Other fruits or vegetables… 1 2 8 [I] LIVER, KIDNEY, HEART, INTESTINES, SPLEEN OR OTHER ORGAN MEATS? Liver, kidney.… 1 2 8 [J] ANY MEAT, SUCH AS BEEF, LAMB, GOAT, CAMEL, PORK CHICKEN, OR DUCK? Meat, such as beef, lamb, goat, etc…. 1 2 8 [K] EGGS? Eggs… 1 2 8 [L] FRESH OR DRIED FISH / KAJEED, SARDEEN/ FASEEKH OR SHELLFISH? Fresh or dried fish…. 1 2 8 [M] ANY FOODS MADE FROM BEANS, LENTILS, CHICKPEAS, FAVA BEANS, LEMA BEANS, ADASEEYA OR LUBYA? Foods made from lentils. 1 2 8 [N] CHEESE OR OTHER FOOD MADE FROM MILK (MULAH ALROOB, MOLAH ALLABAN, MISH? Cheese …… 1 2 8 [O] ANY OTHER SOLID, SEMI-SOLID, OR SOFT FOOD THAT I HAVE NOT MENTIONED? (Specify)_____________________________ Other food…… 1 2 8 BD9. Check BD8 (Categories “A” through “O”). … If you circle “Yes” at least once or all answers where “DK Ö Go to BD11. … Else Ö Continue with BD10. BD10. Probe to determine whether the child ate any solid, semi-solid or soft foods yesterday during the day or night. … The child did not eat or the respondent does not know Ö Go to Next Module. … The child ate at least one solid, semi-solid or soft food item mentioned by the respondent Ö Go back to BD8 and record food eaten yesterday [A to O]. When finished, continue with BD11. BD11. HOW MANY TIMES DID (name) EAT ANY SOLID, SEMI-SOLID OR SOFT FOODS YESTERDAY DURING THE DAY OR NIGHT? If 7 or more times, record '7'. Number of times . __ DK . 8 388 IMMUNIZATION MODULE IM If an immunization (child health) card is available, copy the dates in IM3 for each type of immunization recorded on the card. IM6-IM16A will only be asked if a card is not available. IM1. DO YOU HAVE A CARD WHERE (name)’S VACCINATIONS ARE WRITTEN DOWN? If yes: MAY I SEE IT PLEASE? Yes, seen . 1 Yes, not seen . 2 No card . 3 1ÖIM3 2ÖIM6 IM2. DID YOU EVER HAVE A VACCINATION (child health) CARD FOR (name)? Yes . 1 No . 2 1ÖIM6 2ÖIM6 IM3. (a) Copy dates for each vaccination from the card. (b) Write ‘44’ in day column if card shows that vaccination was given but no date recorded. Date of Immunization Day Month Year BCG BCG POLIO AT BIRTH OPV0 POLIO 1 (FIRST DOSE) OPV1 POLIO 2 (SECOND DOSE) OPV2 POLIO 3 (THIRD DOSE) OPV3 PENTA FIRST DOSE PENTA1 PENTA SECOND DOSE PENTA2 PENTA THIRD DOSE PENTA3 MEASLES FIRST DOSE (OR MMR OR MR) MEASLES 1 MEASLES SECOND DOSE (OR MMR OR MR) MEASLES 2 IM4. Check IM3. Are all vaccines (BCG to Measles) recorded? … Yes Ö Go to IM19A. … No Ö Continue with IM5. IM5. IN ADDITION TO WHAT IS RECORDED ON THIS CARD, DID (name) RECEIVE ANY OTHER VACCINATIONS? … Yes Ö Go back to IM3 and probe for these vaccinations and write ‘66’ in the corresponding day column for each vaccine mentioned. When finished, skip to IM19A. … No/DK Ö Go to IM19. IM6. HAS (name) EVER RECEIVED ANY VACCINATIONS TO PREVENT HIM/HER FROM GETTING DISEASES INCLUDING VACCINATIONS RECEIVED IN A CAMPAIGN OR IMMUNIZATION DAY OR CHILD HEALTH DAY? Yes . 1 No . 2 DK . 8 2ÖIM19A 8ÖIM19A 389 IM7. HAS (name) EVER RECEIVED A BCG VACCINATION AGAINST TUBERCULOSIS – THAT IS, AN INJECTION IN THE ARM? Yes . 1 No . 2 DK . 8 IM8. HAS (name) EVER RECEIVED ANY VACCINATION DROPS IN THE MOUTH TO PROTECT HIM/HER FROM POLIO? Yes . 1 No . 2 DK . 8 2ÖIM11 8ÖIM11 IM9. WAS THE FIRST POLIO VACCINE RECEIVED IN THE FIRST TWO WEEKS AFTER BIRTH? Yes . 1 No . 2 IM10. HOW MANY TIMES WAS THE POLIO VACCINE RECEIVED? Count only those take during routine immunization Number of times . __ IM11. HAS (name) EVER RECEIVED A PENTA VACCINATION – THAT IS, AN INJECTION IN THE LEFT THIGH TO PREVENT HIM/HER FROM GETTING TETANUS, WHOOPING COUGH, DIPHTHERIA, MENINGITIS AND HEPATITIS? Probe by indicating that PENTA vaccination is sometimes given at the same time as Polio. Yes . 1 No . 2 DK . 8 2ÖIM16 8ÖIM16 IM12. HOW MANY TIMES WAS THE PENTA VACCINE RECEIVED? Number of times . __ IM16. HAS (name) EVER RECEIVED A MEASLES INJECTION (OR AN MMR OR MR) – THAT IS, A SHOT IN THE LEFT ARM AT THE AGE OF 9 MONTHS OR OLDER - TO PREVENT HIM/HER FROM GETTING MEASLES? Yes . 1 No . 2 DK . 8 2 19A 8 19 A IM16A. HOW MANY TIMES (name) RECEIVED MEASLES DOSES? Measles doses received . ___ IM19A. PLEASE TELL ME IF (name) HAS PARTICIPATED IN ANY OF THE POLIO CAMPAIGNS, POLIO NATIONAL IMMUNIZATION DAYS AND/ OR POLIO CHILD HEALTH DAYS? Yes . 1 No . 2 DK . 8 IM19B. PLEASE TELL ME IF (NAME) HAS PARTICIPATED IN ANY OF THE MEASLES CAMPAIGNS, MEASLES NATIONAL IMMUNIZATION DAYS AND/ OR MEASLES CHILD HEALTH DAYS? Yes . 1 No . 2 DK . 8 IM20. Check AG2: Age of child. … 6 month or more Ö Continue to IM21. … 0-5 month Ö Go to next module (Care of illness). IM21. DID THE (name) TAKE ANY VITAMIN A LIKE THIS IN THE LAST 6 MONTH? Display the capsules & different containers to the respondent 100,000 unit (blue) for 6-11 month 200,000 unit (red) for 12-59 month Yes . 1 No . 2 DK . 8 2Ö IM24 8Ö IM24 IM22. WHEN DID (name) RECEIVE THE LAST DOES? Less than 6 month . 1 More than 6 month. ………………….….2 DK . …………………………………………8 390 IM23. HOW DID YOU GET THE LAST DOSE? Routine visit to health center . ………….1 Visit to the health center while child is sick. 2 National campaign . 3 Other (specify) _____________________ .6 DK . 8 IM24. DID THE (NAME) SUFFER FROM VISION DIFFICULTY AFTER SUN SET (NIGHT BLINDNESS)? Yes . 1 No . 2 DK . 8 391 CARE OF ILLNESS MODULE CA CA1. IN THE LAST TWO WEEKS, HAS (name) HAD DIARRHOEA? Yes . 1 No . 2 DK. 8 2ÖCA7 8ÖCA7 CA2. I WOULD LIKE TO KNOW HOW MUCH (name) WAS GIVEN TO DRINK DURING THE DIARRHOEA (INCLUDING BREASTMILK). DURING THE TIME (name) HAD DIARRHOEA, WAS HE/SHE GIVEN LESS THAN USUAL TO DRINK, ABOUT THE SAME AMOUNT, OR MORE THAN USUAL? If ‘less’, probe: WAS HE/SHE GIVEN MUCH LESS THAN USUAL TO DRINK, OR SOMEWHAT LESS? Much less . 1 Somewhat less . 2 About the same . 3 More . 4 Nothing to drink . 5 DK. 8 CA3. DURING THE TIME (name) HAD DIARRHOEA, WAS HE/SHE GIVEN LESS THAN USUAL TO EAT, ABOUT THE SAME AMOUNT, MORE THAN USUAL, OR NOTHING TO EAT? If ‘less’, probe: WAS HE/SHE GIVEN MUCH LESS THAN USUAL TO EAT OR SOMEWHAT LESS? Much less . 1 Somewhat less . 2 About the same . 3 More . 4 Stopped food . 5 Never gave food . 6 DK. 8 CA3A. DID YOU SEEK ANY ADVICE OR TREATMENT FOR THE DIARRHOEA FROM ANY SOURCE? Yes . 1 No . 2 DK. 8 2ÖCA4 8ÖCA4 CA3B. FROM WHERE DID YOU SEEK ADVICE OR TREATMENT? Probe: ANYWHERE ELSE? Circle all providers mentioned, but do NOT prompt with any suggestions. Probe to identify each type of source. If unable to determine if public or private sector, write the name of the place. (Name of place) Public sector Government hospital . A Government health centre . B Primary heathcare unit . C Community health worker . D Mobile / Outreach clinic . E Other public (specify) _______________ H Private medical sector Private hospital / clinic . I Private physician . J Private pharmacy . K Mobile clinic . L Other private medical (specify) ________ O Other source Relative / Friend . P Shop . Q Traditional practitioner . R Other (specify) ______________________ X 392 CA4. During the time (name) had diarrhoea, was (name) given to drink: [A] A fluid made from a special packet called amlah mualajat aljafaf for ORS packet solution? [B] A pre-packaged ORS fluid for diarrhoea for pre-packaged ORS fluid? Y N DK Fluid from ORS packet . 1 2 8 Pre-packaged ORS fluid . 1 2 8 CA4A. Check CA4: ORS. … Child was given ORS (‘Yes’ circled in ‘A’ or ‘B’ in CA4) Ö Continue with CA4B. … Child was not given ORS Ö Go to CA4C. CA4B. WHERE DID YOU GET THE ORS? Probe to identify the type of source. If unable to determine whether public or private, write the name of the place. (Name of place) Public sector Government hospital . 11 Government health centre . 12 Government health post . 13 Community health worker . 14 Mobile / Outreach clinic . 15 Other public (specify) ______________ 16 Private medical sector Private hospital / clinic . 21 Private physician . 22 Private pharmacy . 23 Mobile clinic . 24 Other private medical (specify) _______ 26 Other source Relative / Friend . 31 Shop . 32 Traditional practitioner . 33 Already had at home . 40 Other (specify) _____________________ 96 CA4C. DURING THE TIME (name) HAD DIARRHOEA, WAS (name) GIVEN: [A] ZINC TABLETS? [B] ZINC SYRUP? Y N DK Zinc tablets . 1 2 8 Zinc syrup . 1 2 8 CA4D. Check CA4C: Any zinc? … Child given any zinc (‘Yes’ circled in ‘A’ or ‘B’ in CA4C) Ö Continue with CA4E. … Child was not given any zinc Ö Go to CA4F. 393 CA4E. WHERE DID YOU GET THE ZINC? Probe to identify the type of source. If unable to determine whether public or private, write the name of the place. (Name of place) Public sector Government hospital . 11 Government health centre . 12 Government health post . 13 Community health worker . 14 Mobile / Outreach clinic . 15 Other public (specify) ______________ 16 Private medical sector Private hospital / clinic . 21 Private physician . 22 Private pharmacy . 23 Mobile clinic . 24 Other private medical (specify) _______ 26 Other source Relative / Friend . 31 Shop . 32 Traditional practitioner . 33 Present at home……………….………. 40 Other (specify) _____________________ 96 CA4F. DURING THE TIME (name) HAD DIARRHOEA, WAS (name) GIVEN TO DRINK ANY OF THE FOLLOWING: Read each item aloud and record response before proceeding to the next item. [A] Fresh juice (lemon, karkade, gongoliz)? [B] Rice water or starch? [C] Water? Y N DK Fresh juice . 1 2 8 Rice water or starch . 1 2 8 Water . 1 2 8 CA5. WAS ANYTHING (ELSE) GIVEN TO TREAT THE DIARRHOEA? Yes . 1 No . 2 DK. 8 2ÖCA7 8ÖCA7 CA6. WHAT (ELSE) WAS GIVEN TO TREAT THE DIARRHOEA? Probe: ANYTHING ELSE? Record all treatments given. Write brand name(s) of all medicines mentioned. (Name) Pill or Syrup Antibiotic . A Antimotility . B Other pill or syrup (Not antibiotic, antimotility or zinc) . G Unknown pill or syrup . H Injection Antibiotic . L Non-antibiotic . M Unknown injection . N Intravenous . O Home remedy / Herbal medicine . Q Other (specify) ______________________ X 394 CA7. AT ANY TIME IN THE LAST TWO WEEKS, HAS (name) HAD AN ILLNESS WITH A COUGH? Yes . 1 No . 2 DK. 8 2ÖCA14 8ÖCA14 CA8. WHEN (name) HAD AN ILLNESS WITH A COUGH, DID HE/SHE BREATHE FASTER THAN USUAL WITH SHORT, RAPID BREATHS OR HAVE DIFFICULTY BREATHING? Yes . 1 No . 2 DK. 8 CA10. DID YOU SEEK ADVICE OR TREATMENT FOR THE ILLNESS FROM ANY SOURCE? Yes . 1 No . 2 DK. 8 2ÖCA12 8ÖCA12 CA11. FROM WHERE DID YOU SEEK CARE (ADVICE OR TREATMENT? Probe: ANYWHERE ELSE? Circle all providers mentioned, but do NOT prompt with any suggestions. Probe to identify the type of source and circle the appropriate code. If unable to determine if public or private sector, write the name of the place. ____________________________________ (Name of place) Public sector: Govt. hospital .A Govt. health centre .B Govt. health Unit . C Village health worker . D Mobile/outreach clinic .E Other public sector(specify) . H Private medical sector: Private hospital/clinic . I Private physician . J Private pharmacy .K Mobile clinic (private). L Other private sector(specify) . O Other source: Relative or friend . P Shop . Q Traditional healer . R Other (specify . X CA12.AT ANY TIME DURING THE ILLNESS, WAS (name) GIVEN ANY MEDICINE FOR THE ILLNESS? Yes . 1 No . 2 DK. 8 2ÖCA14 8ÖCA14 CA13. WHAT MEDICINE WAS (name) GIVEN? Probe: ANY OTHER MEDICINE? Circle all medicines given. Write brand name(s) of all medicines mentioned. (Names of medicines) Antibiotics: Pill / Syrup . I Injection . J Other medications: Paracetamol/ Panadol /Acetaminophen . P Aspirin . Q Ibuprofen . R Other (specify) ______________________ X DK. Z CA14. Check AG2: Is child under age 3? … Yes Ö Continue with CA15. … No Ö Go to UF13. 395 CA15. THE LAST TIME (name) PASSED STOOLS, WHAT WAS DONE TO DISPOSE OF THE STOOLS? Child used toilet / latrine . 01 Put / Rinsed into toilet or latrine . 02 Put / Rinsed into drain or ditch . 03 Thrown into garbage (solid waste) . 04 Buried . 05 Left in the open . 06 Other (specify) _____________________ 96 DK. 98 UF13. Record the time. Morning . 1 Afternoon . 2 Hour and minutes . __ __ : __ __ UF13A Indicate to the respondent that you will need to measure the weight and height of the child and the haemoglobin test later, ask her if she agree : … Yes … No UF14. Is the respondent the mother or caretaker of another child age 0-4 living in this household? … Yes ÖGo to the next QUESTIONNAIRE FOR CHILDREN UNDER FIVE to be administered to the same respondent. … No Ö End the interview with this respondent by thanking her/him for her/his cooperation . before you leave the household. Check to see if there are other woman’s, or under-5 questionnaires to be administered in this household 396 ANTHROPOMETRY MODULE AN After questionnaires for all children are complete, the measurer weighs and measures each child. Record weight and length/height below, taking care to record the measurements on the correct questionnaire for each child. Check the child’s name and line number in the List of Household Members before recording measurements. AN1. Measurer’s name and number: Name ___ ___ AN2. Result of height / length and weight measurement: Either or both measured . 1 Child not present . 2 Child or mother/caretaker refused . 3 Other (specify) ______________________ 6 2ÖAN6 3ÖAN6 6ÖAN6 AN3. Child’s weight: Kilograms (kg) . __ __ . __ Weight not measured . 99.9 ÖAN3B AN3A. Was the child undressed to the minimum? … Yes…………………………………………………………………….1 … No, the child could not be undressed to the minimum…………….2 AN3B. Check age of child in AG2: … Child under 2 years old Ö Measure length (lying down). … Child age 2 or more years Ö Measure height (standing up). AN4. Child’s length or height: Length / Height (cm) . __ __ __ . __ Length / Height not measured . 999.9 Ö AN4B AN4A. How was the child actually measured? Lying down or standing up? Lying down . 1 Standing up . 2 AN4B. Mid upper arm circumference (MUAC) Circumference (cm) . __ __ . __ Circumference not measured . 99.9 AN5. Check both child legs for oedema and record the result Observe and record Child has odema: Yes . 1 No . 2 Child not present . 3 Refused . 4 AN6. Is there another child in the household who is eligible for measurement? … Yes Ö Record measurements for next child. … No Ö Go to next module. 397 HAEMOGLOBIN TESTING (ANAEMIA) HT After questionnaires for all women and children are complete, the measurer measures the Haemoglobin. HT1. Check AUF14: Permission given? … Yes Ö Continue with HT2. … No Ö Go to HT4. HT2. Result of the HB measurement HB measured .1 Child not present .2 Other (specify) _______________________6 2ÖHT4 6ÖHT4 HT3. HB measurements ___ ___ . ___ HT4. Is there another child in the household who is eligible for the blood test? … Yes Ö Go to the Haemoglobin testing module in the next child questionnaire. … No Ö End the testing procedure. 398 Field Editor’s Observations Supervisor’s Observations Measurer’s Observations 399 Percentage of children attending first grade who attended preschool in previous year1 Number of children attending first grade of primary school Sudan 69.2 2696 Sex Male 65.3 1357 Female 73.1 1339 State Northern 79.9 56 River Nile 86.7 95 Red Sea 65.5 58 Kassala 67.4 81 Gadarif 72.4 150 Khartoum 87.2 333 Gezira 77.4 506 White Nile 82.8 147 Sinnar 72.5 92 Blue Nile 76.6 112 North Kordofan 66.6 181 South Kordofan 60.5 90 West Kordofan 54.1 128 North Darfor 59.6 234 West Darfor 58.3 77 South Darfor 39.0 223 Central Darfor 31.4 49 East Darfor 59.5 82 Area Urban 80.6 805 Rural 64.3 1891 Wealth index quintile Poorest 49.6 503 Second 57.1 505 Middle 70.3 604 Fourth 80.1 586 Richest 87.0 498 Percentage of children attending first grade of primary school who attended pre- school the previous year, Sudan, 2014 Table ED.2: School readiness 1 MICS indicator 7.2 - School readiness Percentage of children of primary school entry age entering grade 1 Number of children of primary school entry age Sudan 38.0 3142 Sex Male 37.3 1560 Female 38.7 1582 State Northern 74.3 54 River Nile 66.5 88 Red Sea 44.7 78 Kassala 28.7 141 Gadarif 35.1 180 Khartoum 69.2 372 Gezira 47.7 456 White Nile 42.2 163 Sinnar 32.8 129 Blue Nile 29.4 141 North Kordofan 38.2 225 South Kordofan 28.8 111 West Kordofan 13.4 180 North Darfor 22.8 263 West Darfor 24.5 122 South Darfor 22.6 272 Central Darfor 24.4 58 East Darfor 20.1 108 Area Urban 57.6 843 Rural 30.8 2299 Wealth index quintile Poorest 15.7 727 Second 21.3 693 Middle 34.3 704 Fourth 58.9 548 Richest 78.4 469 Percentage of children of primary school entry age entering grade 1 (net intake rate), Sudan, 2014 Table ED.3: Primary school entry Not attending school or preschool Attending preschool Out of schoola Not attending school or preschool Attending preschool Out of schoola Not attending school or preschool Attending preschool Out of schoola Sudan 71.3 19.1 9.1 28.2 11522 69.6 21.1 8.9 30.0 11454 70.5 20.1 9.0 29.1 22977 State Northern 93.8 3.2 3.1 6.2 204 93.9 2.8 3.3 6.1 200 93.8 3.0 3.2 6.2 404 River Nile 87.0 6.8 5.9 12.7 321 90.5 6.9 2.3 9.2 344 88.8 6.8 4.1 10.9 665 Red Sea 77.8 13.3 8.5 21.8 263 76.9 14.5 7.9 22.4 249 77.4 13.9 8.2 22.1 512 Kassala 59.5 27.4 12.6 40.0 547 52.8 29.1 17.9 47.0 469 56.4 28.2 15.0 43.3 1016 Gadarif 65.7 21.5 12.8 34.3 621 61.4 27.6 11.1 38.6 600 63.6 24.5 11.9 36.4 1220 Khartoum 89.2 3.2 7.4 10.6 1377 91.2 2.5 6.2 8.6 1411 90.2 2.8 6.8 9.6 2788 Gezira 82.0 11.2 6.4 17.6 1801 80.2 11.4 8.4 19.8 1783 81.1 11.3 7.4 18.7 3585 White Nile 76.5 16.8 5.7 22.5 564 76.2 17.5 6.0 23.4 584 76.3 17.2 5.8 23.0 1148 Sinnar 69.9 15.3 14.8 30.1 408 65.9 17.2 16.8 34.1 409 67.9 16.3 15.8 32.1 816 Blue Nile 51.7 18.9 29.3 48.3 500 52.1 19.4 28.5 47.9 479 51.9 19.2 28.9 48.1 979 North Kordofan 75.2 20.0 4.3 24.3 748 71.6 24.6 2.9 27.4 758 73.4 22.3 3.6 25.9 1506 South Kordofan 66.7 26.7 6.1 32.7 399 64.3 26.3 9.2 35.5 380 65.5 26.5 7.6 34.1 779 West Kordofan 54.0 39.6 5.7 45.3 715 45.7 44.8 8.5 53.2 769 49.7 42.3 7.2 49.4 1483 North Darfor 70.5 19.3 9.7 29.1 989 72.0 19.1 7.9 27.0 959 71.2 19.2 8.8 28.1 1949 West Darfor 57.5 31.1 9.8 40.9 436 52.6 41.0 5.3 46.3 405 55.1 35.9 7.6 43.5 841 South Darfor 59.2 29.7 10.8 40.5 979 60.8 29.8 9.1 38.9 996 60.0 29.7 10.0 39.7 1975 Central Darfor 54.9 36.5 7.1 43.6 219 48.3 43.5 6.4 49.9 230 51.5 40.1 6.7 46.8 449 East Darfor 61.9 28.6 8.4 37.0 431 53.0 39.2 7.0 46.2 428 57.5 33.9 7.7 41.6 859 Area Urban 86.9 6.5 6.2 12.7 3205 88.3 5.6 5.6 11.2 3241 87.6 6.1 5.9 12.0 6446 Rural 65.3 24.0 10.2 34.2 8317 62.2 27.2 10.2 37.4 8213 63.8 25.6 10.2 35.8 16531 Age at beginning of school year 6 38.9 34.5 25.5 60.0 1560 40.8 32.4 26.2 58.6 1582 39.8 33.5 25.8 59.3 3142 7 62.7 24.7 12.1 36.8 1605 62.5 25.5 11.3 36.8 1706 62.6 25.1 11.7 36.8 3311 8 71.3 20.2 7.8 28.0 1637 71.4 20.1 7.9 28.0 1567 71.3 20.2 7.8 28.0 3204 9 81.6 12.5 5.7 18.1 1357 77.2 15.6 6.6 22.1 1284 79.5 14.0 6.1 20.1 2640 10 78.3 16.4 5.0 21.4 1607 78.7 16.8 4.4 21.2 1456 78.5 16.6 4.7 21.3 3063 11 85.3 10.4 4.0 14.5 1127 81.0 14.5 4.4 18.9 1161 83.1 12.5 4.2 16.7 2289 12 80.7 13.6 5.6 19.1 1541 78.2 18.6 3.0 21.6 1509 79.4 16.0 4.3 20.4 3051 13 79.8 16.6 3.5 20.1 1088 74.6 21.7 3.5 25.2 1189 77.1 19.2 3.5 22.8 2277 Wealth index quintile Poorest 54.3 35.9 9.2 45.1 2710 50.4 40.5 8.3 48.8 2644 52.4 38.2 8.7 46.9 5353 Second 59.6 29.2 10.7 39.9 2473 54.5 34.0 11.0 45.0 2469 57.1 31.6 10.9 42.5 4942 Middle 70.5 14.7 14.3 29.1 2462 69.8 15.9 13.8 29.7 2326 70.2 15.3 14.1 29.4 4788 Fourth 88.6 5.8 5.2 11.0 2154 87.9 5.1 6.7 11.8 2197 88.3 5.5 6.0 11.4 4352 Richest 94.5 1.3 4.0 5.3 1724 95.7 1.2 3.1 4.3 1818 95.1 1.2 3.5 4.8 3542 Percentage of children: Net attendance ratio (adjusted) Number of children Percentage of children: Percentage of children: Net attendance ratio (adjusted) Number of children Net attendance ratio (adjusted) Number of children Table ED.4: Primary school attendance and out of school children a The percentage of children of primary school age out of school are those not attending school and those attending preschool Percentage of children of primary school age attending primary or secondary school (adjusted net attendance ratio), percentage attending preschool, and percentage out of school, Sudan, 2014 Male Female Total Attending primary school Out of schoola Attending primary school Out of schoola Attending primary school Out of schoola Sudan 28.2 43.7 27.7 3087 30.3 34.8 34.6 3214 29.3 39.1 31.2 6300 State Northern 36.3 43.4 20.3 77 58.2 30.4 11.5 64 46.3 37.5 16.3 141 River Nile 49.4 31.3 19.2 118 51.6 19.7 28.7 104 50.5 25.9 23.7 222 Red Sea 33.1 46.9 20.0 79 38.1 35.0 25.8 58 35.2 41.9 22.4 137 Kassala 13.7 46.2 39.3 148 17.1 29.8 52.6 127 15.2 38.6 45.5 275 Gadarif 15.7 48.1 36.2 167 18.3 39.2 42.5 154 16.9 43.8 39.3 321 Khartoum 56.3 27.7 16.0 369 59.8 29.4 10.8 422 58.2 28.6 13.2 790 Gezira 39.1 40.9 19.9 464 40.9 19.5 39.2 567 40.1 29.2 30.5 1031 White Nile 25.5 41.7 32.3 172 28.7 35.9 34.3 150 27.0 39.0 33.2 322 Sinnar 18.3 44.3 37.4 102 27.5 37.3 35.3 100 22.8 40.8 36.4 202 Blue Nile 11.1 37.7 50.9 137 14.9 28.1 56.4 137 13.0 32.9 53.7 274 North Kordofan 16.5 43.3 39.8 213 15.1 41.5 42.9 192 15.8 42.5 41.3 405 South Kordofan 14.9 46.2 38.1 73 20.9 34.2 44.9 92 18.2 39.5 41.9 165 West Kordofan 18.0 45.3 35.6 178 13.2 44.2 42.6 197 15.5 44.7 39.3 374 North Darfor 22.3 57.0 19.9 248 23.7 52.1 23.8 285 23.0 54.4 22.0 533 West Darfor 30.2 54.8 14.4 105 18.8 44.4 35.9 114 24.3 49.4 25.6 219 South Darfor 20.4 50.5 27.4 263 17.0 44.6 38.2 273 18.7 47.5 32.9 536 Central Darfor 14.5 54.8 29.7 63 11.4 40.1 46.9 66 12.9 47.3 38.5 130 East Darfor 15.0 52.6 32.4 112 17.6 43.9 38.4 111 16.3 48.3 35.4 224 Area Urban 40.9 43.9 14.9 959 46.4 38.7 14.6 1007 43.7 41.2 14.8 1966 Rural 22.4 43.6 33.5 2128 23.0 33.0 43.7 2207 22.7 38.2 38.7 4334 Age at beginning of school year 14 19.6 58.0 22.3 1094 21.3 48.4 30.0 1499 20.6 52.5 26.7 2593 15 28.9 41.8 28.7 1025 33.5 29.9 36.3 848 30.9 36.4 32.1 1873 16 37.2 29.5 32.8 969 42.8 15.9 40.7 866 39.8 23.1 36.5 1835 Mother's education None 14.9 46.7 38.1 1699 14.6 37.2 48.0 1713 14.7 41.9 43.0 3412 Primary 33.1 49.1 17.2 708 43.2 40.9 15.8 754 38.3 44.9 16.5 1462 Secondary 62.6 29.0 8.1 437 69.7 25.9 3.5 414 66.1 27.5 5.9 851 Higher 77.0 21.7 1.3 72 85.5 14.5 0.0 71 81.2 18.1 0.6 143 Cannot be determinedb 30.5 39.1 29.3 166 19.7 18.7 60.6 253 24.0 26.7 48.2 419 Missing/DK * * * 6 * * * 8 * * * 14 Wealth index quintile Poorest 9.9 49.6 40.1 658 8.9 40.2 50.6 679 9.4 44.8 45.4 1337 Second 17.9 44.2 37.2 674 14.0 39.3 46.4 645 16.0 41.8 41.7 1320 Middle 15.0 52.1 32.3 590 16.0 38.4 45.0 640 15.5 45.0 38.9 1230 Fourth 36.7 43.2 19.9 565 41.8 36.1 21.7 645 39.4 39.4 20.9 1210 Richest 64.7 28.7 6.2 599 74.7 18.6 6.6 604 69.7 23.6 6.4 1204 a The percentage of children of secondary school age out of school are those who are not attending primary, secondary, or higher education Net attendance ratio (adjusted) Number of children Net attendance ratio (adjusted) Number of children (*) Based on less than 25 unweighted cases and has been suppressed Table ED.5: Secondary school attendance and out of school children b Children age 15 or higher at the time of the interview whose mothers were not living in the household Percentage of children of secondary school age attending secondary school or higher (adjusted net attendance ratio), percentage attending primary school, and percentage out of school, Sudan, 2014 Male Female Total Net attendance ratio (adjusted) Number of children Percentage of children: Percentage of children: Percentage of children: Percent attending grade 1 last school year who are in grade 2 this school year Percent attending grade 2 last school year who are attending grade 3 this school year Percent attending grade 3 last school year who are attending grade 4 this school year Percent attending grade 4 last school year who are attending grade 5 this school year Percent attending grade 5 last school year who are attending grade 6 this school year Percent attending grade 6 last school year who are attending grade 7 this school year Percent attending grade 7 last school year who are attending grade 8 this school year Percent who reach grade 6 of those who enter grade 1 Sudan 97.2 98.5 97.6 97.4 97.3 96.1 93.8 79.9 Sex Male 96.6 98.5 98.0 97.7 97.2 95.3 93.8 79.1 Female 97.8 98.4 97.1 97.2 97.4 96.9 93.9 80.6 State Northern 100.0 99.5 97.9 98.6 95.7 95.8 92.4 81.3 River Nile 100.0 98.8 98.4 98.8 99.0 97.1 96.0 88.6 Red Sea 100.0 98.7 99.2 95.9 100.0 98.1 97.9 90.3 Kassala 99.0 98.8 100.0 99.3 100.0 98.4 96.9 92.6 Gadarif 98.4 99.6 98.1 97.0 96.1 98.3 89.2 78.6 Khartoum 100.0 100.0 98.8 98.9 99.4 98.0 99.3 94.5 Gezira 97.1 99.7 98.0 98.6 98.4 94.5 94.5 82.2 White Nile 98.4 98.0 97.6 97.7 97.8 97.4 92.1 80.7 Sinnar 99.1 97.6 97.9 98.3 98.7 97.1 87.1 77.8 Blue Nile 93.9 93.0 92.5 94.5 96.5 89.8 90.6 59.9 North Kordofan 99.0 99.6 98.2 100.0 97.8 93.4 86.8 76.8 South Kordofan 96.7 99.0 100.0 98.1 94.7 93.9 93.5 78.2 West Kordofan 95.9 96.3 93.2 93.5 94.5 97.9 90.4 67.3 North Darfor 98.8 98.4 98.6 96.0 96.5 95.8 91.0 77.4 West Darfor 89.3 95.6 93.4 92.5 91.0 92.4 91.8 56.9 South Darfor 91.7 96.2 95.8 95.5 94.0 95.9 93.9 68.4 Central Darfor 92.0 98.1 94.9 95.2 89.3 96.1 98.5 69.0 East Darfor 96.3 100.0 97.5 97.7 98.7 98.9 97.5 87.3 Area Urban 99.3 99.8 98.9 99.3 99.0 99.1 96.8 92.5 Rural 96.2 97.9 96.9 96.4 96.3 94.4 91.9 73.5 Wealth index quintile Poorest 94.5 98.0 95.9 93.7 94.0 94.1 89.2 65.7 Second 95.9 96.7 96.3 96.9 94.7 96.6 91.6 72.6 Middle 96.7 98.3 97.1 96.8 97.0 94.1 90.3 73.6 Fourth 99.5 99.4 98.8 99.4 99.0 96.0 97.5 90.0 Richest 100.0 100.0 99.8 100.0 99.8 99.5 98.3 97.3 Table ED.6: Children reaching last grade of primary school Percentage of children entering first grade of primary school who eventually reach the last grade of primary school (Survival rate to last grade of primary school), Sudan, 2014 Primary school completion rate Number of children of primary school completion age Transition rate to secondary school Number of children who were in the last grade of primary school the previous year Effective transition rate to secondary school Number of children who were in the last grade of primary school the previous year and are not repeating that grade in the current school year Sudan 82.7 2277 90.9 1203 98.1 1115 Sex Male 88.8 1088 90.6 610 99.7 555 Female 77.1 1189 91.2 592 96.5 560 State Northern 98.1 45 92.6 27 92.6 27 River Nile 95.5 67 96.1 48 97.0 47 Red Sea 104.1 41 95.2 15 99.7 14 Kassala 63.6 104 89.5 27 112.4 22 Gadarif 54.9 129 87.8 57 93.5 54 Khartoum 120.5 285 92.9 171 96.9 164 Gezira 72.2 363 91.2 258 96.9 243 White Nile 94.1 110 96.8 64 106.0 58 Sinnar 60.9 85 90.3 30 105.3 26 Blue Nile 51.8 91 80.7 34 94.5 29 North Kordofan 62.4 160 87.6 49 122.3 35 South Kordofan 82.9 64 87.4 28 92.0 27 West Kordofan 60.9 148 83.2 37 84.0 37 North Darfor 97.7 176 89.1 159 97.0 146 West Darfor 91.7 81 95.0 49 103.9 45 South Darfor 103.2 188 90.1 96 94.3 92 Central Darfor 74.3 47 92.4 18 107.9 16 East Darfor 73.5 91 94.2 35 97.8 34 Area Urban 114.0 677 94.0 455 100.5 426 Rural 69.4 1600 89.0 747 96.6 689 Wealth index quintile Poorest 63.3 510 84.9 173 94.2 155 Second 61.0 489 91.4 205 98.7 190 Middle 81.1 447 87.2 202 96.8 182 Fourth 98.4 452 90.3 301 99.1 275 Richest 119.7 378 96.6 322 99.5 313 Table ED.7: Primary school completion and transition to secondary school Primary school completion rates and transition and effective transition rates to secondary school, Sudan, 2014 Primary school adjusted net attendance ratio (NAR), girls Primary school adjusted net attendance ratio (NAR), boys Gender parity index (GPI) for primary school adjusted NAR Secondary school adjusted net attendance ratio (NAR), girls Secondary school adjusted net attendance ratio (NAR), boys Gender parity index (GPI) for secondary school adjusted NAR Sudan 69.6 71.3 0.98 30.3 28.2 1.08 State Northern 93.9 93.8 1.00 58.2 36.3 1.60 River Nile 90.5 87.0 1.04 51.6 49.4 1.04 Red Sea 76.9 77.8 0.99 38.1 33.1 1.15 Kassala 52.8 59.5 0.89 17.1 13.7 1.25 Gadarif 61.4 65.7 0.93 18.3 15.7 1.17 Khartoum 91.2 89.2 1.02 59.8 56.3 1.06 Gezira 80.2 82.0 0.98 40.9 39.1 1.04 White Nile 76.2 76.5 1.00 28.7 25.5 1.12 Sinnar 65.9 69.9 0.94 27.5 18.3 1.50 Blue Nile 52.1 51.7 1.01 14.9 11.1 1.34 North Kordofan 71.6 75.2 0.95 15.1 16.5 0.92 South Kordofan 64.3 66.7 0.96 20.9 14.9 1.40 West Kordofan 45.7 54.0 0.85 13.2 18.0 0.73 North Darfor 72.0 70.5 1.02 23.7 22.3 1.06 West Darfor 52.6 57.5 0.91 18.8 30.2 0.62 South Darfor 60.8 59.2 1.03 17.0 20.4 0.83 Central Darfor 48.3 54.9 0.88 11.4 14.5 0.78 East Darfor 53.0 61.9 0.86 17.6 15.0 1.18 Area Urban 88.3 86.9 1.02 46.4 40.9 1.13 Rural 62.2 65.3 0.95 23.0 22.4 1.02 Wealth index quintile Poorest 50.4 54.3 0.93 8.9 9.9 0.90 Second 54.5 59.6 0.91 14.0 17.9 0.78 Middle 69.8 70.5 0.99 16.0 15.0 1.07 Fourth 87.9 88.6 0.99 41.8 36.7 1.14 Richest 95.7 94.5 1.01 74.7 64.7 1.15 Table ED.8: Education gender parity Ratio of adjusted net attendance ratios of girls to boys, in primary and secondary school, Sudan, 2014 Primary school Secondary school Percentage of out of school children Number of children of primary school age Percentage of girls in the total out of school population of primary school age Number of children of primary school age out of school Percentage of out of school children Number of children of secondary school age Percentage of girls in the total out of school population of secondary school age Number of children of secondary school age out of school Sudan 29.1 22977 51.3 6684 31.2 6300 56.5 1966 State Northern 6.2 404 49.2 25 16.3 141 32.3 23 River Nile 10.9 665 43.8 73 23.7 222 56.8 53 Red Sea 22.1 512 49.3 113 22.4 137 48.5 31 Kassala 43.3 1016 50.2 440 45.5 275 53.6 125 Gadarif 36.4 1220 52.1 445 39.3 321 51.8 126 Khartoum 9.6 2788 45.5 268 13.2 790 (43.5) 104 Gezira 18.7 3585 52.6 670 30.5 1031 70.6 315 White Nile 23.0 1148 51.9 264 33.2 322 48.1 107 Sinnar 32.1 816 53.1 262 36.4 202 48.1 73 Blue Nile 48.1 979 48.7 471 53.7 274 52.6 147 North Kordofan 25.9 1506 53.3 390 41.3 405 49.2 167 South Kordofan 34.1 779 50.9 266 41.9 165 59.7 69 West Kordofan 49.4 1483 55.8 733 39.3 374 57.0 147 North Darfor 28.1 1949 47.4 547 22.0 533 57.9 117 West Darfor 43.5 841 51.3 366 25.6 219 73.0 56 South Darfor 39.7 1975 49.4 784 32.9 536 59.2 176 Central Darfor 46.8 449 54.6 210 38.5 130 62.3 50 East Darfor 41.6 859 55.4 357 35.4 224 54.1 79 Area Urban 12.0 6446 47.1 771 14.8 1966 50.7 290 Rural 35.8 16531 51.9 5912 38.7 4334 57.5 1676 Wealth index quintile Poorest 46.9 5353 51.4 2512 45.4 1337 56.6 607 Second 42.5 4942 53.0 2099 41.7 1320 54.4 550 Middle 29.4 4788 49.1 1407 38.9 1230 60.2 479 Fourth 11.4 4352 52.3 497 20.9 1210 55.4 253 Richest 4.8 3542 46.0 169 6.4 1204 52.0 77 ( ) Figures that are based on 25-49 unweighted cases Primary school Secondary school Table ED.9: Out of school gender parity Percentage of girls in the total out of school population, in primary and secondary school, Sudan, 2014 Transition (ISCED 1 to 2) Secondary school (ISCED 2+3) Percentage of children of primary school entry age entering grade 11 Net attendance ratio (adjusted)2 Percent who reach grade 6 of those who enter grade 13 Primary school completion rate4 Transition rate to secondary school5 Net attendance ratio (adjusted)6 Sudan 36.8 68.1 88.5 86.9 96.2 30.8 Sex Male 36.1 68.7 88.5 86.5 95.4 30.2 Female 37.5 67.5 88.5 87.4 97.0 31.4 Gender parity index (GPI)7, 8 na 0.98 na na na 1.04 2 MICS indicator 7.4; MDG indicator 2.1 - Primary school net attendance ratio (adjusted) 3 MICS indicator 7.6; MDG indicator 2.2 - Children reaching last grade of primary 4 MICS indicator 7.7 - Primary completion rate 5 MICS indicator 7.8 - Transition rate to secondary school 6 MICS indicator 7.5 - Secondary school net attendance ratio (adjusted) 7 MICS indicator 7.9; MDG indicator 3.1 - Gender parity index (primary school) a ISCED 1 are grades 1-6 , ISCED 2 are grades 7-9 , and ISCED 3 are grades 10-12 . na: not applicable 8 MICS indicator 7.10; MDG indicator 3.1 - Gender parity index (secondary school) Table ED.10: Summary of education indicators (ISCEDa) Summary of education indicators classified according to the International Standard Classification of Education (ISCED), Sudan, 2014 Primary school (ISCED 1) 1 MICS indicator 7.3 - Net intake rate in primary education UNICEF-MICS Sticky Note Correction has been made in column "Secondary school (ISCED 2+3)". Corrected values are: Sudan: 43.8 Male: 44.1 Female: 43.5 Gender parity index: 0.99

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