South Sudan - Multiple Indicator Cluster Survey - 2010

Publication date: 2010

South Sudan Household Health Survey 2010 Final Report August 2013 SOUTH SUDAN Household Survey 2010 MINISTRY OF HEALTH NATIONAL BUREAU OF STATISTICS UNITED NATIONS CHILDREN’S FUND (UNICEF) MONITORING THE SITUATION OF CHILDREN AND WOMEN IN SOUTH SUDAN Publisher: Ministry of Health Design and Layout: Universal Printers Company Limited Cover photo: UNICEF South Sudan / 2011 Kolok Printed by: Afristar International Limited Published in August 2013 The Second South Sudan Household Health Survey (SHHS 2) was carried out in 2010 by the Ministry of Health in collaboration with National Bureau of Statistics. Financial and technical support was provided by the United Nations Children’s Fund (UNICEF) and United Nations Population Fund, World Bank, UNDP, WFP, USAID, WHO, UNAIDS. Sudan Household Health Survey is modelled on MICS, an international household survey programme developed by UNICEF. SHHS 2 was conducted as part of the fourth global round of MICS surveys (MICS4). MICS provides up-to-date information on the situation of children and women and measures key indicators that allow countries to monitor progress towards the Millennium Development Goals (MDGs) and other internationally agreed upon commitments. Additional information on the global MICS project may be obtained from www.childinfo.org. Suggested citation: Ministry of Health and National Bureau of Statistics, 2010. South Sudan Household Survey 2010, Final Report. Juba, South Sudan. South Sudan Household Survey 2010 Acknowledgements The second South Sudan Household Health (SHHS 2) saw success through a gamut of joint efforts by organisations, individual government institutions and staff, and subject matter experts. The team responsible for the supervision and production of this report acknowledges the extraordinary contributions of these institutions and individuals. The Ministry of Health (MoH) and the National Bureau of Statistics (NBS) played a significant role with respect to the administrative and technical aspects of the survey. In particular, we acknowledge the administrative and institutional contributions of All director Generals Ministry of Health and Hon. Isaiah Chol Aruai, Chairman of the National Bureau of Statistics, whose leadership was instrumental in setting the direction of the study. Many staff of the Ministry of Health and the National Bureau of Statistics were instrumental in this survey, therefore are greatly appreciated. The South Sudan AIDS Commission (SSAC) was critical in the planning processes of the survey and is highly acknowledged. We acknowledge the combination of all international agencies, including the United Nations (UN), the bilateral donors, the NGOs and other development partners whose financial and technical assistance to the health sector immensely contributed to effective planning, implementation, and publication of the results of this survey. In particular, this survey would have not been possible without the profound contributions of the United Nations Children’s Fund (UNICEF), the World Food Programme (WFP), the United Nations Fund for Population Activities (UNFPA), the World Bank, the United States Agency for International Development (USAID), and the World Health Organisation (WHO), UNAIDS. We are indebted to the Multiple Indicator Cluster Survey (MICS) support desks, both at UNICEF Headquarter offices, ESARO and MENA Regions, for providing technical assistance on methodology, especially with respect to data analysis. Our sincere appreciation equally goes to our colleagues in the then Sudan’s Government of National Unity (GoNU) for their collaboration during the survey planning and implementation processes. Sincere appreciation is also due to the State Ministries of Health and Sub-Offices of the National Bureau of Statistics for assisting in the data collection phase of the survey. Finally, we are grateful to the individuals in selected sample units for participating in this important study and allowing us access to their households. This study would have not been a success without their consent and participation. Eliaba Yona Damundu Director Social and Demographic Statistics Dept. National Bureau of Statistics Dr. Makur Matur Kariom Undersecretary Ministry of Health Foreword The South Sudan Household Health Survey (SHHS 2) marks the second household and health study in post-conflict South Sudan. This exercise was timely, given its relevance to changes in Sudanese geopolitics, which have considerable implications for children and women’s health in the nascent polity. The emphasis of the study is to assess the state of health for children and women and some other important aspects of their wellbeing following the first survey, and to streamline childhood and maternal health services in South Sudan. The study also assesses the state of other facets related to children and women’s livelihood. This study establishes evidence- based insights concerned with childhood and maternal health experience in South Sudan, the results of which could be used to develop key strategies for health policy in the area. Covering the ten states South Sudan, the SHHS 2 provides comparative analyses of childhood and maternal health and other aspects of children’s welfare across spaces and according to individual and residence specific indicators. The success of this project depended primarily on the extraordinary contributions made by various developmental partners and the then Government of Southern Sudan. The joint efforts enabled efficient and effective planning processes for generating and analysing data. As well, the efforts are crucial in mobilising resources that assist in poverty reduction and equitable distribution of social services in South Sudan. The present data are useful for objectively informing strategies towards attaining the Millennium Development Goals (MDGs) in South Sudan. The principal importance of the data lies in devising solutions geared towards restructuring the health infrastructure, services, and institutional structures in order to ensure effective service delivery practices in the polity. The SHHS 2 helps illuminate upon current health and other social conditions of children and women in South Sudan, making reference to prior status as provided in the first study with exlusion of MMR which will be done seperately The Survey is a periodical study meant to continuously generate health and other key aspects of social and health history for the population of South Sudan. It is therefore our sincere hope that this report will enable the relevant institutions and their partners to make objectively informed decisions in policy formulation concerned with the provision of services, while promoting consistency in preventive and curative health programs. Hon. Dr. Michael Milli Hussein Minister Minister of Health Hon. Mr. Isaiah Chol Aruai Chairman National Bureau of Statistics (NBS) Message from UNICEF’s Country Office I congratulate the Ministry of Health and the National Bureau of Statistics on the successful completion of the second round of the South Sudan Household Health Survey. This report is extremely opportune as it comes only five months after the birth of this new nation: The Republic of South Sudan. This is the first report ever produced on the situation of children and women in the independent country. The report provides updated data at the national and sub-national level on health as well as social status of children and women in the new state. The data in the survey reveal the alarmingly poor status of children and women in the country and also highlights geographic and social inequities within the country. It is well established that the wellbeing of children and women form the cornerstone of the Millennium Development Goals (MDGs). Promoting the rights of children to better life, survival and development is a prerequisite for making tangible and significant progress in attainment of the relevant MDGs. This report forms the primary basis for effective and relevant planning and policy development for promoting the welfare of children and women, in the process simultaneously accelerating progress towards the MDGs. Further, it lays a strong baseline for tracking obligations as laid out in the South Sudan Child Act of 2008. Our vision at UNICEF for this report goes beyond being a useful reference document for policy makers and administrators only. We strongly encourage academics, researchers, development partners and the civil society to use information contained therein for evidence-based planning, decision-making and reporting on children and women’s issues in South Sudan. This report and the survey that generated this critical information are proof of the rewards of cooperation between the government of the Republic of South Sudan and partnership with Swedish International Development Agency (SIDA) USAID and sister UN agencies, namely United Nations Population Fund (UNFPA), World Health Organisation (WHO) and World Food Programme (WFP). UNICEF stands committed to further strengthen this cooperation and partnerships with relevant institutions of the Republic of South Sudan, civil society, the UN community and international agencies to improve child survival and development in South Sudan within the framework of equitable development and the progressive realisation of the rights of children. Dr. Yasmin Ali Haque UNICEF Representative Republic of South Sudan Table of Contents Table of Contents . i List of Tables . iii List of Figures . vi List of Abbreviations . vii Summary Table of findings . viii Executive Summary . xi I. Introduction . 1 Background. 1 Survey Objectives . 2 II. Sample and Survey Methodology . 3 Sample Design . 3 Questionnaires . 3 Training and Fieldwork . 5 Data Processing . 5 III. Sample Coverage and the Characteristics of Households and Respondents . 6 Sample Coverage . 6 Characteristics of Households . 6 Characteristics of Female Respondents 15-49 Years of Age and Children Under-5 . 12 IV. Child Mortality . 17 V. Nutrition Nutritional Status . 26 Breastfeeding and Infant and Young Child Feeding . 29 Salt Iodization . 41 Children’s Vitamin A Supplementation . 43 Low Birth Weight . 44 VI. Child Health . 45 Vaccinations . 45 Neonatal Tetanus Protection . 49 Oral Rehydration Treatment . 51 Care Seeking and Antibiotic Treatment of Pneumonia . 59 Solid Fuel Use . 61 Malaria . 64 VII. Water and Sanitation . 71 Use of Improved Water Sources . 71 Use of Improved Sanitation Facilities . 84 VIII. Reproductive Health . 94 Fertility . 94 Contraception . 97 Unmet Need . 100 i Antenatal Care . 103 Assistance at Delivery . 108 Place of Delivery . 111 IX. Literacy and Education . 113 Literacy among Young Women . 113 School Readiness . 113 Primary and Secondary School Participation . 116 X. Child Protection . 126 Birth Registration . 126 Early Marriage and Polygyny . 128 Attitudes toward Domestic Violence . 133 XI. HIV/AIDS, Sexual Behaviour, and Orphans . 135 Knowledge about HIV Transmission and Misconceptions about HIV/AIDS . 143 Accepting Attitudes toward People Living with HIV/AIDS . 144 Knowledge of a Place for HIV Testing, Counselling and Testing during Antenatal Care . 148 Sexual Behaviour Related to HIV Transmission . 153 Orphans . 160 Appendix A. Sample Design . 164 Appendix B. Estimates of Sampling Errors . 168 Appendix C. Data Quality Tables . 197 Appendix D. MICS4 Indicators: Numerators and Denominators . 211 Appendix E. Questionnaires . 219 ii List of Tables Table HH.1: Results of household, women’s, men’s and under-5 interviews . 7 Table HH.2: Household age distribution by sex . 8 Table HH.3a: Household composition. 11 Table HH.3b: Household composition . 12 Table HH.4: Women’s background characteristics . 14 Table HH.5: Under-5’s background characteristics . 16 Table CM.1: Early childhood mortality rates . 19 Table CM.2: Early childhood mortality rates by socioeconomic characteristics . 21 Table CM.3: Early childhood mortality rates by demographic characteristics . 24 Table NU.1: Nutritional status of children . 28 Table NU.2: Initial breastfeeding . 31 Table NU.3: Breastfeeding . 33 Table NU.4: Duration of breastfeeding . 34 Table NU.5: Age-appropriate breastfeeding . 36 Table NU.6: Introduction of solid, semi-solid or soft foods . 37 Table NU.7: Minimum meal frequency . 39 Table NU.8: Bottle feeding . 40 Table NU.9: Iodized salt consumption . 42 Table NU.10: Children’s vitamin A supplementation . 44 Table CH.1: Vaccinations in first year of life . 45 Table CH.2: Vaccinations by background characteristics . 48 Table CH.3: Neonatal tetanus protection . 50 Table CH.4: Oral rehydration solutions and recommended homemade fluids . 53 Table CH.5: Feeding practices during diarrhoea . 55 Table CH.6: Oral rehydration therapy with continued feeding and other treatments . 57 Table CH.7: Care seeking for suspected pneumonia and antibiotic use during suspected pneumonia . 60 Table CH.8: Solid fuel use . 62 Table CH.9: Solid fuel use by place of cooking . 63 Table CH.10: Household availability of insecticide treated nets . 66 Table CH.11: Anti-malarial treatment of children with anti-malarial drugs . 67 Table CH.12: Malaria diagnostics usage . 69 Table CH.13: Intermittent preventive treatment for malaria . 70 Table WS.1A: Use of improved water sources (country specific table) . 70 Table WS.1B: Use of improved water sources . 75 Table WS.2A: Household water treatment (country specific table) . 77 Table WS.2B: Household water treatment . 78 Table WS.3A: Time to source of drinking water (country specific table) . 80 Table WS.3B: Time to source of drinking water . 81 Table WS.4: Person collecting water . 83 Table WS.5: Types of sanitation facilities . 85 Table WS.6: Use and sharing of sanitation facilities . 87 Table WS.7: Disposal of child’s faeces . 89 Table WS.8: Drinking water and sanitation ladders (country specific table) . 91 Table WS.8A: Drinking water and sanitation ladders (country specific table) . 93 iii Table RH.1: Adolescent birth rate and total fertility rate . 95 Table RH.2: Early childbearing . 96 Table RH.3: Trends in early childbearing. 97 Table RH.4: Use of contraception . 98 Table RH.5: Unmet need for contraception . 102 Table RH.6: Antenatal care coverage . 104 Table RH.7: Number of antenatal care visits . 106 Table RH.8: Content of antenatal care . 107 Table RH.9: Assistance during delivery . 109 Table RH.10: Place of delivery . 112 Table ED.1: Literacy among young women . 114 Table ED.2: School readiness . 115 Table ED.3: Primary school entry . 117 Table ED.4: Primary school attendance . 119 Table ED.5: Secondary school attendance . 120 Table ED.6: Children reaching last grade of primary school . 122 Table ED.7: Primary school completion and transition to secondary school . 123 Table ED.8: Education gender parity . 125 Table CP.1: Birth registration . 127 Table CP.2: Early marriage and polygyny . 130 Table CP.3: Trends in early marriage . 131 Table CP.4: Attitudes toward domestic violence . 134 Table HA.1: Knowledge about HIV transmission, misconceptions about HIV/AIDS, and comprehensive knowledge about HIV transmission . 137 Table HA.2: Knowledge about HIV transmission, misconceptions about HIV/AIDS, and comprehensive knowledge about HIV transmission among young women . 141 Table HA.3: Knowledge of mother-to-child HIV transmission . 145 Table HA.4: Accepting attitudes toward people living with HIV/AIDS. 146 Table HA.5: Knowledge of a place for HIV testing . 149 Table HA.6: Knowledge of a place for HIV testing among sexually active young women . 150 Table HA.7: HIV counselling and testing during antenatal care . 152 Table HA.8: Sexual behaviour that increases the risk of HIV infection . 154 Table HA.9: Sex with multiple partners . 156 Table HA.10: Sex with multiple partners among young women . 157 Table HA.11: Sex with non-regular partners . 159 Table HA.12: Children's living arrangements and orphanhood . 161 Table HA.13: School attendance of orphans and non-orphans . 162 Table SE.1: Indicators selected for sampling error calculations . 169 Table SE.2: Sampling errors: (Total sample) . 171 Table SE.3: Sampling errors: Urban areas . 173 Table SE.4: Sampling errors: Rural areas . 175 Table SE.5: Sampling errors: Upper Nile . 177 Table SE.6: Sampling errors: Jonglei . 179 Table SE.7: Sampling errors: Unity . 181 Table SE.8: Sampling errors: Warap . 183 Table SE.9: Sampling errors: Northern Bahr EL Ghazal . 185 iv Table SE.10: Sampling errors: Western Bahr EL Ghazal . 187 Table SE.11: Sampling errors: Lakes . 189 Table SE.12: Sampling errors: Western Equatoria . 191 Table SE.13: Sampling errors: Central Equatoria . 193 Table SE.14: Sampling errors: Eastern Equatoria . 195 Table DQ.1: Age distribution of household population . 198 Table DQ.2: Age distribution of eligible and interviewed women . 199 Table DQ.3: Age distribution of under-5s in household and under-5 questionnaires . 199 Table DQ.4: Women's completion rates by socio-economic characteristics of households . 200 Table DQ.5: Completion rates for under-5 questionnaires by socio-economic characteristics of . households . 201 Table DQ.6: Completeness of reporting . 202 Table DQ.7: Completeness of information for anthropometric indicators . 203 Table DQ.8: Heaping in anthropometric measurements . 204 Table DQ.9: Observation of women’s health card . 204 Table DQ.10: Observation of under-5s birth certificates . 205 Table DQ.11: Presence of mother in the household and the person interviewed for the under-5 questionnaire . 205 Table DQ.12: School attendance by single age . 206 Table DQ.13: Sex ratio at birth among children ever born and living . 206 Table DQ.14: Births by calendar years . 208 Table DQ.15: Reporting of age at death in days . 209 Table DQ.16: Reporting of age at death in months . 210 v List of Figures Figure HH.1: Age and sex distribution of household population . 9 Figure CM.1: Trend in early childhood mortality rates . 19 Figure CM.2: Early childhood mortality rates by background characteristics . 21 Figure CM.3: Early childhood mortality rates by demographic background characteristics . 22 Figure NU.1: Percentage of children under age 5 who are underweight, stunted and wasted . 29 Figure NU.2: Percentage of households consuming adequately iodized salt . 42 Figure CH.1: Percentage of children aged 12-23 months who received the recommended vaccinations by 12 months . 47 Figure CH.2: Percentage of women with a live birth in the last 12 months who are protected against neonatal tetanus . 51 Figure CH.3: Percentage of children under age 5 with diarrhoea who received oral rehydration treatment . 54 Figure CH.4: Percentage of children under age 5 with diarrhoea who received ORT or increased fluids, AND continued feeding . 58 Figure WS.1: Percent distribution of household members by source of drinking water . 76 Figure CP.1: Percentage of birth registration . 128 Figure CP.2: Percentage of women who were first married/union before age 15 by age- groups and residence . 132 Figure CP.3: Percentage of women who were first married/union before age 18 by age- groups and residence . 132 Figure HA.1: Percentage of young women who have comprehensive knowledge of HIV/AIDS transmission . 143 Figure HA.2: Sexual behaviour that increases risk of HIV infection . 155 vi List of Abbreviations AIDS Acquired Immune Deficiency Syndrome BCG Bacillis-Cereus-Geuerin (Tuberculosis) CSPro Census and Survey Processing System DPT Diphteria Pertussis Tetanus EPI Expanded Programme on Immunization FGM/C Female genital mutilation/cutting GPI Gender Parity Index HIV Human Immunodeficiency Virus IDD Iodine Deficiency Disorders ITN Insecticide Treated Net IUD Intrauterine Device LAM Lactational Amenorrhea Method MDG Millennium Development Goals MICS Multiple Indicator Cluster Survey MICS4 Fourth global round of Multiple Indicator Clusters Surveys programme MoH Ministry of Health NAR Net Attendance Rate ORT Oral rehydration treatment ppm Parts Per Million SPSS Statistical Package for Social Sciences 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 USAID United States Agency for Development UNICEF United Nations Children’s Fund WFFC World Fit For Children WHO World Health Organization WFP World Food Programme vii Summary Table of Findings Multiple Indicator Cluster Surveys (MICS) and Millennium Development Goals (MDG) Indicators, South Sudan, 2010 viii ix x Executive Summary The South Sudan Household Health Survey (SHHS 2), the second round of its kind, is a nationally representative sample survey of households, women and men aged 15-49 years and children aged 0-5 years. The survey studies the general well-being of women and children in South Sudan. It aims to collect health and related indicators essential to identifying women, men and children’s health needs and for establishing priorities for evidence-based planning, decision- making and reporting. The sample design, based on MICS4 (Multiple Indicator Cluster Survey 4) methodology, provides robust estimates of the selected health and social development indicators required for effective planning and management purposes. The South Sudan Household Health Survey (SHHS 2) was carried out in 2010 by the National Bureau of Statistics, and Ministry of Health with Financial & Technical Support from UNICEF and the Ministry of Health. The results presented in this report pertain to last week of March to the end of June 2010, when the field work was conducted. Household Characteristics Of the 9,950 households selected for the sample, 9,760 were contacted for interviews. Of these, 9,369 were interviewed, giving a response rate of 96 percent. In the households interviewed, 11,568 women aged 15–49 years were identified. Of these, 9,069 were duly interviewed, producing a response rate of 78 per cent. Concerning children under the age of 5 years, 10,040 were identified, for whom responses were obtained from their mothers or caregiver in 8,338 complete interviews, giving a response rate of 83 percent. For the male survey, 8,656 men aged 15-49 years were identified, and 4,345 successfully interviewed, yielding a response rate of 50 percent. However, given this very low response rate, the men’s results were dismissed from this SSHS2 report analysis. Overall, the survey found that 42 percent of households in South Sudan are headed by women. Children less than 15 years constitute 53 percent of the total population. Furthermore, 23 percent of households are in urban areas compared to 77 percent in rural areas. The most common household size is 5-6 household members (33 percent), followed by 3-4 and 7-8 household members with 22 percent each. Characteristics of Female Respondents The SHHS 2 data show that for women, the largest population age-group is 20-29 years with 40 percent in this category. In addition, 81 percent of women are currently married/in union, while 11 percent have never been married/in union. Jonglei, Warap and Central Equatoria have the highest proportion of women, with 14 percent each. The lowest proportion of women is in Western Bahr El Ghazal (4 percent). In South Sudan, 81 percent of women have given birth at least once, and 38 percent gave birth in the last two years. About 74 percent women live in rural areas; while for children, about 76 percent live in rural areas compared to 24 percent in urban areas. With respect to educational level, 79 percent of women have no education; 17 percent of women have primary education; and only 4 percent of women have secondary or higher levels of education. xi For children under five, South Sudan has roughly the same proportion of girls (49 percent) and boys (51 percent) but there are more children in rural areas (76 percent) than in urban areas (24 percent). Eighty-four percent of the children have mothers with no formal education, while 13 percent have mothers/care takers with primary education and only 3 percent have mothers/ caretakers with secondary and higher education. The highest proportions of children are in Jonglei (15 percent) and Warap (14 percent), while the lowest proportion is found in Western Bahr El Ghazal (4 percent). The age distribution in months of the children under-five years is also provided. Children are somehow evenly distributed across age-groups (months), except for the last age-group of 48-59 months with only 14 percent. Child Mortality The second South Sudan Household Survey (SHHS 2) was conducted from the last week of March and concluded by the end of June 2010 and early childhood mortality rates were estimated using the direct method. The reference point (mid-point interval) for the childhood mortality for the most recent five year period is the last week of September 2007. The results estimate South Sudan under-five mortality rate at 108 deaths per 1,000 live births. The child mortality rate is estimated at 32 deaths per 1,000 children aged 1 year, while the infant mortality rate is estimated at 79 deaths per 1,000 live births. Post neonatal and neonatal mortality rates are estimated at 36 and 43 deaths per 1000 live births, respectively, for the same period. Neonatal mortality rate represents 55 percent of the infant mortality rate in South Sudan, meaning that 55 percent of deaths in infancy occur during the first 28 days of a child’s life. Significant variations are also noted across the states. The highest infant mortality rates are in Northern Bahr El Ghazal (120 deaths per 1,000 live births), Central Equatoria (115 deaths per 1,000 live births) and Eastern Equatoria (106 deaths per 1,000 live births), while the lowest are in Jonglei and Unity with 31 deaths per 1,000 live births each. The highest proportions of under- five morality rates are in Northern Bahr El Ghazal (157 deaths per 1,000 live births) and Central Equatoria (152 deaths per 1,000 live births), and the lowest proportions are found in Jonglei (48 deaths per 1,000 live births) and Unity (51 deaths per 1,000 live births). An unexpected pattern is observed across residence and wealth index quintiles. Children living in urban areas experience higher levels of infant and under-five mortality rates (90 and 118 deaths per 1,000 live births respectively), compared to those living in rural areas (75 and 105 deaths per 1000 live births respectively). The infant mortality rate is estimated at 90 deaths per 1000 live births for children from the richest wealth quintile, and 71 deaths per 1000 live births for children in the middle wealth quintile; and the under-5 mortality rate is estimated at 117 deaths per 1,000 live births for children from the richest households, compared to 99 deaths per 1,000 live births for children belonging to the middle households. Nutritional Status Almost one in 4 children (28 percent) under the age of five years is moderately or severely underweight and 12 percent are classified as severely underweight. The results also reveal that nearly 1 in every 3 children (31 percent) is moderately or severely stunted, and 17 percent are xii severely stunted. Sixteen percent of the children are moderately or severely wasted, and 6 percent can be considered severely wasted. There are no significant variations across the gender and residence for all three indicators. However at state level, differentials are noticed. The highest rates for underweight (46 percent), stunting (40 percent) and wasting (35 percent) are found in Unity; while the lowest rates for underweight are recorded in Central Equatoria (17 percent), for the stunting in Upper Nile and Western Bahr El Ghazal (27 percent each) and in Central Equatoria for wasting (11 percent). For all three indicators, the rates decrease with mother’s/caretaker educational level and wealth index quintiles. Breastfeeding and Infant and Young Child Feeding Approximately 45 percent of children aged 0-5 months are exclusively breastfed, a level considerably lower than recommended. The mean duration for any breastfeeding is 17 months, 4 month for exclusively breastfeeding and 8 months for predominant breastfeeding. In addition, 21 percent of children aged 6-8 months are currently breastfed and receiving solid, semi-solid or soft foods, and 30 percent of children aged 0-23 months are appropriately breastfed. SHHS2 data also show that, for children aged 6-23 months currently breastfeeding, 11 percent are receiving solid, semi-solid and soft foods the recommended minimum number of times. For children aged 6-23 months not currently breastfeeding, 14 percent are receiving solid, semi-solid and soft foods or milk feeds 4 times or more. And for all children aged 6-23 months, 12 percent receive minimum meal frequency. About 6 percent of children aged 0-23 months and 7 percent of children aged 6-11 months are fed using a bottle with a nipple. Results also show that the most likely children to be bottle-fed are those from Jonglei and Central Equatoria (8 percent each), those living in urban areas (9 percent), those whose mothers have primary (9 percent) or secondary education (10 percent) and those from the wealthiest households (10 percent). Salt Iodization Salt used for household cooking was tested in the SHHS 2 through the use of Rapid Salt Kits. In about 78 percent of households, salt used for cooking was tested for iodine content by using salt test kits and testing for the presence of potassium iodide or potassium iodate content or both. In 45 percent of households where the test was carried out, salt was found to contain 15 parts per million (ppm) or more of iodine. Use of adequately iodized salt was lowest in Northern Bahr El Ghazal (13 percent), Unity (14 percent) and Upper Nile (15 percent); and highest in Central Equatoria (83 percent) and Western Equatoria (81 percent).More than one in two (57 percent) of urban households were found to be using adequately iodized salt, compared to 42 percent in rural areas. Also, 61 percent of richest households use iodized salt compared to 37 percent in the poorest and 38 percent in second households. Vitamin A Supplement Within the six months prior to SHHS2, 4 percent of children aged 6-59 months received a high dose Vitamin A supplement. Vitamin A supplementation coverage is lower in Warap, Jonglei xiii and Unity than in other States. Overall, percentages for most of the States are below 5 percent, except for Jonglei (8 percent) and Western Bahr El Ghazal (6 percent). Urban areas record 6 percent compared to 3 percent in rural areas). In addition, the Vitamin A supplementation increases with mother’s educational level and household wealth index. The highest proportion (16 percent) of Vitamin A supplementation was found in age-group 12-23 months. Immunization According to UNICEF and WHO guidelines, a child should receive a BCG vaccination to protect against tuberculosis, three doses of DPT to protect against diphtheria, pertussis, and tetanus, three doses of polio vaccine, and a measles vaccination by the age of 12 months. In South Sudan, the SSHH2 results show that 6 percent of children aged 12-23 months are fully immunized before their first birthday; and the coverage rate for all vaccination for children aged 12-23 months is also 6 percent, while 56 percent of children have not received any vaccinations. Approximately 31 percent of children aged 12-23 months received a BCG vaccination by their first birthday, 20 percent were immunized against measles by their first birthday, and 13 percent received 3 doses of DPT/HepB/INFL. Also, 13 percent of children aged 12-23 months had received 3 doses of polio. Tetanus toxoid Thirty-seven percent of women who gave birth in the last two years are protected against tetanus. Nearly 1 in four (28 percent) of them are protected because they received at least two doses of tetanus toxoid injection during their most recent pregnancy, while 9 per cent of women are protected because they received at least two doses of the vaccine in the last three years. More women in urban areas received the 2 doses during their last pregnancy (51 percent), compared to their rural counterparts (32 percent). The Central Equatoria has the highest percentage of women who received at least 2 doses of tetanus vaccination during their last pregnancy (71 percent), while Warap state the lowest with 17 percent. Also the proportion of protection against tetanus increases with mother’s educational level and wealth index. Oral rehydration treatment Thirty percent of children under-five had diarrhoea in the two weeks prior to the survey. Around 2 in 5 third (39 percent) of children with diarrhoea were treated with ORS (fluid made with an ORS packet or pre-packaged ORS fluids), and 25 percent received recommended home-prepared fluids. Less than half (49 percent) of children with diarrhea in the two weeks prior to the survey received oral rehydration treatment (ORT), meaning that they received either ORS, or the recommended home-prepared liquids, or increase of fluids. The rate of use of ORT is higher in Central Equatoria state (73 percent) compared to Lakes (33 percent) Warap (35 percent). The SHHS 2 data also show that 23 percent of children received ORT and, at the same time, feeding was continued, as recommended. Care-seeking and antibiotic treatment of pneumonia About 1 in 5 (19 percent) of children aged 0–59 months were reported as presenting symptoms suggestive of pneumonia in the two weeks prior to the survey. Of the children with suspected pneumonia, less than half (48 percent) were taken to an appropriate health provider. In addition, 33 percent of children with suspected pneumonia received antibiotics. xiv Malaria More than half (52 percent) of all households own at least one mosquito net and 34 percent of all households have at least one long-lasting insecticidal net (LLIN). The availability of LLIN is slightly lower in rural areas (31 percent) than in urban areas (44 percent). Western Equatoria state has the highest (58 percent) LLIN coverage, while the lowest coverage rates are found in Warap (17 percent), Unity (20 percent) and Upper Nile (22 percent). This proportion is higher in urban areas (44 percent) than in rural areas (31 percent). Nearly 31 percent of households with an uneducated heads have at least one LLIN, compared to 45 percent for households where the heads have secondary education or higher. The proportion of poorest households with at least one LLIN is lower (27 percent) than that of households from the richest households, standing at 45 percent The SHHS 2 data also reveal that nearly 1 in 3 children under-five (32 percent) had fever in the two weeks preceding the survey, and 51 percent of them took antimalarial drugs; just over 1 in 4 of them (27) took the antimalarial drugs the same or next day. The malaria diagnostics usage is at 28 percent. Water and Sanitation Nearly 69 percent of household members in South Sudan are using improved sources of drinking water, which means that South Sudan still has to make progress in order to achieve the 2015 MDG 7 target of 78 percent of the population using improved drinking water. However, wide variations exist across states with the highest proportion in Lakes (92 percent) compared to 52 Western Bahr El Ghazal. There seems not be significant variations across residence, education and wealth index. The great majority of households (89 percent) do not use any method for treating water. Regarding households with unimproved sources of water, 9 percent of them treat their water using appropriate water treatment method before they drink it. Concerning access to water for those households without water on the premises, for about 33 percent of all households that use an improved drinking water source, it takes less than 30 minutes for the round trip to fetch water, while 34 percent of households spend 30 minutes or more. Ninety-eight percent of households do not have drinking water on premises or delivered by tankers/carts. And in the majority of households (86 percent), the person who fetches water is an adult woman. Adult men collect water in only 5 percent of cases, while for the rest of the households, female or male children under age 15 collect water (9 and 1 percent respectively). The MDGs and the WHO / UNICEF Joint Monitoring Programme (JMP) for Water Supply and Sanitation classify households as using an unimproved sanitation facility if they are using otherwise acceptable sanitation facilities but sharing a facility between two or more households or using a public toilet facility. Taking into account this definition, only 7 percent of household members were using an improved and not shared sanitation facility. The highest proportions are in Western Equatoria (23 percent) and Central Equatoria (13 percent), while the lowest are in Warap (1 percent) and Northern Bahr El Ghazal (2 percent). xv About 64 percent of households in South Sudan practice open defecation or have no toilet facility, and this was more pronounced in rural areas (70 percent) than urban areas (46 percent). And except Western Equatoria (15 percent) and Central Equatoria (49 percent), the proportions of open defecation are above 60 percent in all remaining 8 states. The proportion of access to both improved drinking water sources and improved sanitation is 6 percent in South Sudan. Fertility The adolescent birth rate and total fertility rate (TFR) are respectively 158 live births per 1,000 women and 7.5 children per woman. The average TFR is 7.4 children per woman in the urban areas and 7.5 per woman in the rural areas. At state level, the Upper Nile, Northern Bahr El Ghazal and Western Bahr El Ghazal states have the highest TFR with 8.1children per woman each and they are followed by Unity state with 7.8 children per woman. And as can be expected, the lowest TFR is observed among women with secondary or higher education (5.3 children per woman) and in the richest quintile (6.9 children per woman). Twenty-six percent of women aged 15-19 years had already given birth, 5 percent were pregnant with their first child and therefore, in total, 31 percent had begun childbearing. Furthermore, 3 percent have had a live birth before the age 15 and about 28 percent of women aged 20-24 years have had a live birth before age 18. Contraception use and unmet need Only 4 percent women currently married or in union reported using any method of contraception: 1 percent of all women use modern methods and 3 percent use traditional methods. There is a slight difference in contraceptive use depending on residence, with 5 percent of users in urban areas against 4 percent in rural areas. The unmet need for contraception refers to fecund women who are not using any method of contraception, but who wish to postpone the next birth (spacing) or who wish to stop childbearing altogether (limiting). Overall, 26 percent of women aged 15-49 years have an unmet need for contraception. Nineteen percent have an unmet need for spacing and 7 percent have an unmet need for limiting. Antenatal care Forty percent of women aged 15-49 years who gave birth in the 2 years preceding the survey received at least one antenatal care (ANC) visit by skilled health personnel and 17 percent had 4 or more antenatal care visits. Central Equatoria state recorded the highest proportions of pregnant women who attended 4 or more antenatal care visits with 35 percent. The Warap state recorded the lowest proportion of pregnant women that had at least 4 antenatal care visits (6 percent). During their antenatal care, 13 percent of the women had blood pressure measured, a urine specimen taken and a blood test. xvi Assistance at delivery Around 19 percent of women aged 15-49 years who gave birth in the last two years were assisted by skilled personnel during the delivery. This percentage is highest in the State of Central Equatoria at 39 percent and lowest in Warap state at 9 percent. The data also show that 12 percent of women delivered in health facilities, and nearly 1 percent had a C-section. Literacy and Education Thirteen percent of young women (aged 15-24 years) are literate. In the richest wealth quintile, 29 percent of young women are literate while in the poorest wealth quintile only 4 percent of young women are literate. Seventeen percent of children attending first grade attended preschool in the previous year. Only 11 percent of children of primary school entry age entered grade 1, which means that 89 percent of children enter the education system late. Timely entry into school is greater in urban (20 percent) than in rural areas (9 percent). The SHHS 2 shows that there is a strong relationship between timely entry into grade 1 and the educational level of the mother and the household’s economic situation. The primary school net attendance rate (adjusted) is 26 percent. In urban areas, the net attendance rate (adjusted) is 43 percent compared to 21 percent in rural areas. The secondary school net attendance rate (adjusted) is 4 percent, with 8 percent in urban areas compared to 3 percent in rural areas. In addition, 65 percent of children who enter grade 1 reach grade 8. The primary school completion rate is 11 percent while the transition rate to secondary school is 56 percent. The gender parity ratio for net attendance rate (adjusted) is 0.81 in primary school and 0.43 in secondary school. Birth registration The births of 35 percent of children under-five years have been registered with civil authorities. Forty-five percent of children in urban areas are registered, compared to 33 percent of children in rural areas. Across states, children in the Central Equatoria are more likely to be registered (61 percent), followed by children in the Western Equatoria (56 percent), while those in the Lakes and Northern Bahr El Ghazal are the least likely to be registered (17 percent). Among children whose births are registered, 29 percent have birth certificates and 6 percent do not have their birth certificates. The birth registrations as well as the possession of birth certificates increase with mother’s educational level and wealth index quintiles. No significant variations observed across gender. Early marriage and polygamy The SHHS 2 data show that the proportion of women aged 15-49 years married before age 15 is 7 percent; and proportion of women aged 20-49 years married before age 18 is about 45 percent. Such marriages (before age 15) are higher in Western Equatoria (13 percent) and Western Bahr Ghazal (12 percent) than in Lakes (4 percent), Upper Nile (5 percent) Northern Bahr Ghazal (5 percent). No significant differentials observed across the residence, age-group, education and economic status among women aged 15-59 years married before the age 15. The SHHS 2 data also show that 41 percent of women aged 15-49 years are in polygynous marriages/ unions. In addition, 40 percent of women aged 15-19 years are currently married/in union. xvii Domestic violence The SHHS 2 results reveal that 79 percent of women think that a husband is justified in beating his wife for at least one of the following reasons: when the woman goes out without telling him, if she neglects the children, if she argues with him, if she refuses to have sex with him, if she burns the food, if she insults him, if she refuses to give him food, if she has another partner, if she steals, if she gossips, and for any of other reasons. The proportions range from 74 percent in Western Bahr El Ghazal to 88 percent in Warap. No significant variations noted across residence, age-groups, education and wealth index quintiles. Children's living arrangements and orphanhood Overall, 54 percent of children aged 0-17 years in South Sudan live with both their parents, but 13 percent are not living with a biological parent. Seventeen percent of children in South Sudan are orphans of one or both parents, and 2 percent of the children aged 0-17 years are double orphans. While about 29 percent live with their mother only, just 3 percent live with their father only. For children living with neither of their biological parents, 8 percent have both parents alive, 1 percent has only their father alive, 3 percent have only their mother alive, and 2 percent both parents are dead. For children living with their mother only, 18 percent have their father alive, while for 11 percent of them their father is dead. For the 3 percent of all children aged 0-17 years living with only their father, their mothers are alive in two in three cases. HIV/AIDS and Sexual Behaviour The SHHS 2 shows that 53 percent of women have heard about AIDS, but only 9 percent of women aged 15-49 years have comprehensive knowledge of AIDS. Specifically, 15 percent of women reject the two most common misconceptions about AIDS and know that a healthy looking person can have the AIDS virus. Fifty-nine percent of young women (aged 15-24 years) have heard of AIDS, and 10 percent of young women have comprehensive knowledge of the disease. Seventeen percent of young women reject the two most common misconceptions and know that a healthy looking person can have the AIDS virus. Forty-one percent of women aged 15-49 years know that HIV can be transmitted from mother to child, and 15 percent know all three means of transmission of AIDS from mother to child. Only 10 percent of women aged 15-49 years express accepting attitudes toward people living with HIV/AIDS on all four indicators analysed in the SHHS 2. A positive attitude towards people living with HIV/AIDS is strongly correlated with educational levels, household wealth, and area of residence. This is also true for knowledge of a place for HIV testing. At the national level, 19 percent of interviewed women know a place for HIV testing. Among women aged 15-49 years who gave birth in the last 2 years, 15 percent received HIV counselling during antenatal care; and 9 percent were offered an HIV test and were tested for HIV during antenatal care, and received the results. During the last 12 months prior to the survey, 54 percent of young women had sex. For young women who are sexually active, 25 percent of them know where to get HIV testing, 16 percent have been tested, 10 percent were tested in the 12 months prior to the survey, and 6 percent were told their results. The SHHS 2 results also show that about 4 percent of women aged 15-49 years had sex with more than one partner in last 12 months. Among those, only 5 percent of women used a condom. For young women aged 15-24 years, the proportion of having sex with more than one partner in the last 12 months is 4 percent and among them, 7 percent used a condom. xviii 1 I. Introduction Background This report is based on the second South Sudan Household Health Survey (SHHS 2), conducted in 2010 by the Ministry of Health and National Bureau of Statistics. The survey provides valuable information on the situation of children and women in South Sudan, and was based, in large part, on the needs to monitor progress towards goals and targets emanating from recent international agreements: the Millennium Declaration, adopted by all 191 United Nations Member States in September 2000, and the Plan of Action of A World Fit For Children, adopted by 189 Member States at the United Nations Special Session on Children in May 2002. Both of these commitments build upon promises made by the international community at the 1990 World Summit for Children. In signing these international agreements, governments committed themselves to improving conditions for their children and to monitoring progress towards that end. UNICEF was assigned a supporting role in this task (see table below). 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 regional level and assess progress towards the goals and targets of the present Plan of Action at the national, regional 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 (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 report is based on the analysis of the information collected during the second South Sudan Household Survey (SHHS 2) carried out in 2010. The survey was largely based on the methodology of the UNICEF supported Multiple Indicator Cluster Survey (MICS). Additional questions and modules were incorporated in the questionnaires during the planning stage in order to obtain additional information required by the Ministry of Health and various development partners for improved planning, decision-making, reporting and management. Planning for the survey was a participatory exercise steered by the Ministry of Health in South Sudan, with technical support from the National Bureau Statistics (NBS). Since the signing of the Comprehensive Peace Agreement (CPA) in 2005 between the then Government of Sudan and the Sudan People¡¦s Liberation Movement (SPLM), the then government of Southern Sudan has worked to establish evidence-based health care system in accordance with the health policy 2006-2011. This survey is part of this effort of establishing the Health Management Information System (HMIS) in the country. A noteworthy capacity development aspect of this survey is that it provides the foundation for the new country to conduct similar surveys in the future. This is the second large-scale household health survey conducted in South Sudan. Along with the success and satisfaction of having completed this very large and important task were also many challenges. The enormity of the task; the anticipated but challenging logistical arrangements to reach selected households; the difficulties for effective field supervision; the complexity of the questionnaire; and the unanticipated non-response by one of the target groups (men aged 15-49), resulting in some data being invalid for inclusion in the report. Still, all of these lessons will no doubt benefit future exercises. Finally, this report presents results on principal topics covered in the survey. The MICS and MOH-GoSS indicators are presented in the summary Table 1. The next chapters present specific objectives, methodology, findings, and conclusions. This final report presents the results of the indicators and topics covered in the survey. Survey Objectives The primary objectives of the second South Sudan Household Health Survey (SHHS 2) include: • To provide up-to-date information for assessing the situation of children and women in South Sudan; • To furnish data needed for monitoring progress toward goals established in the Millennium Declaration and other internationally agreed upon goals, as a basis for future action; • To contribute to the improvement of data and monitoring systems in South Sudan and to strengthen technical expertise in the design, implementation, and analysis of such systems. • To generate data on the situation of children and women, including the identification of vulnerable groups and of disparities, to inform policies and interventions. • To provide up-to-date information on the health status of children and women of South Sudan in order to understand differences related to determinants of health, such as poverty, education, gender, residence type (rural/urban), and the State of residence; • To generate data that assist in monitoring progress towards achieving the MDGs and WFFC’s goals; and • To contribute to essentially desired improvements of data collection, quality, and analysis in South Sudan. 3 II. Sample and Survey Methodology Sample Design The sample for the second South Sudan Household Health Survey (SHHS 2) was designed to provide estimates for a large number of indicators on the situation of children and women at the national level, for urban and rural areas, and for the 10 states across the country: The said States are Upper Nile, Jonglei, Unity, Warap Northern Bahr El Ghazal, Western Bahr El Ghazal, Lakes, Western Equatoria, Central Equatoria, Eastern Equatoria. The sampling frame used for the SHHS 2 is the 2008 Sudan Population and Housing Census. States were identified as the sampling domains or domains of analysis. The sample uses 20 urban and rural strata, two per State. The sample size for the survey was determined by the degree of precision required for survey estimates for each state: 1,000 households in each state. Since a similar level of precision was required for the survey results from each state, it was decided to draw 40 clusters from each state and 25 households from each cluster. However, in each of Unity and Jonglei states only 39 clusters were selected and that yields 975 households by state. The total sample was finally 9,950 households or 398 clusters (enumeration areas) The sample was selected in two stages: within each State, enumeration areas were randomly selected with probability proportional to size as primary sampling units. After a household listing was carried out within the selected enumeration areas, a sample of 25 households was drawn in each sampled enumeration area. The sample is not self-weighting; for reporting national level results, sample weights are used. Questionnaires Four sets of questionnaires were used in the survey: 1) a household questionnaire which was used to collect information on all de jure household members (usual residents), the household, and the dwelling; 2) a women’s questionnaire administered in each household to all women aged 15-49 years; 3) a men’s questionnaire administered in each household to all men aged 15-49 years; and 4) an under-5 questionnaire, administered to mothers or caretakers for all children under 5 living in the household. The questionnaires included the following modules: The Household Questionnaire included the following modules: o household information panel o Household Listing Form and Education o Water and Sanitation (country specific tables were produced for use of improved water sources, Household water treatment, Time to source of drinking water and Drinking water and sanitation ladders) o Household Characteristics o Insecticide Treated Nets (Results are only available for household possession of at least one mosquito net and one long-lasting treated net)Salt Iodization The Questionnaire for Individual Women was administered to all women aged 15-49 years living in the households, and included the following modules: 4 o Woman’s Information Panel o Women’s Background o Child Mortality o Live Birth History o Desire for Last Birth (Results not available) o Maternal and Newborn Health o Contraception o Unmet Need o Attitudes Towards Domestic Violence o Marriage/Union o Female Genital Mutilation/Cutting (Results not available) o Sexual Behaviour o HIV/AIDS o Sexually Transmitted Infections (Results not available) The Questionnaire for Individual Men was administered to all men aged 15-49 years living in the households, and included the following modules: o Men’s information panel o Men’s Background o Attitudes Towards Domestic Violence o Marriage/Union o Sexual Behaviour o HIV/AIDS o Sexually Transmitted Infections The Questionnaire for Children Under -Five was administered to mothers or caretakers of children under 5 years of age1 living in the households. Normally, the questionnaire was administered to mothers of under-5 children; in cases when the mother was not listed in the household roster, a primary caretaker for the child was identified and interviewed. The questionnaire included the following modules: o Under-five Child Information Panel o Age o Birth Registration o Breastfeeding o Early Child Development (Results not available) o Care of Illness o Malaria o Immunization o Anthropometry 1The terms “children under 5”, “children age 0-4 years”, and “children aged 0-59 months” are used interchangeably in this report. 5 The questionnaires are based on the MICS4 model questionnaire2. Based on the results of the pre-test, modifications were made to the wording and translation of the questionnaires. A copy of the South Sudan Household Health Survey questionnaires is provided in Appendix F. In addition to the administration of questionnaires, fieldwork teams tested the salt used for cooking in the households for iodine content, and measured the weights and heights of children age under 5 years. Details and findings of these measurements are provided in the respective sections of the report. 2The model MICS4 questionnaires can be found at www.childinfo.org/mics4_questionnaire.html Training and Fieldwork Training for the fieldwork was conducted from February to March 2010. Training included lectures on interviewing techniques and the contents of the questionnaires, and mock interviews between trainees to gain practice in asking questions. Towards the end of the training period, trainees spent 2 days in practice interviewing in Juba Payam, Central Equatoria State. Field work staff and data analysts were selected across the ten states. A total of 677 field staffs were recruited and trained in January, February and March 2010. The data were collected by these staffs, comprising 40 teams. Each team was comprised of 3 interviewers, one driver, one editor, one measurer and a supervisor. Fieldwork began in last week of March and concluded by the end of June 2010. Data Processing Data were entered using the CSPro software. The data were entered on 20 microcomputers and carried out by 40 data entry operators and 4 data entry supervisors. In order to ensure quality control, all questionnaires were double entered and internal consistency checks were performed. Procedures and standard programs developed under the global MICS4 programme and adapted to the South Sudan questionnaire were used throughout. Data processing began after the end of data collection and was completed in July 2010. Data were analysed using the Statistical Package for Social Sciences (SPSS) software program, Version 18, and the model syntax and tabulation plans developed by UNICEF were used for this purpose. 6 III. Sample Coverage and the Characteristics of Households and Respondents Sample Coverage Of the 9,950 households selected for the sample, 9,760 were found to be occupied. Of these, 9,369 were successfully interviewed for a household response rate of 96 percent. In the interviewed households, 11,568 women (age 15-49 years) were identified. Of these, 9,069 were successfully interviewed, yielding a response rate of 78 percent within interviewed households. In addition, 8,656 men (age 15-49 years) were listed in the household questionnaire. Questionnaires were completed for 4,345 of eligible men, which corresponds to a response rate of 50 percent within interviewed households. There were 10,040 children under age five listed in the household questionnaire. Questionnaires were completed for 8,338 of these children, which corresponds to a response rate of 83 percent within interviewed households. Overall response rates of 75, 48, and 80 are calculated for the women’s, men’s and under-5’s interviews respectively (Table HH.1). Across the 10 States, women’s response rates, except Northern Bahr el Ghazal, are below 85 percent. The results for these States should thus be interpreted with some caution, as their response rates are low. The response rates for the children under five years of age in 5 of the 10 States were equally low. These are Western Equatoria, Central Equatoria, Unity, Upper Nile and Lakes States. These results are low, and therefore interpretation in these States should also be handled with caution. Response rates for urban and rural areas for the three categories (women, men and children under-five) are also below 85 percent; this as well requires some caution in the interpretation of the results. Crucially, response for the men’s module was exceedingly low, as their overall response rate is 48. Accordingly, all analysis on men has been dropped from this report. Characteristics of Households The weighted age and sex distribution of survey population is provided in Table HH.2. The distribution is also used to produce the population pyramid in Figure HH.1. In the 9,369 households successfully interviewed in the survey, 56,001 household members were listed. Of these, 26,392 were males, and 29,609 were females. Table HH.2 presents percent and frequency distribution of the household population by five- year age- groups, together with dependency age-groups by child and adult populations. The table also shows the proportions of households with at least one child under 18, and household with at least one adult aged 18 years and above. Almost 18 percent of the population in the country is below the age five years. Of these, about 49 percent are males and 51 percent are females. Put together, age-groups 0-4 and 5-9 constitute 38 percent of the total population of the country. This proportion was 32 percent in 2008 Population and Housing Census. Accordingly, 60 percent of the population is below age 20 years, indicative of an exceedingly young population. The percentages for the dependency age-groups of 0-14 years, 15-64 years, and 65+ years are 53, 45 and 2 percent, respectively. The comparison of the age-groups and sex distributions of SHHS 2 with those from the 2008 Population and Housing Census (Southern Sudan Counts, 2010, Table 1-4, p. 10) shows no significant differences. 7 Ta bl e H H .1 : R es ul ts o f h ou se ho ld , w om en 's , m en 's a nd u nd er -f iv e in te rv ie w s N um be rs o f h ou se ho ld s, w om en , m en a nd c hi ld re n un de r 5 b y re su lts o f t he h ou se ho ld , w om en 's, m en 's an d un de r- 5' s i nt er vi ew s, a nd h ou se ho ld , w om en 's, m en 's an d un de r- 5' s r es po ns e ra te s, S ou th S ud an , 2 01 0 To ta l Ur ba n Ru ra l Up pe r N ile Jo ng le i Un ity W ar ap N or th er n Ba hr E l G ha za l W es te rn Ba hr E l G ha za l La ke s W es te rn Eq ua to ria Ce nt ra l Eq ua to ria Ea st er n Eq ua to ria Re sid en ce St at e Ho us eh ol ds S am pl ed 26 00 73 50 10 00 97 5 97 5 10 00 10 00 10 00 10 00 10 00 10 00 10 00 99 50 Ho us eh ol ds O cc up ie d 25 42 72 18 98 2 94 7 94 2 96 6 99 1 98 7 98 8 97 8 99 0 98 9 97 60 Ho us eh ol ds In te rv ie w ed 24 20 69 49 94 9 91 2 84 0 93 5 98 2 95 0 93 9 94 4 96 3 95 5 93 69 Ho us eh ol d re sp on se ra te 95 .2 96 .3 96 .6 96 .3 89 .2 96 .8 99 .1 96 .3 95 .0 96 .5 97 .3 96 .6 96 .0 W om en E lig ib le 32 33 83 35 13 14 10 69 10 77 12 72 10 58 10 21 11 69 12 05 12 57 11 26 11 56 8 W om en In te rv ie w ed 24 38 66 31 97 6 84 3 78 7 10 24 94 8 84 0 95 7 95 3 91 7 82 4 90 69 M en E lig ib le 26 57 59 99 10 07 62 7 73 7 98 0 65 5 87 2 79 8 91 5 11 97 86 8 86 56 M en In te rv ie w ed 13 24 30 21 49 3 37 5 29 4 36 6 38 3 59 1 28 5 62 2 62 9 30 7 43 45 W om en 's re sp on se ra te 75 .4 79 .6 74 .3 78 .9 73 .1 80 .5 89 .6 82 .3 81 .9 79 .1 73 .0 73 .2 78 .4 W om en 's ov er al l r es po ns e ra te 71 .8 76 .6 71 .8 75 .9 65 .2 77 .9 88 .8 79 .2 77 .8 76 .3 71 .0 70 .7 75 .3 M en 's re sp on se ra te 49 .8 50 .4 49 .0 59 .8 39 .9 37 .3 58 .5 67 .8 35 .7 68 .0 52 .5 35 .4 50 .2 M en 's o ve ra ll re sp on se ra te 47 .4 48 .5 47 .3 57 .6 35 .6 36 .1 57 .9 65 .2 33 .9 65 .6 51 .1 34 .2 48 .2 Ch ild re n un de r 5 E lig ib le 27 18 73 22 10 95 96 8 10 70 10 98 10 42 96 2 10 32 92 3 96 1 88 9 10 04 0 Ch ild re n un de r 5 M ot he r/ Ca re ta ke r In te rv ie w ed 21 74 61 64 82 7 82 5 90 0 95 0 96 7 82 0 86 3 77 1 66 2 75 3 83 38 Un de r- 5' s r es po ns e ra te 80 .0 84 .2 75 .5 85 .2 84 .1 86 .5 92 .8 85 .2 83 .6 83 .5 68 .9 84 .7 83 .0 Un de r- 5' s o ve ra ll re sp on se ra te 76 .1 81 .0 73 .0 82 .1 75 .0 83 .7 92 .0 82 .0 79 .5 80 .6 67 .0 81 .8 79 .7 8 Table HH.2: Household age distribution by sex, South Sudan, 2010 Percent and frequency distribution of the household popilation by five-year age groups, dependency age groups and by child (age 0-17 years) and adult populations (age 18 or more) by sex, south sudan, 2010 Number Percent Number Percent Number Percent Percent Males Females Total Some discussion on the age pyramid (Figure HH.1) is provided here. The Figure HH.1 presents some irregularities for both sexes in comparison with the 2008 Population and Housing Census data. However, the irregularities of most concerns are those that may have impact on outcomes of under-five children, children mortality and birth history of women aged 15-49 years. And in this regards the Figure HH.1 shows an excess of children aged 5-9 years compared to those aged 0-4 years. It is probably due to a preference for reporting age 5 and therefore under- reporting for age-group 0-4 years. This is quiet visible when examining the Table DQ.1. The figures reported at age 4 for both sexes are lower compared that reported at ages 5 and 6.The same situation (under-reporting) is observed for women aged 45-49 years compared to those aged 50-54 year); and the Table DQ.1 also shows that the figures reported at age 49 years are lower than that reported to age 50 years for both sexes. For women, the difference is huge: the number of women reporting age 50 years is nearly 9 times higher (805 women) than that aged Age-group 0-4 5075 19.2 4960 16.7 10035 17.9 15.8 5-9 5726 21.7 5698 19.2 11424 20.4 15.7 10-14 4258 16.1 4018 13.6 8276 14.8 12.8 15-19 1739 6.6 2154 7.3 3893 7.0 10.8 20-24 1299 4.9 2124 7.2 3423 6.1 8.9 25-29 1387 5.3 2561 8.7 3948 7.0 8.4 30-34 1163 4.4 1768 6.0 2932 5.2 6.5 35-39 1340 5.1 1628 5.5 2968 5.3 5.8 40-44 796 3.0 752 2.5 1548 2.8 4.1 45-49 951 3.6 685 2.3 1636 2.9 3.3 50-54 996 3.8 1548 5.2 2544 4.5 2.4 55-59 549 2.1 639 2.2 1188 2.1 1.5 60-64 527 2.0 530 1.8 1057 1.9 1.4 65-69 258 1.0 264 0.9 523 0.9 2.6 70-74 164 0.6 141 0.5 305 0.5 2.6 75-79 78 0.3 53 0.2 131 0.2 2.6 80-84 48 0.2 52 0.2 101 0.2 2.6 85+ 36 0.1 31 0.1 68 0.1 2.6 Missing/DK 1 0.0 2 0.0 2 0.0 2.6 Dependency age groups 0-14 15058 57.1 14676 49.6 29734 53.1 44.0 15-64 10748 40.7 14390 48.6 25137 44.9 52.0 65+ 585 2.2 542 1.8 1127 2.0 4.0 Missing/DK 1 0.0 2 0.0 2 0.0 0.0 Children and adult populations Children age 0-17 years 16126 61.1 15846 53.5 31972 57.1 na Adults age 18+ years 10265 38.9 13762 46.5 24027 42.9 na Missing/DK 1 0.0 2 0.0 2 0.0 na Total 26392 100.0 29609 100.0 56001 100.0 100.0 Population and Housing Census 2008 9 49 years (90 women). Furthermore, the Table DQ.2 shows that the ratio of women aged 50-54 years to those aged 45-49 years is more than double (2.26 times), which is a another confirmation of under-reporting of women age-group 45-49 years. This under-reporting phenomenon can also be a result of the two other following factors: • Cheating on behalf of some data collectors in order to reduce the workload on under-five questionnaire and on women birth history module • Another explanation is that the household’s respondent providing the age of each household member might have genuinely rounded ages. Indeed data from South Sudan 2008 Population and Housing Census provide a different structure for children age-groups 0-4 years and 5-9 years, and for women age-groups 45-49 and 50-54 years. For example, for both sexes, as well as the total, the number of children aged 0-4 years exceeds slightly that of children aged 5-9 years; also for women, the number of women aged 45-49 years is higher than that of women aged 50-54 years. Figure HH.1: Age and sex distribution of household population, South Sudan, 2010 10 Tables HH.3 - HH.5 provide basic information on the households, female respondents aged 15- 49 years and children under-5 by presenting the unweighted, as well as the weighted numbers. Information on the basic characteristics of households, women and children under-5 interviewed in the survey is essential for the interpretation of findings presented later in the report and also can provide an indication of the representativeness of the survey. The remaining tables in this report are presented only with weighted numbers. See Appendix A for more details about the weighting. Table HH.3 provides basic background information on the households. Within households, the sex of the household head, state, residence, number of household members, and education of household head are 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. The weighted and unweighted numbers of households are equal, since the sample weights were normalized (See Appendix A). Generally, the head of household is considered as the key person because he/she ensures that the needs and well-being of the members are addressed in the household. Table HH.3 shows that 58 percent of the head of households interviewed were male, while female were 42 percent. More than three quarters of the households are rural. And 58 percent of households have members in the range 4 -7 persons; only 9 percent of households reported having 10 and more family members. Jonglei, Warap, Central Equatoria, Eastern Equatoria and Upper Nile states constitute about two-third (64 percent) of the entire household population in South Sudan for both SHHS 2 and the 2008 South Sudan Population and Housing Census. The education of the head of household has an impact on the welfare of the household members. The proportion of heads of households who have no education is nearly 80 percent, while it is 12 percent for those with primary education and about 9 percent for those with secondary and higher education. The weighted percent of households and respondents presented in Table HH.3 was also compared to the data of the 2008 South Sudan Population and Housing Census. The main discrepancies observed are the following: • The current share of male is 58 percent compared to 52 percent in 2008 South Sudan Population and Housing Census. Likewise, the current share of female is 42 percent, while it was 48 percent in 2008; • The distribution of population by residence is 23 percent for urban areas and 77 percent for rural areas, compared to 9 and 91 percent respectively in the 2008 South Sudan Population and Housing Census. 11 Table HH.3a: Household composition Percent distribution of households by selected characteristics, South Sudan, 2010 Population and Housing Census 2008 Weighted percent Number of households Weighted Unweighted Percent Sex of household head Male 58.0 5437 5377 52.0 Female 42.0 3932 3992 48.0 State Upper Nile 10.7 998 949 11.7 Jonglei 15.3 1432 912 16.4 Unity 6.5 608 840 7.1 Warap 12.9 1205 935 11.8 Northern Bahr El Ghazal 9.9 930 982 8.7 Western Bahr El Ghazal 4.1 387 950 4.0 Lakes 7.2 676 939 8.4 Western Equatoria 8.2 770 944 7.5 Central Equatoria 13.3 1249 963 13.4 Eastern Equatoria 11.9 1114 955 11.0 Residence Urban 23.1 2161 2420 8.9 Rural 76.9 7208 6949 91.1 Number of household members na 1 3.2 295 325 na 2 5.6 524 560 na 3 9.0 840 851 na 4 13.1 1224 1226 na 5 16.3 1528 1491 na 6 16.2 1520 1478 na 7 12.5 1173 1135 na 8 9.0 847 839 na 9 5.7 533 543 na 10+ 9.4 885 921 na Education of household head None 79.5 7446 7363 na Primary 11.9 1120 1196 na Secondary + 8.5 797 804 na Missing/DK 0.1 6 6 na Total 100.0 9369 9369 100.0 12 Table HH.3a provides the proportions of households with at least one child under 18 years, at least one child under 5 years, at least one eligible woman aged 15-49 years and at least one eligible man aged 15-49 years, and the mean household size. In South Sudan, 68 percent of Households have at least one child aged 0-4 years, 91 percent of Households have at least one child aged 0-17 years, 88 percent of Households have at least one woman aged 15-49 years, 64 percent of Households have at least one man aged 15-49, and the mean household size is 6 persons. This average size was 7 persons per household in 2008 Population and Housing Census. Characteristics of Female Respondents 15-49 Years of Age and Children Under-5 Tables HH.4 and HH.5 provide information on the background characteristics of female respondents 15-49 years of age and of children under age 5. In both tables, the total numbers of weighted and unweighted observations are equal, since sample weights have been normalized (standardized). In addition to providing useful information on the background characteristics of women and children, 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. Table HH.3b: Household composition Percent distribution of households by selected characteristics, South Sudan, 2010 Number of households Weighted percent Weighted Unweighted Households with at least: one child age 0-4 years 67.8 9369 9369 Households with at least: one child age 0-17 years 90.6 9369 9369 Households with at least: one woman age 15-49 years 88.2 9369 9369 Households with at least: one man age 15-49 years 64.1 9369 9369 Mean household size 6.0 9369 9369 13 Table HH.4 provides background characteristics of female respondents aged 15-49 years. The table includes information on the distribution of women according to state, residence, age, marital status, motherhood status, births in last two years, education3, and wealth index quintiles4. According to Table HH.4, Jonglei, Central Equatoria and Warap States are some of the States with relatively higher proportion of women aged 15-49 years (14 percent, each). These proportions are lower in Western Bahr El Ghazal State (4 percent), and also in Unity and Lakes States, each reporting 7 percent. Besides, 32 percent of the women are from age-groups 15-19 and 20-24 years. The age-groups 40-44 and 45-49 years constitute 13 percent of the women of aged 15-49 years. The SHHS 2 has also shown that almost three quarters of women aged 15-49 years are from rural areas. Most women of reproductive age-group were found to be either married or in union (81 percent), and the same proportion reported to ever given birth. Besides, 38 percent are reported to have given birth in last two years prior to the survey. The proportion of women aged 15-49 years who never married or being in union constitutes 11 percent, while the proportion divorced and separated, collectively, makes 4 percent. Most of the women (79 percent) have no education. Those that have primary and secondary education constitute relatively small percentages of 17 and 4 percents, respectively. 3 Unless otherwise stated, “education” refers to educational level attended by the respondent throughout this report when it is used as a background variable. 4 Principal components analysis was performed by using information on the ownership of consumer goods, dwelling characteristics, water and sanitation, and other characteristics that are related to the household’s wealth to assign weights (factor scores) to each of the household assets. Each household was then assigned a wealth score based on these weights and the assets owned by that household. The survey household population was then ranked according to the wealth score of the household they are living in, and was finally divided into 5 equal parts (quintiles) from lowest (poorest) to highest (richest). The assets used in these calculations were as follows: source of drinking water, type of sanitation facility, persons per sleeping room, type of floor, type of roof, type of wall, type of cooking fuel, household member assets (watch, mobile phone, bicycle, motor cycle, car/truck, computer, internet), ownership of agricultural land. The wealth index is assumed to capture the underlying long-term wealth through information on the household assets, and is intended to produce a ranking of households by wealth, from poorest to richest. The wealth index does not provide information on absolute poverty, current income or expenditure levels. The wealth scores calculated are applicable for only the particular data set they are based on. Further information on the construction of the wealth index can be found in Filmer, D. and Pritchett, L., 2001. “Estimating wealth effects without expenditure data – or tears: An application to educational enrolments in states of India”. Demography 38(1): 115-132. Gwatkin, D.R., Rutstein, S., Johnson, K. , Pande, R. and Wagstaff. A., 2000. Socio-Economic Differences in Health, Nutrition, and Population. HNP/Poverty Thematic Group, Washington, DC: World Bank. Rutstein, S.O. and Johnson, K., 2004. The DHS Wealth Index. DHS Comparative Reports No. 6. Calverton, Maryland: ORC Macro. 14 Table HH.4: Women's background characteristics Percent and frequency distribution of women age 15-49 years by selected characteristics, South Sudan, 2010 Weighted percent Number of women Weighted Unweighted State Upper Nile 12.0 1088 976 Jonglei 14.3 1299 843 Unity 6.5 594 787 Warap 14.0 1273 1024 Northern Bahr El Ghazal 8.6 779 948 Western Bahr El Ghazal 3.6 323 840 Lakes 7.3 659 957 Western Equatoria 8.6 778 953 Central Equatoria 13.9 1264 917 Eastern Equatoria 11.2 1012 824 Residence Urban 25.6 2321 2438 Rural 74.4 6748 6631 Age 15-19 14.8 1344 1360 20-24 17.5 1589 1612 25-29 22.8 2067 2097 30-34 16.4 1490 1468 35-39 15.4 1396 1370 40-44 6.9 627 620 45-49 6.1 555 542 Marital/Union status Currently married/in union 81.0 7350 7340 Widowed 3.9 350 343 Divorced 1.3 117 124 Separated 2.5 227 235 Never married/in union 11.1 1009 1013 Missing 0.2 16 14 Motherhood status Ever gave birth 81.0 7345 7322 Never gave birth 7.9 715 734 Never married/in union 11.1 1009 1013 Births in last two years Had a birth in last two years 38.4 3479 3516 Had no birth in last two years 50.5 4581 4540 Never married/in union 11.1 1009 1013 Education None 78.8 7150 7153 Primary 16.9 1537 1559 Secondary + 3.9 353 331 Adult education/Khalwa/Sunday education 0.3 29 26 Wealth index quintiles Poorest 19.0 1724 1613 Second 19.3 1746 1726 Middle 19.8 1798 1818 Fourth 20.5 1859 1920 Richest 21.4 1943 1992 Total 100.0 9069 9069 15 Selected background characteristics of children under 5 are presented in Table HH.5. These include the distribution of children by several attributes: sex, region and area, age, mother's or caretaker's education, and wealth. Fifty-one percent of the children under-five years are male. Five of the ten States have a slight higher proportion of children under-five years. These are Jonglei (15 percent), Warap (14 percent), Central Equatoria and Upper Nile States (each having 12 percent), and Easter Equatoria, with a reported 10 percent of children under five. The State with the lowest proportion is Western Bahr El Ghazal (4 percent). Table HH.5 also showed that about three quarters (76 percent) of children under-five years are from rural areas. The age distribution in months of the children under-five years is also provided. Children are somehow evenly distributed across age-groups (months) of 0-11, 12-23, 24-35, 36-47, on average with 22 percent in each age group (months). However the last age-group of 48-59 months has only 14 percent, due probably to mortality. The average for all 5 age-groups should be 20 percent. Eighty-four percent of the children have mothers/caretakers with no formal education, while 13 percent have mothers/care takers with primary education and 3 percent have mothers/ caretakers with secondary and higher education. On contrary, the proportions of children under- five years are evenly (20 percent) distributed across wealth groups. 16 Table HH.5: Under-5's background characteristics Percent and frequency distribution of children under five years of age by selected characteristics, South Sudan, 2010 Weighted percent Number of children Weighted Unweighted Sex Male 51.1 4261 4258 Female 48.9 4077 4080 State Upper Nile 11.6 967 827 Jonglei 15.0 1254 825 Unity 7.6 635 900 Warap 14.1 1176 950 Northern Bahr El Ghazal 9.8 820 967 Western Bahr El Ghazal 3.9 326 820 Lakes 7.4 618 863 Western Equatoria 7.7 644 771 Central Equatoria 12.4 1036 662 Eastern Equatoria 10.3 862 753 Residence Urban 24.5 2042 2174 Rural 75.5 6296 6164 Age-group 0-5 10.4 866 877 6-11 10.4 864 870 12-23 20.4 1704 1683 24-35 23.5 1958 1971 36-47 21.5 1789 1798 48-59 13.9 1156 1139 Mother's education None 83.9 6993 7031 Primary 13.0 1080 1060 Secondary + 3.1 262 245 Missing/DK 0.0 3 2 Wealth index quintiles Poorest 20.5 1712 1644 Second 19.6 1635 1609 Middle 19.8 1653 1672 Fourth 21.0 1753 1802 Richest 19.0 1585 1611 Total 100.0 8338 8338 17 IV. Child Mortality One of the overarching goals of the Millennium Development Goals (MDGs) and the World Fit for Children (WFFC) is to reduce infant and under-five mortality. Specifically, the MDG4 calls for the reduction of under-five mortality by two-thirds between 1990 and 2015. Monitoring progress towards this goal is an important but difficult objective. This chapter describes levels, trends, and differentials in early childhood mortality in South Sudan. Early childhood mortality rates in general and infant mortality rate (Miller and Goldman, 2011) in particular contribute to a better understanding of a country’s socio-economic situation and is a major indicator of the quality of life of the population. The information in this chapter is disaggregated by geographic, socio-economic and demographic characteristics since they help to identify subgroups that are at high risk and therefore to put in place appropriate health programmes for child survival. Measuring childhood mortality may seem easy, but attempts using direct questions, such as “Has anyone in this household died in the last year?” give inaccurate results. Using direct measures of child mortality from birth histories is time consuming, more expensive, and requires greater attention to training and supervision. Alternatively, indirect methods developed to measure child mortality produce robust estimates that are comparable with the ones obtained from other sources. The previous MICS rounds used the indirect estimation technique, known as the Brass method (United Nations, 1983) for the estimation of childhood mortality rates. Indirect methods minimize the pitfalls of memory lapses, inexact or misinterpreted definitions, and poor interviewer performance. However, the indirect methods cannot provide the very important infant mortality rate breakdown (neonatal and post-neonatal mortality rates) and the estimate of child mortality rate (4q1); it also does not provide the richness of data collected from female respondents’ birth histories. The childhood mortality rates presented in this chapter are computed directly from birth histories collected from the female respondents. Women in the age-group 15-49 years who had ever given birth were asked to provide a detailed history of all their live births in chronological order starting with the first live birth. All children born to the respondents, whether dead or alive, were listed by name, sex, birthday and if dead, the date of death. The data analysis on childhood mortality was limited to a period of 15 years prior to the survey, in order to minimize the effect of the pitfalls of memory lapses and also due to the failure to capture births from old women. Since the primary causes of childhood mortality change according to child’s age, from mostly biological factors to environmental factors, the childhood mortality rates are expressed by age categories and are defined as follows: • Neonatal mortality rate (NMR): the probability of dying within the first month of life • Post-neonatal mortality (PNMR): the difference between infant and neonatal mortality rates • Infant mortality rate (1q0): the probability of dying between birth and the first birthday • Child mortality rate (4q1): the probability of dying between exact ages one and five • Under-five mortality rate (5q0): the probability of dying between birth and the fifth birthday 18 Assessment of Data Quality in early childhood mortality In any survey, the quality of early childhood mortality estimates depends on sampling and non-sampling errors. For SHHS 2, the sampling errors are dealt with in Appendix F. The non-sampling errors have to do with the completeness of data on childhood mortality and the accuracy of the information provided by mother on the date of birth for all live births, and date of death for deceased children. Typically, three types of non-sampling errors are known to affect the childhood mortality estimates: omission of births and deaths, displacement of dates of births and deaths, and misreporting of age at death. Taking into consideration the different elements described above as well as the response rate for women’s questionnaire, some caution is necessary when interpreting the childhood mortality trends suggested by SHHS 2. The Data Quality Tables presented in Appendix E were reviewed and the main observations are summarized below: Table DQ.2: The focus of this table is the completion rate by age-group. The results show that the completion rate is low: it goes from 63 percent to 86 percent for the 7 age-groups, with an overall rate of 78 percent for all women aged 15-49 years. Furthermore, the ratios of age- groups 15-19 years to 10-14 years and 50-54 years to 45-49years are 0.54 and 2.26 respectively. This means that some eligible women aged 15-49 years were left out of the SSHH2 women’s sample. This has an impact on early childhood mortality rates estimates as well as on the fertility rate estimate. Table DQ.3: This table provides data on the household population of children aged 0-7 years, children aged 0-4 years whose mothers/caretakers were interviewed, and the percentage of under-5 children whose mothers/caretakers were interviewed, by single ages. This table shows that the ratio of the population aged 5 years to that aged 4 years is 1.26. In other words, there is evidence of misreporting of age at birth for some children aged 4 years. As result, some children aged 4 years were not included in the under-five children sample. Table DQ.17: This table shows the number of births, percentage with complete birth date, sex ratio at birth, and calendar year ratio by year of birth, according to living, dead, and total children. Some discrepancies are visible in the following areas: • Number of births: For 2010, the numbers of births reported are lower (around one-quarter) compared to 10 previous years. The numbers should have been close to the half of the numbers of reported births for the 10 previous years, since the survey covered the half of 2010; • Percent of dead children with complete birth date: From 1993 to 2010, the percentage of dead children with complete birth date is below 85%; • Sex ratio at birth: Significant variations are noticed for the sex ratio at birth. For all births, for example, the sex ratio at birth ranges from 97.1 in 2006 to 141.0 in 1991; • Calendar year ratio: Major variations are also noted. These range from 9.1 in 1990 to 159.9 in 2000 for all births. Table DQ.18: This table provides information on the distribution of reported deaths under one month of age by age at death in days, and the percentage of neonatal deaths reported to have occurred at ages 0-6 days, by 5-year periods preceding the survey. For the four five-periods considered (0-4, 5-9, 10-14 and 15-19 years before the survey), the figures show some heaping at ages zero, one, three, four and seven days. 19 Table DQ.19: The focus of this table is to examine the degree of heaping at ages one and 12 months as these are the cut-off points for specific childhood mortality rates. The data do not suggest any heaping at these two cut-offs points. Although there is evidence of some typical data issues found in different surveys (MICS and DHS) worldwide, there is no apparent major reason to challenge the overall data quality in SHHS 2, and especially for the most recent period of 0–4 years preceding the survey. Levels and Trends of Early Childhood Mortality The second South Sudan Household Health Survey (SHHS 2) was conducted from the last week of March to the end of June 2010 and early childhood mortality rates were estimated using the direct method. The reference point (mid-point interval) for the childhood mortality for the most recent five year period is the last week of September 2007. Table CM.1 presents the childhood mortality rates computed using the ‘direct’ or ‘birth history’ method of estimation during the last 15 years before the survey. The Neonatal mortality rate in the most recent 5-year period is estimated at 43 per 1,000 live births, while the post-neonatal mortality rate is estimated as 36 per 1,000 live births. The infant mortality rate in the five years preceding the survey is 79 per 1,000 live births and under-five mortality is 108 deaths per 1,000 live births for the same period. And the child mortality rate is estimated at 32 deaths per 1,000 children aged 1 year for the 5 years preceding the survey. Table CM.1 also show that for the 5 years preceding the survey the proportion of neonatal mortality rate in the infant mortality rate is 54 percent. This means that in the last 5 years before the survey, 54 percent of infant deaths occur within the month of life. This proportion was estimated at 50 percent in 2011 (UNICEF et al., 2012). [1] MICS indicator 1.3 [2] MICS indicator 1.4 [3] MICS indicator 1.1, MDG indicator 4.1 [4] MICS indicator 1.5; [5] MICS indicator 1.2; MDG indicator 4.2 Neonatal mortality rate [1] Years Preceeding the Survey Postneonatal mortality rate [2] Infant mortality rate [3] Child mortality rate [4] Underfive mortality rate [5] 20 Figure CM.1 shows that the under-five mortality rate declined from 121 deaths per 1,000 live births for the period 10-14 years before the survey to 84 deaths per 1,000 live births during the 5-9 years before the survey, and then increased significantly to 108 deaths per 1,000 live births during the 5-year period prior to the survey. For the 10-14 years before the survey, the infant mortality ratedeclined from 75 deaths per 1,000 live births to 55 deaths per 1,000 live births and then increased to 79 deaths per 1,000 live births for the 5-9 years before the survey. The child mortality rate declined from 50 deaths per 1,000 children aged 1 for the 10-14 years before the survey, and then remained at about the same level: 30 and 32 deaths per 1,000 children respectively for the periods 5-9 and 0-4 years before the survey. The neonatal mortality rate remained at comparable levels for 10-14 and 5-9 years before the survey with 33 and 29 deaths per 1,000 live births, respectively, and then increased at 43 deaths per 1,000 live births. It is also observed that the proportion (contribution) of neonatal mortality rate in infant mortality rate has increased from 44 percent (10-14 years before the survey) to 55 percent (0-4 years before the survey). The post-neonatal mortality rate declined from 41 deaths per 1,000 live births for the period 10-14 years before the survey to 26 deaths per 1,000 live births during the 5-9 years before the survey, and then increased slightly to 36 deaths per 1,000 live births during the 5-year period prior to the survey. Figure CM.1: Trends in Childhood Mortality Rates for MICS4, South Sudan, 2010 21 Early childhood mortality rates by state, residence and socio-economic characteristics Table CM.2 provides estimates of childhood mortality by state, residence and two socio-eco- nomic characteristics. The SHHS 2 data indicate that there are also some differences across all the background characteristics considered. The early childhood mortality estimates for the state level show that Northern Bahr El Ghazal and Central Equatoria have the highest under- five mortality rate with 157 deaths per 1,000 live births and 152 deaths per 1,000 live births, respectively; and the lowest proportions are reported in Jonglei (48 percent) and Unity (51 deaths per 1,000 live births). Northern Bahr El Ghazal state has also the highest infant mortal- ity rate (120 deaths per 1,000 live births) and the lowest infant mortality rates are in Jonglei and Unity (31 deaths per 1,000 live births each). Table CM.2: Early childhood mortality rates by background characteristics Neonatal, post neonatal, Infant and Under-five mortality rates for the 5-year period preceding the survey by socioeconomic characteristics, South Sudan, 2010 Neonatal mortality rate [1] Post neonatal mortality rate [2] Infant mortality rate [3] Child mortality rate [4] Under five mortality rate [5] [1] MICS indicator 1.3 [2] MICS indicator 1.4 [3] MICS indicator 1.2, MDG indicator 4.2 [4] MICS indicator 1.5; [5] MICS indicator 1.1; MDG indicator 4.1 Figures in parentheses '()' are based on 250-499 unweighted exposed persons State Upper Nile 29 44 74 26 98 Jonglei 14 17 31 17 48 Unity 15 16 31 20 51 Warap 31 40 71 50 117 Northern Bahr El Ghazal 78 42 120 42 157 Western Bahr El Ghazal 35 56 91 27 115 Lakes 29 23 52 22 73 Western Equatoria 53 43 95 38 130 Central Equatoria 76 39 115 42 152 Eastern Equatoria 59 47 106 35 137 Residence Urban 47 44 90 31 118 Rural 41 33 75 33 105 Education None 42 36 78 31 107 Primary 47 35 82 39 118 Secondary + (43) (40) (83) (35) (115) Wealth index quintile Poorest 48 31 79 31 108 Second 43 37 80 35 112 Middle 40 31 71 30 99 Fourth 38 35 73 35 106 Richest 44 46 90 29 117 Total 43 36 79 32 108 22 Residence and Socio-economic Differentials in Childhood Mortality The data presented in Table CM.2 show an unexpected pattern for infant and under-five mortality rates across residence, mother’s education and economic status. The two childhood mortality indicators are higher in urban areas, primary education and richest households. The SHHS 2 results show that under-5 mortality is estimated at 118 deaths per 1,000 live births in urban areas, and 105 deaths per 1,000 live births in rural areas. For infant mortality, this is estimated at 90 deaths per 1,000 live births in urban areas, and 75 deaths per 1,000 live births in rural areas. Secondary and higher education is not included in analysis due to the fewer cases of exposure (250-499 women). The findings show that under-five mortality rate is estimated at 107 deaths per 1000 live births for children whose mothers have no education and at 118 deaths per 1,000 live births for mothers with primary education. For children whose mothers have no education, infant mortality rate is estimated at 78 deaths per 1000 live births, and at 82 deaths per 1000 live births for children whose mothers have primary education. As already mentioned above, the infant and under-five mortality rates are higher in the richest households compared to the remaining four and lower quintiles. Significant variations are also noted between middle and richest quintiles. The SSHHS 2 data indicate that children from the richest households have higher mortality rates, compared to those from the middle households (Table CM.2 and Figure CM.2). For example, infant mortality is estimated at 71 per 1000 live deaths for children from the middle wealth quintile, and 90 deaths per 1000 live deaths for children in the richest wealth quintile. This means that the children from the richest wealth quintile are more (1.27 times) likely to die before their first birthday compared to those from the middle wealth quintile. Under-5 mortality is estimated at 117 deaths per 1,000 live births for children from the richest households, compared to 99 deaths per 1,000 live births for children belonging to the middle households. This means that the children from the richest households are more (1.18 times) likely to die before their fifth birthday as those from the middle households (Figure CM.2). 23 Figure CM.2: Infant and under-5 mortality rates by background characteristics, South Sudan, 2010 Residence Wealth index Quintiles Education 24 Demographic Characteristics and Childhood Mortality Demographic factors such as the sex of the child, age of the mother at birth, birth order, and length of the preceding birth interval, are strongly associated with the survival chances of young children. Table CM.3 and Figure CM.3 show the relationships between early childhood mortality rates and these demographic variables. For all childhood mortality indicators (Figure CM.3), early childhood mortality rates are higher for males than females. For example, under-five mortality rate is estimated at 117 deaths per 1,000 live births for boys, and 99 deaths per 1,000 live births for girls. This means that male children are 1.18 times more likely to die before the fifth birthday than females. Neonatal mortality rate is estimated at 46 deaths per 1000 live births for male children, and 39 deaths per 1000 live births for female children, which means that male children are 1.18 times more likely to die during the first month of life than their female counterparts. Table CM.3 and Figure CM.3 show that for mothers aged below 20 years, the infant mortality rate is estimated at 72 deaths per 1,000 live births, compared to 67 deaths per 1,000 live births for mothers aged 20-34 years. The under-five mortality rate is estimated at 91 deaths per 1,000 for women below the age of 20 years, and at 96 deaths per 1,000 live births for women aged 20-34 years. Infant and under-five mortality rates are higher for children born to women aged 35-49 years, with 134 deaths per 1,000 live births and 188 deaths per 1,000 live births, respectively. Table CM.3: Early childhood mortality rates by demographic characteristics Neonatal, post neonatal, Infant and Under-five mortality rates for the 5-year period preceding the survey by demographic characteristics, South Sudan, 2010 Neonatal mortality rate [1] Post neonatal mortality rate [2] Infant mortality rate [3] Child mortality rate [4] Under five mortality rate [5] [1] MICS indicator 1.3 [2] MICS indicator 1.4 [3] MICS indicator 1.2, MDG indicator 4.2 [4] MICS indicator 1.5; [5] MICS indicator 1.1; MDG indicator 4.1 Sex of child Male 46 38 84 36 117 Female 39 34 73 29 99 Mothers age at birth < 20 years 34 38 72 20 91 20 - 34 years 37 30 67 31 96 35 - 49 years 75 59 134 56 182 Birth order 1 31 31 63 22 83 2-3 26 26 52 26 76 4-6 44 42 86 34 117 7+ 107 54 161 91 238 Previous birth interval < 2 years 87 60 147 49 188 2 years 34 26 60 31 89 3 years 21 26 47 27 72 4 + years 29 31 60 26 84 Total 43 36 79 32 108 25 Table CM.3 and Figure CM.3 also show that birth order 4-6 and above face a higher risk of under-five mortality. Birth orders seven and higher experience the highest levels of childhood mortality, while mortality is lowest for second and third order births. For example, under-5 mortality rate is estimated at 238 deaths per 1,000 live births for birth order seven and higher, 76 deaths per 1,000 live births for birth orders 2-3, and 117 deaths per 1,000 live births for birth order 4-6 (Figure CM.3). The birth interval also affects survival when there is an interval of less than two years between pregnancies, demonstrating the importance of spacing on child survival. This is fairly consistent in all childhood mortality indicators. For example, infant mortality rate for children born at less than a two-year interval is 147 deaths per 1,000 live births and 47 deaths per 1,000 live births when the birth interval is 3 years. This means that the children born at less than a two-year interval are more than three times likely to die before their first birthday compared to the ones born at 3 years interval. Under-five mortality rate is 188 deaths per 1,000 live births for birth intervals of less than 2 years and 72 deaths per 1,000 live births when a birth occurs 3 years after a previous birth. Children born at less than a two-year interval are more likely to die before their fifth birthday compared to the ones born at 3 years interval. Figure CM. 3: Under-5 mortality rates by demographic characteristics, South Sudan, 2010 26 V. Nutrition 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 the children who die from causes related to malnutrition were only mildly or moderately malnourished – showing no outward sign of their vulnerability. The Millennium Development 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 standards5. Each of the three nutritional status indicators 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. Finally, 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 may exhibit significant seasonal shifts associated with changes in the availability of food or disease prevalence. In SHHS 2, weights and heights of all children under 5 years were measured using anthropometric equipment recommended by UNICEF (www.childinfo.org). Findings in this section are based on the results of these measurements. Table NU.1 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 the percentage of children who are overweight, which takes into account 5http://www.who.int/childgrowth/standards/second_set/technical_report_2.pdf 27 those children whose weight for height is above 2 standard deviations from the median of the reference population, and mean z-scores for all three anthropometric 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.1. 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.6 and DQ.7 in Appendix D. Overall, 18 percent of children did not have both their weights and heights measured (Table DQ.6). Nearly 19 and 24 percent of children did not have complete information on weights and heights, respectively. Four percent of children did not have their months of birth recorded. However, there was no case of children with neither year nor month missing. Table DQ.7 shows that due to incomplete dates of birth, implausible measurements, and missing weight and/or height, 13 percent of children have been excluded from the calculations of the weight-for-height indicator. About 28 percent of children under-five years in South Sudan are moderately and severely underweight and 12 percent are classified as severely underweight (Table NU.1). About a third of children (31 percent) are moderately and severely stunted or too short for their age and 17 are severely stunted; while 23 percent are moderately and severely wasted or too thin for their height and 10 percent are severely wasted. Children in Unity State are more likely to be underweight (46 percent), stunted (40 percent) and wasted (35 percent) than children in other states. However, the result for wasting is comparable to those from Jonglei (31 percent) and Warap (32 percent). The three states of Central, Western and Eastern Equatoria as well as the state of Western Bahr EL Ghazal record the lowest rates of wasting with 11, 12, 14 and 16 percent, respectively. Central and Western Equatoria have also the lowest rates for underweight with 17 and 18 percent, respectively. Those children whose mothers have secondary or higher education are the least likely to be underweight (15 percent), stunted (22 percent) and wasted (13 percent) compared to children of mothers with no education across the three nutritional status indicators. Boys appear to be slightly more likely to be underweight (30 percent), stunted (33 percent), and wasted (26 percent) than girls with 25 percent of underweight, 29 percent of stunted and 20 percent of wasted. Results of the age pattern suggest prevalence of higher proportion of undernourished children in the age-group 24-35 months for underweight and stunting compared to proportions of children from youngest age-group (Figure NU.1). This pattern is expected and is related to the age at which many children cease to be breastfed and are exposed to contamination in water, food and environment. The overweight seems not to be a major problem among children under five: only 6 percent of them were found to be overweight. These are the children whose weight for height is above 2 standard deviations from the median of the reference population (Table NU.1). 28 Ta bl e N U .1 : N ut rit io na l s ta tu s o f c hi ld re n Pe rc en ta ge o f c hi ld re n un de r a ge 5 b y nu tr iti on al st at us a cc or di ng to th re e an th ro po m et ric in di ce s: w ei gh t f or a ge , h ei gh t f or a ge , an d w ei gh t f or h ei gh t S ou th S ud an , 2 01 0 W ei gh t f or a ge (U nd er w ei gh t) He ig ht fo r a ge (S tu nt ed ) W ei gh t f or h ei gh t ( W as te d) % b el ow -2 sd [1 ] % b el ow -3 sd [2 ] M ea n Z- Sc or e (S D) N um be r o f ch ild re n % b el ow -2 sd [3 ] % b el ow -3 sd [4 ] M ea n Z- Sc or e (S D) N um be r o f ch ild re n % b el ow -2 s d [5 ] % b el ow -3 s d [6 ] % a bo ve +2 sd M ea n Z- Sc or e (S D) N um be r o f ch ild re n [1 ] M IC S in di ca to rs se e at ta ch ed ta bl e Se x M al e 30 .4 14 .3 -1 .3 34 21 33 .1 18 .3 -1 .0 30 95 25 .7 11 .7 6. 1 - 0 .9 30 23 Fe m al e 24 .5 9. 9 -1 .0 32 40 28 .9 15 .8 - 0 .9 29 52 19 .7 8. 1 5. 9 - 0 .7 29 02 Re si de nc e Ur ba n 22 .8 9. 1 -1 .0 16 31 29 .1 13 .8 - 0 .9 14 70 18 .1 7. 1 4. 4 - 0 .7 14 39 Ru ra l 29 .1 13 .2 -1 .2 50 29 31 .7 18 .1 -1 .0 45 77 24 .2 10 .8 6. 5 - 0 .8 44 86 St at e Up pe r N ile 24 .2 10 .2 -1 .0 82 4 27 .1 14 .3 - 0 .7 77 8 21 .5 8. 7 5. 7 - 0 .9 76 1 Jo ng le i 29 .3 14 .3 -1 .3 10 50 27 .8 17 .1 - 0 .7 91 4 31 .2 17 .4 7. 6 -1 .1 91 0 Un ity 46 .1 23 .0 -1 .8 36 6 40 .4 24 .1 -1 .3 35 8 35 .4 16 .5 3. 7 -1 .4 34 1 W ar ap 35 .0 13 .7 -1 .3 77 5 29 .4 17 .1 - 0 .8 74 1 31 .9 12 .4 3. 4 -1 .3 67 2 N or th er n Ba hr E l G ha za l 29 .7 12 .1 -1 .3 74 4 27 .6 14 .1 - 0 .8 69 4 26 .7 10 .4 2. 6 -1 .2 69 1 W es te rn B ah r E l G ha za l 22 .3 9. 7 -1 .0 29 5 26 .9 14 .1 - 0 .8 27 7 16 .4 5. 3 4. 0 - 0 .7 27 1 La ke s 29 .9 15 .3 -1 .1 45 9 35 .4 20 .3 - 0 .9 37 9 27 .9 15 .3 11 .6 - 0 .7 36 5 W es te rn E qu at or ia 18 .2 5. 9 - 0 .9 54 0 34 .5 19 .1 -1 .3 48 5 11 .8 4. 8 7. 5 - 0 .1 48 8 Ce nt ra l E qu at or ia 17 .0 6. 7 - 0 .7 85 1 31 .1 13 .3 -1 .1 74 4 11 .0 3. 4 9. 0 - 0 .1 72 9 Ea st er n Eq ua to ria 29 .2 14 .2 -1 .1 75 5 37 .2 21 .6 -1 .4 67 8 13 .7 4. 6 5. 2 - 0 .5 69 6 Ag e- gr ou p 0- 5 16 .7 6. 8 - 0 .1 54 3 11 .8 7. 1 0. 5 28 1 19 .6 8. 6 9. 6 - 0 .5 28 7 6- 11 24 .6 10 .4 -1 .0 69 3 17 .4 8. 6 - 0 .1 59 7 27 .1 11 .5 5. 8 -1 .0 58 9 12 -2 3 27 .1 11 .9 -1 .1 14 21 30 .9 15 .5 - 0 .8 13 06 22 .9 10 .1 5. 4 - 0 .8 12 98 24 -3 5 31 .7 15 .2 -1 .3 16 22 36 .7 20 .0 -1 .2 15 55 25 .0 11 .4 5. 3 - 0 .8 15 23 36 -4 7 27 .4 12 .4 -1 .3 14 50 34 .8 19 .7 -1 .3 14 24 19 .2 8. 0 7. 5 - 0 .7 13 72 48 -5 9 29 .8 11 .4 -1 .5 93 2 30 .8 18 .8 -1 .3 88 5 22 .2 9. 5 4. 8 - 0 .9 85 5 M ot he r’s e du ca tio n N on e 29 .0 13 .0 -1 .2 55 17 31 .7 17 .9 -1 .0 50 11 24 .1 10 .7 6. 0 -0 .9 49 04 Pr im ar y 22 .0 8. 7 -.9 91 1 29 .8 13 .7 -1 .0 82 6 17 .3 6. 5 7. 0 -0 .5 81 3 Se co nd ar y + 15 .0 6. 5 -.8 23 2 21 .9 11 .0 -0 .7 20 9 13 .0 4. 0 3. 1 -0 .5 20 7 M is si ng /D K * * * 1 * * * 1 * * * * 1 W ea lth in de x qu in til es Po or es t 32 .1 15 .0 -1 .4 13 36 31 .3 18 .2 -1 .0 12 02 28 .5 13 .8 4. 7 -1 .1 11 77 Se co nd 35 .0 15 .4 -1 .3 12 87 34 .1 20 .2 -1 .0 11 62 27 .9 13 .8 6. 3 -1 .0 11 25 M id dl e 26 .8 12 .5 -1 .1 12 87 32 .0 17 .0 -1 .0 11 76 21 .6 8. 6 6. 9 - 0 .7 11 49 Fo ur th 23 .9 10 .7 -1 .1 13 74 31 .7 18 .0 -1 .0 12 51 20 .3 7. 9 7. 1 - 0 .6 12 31 Ri ch es t 20 .5 7. 6 -.9 13 76 26 .5 12 .2 -0 .8 12 55 16 .1 5. 9 5. 1 - 0 .6 12 42 To ta l 27 .6 12 .2 -1 .1 66 60 31 .1 17 .1 -1 .0 60 48 22 .7 9. 9 6. 0 - 0 .8 59 25 29 Breastfeeding and Infant and Young Child Feeding 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 stop breastfeeding too soon and there are often pressures to switch to infant formula, which can contribute to growth faltering and micronutrient malnutrition and is unsafe if clean water is not readily available. WHO/UNICEF have the following feeding recommendations: • Exclusive breastfeeding for first six months • Continued breastfeeding for two years or more • Safe and age-appropriate complementary foods beginning at 6 months • Frequency of complementary feeding: 2 times per day for 6-8 month olds; 3 times per day for 9-11 month olds It is also recommended that breastfeeding be initiated within one hour of birth. The indicators related to recommended child feeding practices are as follows: • Early initiation of breastfeeding (within 1 hour of birth) • Exclusive breastfeeding rate (< 6 months) • Predominant breastfeeding (< 6 months) • Continued breastfeeding rate (at 1 year and at 2 years) • Duration of breastfeeding • Age-appropriate breastfeeding (0-23 months) Figure NU.1: Nutritional Status of Children Percentage of children under age 5 who are underweight, stunted and wasted, South Sudan, 2010 30 • Introduction of solid, semi-solid and soft foods (6-8 months) • Minimum meal frequency (6-23 months) • Milk feeding frequency for non-breastfeeding children (6-23 months) • Bottle feeding (0-23 months) Table NU.2 provides the proportion of children born in the last two years who were ever breastfed, those who were first breastfed within one hour and one day of birth. Overall, 93 percent of children were ever breastfed, less than half (48 percent) of babies are breastfed for the first time within one hour of birth and 75 percent of new-borns in South Sudan start breastfeeding within one day of birth. The proportions of ever breastfed range from 83 percent in Upper Nile to 98 percent in Central Equatoria. No significant variations noted across residence, mother’s educational levels and economic status. Initiation of breastfeeding varies among states. The proportion of infants that are breastfed within one hour of birth is higher (76 percent) in Warap, and the proportions are lower in Central Equatoria (27 percent) and Eastern Equatoria (31 percent). No variation across residence, while differences are observed across mother’s education with 50 percent for children whose mothers/caretakers have no education compared to 40 percent for children whose mothers/ caretakers have primary or higher education. An irregular pattern is observed in household wealth index quintiles for initial breastfeeding. For example, 41 percent of mothers in the fourth wealth quintile breastfed their infants within one hour of birth, compared to 57 percent of mothers from the poorest households, and 45 percent of mothers in the richest households. The highest percentages of infants who started breastfeeding within one day of birth are in Unity (87 percent), Warap (86 percent), Lakes (84 percent) and Northern Bahr El Ghazal (82 percent), while the lowest proportions are found in Western Equatoria (57 percent) and Eastern Equatoria (65 percent). No variation noted across residence. However, the percentages decrease with mother’s educational level, from 76 percent for children whose mothers/caretakers have no education to 67 percent for children whose mothers/caretakers have primary or higher education. An erratic pattern is also observed across the economic status. For example, 70 percent of mothers in the fourth wealth quintile breastfed their babies within one day of birth, compared to 80 percent of mothers/caretakers in the poorest and second wealth index quintiles, and 73 percent for mothers/caretakers in the richest wealth index quintiles. 31 In Table NU.3, breastfeeding status is based on the reports of mothers/caretakers of children’s consumption of food and fluids during the previous day or night prior to the interview. Exclusively breastfed refers to infants who received only breast milk (and vitamins, mineral supplements, or medicine). The table shows exclusive breastfeeding of infants during the first six months of life, as well as continued breastfeeding of children at 12-15 and 20-23 months of age. Approximately 45 percent of children aged 0-5 month are exclusively breastfed, a level considerably lower than recommended. Gender differentials as well as those pertained to residence are not significant. There are however some difference across levels of education (none and primary only) of the mothers/caretakers of the children; the proportion of children exclusively breastfed is slightly higher amongst children whose mothers/caretakers have no education (46 percent) compared to the proportion of the children whose parents with primary education educated (40 percent). Differentials across wealth groups show a decline in Table NU.2: Initial breastfeeding Percentage of last-born children in the 2 years preceding the survey who were ever breastfed, and percentage who were breastfed within one hour of birth and within one day of birth, South Sudan, 2010. Percentage who were ever breastfed1 Within one hour of birth2 Within one day of birth Number of last-born children in the two years preceding the survey Percentage who were first breastfed 1 MICS indicator 2.4 2 MICS indicator 2.5 *: Based on unweighted cases < 25 Region Upper Nile 83.4 37.9 70.7 371 Jonglei 89.1 52.7 74.7 409 Unity 95.3 61.5 86.9 194 Warap 93.3 75.6 86.4 421 Northern Bahr El Ghazal 94.0 58.9 82.1 284 Western Bahr El Ghazal 95.2 40.6 72.1 141 Lakes 91.8 64.5 84.4 234 Western Equatoria 94.1 38.0 57.4 258 Central Equatoria 98.1 26.7 71.4 461 Eastern Equatoria 94.6 31.0 64.6 332 Residence Urban 91.4 47.6 73.2 824 Rural 93.1 48.3 75.4 2,280 Mother's education None 92.2 50.2 76.1 2,482 Primary 95.3 39.6 70.5 507 Secondary + 90.8 39.8 67.1 113 Missing/DK * * * 1 Wealth index quintile Poorest 92.4 56.8 79.9 609 Second 94.8 54.8 79.6 582 Middle 93.4 44.9 72.5 584 Fourth 91.4 40.5 69.9 671 Richest 91.6 44.7 73.2 658 Total 92.7 48.1 74.9 3,104 32 breastfeeding as with economic status increased, from 51 percent (poorest) to 42 percent (richest). State variations are also noticeable with 56 percent recorded in Warap while Lakes has 33 percent. Western Bahr El Ghazal was not taken into consideration due to the small numbers. Similarly, the national proportion of children aged 0-5 month who were predominantly breastfed is 73 percent. The proportions are highest in Western Equatoria (83 percent) and Warap (81 percent); the lowest proportions are in Lakes and Northern Bahr El Ghazal States with 64 percents each. There are no significant differentials across wealth index, education, gender, and residence. The proportion of children aged 12-15 month who were continually breastfeed until their first birthday is 82 percent. There are no significant variations across gender and mother/caretaker educational level (none and primary only). There are nonetheless significant differences across the states; the proportions are higher in Warap (91 percent) and Lakes (81 percent) and the lowest is in Upper Nile (68 percent). A slight variation is also noted at residence level with 84 percent in rural areas compared to 75 in urban areas. Differentials across wealth groups show a decline as the economic status increases, from 89 percent (poorest) to 75 percent (richest). Table NU.3 shows that the proportion of Children aged 20-23 months breastfed is 38 percent. No significant variations observed for gender, residence and wealth index levels. Due to small numbers of children for some states, no conclusive comparative analysis can be done at state level. The mother’s/caretaker educational levels show a notable difference between no education (36 percent) and primary education (48 percent). 33 Ta bl e N U .3 : B re as tf ee di ng Pe rc en ta ge o f l iv in g ch ild re n ac co rd in g to b re as tfe ed in g st at us a t s el ec te d ag e gr ou ps , S ou th S ud an , 2 01 0 Pe rc en t e xc lu si ve ly br ea st fe d [1 ] Pe rc en t pr ed om in an tly br ea st fe d [2 ] N um be r o f c hi ld re n Pe rc en t b re as tfe d (C on tin ue d br ea st fe ed in g at 1 y ea r) [3 ] N um be r o f ch ild re n Pe rc en t b re as tfe d (C on tin ue d br ea st fe ed in g at 2 ye ar s) [4 ] N um be r o f ch ild re n Ch ild re n 20 -2 3 m on th s Ch ild re n 12 -1 5 m on th s Ch ild re n 0- 5 m on th s Se x M al e 45 .5 73 .5 43 2 83 .7 39 2 37 .6 26 3 Fe m al e 44 .7 72 .4 43 4 80 .9 40 2 38 .5 18 7 St at e Up pe r N ile 47 .3 71 .3 92 67 .8 89 31 .8 78 Jo ng le i 41 .4 73 .6 11 3 84 .6 13 5 (3 4. 0) 63 Un ity 51 .0 70 .8 61 85 .0 56 (3 3. 3) 25 W ar ap 56 .0 81 .2 11 9 91 .1 98 (3 8. 2) 39 N or th er n Ba hr E l G ha za l 37 .8 64 .4 76 84 .7 67 (2 3. 2) 33 W es te rn B ah r E l G ha za l 56 .7 74 .5 42 88 .5 38 (3 4. 1) 14 La ke s 32 .6 63 .5 67 81 .0 64 21 .2 39 W es te rn E qu at or ia 45 .7 82 .6 79 78 .8 54 (5 3. 9) 21 Ce nt ra l E qu at or ia 42 .3 71 .3 12 4 75 .9 10 6 54 .5 81 Ea st er n Eq ua to ria 42 .4 71 .6 93 88 .0 87 44 .2 57 Re si de nc e Ur ba n 43 .2 72 .5 22 6 75 .1 17 7 42 .9 10 9 Ru ra l 45 .8 73 .1 64 0 84 .3 61 6 36 .4 34 1 M ot he r's e du ca tio n N on e 45 .6 72 .9 69 8 83 .6 65 7 35 .8 37 1 Pr im ar y 39 .8 72 .4 14 0 80 .0 10 8 48 .4 63 Se co nd ar y + (5 9. 5) (7 6. 7) 28 (5 8. 8) 27 * 15 M is si ng /D K - - 0 * 1 - 0 W ea lth in de x qu in til es Po or es t 50 .9 74 .2 16 8 88 .7 17 0 39 .4 78 Se co nd 45 .9 72 .9 16 3 84 .7 15 9 37 .2 84 M id dl e 44 .3 77 .8 16 1 80 .2 15 3 37 .0 94 Fo ur th 43 .4 69 .4 18 9 81 .7 17 1 38 .9 98 Ri ch es t 41 .5 71 .1 18 5 74 .5 14 1 37 .5 95 T ot al 45 .1 72 .9 86 6 82 .3 79 4 38 .0 45 0 [1 ] M IC S in di ca to r 2 .6 [2 ] M IC S in di ca to r 2 .9 [3 ] M IC S in di ca to r 2 .7 [4 ] M IC S in di ca to r 2 .8 ( ) : B as ed o n 25 -4 9 un w ei gh te d ca se s (* ): Ba se d on u nw ei gh te d ca se s < 2 5 34 Table NU.4 presents indicators on the duration, in months, of breastfeeding practices among children aged 0-35 months. The main indicator is the median duration, in months, of any breastfeeding practice. Overall, the mean duration of breastfeeding for children aged 0-35 months who were reported to have had any breastfeeding is 17 months. However, the median duration for children reportedly to have been exclusively breastfed is relatively small, standing at 4 months. As for children reportedly to have had predominant breastfeeding practice, the median duration is 8 months. No significant variations noted across all background characteristics for the duration of any breastfeeding. The adequacy of infant feeding in children under 24 months is provided in Table NU.5. Different criteria of feeding are used depending on the age of the child. For infants aged 0-5 months, exclusive breastfeeding is considered as age-appropriate feeding, while infants aged 6-23 months are considered to be appropriately fed if they are receiving breast milk and solid, semi-solid or soft food. Table NU.5 presents the pattern of exclusive breast fed infants aged 0-5 months. The nation- wide percentage is 45, with no gender difference. There is however some difference across wealth index, as the pattern of exclusive breast feeding amongst those from the richest quintile (42 percent) is slightly lower than that of the poorest quintile (51 percent). Exclusive Table NU.4: Duration of breastfeeding Median duration of any breastfeeding, exclusive breastfeeding, and predominant breastfeeding among children age 0-35 months, South Sudan, 2010 Any breastfeeding [1] Exclusive breastfeeding Predominant breastfeeding Median duration (in months) of Number of children age 0-35 months [1] MICS indicator 2.10 Sex Male 18.3 2.0 6.0 2789 Female 18.8 2.0 5.3 2603 Residence Urban 18.9 1.8 4.7 1372 Rural 18.4 2.0 6.1 4021 Mother's education None 18.2 2.0 6.1 4441 Primary 19.8 1.9 4.6 764 Secondary + 20.5 3.2 4.2 186 Wealth index quintile Poorest 18.1 2.6 5.9 1059 Second 17.9 1.9 5.7 1040 Middle 19.3 2.0 7.7 1077 Fourth 17.6 2.0 5.1 1128 Richest 19.3 0.7 4.7 1089 Median 18.4 2.0 5.6 5393 Mean for all children (0-35 Months) 17.2 3.7 8.0 5393 35 breastfeeding of children is slightly higher among uneducated mothers (60 percent) than those who have primary education (46 percent). Across the States, exclusive breast feeding amongst infants aged 0-5 months is highest in Western Bahr el Ghazal and Warap States, 57 and 56 percents, respectively. The State with the lowest proportion of exclusive breasting of infants aged 0-5 is Lakes State, reported at 33 percent. Similarly, Table NU.5 also presents the proportion of children aged 6-23 months currently breastfeeding and receiving solid, semi-solid or soft foods. The national proportion for the indicator is 26 percent with the highest in Central Equatoria (40 percent) and lowest in Northern Bahr El Ghazal (17 percent) and Upper Nile (15 percent). There is no marked difference in feeding patterns between boys and girls. The urban-rural differentials are relatively small. There are however slight differences across wealth groups and the educational levels of the mothers/ caretakers of the children. The proportion of the appropriately fed infants aged 6-23 months is highest amongst the richest (30 percent) compared to the proportion of these children amongst the poorest (23 percent). This pattern is also markedly visible amongst infants of uneducated mothers/caretakers (23 percent) compared to that of children whose parents attained primary educational level (36 percent). Finally, Table NU.5 also presents the pattern of appropriately breastfed infants aged 0-23 months. Overall, the national proportion for the indicator is 30 percent. The proportions are highest in Central Equatoria (41 percent), Western Equatoria (39 percent) and Western Bahr El Ghazal (38 percent), and are lowest in Upper Nile and Northern Bahr El Ghazal (22 percent each). There are no significant differences across gender, residence, wealth groups, and education levels of mothers/caretakers. 36 [1] MICS indicator 2.6 [2] MICS indicator 2.4 ( ): Based on 25-49 unweighted cases (*):Based on 25-49 unweighted cases Table NU.5: Age-appropriate breastfeeding Percentage of children age 0-23 months who were appropriately breastfed during the previous day, South Sudan, 2010 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 Children age 0-5 months Children age 6-23 months Children age 0-23 months Sex Male 45.5 432 25.3 1333 30.3 1765 Female 44.7 434 25.6 1236 30.6 1670 State Upper Nile 47.3 92 15.2 335 22.1 427 Jonglei 41.4 113 23.0 344 27.6 457 Unity 51.0 61 21.7 152 30.1 213 Warap 56.0 119 20.4 352 29.4 470 Northern Bahr El Ghazal 37.8 76 17.4 234 22.4 310 Western Bahr El Ghazal (56.7) 42 30.2 108 37.6 150 Lakes 32.6 67 20.5 204 23.5 272 Western Equatoria 45.7 79 36.0 188 38.9 267 Central Equatoria 42.3 124 40.4 383 40.8 507 Eastern Equatoria 42.4 93 30.5 269 33.6 362 Residence Urban 43.2 226 29.3 686 32.8 912 Rural 45.8 640 24.1 1882 29.6 2522 Mother's education None 45.6 698 23.4 2068 29.0 2766 Primary 39.8 140 35.8 402 36.8 542 Secondary + (59.5) 28 27.5 97 34.7 125 Missing/DK - 0 * 1 * 1 Wealth index quintiles Poorest 50.9 168 22.8 506 29.8 674 Second 45.9 163 22.1 497 28.0 661 Middle 44.3 161 24.1 487 29.1 648 Fourth 43.4 189 27.4 544 31.5 732 Richest 41.5 185 30.4 535 33.2 720 Total 45.1 866 25.5 2569 30.4 3434 37 Appropriate complementary feeding of children from 6 months to two years of age is particularly important for growth and development and the prevention of undernutrition. Continued breastfeeding beyond six months should be accompanied by consumption of nutritionally adequate, safe and appropriate complementary foods that help meet nutritional requirements when breastmilk is no longer sufficient. This requires that for breastfed children, two or more meals of solid, semi-solid or soft foods are needed if they are six to eight months old, and three or more meals if they are aged 9-23 months of age. For children aged 6-23 months and older who are not breastfed, four or more meals of solid, semi-solid or soft foods or milk feeds are needed. Overall, 21 percent of infants aged 6-8 received solid, semi-solid, or soft foods (Table NU.6). Among currently breastfeeding infants the proportion is 22 percent. Table NU.6 shows a significant difference in the percentage of infants aged 6-8 months receiving solid, semi-solid or soft foods by area of residence. The urban percentage is nearly twice that of the rural one, 30 and 17 percent, respectively. There is no difference between male and female infants in terms of appropriate feeding. Table NU.7 presents the proportion of children aged 6-23 months who received semi-solid or soft foods the minimum number of times or more during the day or night preceding the interview by breastfeeding status. Only one in ten (11 percent) currently breastfeeding children aged 6-23 months were receiving solid, semi-solid and soft foods the minimum number of times. Across age groups, the proportion is relatively higher amongst age-groups 6-8 months and 18-23 months, but lower in age-groups 9-11 months and 12-17 months. The respective percentages for the earlier group are 15 and 16, respectively, while the proportions for the latter group stood at respectively 5 and 9. The States with relatively higher proportions are Western Equatoria (19 percent), Eastern Equatoria (17 percent), Central Equatoria (16 percent) and Western Bahr El Ghazal (15 percent). The Table NU.6: Introduction of solid, semi-solid or soft food Percentage of infants age 6-8 months who received solid, semi-solid or soft foods during the previous day, South Sudan, 2010 [1] MICS indicator 2.12 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 Sex Male 20.1 194 34.3 6 20.0 217 Female 23.5 203 12.8 7 21.7 227 Residence Urban 34.3 120 0 3 30.3 138 Rural 16.5 278 31.8 9 16.6 3.7 Total 21.9 398 23.0 13 20.9 444 38 remaining States have proportions in the range 4 – 10 percent. Slight difference is noted across residence: 15 percent for urban compared to 9 percent for rural. Differentials across wealth index quintiles and education are also significant. The proportion amongst children whose mothers/caretakers have secondary education or higher (22 percent) is markedly higher than that of children of uneducated mothers (9 percent). Besides, the proportion amongst children from richest quintile (16 percent) doubles that of children from the poorest households (8 percent). Among no breastfeeding children aged 6-23 months, 14 percent received solid, semi-solid and soft foods or milk feeds 4 times or more. While there is no gender difference, the results show a marked difference between urban and rural areas: 23 and 11 percent, respectively. There are also some variations across wealth quintiles. The proportion of children from the richest households is 28 percent compared to 8 percent for the poorest households. Finally, Table NU.7 also presents the proportion of all children aged 6-23 months who received minimum meal. Overall, 12 percent of children aged 6-23 months received minimum meal. Across age- groups, the proportions are relatively higher in age-groups 6-8 months (14 percent), 18-23 months (13 percent) and 12-17 months (12 percent). The age-group with the lowest proportion is the age-group 9-11 months, with only 7 percent. Children aged 6-23 months and living in urban areas are more (17 percent) likely to receive minimum meal than the children from rural areas with 10 percent. Minimal meal frequency increases with the educational level of mothers/caretakers as well as with the household wealth. 39 Table NU.7: Minimum meal frequency Percentage of children age 6-23 months who received solid, semi-solid, or soft foods (and milk feeds for non-breastfeeding children) the minimum number of times or more during the previous day, according to breastfeeding status, South Sudan, 2010 Currently breastfeeding Currently not breastfeeding All Percent receiving solid, semi-solid and soft foods the minimum number of times Number of children age 6-23 months Percent receiving at least 2 milk feeds [1] Percent receiving solid, semi-solid and soft foods or milk feeds 4 times or more Number of children age 6-23 months Percent with minimum meal frequency [2] Number of children age 6-23 months [1] MICS indicator 2.15 [2] MICS indicator 2.13 ( ): Based on 25-49 unweighted cases (*): Based on unweighted cases < 25 Sex Male 9.5 934 17.8 12.5 399 10.4 1333 Female 11.6 899 18.0 15.7 336 12.7 1236 Age 6-8 months 14.7 398 19.2 (9.8) 47 14.2 444 9-11 months 5.4 381 (22.9) (17.2) 39 6.5 420 12-17 months 9.0 767 24.5 20.0 229 11.5 995 18-23 months 15.8 288 13.7 10.8 421 12.9 709 State Upper Nile 10.1 195 31.5 23.3 141 15.6 335 Jonglei 9.8 245 12.9 10.0 99 9.8 344 Unity 3.9 108 17.9 17.9 44 7.9 152 Warap 4.3 269 7.7 6.2 83 4.7 352 Northern Bahr El Ghazal 3.5 172 15.0 11.0 62 5.4 234 Western Bahr El Ghazal 14.5 85 17.0 17.0 23 15.0 108 Lakes 8.4 131 15.0 8.8 73 8.5 204 Western Equatoria 19.1 142 11.3 9.8 46 16.8 188 Central Equatoria 15.6 280 18.2 15.2 103 15.5 383 Eastern Equatoria 16.5 206 19.9 15.7 63 16.3 269 Residence Urban 14.5 479 26.9 22.7 208 17.0 686 Rural 9.2 1355 14.4 10.5 528 9.5 1882 Mother's education None 9.4 1475 15.3 11.4 593 9.9 2068 Primary 13.9 293 30.8 25.8 109 17.2 402 Secondary + 22.3 64 22.0 (21.0) 33 21.9 97 Missing/DK * 1 0 0 0 * 1 Wealth index quintiles Poorest 7.7 377 12.1 8.1 128 7.8 506 Second 5.9 369 14.0 10.0 129 7.0 497 Middle 8.5 348 14.3 10.5 139 9.1 487 Fourth 14.9 376 11.7 10.4 167 13.5 544 Richest 15.6 363 34.3 27.6 172 19.5 535 Total 10.5 1833 17.9 14.0 735 11.5 2569 40 The continued practice of bottle-feeding is a concern because of the possible contamination due to unsafe water and lack of hygiene in preparation. Table NU.8 shows that bottle-feeding is not prevalent in South Sudan. Only 6 percent of children aged 0-23 months are fed using a bottle with a nipple. Table NU.8: Bottle feeding Percentage of children age 0-23 months who were fed with a bottle with a nipple during the previous day, South Sudan, 2010 Percentage of children age 0-23 months fed with a bottle with a nipple [1] Number of children age 0-23 months: [1] MICS indicator 2.11 (*): Based on unweighted cases < 25 Sex Male 5.8 1765 Female 5.1 1670 Age 0-5 months 5.7 866 6-11 months 6.9 864 12-23 months 4.6 1704 State Upper Nile 5.8 427 Jonglei 8.2 457 Unity 4.3 213 Warap 3.2 470 Northern Bahr El Ghazal 3.6 310 Western Bahr El Ghazal 5.3 150 Lakes 4.8 272 Western Equatoria 6.3 267 Central Equatoria 8.0 507 Eastern Equatoria 3.1 362 Residence Urban 8.5 912 Rural 4.4 2522 Mother's education None 4.5 2766 Primary 9.4 542 Secondary + 9.8 125 Missing/DK * 1 Wealth index quintiles Poorest 1.5 674 Second 4.6 661 Middle 5.1 648 Fourth 5.4 732 Richest 10.3 720 Total 5.5 3434 41 The prevalence of bottle feeding practice amongst urban dwellers (9 percent) is more than double that in the rural areas (4 percent). There is however little or no difference in the practice across gender, as well as across age-groups 0-5, 6-11 and 12-23 months. The States with highest percentages of bottle feeding practice are Jonglei and Central Equatoria, with 8 percent each; while those with relatively lower proportions are Eastern Equatoria and Warap States with 3 percent each. Children whose mothers/caretakers have secondary and higher education are more (10 percent) likely to be fed with nipple than those children whose mothers have no education (5 percent). Similarly, children from the richest households are more (10 percent) likely to be fed with nipple than those from the poorest households with only 2 percent. While there is no gender difference, bottle feeding is more common in urban areas, among educated mothers/caretakers, in richest households and in the states of Jonglei, and Central Equatoria. 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). Currently there is no national salt iodization program in South Sudan; most of the salt consumed in South Sudan is imported from the neighbouring countries mainly Uganda, Kenya and Sudan. Efforts are underway to develop the National Salt Legislation, and to as well institute a monitoring system at various levels, including the border entry points. The results in Table NU.9 show a low coverage of salt testing. This may introduce a bias and therefore the results should be interpreted with caution. In 78 percent of households, salt used for cooking was tested for iodine content by using salt test kits and testing for the presence of potassium iodide or potassium iodate content or both. In 45 percent of households where the test was carried out, salt was found to contain 15 parts per million (ppm) or more of iodine. Use of adequately iodized salt was lowest in Northern Bahr El Ghazal (13 percent), Unity (14 percent) and Upper Nile (15 percent); and highest in Central Equatoria (83 percent) and Western Equatoria (81 percent). In fact, there is a huge gap (Figure NU.2) between on one hand the three states of Equatoria and the state of Lakes, and on other hand the remaining 6 states. More than one in two (57 percent) of urban households were found to be using adequately iodized salt, compared to 42 percent in rural areas. As shown in Table NU.9 and Figure NU.2, there is a significant difference across the economic status in terms of iodized salt consumption. About 61 percent of richest households use iodized salt compared to 37 percent in the poorest households. 42 Table NU.9: Iodized salt consumption Percent distribution of households by consumption of iodized salt, South Sudan, 2010 Percent of households in which salt was tested Number of households No salt Not iodized 0 PPM >0 and <15 PPM 15+ PPM [1] Total Number of households in which salt was tested or with no salt Percent of households with [1] MICS indicator 2.16 Figure NU.2: Percentage of households consuming adequately iodized salt, South Sudan, 2010 Salt Test Result Residence Upper Nile 74.8 998 20.0 52.4 13.1 14.6 100.0 933 Jonglei 59.0 1432 32.9 13.7 18.0 35.4 100.0 1259 Unity 56.9 608 28.7 44.2 13.1 14.0 100.0 486 Warap 70.3 1205 20.5 36.4 20.1 23.0 100.0 1066 Northern Bahr El Ghazal 94.3 930 4.9 57.8 24.4 12.9 100.0 923 Western Bahr El Ghazal 89.8 387 7.1 45.7 12.4 34.7 100.0 374 Lakes 83.1 676 11.0 1.9 25.5 61.6 100.0 632 Western Equatoria 92.7 770 2.5 7.9 8.3 81.3 100.0 732 Central Equatoria 87.9 1249 10.3 1.1 5.6 83.0 100.0 1224 Eastern Equatoria 83.5 1114 14.8 2.6 9.0 73.6 100.0 1092 Residence Urban 87.0 2161 6.6 23.7 12.4 57.3 100.0 2015 Rural 75.4 7208 19.0 23.9 15.4 41.7 100.0 6705 Wealth index quintiles Poorest 70.0 1879 23.1 25.1 14.7 37.0 100.0 1712 Second 72.2 1995 22.1 25.3 15.0 37.7 100.0 1851 Middle 78.0 2004 17.6 25.4 16.8 40.3 100.0 1896 Fourth 83.2 1913 10.6 20.9 15.5 53.0 100.0 1779 Richest 88.9 1578 5.3 22.2 11.0 61.4 100.0 1483 Total 78.1 9369 16.1 23.9 14.7 45.3 100.0 8720 43 Children’s Vitamin A Supplementation Vitamin A is essential for eye health and proper functioning of the immune system. It is found in foods such as milk, liver, eggs, red and orange fruits, red palm oil and green leafy vegetables, although the amount of vitamin A readily available to the body from these sources varies widely. In developing areas of the world, where vitamin A is largely consumed in the form of fruits and vegetables, daily per capita intake is often insufficient to meet dietary requirements. Inadequate intakes are further compromised by increased requirements for the vitamin as children grow or during periods of illness, as well as increased losses during common childhood infections. As a result, vitamin A deficiency is quite prevalent in the developing world and particularly in countries with the highest burden of under-five deaths. The 1990 World Summit for Children set the goal of virtual elimination of vitamin A deficiency and its consequences, including blindness, by the year 2000. This goal was also endorsed at the Policy Conference on Ending Hidden Hunger in 1991, the 1992 International Conference on Nutrition, and the UN General Assembly’s Special Session on Children in 2002. The critical role of vitamin A for child health and immune function also makes control of deficiency a primary component of child survival efforts, and therefore critical to the achievement of the fourth Millennium Development Goal: a two-thirds reduction in under-five mortality by the year 2015. For countries with vitamin A deficiency problems, current international recommendations call for high-dose vitamin A supplementation every four to six months, targeted to all children between the ages of six to 59 months living in affected areas. Providing young children with two high-dose vitamin A capsules a year is a safe, cost-effective, efficient strategy for eliminating vitamin A deficiency and improving child survival. Giving vitamin A to new mothers who are breastfeeding helps protect their children during the first months of life and helps to replenish the mother’s stores of vitamin A, which are depleted during pregnancy and lactation. For countries with vitamin A supplementation programs, the definition of the indicator is the percent of children 6-59 months of age receiving at least one high dose vitamin A supplement in the last six months. Based on UNICEF/WHO guidelines, the Ministry of Health in South Sudan recommends that children aged 6-11 months be given a Vitamin A capsules (100,000 IU), and children aged 12- 59 months given a one high dose of vitamin A capsule (200,000 IU) every 6 months. In some parts of the country, Vitamin A capsules are linked to immunization services (mainly during polio immunization days) and are given when the child has contact with these services after six months of age. It is also recommended that mothers take a Vitamin A supplement within eight weeks of giving birth due to increased Vitamin A requirements during pregnancy and lactation. Within the six months prior to SHHS2, 4 percent of children aged 6-59 months received a high dose Vitamin A supplement (Table NU.10). Vitamin A supplementation coverage is lower in Warap, Jonglei and Unity than in other States. Overall, percentages for most of the States are below 5 percent, except for Jonglei (8 percent) and Western Bahr El Ghazal (6 percent). Urban areas record 6 percent compared to 3 percent in rural areas. Besides, there is also marked difference across wealth index quintiles, as the proportion of children aged 6-59 months who received a high dose Vitamin A supplement in the poorest households (2 percent) is markedly lower than that in the richest households (8 percent). The age pattern of Vitamin A supplementation shows that supplementation in the last six months rises from 2 percent among children aged 6-11 months to 16 percent among children 44 aged 12-23 months, and then declines sharply with age to 0 percent among the oldest children. Mother’s level of education is also related to the likelihood of Vitamin A supplementation. The percentage receiving a supplement in the last six months increases from 3 percent among children whose mothers/caretakers have no education to 8 percent for children whose mothers/ caretakers have primary education, and to 10 percent among children whose mothers/caretakers have secondary or higher education. Table NU.10: 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, South Sudan, 2010 Percentage of children who received Vitamin A during the last 6 months [1] Number of children age 6-59 months [1] MICS indicator 2.17 (*): Based on unweighted cases < 25 Results are based on mother's report Sex Male 4.0 3829 Female 3.9 3643 State Upper Nile 7.7 874 Jonglei 2.1 1141 Unity 2.1 574 Warap 1.1 1057 Northern Bahr El Ghazal 3.0 744 Western Bahr El Ghazal 5.8 284 Lakes 2.9 551 Western Equatoria 4.9 565 Central Equatoria 6.8 913 Eastern Equatoria 4.5 769 Residence Urban 5.9 1816 Rural 3.3 5656 Age 6-11 2.3 864 12-23 15.9 1704 24-35 0.2 1958 36-47 0.0 1789 48-59 0.0 1156 Mother's education None 3.0 6295 Primary 8.4 940 Secondary + 9.9 234 Missing/DK * 3 Wealth index quintiles Poorest 2.3 1544 Second 2.6 1472 Middle 3.0 1492 Fourth 4.4 1564 Richest 7.6 1400 Total 3.9 7472 45 VI. Child Health Vaccinations The Millennium Development Goal (MDG) 4 is to reduce child mortality by two thirds between 1990 and 2015. Immunization plays a key part in this goal. Immunizations have saved the lives of millions of children in the three decades since the launch of the Expanded Programme on Immunization (EPI) in 1974. Worldwide there are still 27 million children overlooked by routine immunization and as a result, vaccine-preventable diseases cause more than 2 million deaths every year. A World Fit for Children goal is to ensure full immunization of children under one year of age at 90 percent nationally, with at least 80 percent coverage in every district or equivalent administrative unit. According to UNICEF and WHO guidelines, a child should receive a BCG vaccination to protect against tuberculosis, three doses of DPT to protect against diphtheria, pertussis, and tetanus, three doses of polio vaccine, and a measles vaccination by the age of 12 months. Table CH.1: Vaccinations in first year of life Percentage of children age 12-23 months immunized against childhood diseases at any time before the survey and before the first birthday, South Sudan, 2010 Vaccinated at any time before the survey according to: Vaccination card Vaccinated at any time before the survey according to: Mother's report Vaccinated at any time before the survey according to: Either Vaccinated by 12 months of age BCG [1] 8.7 25.7 34.4 31.4 Polio 0 6.1 12.7 18.7 18.4 Polio 1 7.6 28.8 36.4 34.7 Polio 2 7.5 15.3 22.8 20.9 Polio 3 [2] 5.8 9.0 14.8 12.7 DPT/HepB/INFL1 7.2 20.9 28.1 24.9 DPT/HepB/INFL2 6.5 15.8 22.3 20.4 DPT/HepB/INFL3 [3] 5.4 9.7 15.1 13.1 Measles [4] 5.8 20.5 26.3 20.4 All vaccinations 4.3 2.0 6.3 6.0 No vaccinations 0.1 45.9 45.9 45.9 Number of children age 1704 1704 1704 1704 12-23 months [1] MICS indicator 3.1 [2] MICS indicator 3.2 [3] MICS indicator 3.3 [4] MICS indicator 3.4; MDG indicator 4.3 46 The vaccination schedule followed by the South Sudan National Immunization Programme provides only BCG and DPT (against Diphtheria, tetanus and whooping cough). Oral polio vaccine and measles are used for routine infant immunization schedule. Taking into consideration this vaccination schedule, the estimates for full immunization coverage from the South Sudan Household Health Survey are based on children aged 12-23 months. Information on vaccination coverage was collected for all children under five 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 SHHS II 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 and DPT, how many doses were received. The final vaccination coverage estimates are based on both information obtained from the vaccination card and the mother’s report of vaccinations received by the child. The percentage of children aged 12 to 23 months who have received each of the specific vaccinations by source of information (vaccination card and mother’s recall) is shown in Table CH.1. The denominator for the table is the number of children aged 12-23 months so that only children who are old enough to be fully vaccinated are counted. In the first three columns of the table, the numerator includes all children who were vaccinated at any time before the survey according to the vaccination card or the mother’s report. In the last column, only those children who were vaccinated before their first birthday, as recommended, are included. For children without vaccination cards, the proportion of vaccinations given before the first birthday is assumed to be the same as for children with vaccination cards. Approximately 31 percent of children aged 12-23 months received a BCG vaccination by the age of 12 months and the first dose of DPT was given to 25 percent. The percentage declines for subsequent doses of DPT to 20 percent for the second dose and the 13 percent for the third dose (Table CH.1 and Figure CH.1). Similarly, 35 percent of children received Polio 1 by age 12 months, and this declines to 13 percent for the third dose. The coverage for measles vaccine by 12 months is 20 percent. The proportion of children who received all vaccinations is very low at 6 percent, while those who didn’t receive any vaccinations is 46 percent 47 Table CH.2 presents vaccination coverage estimates among children aged 12-23 months by background characteristics. The results 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 and mothers’/caretakers’ reports. The proportion of vaccination cards that have been seen by the interviewer is only 10 percent of children. The proportion of children fully immunized for all antigens is 6 percent. There is no significant difference in percentages of BCG vaccination coverage amongst male and female children aged 12-23 months; on average this proportion stands at 35 percent. Polio coverage was 36, 23 and 15 percent for the first, second and third doses, respectively. In like manner there are no notable differences across gender in the percentages pertaining to the coverage of measles and DPT. In addition, measles vaccination coverage was documented as 26 percent, although only 6 percent had their cards verified (Table CH.1). There are differences in coverage of vaccination across States. The State with the highest percentage of children aged 12-23 months who received a BCG vaccination by the age of 12 months is Central Equatoria (58 percent). The lowest proportion of this vaccination was in Warap State, having BCG vaccination of only 16 percent. The coverage of Polio 3 vaccination is also highest in Central Equatoria, but lowest across Lakes, Warap, Unity, Northern Bahr El Ghazal and Jonglei States (6-7 percent). Similarly, the coverage for measles vaccine is equally highest in Central Equatoria (45 percent) and lowest in Warap (11 percent). Accordingly, the percentage of children fully immunized was highest in Central Equatoria (19 percent) and lowest across Northern Bahr El Ghazal, Jonglei and Warap states (below 2 percent in all three states). There are urban-rural differences in vaccination coverage. Children residing in urban areas are more likely to be fully immunized (10 percent) compared with children in rural areas (5 percent). BCG coverage in urban areas (45 percent) is markedly higher than that in the rural areas (31 percent). Similarly, coverage of Polio 3 and DPT 3 in urban areas is twice that of rural areas. Measles coverage in urban areas is 36 percent compared to 23 percent in rural areas. Figure CH.1: Percentage of children aged 12-23 months who received the recommended vaccinations by 12 months, South Sudan, 2010 48 Ta bl e CH .2 : V ac ci na tio ns b y ba ck gr ou nd c ha ra ct er is tic s Pe rc en ta ge o f c hi ld re n ag e 12 -2 3 m on th s c ur re nt ly v ac ci na te d ag ai ns t c hi ld ho od d is ea se s, S ou th S ud an , 2 01 0 Pe rc en ta ge w ith va cc in at io n ca rd se en BC G Po lio a t bi rt h Po lio 1 Po lio 2 Po lio 3 DP T 1 DP T 2 DP T 3 M ea sl es N on e Al l Pe rc en ta ge o f c hi ld re n w ho re ce iv ed N um be r o f ch ild re n ag e 12 -2 3 m on th s (* ): Fi gu re s b as ed o n un w ei gh te d ca se s < 2 5 Se x M al e 33 .7 17 .7 34 .6 21 .9 13 .6 27 .2 21 .9 14 .6 26 .3 47 .6 5. 6 9. 5 89 6 Fe m al e 35 .2 19 .9 38 .4 23 .7 16 .1 29 .1 22 .8 15 .6 26 .3 44 .1 7. 0 10 .4 80 8 St at e Up pe r N ile 42 .4 21 .3 42 .8 35 .0 21 .0 29 .7 20 .7 14 .9 32 .8 41 .6 6. 7 8. 6 24 2 Jo ng le i 27 .3 11 .8 32 .4 15 .0 7. 1 22 .0 18 .4 14 .9 22 .3 53 .5 1. 8 2. 3 24 8 Un ity 23 .4 12 .0 22 .5 11 .5 7. 0 17 .3 13 .9 9. 7 19 .8 61 .7 3. 5 7. 8 10 7 W ar ap 16 .4 6. 9 24 .1 9. 8 5. 9 9. 3 4. 9 3. 2 11 .1 62 .8 1. 4 4. 2 20 8 N or th er n Ba hr E l G ha za l 20 .9 13 .0 30 .7 9. 9 6. 1 13 .9 6. 9 2. 5 16 .4 55 .8 1. 3 4. 3 13 6 W es te rn B ah r E l G ha za l 38 .4 23 .1 41 .6 31 .5 18 .6 33 .7 26 .4 19 .6 33 .3 41 .1 7. 5 12 .0 72 La ke s 23 .3 13 .9 25 .5 12 .0 7. 3 20 .6 16 .0 8. 1 17 .1 58 .3 2. 9 5. 6 13 2 W es te rn E qu at or ia 41 .2 27 .1 42 .9 29 .0 16 .9 31 .9 27 .6 18 .1 32 .6 41 .0 8. 7 9. 3 11 8 Ce nt ra l E qu at or ia 58 .0 28 .9 55 .6 43 .3 33 .1 56 .2 47 .8 31 .9 45 .1 14 .8 19 .2 26 .0 25 8 Ea st er n Eq ua to ria 39 .5 28 .6 34 .4 17 .2 13 .2 33 .2 29 .0 19 .2 24 .7 46 .0 5. 5 13 .9 18 2 Re si de nc e Ur ba n 45 .2 22 .5 45 .8 32 .4 23 .8 36 .5 28 .6 23 .3 35 .5 33 .9 10 .1 13 .9 43 1 Ru ra l 30 .8 17 .5 33 .3 19 .6 11 .8 25 .4 20 .3 12 .4 23 .2 50 .1 5. 1 8. 6 12 73 M ot he r's e du ca tio n N on e 28 .6 15 .3 31 .9 18 .4 11 .3 22 .7 18 .0 12 .1 21 .1 51 .7 4. 5 7. 8 13 74 Pr im ar y 57 .9 33 .8 54 .9 40 .2 28 .5 50 .1 40 .0 27 .2 46 .8 24 .7 13 .6 17 .8 26 0 Se co nd ar y + 61 .6 30 .0 58 .1 47 .7 34 .5 53 .2 43 .3 30 .8 55 .0 21 .9 15 .7 22 .1 69 M is si ng /D K * * * * * * * * * * * * 1 W ea lth in de x qu in til es Po or es t 20 .4 10 .3 22 .0 11 .2 7. 9 15 .4 12 .3 6. 3 16 .5 64 .1 2. 3 3. 0 33 2 Se co nd 23 .9 15 .1 29 .3 14 .2 9. 0 19 .3 13 .6 10 .0 16 .6 56 .3 3. 2 5. 7 31 0 M id dl e 32 .7 16 .8 35 .8 19 .3 9. 7 27 .2 20 .8 13 .7 21 .6 46 .5 5. 1 9. 7 33 0 Fo ur th 34 .6 22 .1 38 .2 24 .0 14 .3 28 .3 22 .6 14 .5 30 .1 43 .1 6. 2 9. 7 37 9 Ri ch es t 58 .5 28 .2 55 .2 44 .5 32 .5 49 .1 41 .1 30 .3 44 .5 24 .4 14 .6 20 .6 35 4 To ta l 34 .4 18 .7 36 .4 22 .8 14 .8 28 .1 22 .3 15 .1 26 .3 45 .9 6. 3 9. 9 17 04 49 Vaccination levels are associated with the level of education of the mothers/caretakers of the children. Children of uneducated mothers/caretakers are relatively less likely to be fully immunized (5 percent) than those whose mothers/caretakers attained secondary or higher level education (16 percent). This is also true for BCG, Polio 3, DPT 3 and measles. Vaccination coverage is also associated with the economic status of the households. Children aged 12-23 months from richest households are more (15 percent) likely to be fully vaccinated than those from poorest households (2 percent). And this pattern is particularly observed in the vaccination coverage for BCG, Polio 3, DPT 3 and measles. Neonatal Tetanus Protection One of the MDGs is to reduce by three quarters the maternal mortality ratio, with one strategy to eliminate maternal tetanus. In addition, another goal is to reduce the incidence of neonatal tetanus to less than 1 case of neonatal tetanus per 1000 live births in every district. A World Fit for Children goal is to eliminate maternal and neonatal tetanus by 2005. The strategy for preventing maternal and neonatal tetanus is to assure all pregnant women receive at least two doses of tetanus toxoid vaccine. If a woman has not received at least two doses of tetanus toxoid during a particular pregnancy, she (and her newborn) are also considered to be protected against tetanus if the woman: • Received at least two doses of tetanus toxoid vaccine, the last within the previous 3 years; • Received at least 3 doses, the last within the previous 5 years; • Received at least 4 doses, the last within the previous 10 years; • Received 5 or more doses anytime during her life. To assess the status of tetanus vaccination coverage, women who gave birth during the two years before the survey were asked if they had received tetanus toxoid injections during the pregnancy for their most recent birth, and if so, how many. Women who did not receive two or more tetanus toxoid vaccinations during this pregnancy were then asked about tetanus toxoid vaccinations they may have received prior to this pregnancy. Interviewers also asked women to present their vaccination card, on which dates of tetanus toxoid are recorded and referred to information from the cards when available. Table CH.3 shows the protection status from tetanus of women who have had a live birth within the last 2 years. Figure CH.2 shows the protection of women against neonatal tetanus by major background characteristics. In South Sudan, 37 percent of women aged 15-49 who had a live birth in the two years preceding the study were protected against neonatal tetanus in 2010. Women residing in urban areas (51 percent) are more likely to be protected than their rural counterparts (32 percent). Neonatal tetanus Protection varies across States, with Central Equatoria State posting the highest rates (71 percent) and Warap State the lowest (17 percent). Neonatal tetanus protection also varies with mother’s education and economic status. Only 31 percent of uneducated mothers were vaccinated, compared to 68 percent of mothers who have secondary education or higher. Sixty percent of mothers from the richest households were protected against tetanus compared to 20 percent from the poorest households. 50 Ta bl e CH .3 : N eo na ta l t et an us p ro te ct io n Pe rc en ta ge o f w om en a ge 1 5- 49 y ea rs w ith a li ve b irt h in th e la st 2 y ea rs p ro te ct ed a ga in st n eo na ta l t et an us , S ou th S ud an , 2 01 0 Pe rc en ta ge o f w om en w ho re ce iv ed a t l ea st 2 do se s d ur in g la st pr eg na nc y Pe rc en ta ge o f w om en w ho d id n ot re ce iv e tw o or m or e do se s d ur in g la st p re gn an cy b ut re ce iv ed : 2 do se s, th e la st w ith in p rio r 3 y ea rs 3 do se s, th e la st w ith in p rio r 5 y ea rs 4 do se s, th e la st w ith in p rio r 1 0 ye ar s 5 or m or e do se s du rin g lif et im e Pr ot ec te d ag ai ns t te ta nu s [ 1] N um be r o f w om en w ith a li ve b irt h in th e la st 2 y ea rs [1 ] M IC S in di ca to r 3 .7 (* ): Fi gu re s b as ed o n un w ei gh te d ca se s < 2 5 Re si de nc e Ur ba n 38 .9 9. 8 1. 0 0. 9 0. 0 50 .6 91 3 Ru ra l 24 .4 6. 4 0. 6 0. 5 0. 2 32 .1 25 66 St at e Up pe r N ile 22 .9 9. 6 1. 3 0. 2 0. 0 34 .0 43 6 Jo ng le i 18 .4 7. 6 0. 3 0. 0 0. 0 26 .3 45 9 Un ity 22 .7 5. 0 0. 7 0. 3 0. 0 28 .6 21 5 W ar ap 14 .3 3. 1 0. 0 0. 0 0. 0 17 .4 48 5 N or th er n Ba hr E l G ha za l 22 .8 5. 5 0. 3 0. 0 0. 0 28 .6 29 9 W es te rn B ah r E l G ha za l 35 .8 6. 5 0. 3 0. 5 0. 3 43 .5 13 9 La ke s 27 .2 4. 6 0. 3 0. 0 0. 0 32 .1 27 5 W es te rn E qu at or ia 39 .6 7. 3 0. 4 0. 4 0. 0 47 .7 27 0 Ce nt ra l E qu at or ia 50 .4 14 .2 2. 0 3. 3 0. 9 70 .7 50 3 Ea st er n Eq ua to ria 31 .8 5. 4 0. 9 0. 0 0. 0 38 .1 39 8 Ed uc at io n N on e 22 .8 6. 7 0. 6 0. 4 0. 1 30 .6 27 78 Pr im ar y 49 .6 8. 4 0. 9 1. 5 0. 3 60 .7 56 9 Se co nd ar y + 49 .3 16 .2 2. 5 0. 3 0. 0 68 .2 12 2 Ad ul t e du ca tio n/ Kh al w a/ Su nd ay e du ca tio n * * * * * * 10 W ea lth in de x qu in til es Po or es t 14 .2 4. 6 0. 3 0. 1 0. 2 19 .5 66 6 Se co nd 24 .2 4. 1 0. 4 0. 0 0. 1 28 .8 67 9 M id dl e 24 .0 7. 8 0. 6 0. 2 0. 0 32 .5 68 6 Fo ur th 32 .7 8. 4 .8 0. 0 0. 0 41 .9 72 6 Ri ch es t 44 .4 11 .1 1. 4 2. 5 0. 4 59 .9 72 2 To ta l 28 .2 7. 3 0. 7 0. 6 0. 1 36 .9 34 79 51 Oral Rehydration Treatment Diarrhoea is the second 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. Preventing dehydration and malnutrition by increasing fluid intake and continuing to feed the child are also important strategies for managing diarrhoea. The goals are to: 1) reduce by one half death due to diarrhoea among children under five by 2010 compared to 2000 (A World Fit for Children); and 2) reduce by two thirds the mortality rate among children under five by 2015 compared to 1990 (Millennium Development Goals). In addition, the World Fit for Children calls for a reduction in the incidence of diarrhoea by 25 percent. Figure CH.2: Percentage of women with a live birth in the last 2 years who are protected against neonatal tetanus South Sudan, 2010 State Area of Residence Mother’s Education 52 In SHHS 2, prevalence of diarrhoea was estimated by asking mothers or caretakers 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 to drink and eat during the episode and whether this was more or less than the child usually drinks and eats. Overall, 34 percent of under-five children had diarrhoea in the two weeks preceding the survey (Table CH.4). Of these, 49 percent received the ORS or any recommended homemade fluid. The prevalence of diarrhoea in the two weeks preceding the survey ranges from 30 percent in Lakes to 44 percent in Eastern Equatoria. There are no significant differences across gender, residence, education and wealth index quintiles. The peak of diarrhoea prevalence occurs in the weaning period, among children age 12-23 months. Table CH.4 also shows the percentage of children receiving various types of recommended liquids during the episode of diarrhoea. Since children may have been given more than one type of liquid, the percentages do not necessarily add to 100. About 39 percent received fluids from ORS packets or pre-packaged ORS fluids and 25 percent received recommended homemade fluids. In terms of ORS or any recommended homemade fluid (Table CH.4 and Figure CH.3), variations are noted across states with the highest proportion (73 percent) in Central Equatoria and the lowest are in in Lakes (33 percent) and Warap (35 percent). Slight differences are observed across gender and residence. However, for education and economic status, the differences are significant. For example, 77 percent of children whose mothers have secondary and higher education received ORS or any recommended homemade fluid, compared to 46 percent of those children whose mothers have no education; and 65 percent children for richest households received ORS or any recommended homemade fluid, while this proportion was 37 percent for children from the poorest households. 53 Table CH.4: Oral rehydration solutions and recommended homemade fluids Percentage of children age 0-59 months with diarrhoea in the last two weeks, and treatment with oral rehydration solutions and recommended homemade fluids, South Sudan, 2010 Had diarrhoea in last two weeks Number of children age 0-59 months Children with diarrhoea who received: ORS or any recommended homemade fluid Number of children aged 0-59 months with diarrhoea ORS (Fluid from ORS packet, ORADEX) Any recommended homemade fluid (*): Figures based on unweighted cases < 25 Sex Male 34.9 4261 39.1 24.7 48.4 1488 Female 33.1 4077 38.0 25.9 50.0 1349 State Upper Nile 32.3 967 45.1 26.0 54.0 312 Jonglei 28.5 1254 38.0 22.5 49.1 357 Unity 38.9 635 37.4 10.4 43.2 247 Warap 32.3 1176 26.0 15.8 35.1 380 Northern Bahr El Ghazal 37.4 820 28.7 29.5 43.6 307 Western Bahr El Ghazal 42.2 326 36.7 32.4 55.8 137 Lakes 30.0 618 27.1 13.0 33.0 185 Western Equatoria 33.0 644 42.4 33.0 54.1 212 Central Equatoria 31.2 1036 58.3 44.2 73.0 323 Eastern Equatoria 43.7 862 42.7 25.9 50.0 376 Residence Urban 33.6 2042 44.4 29.0 55.3 686 Rural 34.2 6296 36.8 24.1 47.2 2152 Age-group 0-11 33.8 1730 32.3 23.0 42.7 585 12-23 43.1 1704 43.2 28.4 53.5 735 24-35 35.0 1958 38.6 22.3 48.0 686 36-47 30.3 1789 37.1 25.9 48.8 542 48-59 25.1 1156 42.5 27.7 54.4 290 Mother's education None 33.9 6993 36.3 23.7 46.3 2371 Primary 36.8 1080 48.1 33.3 61.2 397 Secondary + 26.2 262 62.3 33.3 76.5 69 Missing/DK * 3 - - - 0 Wealth index quintiles Poorest 35.9 1712 27.3 19.0 37.3 615 Second 33.9 1635 34.6 22.1 45.2 554 Middle 35.2 1653 35.0 24.7 45.3 581 Fourth 33.3 1753 46.0 28.1 55.9 584 Richest 31.7 1585 52.4 33.8 64.6 503 Total 34.0 8338 38.6 25.3 49.1 2838 54 Table CH.5 shows percent distribution of children aged 0-59 months with diarrhoea in the last two weeks by amount of liquids and food given during episode of diarrhoea. Of importance in this table are the drinking and eating practices of these children during diarrhoeal episodes. A quarter (25 percent) of under-five children with diarrhoea drank more than usual while 27 percent drank the same (Table CH.5). More than a quarter (27 percent) was given about the same to eat (continued feeding), but 11 percent stopped feeding. There are no significant differences across gender, residence and wealth index quintiles in terms of feeding practices (both drinking and eating) of children during diarrhoeal episodes. There are however some differences across states and mother’s education in terms of feeding practices of children during diarrhoeal episodes. Figure CH.3: Percentage of children under age 5 with diarrhoea who received ORS or recommended homemade fluids, South Sudan, 2010 St at e M ot he r’s Ed uc at io n 55 Ta bl e CH .5 : F ee di ng p ra ct ic es d ur in g di ar rh oe a Pe rc en t d ist rib ut io n of c hi ld re n ag e 0- 59 m on th s w ith d ia rr ho ea in th e la st tw o w ee ks b y am ou nt o f l iq ui ds a nd fo od g iv en d ur in g ep is od e of d ia rr ho ea , S ou th S ud an , 2 01 0 Ha d di ar r ho ea in la st tw o w ee ks N um be r of ch ild re n ag e 0- 59 m on th s G iv en le ss th an us ua l t o dr in k G iv en ab ou t t he sa m e to dr in k G iv en m or e th an us ua l t o dr in k G iv en no th in g to d rin k M is si ng / DK To ta l G iv en le ss th an us ua l t o ea t G iv en ab ou t t he sa m e to ea t G iv en m or e to ea t St op p ed fo od Ex cl us i ve ly br ea st fe d M is si n g/ DK To ta l (* ): Fi gu re s b as ed o n un w ei gh te d ca se s < 2 5 Nu m be r o f ch ild re n ag ed 0 -5 9 m on th s w ith di ar rh oe a Se x M al e 34 .9 42 61 35 .0 25 .9 25 .4 10 .6 3. 2 10 0. 0 44 .5 27 .0 8. 7 11 .0 6. 9 2. 0 10 0. 0 14 88 Fe m al e 33 .1 40 77 34 .3 27 .1 25 .2 9. 9 3. 5 10 0. 0 42 .4 27 .6 9. 0 11 .2 7. 5 2. 2 10 0. 0 13 49 St at e Up pe r N ile 32 .3 96 7 37 .2 21 .5 23 .2 13 .3 4. 8 10 0. 0 48 .5 17 .0 8. 9 12 .2 10 .5 3. 0 10 0. 0 31 2 Jo ng le i 28 .5 12 54 34 .4 27 .0 21 .1 13 .4 4. 0 10 0. 0 36 .3 34 .4 6. 8 13 .0 7. 8 1. 8 10 0. 0 35 7 Un ity 38 .9 63 5 48 .3 13 .1 26 .2 6. 7 5. 7 10 0. 0 48 .1 14 .0 19 .0 8. 8 5. 0 5. 2 10 0. 0 24 7 W ar ap 32 .3 11 76 33 .2 27 .5 29 .1 8. 6 1. 6 10 0. 0 41 .8 23 .6 8. 5 16 .5 6. 3 3. 3 10 0. 0 38 0 N or th er n Ba hr E l G ha za l 37 .4 82 0 29 .0 33 .1 26 .8 10 .2 0. 8 10 0. 0 42 .1 30 .0 8. 0 11 .0 8. 8 0. 0 10 0. 0 30 7 W es te rn B ah r E l G ha za l 42 .2 32 6 41 .4 26 .2 17 .4 9. 8 5. 2 10 0. 0 49 .8 24 .8 5. 2 8. 1 9. 3 2. 9 10 0. 0 13 7 La ke s 30 .0 61 8 25 .8 29 .1 34 .4 8. 3 2. 4 10 0. 0 41 .9 26 .7 11 .4 10 .2 7. 9 2. 0 10 0. 0 18 5 W es te rn E qu at or ia 33 .0 64 4 31 .9 26 .8 30 .6 5. 9 4. 7 10 0. 0 51 .7 23 .7 4. 9 13 .4 5. 7 0. 7 10 0. 0 21 2 Ce nt ra l E qu at or ia 31 .2 10 36 33 .8 31 .1 27 .0 7. 0 1. 0 10 0. 0 50 .0 32 .1 5. 4 8. 8 3. 3 0. 5 10 0. 0 32 3 Ea st er n Eq ua to ria 43 .7 86 2 34 .1 26 .8 19 .3 15 .1 4. 7 10 0. 0 34 .5 38 .3 10 .5 6. 9 7. 8 2. 1 10 0. 0 37 6 Re si de nc e Ur ba n 33 .6 20 42 32 .4 26 .6 28 .9 9. 7 2. 4 10 0. 0 48 .8 28 .1 6. 5 7. 9 7. 3 1. 4 10 0. 0 68 6 Ru ra l 34 .2 62 96 35 .4 26 .4 24 .1 10 .4 3. 6 10 0. 0 41 .8 27 .0 9. 6 12 .1 7. 1 2. 3 10 0. 0 21 52 Ag e- gr ou p 0- 11 33 .8 17 30 34 .3 31 .0 20 .6 12 .6 1. 4 10 0. 0 34 .3 27 .0 8. 8 7. 3 21 .0 1. 7 10 0. 0 58 5 12 -2 3 43 .1 17 04 34 .7 24 .0 28 .9 8. 7 3. 8 10 0. 0 45 .8 23 .6 10 .1 12 .0 6. 2 2. 2 10 0. 0 73 5 24 -3 5 35 .0 19 58 35 .5 27 .1 23 .3 9. 5 4. 5 10 0. 0 47 .2 28 .8 7. 8 11 .3 2. 7 2. 3 10 0. 0 68 6 36 -4 7 30 .3 17 89 32 .4 24 .9 27 .5 11 .8 3. 4 10 0. 0 45 .9 28 .3 8. 1 13 .1 2. 1 2. 5 10 0. 0 54 2 48 -5 9 25 .1 11 56 37 .4 24 .9 26 .2 8. 2 3. 2 10 0. 0 43 .2 31 .4 9. 6 12 .5 1. 8 1. 5 10 0. 0 29 0 M ot he r's e du ca tio n N on e 33 .9 69 93 34 .6 26 .3 24 .7 10 .7 3. 7 10 0. 0 42 .6 27 .1 9. 0 11 .7 7. 4 2. 2 10 0. 0 23 71 Pr im ar y 36 .8 10 80 37 .4 26 .0 26 .7 8. 7 1. 3 10 0. 0 48 .0 27 .8 7. 4 8. 8 6. 3 1. 7 10 0. 0 39 7 Se co nd ar y + 26 .2 26 2 22 .5 33 .8 36 .3 5. 5 1. 9 10 0. 0 48 .1 30 .0 11 .2 3. 2 5. 6 1. 9 10 0. 0 69 W ea lth in de x qu in til es Po or es t 35 .9 17 12 35 .4 27 .3 24 .1 10 .4 2. 9 10 0. 0 39 .6 31 .7 9. 6 11 .2 6. 1 1. 8 10 0. 0 61 5 Se co nd 33 .9 16 35 35 .0 26 .6 23 .5 12 .2 2. 7 10 0. 0 40 .2 25 .7 9. 5 12 .9 9. 2 2. 5 10 0. 0 55 4 M id dl e 35 .2 16 53 36 .2 23 .4 25 .2 10 .8 4. 3 10 0. 0 43 .7 25 .1 9. 9 12 .3 6. 8 2. 2 10 0. 0 58 1 Fo ur th 33 .3 17 53 33 .7 29 .4 24 .5 8. 4 3. 9 10 0. 0 45 .2 26 .8 8. 1 10 .1 7. 3 2. 6 10 0. 0 58 4 Ri ch es t 31 .7 15 85 32 .8 25 .4 29 .7 9. 4 2. 8 10 0. 0 49 .8 26 .7 6. 8 9. 0 6. 5 1. 3 10 0. 0 50 3 To ta l 34 .0 83 38 34 .7 26 .5 25 .3 10 .3 3. 3 10 0. 0 43 .5 27 .3 8. 8 11 .1 7. 2 2. 1 10 0. 0 28 38 56 Table CH.6 provides the proportion of children aged 0-59 months with diarrhoea in the last two weeks who received oral rehydration therapy with continued feeding (Figure CH.3), and percentage of children with diarrhoea who received other treatments. Overall, 52 percent of children with diarrhoea received ORS or increased fluids, 60 percent received ORT (ORS or recommended homemade fluids or increased fluids) and 27 percent were not given any treatment or drug. Combining the information in Table CH.5 with those in Table CH.4 on oral rehydration therapy, it is observed that 23 percent of children either received ORT and, at the same time, feeding was continued, as is the recommendation. Across states, the proportions range from 15 percent in Western Equatoria to 31 percent in Central Equatoria. There are no significant differences in terms of oral rehydration therapy with continued feeding in South Sudan across gender, residence and economic status. However, children whose mothers/caretakers have secondary and higher education are more (38 percent) likely to receive ORT with continued feeding compared to 23 percent for those children whose mothers/ caretakers have no education or primary education. Also, the proportion for children aged 48- 59 months who received ORT and continued feeding is 31 percent compared to 20-23 percent for other age-groups. 57 N ot g iv en a ny tr ea t m en t o r dr ug In tr av - en ou s H om e re m ed y/ He rb al m ed ic in e O th er O RS o r in cr ea se d flu id s OR T (O RS or re co - m m en de d ho m e m ad e flu id s o r in cr ea se d flu id s) O RT w ith co nt in ue d fe ed in g [1 ] Pi ll or sy ru p: An tib io tic Pi ll or sy ru p: An tim ot ili ty Pi ll or sy ru p: Zi nc Pi ll or sy ru p: O th er Pi ll or sy ru p: Un kn ow n In je ct io n: An ti bi ot ic In je c tio n: N on - an tib io tic In je ct io n: Un kn ow n Ch ild re n w ith d ia rr ho ea w ho re ce iv ed : O th er tr ea tm en t: Ta bl e CH .6 : O ra l r eh yd ra tio n th er ap y w ith c on tin ue d fe ed in g an d ot he r t re at m en ts Pe rc en ta ge o f c hi ld re n ag e 0- 59 m on th s w ith d ia rr ho ea in th e la st tw o w ee ks w ho re ce iv ed o ra l r eh yd ra tio n th er ap y w ith c on tin ue d fe ed in g, a nd p er ce nt ag e of c hi ld re n w ith d ia rr ho ea w ho re ce iv ed o th er tr ea tm en ts , S ou th S ud an , 2 01 0 [1 ] M IC S in di ca to r 3 .8 Se x M al e 53 .4 61 .1 22 .7 17 .2 2. 6 3. 2 p. 5 6. 9 1. 7 p. 6 p. 8 p. 3 7. 5 6. 9 26 .0 14 88 Fe m al e 50 .3 59 .7 23 .3 17 .0 1. 9 3. 0 p. 5 5. 8 2. 4 p. 3 p. 6 p. 5 8. 8 6. 3 27 .8 13 49 St at e Up pe r N ile 56 .4 63 .4 18 .6 20 .6 0. 9 0. 4 0. 0 3. 0 1. 8 1. 5 0. 8 0. 0 0. 4 3. 3 28 .7 31 2 Jo ng le i 48 .8 57 .7 26 .6 18 .6 3. 6 6. 2 0. 8 4. 1 2. 1 0. 0 .8 0. 4 2. 6 2. 9 29 .7 35 7 Un ity 52 .3 56 .6 22 .7 10 .6 2. 6 8. 0 1. 2 10 .2 2. 0 0. 9 1. 1 0. 0 3. 1 7. 5 29 .6 24 7 W ar ap 45 .6 53 .5 17 .7 6. 1 2. 2 1. 1 0. 0 4. 1 .8 0. 0 0. 3 0. 0 9. 5 5. 9 38 .0 38 0 N or th er n Ba hr E l G ha za l 44 .8 56 .6 24 .8 8. 9 1. 1 2. 2 0. 0 6. 6 .5 0. 0 0. 5 0. 0 24 .0 6. 9 22 .3 30 7 W es te rn B ah r E l G ha za l 45 .9 61 .9 17 .0 23 .6 1. 7 .3 0. 3 6. 6 2. 6 0. 3 1. 1 0. 3 9. 8 5. 2 21 .1 13 7 La ke s 49 .6 52 .7 21 .4 18 .4 2. 0 2. 1 0. 4 4. 6 2. 0 1. 1 0. 4 0. 0 2. 5 4. 3 33 .3 18 5 W es te rn E qu at or ia 55 .3 64 .9 14 .8 24 .2 5. 2 6. 0 0. 5 6. 7 4. 2 0. 7 1. 8 0. 3 10 .2 7. 1 19 .8 21 2 Ce nt ra l E qu at or ia 68 .0 80 .2 30 .6 25 .8 2. 5 1. 8 0. 4 11 .3 3. 5 0. 0 0. 0 1. 3 8. 2 13 .2 8. 8 32 3 Ea st er n Eq ua to ria 50 .6 56 .9 28 .3 20 .4 1. 6 2. 8 1. 0 7. 1 1. 9 0. 7 0. 7 1. 1 9. 7 8. 8 31 .5 37 6 Re si de nc e Ur ba n 57 .2 66 .2 21 .6 22 .1 4. 1 4. 0 0. 8 8. 1 2. 4 0. 4 1. 0 1. 0 5. 4 9. 2 19 .5 68 6 Ru ra l 50 .2 58 .6 23 .4 15 .5 1. 7 2. 8 0. 4 5. 8 1. 9 0. 5 0. 6 0. 2 9. 0 5. 8 29 .2 21 52 Ag e- gr ou p 0- 11 43 .6 52 .8 20 .0 19 .7 2. 8 1. 9 0. 4 8. 0 1. 8 0. 6 0. 3 0. 6 6. 6 6. 6 29 .2 58 5 12 -2 3 56 .4 64 .8 22 .7 18 .1 3. 1 2. 4 0. 6 5. 9 2. 0 0. 3 0. 7 0. 7 8. 6 7. 8 24 .6 73 5 24 -3 5 50 .6 58 .4 22 .7 14 .4 2. 1 4. 3 0. 5 5. 7 2. 7 .0 6 0. 8 0. 0 6. 9 5. 5 29 .4 68 6 36 -4 7 54 .0 62 .1 22 .7 16 .5 1. 8 3. 4 0. 2 6. 1 1. 3 0. 5 0. 7 0. 4 7. 6 5. 9 27 .5 54 2 48 -5 9 56 .6 66 .5 30 .8 16 .9 .5 3. 9 0. 5 5. 9 2. 4 .0 1. 2 0. 0 13 .7 7. 9 20 .3 29 0 M ot he r's e du ca tio n N on e 50 .2 58 .4 22 .6 15 .7 2. 2 3. 4 0. 4 5. 7 1. 9 0. 5 0. 7 0. 2 8. 9 5. 7 28 .8 23 71 Pr im ar y 59 .0 69 .3 23 .0 23 .2 2. 7 1. 3 0. 6 9. 1 2. 6 0. 4 0. 4 0. 9 4. 8 11 .3 18 .3 39 7 Se co nd ar y + 68 .2 80 .9 37 .5 30 .6 3. 4 2. 5 1. 1 13 .1 2. 0 0. 0 4. 0 3. 0 2. 0 10 .6 8. 8 69 W ea lth in de x qu in til es Po or es t 41 .9 50 .2 22 .6 10 .2 2. 0 2. 8 0. 5 5. 6 0. 2 0. 7 .6 0. 0 10 .4 4. 9 36 .3 61 5 Se co nd 48 .9 57 .5 21 .3 12 .9 1. 1 4. 3 0. 5 4. 4 0. 9 0. 0 .6 0. 4 10 .8 5. 1 28 .2 55 4 M id dl e 50 .5 59 .0 23 .1 14 .1 1. 2 2. 8 0. 4 6. 6 2. 4 0. 4 .0 0. 3 7. 4 7. 2 30 .2 58 1 Fo ur th 57 .3 65 .4 23 .4 22 .0 3. 6 1. 9 0. 5 6. 0 3. 6 0. 8 1. 3 0. 5 6. 2 6. 4 21 .8 58 4 Ri ch es t 62 .8 72 .1 24 .7 28 .0 3. 8 4. 0 0. 5 9. 5 3. 2 0. 4 1. 1 0. 8 5. 4 10 .2 15 .6 50 3 To ta l 51 .9 60 .4 23 .0 17 .1 2. 3 3. 1 0. 5 6. 3 2. 0 0. 5 0. 7 0. 4 8. 1 6. 6 26 .8 28 38 Nu m be r o f ch ild re n ag ed 0 -5 9 m on th s w ith d ia rr- ho ea 58 Care Seeking and Antibiotic Treatment of Pneumonia Pneumonia is the leading cause of death in children and the use of antibiotics in under-5s with suspected pneumonia is a key intervention. A World Fit for Children goal is to reduce by one- third the deaths due to acute respiratory infections. In the South Sudan Household Health Survey, the prevalence of suspected pneumonia was estimated by asking mothers or caretakers whether their child under age five had an illness with a cough accompanied by rapid or difficult breathing, and whose symptoms were due to a problem in the chest or both a problem in the chest and a blocked nose. Figure CH.3: Precentage of children under age 5 with diarrhoea who received ORT or increased fluids, AND continued feeding South Sudan, 2010 State Mother’s Education Place of Residence 59 Table CH.7 presents the prevalence of suspected pneumonia and, if care was sought outside the home, the site of care. Overall, 19percent of children aged 0-59 months were reported to have had symptoms of pneumonia during the two weeks preceding the survey. Of these children, 48 percent were taken to an appropriate provider. There is no gender difference in the proportions of children aged 0-59 months reported to have had symptoms of pneumonia and were taken to an appropriate provider. However, 59 percent of urban children with suspected pneumonia were taken to an appropriate provider compared to 44 percent for rural children. The State with the highest proportion of children aged 0-59 months reported to have had symptoms of pneumonia during the two weeks preceding the survey and were taken to an appropriate provider is Central Equatoria (64 percent). The lowest proportions are in Lakes State (28 percent), Warap (28 percent) and Northern Bahr El Ghazal (32 percent). The proportion of children aged 0-59 months reported to have had symptoms of pneumonia during the two weeks preceding the survey and taken to an appropriate provider amongst the richest is twice that of the poorest, reported at 66 and 33 percent, respectively. This pattern is also observed across educational level of the mothers/caretakers of these children, with those with no education having lower proportion (45 percent) compared to that (64 percent) of mothers with secondary or higher educational levels. The providers most visited are from government hospitals and health centres, and private hospitals/clinics and pharmacy clinics. Table CH.7 also presents the use of antibiotics for the treatment of suspected pneumonia in under-5s by sex, age, state, residence, age, and socioeconomic status. In South Sudan, 33 percent of under-5 children with suspected pneumonia had received an antibiotic during the two weeks prior to the survey. The percentage was considerably higher in Western Bahr El Ghazal (53 percent), compared to only 17 percent in Warap State. Similarly, the proportion is higher in urban areas (43 percent) than in rural areas (29 percent). Table CH.7 also shows that antibiotic treatment of suspected pneumonia is very low among the poorest households and among children whose mothers/caretakers have no education. The use of antibiotics doesn’t vary much across age- groups. 60 Ta bl e CH .7 : C ar e se ek in g fo r s us pe ct ed p ne um on ia a nd a nt ib io tic u se d ur in g su sp ec te d pn eu m on ia Pe rc en ta ge o f c hi ld re n ag e 0- 59 m on th s w ith su sp ec te d pn eu m on ia in th e la st tw o w ee ks w ho w er e ta ke n to a h ea lth p ro vi de r a nd p er ce nt ag e of c hi ld re n w ho w er e gi ve n an tib io tic s, S ou th S ud an , 2 01 0 Had suspected pneumonia in the last two weeks Number of children age 0-59 months Hospital Health center Health unit Village health worker Mobile/Outreach clinic Other Hospital/ clinic Physician Other medical Pharmacy Mobile clinic Other medical Religious healer Traditional healer Relative or friend Other Any appro priate provider [1] Percentage of children with suspected pneumonia who received antibiotics in the last two weeks [2] Ch ild re n w ith su sp ec te d pn eu m on ia w ho w er e ta ke n to [1 ] M IC S in di ca to r 3 .9 [2 ] M IC S in di ca to r 3 .1 0 Pu bl ic S ec to r Se x M al e 19 .1 42 61 12 .8 14 .1 11 .3 4. 2 1. 3 0. 4 7. 2 1. 3 0. 8 7. 0 0. 3 0. 8 0. 6 1. 8 0. 1 1. 4 48 .0 32 .4 81 6 Fe m al e 18 .8 40 77 13 .6 12 .3 10 .1 3. 6 2. 0 0. 3 7. 7 0. 7 0. 4 6. 9 0. 9 0. 4 0. 1 1. 2 0. 4 0. 9 47 .2 33 .3 76 6 St at e Up pe r N ile 15 .9 96 7 16 .5 16 .9 11 .9 2. 2 2. 3 2. 3 3. 9 1. 7 2. 2 2. 3 1. 6 2. 2 0. 0 0. 0 0. 0 2. 3 58 .4 37 .0 15 4 Jo ng le i 13 .5 12 54 8. 6 10 .7 14 .0 9. 7 .0 0. 0 7. 5 0. 9 0. 0 6. 9 0. 8 0. 0 0. 0 0. 0 0. 0 0. 0 52 .2 33 .7 17 0 Un ity 18 .0 63 5 15 .7 9. 8 5. 5 12 .9 6. 1 0. 6 6. 3 1. 2 3. 1 7. 4 0. 6 3. 1 0. 0 0. 0 0. 6 2. 5 52 .1 30 .0 11 4 W ar ap 17 .6 11 76 6. 2 13 .3 13 .1 1. 7 1. 7 0. 0 5. 4 1. 3 0. 0 4. 4 1. 3 0. 0 0. 0 3. 1 0. 0 2. 5 28 .1 16 .9 20 6 No rth ern Ba hr El Gh aza l 27 .0 82 0 8. 8 8. 1 4. 2 5. 4 1. 2 0. 0 4. 2 0. 8 0. 0 5. 4 0. 0 0. 0 0. 4 1. 9 0. 0 0. 4 31 .5 23 .8 22 1 We ste rn Ba hr El Gh aza l 19 .5 32 6 15 .6 6. 9 14 .4 2. 5 2. 5 0. 0 12 .5 4. 3 0. 6 3. 7 0. 0 0. 6 1. 3 1. 2 0. 6 0. 0 58 .1 53 .1 63 La ke s 15 .0 61 8 7. 7 7. 6 7. 7 1. 5 .8 0. 8 2. 3 0. 0 0. 0 11 .9 0. 0 0. 0 0. 0 2. 1 0. 0 1. 7 27 .8 31 .0 92 W es te rn E qu at or ia 18 .1 64 4 28 .0 16 .2 7. 5 5. 9 1. 5 0. 6 8. 2 .0 1. 5 15 .3 0. 6 1. 5 1. 2 3. 9 0. 9 0. 6 56 .9 37 .0 11 6 Ce nt ra l E qu at or ia 22 .6 10 36 17 .2 18 .5 12 .9 0. 7 0. 7 0. 0 15 .7 0. 6 0. 0 7. 8 0. 0 0. 0 0. 0 0. 7 0. 0 0. 0 63 .9 47 .1 23 4 Ea st er n Eq ua to ria 24 .4 86 2 13 .6 16 .6 14 .2 0. 3 1. 6 0. 0 7. 0 0. 6 0. 0 7. 6 0. 3 0. 0 1. 3 2. 2 0. 6 1. 6 52 .1 32 .4 21 0 Re si de nc e Ur ba n 20 .0 20 42 19 .7 13 .2 8. 7 3. 1 1. 1 0. 3 13 .6 2. 3 0. 3 9. 5 1. 2 0. 3 0. 0 1. 5 0. 2 1. 1 59 .0 43 .2 40 9 Ru ra l 18 .6 62 96 10 .9 13 .2 11 .4 4. 2 1. 8 0. 4 5. 2 0. 5 0. 6 6. 1 0. 3 0. 6 0. 5 1. 5 0. 2 1. 2 43 .7 29 .3 11 73 Ag e- gr ou p 0- 11 19 .5 17 30 8. 6 13 .2 12 .5 3. 3 2. 4 0. 0 8. 4 0. 7 .0 7. 6 0. 4 0. 0 0. 2 1. 0 0. 0 0. 6 45 .2 34 .3 33 7 12 -2 3 20 .3 17 04 15 .8 13 .7 10 .0 2. 9 1. 5 1. 1 10 .2 1. 1 1. 3 8. 7 0. 3 1. 3 0. 9 0. 9 0. 0 1. 1 54 .5 36 .2 34 6 24 -3 5 18 .6 19 58 16 .5 15 .0 9. 4 3. 3 0. 7 0. 0 6. 2 0. 6 0. 8 6. 6 0. 2 .8 0. 5 1. 8 0. 4 1. 6 47 .1 34 .6 36 4 36 -4 7 19 .3 17 89 12 .7 12 .9 13 .5 6. 2 2. 3 0. 2 5. 9 1. 1 0. 0 6. 4 1. 1 0. 0 0. 0 1. 9 0. 3 1. 6 48 .6 27 .2 34 5 48 -5 9 16 .4 11 56 11 .0 9. 7 6. 3 4. 0 1. 0 0. 6 5. 4 1. 9 0. 9 4. 4 1. 0 0. 9 0. 0 2. 4 0. 5 0. 4 38 .6 31 .2 19 0 W ea lth in de x qu in til es N on e 18 .3 69 93 11 .5 13 .0 9. 8 4. 6 1. 7 0. 4 6. 4 0. 8 0. 5 6. 1 0. 4 0. 5 0. 3 1. 8 0. 2 1. 1 44 .6 29 .0 12 78 Pr im ar y 23 .0 10 80 19 .2 14 .9 16 .7 .4 .6 0. 3 11 .2 1. 7 1. 0 10 .1 1. 3 1. 0 0. 8 0. 4 0. 4 1. 3 59 .5 48 .2 24 8 Se co nd ar y + 21 .4 26 2 24 .0 10 .5 5. 5 4. 6 4. 0 0. 0 13 .8 2. 4 0. 7 13 .0 0. 0 0. 7 0. 0 0. 0 0. 0 1. 2 63 .5 53 .0 56 W ea lth in de x qu in til es Po or es t 18 .6 17 12 8. 3 10 .8 7. 1 3. 6 1. 3 0. 4 4. 3 1. 0 1. 6 3. 6 .0 4 1. 6 .4 3. 1 0. 0 1. 0 33 .2 17 .5 31 8 Se co nd 18 .6 16 35 12 .7 14 .0 10 .1 4. 4 1. 6 0. 8 7. 5 .5 0. 0 7. 8 0. 0 0. 0 0. 0 2. 2 0. 1 1. 6 45 .6 28 .9 30 5 M id dl e 21 .0 16 53 7. 9 13 .1 9. 7 3. 9 3. 2 0. 4 5. 7 1. 0 0. 3 5. 1 0. 5 0. 3 0. 8 0. 7 0. 0 1. 4 42 .9 25 .3 34 7 Fo ur th 18 .2 17 53 11 .1 15 .4 15 .3 4. 6 .4 0. 2 9. 6 .0 0. 2 9. 1 0. 0 0. 2 0. 3 1. 1 0. 0 1. 4 52 .6 41 .3 31 9 Ri ch es t 18 .5 15 85 27 .5 12 .8 11 .5 3. 1 1. 4 0. 0 10 .4 2. 6 0. 7 9. 6 1. 8 0. 7 0. 2 0. 5 1. 0 0. 2 65 .5 53 .3 29 4 To ta l 19 .0 83 38 13 .2 13 .2 10 .7 3. 9 1. 6 0. 4 7. 4 1. 0 0. 6 7. 0 0. 5 0. 6 0. 4 1. 5 0. 2 1. 1 47 .6 32 .9 15 82 Pr iv at e Se ct or O th er Number of children age 0-59 months with suspected pneumonia in the last two weeks 61 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.8. Almost all households (99 percent) in South Sudan use Solid fuels for cooking, with wood and charcoal being used by 81 and 14 percent of all households respectively. Furthermore, there is little or no difference across the different background characteristics. Solid fuel use by place of cooking is depicted in Table CH.9. 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 SHHS 2 data, 30 percent of households cook in a separate room used as a kitchen, 19 percent elsewhere in the house, 9 percent in a separate building and 41 percent outdoors. The percentage of households that cook elsewhere in the house is slightly lower in urban areas (15 percent) than in rural areas (20 percent). The percentages for this same category of households range from 8 percent in Western Equatoria and Central Equatoria to 30 percent in Warap. Furthermore, there is significant difference across educational level of the head of the household. The percentage of households whose household head is uneducated and that cook elsewhere in the house is nearly twice (21 percent) that of the households headed by educated persons (11 percent). A slight variation also exists by wealth status with 21 percent of the poorest households cooking elsewhere in the house compared to 13 percent for the richest households. 62 Ta bl e CH .8 : S ol id fu el u se Pe rc en t d ist rib ut io n of h ou se ho ld m em be rs a cc or di ng to ty pe o f c oo ki ng fu el u se d by th e ho us eh ol d, a nd p er ce nt ag e of h ou se ho ld m em be rs li vi ng in ho us eh ol ds u si ng so lid fu el s f or c oo ki ng , S ou th S ud an , 2 01 0 Pe rc en ta ge o f h ou se ho ld m em be rs in h ou se ho ld s u si ng So lid fu el s fo r co ok in g [1 ] El ec tr ic ity G as Bi og as Ke ro se ne Ch ar co al W oo d St ra w / Sh ru bs / G ra ss An im al du ng Ag ric ul - tu ra l c ro p re sid ue No fo od co ok ed in ho us e ho ld O th er M is si ng To ta l [1 ] M IC S in di ca to r 3 .1 1 ( ) : F ig ur es b as ed o n 25 -4 9 un w ei gh te d ca se s N um be r o f ho us e ho ld m em be rs St at e Up pe r N ile 0. 1 1. 1 0. 4 0. 0 26 .7 63 .5 6. 2 0. 0 0. 4 0. 1 0. 7 0. 9 10 0. 0 96 .8 67 63 Jo ng le i 0. 1 0. 0 0. 0 0. 0 4. 4 91 .6 3. 2 0. 0 0. 2 0. 0 0. 0 0. 5 10 0. 0 99 .5 81 72 Un ity 0. 1 0. 3 0. 1 0. 0 10 .8 78 .0 9. 4 0. 3 0. 7 0. 2 0. 0 0. 2 10 0. 0 99 .2 39 69 W ar ap 0. 0 0. 1 0. 0 0. 0 2. 3 92 .8 1. 7 1. 3 1. 4 0. 1 0. 0 0. 2 10 0. 0 99 .5 75 87 No rt he rn B ah r E l G ha za l 0. 0 0. 0 0. 0 0. 0 1. 9 87 .6 6. 4 0. 3 3. 3 0. 4 0. 1 0. 0 10 0. 0 99 .5 52 10 W es te rn B ah r E l G ha za l 0. 0 0. 4 0. 0 0. 1 37 .8 61 .2 0. 2 0. 0 0. 0 0. 4 0. 0 0. 0 10 0. 0 99 .1 21 17 La ke s 0. 0 0. 0 0. 1 0. 0 6. 6 92 .5 0. 5 0. 0 0. 0 0. 0 0. 0 0. 4 10 0. 0 99 .6 44 35 W es te rn E qu at or ia 0. 0 0. 3 0. 0 0. 5 11 .2 87 .8 0. 1 0. 0 0. 0 0. 0 0. 1 0. 0 10 0. 0 99 .1 43 55 Ce nt ra l E qu at or ia 0. 0 0. 3 0. 2 0. 0 37 .0 61 .8 0. 0 0. 0 0. 2 0. 2 0. 1 0. 0 10 0. 0 99 .1 73 36 Ea st er n Eq ua to ria 0. 0 0. 0 0. 0 0. 7 10 .7 88 .3 0. 1 0. 0 0. 0 0. 1 0. 0 0. 2 10 0. 0 99 .1 60 56 Re si de nc e Ur ba n 0. 0 0. 8 0. 3 0. 2 34 .4 61 .6 1. 9 0. 1 0. 2 0. 2 0. 0 0. 1 10 0. 0 98 .2 13 95 1 Ru ra l 0. 0 0. 1 0. 0 0. 1 7. 2 88 .0 3. 1 0. 3 0. 8 .1 0. 1 0. 3 10 0. 0 99 .3 42 05 0 Ed uc at io n of h ou se ho ld h ea d N on e 0. 0 0. 2 0. 1 0. 1 9. 6 85 .2 3. 3 0. 3 0. 7 0. 1 0. 1 0. 3 10 0. 0 99 .0 43 91 9 Pr im ar y 0. 0 0. 0 0. 0 0. 1 21 .3 76 .6 1. 3 0. 2 0. 2 0. 1 0. 1 0. 2 10 0. 0 99 .5 65 26 Se co nd ar y + 0. 0 1. 0 0. 3 0. 3 39 .7 57 .2 0. 6 0. 0 0. 5 0. 3 0. 0 0. 0 10 0. 0 98 .0 55 08 M is si ng /D K 0. 0 0. 0 0. 0 0. 0 (6 8. 7) (3 1. 3) 0. 0 0. 0 0. 0 0. 0 0. 0 0. 0 (1 00 .0 ) (1 00 .0 ) 48 W ea lth in de x qu in til es Po or es t 0. 0 0. 0 0. 0 0. 0 0. 0 99 .9 0. 1 0. 0 0. 0 0. 0 0. 0 0. 0 10 0. 0 10 0. 0 11 20 3 Se co nd 0. 0 0. 0 0. 0 0. 0 0. 0 97 .5 1. 6 0. 3 0. 6 0. 0 0. 0 0. 0 10 0. 0 10 0. 0 11 19 8 M id dl e 0. 0 0. 0 0. 0 0. 0 0. 0 91 .4 6. 1 0. 5 1. 4 0. 0 0. 1 0. 6 10 0. 0 99 .3 11 20 2 Fo ur th 0. 1 0. 0 0. 0 0. 1 6. 2 86 .1 5. 1 0. 4 0. 8 0. 3 0. 4 0. 6 10 0. 0 98 .5 11 20 0 Ri ch es t 0. 1 1. 2 0. 5 0. 5 63 .6 32 .1 1. 0 0. 0 0. 5 0. 4 0. 0 0. 2 10 0. 0 97 .2 11 19 8 To ta l 0. 0 0. 2 0. 1 0. 1 14 .0 81 .4 2. 8 0. 2 0. 6 0. 1 0. 1 0. 3 10 0. 0 99 .0 56 00 1 63 Table CH.9: Solid fuel use by place of cooking Percent distribution of household members in households using solid fuels by place of cooking, South Sudan, 2010 Place of cooking: Number of household members in households using solid fuels for cooking In a separate room used as kitchen Elsewhere in the house In a separate building Outdoors Other Missing Total ( ): Figures based on 25-49 unweighted cases State Upper Nile 37.9 18.0 3.4 37.5 1.6 1.6 100.0 6544 Jonglei 24.4 9.5 7.9 57.8 0.0 0.4 100.0 8128 Unity 16.6 29.0 8.6 44.8 0.7 0.3 100.0 3938 Warap 20.4 30.0 14.3 34.0 0.3 1.1 100.0 7547 Northern Bahr El Ghazal 25.3 28.7 11.2 34.2 0.2 0.3 100.0 5183 Western Bahr El Ghazal 35.9 14.1 3.7 44.5 1.7 0.1 100.0 2098 Lakes 16.1 27.5 6.2 48.3 0.3 1.6 100.0 4417 Western Equatoria 62.2 8.0 8.1 20.9 0.8 0.0 100.0 4317 Central Equatoria 43.1 7.8 8.8 39.9 0.4 0.0 100.0 7271 Eastern Equatoria 26.5 16.2 12.2 39.9 5.0 0.2 100.0 6001 Residence Urban 45.0 14.9 8.0 30.5 0.9 0.6 100.0 13704 Rural 25.6 19.7 9.2 43.9 1.1 0.6 100.0 41740 Education of household head None 25.4 20.5 8.8 43.4 1.1 0.7 100.0 43502 Primary 47.7 10.8 8.6 32.2 0.7 0.0 100.0 6494 Secondary + 49.0 11.4 10.2 28.1 0.9 0.4 100.0 5400 Missing/DK (62.9) (0.0) (3.3) (33.8) (0.0) (0.0) (100.0) 48 Wealth index quintiles Poorest 15.4 21.2 10.4 50.0 2.1 0.8 100.0 11203 Second 18.2 23.2 7.0 50.2 1.1 0.3 100.0 11196 Middle 24.0 19.9 9.0 45.5 0.6 0.8 100.0 11124 Fourth 40.7 14.5 9.9 33.7 0.8 0.4 100.0 11036 Richest 54.4 13.3 8.2 23.0 0.5 0.6 100.0 10885 Total 30.4 18.5 8.9 40.6 1.0 0.6 100.0 55444 64 Malaria Malaria is a leading cause of death of children under age five in South Sudan. It also contributes to anaemia in children and is a common cause of school absenteeism. Preventive measures can dramatically reduce malaria mortality rates among children. In areas where malaria is common, the WHO recommends Indoor Residual Spraying (IRS), use of insecticide treated bednets (ITNs) and prompt treatment of confirmed cases with recommended anti-malarial drugs. International recommendations also suggest treating any fever in children as if it were malaria and immediately giving the child a full course of recommended anti-malarial tablets. Children with severe malaria symptoms, such as fever or convulsions, should be taken to a health facility. Also, children recovering from malaria should be given extra liquids and food and, for younger children, should continue breastfeeding. Insecticide-treated mosquito nets, or ITNs, if used properly, are very effective in offering protection against mosquitos and other insects. The use of ITNs is one of the main health interventions applied to reduce malaria transmission in South Sudan. The questionnaire incorporates questions on the availability and use of bed nets, both at household level and among children under five years of age and pregnant women. In addition, all households in the SHHS II were asked whether the interior dwelling walls were sprayed with an insecticide to kill mosquitoes that spread malaria during the 12 months preceding the survey. Malaria is the leading cause of morbidity and Mortality in South Sudan. Pregnant women and children under 5 years are the most vulnerable groups. A key objective of the South Sudan Malaria Strategic Plan 2006-2013 is to strengthen the Malaria Control Programme within the Ministry of Health of the Government of South Sudan to be able to lead in integrated efforts aimed at the control of malaria. The goal of malaria prevention and control in South Sudan is to reduce malaria related morbidity and mortality through rapidly increase coverage/scale-up of cost effective malaria prevention and curative interventions at least 60 percent of the target populations. The target is to ensure that at least 80 percent of those at risk of, or suffering from malaria, benefit from major preventive and curative interventions. Key elements of the control strategy include: • Malaria Prevention: universal population coverage with an integrated vector control package that includes use of long-lasting insecticidal nets (LLINs), indoor residual spraying and environmental management where applicable. • Malaria Diagnosis and Treatment: increase access to appropriate diagnosis and effective antimalarial medicines (artemisinin-based combination therapies – ACTs) with mixed approached that included both public and private sectors and at community level. • Control of Malaria in Pregnancy: provide a package consisting of LLINs, Intermittent Preventive Treatment (IPT) and effective malaria treatment to pregnant women as part of ante-natal care services. • Control of Epidemics and Outbreaks: detect early and respond rapidly to malaria epidemics and outbreaks as part of the overall MOH disease surveillance, epidemic preparedness and response programs. 65 The survey results indicate that 34 percent of households have at least one long-lasting treated net (Table CH.10). Across the states, this proportion is highest in Western Equatoria (58 percent) and lowest in Warap (17 percent), Unity (20 percent) and Upper Nile (22 percent). This proportion is higher in urban areas (44 percent) than in rural areas (31 percent). About one third of households (31 percent) with an uneducated head has at least one long-lasting treated net, compared to 46 percent for households where the head has secondary education or higher. Differentials are also significant across wealth index quintiles, as the proportion of poorest households with at least one long-lasting treated net is lower (27 percent) than that of households from the richest households, standing at 45 percent. The widely used types of mosquito nets in South Sudan include: a) mosquito nets which are not treated with insecticide; b) the insecticide treated net (ITN), which need to be retreated after every 6 months; and c) the Long-Lasting Insecticide Treated Net (LLINs), which are durable for the period of 5 years. Providers of nets in South Sudan include: a) Global Fund for Tuberculosis, AIDS and Malaria (GFTAM), provided through the primary recipient Population Services International (PSI) and implementing partners mainly NGOs; b) UN agencies: mainly WHO and UNICEF; NGOs, provided through emergency humanitarian funding; and d) The Private sector. Questions on the prevalence and treatment of fever were asked for all children under age five. Roughly one in three (32 percent) of under five children was ill with fever in the two weeks prior to the survey (Table CH.11). State level differences in fever prevalence are large, ranging from 25 percent in Unity to 46 percent in Eastern Equatoria. No significant variations noted across all other background characteristics. Mothers were asked to report all of the medicines given to a child to treat the fever, including both medicines given at home and medicines given or prescribed at a health facility. Overall, 51 percent of children with fever in the last two weeks were treated with an anti-malarial drug and 27 percent received anti-malarial drugs either on the same day or day after the onset of symptoms. Anti-malarial drugs include chloroquine, SP (sulfadoxine-pyrimethamine), artimisine combination drugs, etc. In South Sudan, 12 percent of children with fever were given chloroquine tablets, 6 percent chloroquine injection, 18 percent chloroquine syrup, 11 percent were given SP and 9 percent were given amodiaquine tablet. Only 4 percent received artemisinin combination therapy. Table CH.11 shows variations in terms of administration of any anti-malarial drug. The proportions range from 34 percent in Warap to 64 percent in Western Equatoria. Urban children are more likely than rural children to receive any anti-malaria drug as well as the children whose mothers/caretakers with primary or higher education, and children from the fourth and richest households. Little difference was noted between boys and girls receiving anti-malarial drugs. Regarding the children who received anti-malarial drugs either on the same day or day after the onset of symptoms, the proportion was higher in Western Equatoria (44 percent), where malaria is known to be most prevalent, while the lowest was in Warap State (11 percent). Urban children are more likely than rural children to be treated as they are the children whose mothers/ caretakers with primary or higher education, and children from the fourth and richest households. Little difference was noted between boys and girls receiving anti-malarial drugs. 66 Table CH.10: Household availability of treated nets Percentage of households with at least one mosquito net and percentage of households with at least one long-lasting treated net, South Sudan, 2010 Percentage of households with at least one mosquito net Percentage of households with at least one long-lasting treated net Number of households Country specific question (*): Figures based on unweighted cases < 25 State Upper Nile 47.3 21.7 998 Jonglei 43.9 32.8 1432 Unity 38.0 20.0 608 Warap 27.9 16.8 1205 Northern Bahr El Ghazal 56.9 42.6 930 Western Bahr El Ghazal 45.3 34.4 387 Lakes 54.5 30.9 676 Western Equatoria 71.3 57.5 770 Central Equatoria 64.7 38.4 1249 Eastern Equatoria 71.7 48.0 1114 Residence Urban 64.0 43.6 2161 Rural 48.7 31.4 7208 Education of household head None 48.4 31.3 7446 Primary 65.2 45.0 1120 Secondary + 70.0 46.3 797 Missing/DK * * 6 Wealth index quintiles Poorest 45.9 27.1 1879 Second 41.7 26.6 1995 Middle 47.2 31.3 2004 Fourth 61.4 43.3 1913 Richest 68.6 45.0 1578 Total 52.3 34.2 9369 67 Ha d a fe ve r i n la st tw o w ee ks N um be r of ch ild re n ag e 0- 59 m on th s SP/Fansidar tablet Chloroquine tablet Chloroquine injection Chloroquine syrup Amodiaquine tablet Metacalfin tablet Quinine pills Quinine injection Artemisinin-based combinations Any anti-malarial drug [1] Paracetamol/Panadol /Acetaminophan Aspirin Ibuprofen Other medications Don't know An ti- M al ar ia ls O th er m ed ic at io ns Ta bl e CH .1 1: A nt i-m al ar ia l t re at m en t o f c hi ld re n w ith a nt i-m al ar ia l d ru gs Pe rc en ta ge o f c hi ld re n ag e 0- 59 m on th s w ho h ad fe ve r i n th e la st tw o w ee ks w ho re ce iv ed a nt i-m al ar ia l d ru gs , S ou th S ud an , 2 01 0 [1 ] M IC S in di ca to r 3 .1 8; M DG in di ca to r 6 .8 [2 ] M IC S in di ca to r 3 .1 7 (* ): Fi gu re s b as ed o n un w ei gh te d ca se s < 2 5 Pe rc en ta ge w ho to ok a n an ti- m al ar ia l dr ug sa m e or ne xt d ay [2 ] Antibiotic Injection Se x M al e 33 .1 42 61 11 .8 12 .4 5. 3 19 .6 9. 0 0. 5 3. 1 2. 9 4. 4 53 .4 14 .7 1. 6 6. 5 2. 2 5. 2 3. 1 29 .2 14 11 Fe m al e 31 .7 40 77 10 .5 12 .4 6. 2 15 .3 9. 5 0. 9 3. 2 3. 8 4. 0 48 .7 14 .2 1. 3 6. 4 2. 1 5. 6 3. 9 24 .8 12 91 St at e Up pe r N ile 27 .6 96 7 17 .3 15 .7 7. 7 13 .9 5. 9 0. 9 1. 7 1. 3 5. 5 56 .7 8. 6 0. 5 2. 6 0. 4 1. 8 3. 4 27 .7 26 7 Jo ng le i 28 .7 12 54 17 .9 15 .6 5. 3 23 .6 10 .1 0. 4 0. 4 1. 6 2. 1 48 .4 11 .6 1. 8 5. 1 2. 5 2. 9 2. 0 20 .1 36 0 Un ity 25 .4 63 5 17 .1 14 .9 8. 3 12 .3 6. 9 3. 5 2. 6 4. 4 1. 3 55 .4 11 .8 3. 1 7. 4 3. 5 2. 6 7. 4 22 .4 16 1 W ar ap 27

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