Mozambique Multiple Indicator Cluster Survey 1995

Publication date: 1996

A -- II I I I I I I il I I il I !I .I I I I I I il I ~· r . This survey report is the result of fruitful cooperation between the National Department of Statistics (DNE) of the Ministry of Planning and Finance, and the Planning, Monitoring and Evaluation section of the United Nations Children's Fund. Mr.Manuel da Costa Gaspar (DNE, coordinator) Mr.Ronald Ernst van Dijk (UNICEF, coordinator, analysis and report) Mr.Gurpreet Samrow (UNICEF, statistical analysis) Mr.Luis Mungamba (DNE, data processing) Ms.lracema Vasconcelos (UNICEF, administration) Mr.Leonel Lopes (DNE consultant, questionnaire and data collection) Mr.Cesar Palha de Sousa (DNE consultant, questionnaire and data collection) Staff of central and provincial directorates of ministries of Health, Planning & Finance and of UEM (data collection) ~ I I I I I I I I I I I I I I I I I I I I I , I I I I I I I I I I I I I I I I I I I I \1 "'' . --··-- ·- - . -- INTRODUCTION Every country needs information about the well being of its people, in particular with regards to the most vulnerable groups in society, women and children. Mozambique is in the especially difficult situation of recovering from a lengthy civil war which started almost immediately after winning its Independence from colonial powers in 1975. The only nation-wide survey after independence was conducted in 1980 when a census was held. Since then no population-based data were collected. So far all national statistics have been derived from data provided by facilities for social services, such as schools and health facilities. No data had been collected from the population itself, the "end-users" of these setvices, and no population-based national statistics could be calculated for social indicators. Filling this void, the National Department of Statistics (DNB) of the Ministry of Planning and Finance and the United Nations Children's Fund, collaborated through a national population-based survey including key-indicators in health, nutrition, education, water and sanitation. This Multi Indicator Cluster Survey was designed and carried out in 1995 while data processing and analysis were completed in 1996. The publication of this Survey report is a good example of the excellent cooperation between Government and UNICEF. The completion of the Survey opens up new perspectives to monitor progress in service delivery in the public sector, baseline to measure future impact of rehabilitation and development on the well being of the women and children. Therefore, to make this Survey into a dynamic instrument of monitoring progress in social services, population-based data collection and analysis has to continue on a regular basis. · UNICEF is prepared to continue to assist the Government in this effort. '---:4<-6~1'----- I Shob Jhie Representative Maputo, June 1996 I I I II II II II I I I II I I I I I I I ----~-~· - Multi-Indicator Cluster Survey- 1995, GOM-UNICEF TABLE OF CONTENTS I. Executive SlDlliDary and conclusions n. Summary of MICS results 1. Introduction 2. Purpose and objective 3. Methodology 3.1 Questionnaire design 3.2 Selection and training interviewers 3.3 Sampling 3.4 Data collection 3.5 Data processing 4. Analysis and results 4.1 Demography 4.2 Vaccination 4.3 Oral rehydration therapy 4.4 Nutrition Salt iodization Protein energy malnutrition 4.5 Education 4.6 Water and sanitation Reference literature Annex A Questionnaire B Provincial statistical weights C Cluster statistical weights D Sample size calculation E Definitions of indicators F Graph: Distribution of sample population by age and gender G Early age mortality calculation Page 4 8 10 10 11 11 11 12 13 13 14 14 15 18 20 20 21 22 24 26 I I I I I I I I I I I I I I I I I Multi-Indicator Cluster Survey- 1995, GOM-UNICEF I. EXECUTIVE SUMMARY AND CONCLUSIONS Coordinated by the Ministry of Planning & Finance (MPF) department of statistics (DNE), a survey was carried out in 1995 in close cooperation with the Ministry of Health (MOH) with technical and financial support from UNICEF. To measure progress in achieving Goals set for the Mid-Decade with regards to health, nutrition, education, water and sanitation throughout Mozambique with particular emphasis on children and women, the survey was population based and carried out nation wide. On selected indicators data was collected through interviews at household level using a questionnaire. Households were selected through stratified sampling of clusters taking population distribution into account. Reported results are weighted rates for which 95 per cent confidence intervals have been calculated. In the survey 6,433 households participated divided over 220 clusters in neighbourhoods in 220 localities in 55 districts in 10 provinces and the capital Maputo as a separate area. Data collection took place in July and August 1995. What follows is a descriptive analysis of the major fmdings as far as they are related to Mid- Decade Goals. Other aspects covered in the survey, but beyond the scope of the Mid-Decade Goals, have not been included in this report. Whenever possible, results are compared with data from other sources, such as Government reports and surveys. Demography An average household size of 4.4 persons is found. This supports the average of 4.8 reported by ONE (MPF 1993). The relative small household size indicates that the household as a socio- economic unit concerns "nuclear-families", i.e. parents and unmarried children, and that today the "extended-family" does not play an important role in the social organization of Mozambican society. This is important because, without Government providing social security benefits, the unemployed, poor, old-age and handicapped, depend entirely on family for economic support. The "nuclear-family" however, is a much narrower base and has more difficulty in providing support than the "extended- family". The gender ratio (males/females) is 88 per cent. This figure supports to certain extent the ONE projection of 94 per cent. Inequity between the sexes is mainly due to a shortage of males in the 10- 39 age group. This is probably caused by a combination of factors related to the recent war, migrant labour, and international refugees who did not return. Early age mortality calculation is possible because the sample population provided reliable and consistent data. Using the 1982 United Nations Life Tables for indirect estimation, the infant mortality rate (IMR) is found to be 123 per 1,000 live births and the under-five mortality rate (U5MR) is 191 per 1,000 live births. This outcome supports the 1995 IMR projection by ONE of 128 per 1,000 live births. Maternal mortality rate (MMR) calculation is beyond the scope of data from the MICS. However, the recently refined technique of indirect calculation of MMR estimates for Mozambique 4 I I I I I I I I I II I I I I I I I I I Multi-Indicator Cluster Survey- 1995, GOM-UNICEF 1,453 maternal deaths per 100,000 live births. At a 95 confidence the true value lies between 1.169 and 1,765 per 100,000 live births (UNICEF- WHO 1995). The sample population reveals a smaller number of under-five year old children than expected given the structure of the population pyramid. Taking the early age mortality into account, we would have expected at least 19 per cent of the population to fall in this age group. The fact that only 15 per cent is less than five years old is an indication for postponed fertility, a phenomenon not uncommon in populations living in extremely difficult circumstances. Expanded Programme on Immunization (EPI) RTH cards are used to calculate vaccination coverage. Only 63 per cent of the 12 - 23 months old children had RTH cards. However, regardless of the 'hard data' from RTH cards, mothers of 63 per cent of the children believe that their child is fully vaccinated. Many parents are apparently not well informed about vaccination. Health education is very much needed to correct this misunderstanding. The achievements of the health services in the BPI have resulted in coverage rates of under- one year old children of 58 per cent for BCG, 46 per cent for DPT3, 46 per cent OPV3, and 40 per cent for measles (95% CI = ±3 per cent). Although the coverage rates are still at a dangerous low level, EPI has improved significantly over the past five years and is catching up. When a child is not picked-up before the first birthday, chances are small that the child will ever receive vaccinations. Of the under-five year old children only 3 per cent receives BCG, 3 per cent DPT3, 4 per cent OPV3, and 8 per cent receives measles vaccination after the first birthday. Finally, the mothers of under one and under five year old children, are used to calculate the tetanus vaccination coverage rate. Respectively 61 per cent and 60 per cent of the mothers are vaccinated against tetanus by having ever in their life received S vaccinations, or have received at least two vaccinations before delivery of the last child. In summary, vaccination coverage is low for all antigens and provincial differences are big. There is a need for geographical adaptations in the health programme. For all provinces it is true that once a child is not vaccinated before the first birthday, chances are small that the child will ever receive vaccination at a later age. Moreover, it is important to note that those who take decisions with regards to vaccinating a child, i.e. the mothers, are often not aware of the bad vaccination status of their child, but instead believe that the child is fully vaccinated. Finally, comparing the rates of under one year old children with those of the under fives, it is clear that the effectiveness of the vaccination services has increased over the past five years . Control of Diarrhoeal Diseases (CDD) In August 1995 when data collection took place diarrhoeal disease in under-five year old children had a prevalence rate of almost 20 per cent. The treatment of 46 per cent of the diarrhoea cases had been carried out in line with WHO guidelines, i.e. giving increased liquids and food whether or not in combination with recommended rehydration fluids or ORS (95% CI = ±4 per cent). In 54 per cent of the cases this was not done. The worst provinces appeared to be Nampula, Niassa and Tete. 5 I I I I I I I I I I I I I I I I I I I I Multi-Indicator Cluster Survey- 1995, GOM-UNICEF Government statistics from health facilities show that in 1995 the prevalence of diarrhoeal cases seen by health workers is almost 5 per cent (MOH 1995). Comparing this statistic with the prevalence rate in population of almost 20 per cent, shows that one quarter of all cases are seen by health workers. On the other hand, three quarters of all diarrhoea cases are completely treated at home and never brought to the attention of health workers. Therefore, much emphasis has to be given to improving home treatment of diarrhoeal disease which, after malaria, is the second most important "killer disease" in children in Mozambique. Nutrition: control of Iodine Deficiency Disorders through salt iodization In 62 per cent of the households, salt is found to contain iodine (95% CI = ±2 per cent). Geographical differences deserve attention. In Maputo city 72 per cent of the salt tested, proved positive for iodine, while both Zambezia and Niassa just 15 per cent (95% CI = ±8 per cent). The emphasis actually put on salt iodization can be expected to rapidly improve this situation nation wide. Special attention, particularly in Niassa and Zambezia, will improve the situation drastically and increase the national rate found for this indicator. Nutrition: protein-energy malnutrition General malnutrition or underweight compared to age (WI A), is in 27 per cent of the under- five year old children. In 16 per cent of the children there is moderate and in 11 per cent severe underweight (95% CI = ± 1 per cent). Acute malnutrition or weight compared to height (W /H) is in 8 per cent of the under-five year old children. Five per cent is moderately under nourished, and 3 per cent severe (95% CI = ± 1 per cent). This is high for a national level and a significant contributor to infant and child mortality. The populated Zambezia province scores highest with 12 per cent moderate and 10 per cent severe W/H malnutrition. This observation is supported by scores on W/A showing that the general nutritional status of the under fives in Zambezia is among the weakest as compared to other provinces. However, also the provinces Gaza and Sofala show substantial W/H malnutrition, while in Gaza, Tete, and Cabo Delgado also WI A malnutrition rates are higher than the national average. Education Just over half of the 6 - 11 year old children is reported by parents to be enrolled in primary school, giving a net-enrollment-rate (NER) of 52 per cent (95% CI = ±3 per cent). The 1993 estimate by UNESCO is 46 per cent based on information provided by education facilities (UNESCO 1995). The MOE however, reports for 1995 a NER of 34 per cent. Provincial differences show that the five southern provinces score higher than the national average, while all northern provinces score lower. Provinces further away from the capital have a lower NER. There is almost no difference in NER with regards to gender. Nationally SO per cent of the 6 - 11 year old girls enroll in primary school compared to 54 per cent of the boys in the same age group. Also at provincial level differences are not significant. 6 J I I I I II :I I I I I II I I I ' II I I I I I I Multi-Indicator Cluster Survey - 1995, GOM-UNICEF In none of the provinces many children start school at the age of 6. The national primary school entrance rate (PSER) is 22 per cent (95% CI = ±3 per cent), and even in Maputo City not more than 35 per cent of the 6 year olds enroll in the first grade of primary school (95% CI = ± 8 per cent). Nationally, less 6 year old girls than boys enroll in primary school grade one, 18 per cent and 26 per cent respectively. This gender difference is not consistent in all provinces. There are provinces where a much bigger proportion of the 6 year old boys enroll than of the 6 year old girls, such as in Gaza, Manica and Zambezia, but also to a certain extent, Maputo city. However, there are also provinces where the opposite occurs, such as in Sofala and Tete. Further studies at provincial level are needed to reveal the causes of these differences. A very high proportion of children in school is older than expected in primary education. Not less than 39 per cent of the primary school children is 12 years or older (95% CI = ±2 per cent). This supports calculation from Government data resulting in 41 per cent. There are more boys than girls in this category. Not less than 42 per cent of all the boys enrolled in primary school is 12 years or older compared to 34 per cent of all the girls in primary school. This difference is not consistent in all provinces. In Cabo Delgado, Nampula, Zambezia, Tete, lnhambane and in Maputo City, the percentage of boys enrolled in primary school who are 12 years or older, is higher than that of girls. Only Gaza and Sofala have percentages of girls enrolled in primary school who are 12 years or older, which are higher than that of boys. Further studies at provincial level are needed to explain these differences. Although the results of the survey show that there is a bad situation in the education sector nation wide, the reality is probably even worse. The indicator used in the survey is "enrollment rate" which reflects how many children are registered and reported by parents as "going to school". It does however, not mean that the child really attends daily classes. Case studies and information from the field indicate a serious discrepancy between "enrollment" and "attendance". Water and Sanitation Sixty three per cent of the respondents report to have drinking water at walking distance, i.e. a tap, handpump or well in the house or at a distance of about 500 meter from the house (95% CI = ± 4 per cent). Provincial differences are big, ranging from 97 per cent in Maputo city to just 27 per cent in Inhambane (95% CI = ± 10 per cent). Assessment of quality and cleanliness of water from the tap and of containers in which water is carried home, is beyond the scope of this survey and therefore not considered. An average of 54 per cent of the respondents report to have access to hygienic sanitation facilities (95% CI = ± 4 per cent). The results vary much between geographical areas, ranging from 99 per cent in Maputo city to 5 per cent in Zambezia (95% CI = ± 10 per cent). Given the recent history of war and destruction, the availability of water and sanitation facilities could have been much worse. Although this is true, the health status of women and children can not be expected to improve equally fast as the expansion of water and sanitation facilities because much has still to be done in terms of utilization of these facilities. 7 I I I I I I I I I I I I I I I I I I I I I Multi-Indicator Cluster Survey- 1995, GOM-UNICEF II. SUMMARY OF MICS RESULTS »EM<>~It •·••••••••••• •••·•••• > t> ··········· > . { . . < \ .•. • ••••• • ••• •••••••• . :.: . ·.·. . . · .:. Population distribution by sex (%): Male 47 Female 53 % of Population in selected age groups: < 1 Year old 3 < 5 Years old 15 Women in child bearing age (15-49) 26 Infant Mortality Rate (IMR) 123 Under 5 Mortality Rate (U5MR) 191 Average household size 4.4 ~~\4 ~~· ·· < ············ ··••• ·• } · . > ) .•. < ····· ·•••·••• ) •. ·.·• ••·••· < < ······; . . . . . \ < ·•·' .•. ' . < .) . •·.·•··· .•.• ···••••••· . . ··. •····· >/ . . < ) ; •··•• . ······ . Vaccination Coverage: % Children 12-59 months vaccinated before their 1st birthday. (Based on RTH card) BCG 42 DPT3 34 OPV3 33 Measles 29 Vaccination Coverage: % Children 12-23 months vaccinated before their 1st birthday. (Based on RTH Card) BCG 58 DPT3 46 OPV3 46 Measles 40 %Children 12-59 mths. with RTH cards. 63 Vaccination Coverage: %Children 12-23 months with complete vaccination. 63 Based on mother's opinion about vaccination status. TT Coverage: %Mothers who received two Tetanus vaccinations during last pregnancy or five TT vaccinations during life. Mothers with children 0-11 months 61 Mothers with children 0-59 months 60 8 I I I II il I I I I II I I I I I I I I I I I Multi-Indicator Cluster Survey- 1995, GOM-UNICEF Treatment of diarrhoea: ORT use. % Children 0-59 months with diarrhoea in two weeks prior to survey treated with ORS or home recommended fluids. (pre- 1993 definition) % Children 0-59 months with diarrhoea in two weeks prior to survey treated with increased fluids and continued feeding. Use of iodized salt: % Households using iodized salt Malnutrition : % Children 0-59 months old Wastedness : Weight I Height Moderate ( -3 SO < -2 SO) Severe ( Below -3 SO) General Malnutrition: Weight I Age Stuntedness : Net Enrollment Rate (NER) : Primary School Entry Rate (PSER): Over-Age Children in Primary School: Moderate ( -3 SD < -2 SD) Severe (Below -3 SD) Height I Age Moderate ( -3 SD < -2 SD) Severe ( Below -3 SD) % Of 6--11 yrs old children who are currently enrolled in primary school Male Female % Of 6 yrs old children who are currently enrolled in grade 1. Male Female % Of children currently enrolled in primary school who are > = 12 Yrs old. Male Female % Households with access to safe drinking water % Household with access to latrines 9 83 46 62 5 3 16 11 24 31 52 54 50 22 26 18 39 42 34 63 54 I I I I I I I I I I I I I I I I I I Multi-Indicator Cluster Survey- 1995, GOM-UNICEF 1. INTRODUCTION In 1990 at the World Summit for Children, 158 countries committed themselves to proceed with the development of National Programmes of Action for Children (NPAC). Mozambique participated in the Summit but, due to circumstances of war, has been delayed in finalizing the draft NPAC. To date the implementation of many of its components has started in UNICEF supported programmes in health, nutrition, ec!ucation, water, sanitation, and community development. To measure progress on achieving Goals set for the Mid-Decade, a survey was designed which included major social indicators and covered all programmes. It is the first nation-wide survey since 1980, when a census was held. The survey is population based, i.e. data is collected directly from the population at household level, and not from facilities providing services such as schools, health centers, etc . Results can be used for updating the situation analysis for the NPAC and can serve as reference material. Through further analysis and comparison with data about availability of services, service delivery can be planned where they are needed most. From an international point of view, this multi-indicator-cluster-survey or "MICS" is carried out globally in many countries simultaneously, applying the same method of investigation, and addressing the same subjects. International comparison of survey results is therefore possible ( 1 ). The methodology of cluster sampling is used . This method is recommended by WHO and UNICEF and has been tested and refined in previous surveys in various countries with good results in measuring achievements in EPI and other programmes. The survey was coordinated by the Ministry of Planning and Finance (MPF) and in particular by the National Department of Statistics (DNE). DNE also took responsibility for the implementation which was carried out in close coordination with the Ministry of Health. 2. PURPOSE AND OBJECTIVE The survey is a base-line study providing reference data. It is meant, in the first place, as a tool for planning, and not as a scientific study for academic reasons. The purpose is to obtain an accurate estimate about the health, nutrition, education, water and sanitation situation throughout Mozambique with particular emphasis on the situation of children and women. The survey results are to assist national and provincial governmental authorities and other institutions who plan and monitor rehabilitation and development of social services in Mozambique. The results give an overview of the situation at national level, but allows also for comparison between provinces. However, it is beyond the scope of this survey to picture the situation at district and lower administrative levels. The survey is a descriptive study. It reflects the actual situation as it was found during the time of data collection in August 1995, but it does not consider correlations to explain the findings. 1 Other examples as the World Fertility Survey (WFS) and the Demographic Health Survey have similar advantages as being comparable in terms of method and subject. 10 I I I I I I I I I I I I I I I I I I I I I Multi-Indicator Cluster Survey- 1995, GOM-UNICEF 3. METHODOLOGY A series of highly relevant indicators have been selected to describe the situation influencing the well being of children and women. Indicators have been identified in the fields of health, education, nutrition, water and sanitation which have proven to be "valid", i.e. they are reliabie measuring tools, as well as "sensitive", i.e. quickly reacting on changes in the situation. The situation in the health sector is measured through infant mortality rate (IMR), under-five mortality rate (U5MR), and vaccination coverage through BPI. The use of oral rehydration treatment (ORT) is measured as part of the control of diarrhoeal diseases (COD) project. Nutrition is measured through salt iodization at household level as part of the control of iodine deficiency disorders (IDD) and through nutritional status using three indicators of protein-energy-malnutrition (PEM). The situation in education is measured through calculating various enrollment rates in primary school services. Finally, environmental conditions are included by calculating the percentage of population with access to safe drinking water and hygienic sanitation facilities. The nutrition indicators are immensely important for understanding not only the nutritional situation, but also and in panicular the overall status of well being of children. More and more studies prove the relationship between a population's health, educational level and sanitary conditions, showing how nutritional status in children can serve as an indicator correlated with morbidity and mortality. From reviewing 21 nutrition surveys in Africa and Asia, it is concluded that "the present results indicate that somewhere between 20 - 75 per cent of child deaths are statistically attributable to anthropometric deficits . " ( 2 ). Special attention is therefore given to the nutrition indicators. 3.1 Questionnaire design A questionnaire is the most appropriate tool for collection of data in a big descriptive survey of which the results have to be generalized. Most questions asked in the MICS had been pre-tested and used before in a similar survey in Maputo city and some rural areas ( 3 ) . The questionnaire used in the MICS is attached as Annex A. Vaccination and child age data were during the interviews retrieved from the road-to-health (RTH) cards, if available. The coverage rate in vaccination is solely based on RTH card data except vaccination of mothers against tetanus. Anthropometric measurements were carried out with portable salter scales and light weight (locally made) measuring boards. To measure iodine in salt households, the UNICEF test-kits were made available to the interviewers and their supervisors. 3.2 Selection and training of interviewers and supervisors DNE of the MPF and the MOH selected 40 interviewers and 10 supervisors from among their personnel at central and provincial level. During two weeks interviewers and supervisors were brought together in Maputo, and trained in using the questionnaire, selecting households, and in solving logistical and administrative problems they were expected to face during field work. The questionnaire, and interviewers, were tested after the training by way of carrying out a pilot survey among households in Maputo city. Pelletier 1994 Lopes & Santos 1995. 11 ,I I I I I I I I I I I I I I Multi-Indicator Cluster Survey- 1995, GOM-UNICEF 3.3 Sampling Registration of voters for the 1994 elections is used as sampling frame for the survey. Since 1980 no census has been held in Mozambique, no vital statistics have been collected and neither does there exist another nation-wide population registration except for voters registration for the elections held in October 1994. This registration shows the number of people who were listed for voting in a particular province, district, sub-district or locality. It has been estimated that approximately 80 per cent of the population eligible for voting, actually registered. It is unknown who the missing 20 per cent non-voters are, where they live and if they are mainly illiterates, poor, rural, job-less Mozambicans or, if the majority of them are urban middle class, or peasants, etc. However, it is assumed that the "missing 20 percent" is equally distributed over the country and over all socio- economic categories in society. The voters registration has therefore been considered the best possible choice to base the sampling on. From all ten provinces and from Maputo city, equally sized samples were drawn. Based on the number of voters in each province and in Maputo city, "weights" were calculated for every sample. These weights were used to calculate national averages from the outcomes at provincial level and Maputo city. ( 4 ) See Annex B for provincial and Maputo city weights. Five districts were randomly selected in each province applying the concept of Probability Proportional to Size (PPS). Four localities were randomly selected in every chosen district again using PPS. Per locality one neighbourhood, aldeia (rural) or bairro (urban), was selected at random. Finally, when the interview team arrived, the supervisor selected randomly in the neighbourhood one house as starting point to interview heads of household in the neighboring 30 houses. Such group of households is in the survey referred to as a "cluster". Unfortunately, before field work started, no information about population size of aldeias or bairros was available and the decision had to be taken that only one cluster could be selected at random per locality, irrespective its size. This made weighing of every cluster necessary. ( s) These weights have been used to calculate the survey results for provincial level. ( ' ) A detailed overview is given in Annex C. 4 6 National rate = 1: provincial (rate x weight) For cluster weights was 1 + P calculated where P is the probability of a household to be selected. P={(5 x A) + B} x {(4 x C) + A} x {1 + D} x {30 + E} A = number of voters in a particular district B = number of voters in a particular province C = number of voters in a particular sub-district (locality) D = number of aldeias or bairros in a particular sub-district (locality) E = number of households in a particular aldeia or bairro Provincial rates were calculated from cluster rates by I:{Xi-:i + Yi-:i ) * Wi-:i } Another formula which gives slightly different results could have been I:{Xi-j * Wi-j}+I:{Yi-j"' Wi-j} Both formulas are correct ways of calculating. X = cluster sc{)re. Y = number of people exposed in cluster. W = provincial cluster weight. 12 - I I I I I I I I I I I I I I I I I I I Multi-Indicator Cluster Survey - 1995, GOM-UNICEF A sample size of 3690 households would have been sufficient to calculate national estimates with 95 per cent chance that the margin of error would be 5 per cent or smaller. In order to have a 10 per cent margin of error for provincial level estimates, 467 households were needed. Compensating for losses during data collection it was decided to increase the sample size at provincial level to 600. In summary, from 11 areas 55 districts have been selected, from where 220 localities and 220 clusters in aldeias and bairros (rural and urban neighbourhoods)with 6600 households were chosen. They have become the survey population. 3.4 Data collection In every selected household, the head of the house was interviewed, and in case of his or her absence, the one next in charge. Answering questions and filling in the questionnaire took usually about 30 - 40 minutes including anthropometric measurement of under-five year old children. Starting with sampling and fieldwork preparation in Maputo in May/June 1995, the interviewers and supervisors worked in the conununities in July and August. These months are in the dry season which facilitated access. The circumstances under which it was carried out were extremely difficult because of geographical distances, problematic conununications, scarcity in transport facilities, and the almost total absence of basic population data. In some cases places were inaccessible due to land-mines or refusal by population based on cultural beliefs. The size of the survey gave an extra dimension to the difficulties faced during implementation. Even so the difficulties in fieldwork, a total of 6433 households were actually interviewed of the originally planned 6600. 3.5 Data processing Data entry and cleaning procedures were carried out centrally in Maputo by DNE using the IMPS version 3.1 programme. In close cooperation with DNE, data were analyzed at UNICEF where the draft report was written. For data analysis, definitions are applied as spelled out in appendix 4 of the UNICEF handbook for multiple cluster surveys ( 7 ) • In Annex E all definitions are sununarized. Based on these definitions calculations are made using dBase 4.0 and RR 5.0, except for nutrition data which are analyzed in the EPI-Info 6.0 programme. All results in this report, such as coverage rates, are "weighted results". This means that the size of the voters population in a particular area, is taken into account when calculating results. For example, to calculate national estimates, the 20 sub-samples representing the province of Nampula with over 1,3 million voters, is given almost three times more "weight" than the 20 sub-samples representing the province of Inhambane with less than 0.5 million voters. 7 UNICEF, Evaluation and Research Office, 1995 13 I I I I I I I I I I I I I I I I I I I I Multi-Indicator Cluster Survey- 1995, GOM-UNICEF 4. ANALYSIS AND RESULTS Only a part of the available data is analyzed to obtain the results presented here. Analysis is limited to data about selected indicators for Mid-Decade Goals. Not included are for example, data about house construction, employment, and adult literacy. Neither is the correlation between findings analyzed. The fmdings are presented in rates. Margins of error are calculated for every rate with 95 per cent confidence. For example, the national measles vaccination coverage rate is found to be 40 per cent with 95% CI = ± 3 per cent. This means that the we are for 95 per cent sure that the true coverage rate lies between 37 per cent and 43 per cent. The national rates are given with their individual 95%CI, the provincial rates are given with an average provincial 95%CI. 4.1 Demography The graph in Annex F shows the sample population divided by gender and age. The sample is composed of 29,664 people with an average household size of 4.4 persons. ( 8 ) There is a total of 13,916 males and 15,748 females. The gender ratio (males/females) is 88 per cent due to lack of males in the 10- 39 age group. ( 9 ) Calculation of early age mortality rates is based on child survivorship per age group of mothers. The 7,355 women in the sample who had given births, reported a total of 23,599 children born alive and 19,016 surviving. Depending on the age group of the mother, sex ratio of live horns varies only between 0.0939 and 1.040. This is a minimal variation which indicates high consistency in answers given by the respondents. ( 10 ) The average sex ratio of the zero-year olds is 0.973. This is very close to 1.012, the ratio calculated from the projected 1995 population of zero year old children. ( 11 ) It can be safely concluded that the sample population provided reliable data allowing mortality rate calculation. The 1982 UN Model Life Tables are used for this purpose. An average mortality rate is caculated for the last five years from the "general" model (Annex G). The infant mortality rate (IMR) over the last five years is found to be 123 per 1,000 live births and the under-five mortality rate (U5MR) 191 per 1,000 live births. ( u) 9 10 11 12 This finding close to ONE's 1991 average of 4.8 (ONE 1993) ONE projection for 1995 shows a comparable ratio of 94 percent. Mortality and migration are assumed to cause this inequality between the sexes. (ONE 1994) See Griffith Feeney 1976 and 1980. ONE 1994 This outcome supports the ONE projected 1995 IMR of 128 per 1,000 live births based on 1980 census data. Both ONE and MICS mortality rates are based on indirect estimation. Although this method is less applicable on small samples, it is worth noting that for Maputo an IMR of 72 is found which equals the IMR of 70 reported for Maputo by Lopes & Santos, and is close to ONE estimate of 87 per 1,000 live births (ONE 1991; Lopes & Santos 1995) 14 I I I I I I I I I I I I I I I I I \I Multi-Indicator Cluster Survey- 1995, GOM-UNICEF 4.2 Vaccination (Tables 1, 2 and 3) Analysis of vaccination data of the 12-59 months age group is used to calculate the effectiveness of the health services in EPI over the last 5 years. It is the proportion of new borns every year, who are "picked-up" by the health services and receive vaccination on time, i.e. before their first birthday (table 1). In addition, the 12-23 months age group is analyzed (table 2). This shows the actual coverage rate, i.e. the performance of the health services in BPI during the 12 months before the survey took place. Finally, mothers of under one and of under five year old children, are used to calculate the tetanus vaccination coverage rate (table 3). With the exception of TT coverage, only those cases which had a road-to-health (RTH) card with properly documented vaccination data are considered. This increased accuracy of the data significantly and improved reliability of the end-results. Table 1 shows vaccination coverage rates of under five year old children who are vaccinated before their first birth day. The national rates are 42 per cent for BCG, 34 per cent for DPT3, 33 per' cent for OPV3 and 29 per cent is vaccinated against measles (95% CI = ± 3 per cent). Concerning only 53 per cent of the children, respondents have RTH cards. Rather alanning is that 60 per cent of the children has mothers who are of the opinion that their children are fully vaccinated (95% CI = ±3 per cent). Provincial differences are enormous. For example, only 5 per cent of the under fives in Cabo Delgado received 3 doses OPV compared to 67 per cent in the capital Maputo.(13) Generally, the vaccination rates are highest in the provinces Gaza, Sofala and Maputo including the capital, and lowest in Zambezia, Cabo Delgado and Niassa. The other provinces have rates close to the national average. Table 1 shows how effective the health services are in picking up new horns and vaccinate them timely, i.e. before their first birthday. This does not mean however, that children cannot be vaccinated when they are two or three years old. The coverage rates of under-fives, including those vaccinated after their first birthday, are 45 per cent for BCG, and 37 per cent for DPT3, for OPV3, as well as for measles. These rates do not differ substantially from the rates in table 1. It means that once a child is not picked up by the health services before the first birthday, chances are small that the child will ever be vaccinated. 13 Similar results were found by Lopes & Santos (1995) for Maputo city in 1994 with 69 per cent for DPT3 and OPV3, and 81 per cent of the children had RTH cards. 15 I I I I I I I I I I I I I I I I I I I I I Table 1: Province Maputo City Maputo Gaza Inhambane Sofala Manica Tete Zambezia Nampula Multi-Indicator Cluster Survey- 1995, GOM-UNICEF Percentage of under-five year old children who received vaccinations before their first birthday, and mother's opinion about vaccination status. Vaccination Coverage Children Total Based on RTH Card Data Mother's with Children opinion Cards 12-59 Mtbs (%) BCG DPr3 OPV3 MSL Children (%) (%) (%) (%) Completed Vaccination (%) 346 69 67 67 62 87 80 288 70 42 42 34 93 76 391 62 51 51 47 83 77 285 44 37 37 30 79 48 401 62 51 50 40 81 67 328 43 36 36 35 62 48 399 40 34 32 26 59 47 150 21 14 14 10 22 31 319 45 39 39 35 71 61 Cabo Delgado 321 25 6 5 8 30 31 Niassa Mozambique Source: 378 26 18 17 15 44 40 3606 42 34 33 29 60 53 Multiple Indicator Cluster Survey, July/August 1995, Mozambique, GOM ·UNICEF National rates 95% CI = ±3 per cent and provincial rates 95% CI = ± 10 per cent. In the following table the actual achievements are analyzed according to international standards, by calculating coverage rates for the 12- 2.3 months age group. National rates are 58 per cent for BCG, 46 per cent for DPT3, 46 per cent for OPV3 and 40 per cent for measles (95% CI = ±3 per cent). These coverage rates are significantly better than those for the under-five age group. This means that in recent years the health system improved and more children are picked-up for vaccination than in the past. Although the coverage rates are still at a dangerous low level, the EPI is progressing and catching up. 16 I I I I I I I I I I ~I Table 2: Province Maputo City Maputo Gaza lnbambane Sofala Manica Tete Zambezia Nampula Multi-Indicator Cluster Survey- 1995, GOM-UNICEF Percentage of 12-23 Months old children who received vaccinations before their first birthday, and mother's opinion about vaccination status. Vaccination Coverage Children Total Based on RTH Card Data Mother's with Children opinion Cards 12-23 Mths (%) BCG DPT3 OPV3 MSL Children (%) (%) (%) (%) Completed Vaccination (%) 116 80 77 77 72 92 8S 88 67 33 33 28 88 71 136 73 66 66 62 94 74 90 70 61 62 Sl 71 77 104 65 59 59 44 70 70 96 62 48 48 48 65 66 124 56 47 43 34 52 59 51 31 21 21 24 34 37 94 71 64 63 51 78 73 Cabo Delgado 87 47 9 8 11 29 49 Niassa Mozambique Source: 99 43 32 30 23 47 51 1085 58 46 46 40 63 63 Multiple Indicator Cluster Survey, July/August 1995, Mozambique, GOM-UNICEF National rates 95% CI = ±3 per cent and provincial rates 95% Cl = ±10 per cent. Tetanus Vaccination Protection of children from tetanus immediately after delivery is achieved by vaccinating the mother at least two times before delivery of the child, or by seeing to it that the mother has received ever in her life five doses and therefore is fully vaccinated against this disease. In table 3 the coverage rates are given based on verbal information from mothers with under one as well as from mothers with under five year old children. The rates have to be considered with caution because data are based on verbal information from the mother and could not be checked against 'hard' data from RTH cards. Nationally 61 per cent and 60 per cent coverage respectively, are found for mothers with under-one year old children and mothers with under-five year olds (95%CI ±3 per cent). The lowest coverage rates are in Tete, Niassa and Cabo Delgado. The provinces Sofala and Maputo including the capital, score highest on this indicator, and also Nampula scores above average. 17 I I I I I I I I I I I I I I I I I I Table 3: Province Maputo City Maputo Gaza lnhambane Sofala Manica Tete Zambezia Nampula Multi-Indicator Cluster Survey- 1995, GOM-UNICEF Percentage of mothers who had received two tetanus vaccinations during last pregnancy or five vaccinations during life Total Total TT Coverage Mothers w/ Mothers w/ Children Children 0·11 Mths 0-59 Mtbs Mothers WI Children Mothers W /Children 0-11 Mths. 0-59 Mtbs. 131 415 73 77 104 362 74 80 168 489 64 58 104 360 61 67 111 488 82 79 138 419 60 62 130 500 41 49 41 187 58 40 102 383 64 67 Cabo Delgado 205 409 41 41 Nfassa Mozambique Source: 163 456 52 60 1397 4468 61 60 Multiple Indicator Cluster Survey, July/August 1995, Mozambique, GOM-UNICEF National rates on TT coverage of mothers with under one year olcls 95% CI = ±4 per cent, and of mothers with under fives 95% CI = ±3 per cent. The provincial rates are both with 95% CI = ± 12 per cent. With regards to EPI, one can conclude that coverage is low for all antigens and provincial differences in coverage are big. It is obvious that there is a need for geographical adaptations in EPI. Once a child is not vaccinated before the first birthday, the chances are small that the child will ever receive vaccination at a later age. Moreover, it is important to note that those who take decisions with regards to vaccinating a child, the mothers, are often not aware of the bad vaccination situation, instead they believe that their child is fully vaccinated. Finally, comparing the rates of under one year old children with those of the under fives, it is clear that effectiveness of the vaccination services improved over the past five years. 4.3 Oral Rehydration Therapy (Table 4) This indicator is measured by asking if the child had diarrhoea on the moment of the interview or during the preceding two weeks. If the answer was positive, questions were asked about food and drinks to determine if the child had been treated as recommended by WHO standards for CDD. 18 I I I I i l I I I I I I I I I I I I I I I I Table 4: Province Maputo City Maputo Gaza lnhambane Sofala Manica Tete Zambezia Nampula Multi-Indicator Cluster Survey- 1995, GOM-UNICEF Percentage under five year old children with diarrhea receiving ORT and/or increased liquids and food. Treatment of Diarrhoea Total Children (0-59 Mths) with Diarrhoea in last Child Treated with Child Treated with two weeks ORS or Home Increased Liq~ds Recommended F1uids &Food (%) (%) 77 95 68 49 92 50 94 65 59 40 83 64 94 86 45 56 94 55 136 74 42 42 89 48 107 79 30 Cabo Delgado 74 77 47 Niassa Mozambique Source: 82 82 30 851 83 46 Multiple Indicator Cluster Survey, July/August 1995, Mozambique, GOM-UNICEF National rates on ORT use have a 95% Cl = ±4 per cent and provincial rates are with 95% CI = ±10 per cent. Table 4 shows national and provincial results. Not less than 851 children were reported as diarrhoea cases indicating a prevalence rate of almost 20 per cent. ( t•) This prevalence rate is high, particularly because the survey was not conducted in a season when diarrhoeal diseases are frequent. It shows once more how poor the health condition is of children in Mozambique. In 83 per cent of the diarrhea cases in under-fives, mothers said to have given rice water, maize porridge, tea or coconut milk (95% CI = ±4 per cent). These are recommended fluids in relation to diarrhoea treatment. Moreover, in 46 per cent of the diarrhoea cases the quantity of liquids and food given to the child, was increased (95% CI = ±4 per cent). However, 54 per cent of diarrhoea cases does not receive such treatment which increases considerably the risk of dying. The provinces Inhambane and Gaza as well as Maputo City show the most positive results in diarrhoea treatment, while Nampula, Niassa, Tete and Zambezia are the worst. 14 Prevalence calculated from health facility data is almost 5 per cent in 1995 (MOH 1995). This means that one quarter of all diarrhoea cases is seen by health workers. 19 I I I I I I I I I I I I I I I I I I I Multi-Indicator Cluster Survey- 1995, GOM-UNICEF 4.4 Nutrition (Tables 5 and 6) In the nutrition part of the survey, three indicators are used and results are given in tables 5 and 6. These are respectively, the use of iodated/iodized salt in households and protein-energy malnutrition. Vitamin-A has been excluded from the survey since no programme on vitamin-A supplementation, fortification or dietary education is implemented so far. A population based study on vitamin-A deficiency was beyond the scope of the MICS, but should be considered for the future. Recent studies conducted elsewhere show 30 to 54 per cent decrease in mortality of under five year old children when vitamin A is given. ( 15 ) Salt iodization <Table 5) The use of iodized salt was measured by asking in every household a sample of the salt they use. The sample was tested during the interview with the UNICEF testing-kit. Table 5 gives the national and provincial results. Of all households 98 per cent uses salt. In 62 per cent of them, salt contains iodine (95% CI = ±2 per cent). The geographical differences deserve attention. In Maputo city 72 per cent of the salt tested, proves positive for iodine, while both in Zambezia and in Niassa just 15 per cent (95% CI = ±8 per cent). Table 5. Percentage households using iodized/iodated salt Household Province Total Households Using Salt (%) Iodized Salt (%) Maputo City 606 97 72 Maputo 602 99 96 Gaza 606 100 94 Inhambane 644 99 90 Sofala 540 98 53 Manica 548 98 83 Tete 570 97 76 Zambezia 508 99 15 Nampula 601 98 78 Cabo Delgado 599 98 61 Niassa 609 97 15 Mozambique 6433 98 62 Source: Multiple Indicator Cluster Suney, July-August 1995, Mozambique, GOM-UNICEF. National rates 95% CI = ±2 per cent and provincial rates 95% CI = ±8 per cent. IS Scrimshaw 1994. 20 I I I I I I I I 'I I I I I I I I I I I I I Multi-Indicator Cluster Survey- 1995, GOM-UNICEF Niassa is known for having a high prevalence of iodine deficiency disorders (IDD). The prevalence of IDD in Zambezia is reportedly lower which could be explained by intake of other food stuffs rich in iodine. That such food is scarce in land-locked province of Tete is to be expected. It is therefore positive to find that 78 per cent of the salt in households in Tete tested positive on iodine.(1') Protein Energy Malnutrition (Table 6) Protein-energy malnutrition (PEM) is used to measure nutritional status applying NCHS/WHO standards expressed in standard deviations from the mean (SO). In the analysis all three indicators are used. Weight for height (W/H), usually called "acute malnutrition", is very useful because it is a sensitive indicator showing the degree of vulnerability and wastedness. The indicator height for age (HI A) shows the proportion of children who become stunted due to chronic malnutrition. Weight for age (W/A) gives an overall picture of the nutritional status, but does not differentiate between acute and chronic malnutrition. ( 17 ) Cut-off points of -2SD and -3SD are maintained to differentiate between "moderate" and "severe" malnutrition, making comparison with other populations possible. For example, recent reviews of the relation between malnutrition and mortality show that when 5 per cent of the under-fives has a W/H score below -2SD, the mortality rate is already elevated. ( 18 ) Although all under fives in the sample were measured, many cases were 'flagged' and excluded from further analysis. For example, a 15 months old child with a height of 1 meter. Fortunately, 'flagged' cases are spread equally over the sample. Results presented here concern only valid cases. Reliability of the results is therefore strong and the outcomes have to be considered seriously. The national W IH score of 5 per cent moderate and 3 per cent severe malnutrition is high (95%CI= ± 1 per cent). The main contributor is the populated Zambezia province with 12 per cent moderate and 10 per cent severe malnutrition, and to a lesser extent the provinces Gaza and Sofala which have 8 per cent moderate malnutrition (95 %CI = ± 5 per cent). Zambezia in particular asks for attention because 22 per cent (12 + 10) of the children, that is one of every five, is under nourished. This observation is supported by the scores on WI A showing the nutritional status in general of the under fives with Zambezia, but also Tete and Cabo Delgado being the weakest provinces showing WI A malnutrition rates above average. The HI A rates indicate growth stuntedness referring to malnutrition of long duration which is, as expected, prevalent in all provinces. ( 19 ) 16 17 18 19 The data on iodized salt have to be interpreted with care. The tool available for testing if salt actually contained iodine, was the UNICEF test kit. Although the application of this test kit is very simple, it remains uncertain whether all interviewers did the testing in the proper way. Jelliffe & Jelliffe 1989. Yip & Scanlon, 1994 With the exception of nutrition surveys carried out by MSF-B in Tete, MSF-CIS in lnhambane, Gaza, Manica and Tete, no population based survey data are available. These surveys however, are district level studies and comparison with data from the MICS is not possible. 21 I I I I I I I I I I I I I I I I I I I I I Table 6: Province Maputo City Maputo Gaza Inhambane Sofala Manica Tete Zambezia Nampula Cabo Delgado Nfassa Mozambique Multi-Indicator Cluster Survey- 1995, GOM-UNICEF Percentage moderately and severely undernourished under five year old children in tenns ofwastedness (W/H), general malnutrition (W/A) and stuntedness (II! A) Valid Cases Nutrition Level Indicators Total Children <5 Yrs Will(%) W/A (%) H/A (%) Will W/A HIA -2SD Below -2SD Below -2SD Below > > > -3SD -3SD -3SD -3SD ·3SD -3SD 441 243 348 242 3 0 8 4 18 18 373 176 303 176 3 0 15 2 19 15 514 352 383 351 8 0 25 2 32 18 373 289 318 281 2 0 12 11 29 27 489 384 420 378 8 0 14 9 34 19 425 250 295 247 3 3 20 4 20 32 505 395 436 380 3 0 21 10 23 35 189 132 143 127 12 10 22 28 21 53 396 301 321 294 1 2 10 8 23 26 417 285 351 265 4 1 22 8 25 33 464 318 329 297 3 1 16 10 27 30 4586 3125 3647 3038 5 3 16 11 24 31 Source: Multiple Indicator Cluster Survey, July/August 1995, Mozambique, GOM-UNICEF. National rates 95% CI = ±1 per cent and provincial rates 95% CI = ±5 per cent. 4.5 Education (Table 7) Data on primary education concern what parents reported about enrollment of their children in school. Whether the children are formally enlisted and if they actually attend classes, was beyond the scope of the survey. "Net-enrollment rate" (NER) is the percentage of 6 - 11 year old children who enrolled in primary school. "Primary school entry rate" (PSER) is the percentage of 6 year olds who enrolled in grade one, and "older age children" (OAC) is the proportion of all children currently enrolled in primary school who are 12 year or older. Just half of the 6 - 11 year old children is actually enrolled in primary school giving a net- enrollment-rate (NER) of 52 per cent (95% CI = ±3 per cent). ( 20 ) Provincial differences show 20 Based on data from the educational sector, UNESCO estimated the 1993 NER 46 per cent and the Ministry of Education reports for 1995 not more than 34 per cent. 22 I I I I I I !I I I II I I I I I I I I I I I Multi-Indicator Cluster Survey- 1995, GOM-UNICEF that Gaza, lnhambene, Sofala, Manica and Maputo including the capital, are above the national rate and that Tete, Zambezia, Nampula and Cabo Delgado are below. Provinces further away from the capital have a lower NER. There is almost no difference inNER with regards to gender. Nationally 50 per cent of the 6 - 11 year old girls enroll in primary school compared to 54 per cent of the boys in the same age group. Also at provincial level differences are not significant. In none of the provinces many children start school at the age of 6. The national PSER is 22 per cent (95% CI = ± 3 per cent), and even in Maputo City not more than 35 per cent of the 6 year olds are enrolled in grade one of the primary school (95% CI = ±8 per cent). Table 7: Enrollment of cbildren in primary school. Total Total Total Primary School Enrollment Rates Chlldren Children Children in Province Prhnary School Primary School Age Entry Age School NER (%) PSER {%) OAC (%) (6-11 Yrs) (6 Yrs) T T T M F T M F T M F T Maputo City 599 100 772 76 76 76 40 33 35 41 34 37 Maputo Prov. 566 101 644 74 71 72 13 14 14 34 32 33 Gaza 637 95 649 62 67 63 41 8 25 32 43 39 Inhambane 547 93 582 63 55 58 22 19 19 43 35 43 Sofala 501 83 492 65 57 60 17 30 19 36 49 43 Manica 435 80 425 64 54 60 41 25 36 35 36 34 Tete 526 120 398 43 42 42 17 27 18 52 36 42 Zambezia 321 43 198 46 42 43 28 8 19 45 26 37 Nampula 478 90 295 48 49 48 25 17 24 47 30 41 Cabo Delgado 372 75 223 44 32 38 25 26 25 41 29 37 Niassa Mozambique Source: NER: PSER: OAC: 617 146 379 39 35 37 14 12 12 so 47 48 5599 1026 5057 54 so 51 16 18 21 42 34 39 Multiple Indicator Cluster Survey, July/August 1995, Mozambique, GOM-UNICEF. National rates 95% CI= ±3 per cent and provincial rates 95%CI= ±12 per cent. Net-enrollment rate. Percentage of 6 - 11 year old children currently enrolled in primary school; Primary school entry rate. Percentage of 6 year old children currently enrolled in grade 1; Older-age children. Percentage of children enrolled in primary school who are 12 years or older. 23 I I I I I I I I I I I I I I I I I Multi-Indicator Cluster Survey- 1995, GOM-UNICEF Nationally, less 6 year old girls than boys enroll in primary school grade one, 18 per cent and 26 per cent respectively. This gender difference is not consistent in all provinces. There are provinces where a much bigger proportion of the 6 year old boys enroll than of the 6 year old girls, such as in Gaza, Manica and Zambezia. However, there are also provinces where the opposite occurs, such as in Sofala and Tete. Further studies at provincial level are needed to reveal the causes of these differences. A high proportion of children is older than what is expected in primary education. So much as 39 per cent of the primary school children is 12 years or older (95% CI = ±2 per cent).( 21 ) In Niassa province even 48 per cent of the school children is 12 years or older, and although Maputo province scores lowest, it is still 33 per cent. (95% CI = = ± 7 per cent) There are more boys than girls in this category. Not less than 42 per cent of boys enrolled in primary school are 12 years or older compared to 34 per cent of girls in primary school. This difference is not consistent in all provinces. In Cabo Delgado, Niassa, Nampula, Zambezia, Tete, lnhambane and in Maputo City, the percentage of boys enrolled in primary school, who are 12 years or older, is higher than that of girls. Only Gaza and Sofala have a percentage of girls enrolled in primary school who are 12 years or older, which is higher than that of boys. Further studies at provincial level are needed to explain these differences. 4.6 Water and sanitation (Table 8) The proportion of people with access to drinking water is measured. "Safe drinking water" is been defined as water from a tap inside or outside the house, or from a community pump in the neighbourhood. Assessment of quality and cleanliness of tap water and of containers in which water is carried home, is not included in the survey. The distance considered "convenient" and labelling a water source "accessible", is set on 500 meter according to national policy. The interpretation of this definition was up to the respondents, interviewers and supervisors. Hygiene and sanitation is measured by counting the number of households with latrines, whether they are constructed inside the building or in the yard. The result on this indicator is the percentage of people with access to such sanitary facilities. Sixty three per cent of the sample population has drinking water at walking distance (95% CI = ±4 per cent). Provincial differences are big, ranging from 97 per cent in Maputo city to just 25 per cent in Inhambane (95%CI= ± 10 per cent). An average of 54 per cent of the sample population has access to hygienic sanitary facilities (95%CI= ±4 per cent). The results vary much between provinces, ranging from 99 per cent in Maputo city to 5 per cent in Zambezia (95%CI= ±10 per cent). Given the recent history of war and destruction, the availability of water and sanitation facilities could have been much worse. Although this is true, the health status of women and children can not be expected to improve equally fast as the expansion of water and sanitation facilities because much has still to be done in terms of utilization of these facilities. 21 Calculation based on government data for 1995 results in 41 per cent (MOE 1995). 24 I I I I I I I I I I I I I I I I I I I I I Multi-Indicator Cluster Survey- 1995, GOM-UNICEF Table 8: Percentage of population with access to safe drinking water and latrines. Total Access to Safe Drinking Water and Latrines Province Nwnber of Residents Residents w/safe Water Residents w/ Latrines (%) (%) Maputo City 3464 97 99 Maputo Prov. 3005 64 98 Gaza 3383 81 93 Inhambane 2897 27 73 Sofala 2712 87 43 Manica 2323 51 65 Tete 2611 44 35 Zambezia 1725 38 5 Nampula 2510 72 62 Cabo Delgado 2216 82 44 Niassa 2780 58 73 Mozambique 29626 63 54 Source: Multiple Indicator Cluster Survey, July/August 1995, Mozambique, GOM-UNICEF National rates have a 95% CI = ±4 per cent and provincial rates 95% CI = ± 10 per cent with some exceptions at ±8 per cent. 25 I I I I 'I I I I I I I I I I I I I I I I I Multi-Indicator Cluster Survey- 1995, GOM-UNICEF REFERENCE LITERATURE Bradford Hill, Sir Austin, 1977, A Short Textbook of Medical Statistics. Linford Press, United Kingdom Feeney Griffith, 1976, "Estimating infant mortality rates from child survivorship data by age of mother . , Asian and Pacific Census Newsletter, Vol.3, No. 2 Feeney Griffith, 1980, "Estimating infant mortality trends from child survivorship data", Population Studies, Vol.XXXIV, No.1 Hennekens, Charles H., and Julie E. Buring, 1987, Epidemiology In Medicine. Little, Brown and Company, Boston/Toronto Jelliffe, D.B. and E.F.P.Jelliffe, 1989, Community Nutritional Assessment. with sBecial reference to less technically developed countries, Oxford University Press, 198, UK. Lopes, Leone! and Clara Santos, 1995, Aspectos Demograficos e de Saude Materno-Infantil na Cidade de Ma£uto: analise dos dados do inguerito Julho de 1994, Ministry of Health, University Eduar o Mondlane, Maputo July 1995. MOE, 1992, Indicadores Educacionais e Efectivos Escolares. Ension Primario 1983 - 1992 MOE, 1995, Estatistica da Educacao. Levantamento escolar 1995. Dados Preliminares. MOH, 1993, Departamento de Epidemiologica e Endemias, Analise Epidemiologica das Doencas Diarreicas. Calera e Disenteria en Mocambigue MOH, 1995, Departamento de E{)idemiologica e Endemias, Analise Epidemiologica das Doencas Diarreicas. Calera e Disenteria en Mocambigue MPF, 1993, Direccao Nacional de Estatistica, Inguerito Demografico Nacional: Composica.Q. por Sexo e !dade da Populacao Abrangida, Serie: Inquerito Demografico National Documento No.1 MPF, 1994, Direccao Nacional de Estatistica, Projeccoes Anuais de Populacao par Provincias: 1990-2000, Serie: Inquerito Demografico National Documento No.3 MPF, 1995, Direcciio Nacional de Estadstica, Mocambigue: Panorama Demografico e Socio- Economico, Serie: Inquerito Demografico National Documento No.5 MSF-Belgium, 1995, Nutritional Assessment. Northern Mutarare District. Tete Province MSF-CIS, 1994, Nutritional Assessment. Southern Mutarare District. Tete Province MSF-CIS, 1995, Inguerito Nutricional Rapido. Distrito de Guiia. Provincia de Gaza MSF-CIS, 1995, Inguerito Nutricional Rapido. Distrito de Guro. Provincia de Manica MSF-CIS, 1995, Inguerito Nutricional Rapido. Distrito de Morrumbene. Provincia de Inhambane Newell, Colin, 1988, Methods and Models In Demography. Belhaven Press, London Pelletier, David L., 1994, "The relationship between child anthropometry and mortality in developing countries: implications for policy, programmes, and future research." in: The Journal of Nutrition, American Institute of Nutrition, Vol.124:2047S-2081S 26 I I I I I I I I I I I I I I I I I I I I I Multi-Indicator Cluster Survey - 1995, GOM-UNICEF Scrimshaw, N.S., 1994, "Consequences of hidden hunger", in: Food and Nutrition Bulletin, pp.3-24, Vol.15, No.1, United Nations University Press. UNESCO, 1995, Statistical Yearbook 1993 UNICEF, 1995, Monitoring Progress toward the Goals of the World Summit for Children. a practical handbook for multi-indicator surveys, UNICEF, PD, Planning Office, Evaluation and Research Office, New York January UNICEF Evaluation and Research Office, 1995, Monitoring Progress toward the Goals of the World Summit for Children. a practical handbook for multi-indicator surveys, New York UNICEF & WHO, 1995, Modeling Maternal Mortalitv in the Developing World UNITED NATIONS, 1983, Indirect Techniques for Mortality Estimation, New York World Health Organization, 1983, Measuring Change in Nutritional Status. WHO, Geneva Yip, Ray and Kelley Scanlon, 1994, "The burden of malnutrition: population perspective", in: The Journal of Nutrition, The American Institute of Nutrition, Vol. 124: 2043S- 2046S 27 - - - - - - - - - - - -- - - - - - - - -REPUBLICA de MO~AMBIQUE MINISTERIO 1)0 PLANO E FINAN~AS ; . Direc~ao Nacional de Estatistica lnquerito sobre "lndicadores multiplos" UNICEF· Nlimero do Bole tim-:---:--- Sa este boletim tem continua~3o, coloque um X no quadrado [] Nome do chafe do ~gregado Familiar --------------------------------------------------------------------------- Provincia ---------------------------------------------------- Distrito -------------------------------~---------- Cidade PostoAdministrativo ---------------------------------------- Localidade ----------------------------------------- Bairro ou Aldeia N° do quarteir. Nome do Inquiridor Data I __ I 1995 Nome do Supervisor Data I I 1995 Pessoas a inscrever no boletim~ Todas as pessoas do Agregado Familiar, isto 6~ que vivem habitualmenta na residencia indicada, quer astejam CIU nlo presentee. As pessoas ausentes da casa h4 mais de seis mesas nlo devam ser inscritas. Nlo inscrever as passoas que1 - apesar de terem dormido a ultima noite nessa Agregado Familiar, normalmante residem noutra casa de~1utro Agregado Familiar. - faleceram •nt~s do dia em qU& sa est' a realizar o inqu6rito _nesse Agregado Familiar - - - - - - - - - - - Habita~ao e outras condi~o.es de vida -. P.4i. A tn• 6 CONINide com pOfedn de: 1. Cimento e tijolo, 2. M-Ira e zinco 3. Adobe 4.C~ oupaue 5. Outroe P.SO. A c••• i co-t• de: 1 . Leje de bello 2. Te!M 3. ltnalita 4.Zinco 5. Capim 8 . OUtroe P.Sl. Clu.ntnjoneln tamec••1 0. Zero 1.Ume 2: 0un .3. Trese meie P.52. 0 chlo do u . 'de: 1. Terre betide 2. Clinento 3. M~eire 4.0utro P. 53. A £vue 4 p<oveniente de: 1 . C oneliJ!a~lo de ride pUblico dentro de cae 2. Cenaliz~lo de ride pUblico fore de co . 3. fontenirlo de eldeia 4 . Po~o 5 . furo art.,.;- _ e . . Rio hu 11190 7. OUtro P.54. Disd·lcla de cao 6 lonte de 4gue: 1. Dentrolforo de cne 2.M-de100m 3. Entre· lOGe 411 m . 4. Superior e 500 m P.S&. f.,. eempre a 6gu• que t~l>e7 1. Sim 2. Nlo . P.Se . Na rel•i1-lo do die .,terlor eo lnqu,rlto, dril• M u-. 1. Slm aal P•• cod~·r oa •limentoe1 2. Nlo J.Nio- P.57 . S. ueou ool, pe<;a um -ce per• fezer e , . ,. •llf• • 1. Com lodo lodiz~lo • <a\ >que o reMJitadp 2 . S.m lodo P.58 . Ao:Y:e . cteca1 1. Caa de benho dentro en a 2. Letrino no quintal 3. No mato - N" . - - - - - - - - Os dados colhidos atrav's do inquArito tam car~cter sacreto • apenas podam aer objecto de an,lisa em forma de dados estat!aticos. A viola~lo do dispoato no par,grafo anterior ser' punida com a pena corraspondante ap crime de viola~lo de segredo profissional previJtO na lei penal. NOME, d• -- pe;tenc:ent• eo A.F. co~ando peto Chafe do A.F. eeguido de IUe •po . e. .,. filhoe, de oull• mulhera e.- filhoe e PD' Ulttrno outr• -- cam outr~ grou de porentnco em relo~lo eo chafe do Agrevedo familiar ' ' - - . IOADE ·- i - - - - - - - - - - - - - - - - - - - - - TODAS AS PESSOAS DO AGREGADO FAMILIAR ·ATEN«;AO: registe1a~ crian~ .a ~eguir a sua mae e por orde~ crescente das suas idades . P.O. NOmepr._.JO. 01 02 03 Ool 05 oe ! • ~ .1 . lndique ., a ,. •tj: 1.Pr~l· 1. Pre~ente 1.Pr•enle 1.Pr-• 1. Preaente 1.Pr-nte 2. ~.- 2.~. 2.Alnanle \. 2.~- 2. Aunnte 2. Aueenta ' P.2. Ael~~ corli· o Chela d4t Afret~odo 1. Chela ·.2. Conjuge 1. Chela .:z.eo,.a 1. Chela :z. c . 1. Chela :Z. Cor1Ug• 1. Chela 2 . C:or1u1Ja 1. Chela :Z . Cor1Uga hmlll11 3 . flho/a 4 . Pei/Ma. 3. Filho/a 4.Pai1Ma. 3. ,_,. 4. ,. . 3 . FIIho/a 4.Pe11Ma. 3 . FMho/a 4.Pei/Mie 3. Fllho/a 4. Pal/Mie 5. Ganro/Noro I . Nato/a 5. Gervo/Nor a I. Nato/a 5. Ganro/Noro • . , . ,a 5. Gento1Nor a I . Nato/a 5. Gionro/Nora II. Neto/a 5. Ganro/Nora il. Nato/a 1. Sam parenteaco 7. Sam parentnco 7. Sem PlflniiiCO 7. Sem p•-•eo 7. Sem parenteacO 7. Sem p•ent••eo I. Outroa, -illque 1 . Outroa. e~p~clllque 8. Oulroa, Hpecillque 8 . Outroa, . pacifique 8 . Outroa, eapacilique 8 . Outroo, a-lliqua . P.3.1ndloto4e . HU 1. M•cullno 2. Femlnino t. M•cullno 2.Fam"*- 1. MMcullno 2. Femlni,. 1. M•culino 2. Farnlnno 1, M•cutlno :Z.F . 1. M•arllno 2. Femlnino P.4. Ouantoa . _tem7 . - -· -· -· -· -· P.&. t partadofde ~~ d4tftcilncla1 1.Nie 1. Na. 1. Nlo 1. Nlo 1.Na. 1. Nlo 2.Cif0 :z.c. :z.cevo :z.c-.• 2. Cago 2. Cogo 3. Surdo·Muclo 3. Surdo·Mudo 3 . Surclo-Muclo 3. Surclo-Muclo 3. Su<clo·Mudo 3. Su<do-Mudo Pualfdcoo ,. . _ Paralldco . Parolfdce Per.wtlco ····~ 4.8r~ 4.8r~ 4. 11<190 4.11r~ . ll<a~ 5. , . · 5. Perna 5. '"'"a 5. Perna 5. Perna 5 . Perna \ Mutledo Mutledo Mutledo Mutled4t Mutlled4t Mudledo 8.8r~ · ·····~ 8. ···~· 8. lira~ 8. llra~o 8. lka~o 7. Perna · 7.Perna 7.P•na 7.Parna 7. Parna 7. ""'"" 8. Doanta Mental 8. Ooenta Mental I . Ooente Mental a. Ooanta Mental I. Ooente Mental 8. Ooanta Mental -- -·--- ~· --- - - - - - - SfPIIJarPcriiit~lrm'motftldt! a:m-s drid=re - - - - . I I P.l. lndlque o .,_.,cia .,. mle P.7.D.a.tle.am.u I /111 ·, /11 I 118 I 111 I 111 . P.8 . A~jj . •vecinM1 I 1. Sim 2. Nie 1. Sim 2.Nio 1. Sim 2.Nio 1. Sim 2. Nio 1. Sim 2.Nio p . ~ . ,.,,,., t . c.sua tica.,. 1.c.s.-.riC • .,. - l.c.s.-.licaiCinge 1. C.S.Ude licalctnge 1.c.s.-.licalctnge 2.Nioumemv.,_ 2.Nie.,._,.,_ 2. Nlo nistem vema. 2.Nioexilotemv._ 2.Nie-v.- 3. Nlo 6 import-. 3.Nioi~-· 3.Nie6~-· 3.Nio6-._.-. 3. Nlo 6 import.,. 4. Outro. . Outro. 4.01otro 4. Ooltro, 4. Outlo, P.10.A cri~o temeertlo de.-.7 1 .Sirn 2.Nio :I.Nio- 1 .Sim 2.Nio 3.Nio - 1.Sim 2.Nio :I.Nio aabe 1.Sim 2.Nio 3.Nio . 1.Sim 2.Nio :I.Nio- ; ! P.11. S. tdcertlo COllie •data de AP.,c __ ,_ __ .,_ AP ne.c: __ , __ ,_ AP. . c __ , __ 1_ APn•c __, __ 1 _ AP- --· _1 __ 1_ ·~.,.,. e tipo de vacina . . BCG --'--'- BCG __ , __ ,_ BCG __ 1 __ 1_ BCG __ ,_. _1_ BCG --·-'--'-OTP 1 I I OTP 1 __ , __ ,_ OTP 1 __ 1 __ 1 _ OTP 1 __ 1 __ 1_ OTP 1 --'--'-APt --,--~-- AP 1 __ , __ ,_ AP1 __ 1 __ 1 _ API __ 1 __ 1_ AP .l __ , __ .,_ 'OTP2 -, I OTP2 __ , __ ,_ ' OTP 2 __ 1 __ 1 _ OTP·2 __ 1 __ 1_ OTP2 --'--'-AP2 __ 1 __ 1_ AP2 . __ 1 __ ,_ AP2 __ 1 __ 1_ AP 2 __ 1 __ 1_. AP 2 __ ,_._,_ OTP 3 --'--'- DTP3 __ , __ 1_ OTP 3 __ 1 __ 1_ OTP 3 __ .1 __ 1_ OTP3 --'--'-AP3 __ 1 __ 1_ AP3 · __ , __ 1_ AP3 __ 1 __ 1_ AP3 __ 1 __ 1_ AP3 __1 __ 1_ S.- I I Sar- I I S.- I I Ser- I I s • .,. ! ' ' . ---· P.12. A~· tern ciulriz do ICG,. 1 .Sim 2.Nio 3 .-Nio . · • 1 .Sim 2.Nio 3.NID - 1.Sim 2.Nio 3.Nio oabe 1.$im 2.Nio 3.Nio - 1.Sim 2.Nio 3.Nio - ' lwll901 • · 1'.13. £• ~ ~· tevo •-• na 1. Sim 2. Nlo 1. Sim 2. Nlo \ Sim 2. Nlo 1. Sim 2. Nlo 1. Sim 2. Nlo ulim•tl--7 3. Nio- 3.NioAbe 3.Nio- 3.NID . • 3.NID- -· P.14. o.-. vez• • ai~o- 1 Umavu 1 Umavez 1 Umavu 1 Uma ver 1 Umavez __ , zo. . 20.•-- 20uavez• 20uave~ea 2Duanz• 3 Tr . .,.z•• 3Tria-eoi 3Travaz• 3Tr6avez• 3Trhvez• 4 Ouairo vu• • m- 40uatrova•ornaie 4 au.tro vez• • Maie 4 Ouacro vozea o maio 4 Oullllo voz• • maie ' P.1S.Oife•.,.•~-- 1. Leite llo poito 1.Loitello.-. 1. Leite • poito 1 • Leite tlo peito \,Leite do pooto .,, 2.PI!Pinha 2.PI!Pinha 2.P.,;ma 2.PoplnN 2 . .,. . 3 . Comicla 3.Comida 3 . Comide 3 . Comicla 3 . Comicle . , 4 . Leite • llibotlo 4. Leite tla . 4. Leite • lliborlo 4. Leite de lllborlo 4.Leitode Biberlo ; 5.Fnn. 5.huse 5 . ftut. 5. Fruto 5. Fruta II.Neoa.obo II.Neoe.obo II. Neo- 8 . Noa . e.Neo- ' . . . P.111 . clacri~e _. __ Jtg _. __ ,, . -·-· _ :_Jtv . _._· _lg . _. __ Itt 118 Nlo •tava pr-o 81 Nlo --• pr- 811 Nlo -ova ,_ 88Nio•-•prtOMnte 81 Nlo . teve ,_. ~· . . Ill Som inform~lo ltSem~ 81 Som inlonn~lo 81Seminf-~ II Som inlorm~ ! P.17.AIIurotle~ .: em -·-- em _,_em I _._em -·- -·-. 88 Nlo ••av• preHnlo 18Nio-ovepr- 88 Nlo -•v• pr- £11 Nlio -""• pr-o 88 Nlo -ev• praente II Som inform~ H·Som inlor~ 88 Som Inform~ 11 Som inform~lo 81 Som inlorm~lo P.ll. A cri~e tam oclem•1 1. Sim 2. Nlo 1. Sim 2.Nio 1. $im 2.Nio 1. Sim 2.Nio 1. Sim 2. Nlo . I'. 11. A medici• da altura foi """""" ne · 1.Emp4 2. Deitecl• 1. fm pe 2. Deitada \ . Em p4 2. Oeitecle 1. Em p4 2. Oeitecl• 1. Em p4 2 . O.itacl• poai~ · 3. Flecu.ou lir ar a altura 3. flo.,._. lir• a elturo 3. Re~ tir• e altura 3.Roo.-. tir••eltu<• ~- Reaaou tir• • alua ~- ---- - ---- .------- - - - --- --------------- - - ------ ------ - - - -· ----- - )> 2 2 ~ ~ - - - - - -----------86 para pessoas com 6 anos e mais de idade - P.20.0ita . oobe: 1. Lir a ••et•v• 1 . Lite.,.,., l.Uroacr- 1. lir e escnrver 1. l.At o •crovw 2.S6oeballt 2.50.-aa. 2.so . ., 2 . so . 2.S6a.MIIt 3. Nlo ·- lir.lacrevet 3 . Nio aeba lir/aaever 3. Nlo aeba lirle~ctavet 3 . Nio •abe lit/aocrevar 3. Nlo ., lir/aaever P.21. Seba Ill• por.-1 1. Nlo 1.Nie 1. Nlo - 1. Nlo 1. Nlo 2. Pouco 2. Pouco 2. PouCD 2. Pouco 2. PouCD 3. Muito 3.Muito 3.Muito 3.Muito 3.Mui1o P.22. Qual a lingua-.,.-, olol11 quando . cri~1 P.23. Foi 6 neola; 1. Sim 2.Nio 1. Sim 2.Nio 1. s;,., 2. Nlo 1. Sim 2. Nlo 1. Sinl 2.Nio P.24.So --_, • .-.,, ---·, ciMMI- --- cfaale/- --- dMM/- --- cl.t- --- deale/- lndique: Curwo . Curio Curoo CurliO Curoo P.25. Cit• o graa clo enoino . ., . deale/- --- ct-1- ___ . ct.~- --- deale/- --- cJ.MI- que comtiletou: . ' Cur.o eur., Curwo Curwo Curwo - - - 1.lha•cr•v• ' 2. S6aebalir 3. Nlo •- lir/eactov . 1. Nio 2. Pauco 3. Muito 1. Sim 2. Nlo d-'- --- Curwo "'-'- --- eur . So para pessoas com idade· compreendida entre os 6 e 15 anos P.26. 5o nlo _, I aiUdlf, diga 1. Pr-o clo treiN!hlf 1. Pr-o do troboiNr 1.Prec:iuclottob . 1. Prociaa clotrob- 1.Proc:iNdotr.,., 1. Pr-· . trobolh• porqui7 2. Folta do . colo 2. 'Folta cte eocola 2.Foltaclo-. 2. Flit• do . col., 2. Folta do IICOIJI 2.Foltaclo.,.,lo 3. E-1• fica Ionge 3. bcola fica Iongo 3, bcolo fico Ionge 3. hcolo lice Ionge 3. Eacola licalonge 3. E•cola Ia Ionge 4. Nlo e.U.to prol-r 4. Nio UISte prol0110< -1-.Nio-prof- 4. Nlo oxlete .,.,_, 4. Nlo exieto prol-r 4.Nio--l- S. Nlo tem lug• na llcola 5. Nlo tem luglf . ISCO . 5. Nlo tam lug• na neola 5. Nlo tem lug• no eocet. 5. Nlo tam luglf na acot. 5. Nlo tern :ug., no eacola I . Niotem-o 6 . Nlotem-• . 6 . Nlo ,., dinhoi<o 6. Nlo tem dinhoiro I . Niotem . 8.Niotem.,_,. 7. Outro 7.0utro 7. 0utro 7. Outro 7. Outro 7. Outre - ~ t<1 >:: :J> V1 - - - - - - - - - - - - - - - - - - - - - So para pessoas com 7 anos e mais de idade ".o. ,._ ""'"" I 01 02 03 04 05 06 CONDJ9AO D& ACTMIMDI NA . 1. Sim 2.Nio 1. Sim 2.Nio 1. Sim 2.Nio 1. Sim 2. Nlo 1. Sim 2.Nio 1.Sim 2.Nio ULTIMA lEMMA 1'.27. ,,.,. ~ Uldme --1 1'.2a.s.aow---.--.o ,_,.,._._.,. . 1.1'rocwa _.,. .,._ 1. Pro_a_ . ,_. . _ . 1. Procura -· pela 1. Ptoc:ura emprego . -.iw: ,.,. 1•va , . 1•va , . ,. \'01 2.,.,._ . _ . 2 . . .,.,.,, 2 . . _ . :Z.Ptocureno""-"90 :Z. Ptocwa,.,._.,. 2 . ._ . 3 . Fol-- l.Foi._ 3. Foi dtUII-o 3 . Foi--• 3. Foi . IUd-. 3. Foi niUd-. f· foj ,.,_.,. 4. foj ••• ., . ,. 4 . Foi refOfm-/e 4 . Fol . -,. •• Fol . ,. 4 . Foi rolorm.SO/a 5.~~- S. Sonri~ milirw s.~milit• 5. Sorvi9o milit• 5. Servi\'0 mililw 5. 5er¥i9o mllil.; . e.FOi~. e. ,., domfttico/a 8. Fol domistico/a - 8. Foi ._.lico/a 6. Foi do""-'ico/~ 8. Foi dorne.tico/a 7. Por incopacid- total 7. Por incop.:icl- IDtal 7. Por -Kid- IDlol 7. Por incopacid- ,., . 7. Por ineopaQol.clo total 7. Por incopiiCicl.cle total I.Ouao 8. Oullo 8 . Outro B.Ouuo 8. Outro - 8.0Utro - . . PMFISSAO .,.NCIPAL .,. - 1'.28.lnllil!ue a proflaalo- oxoice •~ . - •• pro . ocr.,.,. . ou om SMO, lnclique a llhirnal CAnG~ OC:UPAC:IONAL 1 • Aoulariado t.Aoealatiado I . Aoealari- 1. Anol•i.clo 1 . Anolari.SO 1. Anolari.to 1'.30. A profiealo -lncticou lol 2. Trabalhador por _,. 2.r.-.-.,., . 2 . ,, • .,- . 2 . Tr.,_r por conta ·:z. Trat.elhador por conra 2. Tub., por coonta -dolo M . - de: - pr6pria pr6pria p<opria pr6pria prOpria prOprio • 3. Tr-.u.csor familiw 3. T!abelh.clor lamilra 3 . T r abii!Ndor lemiliar 3 . Trabii\Mor farniliw 3. Trebalharlor lemHier 3. Trat.""'-dOf femiliar ' . 4. Pattlo /-og- 4.P111rlo.'-egodor 4 . Patrlo /wnprog.tw 4 . Paulo /omprog.tor 4. Patrlo /-•!Jade>! 4. Petrio I empreg-r S.Ouuo 5. Outro 5 . Ouuo 5. Outro 5. Outro 5. Outro RAMO D£ AC:TMDADE ECON6MIC:A 1'.31.1ndique 0 tlpo . .arvw . ou : . '*'-.~· or.an., etc~ oncr. tr., lc- . r,;o ' . . .,.,. au ern SMO.indi.- a Ullima , . __ , - - - - - IST~O CML - , P.22 • .,._ o-- eMil- - - - - - - - - - - - - So para pessoas com 12 anos e mais de idade 1.!JebiNia z.ea.-.,. 3. Yllivwlo ._,,.MoJOivofa.tala 1. Soluiro/a Z.C•Miol• 3. Yo<iwo/o 4. lioparado/Oivorcilldo/o t.Soltao/a 2.C.Sadota · 3. ViWo/a : ' 4. Separado/Oivorcioldola 1 . Sohlliro/a z.c.,. 3. ViiNo/o 4. Separlldo/Divorci•/• 1. Soheiro/o z.c.,. 3. ViiNoJa 4. Seporado/Oivorciadoio - - 1. Soltlliro/a z.c • .,.;. 3. Vi!No/a - 4. Seporado/Divora./a S~ para mulheres Com idade compreendida entre QS 15 e OS 49 anos P.33. y.,. ~ ,._ .W0 viwOP 1.Sim 1. Sim 1. Sim 1. Sim ' 1. Sim 1. Sim . llnduirdoo .,; folecidoel . 2. Nlolvll p/ouuo _, 2. HloC¥11 pJ.dra ., 2. Nlo 1¥11 pi-a _, 2. Nlo 1¥11 ,_. • ., . 2 . ~lol¥11 p/outra ,._, 2. Nlol"ll p,_ra ,._, P.34. Ckr.t., ~ nMCidn. "'- --- - . - ma.c -- I em - mosc - I em -- m•c -- lam -- mac -- ·- -- m.c: -- lam _, ·--. P.2S.Ckr- ._ ~ -- maoc - ·- - m.: -- ,., . - . -- ,_ -- ., -- ,., -- m•c -- lam mac ,., -. , ;.P.38. 0.- fllhoa ;.cldoe vivoa teve· - - maoc - fem - m.c - ,_ - m.c: - ·- -- -- m., -- I em -- moac •am m•c ,., -.- -- --1108~12-1 - P.37. Doe flhoo nMCidoa wivoa ,. lam lam tom fern fem ·. -- maoc_·_ - m., - - moac - -- ma.c -- -- m•c: -- -- mac tom --~· 12 moooo • .,-. oot1o vivw1 ' ·-· - -- - - - ----- - - - - - - - - - - - - -So para mulheres. com idade compreendida entre os 15 e os 49 anos e que tern fllhos menores de 5 anos P.31. Na F•widc de UltinM fllhlt fill __.,. pr . llll7 P.H. Sa I• a --.Ita ;. do .a.-. . . wa• h darMI a Vecina And Tellnica7 t~lonolor•J P.40. au.W. wa• h.__, o Vacina AnD Tatlnica ., . o .,. Yida? · P.41. CMwN o ?ft01 "-'• o _,., P.42. au.la o cri~., . utili a o SROl c-ar o -lei P.43. Ouande utilila o SRO, - . , P.44. Ouo q\,enlid- do p-1• diluU ne . , • P.4S. Como dl -• miooturo l cri~o? P.46 . au . a oua cr~a tom di•reio. dig• . --·- . d, . . .-.m-.oua_.,. . ,. . nlo_di_ . . P.47. So d6 maia llquldoo i ~ . -. .,., P.41. Ou.,. • """~·tom cliorrotio. . -- - porloclo d6 do cemet menu. lfteitl ou 1 rnesm1 quaftdd . da . do . nlo18mcliwreia t ,Sim 2.Nio 3. Nlo. •- 0 1 2 0- . 1 · 2 . 3 4 S+ ,_ . 2.Nie 1~ 2-Nie 3. Nlo . 1. c- . . 2.F.r,. . . •. . Iitie ·~ 3 . .__ . . 4.~ • . 1.Totlo 2.P--to 1."' . ~-·· 2.1-pordia 3. " co~ trio -• por dia 4 .1_ . . . ·S.Um_._. . •· coda ~ e. " copo "-ia de eade ~ 1. c•• ,.,. • criarlf" . e. au- 1.Maia . 2.'M.o 3. Mama . .;d . 4. N . bobo nodo 1. J.,a de OfTN 2.Papinhademilho 3.A,ualchi 4.1.,. •ca. S.Outro 1.M• 2. M-• 3. Me.na .,.cicl-. 4.Nio-noda 1 .Sim 2.Nio 3. Nlo •obe 0 1 2 . 0 1 2 3 · 4 S+ 1. Sim 2.Nio 1.Sim 2.Nio 3. Nlo .- 1. eom.,litto • .igu• limpa 2. f- . ._. modo""' litto 3. ~umlilrode•• 4.0ulnt t.Totlo 2.P-p-lo 1. 5 eopo porCiie"'·-~ - 2 . 1 eopopordiol 3. " copo tre •••• por •• 4.1_., . •• s. Um copo dapoie . uda dajec~lo 8. W. eopo dapoie de eoda ~~ . 1. Coda., . .,. • cri~ . . 8. Outro 1. Maia 2.Mol18a 3 . M.,aqu-idode 4. Nio bobo nodo 1. 4.,. da wroi 2 . . da milho 3.~ 4.4 . dec6co s. Outro 1. M.;s 2.M-o 3.Mnmoqu-idode 4. Nlo como noda I.Srm 2.Nio 3 , Nlo .- 0 1 2 0 1 2 3 4 S+ 1. Slon 2. Hie 1 .Sim 2.Nio 3. Nlo . . 1. Comumlitrode'tua . limpa . ' 2.Ferw . modo!MIIiiiO 3. fwwa ""' IiilO do 'slu• 4 . 0uko t .Todo 2.P•to JIOC:OIO 1. ,. eopo por dia :Z . 1--rli•' 3. W. copo trio wc• por dio 4 . 1 eopo ttlo ••• por eli a · 5. Um eopo depoie do eoda ~- 8. W. copo depoie de eodo ~ . 7 , Coda . _ ocri~ ·-- . 8 . 0uuo t.Maia 2. ~. 3. Meoma qu.,tidode 4 . Nlo bobo nodo 1./upode .,oz 2 . Papinha da milho 3.~ 4 . /upadedco S. Outro 1 . ~ . 2 . M-• • ;J.M_.qu_,.ode 4 . Nlo c:omo nodo 'r 1 .Sim 2 .Nio 3. Nlo .- 0 1 2 0 1 2 3 4 S+ t. Sim 2.Nio 1.Sim 2.Nio 3.Nioube 1.COmumlitrode'slua limpa 2 . .__ . rnaclaumlitro 3. Fervo.,. 1itro de .lgua 4.a.- t .Totlo 2.P- -le 1. ,. copop0rclio 2.1copopor . 3." _ . ,., . 4 . t - . por dia S.Umcopodepoiede e•• ~ . •• ,. . eod. ~~ 7.Codavu-·~ . I . Outto t . Maia :Z. M.,. 3 . icl . 4 . Nlo bobo noda 1.~•••roz . 2 . P . demilho 3.A.,wcw 4 . A.,. dec6co S. Ouvo 1.Maia 2 . Menos 3 . . ancicl . 4.Nio-nodo 1.Sim 2.N:ko 3 . Nio ·- 0 , 2 0 1 2 3 4 S+ -.,.:s;m 2.Nio 1.Sim 2 .Nio 3. Nlo ube 1. COmumlltrode 'slu• limpa 2 . F.,.a6guao . modoum~uo 3. Fern um 51lo de •• 4 . 0uvo 1.Todo 2.PWio pacota 1. ,. eopo por dia 2. 1 eopo por dio 3. " _ . ., . clia 4 . 1 copotrlo . - eli a .• S. Um copo clopoie da eoda dojec~lo 8. W. eopo dapoia clo e•• ~ . 7 . CodoYU-a~o tomoode •. Ouvo 1. Maia 2.M-o 3. Meuna quanciclode 4 . Nlo bebo nodo ·1. Agua da .,oz 2 . PopintMI de milho 3. Agua1Ch4 4. Agua dtteO. s. Oulro 1. Mais 2 . Meno• 3 . Meoma quonlicloda 4 . Nlo como nado 1.Sim 2.Nio 3. Nlo ·- 0 1 2 0 1 2 3 4 s. t. Sim 2.Nio 1.Sim 2.Nio 3. Nlo ube 1. Com um ~uo dtt 'slu• limpa 2. ferve . rnacla um litro 3. Fwwo um lltro de jguo 4 . Oucro t.Todo 2.Pwto p-1• 1. ,. eopO por dia 2.1 eopo por dia 3. ,. COpO trio WOIOO por clio 4. 1 eopo ttlo wuoo por di• S. Um eopo dapoio do c . dajec~lo 8. W. atpo dapoio da coda dajoe~lo 7. C.lda . - a cri~o ·--8. Outro l.Maia 2. Menoa 3 . Meam•quMllicloda 4. Nlo bobo noda 1 • Aguo ~· arroz 2 . Papinha do mitho l . /upaiCh.i . Avu• da coco S. Outro 1.MM 2 . Menos 3 . M-.o quenticlode 4. Nlo come nada ------~ ~ z trl :X: > 00 I I I I I I I I I I I I I I I I I I I I I ANNEXB CALCULATIONS :FOR NATIONAL WEIGHTS (based on number of voters of province) Province Voters Proportional Weight MAPUTO CIDADE 459,166 0.072 MAPUTO 330,887 0.052 GAZA 398,381 0.063 INHAMBANE 471,524 0.074 MANICA 322,201 0.051 SOFALA 530,066 0.083 TETE 397,260 0.062 NAMPULA 1,365,796 0.215 ZAMBEZIA 1,237,348 0.194 NIASSA 282,513 0.044 CABO DELGADO 568,169 0.089 TOTAL 6,363,311 1.000 - - - - - - - - - - - - - - - - - - - - - ANNEXC1 CAlCULATIONS FOR WEIGHTS M 450,1158 OISlRITO URB. 1 101,685 Alto Mae 'A+B" 11~.756 Quarteirao 9 80 29 468 1500 0 .00067 0 .115 Centrai'A+ B+C" 21 ,Be8 Ouarblirao 25 142 30 432 2147 0 .00047 0 .165 A Malhangal- 'A+B' 40,110 Qualteirao 31 77 30 245 360 0 .00278 0 .028 Malhangalene 'A+ 8' 40,110 Quarteirao 22 77 31 351 499 0 .00200 0 .038 p DISlRITO ~B. 2 85,895 Aeroporto 'A+B" 9 ,517 Ouarteirao 19 87 30 398 2784 0.00036 0.214 u Chamanculo 'A+B+C+D" 33,952 Quarteirao 9 126 31 122 335 0 .002S8 0 .026 Chamanculo 'A+B+C+D" 33,952 Quarteirao 35 126 30 309 878 0.00114 0 .067 T Unidade7 4 ,560 Ouarteirao 11 26 30 381 1662 0.00060 0.128 0 DISlRITO LfiB. 3 89,179 Mafafala 8,490 Quarteirao 50 57 30 127 653 0.00153 0 .050 Maxaquene 'A+B+C+D" 43,51(1 Quarteirao 43 214 32 81 286 0.00350 0 .022 Maxaquene 'A+B+C+D" 43,516 Quarteirao 9 214 30 74 278 0.00359 0 .021 Polana canico 'A + B' 30,247 Quarteirao 30 132 30 130 434 0 .00230 0 .033 c DISlRITO LfiB. 4 89,201 Fenoviario 25,405 Quarteirao 4 90 30 88 2311 0.00419 0 .018 Hulene 'A+B' 37,210 Qualteirao 19 124 36 M 136 0 .00735 0.010 l.aulane 44,583 Qua.rteirao 15 43 24 157 145 0 .00890 0 .011 T L.aulane 44,583 Quarteirao 26 43 30 146 108 0 .00928 0 .008 y DISlRITO UAB. 5 93,206 George Dimilrov 16,634 Cuarteirao 5 40 31 80 142 0.00702 0 .011 Jardim 6,786 Quarteirao 33 35 30 40 158 0 .012 Malhazine 4,755 Quarteirao 8 16 32 70 169 0.013 25 de Junho 'A+B' 14,833 Quarteirao 12 50 31 38 - - - - - - - - M 330,887 BOANE 24,843 A p MATOLA 172,843 u Cidade T 0 MATOLA 172,843 Cidade p MARRACUENE 17,614 R 0 v MANHICA 53,842 - - - - - - - ANNEXC2 CALCULATIONS FOR WEIGHTS Eduardo Mondlane 7,763 Bairro 1 Gueguegue 10,483 Bairro 3, Q.2 MatolaRio 2,077 Q.67/Q.68/Q.69 Chinonanquila 4,527 ~oane Bairro liberdade 11,796 Quarteirao 9 Matola 'A' 15,286 Quarteirao 21 Matola'D' 5,886 Quarteirao 8 /11 Bairro Pair. Lumurnba 7,711 Celula A, Quarteirao 5 Mnchava Sede 14,172 Quarteirao 1 0 Mussurnbuluco 1,983 Quarteirao 2/9 Bairro Kongolote 1,986 Quarteirao 9 Bairro Zona Verde 9,535 Quarteir.o 5 Marracuene Sede 8,410 Massinga, Q.1 Marracuene Sede 8,410 Fafetine, Q.1 Nhongonhane 4,842 Eduardo Mondlane, Q.2 /3 Machlbo 644 Macandza Manhica Sede 17,IHIO Cambe\18 Maciana 7,920 Bairro 1 • Q.2 Nwamatib'*- 5,853 Bairro 1 Maluana Sede 3,496 Bairro 1 16 13 7 7 45 55 12 37 67 9 16 43 10 10 8 2 3 4 11 3 - 30 30 30 30 30 30 30 32 29 30 30 30 31 30 31 30 30 30 30 30 NB. District of Manacoene.localily of Machlbo, village of Macandza- Total# of HH - Value found by adding up the other 3 villages of same district & dividing by 3 - - - - - 156 177 0.00564 0.031 144 98 0.01015 0.017 32 59 0.01681 0.010 40 34 0.02932 0.006 1,095 2304 0.00043 0.400 62 123 0.00813 0.021 106 119 0.00839 0.021 103 256 0 .00391 0.044 269 726 0.00138 0.126 174 436 0.00230 0.076 55 244 0.00409 0.042 230 572 0.00175 0.099 45 29 0.03502 0.005 60 3Q 0.02542 0.007 34 30 0.03336 0.005 48 79 0.01260 0.014 80 7 0.13!585 0.001 50 14 0 .07181 0.002 300 311 0.00322 0 .054 230 - - - - - - - - - - - - - - - - - - - - - ANNEXC3 CALCULATIONS FOR WEIGHTS 3911,381 XAH<Al 59,658 Chongoene 6,072 Venhane 6 32 105 65 0.01543 0.011 Maciene 3,361 Clm1bane 4 32 90 67 0.01500 0.011 Chicumbane 10,635 Bairro 1 /2 4 30 6HI 154 0.00648 0.026 Muzingane 4,697 Julius Nyerere 2 32 12,678 3360 0.00030 0.558 XAH<AI 42,240 Bairro1 4,037 Ouattairao A I C IE 5 31 125 99 0.01005 0.017 Cidade Bairm 9 3,386 Quarteirao E 7 30 50 69 0.01457 0.011 G lnhamissa 4,858 Ouarteirao A I 0 9 30 90 111 0.00903 0.018 Patricio Lumumba 4,896 Qu.teirao A/ B I C/ H 6 30 1,594 1297 0.00077 0.215 A CHIBUTO 62,601 Tlhatlhene 3,137 Tlhatlhene 3 30 620 394 0.00254 0.065 z C. Miss- 4,635 C. Missava 15 30 40 86 0.01163 0.014 Maninqueque 2,287 Manioqueque 30 40 12 0.08611 0.002 A Sede (P .A cia Sede) 20,215 Bairm 1 15 30 80 39 0.02537 0.007 CHOKWE 69,594 ChokweSede 21 ,816 Bairro2 8 30 175 43 0.02347 0.007 ChokweSede 21,816 Bairm 5 8 30 180 44 0 .02282 0.007 Conhane 10,104 1 de Maio 5 30 45 15 0.06763 0.002 Matuba 2,718 Machel 3 30 75 55 0.01819 0.009 CHICUALACUALA 9,284 Chicualacuala Rio 5,191 Chicualacuala Rio 5 29 45 30 0.03359 0.005 Chicualacuala Rio S,Hn lilhalha 5 30 40 0.03009 0.004 Buela 4,313 Dombe 4 30 55 0.02953 0.006 Buela 4,313 Muzumane 4 30 40 - - - - - - - - 471,524 ZAVALA 48,600 N JANGAMO 32,267 H A loll MAXIXE 46,479 B A MASSINGA 76,671 N E VILANCULOS 47,7flfil - - - - - - ANNEXC4 CALCULATIONS FOR WEIGHTS Quissico 13,345 Nhacodue Muane 10,351 Guilundo Macutuva 19,089 Nhamuenda Maculuva 19,089 Chinguambe Jangamo 10,614 Malaica-Nhanala Ugogo 4,641 Madonga Cumbana 11 ,487 Nhacoja Massavane 2 ,687 Guinjata Sede (P .A. da Sede) 22,333 B. Chambone Nhabanda 6.807 Magila Bembe 7,429 Bembe NhaguNiga 4,8fl0 Bairro 1 Rowne 27,361 Queme Guma 14,157 Mapanguela Chicomo 16,085 Chicomo Mlllamba 5 ,935 Macuacua Secle {P .A. da Sede) 19,318 Chigamane Sede {P .A. da Sede) 19,3111 Chirruala Mapinhane 12,429 Chitetemane Belane 7,591 Machunguele - - - - - - - 5 32 820 226 0.00442 0.045 6 35 293 114 0.00873 0 .023 4 30 614 101 0.00989 0.020 4 32 613 95 0.01057 0 .019 4 29 463 142 0.00705 0.028 5 31 378 309 0.00323 0 .062 8 33 882 439 0.00228 0.088 4 31 852 965 0.00104 0 .194 9 30 620 196 0.00510 0.039 13 33 573 782 0.00128 0.157 5 32 637 316 0.00317 0 .063 3 34 441 189 0.00530 0 .038 6 32 302 49 0.02051 0 .010 6 30 660 220 0.00455 0 .044 4 32 431 79 0.01268 0.016 4 29 527 289 0.00346 0 .058 11 37 256 93 0.01077 0.019 11 39 264 91 0.010911 0 .018 6 32 375 133 0.00750 0.027 11 31 141 - - - - - - - - - - - - - - - - - - - - - ANNEXC5 CALCULATIONS FOR WEIGHTS 322.201 MOSSURIZE 34,fl63 Dibi 2,712 Dibi 6 30 542 859 0.00116 0.045 Sitatonga 2 2,801 Gogoi 7 17 560 1768 0.00057 0.094 Mupengo 5,205 25 de Selembro 7 30 1,041 1002 0.00100 0.053 Macuiana 5,132 Nao foi inquirida n/a n/a n/a n/a n/a nl• M GONDOLA 56,63l Macate Sede 3,222 1 de Junho 4 31 644 415 0.00241 0.022 Boa Vista 1 ,505 Boa V"ISta Sede 5 30 301 537 0.00186 0.028 A Amatonge.~ Sede 3,167 CFM 6 31 633 623 0.00160 0.033 Josina Machel 6,320 Quarteirao 3 /9 7 31 1,264 728 0.00137 0.038 N CHIMOIO 70,312 Centro Hipico 8,730 Ouarteirao 6 30 29 1,746 3333 0.00000 0.176 Cidade Bloco9 5,271 Ouarteirao 7 9 30 1,054 96fl 0.00103 0.051 1,2&3 2,491 Ouarteirao 3 14 31 498 1455 0.00069 0.077 c Nr. 5 7,000 Zona2 8 30 1,400 859 0.00116 0.045 A MANICA 52,640 Manica Sede 10,214 Bairro Josina Machel 11 30 2,043 1182 0.00085 0.062 MessicaSee 5.044 Bandula 8 30 1,009 859 0.00116 0.045 Machipanda Sede 4,442 Bairro Chitio 3 29 888 333 0.00300 o.ous Vanduzi Sede 5,928 Bairros Bela 1 e 2 5 31 1,186 520 0.00192 0.027 BARUE 22,187 Cata.ndica Sede 6,479 Cegole 10 28 1,296 1151 0.00087 0.061 Chuala 3,012 Honde 7 32 602 704 0.00142 0.037 NFudze 1 ,605 Pandira 4 30 321 430 0.00233 0.023 Nhauroa 1 ,OfJT Barauro 7 19 213 NB. Oislriet of Mossurize, locality of Sitatonga 2, village of Gogoi - Total #of Bairros - Value found by adding up the other 2 bairros of s11111e district & dividing by 2 Dislriet of Barue, iocality of Chuala. village of Honde & locality of Nhauroa, village of Barauro- Total # of Bairros - Value found by adding up the other 2 bairros of same district & cflviding by 2 - - - - - - - - - - - - - - - - - - - - - ANNEXC6 CALCULATIONS FOR WEIGHTS 530,086 CHIBABAVA 27,545 Toronga 5,930 FtdeiCastm 3 30 137 61 0.01633 0.011 Vila Sede (Muxungue) 10,542 Nhanga 5 30 38 16 0.06280 0 .003 Vila Sede (Muxungue) 10,542 Chilurimutanda - a. 1 5 30 79 33 0.03021 0 .006 Mucheve 7 .510 Chaconja 5 30 116 67 0.01485 0 .012 s BEIRA 185,939 Estuno 12,429 Quarteirao 8 26 30 251 464 0.00216 o.oao Cidade Pioneiros 4 ,966 Cuarteirao 1 12 30 57 122 0.00822 0.021 0 Ponta- Gea 8,244 Quarteirao 9 36 30 193 745 0.00134 0 .128 Macuti 6,000 Cuarteirao 2 20 30 100 294 0.00340 0 .051 F BEIRA 185,939 Chota 4,149 Quarteirao 8 14 30 53 158 0.00633 0.027 A Cidade Alto da Monga 7,205 Quarteirao 1 24 29 443 1348 0.00074 0 .232 lnhamizua 14,006 Quarteirao 21 23 30 37 54 0.01863 0.009 l Manga Laforte 6,606 Quarteirao 1 21 30 575 1615 0 .00062 0.278 A NHAMATANDA 53,1:?.3 V"lla Sede (Nhamatanda) 23,883 Qulll1eirao 9 30 30 110 163 0.00614 0 .028 V"da Sede (Nhamalanda) 23,883 auarteirao 1 30 30 128 186 0.00536 0 .032 Chaianhama 14,097 Quarteirao 3 21 30 137 240 0 .00416 0 .041 N~ 15,143 N110 foi inquirida n/a n/a n/a n/a n/a n/a MARINGlE 22,223 Vila Sede (Marinque) 3,263 Nhavuo 3 30 72 78 0.01282 0.013 Gumbalacai 7,525 N110 foi inquirida n/a n/a n/a n/a n/a n/a Senga-Senga 6~7 Bomba 9 30 32 54 0.01856 0 .009 Senga-Senga 5 ,297 Palame 9 31 68 - - - - - - - - - - - - - - - - - - - - -· ANNEXC7 CALCULATIONS FOR WEIGHTS 3g7 ,260 CHANGAAA 31,696 Luenha 5,9113 Sede - Bairro 1 8 32 797 882 0.00113 0.125 Cactterme 7,508 Nao foi inquirida n/a n/a n/a n/a n/a n/a Mufa-Caconde 2,830 Sede 11 32 213 685 0.00146 o.osn Mazoe 7,219 Tchabua 9 33 155 65 0.01538 0.009 MOATlZE 49,635 Moatize 15,514 lnhangoma 13 31 29 20 0.04884 0.003 M'Panzo 5,569 Nhaondue 9 34 200 252 0.00397 0.036 T Zobue 11,832 Cenjuchi 12 31 800 593 0.00144 0.0911 N'Kondedzi 4,6111 Nao foi inquirida n/a n/a n/a n/a n/a nl• E CHiv'TE 15,5512 Casu Ia 3,677 Chilhe to 32 ttstl 288 0.00348 0.041 T Manje 5,307 Macheza tO 32 39 46 0.02170 0.007 Tamwiri 4,324 Tamwira t:l 30 299 573 0.00175 0.081 E Nfigo aoo Nfigo 7 31 160 833 0.00120 0.118 MACANGA 10,008 Furancungo 2,596 Maleme 16 30 511 242 0.00413 0.034 Chidzolomondo 2,926 Macuca 25 33 38 193 0.00517 0.027 Namadende 1,041 ChigumtJcire 6 30 100 382 0.00262 0.054 Campala 570 Chiramba ttl 31 40 704 0.00142 0.100 ANGONIA 84,405 Mpandula 5,478 Mpandula-Sede 4 33 710 312 0.00321 0.044 Lilonga 3,050 Kho!Tbe 6 33 621 736 0.00138 0.104 Ulongue 21,924 MactJca 21 31 163 100 0 .01000 0.014 Monequera 6,9115 Nachilocoe 4 32 200 NB. Dislrict at Chiute, locality of Casula, lllllage at Chithe - Total # of HH - Value found by adding up the other 3\lillages of same dis1rict & dilliding by 3 District of Macanga, localiry of Furacungo, village of Maleme - T Cltal # of HH - Value found by adding up the other 3\llllages at same cfJStrict & dMcfang by 3 Dislrict of Chiute, all four localities, all fourlllllages- Tolal #of Bairros- Value found by adding up '1st line" of the olher 4dislricts from the other districts & dMding by 4; '2nd line' . & so on. District of Macanga. locality of Campala, village of Chiramba- To!BI #of Bairros- Value found by adding up the other 3 villages of same district & dividing by 3 ---- --·----- -- --·-- - . _, __ . - - - - - - 1,365,796 MOMA N MOGOVOlAS A . p NAMPULA (Cidade) u l MONAPO A NACALA PORTO - - - - - - - - 107,362 99,990 135,896 112,510 68,649 ANNEXC8 CALCULATIONS FOR WEIGHTS MomaSede 27,595 NarJYBY« Jagoma 19,425 Jacagiua Muwgu 24,588 Miropho MucuaiiSde 10,068 Napisa Nametil Sede 21,297 Matula Zieque 3,782 Mupapata lnluti Sede 16,878 Cavin a MuatuaSede 15,641 Terrane Munhala 12,046 Cuarteirao 13 Muatala 15,167 Cuarteirao 58 Napipine 11,058 Ouarteirao 1 Namicopo 9,955 Quarteirao3 MonapoSede 36,339 Jagaia MonapoSede 36,339 Potiro Ofensiva (Murruto) 15,497 Centro de Educacao de ltocu NeliaSede 37,565 Napila Mocone 2(1,809 Bloco 1 Mathapue 6,291 Uli Muanona 9,862 25 de Setembro Nacurula 11,2.98 Nacurula 89 24 21 23 35 13 27 11 45 68 83 53 39 39 12 41 5 5 5 4 - 30 30 31 30 30 30 31 30 29 30 30 30 30 30 30 30 30 30 30 30 NB. District of Morna, locality of Mucuali Sede, village ot Napisa- Total #of HH - Value found by adding up the olher 3 villages of same district & dilliding by 3 District ot Monapo, locality ot Monapo Sede, village ot Potiro - Tolal # ot HH - Value found by adding up the olher 3 villages ot same district & dilliding by 3 - - - - - 310 2276 0.00044 0.036 201 565 o.oo1n 0.009 551 1037 0.00096 0.018 354 1841 0.00054 0.029 2,5116 9674 0.00010 0.152 966 7558 0.00013 0.118 172 606 0.00165 0.009 30 48 0.02082 0.001 2,159 18992 0.00005 0.298 314 3205 0.00031 0.050 381 6510 0.00015 0.102 360 4363 0.00023 0.068 336 821 0 .00122 0.013 210 513 0.0019S 0.008 85 150 0.00867 0.002 209 519 0.00193 0.008 3,067 130:2 0 .00077 0.020 1,315 2379 0.037 964 1113 0.017 434 - - - - - - 1,237,348 CHINDE z A NICOADALA M 8 M.DACOSTA E z LUGE LA A GILE - - - - - - - - 60,973 80,276 100,207 45,067 52,441 ANNEXC9 CALCULATIONS FOR WEIGHTS VilaSede 8,710 Tanque 17 Luabo Sede 3,793 Muide 23 Chis samba 4,382 Sambamboze 11 Arijuane 2,851 Nao foi inquirida n/a Sede (P A da Sede} 13,682 Marques 22 Namacata 9,131 lnugo 34 Madal 14,681 Mapinda 27 Marrongane 4,426 Temane 10 Bala 20,445 Nhacovo 64 Muoloa 2,096 Muebene 15 Nacuda 18,482 Mutiba 14 Mucubela Sede 4,468 Muc:Ona 5 Sede (P .A. da Sede) 6,796 Ngazine 18 M'Pemula 1,302 M'Pemula 2 Mulite 4,905 Mucuequela 19 Tacuane 1,769 Parcongo2 10 Nanhope 5,134 Vassele 9 Moneia 6,054 Ma110jone 13 Alto Ligonha Sede 4,648 Nao foi inquirida n/a Namirreco 3,836 Namale 8 - - - - - - - 30 92 494 0.00203 0.039 30 102 1701 0.00059 0.133 30 80 552 0.00181 0.043 n/a n/a n/a n/a n/a 30 85 376 0.00266 0.029 30 192 1966 0.00051 0.154 5 215 n/a n/a n/a 30 100 621 0.00161 0.049 29 109 728 0.00137 0.057 30 89 1314 0.00076 0.103 30 68 106 0.00941 0.008 29 90 215 0.00465 0.017 30 98 535 0.00187 0.042 30 50 158 0.00631 0.012 30 130 1038 0.00096 0.081 30 95 1107 0.00090 0.087 30 100 482 0.00207 30 110 0.00154 n/a n/a n/a 30 124 - - - - - - - - - - - - - - - - - - - - - ANNEXC10 CALCULATIONS FOR WEIGHTS 282,513 CUAMBA 46,116 LU. # 1 (P A. Cuamba) ~.0119 Bai!To Central - a . a 10 33 73 14 0.07069 0.004 L.U. # 1 (P .A. Cuamba) 22,089 Bairro Aerop. - a. 2 9 30 60 12 0.08688 0.003 L.U. # 2 (P A. Cuamba) 2,000 Bairro 3 de Fev. - a. 7 7 30 126 208 0.00482 0.052 Mitucue 4,923 Povoado Macaue 19 30 350 636 0.00157 0.161 N MANDIMBA 29,620 Madimba Sede Hl,605 POYOado Muambe 15 30 98 41 0 .02449 0.010 Madimba Sede 16,605 POYOado Tongolamusse 15 30 280 119 0.00840 0.030 Meluluca 3,5116 Powado Ngulungo 10 30 118 155 0.00645 0.039 Mitande Sede 9,427 Povoado Lugenda 7 32 587 192 0.00520 0.049 A MAJUNE 6,819 Malanga Sede 3,121 Povoado Muculungo 9 30 611 92 0.01083 0.023 s Malanga Sede 3,121 Povoado Lugenda 9 30 82 111 0.00898 0.028 Micuinha 1,345 POYOado Micuinha 9 33 75 215 0.00466 0.054 s Muaquia Sede 2,349 Powado Pindura 5 25 30 36 0.02772 0.009 A UCHINGA 32,664 Muchenga 8,346 auarteirao 1 o 15 30 200 169 0.00591 0.043 (Cidade) Sanjala 5,0G8 auarteirao 1 311 30 150 526 0.00190 0.133 Assumane 1,620 auarteirao 6 19 30 50 276 0.00362 0.070 Mitava 2,007 auarteirao 7 20 30 78 366 0.00273 0.092 LAGO 19,112 Meluluca 2,018 Povoado Milongue 11 31 180 447 0.00224 0.113 CobueSede 3,391 Polo'Qado Chiloca 11 32 80 115 0.029 Maniamba Sede 3,786 Povoado Chicotochi 4 30 100 50 0.013 Bandece 1,879 Povoado L.icunuile 6 33 130 ~~------------- - - - ANNEX C11 CALCULATIONS FOR WEIGHTS c 568,169 BALAMA 45,119 BalamaSede 7,455 Nacate 7 30 974 1566 0.00115 0.097 Muripa 11,725 Nairobi 10 30 259 209 0.00478 0.023 A Namara 4,096 Miooco 4 30 265 245 0.00408 0.027 Tavane 3,948 Copuito 5 30 89 107 0.00937 0.012 8 CHIURE 74,158 ChiureSede 14,800 Meriha 9 30 975 561 0.00178 0.063 0 Nacupe 5,439 Singano 8 30 520 724 0.00138 0.081 Katapua Sede 3,999 Matiquite 4 30 804 762 0.00131 0.085 OcuaSede 11 ,642 Meriha 11 30 757 677 0.00148 0.076 0 ANCUABE 36,925 Ancuabe Sede 6,557 Nakussa 5 30 1,010 729 0.00137 0.082 E Nacuale 6,759 Ncole 12 3() 156 262 0.00381 0.029 Metoro Sede 4,936 Megaruma 5 30 173 166 0.00603 0.019 L Nanjua 2,332 Nacole 5 30 90 183 0.00547 0.020 G MACOMIA 32,579 Macomia Sede 14,020 Chicomo 9 30 322 196 0.00511 0.022 Chai Sede 8,243 Utandacua 7 30 768 618 0.00162 0.069 A MucujoSede 7,344 Rueia 6 30 621 480 0.00208 0.054 Naunde 5,061 Ningaia 4 30 582 436 0.00230 0.049 0 M.DAPRAIA 33,551 M. da Praia Sede 18,826 Muengue 7 30 1,400 493 0.00203 0.055 0 Quelimane 15,355 Oyeya 17 30 61 64 0.01564 0.007 Quelimane 15,355 Magaia 17 30 483 485 0.00206 0.054 MbauSede 6,274 Mbau 3 30 1,500 I I I I I I I I I I I I I I I I I I I I I ANNEXD SAMPLE SIZE CALCULATION Basic Assumptions Low High Design Effect 2 10 Persons per household 6 Pet of Population < 5 Yrs. 0.18 Prevalence of diarrhoea 15 days 0.25 Indicator DPT3 coverage Measles coverage OPV3 coverage BCG coverage TT2 coverage (pregnancy) Iodized aalt consumption Use of ORT(1) in diarrhoea Percent low weight/age School enrolment Target population 12-23 mos 12-23 mos 12-23 mos 12-23 mas 0-11 mos Households Diarrhoea <5 yrs All <5 yrs 6-11 yrs Safe water Population Sanitation Population Indicator DPT3 coverage Measles coverage OPV3 coverage BCG coverage TT2 coverage (pregnancy) Iodized salt consumption Use of ORT(1) in diarrhoea Target population 12-59 mos 12-59 mos 12-59 mas 12-59 mas 0-11 mas Households Diarrhoea <5 yrs Estimated prevalence 0.47 0.47 0.47 0.72 0.37 0.1 0.3 0.3 0.6 0.3 0.28 Estimated prevalence 0.47 0.47 0.47 0.72 0.37 0.1 0.3 Margin of error 0.05 0.05 0.05 0.05 0.05 0.05 0.05 0.05 0.05 0.05 0.05 Margin of error 0.10 0.10 0.10 0.10 0.10 0.10 0.10 Required Required target number of sample households 797 3690 797 3690 797 3690 645 2987 746 3453 288 288 672 2489 672 622 768 711 3360 560 3226 538 Required Required target number of sample households 199 277 199 277 199 277 161 224 186 207 72 72 168 467 Percent low weight/age All < 5 yrs 0.3 0.10 168 187 School enrolment 6-11 yrs 0.6 0.10 192 213 Safe water Population 0.3 0.10 504 84 Sanitation Population 0.28 0.10 484 81 ~e.®hid · Numbw of H~usenolds ······•···•········ ( .• ···········••>. \\/:.·•········ ··> ::;· •. ······ ·················::·.•> •< ••••··: .• : .•. } .•. >.•< ··•·······•· ·.467 sample size = 4 x proportion x (1 - prooortlon) x design efTect margin of error x margin error I I I I I I I I I I I I I I I I I I 1. 2. 3. 4. 5. 6. 7. Indicator BCG coverage OPT coverage OPV coverage Measles coverage Tetanus toxoid (TT) vaccine coverage Salt iodization ORT use (pre-1993 definition) ANNEXEl DEFINITIONS OF THE INDICATORS Numerator Number 12-23-month-olds receiving BCG vaccine before 1st birthday ' Number 12-23-month-olds receiving DPT3 vaccine before 1st birthday Number 12-23-month-olds receiving OPV3 vaccine before lst birthday Number 12-23-month-olds receiving measles vaccine before 1st birthday Number of mothers of 0-11-month-olds with at least two doses of TT within 3 years of child's birth Number of households with salt testing positive for iodine/ iodate Number of diarrhoea cases among under-fives in 2 weeks before survey who received ORT and/or recommended home fluids Denominator Total number of 12~23~ month~olds surveyed Total number of 12-23- month-olds surveyed Total number of 12-23- month-olds surveyed Total number of 12-23- month-olds surveyed Total number of mothers of under-one-year~olds surveyed Total number of households surveyed Total number of diarrhoea cases among under-ftves in two weeks preceding survey I I I I I I I I I I I I I I I I I I I I I Indicator 8. ORT use (increased fluids and continued feeding) 9. Nutritional status: weight-for-age 10. (OPTIONAL) Nutritional status: height-for-age 11. Education: net enrollment rate 12. Water supply 13. Sanitation ANNRXE2 DEFINITIONS OF TilE INDICATORS Numerator Denominator Number of diarrhoeas cases Total number of diarrhoea among under-fives taking cases among under-fives in "more" fluids AND continued two weeks preceding eating survey Numb~r of under-fives who fall Total number of under-fives below -2 standard deviations weighed from the median weight-for-age of the NCHS/WHO standard; number who fall below -3 SDs Number of under-fives who fall Total number of under-fives below -2 standard deviations measured from the median height-for-age of the NCHS/WHO standard; number who fall below -3 SDs Number of children currently Total number of children of enrolled in primary school of primary-school age surveyed primary-school age Number of household residents Total number of household in defined "safe and convenient" residents surveyed categories Number of household residents Total number of household in defined "safe and convenient" residents surveyed categories ---------------------Distribution of Survey Sample Population by Gender & Age Mozambique, 1995 Age Groups >= 8o~. ------~TTGSTTG?~PT~~3d~~~TDTS~7837~7778ZD387DTI fi1 Male (%) 75- 79 ·.Female(%) 70-74 65- 69 60-64 55-59 50-54 45-49 40 - 44 35-39 30-34 25-29 20-24 15- 19 10- 14 05-09 ()()- 04 ~=~~=-' L.----'-'---~"'--- 10.0 8.0 Male 6.0 4.0 2.0 0 .0 2.0 4.0 6.0 Source: Multiple Indicator Cluster Survey, July/August 1995, Mozambique, UNICEF-GOM 8.0 10.0 Female I ANNEXG I INDIRECT ESTIMATION OF EARLY AGE MORTALITY FOR MOZAMBIQUE II =========~~~~~!~~!~~=~~~~~=:~::!~~~======================================z======================•======•==•==•========•========= AVERAGE NO. UNITED NATIONS MODELS AGE OF CHILDREN PROPORTION AGE (PALLONI-HELIGMAN EQUATIONS) I WOMAN BORN SURVIVING DEAD x LATIN AM CHILEAN SO ASIAN FAR EAST GENERAL q(X) t(X) q(X) t(X) q(X) t(X) q(X) t(X) q(X) t(X) ---·-----~----··-------------------------------------------------·----------------------M••·-----·-·----------------------------- I I I I I I I I I I I I \ 15-20 .407 .356 .125 1 .127 ( 1.1) .140 ( 1.3) .127 ( 1.1) .129 ( 1.3) .128 ( 1.2) 20-25 1.745 1.485 .149 2 .145 ( 2.6) .152 ( 2.8) .146 ( 2.6) .146 ( 2.7) .146 ( 2.6) 25-30 3.199 2.643 .174 3 .176 ( 4.4) .179 ( 4. 7) .178 ( 4.5) .174 ( 4.5) .175 ( 4.4) 30-35 4.779 3.858 .193 5 .212 ( 6.5) .207 ( 6.8) .213 ( 6.7) .206 ( 6.6) .209 ( 6.6) 35-40 5.768 4.670 .190 10 .223 ( 8.9) .211 ( 9.3) .220 ( 9.1) .217 ( 8.9) .220 ( 8.9) 40-45 6.593 5.214 .209 15 .237 ( 11.6) .232 (12.0) .236 ( 11. 9) .242 (11.5) .238 (11.6) 45-50 6.025 4.449 .262 20 .296 (15.2) .293 (15.6) .285 (15.8) .311 (14.8) .300 (15.1) MEAN AGE OF CHILDBEARING = 34.76 ======:======================================================z====~===c::c;::aa•a••••••=~••====•======•==••===:===•===::::::::z: UNITED NATIONS: LATIN AM CHILEAN SO ASIAN FAR EAST GENERAL AGE OF REFERENCE REFERENCE REFERENCE REFERENCE REFERENCE WOMAN DATE q DATE q DATE q DATE q DATE q ----------~----~--------~----------------~---------------~-------~-----------~·------------------------·------------------------INFANT MORTALITY RATE: q(1) 15-20 1994.5 . 127 1994.2 .140 1994.5 .127 1994.3 • 129 1994.4 .128 20-25 1993.0 .112 1992.8 .134 1992.9 .114 1992.8 • 118 1992.9 .117 25-30 1991.1 .120 1990.9 .148 ·1991. 1 .124 1991.0 .125 1991.1 .125 30-35 1989.0 .128 1988.7 .159 1988.9 .133 1988.9 .132 1989.0 .133 35-40 1986.7 .123 1986.3 .154 1986.5 .128 1986.6 • 126 1986.6 • 128 40-45 1983.9 .125 1983.5 .161 1983.6 .133 1984.0 • 130 1984.0 .130 45-50 1980.4 .143 1980.0 .185 1979.8 .150 1980.8 .146 1980.4 .148 -----------------------------------------------------------·--------------------------------------------------------------------PROBABILITY OF DYING BETWEEN AGES 1 AND 5: q 4 1 15-20 1994.5 .095 1994.2 .046 1994.5 .086 1994.3 .082 1994.4 .083 20·25 1993.0 .077 1992.8 .042 1992.9 .072 1992.8 .070 1992.9 .071 25-30 1991.1 .087 1990.9 .050 1991.1 .082 1991.0 .078 1991.1 .079 30-35 1989.0 .096 1988.7 .057 1988.9 .093 1988.9 .085 1989.0 .088 35-40 1986.7 .090 1986.3 .054 1986.5 .087 1986.6 .079 1986.6 .082 40-45 1983.9 .092 1983.5 .058 1983.6 .093 1984.0 .083 1984.0 .085 45-50 1980.4 .115 1980.0 .075 1979.8 .114 1980.8 • 100 1980.4 • 106 PROBABILITY OF DYING BY AGE 5: qC5> 15-20 1994.5 .210 1994.2 .179 1994.5 .202 1994.3 .201 1994.4 .200 20-25 1993.0 .181 1992.8 .171 1992.9 .178 1992.8 .180 1992.9 .179 25·30 1991.1 .197 1990.9 .191 1991.1 .196 1991.0 .194 1991.1 .194 30-35 1989.0 .212 1988.7 .207 1988.9 .213 1988.9 .2D6 1989,0 .209 35-40 1986.7 .202 1986.3 .199 1986.5 .204 1986.6 .195 1986.6 .200 40-45 1983.9 .205 1983.5 .210 1983.6 .213 1984.0 .202 1984.0 .204 45-50 1980.4 .241 1980.0 .246 1979.8 .247 1980.8 .231 1980.4 .238 =======:=========•===a:;z::==============:======================================================================•====•===c====== NOTE: A q VALUE OF .999 DENOTES VALUE FROM TABLE WITH LIFE EXPECTANCY LESS THAN 35 II .000 II GREATER THAN 75

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