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II I I I Il I A -- II I I I I I I il I I il I !I .I I I I I I iI l ~ · r . ~ I I I I I I I I I I I I I This survey report is the result of fruitful cooperation between the National Department of Statistics I (DNE) of the Ministry of Planning and Finance, and the Planning, Monitoring and Evaluation section of the United Nations Children's Fund. I Mr.Manuel da Costa Gaspar (DNE, coordinator) Mr.Ronald Ernst van Dijk (UNICEF, coordinator, analysis and report) Mr.Gurpreet Samrow (UNICEF, statistical analysis) I Mr.Luis Mungamba (DNE, data processing) Ms.lracema Vasconcelos (UNICEF, administration) Mr.Leonel Lopes (DNE consultant, questionnaire and data collection) I 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 INTRODUCTION I 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 I war which started almost immediately after winning its Independence from colonial powers in 1975. I 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 I 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 I could be calculated for social indicators. I 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, I 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 I Government and UNICEF. I 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 I 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 I basis.· UNICEF is prepared to continue to assist the Government in this effort. I '---:4<-6~1'----- I I Shob Jhie Representative I Maputo, June 1996 I I I \1 ---- ~ -~· - I Multi-Indicator Cluster Survey- 1995, GOM-UNICEF I TABLE OF CONTENTS I Page II I. Executive SlDlliDary and conclusions 4 II n. Summary of MICS results 8 II 1. Introduction 10 II 2. Purpose and objective 10 3. Methodology 11 I 3.1 Questionnaire design 11 3.2 Selection and training interviewers 11 3.3 Sampling 12 I 3.4 Data collection 13 3.5 Data processing 13 I 4. Analysis and results 14 II 4.1 Demography 14 I 4.2 Vaccination 15 4.3 Oral rehydration therapy 18 4.4 Nutrition 20 I Salt iodization 20 Protein energy malnutrition 21 4.5 Education 22 4.6 Water and sanitation 24 Reference literature 26 I Annex A Questionnaire B Provincial statistical weights I C Cluster statistical weights D Sample size calculation E Definitions of indicators I F Graph: Distribution of sample population by age and gender G Early age mortality calculation I I I I Multi-Indicator Cluster Survey- 1995, GOM-UNICEF I I. EXECUTIVE SUMMARY AND CONCLUSIONS Coordinated by the Ministry of Planning & Finance (MPF) department of statistics (DNE), I a survey was carried out in 1995 in close cooperation with the Ministry of Health (MOH) with technical and financial support from UNICEF. I 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 I 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 I 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 I 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. I 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 I sources, such as Government reports and surveys. I 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 I 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 I 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 I per 1,000 live births. Maternal mortality rate (MMR) calculation is beyond the scope of data from the MICS. I However, the recently refined technique of indirect calculation of MMR estimates for Mozambique I 4 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 I 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 I uncommon in populations living in extremely difficult circumstances. I 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 I 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 I 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 I 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. I 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. I 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 II least two vaccinations before delivery of the last child. In summary, vaccination coverage is low for all antigens and provincial differences are big. I 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 I 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.
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