Academic journal article Journal of Health Population and Nutrition

Multiple Indicator Cluster Survey 2003 in Afghanistan: Outdated Sampling Frame and the Effect of Sampling Weights on Estimates of Maternal and Child Health Coverage

Academic journal article Journal of Health Population and Nutrition

Multiple Indicator Cluster Survey 2003 in Afghanistan: Outdated Sampling Frame and the Effect of Sampling Weights on Estimates of Maternal and Child Health Coverage

Article excerpt

INTRODUCTION

The Afghanistan Ministry of Public Health (MoPH) initiated a strategy to reconstruct the health system in 2002 with a focus on laying "the foundations for equitable, quality health care for the people of Afghanistan" (1). The MoPH and other stakeholders required baseline population-level health data for planning and evaluation of this health strategy. Information was particularly needed on the coverage of health services to identify provinces with the greatest problems and to provide a reasonable starting point to gauge future change in the health sector. In the post-Taliban period, the first population-based health survey of national scope was conducted by the United Nations Children's Fund (UNICEF) and the Central Statistics Office (CSO) for the MoPH in 2003. This Multiple Indicator Cluster Survey (MICS) used data of the outdated population census from 1979 for sampling of households. This pragmatic decision was guided by the lack of a national census since 1979 and the urgent need to collect information on the coverage of health services across the country (2). However, questions persisted about the accuracy of the 2003 MICS estimates, given the substantial changes that occurred in the population since the sampling frame was constructed in 1979. An opportunity presented itself to re-assess the 2003 estimates when the CSO conducted a pre-census enumeration in 2004 and, in 2006, published the national and provincial census figures (3).

Population surveys, such as MICS, are important tools for planning, monitoring, and evaluation of health programmes in developing countries. The results of these surveys are used for summative evaluations and for influencing significant policy decisions on allocation of resources, continuation, and restructuring of programmes (4). In recent times, the 'instrumental' use of such results has increased as a greater proportion of decisions on programme oversight is directly based on these results (5). The estimates from the MICS 2003 have been put to 'instrumental' use as official health indicators for Afghanistan and have been used as benchmarks for health policy (6). Although the MICS 2003 was the first quantitative assessment of coverage of services targeted to women and children in the post-Taliban period, a further study was needed to assess whether these estimates would be adequate for providing baseline estimates for future evaluation of healthcare coverage in Afghanistan (7).

The basic approach in population-based surveys is to collect information from a random sample of people that is representative of the population (8). The sampling and data-collection are usually conducted in multiple stages to overcome the constraints of time, money, and logistics. In order for the results to reflect the situation in the population from which the data are collected, the sampling scheme must be incorporated in the analysis. This usually requires the use of sampling weights and statistical techniques to accommodate for the multi-stage sampling design. The purpose of weighting sample data is to assure the representativeness of the sample vis-a-vis the study population. The inverse of the selection probability of a sampled unit is used as the sampling weight for that unit. The population estimates generated without sampling weights could be biased (8,9). Evaluations of programmes based on the 'instrumental' use of these survey results can be adversely affected by this potential bias and lead to incorrect conclusions. The field of summative evaluation of health programmes can benefit from applied research on this aspect of survey methods. This is especially true in post-conflict settings where the lack of good, routine health information systems, vital registration systems, and census data make household surveys indispensable for information on the health of the population (10). The scarcity of reliable, comprehensive data is considered one of the greatest challenges in planning and evaluating post-conflict reconstruction of the health systems (11). …

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