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Johns Hopkins University
Health program evaluations typically are concerned with either mortality or nutritional status as an outcome variable. Health interventions can affect both child survival and nutritional status, therefore an impact evaluation should consider both outcomes. If these are to be considered simultaneously, the question is how to combine counts of dead with observations on the living children into a unified index of health status of a population, since the use of either mortality or nutritional status alone may give a misleading result. The purposes of the present study are as follows: first, to determine minimum indicator(s) that can be used to describe the impact of child survival interventions using survey data; second, to assess the relative contribution of child survival interventions and other competing factors affecting health. In 1988, we conducted a cluster survey that used a complex design and interviewed 8054 out of 184,129 households from Timor, Indonesia. A total of 22,440 births were reported to occur among 5,974 married women aged 15 to 49 years. Out of children ever born, 5,292 were born during the last five years, and of these, 282 children were reported to have died. Only 4715 of these children are finally used for the assessment of the index of health status. These had data on nutritional status (anthropometry), child survival interventions (i.e., growth monitoring, oral rehydration therapy, immunization status, antenatal care, and contraceptive use), and socioeconomic factors (i.e., maternal education, father’s occupation, availability of latrine, and total family income) are available. For all athropometric measurements, we consider under–5 children with a NCHS/CDC’s Z–score equal to or above −1 as a grade 0 (normal), below −1 to −2 as a grade I, −2 to −3 as a grade II, and −3 as a grade III of growth faltering. Our index of health status includes these four grades for surviving children, while a child death is assigned a grade IV, so that the index of health status is an ordinal scale variable with 5 possible values. An indirect estimation method is used to present mortality determinants at the aggregate level, while a proportional hazard model for grouped data is used to examine determinants of child survival at the individual level. A generalized linear model for ordinal data (proportional odds) is used to analyze nutritional and health status determinants. Although the mortality level is still high, there is an obvious trend towards mortality decline in the study area. This decline can be attributed to adoption of child survival interventions, specifically growth monitoring, immunization, family planning programs, but cannot be linked with oral rehydration therapy and antenatal care programs. More than half of under–5 years old children are underweight or stunted, and about 16 percent are wasted. Child survival interventions show no independent effect on the probability of becoming underweight, stunted, and wasted. The impact of child survival interventions on health status appears to arise primarily from the protection of children from death. At the same time, socioeconomic factors affect child health status primarily through the reduction of growth faltering. In contrast with the impact of child survival interventions on mortality, socioeconomic factors did not affect nutritional status through the utilization of growth monitoring, oral rehydration therapy, immunization, and family planning programs. Data show strong evidence that the determinants of mortality do not necessarily act as determinants of nutritional status. Among the three indices of health status created (based on weight– for–age, height–for–age, and height–for–age) the index that involves weight–for–age is considered the best indicator. This study shows that ordinary least squares can be used for the assessment of determ
New Index of Health, West Timor, Indonesia, Status-Child Survival