Differential correlates of nutritional status in Kinshasa, Zaire.
In an effort to search for causes of malnutrition in the urban environment to guide intervention efforts, a study of more than 2000 mother/child pairs was conducted in Kinshasa, Zaire. Under the auspices of the Zairian National Nutrition Planning Center a representative sample of a large lower class urban population was interviewed at two points in time. One phase covered morbidity and nutritional status measurements for all children under five years of age. A second phase examined a complex set of socioeconomic and behavioural variables possibly linked to nutritional outcomes for a 20% sample of the households. After merging the data sets bivariate and multivariate regression analyses were performed twice, using the youngest child and the household as the unit of analysis respectively. Results showed that different complexes of variables predicted malnutrition as measured by three separate anthropometric measures. For so-called acute malnutrition (weight-for-height) morbidity, migration, and diarrhoeal knowledge, all emerged as significant predictors. Chronic malnutrition (height-for-age), however, was only significantly predicted by zone of residence, a level of living score, and recent morbidity when all major variables were considered in the regression model. Factors that were significant predictors of each of these two indices also were predictors of the third nutritional indicator, weight-for-age. Birth interval also was associated with this index. The findings here suggest more careful scrutiny of the nature, causes, interpretation and use of these widely accepted measures of nutritional status.
Bertrand
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Department of Biostatistics and Epidemiology, School of Public Health and Tropical Medicine Tulane University, New Orleans, Louisiana.
Mock
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NB
Franklin
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D000293:Adolescent; D000328:Adult; D002675:Child, Preschool; D015023:Democratic Republic of the Congo; D005260:Female; D006801:Humans; D007223:Infant; D008297:Male; D009752:Nutritional Status; D011204:Poverty Areas; D011502:Protein-Energy Malnutrition / Q000453:epidemiology; D012959:Socioeconomic Factors; D014505:Urban Population