Social, economic, health and environmental determinants of child nutritional status in three Central Asian Republics

Type Journal Article - Public health nutrition
Title Social, economic, health and environmental determinants of child nutritional status in three Central Asian Republics
Author(s)
Volume 12
Issue 10
Publication (Day/Month/Year) 2009
Page numbers 1871-1877
URL http://137.215.9.22/bitstream/handle/2263/13472/Nolunkcwe_Social(2009).pdf?sequence=1
Abstract
Objective: To investigate the comparative effect of social, economic, health and environmental characteristics on the nutritional status of children aged ,3 years in Central Asia. Design: Cross-sectional analysis using data from Demographic and Health Surveys. Setting: Uzbekistan, Kyrgyzstan and Kazakhstan. Subjects: Information on demographic health was gathered by Macro International Inc., Uzbekistan, Kyrgyzstan and Kazakhstan governments from a random sample of 14 067 households in the three countries. Anthropometric measurements were performed using standardized procedures on all children ,3 years of age (n 2358). Only children with plausible Z-scores (n 1989) were selected for subsequent analyses. Results: The main results indicated that country of residence, number of people in household, household wealth, birth weight, age of child, knowledge of oral rehydration therapy, maternal education, number of children ,5 years of age and source of drinking water were strong predictors of child nutritional status in these countries. Furthermore, chronic malnutrition was most prevalent in all three countries but at varied levels. An unexpected ?nding was that fully vaccinated children were more likely to be malnourished than children who were partially vaccinated. A further unexpected ?nding was that breast-feeding especially in children .6 months old had a strong negative association with stunting and underweight. Conclusions: In summary, the results from both the descriptive and binary logistic regression analysis are similar in terms of the explanatory variables and the statistical signi?cance in the models

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