BACKGROUND: While obesity is a growing epidemic in most developed countries, we still lack information on countries in economic transition. In this study, we evaluate the built environment, activity levels, economic status and dietary patterns associated with body mass index (BMI) greater than or equal to the 85th percentile among 3-year-old Ukrainian children living through the downturn in the economy during the mid-1990s. METHODS: We evaluated 883 3-year-old children from the Ukraine ELSPAC cohort. Principal components analysis was used as a data reduction tool for dietary, built environment and activity variables. We evaluated predictors of elevated BMI (> or = 85th percentile) using a multivariable logistic regression model. RESULTS: The final multivariable model showed that for every kilogram increase in the mother's weight, there was a corresponding 2% increase in risk of a child having a BMI> or = 85th percentile (OR=1.02; 95% CI: 1.00-1.04). A higher social class and a friendly neighborhood were associated with higher BMI, whereas infrequent outings to places that require spending money was associated with lower BMI. Except for meat consumption, none of the dietary variables were associated with elevated BMI. DISCUSSION: The picture in the Ukraine during the 1990s, a period of economic hardship, revealed that variables associated with higher standards of living were predictive of elevated BMI: higher social class, meat consumption and friendly neighborhoods. Variables associated with economic isolation were predictive of a lower risk of elevated BMI.
BACKGROUND: While obesity is a growing epidemic in most developed countries, we still lack information on countries in economic transition. In this study, we evaluate the built environment, activity levels, economic status and dietary patterns associated with body mass index (BMI) greater than or equal to the 85th percentile among 3-year-old Ukrainian children living through the downturn in the economy during the mid-1990s. METHODS: We evaluated 883 3-year-old children from the Ukraine ELSPAC cohort. Principal components analysis was used as a data reduction tool for dietary, built environment and activity variables. We evaluated predictors of elevated BMI (> or = 85th percentile) using a multivariable logistic regression model. RESULTS: The final multivariable model showed that for every kilogram increase in the mother's weight, there was a corresponding 2% increase in risk of a child having a BMI> or = 85th percentile (OR=1.02; 95% CI: 1.00-1.04). A higher social class and a friendly neighborhood were associated with higher BMI, whereas infrequent outings to places that require spending money was associated with lower BMI. Except for meat consumption, none of the dietary variables were associated with elevated BMI. DISCUSSION: The picture in the Ukraine during the 1990s, a period of economic hardship, revealed that variables associated with higher standards of living were predictive of elevated BMI: higher social class, meat consumption and friendly neighborhoods. Variables associated with economic isolation were predictive of a lower risk of elevated BMI.
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