Childhood overweight in the United States: a quantile regression approach.

The prevalence of overweight children in the United States has increased dramatically over the past two decades, and is creating well-known public health problems. Moreover, there is also evidence that children who are not overweight are becoming heavier. We use quantile regression models along with standard ordinary least squares (OLS) models to explore the correlates of childhood weight status and overweight as measured by the Body Mass Index (BMI). This approach allows the effects of covariates to vary depending on where in the BMI distribution a child is located. Our results indicate that OLS masks some of the important correlates of child BMI at the upper and lower tails of the weight distribution. For example, mother's education has no effect on black children, but is associated with improvements in BMI for overweight white boys and underweight white girls. Conversely, mother's cognitive aptitude has no effect on white boys, but is associated with BMI improvements for underweight black children and overweight white girls. Further, we find that underweight white children and black girls experience similar improvements in BMI as they get older, but that for black boys there is little if any association between age and BMI anywhere in the BMI distribution.