Quantile Regression of Childhood Growth Trajectories: Obesity Disparities and Evaluation of Public Policy Interventions at the Local Level

Quantile regression applied to child growth trajectories has been proposed in the methodological literature but has only seen limited applications even though it is a promising framework for the evaluation of school-based policy interventions designed to address childhood obesity. Data that could be used to support such assessments, school-based collection of height and weight, has become increasingly common. Three states currently mandate annual collection and several other jurisdictions including California and New York City (NYC) collect BMI as part of physical fitness assessments. This has resulted in the establishment of extremely large databases that share important characteristics including the ability to define longitudinal growth curves by student with high coverage rates. In NYC public schools, starting in 2006, student records have been linked to registry, academic, and attendance data and across years resulting in a longitudinal dataset containing 9 cohorts with 2 million unique children. A high level of demographic and geographic detail allow for analysis of public policy at the local scale. We demonstrate the utility of quantile regression longitudinal growth curve models applied to BMI trajectories as a means of assessing policy interventions. Models consisting solely of age terms yield empirical curves similar to CDC growth charts; covariates modify these curves. Incorporating lag terms yields a distribution of possible growth trajectories and the effect of interventions can be explicitly quantified. We evaluate area-based and individual poverty measures, known strong correlates of child obesity, as a baseline assessment of the modeling framework. We then evaluate the impact of a real intervention (water jet installations). Our results indicate that students with access to water jets have a statistically significant leftward shift in the right tail of the BMI distribution relative to students without access to water jets. The absolute magnitude of the shift is comparable to the difference in BMI associated with student residential exposure to low versus extreme poverty.