Analyzing Screening Policies for Childhood Obesity

Yan Yang (), Jeremy D. Goldhaber-Fiebert () and Lawrence M. Wein ()
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Yan Yang: Institute for Computational and Mathematical Engineering, Stanford University, Stanford, California 94305
Jeremy D. Goldhaber-Fiebert: Centers for Health Policy and Primary Outcomes Research, Stanford University School of Medicine, Stanford, California 94305
Lawrence M. Wein: Graduate School of Business, Stanford University, Stanford, California 94305

Management Science, 2013, vol. 59, issue 4, 782-795

Abstract: Because of the health and economic costs of childhood obesity, coupled with studies suggesting the benefits of comprehensive (dietary, physical activity, and behavioral counseling) intervention, the U.S. Preventive Services Task Force recently recommended childhood screening and intervention for obesity beginning at age 6. Using a longitudinal data set consisting of the body mass index of 3,164 children up to age 18 and another longitudinal data set containing the body mass index at ages 18 and 40 and the presence or absence of disease (hypertension and diabetes) at age 40 for 747 people, we formulate and numerically solve---separately for boys and girls---a dynamic programming problem for the optimal biennial (i.e., at ages 2,4,...,16) obesity screening thresholds. Unlike most screening problem formulations, we take a societal viewpoint, where the state of the system at each age is the population-wide probability density function of the body mass index. Compared to the biennial version of the task force's recommendation, the screening thresholds derived from the dynamic program achieve a relative reduction in disease prevalence of 3% at the same screening (and treatment) cost, or---because of the flatness of the disease versus screening trade-off curve---achieves the same disease prevalence at a 28% relative reduction in cost. Compared to the task force's policy, which uses the 95th percentile of body mass index (from cross-sectional growth charts tabulated by the Centers for Disease Control and Prevention) as the screening threshold for each age, the dynamic programming policy treats mostly 16-year-olds (including many who are not obese) and very few males under 14 years old. Although our results suggest that adult hypertension and diabetes are minimized by focusing childhood obesity screening and treatment on older adolescents, the shortcomings in the available data and the narrowness of the medical outcomes considered prevent us from making a recommendation about childhood obesity screening policies. This paper was accepted by Assaf Zeevi, stochastic models and simulation.

Keywords: dynamic programming; applications; healthcare; statistics (search for similar items in EconPapers)
Date: 2013
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Citations: View citations in EconPapers (3)

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