Document Type

Journal Article

Publication Date

1-1-2016

Journal

PLoS ONE

Volume

11

Issue

3

DOI

10.1371/journal.pone.0150735

Keywords

Obesity--epidemiology

Abstract

BACKGROUND: State-level estimates from the Centers for Disease Control and Prevention (CDC) underestimate the obesity epidemic because they use self-reported height and weight. We describe a novel bias-correction method and produce corrected state-level estimates of obesity and severe obesity.

METHODS: Using non-parametric statistical matching, we adjusted self-reported data from the Behavioral Risk Factor Surveillance System (BRFSS) 2013 (n = 386,795) using measured data from the National Health and Nutrition Examination Survey (NHANES) (n = 16,924). We validated our national estimates against NHANES and estimated bias-corrected state-specific prevalence of obesity (BMI≥30) and severe obesity (BMI≥35). We compared these results with previous adjustment methods.

RESULTS: Compared to NHANES, self-reported BRFSS data underestimated national prevalence of obesity by 16% (28.67% vs 34.01%), and severe obesity by 23% (11.03% vs 14.26%). Our method was not significantly different from NHANES for obesity or severe obesity, while previous methods underestimated both. Only four states had a corrected obesity prevalence below 30%, with four exceeding 40%-in contrast, most states were below 30% in CDC maps.

CONCLUSIONS: Twelve million adults with obesity (including 6.7 million with severe obesity) were misclassified by CDC state-level estimates. Previous bias-correction methods also resulted in underestimates. Accurate state-level estimates are necessary to plan for resources to address the obesity epidemic.

Comments

Reproduced with permission of PLoS ONE.

Creative Commons License

Creative Commons License
This work is licensed under a Creative Commons Attribution 4.0 License.

Peer Reviewed

1

Open Access

1

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