Ward, ZacharyLong, Michael W.Resch, StephenGortmaker, StevenCradock, AngieGiles, CatherineHsiao, AmberWang, Y. Claire2016-04-012016Ward, Zachary J., Michael W. Long, Stephen C. Resch, Steven L. Gortmaker, Angie L. Cradock, Catherine Giles, Amber Hsiao, and Y. Claire Wang. 2016. “Redrawing the US Obesity Landscape: Bias-Corrected Estimates of State-Specific Adult Obesity Prevalence.” PLoS ONE 11 (3): e0150735. doi:10.1371/journal.pone.0150735. http://dx.doi.org/10.1371/journal.pone.0150735.1932-6203http://nrs.harvard.edu/urn-3:HUL.InstRepos:26318761Background: 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.en-USBiology and Life SciencesPhysiologyPhysiological ParametersBody WeightObesityMedicine and Health SciencesBody Mass IndexPeople and PlacesPopulation GroupingsAge GroupsAdultsMorbid ObesityPhysical SciencesMathematicsStatistics (Mathematics)Statistical DataSurvey ResearchSurveysDemographyNutritionJournal Article2016-04-0110.1371/journal.pone.0150735