@article {570496, title = {Redrawing the US Obesity Landscape: Bias-Corrected Estimates of State-Specific Adult Obesity Prevalence}, journal = {PLoS One}, volume = {11}, number = {3}, year = {2016}, month = {2016}, pages = {e0150735}, 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.}, keywords = {Adult, Age Factors, Behavioral Risk Factor Surveillance System, Body Mass Index, Datasets as Topic, Female, Humans, Male, Obesity, Obesity, Morbid, Prevalence, Public Health Surveillance, Self Report, United States}, issn = {1932-6203}, doi = {10.1371/journal.pone.0150735}, author = {Ward, Zachary J and Long, Michael W and Resch, Stephen C and Gortmaker, Steven L and Cradock, Angie L and Giles, Catherine and Hsiao, Amber and Wang, Y Claire} }