| Autor: |
Zachary J Ward, Michael W Long, Stephen C Resch, Steven L Gortmaker, Angie L Cradock, Catherine Giles, Amber Hsiao, Y Claire Wang |
| Jazyk: |
angličtina |
| Rok vydání: |
2016 |
| Předmět: |
|
| Zdroj: |
PLoS ONE, Vol 11, Iss 3, p e0150735 (2016) |
| Druh dokumentu: |
article |
| ISSN: |
1932-6203 |
| DOI: |
10.1371/journal.pone.0150735 |
| Popis: |
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. |
| Databáze: |
Directory of Open Access Journals |
| Externí odkaz: |
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