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Journal of Obesity
Volume 2010 (2010), Article ID 637829, 7 pages
Research Article

Variation in Provider Identification of Obesity by Individual- and Neighborhood-Level Characteristics among an Insured Population

1Department of Health Policy and Management, Johns Hopkins Bloomberg School of Public Health, 624 N. Broadway, Room 451, Baltimore, MD 21205, USA
2Division of General Internal Medicine, Department of Medicine, Johns Hopkins University School of Medicine, Baltimore, MD 21205, USA
3Welch Center for Prevention, Epidemiology, and Clinical Research, Johns Hopkins Medical Institutions, Baltimore, MD 21205, USA
4Department of Epidemiology, Johns Hopkins Bloomberg School of Public Health, Baltimore, MD 21205, USA

Received 25 August 2009; Revised 4 January 2010; Accepted 23 February 2010

Academic Editor: Mark A. Pereira

Copyright © 2010 Sara N. Bleich et al. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.


Objective. The purpose of this study was to examine whether neighborhood- and individual-level characteristics affect providers' likelihood of providing an obesity diagnosis code in their obese patients' claims. Methods. Logistic regressions were performed with obesity diagnosis code serving as the outcome variable and neighborhood characteristics and member characteristics serving as the independent variables (N = 16,151 obese plan members). Results. Only 7.7 percent of obese plan members had an obesity diagnosis code listed in their claims. Members living in neighborhoods with the largest proportions of Blacks were 29 percent less likely to receive an obesity diagnosis ( ). The odds of having an obesity diagnosis code were greater among members who were female, aged 44 or below, hypertensive, dyslipidemic, BMI ≥ 35 kg/ , had a larger number of provider visits, or who lived in an urban area (all ). Conclusions. Most health care providers do not include an obesity diagnosis code in their obese patients' claims. Rates of obesity identification were strongly related to individual characteristics and somewhat associated with neighborhood characteristics.