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Research Letter
February 9, 2009

Underdiagnosis of Obesity in Adults in US Outpatient Settings

Arch Intern Med. 2009;169(3):312-316. doi:10.1001/archinternmed.2008.582

Obesity affects nearly 32%—more than 60 million—American adults.1 The obesity epidemic imposes an enormous cost on the nation's health2 and economy.3 Evidence-based clinical guidelines recommend that treatment for obesity incorporates a 2-step process: assessment and management.4 Routine screening and accurate diagnosis are among the first steps leading to proper treatment. However, research on obesity screening and diagnosis in US outpatient settings is limited.

We examined the rates of obesity screening and diagnosis in a nationally representative sample of visits by patients 18 years and older to private physician offices and hospital outpatient departments across the United States. Data were obtained from the 2005 National Ambulatory Medical Care Surveys conducted by the National Center for Health Statistics (NCHS) (http://www.cdc.gov/nchs/about/major/ahcd/ahcd1.htm [accessed July 23, 2008]). Patient, physician, and clinical information is collected at each randomly selected visit and is recorded on NCHS standard patient record forms. Measurements of height and weight were captured for the first time in 2005. Body mass index (BMI) (calculated as weight in kilograms divided by height in meters squared) and obesity were defined according to accepted standards.4 Physician diagnoses were documented using open-ended responses for (up to 3) visit diagnoses, which were later coded by NCHS staff according to the International Classification of Diseases, Ninth Revision, Clinical Modification and check boxes for a prespecified list of current medical problems, one of which was obesity, regardless of visit diagnoses. The unit of analysis was the patient visit. National estimates were generated using the SURVEYMEANS procedure (version 9.1.3; SAS Institute, Cary, North Carolina) for the number and proportion of patient visits, including 95% confidence intervals (CIs), by taking into account the sampling weights and multistage-stratified probability sampling designs of the surveys.

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