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(Hypertension. 2005;46:645.)
© 2005 American Heart Association, Inc.
Editorial Commentaries |
From the Departments of Nutrition and Epidemiology, Harvard School of Public Health, Channing Laboratory, Department of Medicine, Brigham and Womens Hospital and Harvard Medical School, Boston, Mass.
Correspondence to Dr Frank Hu, Department of Nutrition, Harvard School of Public Health, 665 Huntington Ave, Boston, MA 02115. E-mail frank.hu@channing.harvard.edu
An extract of the first 250 words of the full text is provided, because this article has no abstract. |
Obesity has reached epidemic proportions in the United States. Currently, one third of US adults are classified as obese and another one third as overweight. Obesity is also a growing epidemic in other parts of the world. The French, who have enjoyed relatively low rates of obesity and cardiovascular disease (CVD), are also experiencing expanding waistlines.1
Although the health hazards of obesity are widely recognized, the relationship between the middle range of body mass index (BMI) values and mortality is less clear because epidemiologic studies have found linear and curve-linear relationships between BMI and mortality. However, epidemiologic studies of BMI and mortality have been fraught with methodologic problems, including failure to control for cigarette smoking; inappropriate control of biologic effects of obesity, such as hypertension and hyperglycemia; and failure to consider weight loss attributable to subclinical diseases.2 These biases have led to the typical J- or U-shaped relationship between BMI and mortality seen in many epidemiologic studies and to a systematic underestimate of the impact of obesity on premature mortality. For example, in a recent analysis of NHANES (National Health and Nutrition Examination Survey) data sets, Flegal et al3 found that excess mortality attributable to obesity was much lower than reported previously, and that being overweight was associated with a lower mortality compared with normal weight. However, these findings are most likely the result of artifact attributable to the methodologic flaws mentioned above. In particular, the study failed to exclude persons from the analyses who had chronic diseases at baseline
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