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Background: Body mass index (BMI) is the most widely used measure to diagnose obesity. However, the accuracy of BMI in detecting excess body adiposity in the adult general population is largely unknown. Methods: A cross-sectional design of 13 601 subjects (age 20-79.9 years; 49% men) from the Third National Health and Nutrition Examination Survey. Bioelectrical impedance analysis was used to estimate body fat percent (BF%). We assessed the diagnostic performance of BMI using the World Health Organization reference standard for obesity of BF%425% in men and435% in women. We tested the correlation between BMI and both BF% and lean mass by sex and age groups adjusted for race. Results: BMI-defined obesity (X30 kg m À2 ) was present in 19.1% of men and 24.7% of women, while BF%-defined obesity was present in 43.9% of men and 52.3% of women. A BMIX30 had a high specificity (men ¼ 95%, 95% confidence interval (CI), 94-96 and women ¼ 99%, 95% CI, 98-100), but a poor sensitivity (men ¼ 36%, 95% CI, 35-37 and women ¼ 49%, 95% CI, 48-50) to detect BF%-defined obesity. The diagnostic performance of BMI diminished as age increased. In men, BMI had a better correlation with lean mass than with BF%, while in women BMI correlated better with BF% than with lean mass. However, in the intermediate range of BMI (25-29.9 kg m À2 ), BMI failed to discriminate between BF% and lean mass in both sexes. Conclusions: The accuracy of BMI in diagnosing obesity is limited, particularly for individuals in the intermediate BMI ranges, in men and in the elderly. A BMI cutoff ofX30 kg m À2 has good specificity but misses more than half of people with excess fat. These results may help to explain the unexpected better survival in overweight/mild obese patients.

Objective: We performed a systematic review and meta-analysis of studies that assessed the performance of body mass index (BMI) to detect body adiposity. Design: Data sources were MEDLINE, EMBASE, Cochrane, Database of Systematic Reviews, Cochrane CENTRAL, Web of Science, and SCOPUS. To be included, studies must have assessed the performance of BMI to measure body adiposity, provided standard values of diagnostic performance, and used a body composition technique as the reference standard for body fat percent (BF%) measurement. We obtained pooled summary statistics for sensitivity, specificity, positive and negative likelihood ratios (LRs), and diagnostic odds ratio (DOR). The inconsistency statistic (I2) assessed potential heterogeneity. Results: The search strategy yielded 3341 potentially relevant abstracts, and 25 articles met our predefined inclusion criteria. These studies evaluated 32 different samples totaling 31 968 patients. Commonly used BMI cutoffs to diagnose obesity showed a pooled sensitivity to detect high adiposity of 0.50 (95% confidence interval (CI): 0.43-0.57) and a pooled specificity of 0.90 (CI: 0.86-0.94). Positive LR was 5.88 (CI: 4.24-8.15), I 2 ¼ 97.8%; the negative LR was 0.43 (CI: 0.37-0.50), I 2 ¼ 98.5%; and the DOR was 17.91 (CI: 12.56-25.53), I 2 ¼ 91.7%. Analysis of studies that used BMI cutoffs X30 had a pooled sensitivity of 0.42 (CI: 0.31-0.43) and a pooled specificity of 0.97 (CI: 0.96-0.97). Cutoff values and regional origin of the studies can only partially explain the heterogeneity seen in pooled DOR estimates. Conclusion: Commonly used BMI cutoff values to diagnose obesity have high specificity, but low sensitivity to identify adiposity, as they fail to identify half of the people with excess BF%.

Normal weight obesity, defined as the combination of normal BMI and high BF content, is associated with a high prevalence of cardiometabolic dysregulation, metabolic syndrome, and CV risk factors. In women, NWO is independently associated with increased risk for CV mortality.

Obstructive sleep apnea (OSA) adversely affects multiple organs and systems, with particular relevance to cardiovascular disease. Several conditions associated with OSA, such as high BP, insulin resistance, systemic infl ammation, visceral fat deposition, and dyslipidemia, are also present in other conditions closely related to OSA, such as obesity and reduced sleep duration. Weight loss has been accompanied by improvement in characteristics related not only to obesity but to OSA as well, suggesting that weight loss might be a cornerstone of the treatment of both conditions. This review seeks to explore recent developments in understanding the interactions between body weight and OSA. Weight loss helps reduce OSA severity and attenuates the cardiometabolic abnormalities common to both diseases. Nevertheless, weight loss has been hard to achieve and maintain using conservative strategies. Since bariatric surgery has emerged as an alternative treatment of severe or complicated obesity, impressive results have often been seen with respect to sleep apnea severity and cardiometabolic disturbances. However, OSA is a complex condition, and treatment cannot be limited to any single symptom or feature of the disease. Rather, a multidisciplinary and integrated strategy is required to achieve effective and long-lasting therapeutic success.CHEST 2010; 137( 3 ): 711 -719Abbreviations: AHI 5 apnea-hypopnea index ; CPAP 5 continuous positive airway pressure ; HDL 5 high-density lipoprotein ; OSA 5 obstructive sleep apnea