Diagnostic performance of body mass index to identify obesity as defined by body adiposity: A systematic review and meta-analysis

University of Missouri School of Medicine, Columbia, MO, USA.
International journal of obesity (2005) (Impact Factor: 5). 05/2010; 34(5):791-9. DOI: 10.1038/ijo.2010.5
Source: PubMed


We performed a systematic review and meta-analysis of studies that assessed the performance of body mass index (BMI) to detect body adiposity.
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.
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)=97.8%; the negative LR was 0.43 (CI: 0.37-0.50), I (2)=98.5%; and the DOR was 17.91 (CI: 12.56-25.53), I (2)=91.7%. Analysis of studies that used BMI cutoffs >or=30 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.
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%.

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    • "" Normal Fat " group – normal BMI (<25 kg/m 2 ), normal BF% (≥22%,<30%); " Hidden Fat " profile group – normal BMI (<25 kg/m 2 ), high BF% (≥30%); " Apparent Fat " profile group – high BMI (≥25 kg/m 2 ), high BF% (≥30%) (Oliveros et al. 2014; Okorodudu et al. 2010; "
    SpringerPlus 01/2015; 4(128).
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    • "The subject's legs were parted, and the arms were adducted by approximately 30° to prevent skin-to-skin contact. The cut-off used to define obesity was ≥35% BF, which is the most frequently used value reported in the literature.23,24,25,26 "
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    ABSTRACT: Purpose Obesity is a major public health issue and is associated with many metabolic abnormalities. Consequently, the assessment of obesity is very important. A new measurement, the body adiposity index (BAI), has recently been proposed to provide valid estimates of body fat percentages. The objective of this study was to compare the BAI and body mass index (BMI) as measurements of body adiposity and metabolic risk. Materials and Methods This was a cross-sectional analysis performed on Korean women. The weight, height, and hip circumferences of 2950 women (mean age 25±5 years old, 18-39 years) were measured, and their BMI and BAI [hip circumference (cm)/height (m)1.5-18] values were calculated. Bioelectric impedance analysis was used to evaluate body fat content. Glucose tolerance status was assessed with a 75-g oral glucose tolerance test, and insulin sensitivity was estimated with the insulin sensitivity index. Results BMI was more significantly correlated with fat mass and fat percentage. Additionally, BMI was also more significantly associated with metabolic parameters, including fasting glucose, post-load 2-h glucose, fasting insulin, post-load 2-h insulin, triglycerides, and high density lipoprotein cholesterol than BAI. Receiver operating characteristic curve analysis revealed that BMI was a better tool for predicting body fat percentage than BAI. Insulin sensitivity and metabolic syndrome were more significantly associated with BMI than with BAI. Conclusion In Korean women, the current BMI-based classifications for obesity might be superior to BAI-based measurements for determining obesity and predicting metabolic risk.
    Yonsei Medical Journal 07/2014; 55(4):1028-35. DOI:10.3349/ymj.2014.55.4.1028 · 1.29 Impact Factor
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    • "The most commonly used definition of obesity is based on BMI calculation. However, BMI has only 50% sensitivity to detect excess adiposity [36] and it is not able to differentiate between an elevated body fat content and preserved or increased lean mass, especially in individuals with a BMI < 30 kg/ m 2 . This may explain better cardiovascular outcomes seen in overweight and mildly obese [37] and increased risk of mortality in normal weight subjects with central obesity [38]. "
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    ABSTRACT: Objective: Increased aortic stiffness may be one of the mechanisms by which obesity increases cardiovascular risk independently of traditional risk factors. While body mass index (BMI) is generally used to define excess adiposity, several studies have suggested that measures of central obesity may be better predictors of cardiovascular risk. However, data comparing the association between several measures of central and general obesity with aortic stiffness in the general population are inconclusive. Methods: In 1031 individuals (age 53 ± 13 years, 45% men) without manifest cardiovascular disease randomly selected from population, we tested the association between parameters of central obesity (waist circumference - WC, waist-to-hip-ratio - WHR, waist-to-height ratio - WHtR) and general obesity (BMI) with carotid-femoral pulse wave velocity (cfPWV). Results: In univariate analysis, WC and WHtR were more strongly associated with cfPWV than BMI in both genders, while WHR showed a stronger association with cfPWV only in women. WHtR was more closely associated with cfPVW than WHR. This difference between obesity measures remained after multivariate adjustment. When the fully adjusted hierarchical regression was used, among central obesity measures, WHtR had the largest additive value on top of BMI, while there was no additive value of BMI on top of WHtR. Conclusion: Central obesity parameters are more closely associated with aortic stiffness than BMI. Of central adiposity measures, WHtR has the strongest association with aortic stiffness beyond body mass index and cardiovascular risk factors. Our results suggest that WHtR may be the best anthropometric measure of excess adiposity in the general population.
    Atherosclerosis 06/2014; 235(2):625-631. DOI:10.1016/j.atherosclerosis.2014.05.958 · 3.99 Impact Factor
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