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1.
Pediatr Obes ; 10(3): 234-44, 2015 Jun.
Article in English | MEDLINE | ID: mdl-24961794

ABSTRACT

BACKGROUND: The ideal means of identifying obesity in children and adolescents has not been determined although body mass index (BMI) is the most widely used screening tool. OBJECTIVE: We performed a systematic review and meta-analysis of studies assessing the diagnostic performance of BMI to detect adiposity in children up to 18 years. METHODS: Data sources were EMBASE, MEDLINE, Cochrane, Database of Systematic Reviews Cochrane CENTRAL, Web of Science and SCOPUS up to March 2013. Studies providing measures of diagnostic performance of BMI and using body composition technique for body fat percentage measurement were included. RESULTS: Thirty-seven eligible studies that evaluated 53 521 patients, with mean age ranging from 4 to 18 years were included in the meta-analysis. Commonly used BMI cut-offs for obesity showed pooled sensitivity to detect high adiposity of 0.73 (confidence interval [CI] 0.67-0.79), specificity of 0.93 (CI 0.88-0.96) and diagnostic odds ratio of 36.93 (CI 20.75-65.71). Males had lower sensitivity. Moderate heterogeneity was observed (I(2) = 48%) explained in meta-regression by differences across studies in race, BMI cut-off, BMI reference criteria (Center for Disease Control vs. International Obesity Task Force) and reference standard method assessing adiposity. CONCLUSION: BMI has high specificity but low sensitivity to detect excess adiposity and fails to identify over a quarter of children with excess body fat percentage.


Subject(s)
Pediatric Obesity/diagnosis , Adiposity , Adolescent , Body Composition , Body Mass Index , Child , Female , Humans , Male , Pediatric Obesity/prevention & control , Predictive Value of Tests , Sensitivity and Specificity
2.
Int J Obes (Lond) ; 34(5): 791-9, 2010 May.
Article in English | MEDLINE | ID: mdl-20125098

ABSTRACT

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)=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. 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%.


Subject(s)
Adiposity , Body Composition , Body Mass Index , Obesity/diagnosis , Humans , Predictive Value of Tests , United States
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