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Comparability and utility of body composition measurement vs. anthropometric measurement for assessing obesity related health risks in Korean men
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Journal
Int J Clin Prart.
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Authors
J.Y. Kim, S. Oh, M. R. Chang, Y.G. Cho, K.H. Park, Y.J.Paek, S.H.Yoo, J.J. Cho, I.D. Caterson, H.J. Song
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Published
January 2023
Background: Obesity is commonly assessed by body mass index (BMI) of which limitations come from an inability to distinguish body fat mass from lean mass. Several anthropometric measurements, including BMI, waist circumference, waist-to-height ratio and waist-to-hip ratio have been used to predict metabolic syndrome. The purpose of this study was to evaluate the utility of FMI or BF% combined with previous known anthropometric indices to assess the risk of metabolic syndrome in clinical practice.
Methods: In 5534 men visiting a hospital for health check-ups, blood tests, anthropometric measurements and body composition analysis using BIA were performed. Logistic regression analysis was performed to compare the odds ratios for metabolic syndrome and each component of metabolic syndrome among BMI, waist-to-height ratio, waist-to-hip ratio, FMI and BF%. The area under the curve (AUC) of the receiver operating characteristic curve (ROC) for metabolic syndrome was compared between several measurements. The net reclassification improvement with integrated discrimination improvement was used for assessing value of body composition measurement.
Results: The adjusted odds ratios of metabolic syndrome was 1.80 (95% CI, 1.71-1.89) for FMI and 1.15 (95% CI, 1.13-1.17) for BF%. Odds ratio of each metabolic component was highest for FMI among several anthropometric and body composition measurements. AUCs using the ROC curve for metabolic syndrome was highest for waist-to-height ratio, 0.823 (95% CI, 0.808-0.837) by National Cholesterol Education Program criteria. FMI caused a mild increase in integrated discrimination improvement when combined with waist-to-height ratio.
Conclusions: Waist-to-height ratio seems to be the best screening tool for evaluating metabolic syndrome in Korean men, and adding FMI could result in a modest increase in integrated discrimination improvement.
Methods: In 5534 men visiting a hospital for health check-ups, blood tests, anthropometric measurements and body composition analysis using BIA were performed. Logistic regression analysis was performed to compare the odds ratios for metabolic syndrome and each component of metabolic syndrome among BMI, waist-to-height ratio, waist-to-hip ratio, FMI and BF%. The area under the curve (AUC) of the receiver operating characteristic curve (ROC) for metabolic syndrome was compared between several measurements. The net reclassification improvement with integrated discrimination improvement was used for assessing value of body composition measurement.
Results: The adjusted odds ratios of metabolic syndrome was 1.80 (95% CI, 1.71-1.89) for FMI and 1.15 (95% CI, 1.13-1.17) for BF%. Odds ratio of each metabolic component was highest for FMI among several anthropometric and body composition measurements. AUCs using the ROC curve for metabolic syndrome was highest for waist-to-height ratio, 0.823 (95% CI, 0.808-0.837) by National Cholesterol Education Program criteria. FMI caused a mild increase in integrated discrimination improvement when combined with waist-to-height ratio.
Conclusions: Waist-to-height ratio seems to be the best screening tool for evaluating metabolic syndrome in Korean men, and adding FMI could result in a modest increase in integrated discrimination improvement.
