Adiposity measurements in association with metabolic syndrome in older men have different clinical implications

Chun-Hsien Hsu, Jiunn-Diann Lin, Chang-Hsun Hsieh, Shu Chuen Lau, Wei-Yong Chiang, Yen-Lin Chen, Dee Pei, Jin-Biou Chang
Nutrition Research 2014, 34 (3): 219-25
Obesity is a major public health problem, and measuring adiposity accurately and predicting its future comorbidities are important issues. Therefore, we hypothesized that 4 adiposity measurements, body mass index (BMI), waist circumference (WC), waist-to-height ratio, and body fat percentage, have different physiological meanings and distinct associations with adverse health consequences. This study aimed to investigate the relationship of these 4 measurements with metabolic syndrome (MetS) components and identify the most associated factor for MetS occurrence in older, non-medicated men. Cross-sectional data from 3004 men, all 65 years of age and older, were analyzed. The correlation and association between adiposity measurements and MetS components were evaluated by Pearson correlation and multiple linear regression. Based on multivariate logistic regression, BMI and WC were significantly associated with MetS and were selected to build a combined model of receiver operating characteristic curves to increase the diagnosis accuracy for MetS. The results show that BMI is independently associated with systolic and diastolic blood pressure; WC and body fat percentage are associated with fasting plasma glucose and log transformation of triglyceride; BMI and WC are negatively associated with high-density lipoprotein cholesterol (HDL-C); and WC is a better discriminate for MetS than BMI, although the combined model (WC + BMI) is not significantly better than WC alone. Based on these results, we conclude that the 4 adiposity measurements have different clinical implications. Thus, in older men, BMI is an important determinant for blood pressure and HDL-C. Waist circumference is associated with the risk of fasting plasma glucose, HDL-C, triglyceride, and MetS occurrence. The combined model did not increase the diagnosis accuracy.

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