4.0 Article

DXA-Derived vs Standard Anthropometric Measures for Predicting Cardiometabolic Risk in Middle-Aged Australian Men and Women

Journal

JOURNAL OF CLINICAL DENSITOMETRY
Volume 25, Issue 3, Pages 299-307

Publisher

ELSEVIER SCIENCE INC
DOI: 10.1016/j.jocd.2022.01.006

Keywords

Adiposity; visceral adipose tissue; Busselton Healthy Ageing Study; cardiometabolic risk; dual-energy X-ray absorptiometry

Funding

  1. WA Country Health Service

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The study investigates whether DXA adiposity measures are more effective than standard anthropometric measures in predicting cardiometabolic risk factors in middle-aged individuals. The results suggest that DXA-VAT is superior to other measures in predicting metabolic syndrome and its components.
It is not clear if dual-energy X-ray absorptiometry (DXA) adiposity measures are superior to standard anthropometric measures for predicting cardiometabolic (CM) risk factors in a middle-aged general popula-tion. In the Busselton Healthy Ageing Study, we assessed a range of standard anthropometric and DXA-derived adiposity measures to predict metabolic syndrome (MetS) and CM risk factors in 4831 baby boomers aged 45-69 yr. Anthropometric and whole body DXA (GE Lunar Prodigy) measures were col-lected. Cross-sectional relationships of overall adiposity (BMI; DXA fat mass index, body fat %), central adi-posity (waist circumference (WC); DXA trunk fat, android fat, abdominal visceral adipose tissue (VAT)) and ratio index (waist-to-hip ratio; DXA trunk/legs fat, android/gynoid ratio, VAT/total fat) with MetS and its components (as both continuous and binary outcomes) were evaluated using linear and logistic regression adjusting for age and lifestyle factors. Youden's Index was used to determine the optimal cut-points for pre-dicting MetS. In linear regression analyses, central adiposity measures showed stronger associations with MetS score and CM risk factors than overall adiposity measures and fat ratio index, and DXA-VAT provided stronger associations than WC. Logistic regression models showed similar findings. For MetS diagnosis present in 35.9% of males and 24.4% of females, the highest odds ratio (95% CI) per SD change was observed for DXA-VAT (males: 5.02 [4.28, 5.88]; females: 3.91 [3.40, 4.49]), which remained significant (all p < 0.001) after further adjustment for BMI (males: 3.27 [2.65, 4.02]; females: 3.37 [2.79, 4.06]) or WC (males: 2.46 [1.95, 3.10]; females: 2.75 [2.21, 3.43]). The optimal DXA-VAT mass cut-point for predicting MetS was 1608 grams in males and 893 grams in females. DXA-VAT was superior to standard anthropometric and other DXA-derived adiposity measures for prediction of cardiometabolic risk factors, and has clinical utility for identifying middle-aged individuals at increased risk of MetS.

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