Abstract
BACKGROUND: Body mass index (BMI) and percentage of body fat (PBF) are used to measure obesity; however, their performance in identifying cardiometabolic risk in Southeast Asians is unclear. Generally, Asian women have higher PBF and lower BMI than do men and other ethnic populations. This study was conducted to address whether a discord exists between these measures in predicting obesity-related cardiometabolic risk in a Thai population and to test whether associations between the measures and risk factors for cardiovascular disease have a sex-specific inclination. METHODS: A total of 234 (76 men and 158 women) outpatients were recruited. BMI obesity cutoff points were ≥25.0 and ≥27.0 kg/m(2) and PBF cutoff points were ≥35.0% and ≥25.0% for women and men, respectively. Blood samples were analyzed for total cholesterol, triglycerides, low-density lipoprotein-cholesterol, high-density lipoprotein-cholesterol, lipoprotein subclasses, apolipoprotein A-I, apolipoprotein B, glucose, hemoglobin A1c, insulin, high-sensitive C-reactive protein (hsCRP), adiponectin, leptin, and 25-hydroxyvitamin D. RESULTS: Twenty-five percent of participants classified as normal-BMI had excessive fat, whereas 9% classified as normal-PBF had excessive BMI. Good relationships were found between BMI and PBF using sex stratification (R(2) >0.5). The prevalence of metabolic syndrome was markedly increased in overweight and/or excess body fat groups compared with lean group. Logistic regression analyses showed that BMI was the best predictor of hypertension. BMI was an independent predictor of insulin resistance, hyperglycemia, hypertriglyceridemia, and hyperleptinemia in women, whereas PBF was for men. However, PBF proved to be a good indicator for atherogenic lipoprotein particles in both sexes. Notably, neither index predicted increased hsCRP or 25-hydroxyvitamin D insufficiency. CONCLUSION: Considerable sex-specific variations were observed between BMI and PBF in their associations with and predictability of numerous cardiometabolic biomarkers. No single measure provides a comprehensive risk predication as shown herein with the Thai population, and therefore both should be applied in screening activities.