Comparison of multiple obesity indices for cardiovascular disease risk classification in South Asian adults: The CARRS Study

Abstract

Background: We comparatively assessed the performance of six simple obesity indices to identify adults with cardiovascular disease (CVD) risk factors in a diverse and contemporary South Asian population.

Methods: 8,892 participants aged 20-60 years in 2010-2011 were analyzed. Six obesity indices were examined: body mass index (BMI), waist circumference (WC), waist-height ratio (WHtR), waist-hip ratio (WHR), log of the sum of triceps and subscapular skin fold thickness (LTS), and percent body fat derived from bioelectric impedance analysis (BIA). We estimated models with obesity indices specified as deciles and as continuous linear variables to predict prevalent hypertension, diabetes, and high cholesterol and report associations (prevalence ratios, PRs), discrimination (area-under-the-curve, AUCs), and calibration (index χ2). We also examined a composite unhealthy cardiovascular profile score summarizing glucose, lipids, and blood pressure.

Results: No single obesity index consistently performed statistically significantly better than the others across the outcome models. Based on point estimates, WHtR trended towards best performance in classifying diabetes (PR = 1.58 [1.45-1.72], AUC = 0.77, men; PR = 1.59 [1.47-1.71], AUC = 0.80, women) and hypertension (PR = 1.34 [1.26,1.42], AUC = 0.70, men; PR = 1.41 [1.33,1.50], AUC = 0.78, women). WC (mean difference = 0.24 SD [0.21-0.27]) and WHtR (mean difference = 0.24 SD [0.21,0.28]) had the strongest associations with the composite unhealthy cardiovascular profile score in women but not in men.

Conclusions: WC and WHtR were the most useful indices for identifying South Asian adults with prevalent diabetes and hypertension. Collection of waist circumference data in South Asian health surveys will be informative for population-based CVD surveillance efforts.

Fig 1. Associations (PRs or mean difference) between deciles of obesity indices and cardiovascular risk factors in urban South Asian men (panel A) and women (panel B).

Models compare cardiovascular outcomes in higher compared to the lowest decile of each anthropometric index and were adjusted for age in years, age-squared, and city of residence. Deciles were included in the outcome models as a 10-level categorical variable with the first decile as the reference category. Prevalence ratios are shown for diabetes, elevated cholesterol, and hypertension and mean differences (betas) are shown for the cardiovascular risk index. The y-axis differs across the plots to allow for better visualization of the point estimates Data are available in table form in S2 Table and S3 Table. Abbreviations: BMI, body mass index; WC, waist circumference; WHtR, waist-height ratio; WHR, waist-hip ratio; LTS, log of the sum of triceps and subscapular skinfolds; BIA, bioelectric impedance analysis derived percent body fat.

Fig 2

Summary performance of obesity indices in classifying CVD risk factors in men (panel A) and women (panel B): Associations (prevalence ratios or mean difference), discrimination (area under the curve, AUC), and calibration (quasi-likelihood under the independence model criterion; lower value indicates better model fit). All obesity indices were standardized to mean = 0 and SD = 1 to facilitate comparisons across measures. Associations were adjusted for age in years, the age-squared, and city of residence. Data are available in table form in S4 Table. Abbreviations: BMI, body mass index; WC, waist circumference; WHtR, waist-height ratio; WHR, waist-hip ratio; LTS, log of the sum of triceps and subscapular skinfolds; BIA, bioelectric impedance analysis derived percent body fat; AUC, area under the curve.