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Title: Determining the best method for evaluating obesity and the risk for non-communicable diseases in women of childbearing age by measuring the body mass index, waist circumference, waist-to-hip ratio, waist-to-height ratio, A Body Shape Index, and hip index.
Author: Hewage N, Wijesekara U, Perera R.
Journal: Nutrition; 2023 Oct; 114():112135. PubMed ID: 37453224.
Abstract:
OBJECTIVE: Non-communicable diseases (NCDs) are linked to excessive adiposity and anthropometric indices can be used to identify those at risk. The aim of this study was to evaluate the precision of anthropometric indices in identifying obesity and risk factors for NCDs and to investigate the emergence of obesity-related NCDs in young women in Sri Lanka. METHODS: We recruited 282 women 18 to 35 y of age from suburban and rural areas in Sri Lanka. We measured the women's height, weight, body mass index (BMI), waist circumference (WC), waist-to-hip ratio (WHR), waist-to-height ratio (WHtR), A Body Shape Index(ABSI), hip circumference (HC), hip index (HI), anthropometric risk index (ARI), fasting serum glucose, fasting serum insulin, homeostatic model assessment for insulin resistance, cholesterol, high-density lipoprotein, low-density lipoprotein, triacylglycerols, and ovulatory gonadal hormones (progesterone, testosterone). Comparisons were made between women with normal BMI and those who were overweight or obese using anthropometric and biochemical characteristics. RESULTS: The prevalence of obesity was highest in WC and in receiver operating characteristic analysis, BMI, WC, and WHtR showed higher sensitivity and lower 1-specificity as indicators of obesity. BMI had an area under the curve (AUC) of 1.000 with 100% sensitivity and 0% 1-specificity. WC had an AUC of 0.941 with 80% sensitivity and 13.4% 1-specificity. Additionally, WHtR showed a 0.974 AUC, 92.1% sensitivity, and 4.9% 1-specificity. The correlations between body size and shapes were assessed among the study participants using Pearson's correlation. More than other measures, WC and WHtR showed a significant correlation with BMI with P < 0.05 (r = 0.888 and 0.737, respectively). Although ABSI and BMI showed only a weak correlation (P = 0.006, r = 0.162), WHR and BMI showed a moderate correlation (P = 0.001, r = 0.477). Although HI demonstrated a negative association with BMI (P = 0.618, r = -0.030), HC exhibited a strong association (P = 0.001, r = 0.749). A significant association with higher odds ratios was found for obesity-related NCD risk factors such as hypertension, homeostatic model assessment for insulin resistance, hypercholesterolemia, altered ovulatory hormones with these (BMI, WC, WHR, WHtR, ABSI, HI) obesity-assessing criteria (P < 0.05). A significant correlation between WC and hypertriacylglycerolmia (P = 0.001, r = 0.781, odds ratio, >16) was identified. A positive correlation was observed between all MS components and ARI, indicating that ARI may serve as a potential indicator of cardiometabolic risk. CONCLUSION: BMI, WC, WHtR, and HC are intercorrelated anthropometric measurements that can be used either alone or in combination to define obesity and detect the risk for NCDs, including diabetes mellitus, cardiovascular disease, and infertility. On the other hand, BMI, ABSI, and HI are designed to be mutually independent indices and have the advantage of combining the separate risks to generate an overall ARI. Furthermore, ARI appears to be a highly effective predictor of cardiovascular disease.

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