Abstract P268: Predictive Abilities of Anthropometric Indicators for Cardiometabolic Risk Factors and Diseases: The UK Whitehall II Study

Introduction: Obesity is an accepted risk factor for cardiometabolic diseases. Body mass index (BMI) is the most commonly-used anthropometric measurement for accessing healthy weight. However, some studies suggested that other adiposity indices may be better predictors of cardiometabolic risks and diseases. Our study aimed to compare the predictive abilities of 5 indices [BMI, waist circumference (WC), waist-to-height ratio (WHtR), waist-by-height0.5 (WHT.5R), and a body shape index (ABSI)]. Hypothesis: BMI is not good enough for accessing and predicting healthy condition. WHtR may be a more effective index for predicting cardiometabolic risk factors and diseases. Methods: Based on the UK Whitehall II study, we included participants with full records of weight, height, and waist circumference in Phase 3 (1991-1994). Our study indices, BMI, WC, WHtR, WHT.5R, and ABSI, were calculated from measured weight, height, or waist circumference. The outcomes were coronary heart disease (CHD), abnormal blood pressure (BP), insulin resistance (IR), hyperglycemia, and hyperlipidaemia. Receiver operator characteristic (ROC) curve analysis and logistic regression analysis were used to assess the predictive values of the study indices to the cardiometabolic risk factors and diseases. Results: A total of 7979 participants were included [mean age: 50.1 ± 6.0 years; 2468 (30.9%) females; 7188 (90.4%) whites]. Cross-sectionally, except for the association between ABSI and CHD, a significantly-positive association was observed between the all indices and all outcomes (all P<0.001) in Phase 3. All 5 indicators showed the highest predictive ability when the outcome was IR [all the areas under the curve (AUC)>0.714], and among them, WHT.5R had highest predictive value (AUC: 0.770, sensitivity: 76.5%, specificity: 65.1%). For other outcomes, WHtR showed the best prediction for hyperlipidaemia (AUC: 0.719, sensitivity: 54.7%, specificity: 79.6%) relative to the other 4 measurements, whereas WC had higher AUC for predicting abnormal BP (AUC: 0.704, sensitivity: 64.6%, specificity: 65.8%) than any other indices. However, among all of the study outcomes, these 5 indices had the relatively weak ability to predict CHD (all AUCs<0.654). Conclusions: Some indices may provide a more accurate insight into cardiometabolic risk factors and diseases than BMI. WHT.5R appears to be an effective predictor of IR. WHtR has a better prediction for hyperlipidaemia. WC seems to be a good indicator for abnormal BP. We should pay more attention to waist circumference and its derived adiposity indices in the practice of preventing cardiometabolic diseases.