Anthropometric indices in predicting 10-year cardiovascular risk among males and females aged 40-74 years in south and southeast Asia: analysis of 12 WHO STEPS survey data

Abstract

Background: The relevance of anthropometric indices in predicting cardiovascular disease (CVD) or CVD risk factors is established across different countries, particularly in the high-income countries. However, past studies severely lacked representation from the south and southeast Asian countries. The main aim of this study was to determine the performance of conventional and new anthropometric indices to best predict 10-year cardiovascular disease (CVD) risk in south Asian and southeast Asian populations.

Methods: The present study examined data from 14,532 participants in three south Asian and 13,846 participants (all aged between 40 and 74 years) in six southeast Asian countries, drawn from twelve cross-sectional studies (WHO STEPwise approaches to NCD risk factor surveillance [STEPS] survey data from 2008 to 2019). A Predictive performance of ten anthropometric indices were examined for predicting 10-year CVD risk ≥ 10% (CVD-R ≥ 10%). The 10-year CVD-R ≥ 10% was calculated by utilising the WHO CVD risk non-laboratory-based charts. Receiver operating characteristic (ROC) curve analysis was used to identify the optimal anthropometric index.

Findings: Among the ten anthropometric indices, a body shape index (ABSI), body adiposity index (BAI), body roundness index (BRI), hip index (HI), and waist-height ratio (WHtR) performed best in predicting 10-year CVD risk among south Asian males and females. Improved performances were found for ABSI, BRI, conicity index (CI), WHtR, and waist-hip ratio (WHR) for 10-year CVD-R ≥ 10% predictions among southeast Asian males. Contrastingly, among southeast Asian females, ABSI and CI demonstrated optimal performance in predicting 10-year CVD-R ≥ 10%.

Interpretation: The performance of anthropometric indices in predicting CVD risk varies across countries. ABSI, BAI, BRI, HI, and WHtR showed better predictions in south Asians, whereas ABSI, BRI, CI, WHtR, and WHR displayed enhanced predictions in southeast Asians.

Funding: None.

Keywords: Anthropometry indices; Cardiovascular disease risk; Receiver operating characteristic (ROC) curve analysis; south Asia; southeast Asia.

Fig. 1

A schematic diagram of the construction of the analytic sample for WHO non-laboratory based CVD score. (a) South Asia (b) southeast Asia. ASCVD: atherosclerotic cardiovascular disease; CVD: cardiovascular diseases.

Fig. 2

Prevalence of 10-year CVD-R ≥10% by sex and country based on WHO CVD non-laboratory-based charts in south Asia (a) and southeast Asia (b).

Fig. 3

ROC curves representing the predictive accuracy of anthropometric indices for 10-year CVD-R ≥ 10% using WHO-CVD-NL-C. The graphs (a) and (b) represent the outcomes for Bangladeshi males and females, whereas graphs (c), (d), (e), and (f) represent identical outcomes for Nepal and Pakistan, respectively. 10-year CVD-R ≥ 10%; 10-year CVD risk ≥ 10% WHO-CVD-NL-C; WHO CVD risk non-laboratory-based charts. Line pattern '---' indicates best-performing anthropometric index.

Fig. 4

ROC curves representing the predictive accuracy of anthropometric indices for 10-year CVD-R ≥ 10% using WHO-CVD-NL-C. The graphs (a) and (b) represent the outcomes for Cambodian males and females, whereas the (c), (d), (e), and (f) represent identical outcomes for Laos and Myanmar, respectively. 10-year CVD-R ≥ 10%; 10-year CVD risk ≥10% WHO-CVD-NL-C; WHO CVD risk non-laboratory-based charts. Line pattern '---' indicates best-performing anthropometric index.

Fig. 5

ROC curves representing predictive accuracy of anthropometric indices for 10-year CVD-R ≥ 10% using WHO-CVD-NL-C. The graphs (a) and (b) represent the outcomes for Timorese males and females, and (c), (d), (e), and (f) represent identical outcomes for Vietnam and Maldives, respectively. 10-year CVD-R ≥ 10%; 10-year CVD risk ≥10% WHO-CVD-NL-C; WHO CVD risk non-laboratory-based charts. Line pattern '---' indicates best-performing anthropometric index.