What does this research mean for the field?

BMI and waist circumference (WC) predict cardiometabolic multimorbidity (CMM) risk more effectively than novel anthropometric indices in middle-aged and older Chinese adults. Novelty: ClaimNovelty.CONFIRMATORY. Consensus alignment: ConsensusAlignment.SUPPORTS_CONSENSUS.

What question did this study set out to answer?

This study aims to compare the predictive performance of various anthropometric indices for cardiometabolic multimorbidity in middle-aged and older adults.

January 10, 2026Open Access

Comparative predictive values of anthropometric indices for cardiometabolic multimorbidity in middle-aged and older adults: a prospective study from the CHARLS study

Key Result

BMI and WC predict cardiometabolic multimorbidity risk more effectively than novel indices, with BMI showing an AUC of 0.720 in middle-aged and older adults.

Key Points

This study aims to compare the predictive performance of various anthropometric indices for cardiometabolic multimorbidity in middle-aged and older adults.
Conducted a prospective study using CHARLS data from 2011 to 2018.
Utilized propensity score matching to control for age and gender biases.
Applied multivariable logistic regression to examine associations of indices with cardiometabolic multimorbidity.
Employed receiver operating characteristic curves to evaluate predictive performance.
554 participants developed cardiometabolic multimorbidity, indicating a 7.42% prevalence.
Increased risks of cardiometabolic multimorbidity were observed across higher quartiles for BMI, WHtR, BRI, CI, and WC.
BMI demonstrated the highest predictive performance with an area under the curve (AUC) of 0.720, followed closely by WC at 0.712.
U-shaped associations were found for WHtR, BRI, WWI, CI, and WC with cardiometabolic multimorbidity risk, while BMI showed a linear relationship.

Structured PICO

Do anthropometric indices predict the risk of cardiometabolic multimorbidity in middle-aged and older Chinese adults?

Population

7,469 middle-aged and older Chinese adults (aged ≥45 years) from the China Health and Retirement Longitudinal Study (CHARLS) 2011-2018 without cardiometabolic multimorbidity at baseline.

Intervention

Anthropometric indices including body mass index (BMI), waist-to-height ratio (WHtR), body roundness index (BRI), weight-adjusted waist index (WWI), a body shape index (ABSI), conicity index (CI), and waist circumference (WC).

Outcome

Cardiometabolic multimorbidity (CMM), defined as the coexistence of at least two of the following: diabetes mellitus, heart disease, and stroke.composite

Traditional anthropometric indices, specifically BMI and waist circumference, are superior to novel indices for predicting the risk of cardiometabolic multimorbidity in middle-aged and older Chinese adults.

Main Result

Absolute Event Rate: 0% vs 0%

Abstract

Abstract Objectives This study aimed to compare the predictive performance of seven anthropometric indices—body mass index (BMI), waist-to-height ratio (WHtR), body roundness index (BRI), weight-adjusted waist index (WWI), a body shape index (ABSI), conicity index (CI) and waist circumference (WC)—for cardiometabolic multimorbidity (CMM) in middle-aged and older Chinese adults. Methods This study conducted a prospective study using data from the China Health and Retirement Longitudinal Study (CHARLS) 2011–2018. Propensity score matching (PSM) was utilized to control for biases induced by age and gender, with these two factors as the core matching variables and sample matching conducted at a 1:1 ratio. Multivariable logistic regression models were used to examine associations between anthropometric indices and CMM. Restricted cubic splines explored dose-response relationships between anthropometric indices and CMM. Receiver operating characteristic (ROC) curves evaluated discriminative performance of anthropometric indices in predicting CMM and specific types of CMM. Results Before PSM, a total of 7,469 participants were included, 554 participants (7.42%) developed CMM. In Model II, BMI, WHtR, BRI, CI and WC maintained significant associations across higher quartiles. Compared with the BMI Q 1 group, the risk of CMM in Q 2 group increased by 1.55 times (OR = 2.55, 95%CI = 1.65, 3.93, P < 0.001); the risk in Q 3 group increased by 2.04 times (OR = 3.04, 95%CI = 1.93, 4.81, P < 0.001); and the risk in Q 4 group increased by 4.89 times (OR = 5.89, 95%CI = 3.62, 9.57, P < 0.001). Compared with the WHR Q 1 group, the risk of CMM in Q 2 group increased by 1.26 times (OR = 2.26, 95%CI = 1.49, 3.42, P < 0.001); the risk in Q 3 group increased by 1.54 times (OR = 2.54, 95%CI = 1.65, 3.91, P < 0.001); and the risk in Q 4 group increased by 3.54 times (OR = 4.54, 95%CI = 2.87, 7.16, P < 0.001). Similar results were found in BRI. Compared with the CI Q 1 group, the risk in Q 3 group increased by 0.59 times (OR = 1.59, 95%CI = 1.04, 2.44, P = 0.032); and the risk in Q 4 group increased by 0.73 times (OR = 1.73, 95%CI = 1.11, 2.70, P = 0.015). Compared with the WC Q 1 group, the risk of CMM in Q 2 group increased by 0.82 times (OR = 1.82, 95%CI = 1.19, 2.80, P = 0.006); the risk in Q 3 group increased by 1.36 times (OR = 2.36, 95%CI = 1.51, 3.68, P < 0.001); and the risk in Q 4 group increased by 4.63 times (OR = 5.63, 95%CI = 3.46, 9.15, P < 0.001). WHtR, BRI, WWI, CI and WC all showed a U-shaped association with CMM risk. BMI demonstrated a linear relationship with CMM risk. BMI achieved the highest performance with identical AUC values of 0.720 (0.690–0.749), followed by WC with an AUC of 0.712 (0.682–0.742). BMI and WC exhibited superior predictive performance whether in predicting those specific types of CMM. Conclusion BMI and WC were superior to novel anthropometric indices for CMM risk prediction in middle-aged and older Chinese adults. The finding supports their value in identifying high-risk CMM individuals and reinforces their role as practical tools.

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