Obesity-depression-metabolism triad: amplification of cardiometabolic multimorbidity risk in Chinese adults (CHARLS 2011–2018)

Previous studies have shown that obesity and metabolic and psychological factors are related to cardiometabolic comorbidities, and this study focuses on the BRI, TyG index and depression and explores the independent and combined effects of these three factors on cardiometabolic comorbidities from multiple perspectives. We analyzed data from 5,199 participants (baseline 2011) in the China Health and Retirement Longitudinal Study (CHARLS). The participants were stratified into four groups on the basis of the median TyG index (8.62) and BRI (4.03). Logistic regression models were used to assess associations between TyG-BRI strata, depression (CES-D score ≥ 10), and incident CMM (cardiometabolic multimorbidity), incorporating multiplicative interaction terms (BRI×TyG×Depression) and additive interaction indices (RERI/AP). A composite score was developed using standardized biomarker z scores and depression status, with predicti·ve performance evaluated via ROC-AUC comparisons (DeLong’s test) and restricted cubic splines. During the 7-year follow-up period, 331 incident CMM cases were documented. Machine learning models (random forest and XGBoost) identified BRI and TyG as the top predictors of CMM. Logistic regression revealed the highest risk in the high-BRI & high-TyG group (OR = 3.89, 95% CI = 3.02–5.01 vs. low-BRI and low-TyG). Tripartite exposure (high BRI and high TyG and depression) was associated with a striking 14-fold increased risk (OR = 14.2, 95% CI = 7.95–27.6), with a significant multiplicative interaction (p = 0.016). The composite cardiometabolic‒psychosocial score showed superior predictive capacity (AUC = 0.70 vs. BRI = 0.66, TyG = 0.65, depression = 0.56; DeLong’s p < 0.001) and dose‒responsive risk escalation (P-overall < 0.001, P for nonlinearity = 0.70). This study identifies BRI, TyG, and depression as independent and synergistic predictors of CMM. Our findings advocate integrated clinical strategies for effective CMM prevention.

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Publication Details

Journal
Lipids in Health and Disease
Published
2025-09-29
DOI
https://doi.org/10.1186/s12944-025-02724-1
Citations
3
Primary Topic
Cardiac Health and Mental Health
Type
article
Field-Weighted Citation Impact
4.16

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article

Obesity-depression-metabolism triad: amplification of cardiometabolic multimorbidity risk in Chinese adults (CHARLS 2011–2018)

Lin Dong, Fuzhou Hua, Xifeng Wang, Feng Lu et al.
3 citations
Lipids in Health and Disease
Cardiac Health and Mental Health
4.16
article

Obesity-depression-metabolism triad: amplification of cardiometabolic multimorbidity risk in Chinese adults (CHARLS 2011–2018)

Lin Dong, Fuzhou Hua, Xifeng Wang, Feng Lu, Qinglin He, Wei Lin, Yu Wen, Shan Huang, Min Zhong, Shao‐Ying Hua, Chubing Long
article en
3 citations

Abstract

Previous studies have shown that obesity and metabolic and psychological factors are related to cardiometabolic comorbidities, and this study focuses on the BRI, TyG index and depression and explores the independent and combined effects of these three factors on cardiometabolic comorbidities from multiple perspectives. We analyzed data from 5,199 participants (baseline 2011) in the China Health and Retirement Longitudinal Study (CHARLS). The participants were stratified into four groups on the basis of the median TyG index (8.62) and BRI (4.03). Logistic regression models were used to assess associations between TyG-BRI strata, depression (CES-D score ≥ 10), and incident CMM (cardiometabolic multimorbidity), incorporating multiplicative interaction terms (BRI×TyG×Depression) and additive interaction indices (RERI/AP). A composite score was developed using standardized biomarker z scores and depression status, with predicti·ve performance evaluated via ROC-AUC comparisons (DeLong’s test) and restricted cubic splines. During the 7-year follow-up period, 331 incident CMM cases were documented. Machine learning models (random forest and XGBoost) identified BRI and TyG as the top predictors of CMM. Logistic regression revealed the highest risk in the high-BRI & high-TyG group (OR = 3.89, 95% CI = 3.02–5.01 vs. low-BRI and low-TyG). Tripartite exposure (high BRI and high TyG and depression) was associated with a striking 14-fold increased risk (OR = 14.2, 95% CI = 7.95–27.6), with a significant multiplicative interaction (p = 0.016). The composite cardiometabolic‒psychosocial score showed superior predictive capacity (AUC = 0.70 vs. BRI = 0.66, TyG = 0.65, depression = 0.56; DeLong’s p < 0.001) and dose‒responsive risk escalation (P-overall < 0.001, P for nonlinearity = 0.70). This study identifies BRI, TyG, and depression as independent and synergistic predictors of CMM. Our findings advocate integrated clinical strategies for effective CMM prevention.

Lipids in Health and DiseaseVol. 24(1)
Nanchang University (CN), First Affiliated Hospital of Jiangxi Medical College (CN), Second Affiliated Hospital of Nanchang University (CN), First Affiliated Hospital of Gannan Medical University (CN), Education Department of Jiangxi Province (CN), First Affiliated Hospital of Nanchang University (CN)
National Natural Science Foundation of China, Natural Science Foundation of Jiangxi Province, Peking University
Openalex Percentile: Top 5%
Cardiac Health and Mental Health
4.16
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