A study on the trajectory of depression in Chinese middle-aged and elderly patients with cardiometabolic comorbidities: based on a group trajectory model

Research indicates that cardiovascular metabolic comorbidity (CMM) is an important risk factor for depression in middle-aged and older adults. However, the relationship between depression trajectories and CMM remains unclear. This study analyzed data from the China Health and Retirement Longitudinal Study (CHARLS) to explore the relationship between depression trajectories and CMM in middle-aged and older adults. This study utilized four waves of data (2011, 2013, 2015, and 2018) from the China Health and Retirement Longitudinal Study (CHARLS), including 848 participants aged 45 years and older with CMM, each with depressive symptom assessments at a minimum of three time points. Group-based trajectory modeling (GBTM) was applied to identify distinct depressive symptom trajectories, with model fit evaluated using the Bayesian information criterion (BIC), average posterior probability (AvePP), and odds of correct classification (OCC). Multinomial logistic regression was used to examine associations between sociodemographic characteristics and trajectory membership. Four depression trajectories were identified: Low-stable (45.01%), Relieved (31.48%), Worsen (12.20%), and High-fluctuating (11.32%). Pronounced gradients were observed for sex (p < 0.001), education (p < 0.001), rural residence (p < 0.001), marital status (p = 0.048), contact with children (p = 0.032), smoking (p = 0.031) and sleep duration (p < 0.001). In multivariable analyses, short sleep duration (<7 h) was consistently associated with increased odds of the High-fluctuating trajectory (OR = 3.01, 95% CI 1.81–5.00). Non-participation in social activities was associated with increased odds of the High-fluctuating trajectory (OR = 1.87, 95% CI 1.16–3.01). Among middle-aged and older Chinese adults living with CMM, depressive symptoms follow four distinct long-term patterns: Low-stable, Relieved, Worsen, and High-fluctuating. These findings underscore the importance of integrating sleep pattern, gender-sensitive care and social support into routine management of CMM to mitigate the risk of chronic or relapsing depression in this population.

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Publication Details

Journal
Psychology Health & Medicine
Published
2026-06-26
DOI
https://doi.org/10.1080/13548506.2026.2693805
Primary Topic
Cardiac Health and Mental Health
Type
article
Field-Weighted Citation Impact
0.00
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article

A study on the trajectory of depression in Chinese middle-aged and elderly patients with cardiometabolic comorbidities: based on a group trajectory model

Yajie Chen, Bingjian Yuan, Geng Yadong, Li Yueren et al.
Psychology Health & Medicine
Cardiac Health and Mental Health
article

A study on the trajectory of depression in Chinese middle-aged and elderly patients with cardiometabolic comorbidities: based on a group trajectory model

Yajie Chen, Bingjian Yuan, Geng Yadong, Li Yueren, Guo Shuanglei, Liu Zhijun, Liu Honglin, Zhang Peng
article en

Abstract

Research indicates that cardiovascular metabolic comorbidity (CMM) is an important risk factor for depression in middle-aged and older adults. However, the relationship between depression trajectories and CMM remains unclear. This study analyzed data from the China Health and Retirement Longitudinal Study (CHARLS) to explore the relationship between depression trajectories and CMM in middle-aged and older adults. This study utilized four waves of data (2011, 2013, 2015, and 2018) from the China Health and Retirement Longitudinal Study (CHARLS), including 848 participants aged 45 years and older with CMM, each with depressive symptom assessments at a minimum of three time points. Group-based trajectory modeling (GBTM) was applied to identify distinct depressive symptom trajectories, with model fit evaluated using the Bayesian information criterion (BIC), average posterior probability (AvePP), and odds of correct classification (OCC). Multinomial logistic regression was used to examine associations between sociodemographic characteristics and trajectory membership. Four depression trajectories were identified: Low-stable (45.01%), Relieved (31.48%), Worsen (12.20%), and High-fluctuating (11.32%). Pronounced gradients were observed for sex (p < 0.001), education (p < 0.001), rural residence (p < 0.001), marital status (p = 0.048), contact with children (p = 0.032), smoking (p = 0.031) and sleep duration (p < 0.001). In multivariable analyses, short sleep duration (<7 h) was consistently associated with increased odds of the High-fluctuating trajectory (OR = 3.01, 95% CI 1.81–5.00). Non-participation in social activities was associated with increased odds of the High-fluctuating trajectory (OR = 1.87, 95% CI 1.16–3.01). Among middle-aged and older Chinese adults living with CMM, depressive symptoms follow four distinct long-term patterns: Low-stable, Relieved, Worsen, and High-fluctuating. These findings underscore the importance of integrating sleep pattern, gender-sensitive care and social support into routine management of CMM to mitigate the risk of chronic or relapsing depression in this population.

Psychology Health & Medicine
Henan University of Science and Technology (CN), Henan University (CN)
Good health and well-being
Openalex Percentile: Top 7%
Cardiac Health and Mental Health
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