Investigating Gender Differences in the Link Between Physical Activity and Depression in Middle-aged and Older Chinese Adults via Network Analysis and Simulation Study

BACKGROUND: Depression affects 28.4% of middle-aged and older adults globally, exacerbating functional decline, mortality, and healthcare burdens. Physical activity mitigates depression through neurobiological and psychosocial pathways, although efficacy varies significantly by gender. Current evidence lacks clarity regarding optimal physical activity intensity and interventions. This study aimed to identify the physical activity patterns most strongly associated with depression and to derive potential intervention targets for middle-aged and older Chinese adults. METHODS: The data from 3739 participants in the 2020 China Health and Retirement Longitudinal Study were analyzed. Gaussian graphical models were adopted to recognize core and bridge symptoms within physical activity-depression networks across genders. Subsequently, computer-simulated interventions were conducted to determine the optimal targets for reducing depressive symptoms by gender. RESULTS: = 0.007), with 14 edges being statistically significant. Simulation interventions consistently pinpointed "depressed" and "stuck" as effective targets for intervention across genders. CONCLUSIONS: Moderate physical activity most strongly correlated with depression. For men, interventions might prioritize increasing the regularity per week with moderate physical activity to prevent depression, whereas for women, focusing on the duration per day of such activity could be a promising target.

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Publication Details

Journal
Journal of Integrative Neuroscience
Published
2026-04-21
DOI
https://doi.org/10.31083/jin47468
Primary Topic
Mental Health Research Topics
Type
article
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article

Investigating Gender Differences in the Link Between Physical Activity and Depression in Middle-aged and Older Chinese Adults via Network Analysis and Simulation Study

Qihan Zhang, Zengjie Ye, Yiguo Deng, Ying Xiong et al.
Journal of Integrative Neuroscience
Mental Health Research Topics
article

Investigating Gender Differences in the Link Between Physical Activity and Depression in Middle-aged and Older Chinese Adults via Network Analysis and Simulation Study

Qihan Zhang, Zengjie Ye, Yiguo Deng, Ying Xiong, Miao Yu, Siyu Li, Jiaying Li
article en

Abstract

BACKGROUND: Depression affects 28.4% of middle-aged and older adults globally, exacerbating functional decline, mortality, and healthcare burdens. Physical activity mitigates depression through neurobiological and psychosocial pathways, although efficacy varies significantly by gender. Current evidence lacks clarity regarding optimal physical activity intensity and interventions. This study aimed to identify the physical activity patterns most strongly associated with depression and to derive potential intervention targets for middle-aged and older Chinese adults. METHODS: The data from 3739 participants in the 2020 China Health and Retirement Longitudinal Study were analyzed. Gaussian graphical models were adopted to recognize core and bridge symptoms within physical activity-depression networks across genders. Subsequently, computer-simulated interventions were conducted to determine the optimal targets for reducing depressive symptoms by gender. RESULTS: = 0.007), with 14 edges being statistically significant. Simulation interventions consistently pinpointed "depressed" and "stuck" as effective targets for intervention across genders. CONCLUSIONS: Moderate physical activity most strongly correlated with depression. For men, interventions might prioritize increasing the regularity per week with moderate physical activity to prevent depression, whereas for women, focusing on the duration per day of such activity could be a promising target.

Journal of Integrative NeuroscienceVol. 25(4)
Guangzhou University of Chinese Medicine (CN), Chinese University of Hong Kong (HK), Guangzhou Medical University (CN)
Good health and well-being
Openalex Percentile: Top 9%
Mental Health Research Topics
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