The impact mechanism of physical activity levels on active aging among middle-aged and older adults: an age-period-cohort analysis from 2011 to 2018

With the adoption of active aging as a national strategy in China, physical activity has emerged as a vital factor in fostering active aging due to its practicality, feasibility, and accessibility. Serving as a key means for older adults to maintain meaningful engagement in later life, physical activity significantly enhances their well-being. However, most existing studies emphasize discursive analysis and experimental interventions, lacking comprehensive empirical research on how the type, intensity, and frequency of physical activity relate to active aging. Notably, the impact of dynamic factors such as age, period, and cohort effects has been largely neglected. Therefore, this study aims to systematically examine these factors to refine physical activity intervention strategies and establish a scientific foundation for advancing active aging. Based on data from the 2011–2018 China Health and Retirement Longitudinal Study, this study explores the evolving impact of physical activity levels on active aging among middle-aged and older adults (aged 45–90 years). Employing hierarchical age-period-cohort cross-classified random effects models, the analysis investigates how this relationship varies across age, observation period, and birth cohort. From a static standpoint, a significant correlation was observed between physical activity and active aging levels in middle-aged and older adults, with moderate physical activity showing the strongest effect (coef.= 0.013). From a dynamic perspective, the impact of physical activity on active aging was significant across age, period, and cohort (P < 0.001). In terms of age, there was a nonlinear relationship with active aging, where the decline was slower until the age of 55, after which it accelerated. However, a higher level of physical activity can play a role in slowing the decline of active aging. Regarding the period, the level of active aging fluctuated and increased between 2011 and 2018. The influence of low-intensity physical activity on active aging was more pronounced before 2015, while the impact of moderate and high-intensity physical activity grew after 2016. In terms of cohort, the active aging trajectory for middle-aged and older adults followed a “rise-decline-rise” pattern, with the effects of varying intensities of physical activity on active aging showing alternating trends. Varying intensities of physical activity impact the process of active aging. Additionally, age, period, and cohort differences should also be taken into account to inform the development of targeted intervention strategies.

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Publication Details

Journal
BMC Public Health
Published
2025-08-16
DOI
https://doi.org/10.1186/s12889-025-23829-3
Citations
2
Primary Topic
Physical Activity and Health
Type
article
Field-Weighted Citation Impact
2.33

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article

The impact mechanism of physical activity levels on active aging among middle-aged and older adults: an age-period-cohort analysis from 2011 to 2018

L Chen, G Y Wang, Jing Guo, Xiaoli Zhang
2 citations
BMC Public Health
Physical Activity and Health
2.33
article

The impact mechanism of physical activity levels on active aging among middle-aged and older adults: an age-period-cohort analysis from 2011 to 2018

L Chen, G Y Wang, Jing Guo, Xiaoli Zhang
article en
2 citations

Abstract

With the adoption of active aging as a national strategy in China, physical activity has emerged as a vital factor in fostering active aging due to its practicality, feasibility, and accessibility. Serving as a key means for older adults to maintain meaningful engagement in later life, physical activity significantly enhances their well-being. However, most existing studies emphasize discursive analysis and experimental interventions, lacking comprehensive empirical research on how the type, intensity, and frequency of physical activity relate to active aging. Notably, the impact of dynamic factors such as age, period, and cohort effects has been largely neglected. Therefore, this study aims to systematically examine these factors to refine physical activity intervention strategies and establish a scientific foundation for advancing active aging. Based on data from the 2011–2018 China Health and Retirement Longitudinal Study, this study explores the evolving impact of physical activity levels on active aging among middle-aged and older adults (aged 45–90 years). Employing hierarchical age-period-cohort cross-classified random effects models, the analysis investigates how this relationship varies across age, observation period, and birth cohort. From a static standpoint, a significant correlation was observed between physical activity and active aging levels in middle-aged and older adults, with moderate physical activity showing the strongest effect (coef.= 0.013). From a dynamic perspective, the impact of physical activity on active aging was significant across age, period, and cohort (P < 0.001). In terms of age, there was a nonlinear relationship with active aging, where the decline was slower until the age of 55, after which it accelerated. However, a higher level of physical activity can play a role in slowing the decline of active aging. Regarding the period, the level of active aging fluctuated and increased between 2011 and 2018. The influence of low-intensity physical activity on active aging was more pronounced before 2015, while the impact of moderate and high-intensity physical activity grew after 2016. In terms of cohort, the active aging trajectory for middle-aged and older adults followed a “rise-decline-rise” pattern, with the effects of varying intensities of physical activity on active aging showing alternating trends. Varying intensities of physical activity impact the process of active aging. Additionally, age, period, and cohort differences should also be taken into account to inform the development of targeted intervention strategies.

BMC Public HealthVol. 25(1)
Fujian Normal University (CN), Shanghai University of Sport (CN), Xi'an Physical Education University (CN)
China Postdoctoral Science Foundation, Wuhan University, Peking University
Openalex Percentile: Top 11%
Physical Activity and Health
2.33
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