Author
Listed:
- Ya-Mei Chen
- Yu-Kang Tu
- Hsiao-Wei Yu
- Tzu-Ying Chiu
- Tung-Liang Chiang
- Duan-Rung Chen
- Ray-E Chang
Abstract
Objectives: The aims of this study were to investigate (1) whether and (2) the extent to which Taiwanese older adults’ leisure time activity (LTA) trajectories mediated the potential association between their sociodemographic factors and their functional disability trajectories. Methods: Longitudinal data from four waves of the Taiwan Longitudinal Study on Aging (TLSA), collected between 1996 and 2007, were used for analysis (N = 3,429). Parallel-process latent growth curve modeling was adopted to evaluate the process by which LTA mediated between sociodemographic factors (age, gender, education, self-rated health, comorbidities, and depression) and the outcome process of functional disabilities. Results: When mediated by baseline level of LTA, five sociodemographic factors—age, gender, education level, self-rated health, and number of comorbidities—had significant and negative mediating effects on baseline or change in functional disability, thus improving disability outcomes. However, four of the sociodemographic factors (age, education level, and number of comorbidities), when mediated through the rate of change in LTA, were found to have significant and positive mediating effects, which increased disability levels. The proportion of effects mediated by the LTA trajectory ranged from 0% to 194%. Discussion: The large proportion of effects mediated through the LTA process underlines the importance of LTA to public health policy and health programs for older adults. The study’s findings shed light on how to better target populations of older adults to promote an active lifestyle and achieve more successful aging in late life in Asian countries.
Suggested Citation
Ya-Mei Chen & Yu-Kang Tu & Hsiao-Wei Yu & Tzu-Ying Chiu & Tung-Liang Chiang & Duan-Rung Chen & Ray-E Chang, 2018.
"Leisure time activities as mediating variables in functional disability progression: An application of parallel latent growth curve modeling,"
PLOS ONE, Public Library of Science, vol. 13(10), pages 1-15, October.
Handle:
RePEc:plo:pone00:0203757
DOI: 10.1371/journal.pone.0203757
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