The Impact of Perceived Community Services for the Elderly on Self-Rated Health: An Analysis Utilizing a Mediated Latent Growth Model
Abstract
BACKGROUND: This study aims to investigate the relationship between older adults' perceived community services for the elderly (PCSE), life satisfaction (LS), and self-rated health (SRH). METHODS: Data from four rounds of the Chinese Longitudinal Healthy Longevity Survey (CLHLS) from 2008 to 2018 were used. A total of 2454 older adults were obtained. Unconditional Least Squares (ULS) was used to measure PCSE, LS, and SRH growth trajectories without covariates. Finally, a mediating latent growth model was constructed using Mplus 8.3 to examine the mediating role of LS in the relationship between PCSE and SRH after adjusting for some demographic characteristics. RESULTS: The results from the ULS method indicate that the intercepts and slopes for PCSE and LS are significantly negatively correlated (β ₁ = -0.629, β ₂ = -0.579, p < 0.001). Additionally, there is a significant positive correlation between the intercept and slope of health levels (β = 0.774, p < 0.001). Using a parallel growth model, significant regression coefficients were found between the intercept of PCSE and the intercepts of SRH and LS (β ₁ = -0.335, β ₂ = 0.378, p < 0.01). Similarly, the regression coefficients between the slope of PCSE and the slopes of SRH and LS were also significant (β ₁ = -0.532, β ₂ = 0.344, p < 0.01). Furthermore, the regression coefficient between the intercept of LS and the intercept of SRH was significant (β = 0.415, p < 0.001). The regression coefficient between the slope of LS and the slope of SRH was also found to be significant (β = 0.729, p < 0.001). CONCLUSION: It is essential to ensure adequate supply and accessibility of community services for older adults. LS especially is, and should be a promising target for assessing the quality of life and utilization of PCSE supply.
The paper
Xiamen University; Shandong Technology and Business University
Journal of Multidisciplinary Healthcare, 7 Sep 2024, Open access

