Dataset Information

Urban-rural disparities in the healthy ageing trajectory in China: a population-based study.

ABSTRACT:

Purpose

The aim of this study is to measure the trajectory of healthy ageing among Chinese middle-aged and older population, and explore the disparity of the trajectory, as well as contributing factors, between urban and rural areas in China.

Methods

A total of 9402 respondents aged 45 years and older interviewed in four waves (2011, 2013, 2015 and 2018) were selected from the China Health and Retirement Longitudinal Study. Healthy ageing score was calculated through item response theory. A latent growth mixture model (LGMM) was applied to distinguish the trajectory of healthy aging. A multinomial logistics regression model (MLRM) was used to explore the relationship between urban-rural areas and healthy aging trajectories, and further to explore associated factors in rural and urban areas separately.

Results

The healthy ageing score was lower in rural areas than urban areas in each survey wave. Five classes ("continuing-low", "continuing-middle", "continuing-middle-to-high", "significantly-declining", "continuing-high") were grouped through LGMM. The MLRM results showed that urban living was significantly associated with a higher likelihood of being healthy (for [continuing-low/continuing-high]: β = - 1.17, RRR = 0.31, P < 0.001, 95% CI = 0.18-0.53; and for [continuing-middle/continuing-high]: β = - 0.53, RRR = 0.59, P < 0.001, 95% CI = 0.49-0.71).

Conclusion

Healthy ageing is a prominent objective in the development of a country, and rural-urban disparities are an essential obstacle to overcome, with the rural population more likely to develop a low level of healthy ageing trajectory. Prevention and standardized management of chronic diseases should be enhanced, and social participation should be encouraged to promote healthy ageing. The policy inclination and resource investment should be enhanced to reduce disparity in healthy ageing between urban and rural areas in China.

SUBMITTER: Li H

PROVIDER: S-EPMC9308310 | biostudies-literature |

REPOSITORIES: biostudies-literature

ACCESS DATA

Similar Datasets

Project description:Atmospheric particulate matter (PM) is a recognized risk factor for the global burden of disease in human populations. We are presenting here the application of toxicogenomics in the evaluation of the toxic effects of organic content of atmospheric particle matter (PM), from urban and rural environments (city of Barcelona and village of La Pobla, NE Spain), using the developing zebrafish embryo. The main goal is to identify the metabolic pathways involved in the adverse effects observed in zebrafish embryos exposed to PM organic content from urban and rural environments, also allowing the selection of genes of interest that are differentially expressed. The relevance of particle size to the PM toxicity is also addressed. Indeed, the zebrafish embryos were exposed to PM of aerodynamic diameter larger than 7.2 μm and smaller than 0.5 μm (PM10 and PM0.5, respectively). PM0.5 concentrated biological and toxic activities linked to organic substances. Transcriptomic analyses showed strong induction of the AhR signalling pathway (a.k.a. dioxin-like activity) for embryos exposed to both rural and urban extracts, correlating with the concentrations of PAHs. Urban extracts, with strong contribution of traffic emissions, specifically de-regulated oxidative stress-related genes, as well as pancreatic and eye-lens specific genes, two organs known to be affected by air pollution in humans. Exposure to rural extracts, with high contribution of wood burning emissions, affected genes implicated in basic cellular functions, in agreement with their strong embryotoxicity. Extracts from rural and urban samples elicited both common and specific transcriptome responses, suggesting different potentially adverse outcomes depending on PM source and composition. The authors thank the financial support of the Spanish Ministry (project TEA-PARTICLE, grant number CGL2011-29621) and the Portuguese Foundation for Science and Technology for the doctoral grant of Sofia R. Mesquita (SFRH/BD/80710/2011) funded by the Program POPH-QREN through the Portuguese Ministry of Education and Science and the European Social Fund, and support through project PEst-C/MAR/LA0015/2013.