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The impact of rural-urban community settings on cognitive decline: results from a nationally-representative sample of seniors in China
BACKGROUND: Aging and rural-urban disparities are two major social problems in today’s ever-developing China. Much of the existing literature has supported a negative association between adverse community setting with the cognitive functioning of seniors, but very few studies have empirically invest...
Autores principales: | , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
BioMed Central
2018
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6311043/ https://www.ncbi.nlm.nih.gov/pubmed/30594142 http://dx.doi.org/10.1186/s12877-018-1003-0 |
Sumario: | BACKGROUND: Aging and rural-urban disparities are two major social problems in today’s ever-developing China. Much of the existing literature has supported a negative association between adverse community setting with the cognitive functioning of seniors, but very few studies have empirically investigated the impact of rural-urban community settings on cognitive decline in the late life course of the population in developing countries. METHODS: Data of seniors aged 65 or above (n = 1709) within CHARLS (The China Health and Retirement Longitudinal Study, a sister study of HRS), a nationally representative longitudinal cohort (2011–2015) in China, were analyzed using a multilevel modeling (MLM) of time within individuals, and individual within communities. Cognitive impairment was assessed with an adapted Chinese version of Mini-Mental State Examination. RESULTS: Urban community setting showed a significant protective effect (β = − 1.978, p < .000) on cognitive impairment in simple linear regression, and the MLM results showed it also had a significant lower cognitive impairment baseline (β = − 2.278, p < .000). However, the curvature rate of cognitive decline was faster in urban community setting indicated by a positive interaction between the quadratic time term and urban community setting on cognitive impairment (β = 0.320, p < .05). A full model adjusting other individual SES factors was built after model fitness comparison, and the education factor accounted for most of the within and between community setting variance. CONCLUSIONS: The findings suggest that urban community setting in one’s late-life course has a better initial cognitive status but a potentially faster decline rate in China, and this particular pattern of senior cognitive decline emphasize the importance of more specific preventive measures. Meanwhile, a more holistic perspective should be adopted while construct a risk factor model of community environment on cognitive function, and the influence at society level needs to be further explored in future research. |
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