five

The data.

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NIAID Data Ecosystem2026-05-10 收录
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https://figshare.com/articles/dataset/The_data_/30623246
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Background With the global population ageing rapidly, especially in China, promoting active ageing is crucial for ensuring healthy longevity. However, limited studies have examined the levels and predictors of active ageing at the community level in provincially designated age-friendly communities. Methods A cross-sectional study was conducted from August to November 2024 in two age-friendly communities in Yanji City, China. We invited 553 older adults aged 60 years and above using simple random sampling methods. We collected data through structured face-to-face interviews using validated instruments that measured socio-demographic and physical, environmental, health-related, and social variables. We used multiple linear regression to identify significant predictors of active ageing. Results A total of 513 older adults participated 56.9% were female, and 90.4% were aged 60−79. The mean active ageing score was 100.98 (SD = 16.78). Higher educational attainment (β = 0.138, 95% CI [0.513, 8.736]), higher income levels (β = 0.144, 95% CI [1.265, 10.266]), moderate physical activity levels (β = 0.073, 95% CI [0.004, 0.181]), better cognitive function (β = 0.214, 95% CI [0.522, 1.088]), stronger family support (β = 0.124, 95% CI [0.399, 1.535)], close social connectedness (β = 0.277, 95% CI [0.595, 1.021]), and use of community (β = 0.176, 95% CI [3.597, 9.532]) and cultural facilities (β = 0.116, 95% CI [1.659, 6.583]) three or more times a week were significantly associated with higher active ageing. Depression had a significant negative impact on active ageing scores (β = −0.170, 95% CI [−1.362, −0.570]). Conclusion The findings underscore the need for integrated strategies encompassing environmental design, social support systems, physical activity promotion, and mental health care to foster active and meaningful ageing in age-friendly community settings.
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2025-11-14
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