Association between Greenness Structures and Frailty in an Elderly Prospective Longitudinal Cohort in China



Background: Frailty is the accumulation of aging-induced deficits, leading to vulnerability and death. There is evidence of negative associations between greenspaces measured with normalized difference vegetation index (NDVI) and frailty. However, NDVI is not as informative as greenness structure indices which reflect characters such as shape and connectivity. We aim to study the association between greenness structures and frailty in an elderly Chinese cohort.

Methods: We included older adults from 2008-2014 waves of the China Longitudinal Healthy Longevity Survey (CLHLS). We used greenspace indices from satellite to quantify greenspace structures at county-level: area-edge, shape, and proximity, and calculated frailty index (FI) as a health outcome. We did cross-sectional analyses using linear regression and logistical regression, and longitudinal analyses using the generalized estimating equations (GEE). All models were adjusted for covariates.

Results: Among 8,776 participants at baseline, the mean LPI, SHAPE, COHESION, and FI were 7.93, 8.11, 97.6, and 0.17. The correlation between NDVI and greenness structure was unnoticeable. In cross-sectional analyses, we found negative consistent dose-response relationships for greenspace structures and frailty, especially in females, city residents, people without a spouse, and with deteriorated frailty. Compared to participants living in the lowest quartile of greenness structure, those in the highest quartile of LPI, SHAPE, and COHESION had 32%, 44%, and 37% lower odds of frailty. However, we did not find a significant association in longitudinal analyses due to higher mortality rate and FI of participants without follow-up surveys.

Conclusions: The larger value of area-edge, shape, and proximity is related to a lower likelihood of frailty. Assessing complex shapes and connecting fragmentary greenspaces are informative to public health through city planning.

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