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Abstract
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INTRODUCTION: Previous studies have suggested that cognitive impairment is associated with falls in older adults. However, the consistency of results among different subgroups defined by multiple characteristics of the elderly has not yet been tested. Additionally, results are inconsistent regarding the effects of different cognitive domains on falls. Therefore, this study sought to use representative data from a nationwide study to better understand the longitudinal association between cognitive impairment and subsequent falls in older adults.
METHODS: The current study was conducted based on the China Health and Retirement Longitudinal Study (CHARLS) data of respondents aged ≥60 years in 2015 and the fall data in 2018. The respondents were divided into subgroups according to different demographic characteristics. Multiple logistic regression analysis was conducted to adjust for various confounding factors and evaluate the association between cognitive impairment and falls.
RESULTS: Of the 5,110 respondents included in this study, 1,093 (21.39%) had falls within the last 2 years. A significant association was found between cognitive impairment and subsequent falls (OR = 0.97, 95% CI 0.95-0.99, P = 0.001) after adjusting for all of the covariates related to falls. Analysis of different cognitive domains showed that orientation (OR = 0.94, 95% CI 0.90-0.99, P = 0.013) and memory (OR = 0.93, 95% CI 0.90-0.97, P = 0.001) were significantly associated with falls. In subgroup analysis, the ORs of people aged 60-74 years, male, with lower education level were 0.97 (95% CI 0.95-0.99, P = 0.008), 0.96 (95% CI 0.93-0.98, P = 0.001), and 0.97 (95% CI 0.95-0.99, P = 0.001), respectively, suggesting that the associations were also statistically significant in these subgroups. There was also a significant association both in urban (OR = 0.97, 95% CI 0.95-0.99, P = 0.001) and in rural residents (OR = 0.97, 95% CI 0.95-0.99, P = 0.003).
CONCLUSIONS: Our results suggest that the associations between cognition and falls vary depending on the different demographic characteristics of older adults. These findings may be useful for designing more accurate identification and intervention for the fall risk for specific high-risk groups.
Language: en |