ArticleBMC geriatrics2025
Relationship between social network characteristics and falls among older adults living alone: an analysis using Zero-inflated negative binomial regression.
Article in BMC geriatrics, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.
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Abstract
backgroundFalls among older adults are sudden events that can lead to serious injuries. Particularly for older adults living alone, the lack of social relationships increases the risk of falls. This study aimed to identify the risk factors for falls among older adults living alone, focusing on general, health-related, and social network characteristics.
methodsThis cross-sectional study utilised data from the 2020 National Survey of Older Koreans, including 3,109 community-dwelling older adults aged 65 years and older who lived alone. A Zero-inflated Negative Binomial Regression analysis was conducted to identify the risk factors for the number of falls using a count model, whereas factors associated with the likelihood of experiencing zero falls were analysed using a logit model.
resultsAmong the participants, 268 (8.6%) had experienced falls in the past year. In the logit model, participants without family but with acquaintances, as well as those without both family and acquaintances, had a higher risk of falls than those with both family and acquaintances in their social network. According to the count model, the risk factors for the number of falls included low education level, being underweight (body mass index < 18.5), poor perceived health status, and higher depression symptoms.
conclusionsThis study found that social network characteristics played a role in protecting older adults living alone from experiencing falls, whereas general and health-related characteristics such as low education level, poor health, and depressive symptoms were associated with a greater number of falls. Healthcare providers should consider not only general and health-related factors but also social network characteristics when assessing the fall risk in this population.
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