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Factors Associated With Falls Among the Elderly With Type 2 Diabetes in Urban Shanghai: A Cross‐Sectional Study

Jan 2026 · Journal of Diabetes Research · Vol 2026 · 0 citations · 59 references
Medicine

TL;DR

Falls were common among elderly diabetic residents in urban Shanghai, and multiple factors were identified as potential correlates, supporting the use of multidomain screening to identify high‐risk individuals for falls and to inform targeted assessment approaches.

Abstract

Aim This study is aimed at identifying the factors associated with falls among community‐dwelling elderly individuals with Type 2 diabetes mellitus (T2DM) in urban Shanghai, China. Methods The study analyzed data from 842 diabetic patients aged 60 years or older. Information about associated factors and main outcome measures was collected using structured questionnaires. Chi‐square tests and binary logistic regression were used to identify factors associated with falls. Results Among the participants, 239 (28.4%) experienced at least one fall and 41 (17.2%) of these fallers had recurrent falls in the past 1 year. Univariate analysis identified a range of potential factors for falls, including physical impairments (e.g., dizziness, fatigue, unsteadiness), psychological factors (e.g., depression, activity restriction due to fear of falling), and adverse lifestyle factors (e.g., inactivity, poor sleep, frequent nocturia) (p < 0.05). Logistic regression analysis revealed that balance test score (OR = 1.687, 95% CI: 1.162–2.447, p = 0.006), PHQ‐9 depression category (OR = 1.663, 95% CI: 1.028–2.691, p = 0.038) and activity restriction due to fear of falling (OR = 2.503, 95% CI: 1.752–3.575, p < 0.001) were independently associated with falls. For recurrent falls, activity restriction due to fear of falling remained significantly associated across models (OR range: 2.045–2.165, p < 0.05). Conclusion Falls were common among elderly diabetic residents in urban Shanghai, and multiple factors were identified as potential correlates. Our findings support the use of multidomain screening to identify high‐risk individuals for falls and to inform targeted assessment approaches, warranting further prospective investigations.

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