Current Status and Correlated Factors of Fall Risk Among Chinese Elderly Aged 60-79:A 2024 Nationwide Cross-Sectional Analysis

ObjectiveTo investigate the prevalence and associated factors of fall risk among Chinese older adults, and to examine the roles of urban-rural differences, regional disparities, physical health status, and psychosocial factors in falls among this population, thereby providing evidence for tailored fall prevention strategies.MethodsUsing data from the 2024 National Routine Physical Fitness Surveillance, a multi-stage stratified sampling method was employed to recruit community-dwelling older adults aged 60-79 years across China. High fall-risk individuals were identified using the Chinese version of the self-rated fall risk questionnaire, while demographic, physical health, and psychological indicators were collected via questionnaires and objective measurements. A generalized linear mixed model (GLMM) with province as a random effect was used to analyze fall risk factors.ResultsAmong 7000 eligible participants (male: 44.2%, female: 55.8%), the sample comprised 2124 (60-64 years), 2014 (65-69 years), 1660 (70-74 years), and 1202 (75-79 years) individuals, with 58.4% from rural and 41.6% from urban areas. A total of 733(10.5%) were identified as high fall-risk, with higher prevalence among females (10.9%), urban residents (11.5%), and the oldest age group (75-79 years: 12.4%). GLMM random-intercept logistic regression revealed that advanced age (OR=1.14, 95% CI: 1.02-1.26), urban residence (OR=1.14, 95% CI: 1.03-1.27), living without a partner (OR=1.97, 95% CI: 1.43-2.73), and increased 2-minute step test performance (OR=1.17, 95% CI: 1.06-1.30) were associated with elevated fall risk. Conversely, improved sleep quality (OR=0.75, 95% CI: 0.67-0.82), greater grip strength (OR=0.85, 95% CI: 0.73-0.98), higher life satisfaction (OR=0.69, 95% CI: 0.62-0.76), increased exercise frequency (OR=0.92, 95% CI: 0.88-0.96), and regular participation in high-intensity leisure-time physical activity (OR=0.62, 95% CI: 0.45-0.84) were protective factors.ConclusionsThe prevalence of high fall risk among Chinese community-dwelling older adults aged 60-79 years is 10.5%. Fall risk demonstrates significant associations with multiple factors including muscle strength, movement patterns, sleep quality, and social support. Strategies enhancing grip strength, promoting regular exercise and high-intensity leisure activities, improving sleep quality, fostering spousal support, and boosting life satisfaction may substantially reduce fall risk in this population.

Institutions

Publication Details

Journal
SHILAP Revista de lepidopterología
Published
2025-05-01
DOI
https://doi.org/10.12290/xhyxzz.2025-0227
Citations
1
Primary Topic
Balance, Gait, and Falls Prevention
Type
article
Field-Weighted Citation Impact
4.76
Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

Current Status and Correlated Factors of Fall Risk Among Chinese Elderly Aged 60-79:A 2024 Nationwide Cross-Sectional Analysis

1 citations
SHILAP Revista de lepidopterología
Balance, Gait, and Falls Prevention
4.76
article

Current Status and Correlated Factors of Fall Risk Among Chinese Elderly Aged 60-79:A 2024 Nationwide Cross-Sectional Analysis

article en
1 citations

Abstract

ObjectiveTo investigate the prevalence and associated factors of fall risk among Chinese older adults, and to examine the roles of urban-rural differences, regional disparities, physical health status, and psychosocial factors in falls among this population, thereby providing evidence for tailored fall prevention strategies.MethodsUsing data from the 2024 National Routine Physical Fitness Surveillance, a multi-stage stratified sampling method was employed to recruit community-dwelling older adults aged 60-79 years across China. High fall-risk individuals were identified using the Chinese version of the self-rated fall risk questionnaire, while demographic, physical health, and psychological indicators were collected via questionnaires and objective measurements. A generalized linear mixed model (GLMM) with province as a random effect was used to analyze fall risk factors.ResultsAmong 7000 eligible participants (male: 44.2%, female: 55.8%), the sample comprised 2124 (60-64 years), 2014 (65-69 years), 1660 (70-74 years), and 1202 (75-79 years) individuals, with 58.4% from rural and 41.6% from urban areas. A total of 733(10.5%) were identified as high fall-risk, with higher prevalence among females (10.9%), urban residents (11.5%), and the oldest age group (75-79 years: 12.4%). GLMM random-intercept logistic regression revealed that advanced age (OR=1.14, 95% CI: 1.02-1.26), urban residence (OR=1.14, 95% CI: 1.03-1.27), living without a partner (OR=1.97, 95% CI: 1.43-2.73), and increased 2-minute step test performance (OR=1.17, 95% CI: 1.06-1.30) were associated with elevated fall risk. Conversely, improved sleep quality (OR=0.75, 95% CI: 0.67-0.82), greater grip strength (OR=0.85, 95% CI: 0.73-0.98), higher life satisfaction (OR=0.69, 95% CI: 0.62-0.76), increased exercise frequency (OR=0.92, 95% CI: 0.88-0.96), and regular participation in high-intensity leisure-time physical activity (OR=0.62, 95% CI: 0.45-0.84) were protective factors.ConclusionsThe prevalence of high fall risk among Chinese community-dwelling older adults aged 60-79 years is 10.5%. Fall risk demonstrates significant associations with multiple factors including muscle strength, movement patterns, sleep quality, and social support. Strategies enhancing grip strength, promoting regular exercise and high-intensity leisure activities, improving sleep quality, fostering spousal support, and boosting life satisfaction may substantially reduce fall risk in this population.

SHILAP Revista de lepidopterología
China Institute of Sport Science (CN)
Sustainable cities and communities
Openalex Percentile: Top 4%
Balance, Gait, and Falls Prevention
4.76
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.