Knee Extension Strength and Mobility as Key Predictors of Falls in Older Adults: Implications for Fall Prevention Programs

With the global population aging, managing fall risk among older adults has become a critical public health concern. Older adults attending adult daycare centers in South Korea are vulnerable due to poorer physical function and higher walking aid usage compared to community-dwelling counterparts. However, existing studies have primarily targeted community-dwelling older adults and rarely integrated both psychological and physical factors comprehensively. This study aimed to bridge these gaps and enhance fall prevention strategies. A study was conducted with 78 older adults (mean age = 83.24 ± 6.50 years; 82.1% female) from adult daycare centers. Physical assessments and structured interviews were conducted to measure strength, balance, and proprioception. Structured interviews collected demographic data and fear of falling. Significant differences in walking aid use, strength, balance, and proprioception were observed between participants with and without a history of falls (p < 0.05). Logistic regression analysis revealed that knee extension strength (OR = 0.893, 95% CI = 0.819–0.973) and longer timed up and go test times (OR = 1.098, 95% CI = 1.012–1.192) were significant predictors of falls. The combined model achieved an AUC of 0.83 (95% CI = 0.73–0.92), demonstrating good discriminative validity for fall prediction. Given the high fall risk in this population, targeted programs emphasizing lower-limb strengthening and mobility enhancement are essential to reduce fall incidence.

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Publication Details

Journal
Applied Sciences
Published
2025-12-21
DOI
https://doi.org/10.3390/app16010093
Primary Topic
Balance, Gait, and Falls Prevention
Type
article
Field-Weighted Citation Impact
0.00

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article

Knee Extension Strength and Mobility as Key Predictors of Falls in Older Adults: Implications for Fall Prevention Programs

J W Kim, Jong-Seon Oh, Seong-Gil Kim
Applied Sciences
Balance, Gait, and Falls Prevention
article

Knee Extension Strength and Mobility as Key Predictors of Falls in Older Adults: Implications for Fall Prevention Programs

J W Kim, Jong-Seon Oh, Seong-Gil Kim
article en

Abstract

With the global population aging, managing fall risk among older adults has become a critical public health concern. Older adults attending adult daycare centers in South Korea are vulnerable due to poorer physical function and higher walking aid usage compared to community-dwelling counterparts. However, existing studies have primarily targeted community-dwelling older adults and rarely integrated both psychological and physical factors comprehensively. This study aimed to bridge these gaps and enhance fall prevention strategies. A study was conducted with 78 older adults (mean age = 83.24 ± 6.50 years; 82.1% female) from adult daycare centers. Physical assessments and structured interviews were conducted to measure strength, balance, and proprioception. Structured interviews collected demographic data and fear of falling. Significant differences in walking aid use, strength, balance, and proprioception were observed between participants with and without a history of falls (p < 0.05). Logistic regression analysis revealed that knee extension strength (OR = 0.893, 95% CI = 0.819–0.973) and longer timed up and go test times (OR = 1.098, 95% CI = 1.012–1.192) were significant predictors of falls. The combined model achieved an AUC of 0.83 (95% CI = 0.73–0.92), demonstrating good discriminative validity for fall prediction. Given the high fall risk in this population, targeted programs emphasizing lower-limb strengthening and mobility enhancement are essential to reduce fall incidence.

Applied SciencesVol. 16(1)
Korea National University of Transportation (KR), Sun Moon University (KR)
Ministry of Education, India
Openalex Percentile: Top 23%
Balance, Gait, and Falls Prevention
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Knee Extension Strength and Mobility as Key Predictors of Falls in Older Adults: Implications for Fall Prevention Programs — J W Kim, Jong-Seon Oh, et al. · Applied Sciences (2025) | TGRS Research Map | TGRS