Abstract

BackgroundWhile gait speed, one-leg standing balance, and handgrip strength have been shown to be independent predictors for functional disability, it is unclear whether such simple measures of physical function contribute to improved risk prediction of functional disability in older adults.Methods A total of 1,591 adults aged ≥ 65 years and without functional disability at baseline were followed up for up to 7.9 years. Functional disability was identified using the database of Japan’s Long-term Care Insurance System. Maximum gait speed, one-leg standing time, and handgrip strength were measured at baseline. Cox proportional hazard models were used to estimate the hazard ratios (HRs) and 95 % confidence intervals (CIs) for the association of physical function and functional disability incidence. The incremental predictive value of each physical function measure for risk prediction was quantified using the difference in overall C-statistic, category-free net reclassification improvement (NRI), and integrated discrimination improvement (IDI) index.ResultsDuring follow-up (median: 7.8 years), functional disability was identified in 384 participants. All of the physical function measures were inversely associated with the risk of functional disability, independent of potential confounding factors. The multivariable adjusted HRs (95 % CIs) for functional disability per one standard deviation increment of maximum gait speed, one-leg-standing time, and hand grip strength were 0.73 (0.65–0.83), 0.68 (0.59–0.79), and 0.72 (0.59–0.86), respectively. Incorporation of each of maximum gait speed, one-leg-stand time, and hand grip strength into a basic model with other risk factors significantly improved C-statistic from 0.770 (95 % CIs, 0.751–0.794) to 0.778 (0.759–0.803), 0.782 (0.760–0.805), and 0.775 (0.756–0.800), respectively (all p < 0.05). A model including all three measures had the highest C-statistic of 0.787 (0.765–0.810). The improvements in risk prediction were also confirmed by category-free NRI and IDI index.ConclusionsAdding any of the three measures to a basic model with other known risk factors significantly improved the prediction of functional disability and addition of all three measures provided further improvement of the prediction in older Japanese adults. These data provide robust evidence to support the practical utility of incorporating these simple physical function measures into functional disability risk prediction tools.

Highlights

  • Functional disability in older adults causes increased acute care use [1], hospitalization [2], and death [3], and places considerable burdens on social, economic, and healthcare systems [4], underscoring the need for strategies to delay the onset of functional disability

  • As we found no evidence of deviation from linearity examined using restricted cubic splines, hazard ratios (HRs) were calculated per 1-Standard deviation (SD) increment in the respective measure

  • Over a median of 7.8 years of follow-up (IQR, 6.2 to 7.8 years), 384 participants (24.1 %) developed functional disability, 108 died prior to experiencing the event, and 62 participants were lost to follow-up (4 % of the present sample)

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Summary

Introduction

Functional disability in older adults causes increased acute care use [1], hospitalization [2], and death [3], and places considerable burdens on social, economic, and healthcare systems [4], underscoring the need for strategies to delay the onset of functional disability. Measured physical functions, including gait speed, one-leg standing balance, and handgrip strength, have been shown to be strong independent predictors for future functional disability in older adults [10, 11], and have increasingly been accepted as biomarkers of aging [12, 13]. Objectively measured physical functions may contribute information beyond that obtained from other traditional risk factors and thereby improve the prediction of risk for functional disability. One-leg standing balance, and handgrip strength have been shown to be independent predictors for functional disability, it is unclear whether such simple measures of physical function contribute to improved risk prediction of functional disability in older adults

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