Walking difficulty as a marker of high health need and education-related healthcare response in older adults: a cross-national multicohort study

Health systems need simple ways to identify older adults with high health need and to assess whether healthcare response is distributed according to need rather than social position. Walking difficulty is inexpensive to ascertain and widely harmonisable across ageing cohorts, but its value as a denominator for healthcare equity assessment has been less well characterised. We analysed the China Health and Retirement Longitudinal Study (CHARLS), English Longitudinal Study of Ageing (ELSA), Health and Retirement Study (HRS), Korean Longitudinal Study of Aging (KLoSA), Mexican Health and Aging Study (MHAS), and Survey of Health, Ageing and Retirement in Europe (SHARE). Cohort-specific Cox models and DerSimonian-Laird random-effects meta-analysis estimated mortality associations, with a REML-Hartung-Knapp sensitivity analysis. Among adults with walking difficulty in cohorts with linked healthcare data, the relative index of inequality (RII) and slope index of inequality (SII) estimated education-related response after measured-need adjustment. Standardised scenarios expressed response gaps per 1000 high-need older adults. Walking difficulty was associated with higher mortality risk (pooled hazard ratio 2.21, 95% CI 2.06–2.36; I²=73.8%; five cohorts), with substantial between-cohort heterogeneity. A restricted-maximum-likelihood analysis with Hartung-Knapp inference gave a hazard ratio of 2.18 (95% CI 1.87–2.53) and a 95% prediction interval of 1.66–2.87. Walking difficulty also identified greater measured need, including multimorbidity (odds ratio 3.05, 95% CI 2.98–3.13; absolute difference 25.1% points). For any-care contact, higher educational position was associated with greater need-adjusted response in CHARLS, HRS, and SHARE; the MHAS estimate was directionally similar but imprecise. Scenario gaps ranged from 15.6 to 15.7 additional contacts per 1000 high-need adults in HRS and SHARE to 296.7 (95% CI 74.9-456.8) in CHARLS; the MHAS estimate was 70.0 (27.8–101.0). Cost-related unmet-need evidence was clearest in SHARE. Walking difficulty is a pragmatic marker of higher mortality risk and measured health need. Within this high-need population, healthcare response remained patterned by education after measured-need adjustment, although the magnitude and certainty differed across cohorts. Standardised scenarios are policy benchmarks rather than causal intervention effects.

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Journal
BMC Medicine
Published
2026-09-21
DOI
https://doi.org/10.1186/s12916-026-05226-8
Primary Topic
Technology Use by Older Adults
Type
article
Field-Weighted Citation Impact
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article

Walking difficulty as a marker of high health need and education-related healthcare response in older adults: a cross-national multicohort study

伍谟煊, Ninggang Liang, Dan Xing, Long Chen et al.
BMC Medicine
Technology Use by Older Adults
article

Walking difficulty as a marker of high health need and education-related healthcare response in older adults: a cross-national multicohort study

伍谟煊, Ninggang Liang, Dan Xing, Long Chen, Hu Li, Hui Li, Jianhao Lin
article en

Abstract

Health systems need simple ways to identify older adults with high health need and to assess whether healthcare response is distributed according to need rather than social position. Walking difficulty is inexpensive to ascertain and widely harmonisable across ageing cohorts, but its value as a denominator for healthcare equity assessment has been less well characterised. We analysed the China Health and Retirement Longitudinal Study (CHARLS), English Longitudinal Study of Ageing (ELSA), Health and Retirement Study (HRS), Korean Longitudinal Study of Aging (KLoSA), Mexican Health and Aging Study (MHAS), and Survey of Health, Ageing and Retirement in Europe (SHARE). Cohort-specific Cox models and DerSimonian-Laird random-effects meta-analysis estimated mortality associations, with a REML-Hartung-Knapp sensitivity analysis. Among adults with walking difficulty in cohorts with linked healthcare data, the relative index of inequality (RII) and slope index of inequality (SII) estimated education-related response after measured-need adjustment. Standardised scenarios expressed response gaps per 1000 high-need older adults. Walking difficulty was associated with higher mortality risk (pooled hazard ratio 2.21, 95% CI 2.06–2.36; I²=73.8%; five cohorts), with substantial between-cohort heterogeneity. A restricted-maximum-likelihood analysis with Hartung-Knapp inference gave a hazard ratio of 2.18 (95% CI 1.87–2.53) and a 95% prediction interval of 1.66–2.87. Walking difficulty also identified greater measured need, including multimorbidity (odds ratio 3.05, 95% CI 2.98–3.13; absolute difference 25.1% points). For any-care contact, higher educational position was associated with greater need-adjusted response in CHARLS, HRS, and SHARE; the MHAS estimate was directionally similar but imprecise. Scenario gaps ranged from 15.6 to 15.7 additional contacts per 1000 high-need adults in HRS and SHARE to 296.7 (95% CI 74.9-456.8) in CHARLS; the MHAS estimate was 70.0 (27.8–101.0). Cost-related unmet-need evidence was clearest in SHARE. Walking difficulty is a pragmatic marker of higher mortality risk and measured health need. Within this high-need population, healthcare response remained patterned by education after measured-need adjustment, although the magnitude and certainty differed across cohorts. Standardised scenarios are policy benchmarks rather than causal intervention effects.

BMC Medicine
Sechenov University (RU), Peking University (CN), Peking University People's Hospital (CN)
National Key Research and Development Program of China
Quality Education
Openalex Percentile: Top 5%
Technology Use by Older Adults
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