ArticleBMC geriatrics2022
Novel physical performance-based models for activities of daily living disability prediction among Chinese older community population: a nationally representative survey in China.
Article in BMC geriatrics, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 11 papers, 3 of them syntheses that pooled it.
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11 citing papers in PubMed, 3 syntheses or guidelines pooled it, 11 citations in OpenAlex.
- Clinical importance of simple muscular fitness tests to predict long-term health conditions: a systematic review and meta-analysis of 94 cohort studies.British journal of sports medicine · 2026Pooled it
- Disability risk prediction models in community-dwelling older adults: a systematic review.BMC geriatrics · 2026Pooled it
- Risk prediction models for disability in older adults: a systematic review and critical appraisal.BMC geriatrics · 2024Pooled it
- A Prediction Model for One-Year Disability Risk Among Community-Dwelling Older Adults in China: Integrating Physical, Metabolic, and Psychosocial Factors.Health care science · 2026Article
- Development and external validation of a machine learning model for three-tier disability risk stratification in older adults.Frontiers in public health · 2026Article
- Application of interpretable machine learning to predict activities of daily living disability in sarcopenia: insights from the CHARLS dataset.BMC geriatrics · 2025Article
- Association between oral health and physical performance in Brazilian older adults: SABE cohort study.BMC oral health · 2024Article
- Mortality and disability risk among older adults unable to complete grip strength and physical performance tests: a population-based cohort study from China.BMC public health · 2024Article
- Physical activity as a predictor of activities of daily living in older adults: a longitudinal study in China.Frontiers in public health · 2024Article
- Association between disability in activities of daily living and phase angle in hemodialysis patients.BMC nephrology · 2023Observational
- Disability risk prediction model based on machine learning among Chinese healthy older adults: results from the China Health and Retirement Longitudinal Study.Frontiers in public health · 2023Article
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9 authors at 1 institution in 1 country.
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No grant is acknowledged in the PubMed record.
Abstract
backgroundPhysical performances including upper and lower limb functions have predictive roles in activities of daily living (ADL) disability, but they have rarely been incorporated into prediction models. This study primarily aimed to develop and validate novel physical performance-based models for ADL disability among Chinese older adults. Comparisons of predictive performance across multiple models were performed, and model simplification was further explored.
methodsData were obtained from the China Health and Retirement Longitudinal Study in the 2011 and 2015 waves, containing 2192 older adults over 60 years old. Our models were constructed by logistic regression analysis, using a backward stepwise selection. Model performance was internally validated by discrimination, calibration, and clinical utility. Integrated Discrimination Improvement (IDI) and Net Reclassification Improvement (NRI) were used to assess the incremental benefit of the extended models. Moreover, nomograms were built for visualization.
resultsWe selected gender, age, smoking, self-report health condition, BMI, depressive symptoms, and cognitive function into the fundamental model (Model 1). Based on Model 1, five novel prediction models were constructed by adding handgrip strength (Model 2), Short Physical Performance Battery (SPPB) (Model 3), gait speed (Model 4), handgrip strength plus SPPB (Model 5), and handgrip strength plus gait speed (Model 6), respectively. Significant improvement in predictive values were observed for all five novel models compared with Model 1 (C-index = 0.693). The lower limb model (Model 3 SPPB model: C-index = 0.731) may play a key role in the prediction of ADL disability, reflecting a comparable predictive value to the comprehensive models combining both upper and lower limbs (Model 5 handgrip strength + SPPB model: C-index = 0.732). When we simplified the lower limb models by replacing SPPB with gait speed, the predictive values attenuated slightly (C-index: Model 3 vs Model 4: 0.731 vs 0.714; Model 5 vs Model 6: 0.732 vs 0.718), but still better than the upper limb model (Model 2 handgrip strength model: C-index = 0.701).
conclusionsPhysical performance-based models, especially lower limb model, provided improved prediction for ADL disability among Chinese older adults, which may help guide the targeted intervention.
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