ArticleBMC public health2025
Development of a predictive model for long-term care and support eligibility certification associated with dementia-related functional impairments: the IRIDE cohort study.
Article in BMC public health, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.
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Abstract
backgroundThe Long-Term Care Insurance (LTCI) system in Japan provides a framework for assessing dementia-related functional decline, enabling the development of predictive models based on daily functional independence. This study aimed to develop and validate risk prediction models for dementia-related functional impairments using data from the Integrated Research Initiative for Living Well with Dementia Cohort Study (IRIDE-CS), integrating multiple cohort studies conducted in urban Japan.
methodsData, including participant characteristics and dementia-related functional impairments, were collected from 3678 participants in the IRIDE-CS aged 65 and older. These data were separated into a derivation set (n = 2764) and a validation set (n = 914) for model development and validation, based on the independent cohorts that constitute the IRIDE-CS. Dementia-related functional impairments was defined as the first certification of cognitive impairment at Level I or higher in the LTCI system, with follow-up from April 2018 to August 2023. Two models were developed: Model 1, focused on dementia-related functional impairments factors in Japan, whereas Model 2, prioritized social implementation by limiting predictors to self-reportable items. The predictive performance of each model was evaluated using the concordance index (C-index).
resultsDuring follow-up, dementia-related functional impairments occurred in 16.9% of the derivation set and 16.3% of the validation set. Model 1, which included eight predictors (age, history of stroke, visual impairment, hearing impairment, exercise habits, gait speed, grip strength, and albumin), achieved a C-index of 0.75 (95% confidence interval [CI]: 0.73–0.77) in the derivation dataset and 0.78 (95% CI: 0.74–0.82) in the validation dataset. Model 2, which included six predictors (age, history of stroke, history of heart disease, visual impairment, hearing impairment, and exercise habits), achieved a C-index of 0.73 (95% CI: 0.70–0.75) in the derivation dataset and 0.77 (95% CI: 0.73–0.81) in the validation dataset.
conclusionsWe developed and validated two predictive models for assessing the risk of dementia-related functional impairments using cohort data from urban Japan, demonstrating comparable performance to existing models. Further studies are needed to assess the applicability of these models in non-urban areas and middle-aged populations to enhance generalizability.
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