Evidence map›Paper›PMID 42249272›Full record

ArticleBMC public health2026

Programmatic readiness and health literacy predict the adoption of multidomain dementia prevention: a nationwide survey of Japanese municipalities.

Yujiro Kuroda, Aya Goto, Yumi Shindo, Yohei Koyama, Kohta Suzuki

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Article in BMC public health, 2026. 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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1 · What the graph read from it

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4 · The record

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5 · Who and what money

Authors and funding

5 authors.

Yujiro KurodaDepartment of Health and Psychosocial Medicine, Aichi Medical University School of Medicine, Aichi, Japan. kuroday@aichi-med-u.ac.jp.
Aya GotoDepartment of Global Health and Population, Harvard T.H. Chan School of Public Health, Boston, MA, USA.
Yumi ShindoCenter for Cultivating and Enlightenment for Healthy Longevity, Tokyo Metropolitan Institute for Geriatrics and Gerontology, Itabashi-ku, Tokyo, Japan.
Yohei KoyamaDepartment of Public Health, Fukushima Medical University, Fukushima, Japan.
Kohta SuzukiDepartment of Health and Psychosocial Medicine, Aichi Medical University School of Medicine, Aichi, Japan.

Funding

JSPS KAKENHI 24K13409Toyota Foundation D24-R-0091
6 · The paper itself

Abstract

backgroundAlthough multidomain interventions, which simultaneously address several risk factors are an evidence-based strategy for dementia prevention, their implementation status and factors driving their adoption by local governments remain unclear. This implementation gap is critical, as limited uptake on dementia prevention programs may restrict opportunities to reduce dementia risk at the population level. This study aimed to clarify the landscape of dementia prevention activities across Japanese municipalities and identify factors associated with the intention to implement comprehensive multidomain programs.

methodsA nationwide cross-sectional survey was conducted, targeting all 1,741 municipalities in Japan. A structured questionnaire was developed and used to assess the implementation of 12 World Health Organization (WHO)-recommended prevention items as well as the municipalities' intention to adopt a multidomain program. A multinomial logistic regression analysis was performed to identify factors associated with a high adoption intention (Active Group) compared to a clear non-adoption intention (Non-Adoption Group), adjusting for municipal characteristics.

resultsOf 941 included municipalities (54.0% response rate), current prevention efforts were predominantly focused on cognitive, social, and physical activities, with less emphasis on cardiovascular risk management. The strongest predictor of adoption intention was the implementation of measures to improve residents' health literacy (relative risk ratio [RRR] = 2.8, 95% confidence interval [CI]: 1.2-6.5). Other significant factors included prior experience with multidomain programs (RRR = 1.4, 95% CI: 1.2-1.7), awareness of the WHO guidelines (RRR = 1.4, 95% CI: 1.0-2.0), and the number of currently implemented items (RRR = 1.2, 95% CI: 1.1-1.3). Structural factors such as staffing levels were not significant.

conclusionsThe adoption of evidence-based dementia prevention programs by the Japanese municipalities appears to depend more on programmatic readiness and a commitment to public health communication than on structural capacity alone. These findings highlight the importance of strengthening readiness and health literacy to support municipalities in translating evidence-based dementia prevention strategies into practice and advancing population-level risk reduction.

Indexed as

DementiaHealth LiteracyCitiesCross-Sectional StudiesHumansJapanLocal GovernmentSurveys and QuestionnairesCross-sectional studyDementia preventionHealth literacyImplementation scienceMunicipalitiesPublic health policy

Identifiers

PMID42249272
PMCPMC13476930

What Socratic holds

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the Socratic graph.