ArticleNeuroepidemiology2023
Estimating the Prevalence of Dementia in India Using a Semi-Supervised Machine Learning Approach.
Article in Neuroepidemiology, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. An erratum has been issued. Cited by 5 papers, 2 of them syntheses that pooled it.
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Who cites it
5 citing papers in PubMed, 2 syntheses or guidelines pooled it.
- Representation of Rural Older Adults in AI for Health Research: Systematic Literature Review.JMIR human factors · 2025Pooled it
- Effectiveness of neuro-feedback on Alzheimer's rehabilitation: a bibliometric analysis.Neurodegenerative disease management · 2024Pooled it
- Low-burden AI approach for cross-national early identification of cognitive impairment using real-world questionnaire response behaviours.Nature communications · 2026Article
- Missing data and imputation in the international studies following the Harmonized Cognitive Assessment Protocol.The journals of gerontology. Series B, Psychological sciences and social sciences · 2026Article
- Noise during cognitive tests and older adults' cognitive performance: evidence from India.Innovation in aging · 2026Article
Corrections and comments
- Erratum issuedErratum.2025
Authors and funding
5 authors.
Funding
Abstract
introductionAccurate estimation of dementia prevalence is essential for making effective public and social care policy to support individuals and families suffering from the disease. The purpose of this paper is to estimate the prevalence of dementia in India using a semi-supervised machine learning approach based on a large nationally representative sample.
methodsThe sample of this study is adults 60 years or older in the wave 1 (2017-2019) of the Longitudinal Aging Study in India (LASI). A subsample in LASI received extensive cognitive assessment and clinical consensus ratings and therefore has diagnoses of dementia. A semi-supervised machine learning model was developed to predict the status of dementia for LASI participants without diagnoses. After obtaining the predictions, sampling weights and age standardization to the World Health Organization (WHO) standard population were applied to generate the estimate for prevalence of dementia in India.
resultsThe prevalence of dementia for those aged 60 years and older in India was 8.44% (95% CI: 7.89%-9.01%). The age-standardized prevalence was estimated to be 8.94% (95% CI: 8.36%-9.55%). The prevalence of dementia was greater for those who were older, were females, received no education, and lived in rural areas. DISCUSSION: The prevalence of dementia in India may be higher than prior estimates derived from local studies. These prevalence estimates provide the information necessary for making long-term planning of public and social care policy. The semi-supervised machine learning approach adopted in this paper may also be useful for other large population aging studies that have a similar data structure.
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