Evidence map›Paper›PMID 41414039›Full record

ArticleThe journals of gerontology. Series B, Psychological sciences and social sciences2026

Prevalence of dementia and mild cognitive impairment in the Mexican population: evidence from Mex-Cog, a harmonized cognitive assessment protocol study.

Silvia Mejia-Arango, Miguel Arce Rentería, Joseph L Saenz, Rebeca Wong

Abstract read
In one paragraph

Article in The journals of gerontology. Series B, Psychological sciences and social sciences, 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

What it found

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2 · The registry

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3 · Its place in the literature

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4 · The record

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5 · Who and what money

Authors and funding

4 authors.

Silvia Mejia-ArangoInstitute of Neuroscience, School of Medicine, University of Texas Rio Grande Valley, Harlingen, Texas, United States.ORCID 0000-0002-6416-1159
Miguel Arce RenteríaDepartment of Neurology, Taub Institute for Research on Alzheimer's Disease and the Aging Brain, Columbia University College of Physicians and Surgeons, New York City, New York, United States.ORCID 0000-0002-4696-6279
Joseph L SaenzEdson College of Nursing and Health Innovation, Arizona State University, Phoenix, Arizona, United States.ORCID 0000-0002-4200-9615
Rebeca WongBarshop Institute for Longevity and Aging Studies, University of Texas Health San Antonio, San Antonio, Texas, United States.

Funding

The Mexican Health and Aging Study - IIR01AG018016 · NIA · UNIVERSITY OF TEXAS MED BR GALVESTON · PI Rebeca Wong · 1999 to 2026
$22.6M
Rio Grande Valley Alzheimer's Resource Center for Minority Aging Research: Partnerships for ProgressP30AG059305 · NIA · UNIVERSITY OF TEXAS RIO GRANDE VALLEY · PI Eron Grant Manusov · 2018 to 2026
$5.8M
Mild Cognitive Impairment and Alzheimer's Disease and Related Dementias: Cross-national longitudinal prognosis and risk factorsRF1AG088009 · NIA · COLUMBIA UNIVERSITY HEALTH SCIENCES · PI ARCE, MIGUEL, BRICENO, EMILY MARIE · 2024 to 2024
$2.3M
NIA/NIH P30AG059305NIA/NIH RF1AG088009NIA NIH HHS R01 AG018016
6 · The paper itself

Abstract

objectivesThis study aimed to estimate the prevalence of dementia and mild cognitive impairment (MCI) in Mexico and establish sociodemographic, contextual, and health predictors leveraging the first wave of the Mexican Cognitive Aging Ancillary Study (Mex-Cog), a subsample of the Mexican Health and Aging Study.

methodsData came from the 2016 wave of Mex-Cog. The analytic sample included 1,629 participants aged 60 and older who completed a comprehensive cognitive battery and informant questionnaire. We employed a robust normative approach to classify cognitive impairment and developed an algorithmic classification of MCI/dementia based on standard research criteria. Prevalence rates used nationally-representative sampling weights.

resultsWe estimated the prevalence of dementia at 6.7% [95% confidence interval (CI): 5.4-8.0] and MCI at 10% (95% CI: 8.7-11.7). Older age, lower education, living in rural areas, having a history of stroke, and heart attack were associated with higher odds of dementia. Mild cognitive impairment was associated with older age, female sex, lower education, rural residence, and lack of health insurance. DISCUSSION: Leveraging the nationally-representative and comprehensive cognitive data in Mex-Cog, an algorithm-derived classification of dementia and MCI provided the prevalence of dementia and MCI in Mexico. Besides the association with cerebrovascular and cardiovascular disease, the effect of education, rural residence, and lack of health insurance suggests an unequal burden of MCI and dementia among the aging Mexican population.

Indexed as

Cognitive DysfunctionDementiaAgedAged, 80 and overFemaleHumansMaleMexicoMiddle AgedNeuropsychological TestsPrevalenceRisk FactorsAlgorithm classificationNeurodegenerative diseaseRisk factors

Identifiers

PMID41414039
PMCPMC13376952

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.