Evidence map›Paper›PMID 39185851›Full record

ArticleJournal of geriatric psychiatry and neurology2025

The Associations of Sensory Impairment With 10-Year Risk of Dementia and Alzheimer's Disease: The Health and Retirement Study, 2010-2020.

Kun Li, Rahul Ghosal, Donglan Zhang, Yike Li, Matthew C Lohman, Monique J Brown, Anwar T Merchant, Chih-Hsiang Yang, Jean Neils-Strunjas, Daniela B Friedman and 1 more

Abstract read
In one paragraph

Article in Journal of geriatric psychiatry and neurology, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
4citing papers in PubMed, 1 pooled it
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

4 citing papers in PubMed, 1 synthesis or guideline pooled it.

  1. Pooled it
  2. Article
  3. Article
  4. Article
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

11 authors.

Kun LiDepartment of Health Policy and Management, Milken Institute School of Public Health, George Washington University, Washington, DC, USA.ORCID 0000-0002-3638-2974
Rahul GhosalDepartment of Epidemiology and Biostatistics, Arnold School of Public Health, University of South Carolina, Columbia, SC, USA.
Donglan ZhangDepartment of Foundations of Medicine, New York University Long Island School of Medicine, New York, NY, USA.
Yike LiDepartment of Otolaryngology-Head and Neck Surgery, Vanderbilt University Medical Center, Nashville, TN, USA.
Matthew C LohmanDepartment of Epidemiology and Biostatistics, Arnold School of Public Health, University of South Carolina, Columbia, SC, USA.
Monique J BrownDepartment of Epidemiology and Biostatistics, Arnold School of Public Health, University of South Carolina, Columbia, SC, USA.
Anwar T MerchantDepartment of Epidemiology and Biostatistics, Arnold School of Public Health, University of South Carolina, Columbia, SC, USA.
Chih-Hsiang YangOffice for the Study of Aging, Arnold School of Public Health, University of South Carolina, Columbia, SC, USA.
Jean Neils-StrunjasOffice for the Study of Aging, Arnold School of Public Health, University of South Carolina, Columbia, SC, USA.
Daniela B FriedmanOffice for the Study of Aging, Arnold School of Public Health, University of South Carolina, Columbia, SC, USA.
Jingkai WeiDepartment of Family and Community Medicine, McGovern Medical School, University of Texas Health Science Center at Houston, Houston, TX, USA.ORCID 0000-0001-8941-8662

Funding

Using machine learning and causal inference approaches to investigate disparities in Alzheimer’s disease and related dementias outcomesR01MD013886 · NIMHD · UNIVERSITY OF GEORGIA · PI ZHANG, DONGLAN · 2019 to 2022
$2.4M
NIMHD NIH HHS R01 MD013886
6 · The paper itself

Abstract

backgroundStudies have examined the association between dual sensory impairment and late-life cognitive outcomes in the U.S with inconsistent findings.

objectiveTo examine the associations between sensory impairment and 10-year risk of dementia or Alzheimer's disease among U.S. adults aged ≥ 50.

methodsA prospective cohort study based on the Health and Retirement Study from 2010 to 2020. Individuals aged ≥ 50 years without self-reported dementia and Alzheimer's disease in 2010 were included in the analysis. Self-reported visual and hearing impairments were measures in 2010. Main failure events included self-reported incident dementia and Alzheimer's disease over a 10-year follow-up period. Participants were categorized as having no visual or hearing impairment, visual impairment only, hearing impairment only, and dual sensory impairment. Fine-Gray competing risk regression model was applied to estimate the associations of sensory impairment with incident dementia and Alzheimer's disease, adjusted for demographic characteristics, health behaviors, and health conditions at baseline.

resultsOf 20,248 identified individuals, 14.6% had visual impairment only, 11.2% had hearing impairment only, and 9.1% had dual impairment at baseline. After adjusting for all covariates, dual sensory impairment was associated with higher risk of dementia (HR = 1.46, 95% CI: 1.23-1.73) and Alzheimer's disease (HR = 1.35, 95% CI: 1.03-1.76). Visual impairment only was also associated with incident dementia and Alzheimer's disease among individuals <65 years.

conclusionOlder adults in the U.S. with visual and hearing impairments simultaneously had a particularly greater risk of dementia and Alzheimer's disease, indicating the needs of targeted screening for timely treatment and further prevention of dementia and Alzheimer's disease.

Indexed as

Alzheimer DiseaseDementiaHearing LossVision DisordersAgedAged, 80 and overFemaleHumansIncidenceMaleMiddle AgedProspective StudiesRisk FactorsUnited StatesagingAlzheimer’s diseasedementiasensory impairment

Identifiers

PMID39185851
PMCPMC11841694

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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 OpenQuestion graph.