Evidence map›Paper›PMID 40640770›Full record

ArticleBMC psychiatry2025

Associations of cumulative hearing and vision loss with depression among U.S. adults aged 50 and older: results from the health and retirement study.

Nan Wang, Bin Gao, Susan L Stewart, Jeffrey S Hoch, Jing Guo

Abstract read
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Article in BMC psychiatry, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

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1citing papers 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

Who cites it

1 citing paper in PubMed.

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4 · The record

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5 · Who and what money

Authors and funding

5 authors.

Nan Wang *Department of Public Health Sciences, University of California, Davis, CA, 95616, USA.
Bin Gao *Department of Psychiatry, The Second Affiliated Hospital, Zhejiang University School of Medicine, Hangzhou, Zhejiang, 310009, China.
Susan L StewartDepartment of Public Health Sciences, University of California, Davis, CA, 95616, USA.
Jeffrey S HochDivision of Health Policy and Management, Department of Public Health Sciences, Center for Healthcare Policy and Research, University of California, Davis, CA, 95616, USA.
Jing GuoSchool of Public Health, Zhejiang Chinese Medical University, Hangzhou, Zhejiang, 310053, China. guojingzju@zju.edu.cn.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundHearing or vision loss at a single time point was associated with depression. However, little is known about how cumulative hearing and vision loss contributes to the depression risk. We aimed to examine associations of cumulative hearing loss (CHL), vision loss (CVL), dual sensory loss (CDSL), and any sensory loss (CASL) with the subsequent trajectories of depressive symptoms and risks of incident depression among US adults aged ≥ 50.

methodsA subpopulation was extracted from the Health and Retirement Study (HRS), a nationally representative cohort study. The final sample included 7,545 adults aged 50 and older. Burdens of CHL, CVL, CDSL, and CASL were assessed spanning eight years (1998-2006) across five Waves (Waves 4-8) and were categorized into 0, 1, 2, and ≥ 3 time points. Depressive symptoms were measured by the Center for Epidemiologic Studies Depression Scale (CES-D) during a ten-year follow-up from Wave 9 (2008) to Wave 15 (2020). Mixed-effects linear regression models were used to estimate associations between CVL and changes in depressive symptoms over time (CES-D scores), incorporating CVL × time interactions to assess differential rates of change. Cox proportional hazard regression models were used to estimate hazard ratios (HRs) and 95% confidence intervals (CIs) for the association between CVL and the risk of incident depression. Models were adjusted for sociodemographic factors (Model 1) and additionally for lifestyle and health-related covariates (Model 2). Similarly, we separately analyzed associations of CHL, CBSL, and CASL with trajectories of depressive symptoms and risks of incident depression.

resultsTwo thousand four hundred twenty-one participants developed an incident depression over a median follow-up of eight years. Results indicated that compared with participants without vision loss, those with CVL at 1, 2, and ≥ 3 time points during Waves 4-8 had significantly higher CES-D scores and higher risks of incident depression during Waves 9-15. Similar positive associations were found for CHL, CDSL, and CASL.

conclusionsHeavier burdens of CHL, CVL, CDSL, and CASL were associated with accelerated increases in depressive symptoms and elevated risks of incident depression among US adults aged 50 and older.

Indexed as

DepressionHearing LossVision DisordersAgedFemaleHumansIncidenceMaleMiddle AgedRisk FactorsUnited StatesCumulative measurementsDepressive symptomsEpidemiologySensory lossTrajectories

Identifiers

PMID40640770
PMCPMC12243300

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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.