Evidence map›Paper›PMID 41283783›Full record

ArticleInternational journal of epidemiology2025

Heterogeneity in the association between retirement and cognitive function: a machine learning analysis across 19 countries.

Koryu Sato, Haruko Noguchi, Kosuke Inoue

Abstract read
In one paragraph

Article in International journal of epidemiology, 2025. 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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0cells of the map it votes in
0citing papers in PubMed
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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

0 citing papers in PubMed.

No citing paper in PubMed yet.

4 · The record

Corrections and comments

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5 · Who and what money

Authors and funding

3 authors.

Koryu SatoFaculty of Policy Management, Keio University, Kanagawa, Japan.ORCID 0000-0002-8418-8535
Haruko NoguchiGraduate School of Economics, Waseda University, Tokyo, Japan.ORCID 0000-0002-4437-8238
Kosuke InoueDepartment of Health Promotion and Behavioral Sciences, Graduate School of Medicine and School of Public Health, Kyoto University, Kyoto, Japan.ORCID 0000-0001-9614-8103

Funding

Integrting Information About Aging SurveysR01AG030153 · NIA · UNIVERSITY OF SOUTHERN CALIFORNIA · PI Sara Adar, Alden L. Gross · 2007 to 2026
$41.7M
Mega Meta Data Set of the Health and Retirement Surveys Around the WorldRC2AG036619 · NIA · RAND CORPORATION · PI KAPTEYN, ARIE · 2009 to 2010
$2.0M
Archiving & Creating User Friendly Data: the Longitudinal Aging Survey in IndiaR03AG043052 · NIA · RAND CORPORATION · PI LEE, JINKOOK · 2012 to 2012
$95k
Health Care Science Institute ResearchJapan Agency for Medical Research and Development 25ek0210218h0001Japan Science and Technology JPMJPR23R2Japan Society for the Promotion of Science 23KK0240Japan Society for the Promotion of Science 25K02887Japan Society for the Promotion of Sciences 20K18931Japan Society for the Promotion of Sciences 23H03164Japan Society for the Promotion of Sciences 23K27854NIA NIH HHS NIA U01AG009740NIA NIH HHS R01 AG030153NIA NIH HHS R03 AG043052NIA NIH HHS RC2 AG036619University of Michigan
6 · The paper itself

Abstract

backgroundRising state pension ages in many developed countries may influence cognitive aging by delaying retirement, yet the cognitive consequences of retirement likely vary across individuals and contexts. This study investigates the heterogeneous association between retirement and cognitive function.

methodsWe analyzed harmonized data from three longitudinal studies: the Health and Retirement Study, the English Longitudinal Study on Ageing, and the Survey of Health, Ageing and Retirement in Europe. The dataset encompassed three waves across 19 counties from 2014 to 2019. Our study included 12 811 individuals who worked in the first wave, from whom each survey collected covariate information. We assessed retirement status among participants aged 50-80 years in the second wave and measured cognitive function using word recall tests in the third wave. The analysis employed instrumental variable causal forests estimation, utilizing state pension age as an instrument for retirement.

resultsAmong 7432 individuals with retirement propensity scores between 0.1 and 0.9, 2165 (29.1%) retired during the second wave. Analysis revealed that retirees recalled 1.348 more words than workers on average. The association between retirement and cognitive function was heterogeneous; greater cognitive benefits were observed among women, individuals with higher socioeconomic status, those with robust pre-retirement health, and those who engaged in physical activity before retirement.

conclusionsThe observed heterogeneous associations suggest policymakers should consider incorporating early retirement options into the pension system, allowing individuals to make retirement decisions based on their circumstances.

Indexed as

AgingCognitionCognitive AgingMachine LearningRetirementAgedAged, 80 and overEuropeFemaleHumansLongitudinal StudiesMaleMental RecallMiddle AgedPensionscausal forestsepisodic memoryinstrumental variableretirementstate pension age

Identifiers

PMID41283783
PMCPMC12641609

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Registered trials

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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.