Heterogeneity in the association between retirement and cognitive function: a machine learning analysis across 19 countries.
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| Title: | Heterogeneity in the association between retirement and cognitive function: a machine learning analysis across 19 countries. |
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| Authors: | Sato K; Faculty of Policy Management, Keio University, Kanagawa, Japan.; Graduate School of Economics, Waseda University, Tokyo, Japan.; Department of Social Epidemiology, Graduate School of Medicine and School of Public Health, Kyoto University, Kyoto, Japan., Noguchi H; Graduate School of Economics, Waseda University, Tokyo, Japan., Inoue K; Department of Health Promotion and Behavioral Sciences, Graduate School of Medicine and School of Public Health, Kyoto University, Kyoto, Japan. |
| Source: | International journal of epidemiology [Int J Epidemiol] 2025 Oct 14; Vol. 54 (6). |
| Publication Type: | Journal Article |
| Language: | English |
| Journal Info: | Publisher: Oxford University Press Country of Publication: England NLM ID: 7802871 Publication Model: Print Cited Medium: Internet ISSN: 1464-3685 (Electronic) Linking ISSN: 03005771 NLM ISO Abbreviation: Int J Epidemiol Subsets: MEDLINE |
| Imprint Name(s): | Original Publication: [London] Oxford University Press. |
| MeSH Terms: | Retirement*/psychology , Retirement*/statistics & numerical data , Machine Learning* , Cognition* , Cognitive Aging* , Aging*, Humans ; Female ; Aged ; Male ; Middle Aged ; Longitudinal Studies ; Aged, 80 and over ; Europe ; Pensions/statistics & numerical data ; Mental Recall |
| Abstract: | Background: Rising 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. Methods: We 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. Results: Among 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. Conclusions: The 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. (© The Author(s) 2025. Published by Oxford University Press on behalf of the International Epidemiological Association.) |
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| Grant Information: | 20K18931 Japan Society for the Promotion of Sciences; 23H03164 Japan Society for the Promotion of Sciences; 23K27854 Japan Society for the Promotion of Sciences; Health Care Science Institute Research; R01 AG030153 United States AG NIA NIH HHS; RC2 AG036619 United States AG NIA NIH HHS; R03 AG043052 United States AG NIA NIH HHS; NIA U01AG009740 United States AG NIA NIH HHS; University of Michigan; 23KK0240 Japan Society for the Promotion of Science; 25K02887 Japan Society for the Promotion of Science; JPMJPR23R2 Japan Science and Technology; 25ek0210218h0001 Japan Agency for Medical Research and Development |
| Contributed Indexing: | Keywords: causal forests; episodic memory; instrumental variable; retirement; state pension age |
| Entry Date(s): | Date Created: 20251124 Date Completed: 20251124 Latest Revision: 20251127 |
| Update Code: | 20251127 |
| PubMed Central ID: | PMC12641609 |
| DOI: | 10.1093/ije/dyaf201 |
| PMID: | 41283783 |
| Database: | MEDLINE |
Nájsť tento článok vo Web of Science | Abstract: | Background: Rising 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.<br />Methods: We 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.<br />Results: Among 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.<br />Conclusions: The 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.<br /> (© The Author(s) 2025. Published by Oxford University Press on behalf of the International Epidemiological Association.) |
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| ISSN: | 1464-3685 |
| DOI: | 10.1093/ije/dyaf201 |