Evidence map›Paper›PMID 32448823›Full record

ArticleJournal of epidemiology2021

What Factors Affect the Evolution of the Wife's Mental Health After the Husband's Retirement? Evidence From a Population-Based Nationwide Survey in Japan.

Takashi Oshio

Open access · goldAbstract read
In one paragraph

Article in Journal of epidemiology, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

0numbers the graph read from it
0cells of the map it votes in
0citing papers in PubMed
0.5field-weighted citation impact, top 33% of its field
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, 2 citations in OpenAlex.

No citing paper in PubMed yet.

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

1 author at 1 institution in 2 countries.

Takashi OshioInstitute of Economic Research, Hitotsubashi University.ORCID http://orcid.org/0000-0001-8142-5585
Hitotsubashi University · JP

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundThe "retired husband syndrome" refers to the negative impact of the husband's retirement on the wife's health. This study provided new insights by examining whether and to what extent the wife's social participation, interactions with her husband, and job status prior to her husband's retirement affected the evolution of her mental health after her husband's retirement.

methodsWe collected data from a 12-wave nationwide panel survey conducted from 2005 to 2016, starting with individuals aged 50-59 years. Focusing on 3,794 female respondents whose husbands retired during the survey period, we applied random-effects linear regression models to investigate the evolution of their mental health as measured by the Kessler 6 (K6) score (range, 0-24; Mean, 3.41; standard deviation, 4.11) during the 5 years after their husbands' retirement.

resultsOn average, the wife's K6 score rose by 0.18 (95% confidence interval [CI], 0.08-0.28), 0.18 (95% CI, 0.03-0.34), and 0.19 (95% CI, -0.02 to 0.43) in the first 3 years, respectively, after the husband's retirement, before declining toward the baseline level. However, the wife's active social participation, intense interactions with her husband, and absence of paid employment before her husband's retirement prevented her mental health from deteriorating.

conclusionThe results suggest the limited relevance of the "retired husband syndrome" among middle-aged Japanese couples. The effects of a husband's retirement on the wife's mental health depended heavily on her prior behavior.

Indexed as

FemaleHumansJapanMaleMental HealthMiddle AgedRetirementSpousesSurveys and Questionnairesmarital qualitymental healthrandom-effects modelretired husband syndromesocial participation

Identifiers

PMID32448823
PMCPMC8021876
OpenAlexW3026273491

What OpenQuestion holds

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LicenceCC BY
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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.