Evidence map›Paper›PMID 41663230›Full record

ArticleJournal of epidemiology and community health2026

Layoffs in automobile manufacturing and mortality among remaining workers.

Kevin T Chen, Sally Picciotto, Patrick T Bradshaw, Jennifer Ahern, Ellen A Eisen

Abstract read
In one paragraph

Article in Journal of epidemiology and community health, 2026. 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
–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

0 citing papers in PubMed.

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

5 authors.

Kevin T ChenSchool of Public Health, Division of Epidemiology, University of California Berkeley, Berkeley, California, USA kevchen@berkeley.edu.ORCID http://orcid.org/0000-0003-3971-4628
Sally PicciottoSchool of Public Health, Division of Environmental Health Sciences, University of California Berkeley, Berkeley, California, USA.
Patrick T BradshawSchool of Public Health, Division of Epidemiology, University of California Berkeley, Berkeley, California, USA.
Jennifer AhernSchool of Public Health, Division of Epidemiology, University of California Berkeley, Berkeley, California, USA.ORCID http://orcid.org/0000-0002-3853-9760
Ellen A EisenSchool of Public Health, Division of Environmental Health Sciences, University of California Berkeley, Berkeley, California, USA.ORCID http://orcid.org/0000-0002-5114-5264

Funding

X-RAY CRYSTALLOGRAPHYP30CA008748 · NCI · SLOAN-KETTERING INSTITUTE FOR CANCER RES · PI Hongbiao Carl Lekaye · 1985 to 2026
$347.4M
Oncology-focused Postdoctoral Training in Care Delivery and Symptom Science (OPTICS)T32CA275764 · NCI · SLOAN-KETTERING INST CAN RESEARCH · PI JONINE L. BERNSTEIN, JUN J MAO · 2023 to 2026
$1.8M
NCI NIH HHS P30 CA008748NCI NIH HHS T32 CA275764NIOSH CDC HHS R01 OH011092NIOSH CDC HHS T42 OH008429
6 · The paper itself

Abstract

backgroundLayoffs may affect the health of those who lose their jobs as well as those who remain employed. Existing studies have found that remaining employed through layoffs is associated with poorer mental health in the short term, but the implications for long-term outcomes such as mortality remain unclear.

methodsWe estimated adjusted HRs for all-cause and cause-specific mortality associated with layoff intensity while employed among white men, non-white men and women in a cohort of 9761 autoworkers who worked at one of three plants in Michigan between the years 1950 and 1980. We defined layoff intensity as the number of layoff months endured while employed divided by duration of employment. We identified layoff months as those in which the percentage of the workforce leaving employment was 1.96 SD above the predicted value from an autoregressive integrated moving average model.

resultsWe found statistically significant associations among non-white men but not women or white men. Relative to layoff intensity below the first quartile, the adjusted HR associated with layoff intensity between the first and second quartiles was 1.35 (95% CI 1.05 to 1.74) for all-cause mortality among non-white men. The adjusted HRs associated with layoff intensity between the second and third quartiles were 1.85 (95% CI 1.08 to 3.17) and 2.41 (95% CI 1.00 to 5.84) for death due to all cancers and lung cancer, respectively.

conclusionLayoffs endured while employed may lead to early mortality among non-white male employees. Reducing workforce instability may reduce racial disparities in health.

Indexed as

AutomobilesEmploymentManufacturing IndustryMortalityAdultCause of DeathFemaleHumansJob SecurityMaleMichiganMiddle AgedCARDIOVASCULAR DISEASESEMPLOYMENTLONGITUDINAL STUDIESMORTALITYOCCUPATIONAL HEALTH

Identifiers

PMID41663230
PMCPMC13170516

What OpenQuestion holds

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LicenceCC BY-NC
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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.