Evidence map›Paper›PMID 36941937›Full record

ArticleSafety and health at work2023

Impact of Reduced Working Hours and Night Work Hours on Metabolic Syndrome: A Quasi-Experimental Study.

Hye-Eun Lee, Ichiro Kawachi

Open access · goldAbstract read
In one paragraph

Article in Safety and health at work, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 papers.

0numbers the graph read from it
0cells of the map it votes in
5citing papers in PubMed
0.8field-weighted citation impact, top 26% 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

5 citing papers in PubMed, 4 citations in OpenAlex.

  1. Review
  2. Metabolic syndrome prevalence and cardiovascular disease risk among school teachers.International journal of occupational medicine and environmental health · 2025
    Article
  3. Review
  4. Review
  5. Article
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

2 authors at 2 institutions in 2 countries.

Hye-Eun LeeDepartment of Social and Preventive Medicine, Hallym University College of Medicine, Chuncheon, Republic of Korea.
Ichiro KawachiDepartment of Social and Behavioral Sciences, Harvard T.H. Chan School of Public Health, Boston, MA, United States.
Hallym University · KRHarvard University · US

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Objectives: Epidemiological evidence linking long working hours and shift work to metabolic syndrome remains inadequate. We sought to evaluate the impact of reducing working hours on metabolic syndrome. Methods: We compared the prevalence of metabolic syndrome among male manual workers in a manufacturing company (N = 371) before and after the introduction of policy to reduce daily work hours from 10 to 8 hours. Components of metabolic syndrome were measured in periodic health examinations before the intervention, 6-9 months after, and 1.5-2 years after the intervention. Generalized estimating equation models were used to estimate changes in the prevalence of metabolic syndrome. Analyses were stratified by day work versus shift work. Results: The results showed a significantly decreased prevalence of metabolic syndrome 6-9 months following the intervention in day workers (risk ratio = 0.68, 95% confidence interval 0.52-0.88), but the benefit disappeared after 1.5-2 years. Shift workers showed a decreased prevalence of metabolic syndrome for the whole follow-up duration after the intervention, although the change was not statistically significant. Conclusion: Reducing working hours was associated with short-term improvement in metabolic syndrome in male manual workers.

Indexed as

cardiometabolicnight shift workobesityorganizational interventionpre-post studyRepublic of Korea

Identifiers

PMID36941937
PMCPMC10024172
OpenAlexW4309204049

What OpenQuestion holds

Textmetadata
LicenceCC BY-NC-ND
Read underepoch 390

Registered trials

None linked

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.