Evidence map›Paper›PMID 35425614›Full record

ArticleAnnals of occupational and environmental medicine2022

The effect of long working hours on developing type 2 diabetes in adults with prediabetes: The Kangbuk Samsung Cohort Study.

Eunhye Seo, Yesung Lee, Eunchan Mun, Dae Hoon Kim, Youshik Jeong, Jaehong Lee, Jinsook Jeong, Woncheol Lee

Abstract read
In one paragraph

Article in Annals of occupational and environmental medicine, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 10 papers, 2 of them syntheses that pooled it.

0numbers the graph read from it
0cells of the map it votes in
10citing papers in PubMed, 2 pooled it
–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

10 citing papers in PubMed, 2 syntheses or guidelines pooled it.

  1. Pooled it
  2. Pooled it
  3. Article
  4. Article
  5. Social determinants of health and type 2 diabetes in Asia.Journal of diabetes investigation · 2025
    Review
  6. Review
  7. Observational
  8. The impact of long working hours on daily sodium intake.Annals of occupational and environmental medicine · 2024
    Article
  9. Article
  10. The Korea Cohort Consortium: The Future of Pooling Cohort Studies.Journal of preventive medicine and public health = Yebang Uihakhoe chi · 2022
    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

8 authors.

Eunhye SeoDepartment of Occupational and Environmental Medicine, Kangbuk Samsung Hospital, Sungkyunkwan University School of Medicine, Seoul, Korea.ORCID https://orcid.org/0000-0003-0790-6385
Yesung LeeDepartment of Occupational and Environmental Medicine, Kangbuk Samsung Hospital, Sungkyunkwan University School of Medicine, Seoul, Korea.ORCID https://orcid.org/0000-0002-8844-492X
Eunchan MunDepartment of Occupational and Environmental Medicine, Kangbuk Samsung Hospital, Sungkyunkwan University School of Medicine, Seoul, Korea.ORCID https://orcid.org/0000-0002-2808-0423
Dae Hoon KimDepartment of Occupational and Environmental Medicine, Kangbuk Samsung Hospital, Sungkyunkwan University School of Medicine, Seoul, Korea.ORCID https://orcid.org/0000-0002-4844-2110
Youshik JeongDepartment of Occupational and Environmental Medicine, Kangbuk Samsung Hospital, Sungkyunkwan University School of Medicine, Seoul, Korea.ORCID https://orcid.org/0000-0001-7940-2405
Jaehong LeeDepartment of Occupational and Environmental Medicine, Kangbuk Samsung Hospital, Sungkyunkwan University School of Medicine, Seoul, Korea.ORCID https://orcid.org/0000-0003-0449-0652
Jinsook JeongDepartment of Occupational and Environmental Medicine, Kangbuk Samsung Hospital, Sungkyunkwan University School of Medicine, Seoul, Korea.ORCID https://orcid.org/0000-0003-2585-9455
Woncheol LeeDepartment of Occupational and Environmental Medicine, Kangbuk Samsung Hospital, Sungkyunkwan University School of Medicine, Seoul, Korea.ORCID https://orcid.org/0000-0001-8535-3988

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Background: Long working hours are known to account for approximately one-third of the total expected work-related diseases, and much interest and research on long working hours have recently been conducted. Additionally, as the prevalence of prediabetes and the high-risk group for diabetes are increasing worldwide, interest in prediabetes is also rising. However, few studies have addressed the development of type 2 diabetes and long working hours in prediabetes. Therefore, the aim of this longitudinal study was to evaluate the relationship between long working hours and the development of diabetes in prediabetes. Methods: We included 14,258 prediabetes participants with hemoglobinA1c (HbA1c) level of 5.7 to 6.4 in the Kangbuk Samsung Cohort Study. According to a self-reported questionnaire, we evaluated weekly working hours, which were categorized into 35-40, 41-52, and > 52 hours. Development of diabetes was defined as an HbA1c level ≥ 6.5%. Hazard ratios (HRs) and 95% confidence intervals (CIs) for the development of diabetes were estimated using Cox proportional hazards analyses with weekly working 35-40 hours as the reference. Results: During a median follow-up of 3.0 years, 776 participants developed diabetes (incidence density, 1.66 per 100 person-years). Multivariable-adjusted HRs of development of diabetes for weekly working > 52 hours compared with working 35-40 hours were 2.00 (95% CI: 1.50-2.67). In subgroup analyses by age (< 40 years old, ≥ 40 years old), sex (men, women), and household income (< 6 million KRW, ≥ 6 million KRW), consistent and significant positive associations were observed in all groups. Conclusions: In our large-scale longitudinal study, long working hours increases the risk of developing diabetes in prediabetes patients.

Indexed as

Diabetes mellitusLongitudinal studiesPrediabetesPrediabetic stateWorking hoursWorkload

Identifiers

PMID35425614
PMCPMC8980739

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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.