Evidence map›Paper›PMID 36691907›Full record

ArticleChronobiology international2023

Distribution of working hour characteristics by race, age, gender, and shift schedule among U.S. manufacturing workers.

Jacqueline M Ferguson, Patrick T Bradshaw, Ellen A Eisen, David Rehkopf, Mark R Cullen, Sadie Costello

Open access · hybridAbstract read
PubMed Full text at PMC Publisher
In one paragraph

Article in Chronobiology international, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 14 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
14citing papers in PubMed, 1 pooled it
3.8field-weighted citation impact, top 7% 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

14 citing papers in PubMed, 1 synthesis or guideline pooled it, 15 citations in OpenAlex.

  1. Pooled it
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  14. Prevalence of night work in the Brazilian employed population.Revista brasileira de medicina do trabalho : publicacao oficial da Associacao Nacional de Medicina do Trabalho-ANAMT
    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

6 authors at 2 institutions in 1 country.

Jacqueline M FergusonDivision of Environmental Health Sciences, School of Public Health, University of California Berkeley, Berkeley, California, USA.ORCID 0000-0003-0027-387X
Patrick T BradshawDivision of Epidemiology and Biostatistics, School of Public Health, University of California Berkeley, Berkeley, California, USA.ORCID 0000-0001-7761-3129
Ellen A EisenDivision of Environmental Health Sciences, School of Public Health, University of California Berkeley, Berkeley, California, USA.ORCID 0000-0002-5114-5264
David RehkopfDepartment of Epidemiology and Population Health, Stanford University, Stanford, California, USA.ORCID 0000-0002-7597-6513
Mark R CullenDepartment of Epidemiology and Population Health, Stanford University, Stanford, California, USA.ORCID 0000-0001-7996-1864
Sadie CostelloDivision of Environmental Health Sciences, School of Public Health, University of California Berkeley, Berkeley, California, USA.ORCID 0000-0001-6181-5666
University of California, Berkeley · USStanford University · US

Funding

Targeted Research Training CoreT42OH008429 · OH · UNIVERSITY OF CALIFORNIA BERKELEY · PI HARRIS ADAMSON, CARISA · 2005 to 2024
$30.0M
Risk factors for Alzheimer's Disease and Related Dementia: Evidence from a Large Occupational CohortR01AG026291 · NIA · YALE UNIVERSITY · PI CANTLEY, LINDA, EISEN, ELLEN AURA · 2006 to 2021
$12.9M
Occupational Exposure to PM2.5 and Cardiovascular Disease(CVD)R01OH009939 · OH · STANFORD UNIVERSITY · PI CANTLEY, LINDA, CULLEN, MARK RICHARD · 2011 to 2019
$4.7M
ACL HHS R01OH009939ACL HHS T42OH008429NIA NIH HHS R01 AG026291NIOSH CDC HHS R01 OH009939NIOSH CDC HHS T42 OH008429
6 · The paper itself

Abstract

Shift work is a common occupational exposure, however, few studies have examined aspects of shift work beyond night work and long hours, such as rotational patterns or weekend work, which may contribute to poor health through disruption of the body's circadian rhythms. In this manuscript, we calculated the prevalence of working hour characteristics using algorithms for type (e.g., day), duration, intensity, rotational direction, and social aspects (e.g., weekend work) in a nationwide cohort of American manufacturing workers (N = 23,044) between 2003 and 2014. Distributions of working hour characteristics were examined by schedules (e.g., permanent day, day/night) and demographics, and were cross-classified in a matrix to examine co-occurrence. Approximately 55% of shifts may cause circadian rhythm disruption as they were non-day shifts or day shifts with a quick return or rotation, or were 13 h or longer. Older workers, female workers, and White workers worked permanent day shifts most often, while workers of color worked more day/night schedules. Night and evening shifts had more frequent shift rotations, quick returns, and longer hours than day shifts. Yet, day shifts, which are presumed to have little negative circadian impact, may cause circadian rhythm disruption as long hours, quick returns and rotations also occurred within day shifts.

Indexed as

Circadian RhythmSleep Disorders, Circadian RhythmFemaleHumansSleepWork Schedule Tolerancecircadian disruptionjoint distributionshift domainsShift workworking time

Identifiers

PMID36691907
PMCPMC10192004
OpenAlexW4317829831

What OpenQuestion holds

Textmetadata
LicenceTDM
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.