Evidence map›Paper›PMID 38447994›Full record

ArticleIndustrial health2024

Effect of shift work on excessive daytime sleepiness in female nurses: results from the Japan Nurses' Health Study.

Masakazu Terauchi, Yuki Ideno, Kunihiko Hayashi

Open access · diamondAbstract read
In one paragraph

Article in Industrial health, 2024. 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
2.5field-weighted citation impact, top 12% 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, 5 citations in OpenAlex.

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  3. Review
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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

3 authors at 2 institutions in 1 country.

Masakazu TerauchiDepartment of Women's Health, Tokyo Medical and Dental University, Japan.
Yuki IdenoCenter for Food Science and Wellness, Gunma University, Japan.
Kunihiko HayashiGraduate School of Health Sciences, Gunma University, Japan.
Gunma University · JPTokyo Medical and Dental University · JP

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

We investigated the relationship between shift work and excessive daytime sleepiness (EDS) among participants in the Japan Nurses' Health Study (JNHS). Responses of 9,728 female nurses to the 6th follow-up questionnaire were cross-sectionally analyzed. EDS was defined as an Epworth Sleepiness Scale score ≥11. EDS-associated factors were evaluated using Poisson regression analysis after adjustment for multiple confounders. Of the participants (mean age, 52.2 ± 8.0 yr), 28.7% were engaged in shift work, and the overall prevalence of EDS was 24.6%. EDS-associated factors were investigated separately in women aged <40 yr (n=250), 40-59 yr (n=7,467), and ≥60 yr (n=2,011). Current engagement in shift work (prevalence ratio: 1.92 [95% confidence interval: 1.20-3.06], compared with no experience of shift work) and obesity (2.08 [1.11-3.88] for BMI ≥30 and 1.39 [1.02-1.90] for BMI of 25.0-30.0, compared with BMI of 18.5-25.0) showed an independent association with EDS in women aged ≥60 yr. The effect of shift work on EDS in female nurses differed by age, as shift work and obesity contributed to EDS only in older participants. Shift work should be assigned after full consideration of age, sleep, and health status to minimize medical errors.

Indexed as

Disorders of Excessive SomnolenceNursesShift Work ScheduleAdultAge FactorsBody Mass IndexCross-Sectional StudiesFemaleHumansJapanMiddle AgedObesityPrevalenceRisk FactorsSurveys and QuestionnairesWork Schedule ToleranceExcessive daytime sleepinessFemale nurseMenopauseObesitySleep disturbance

Identifiers

PMID38447994
PMCPMC11292310
OpenAlexW4392446566

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.