ArticleNature and science of sleep2025
Influence of Socio-Demographic, Occupational and Lifestyle Variables on Sleep Time.
Article in Nature and science of sleep, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.
What it found
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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.
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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.
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Who cites it
2 citing papers in PubMed.
- From plate to pillow, and vice versa: diet-sleep dynamics in free-living adults with obesity.European journal of nutrition · 2026Trial
- Validation of visual analogue scales to assess occupational stress compared to the Karasek questionnaire: A cross sectional study.PloS one · 2026Observational
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Authors and funding
20 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Background: Socio-demographic, occupational and lifestyle variables influence total sleep time. Therefore, we aimed to evaluate the influence of those variables on sleep time, and to study risk factors of being a short sleeper. Methods: The COVISTRESS international study is an online questionnaire using the secure REDCap Results: We included 549 respondents to the questionnaire, divided into 10-year age groups ranging from <30yo to ≥60yo. The mean quantity of sleep was 7.11±1.43 hours per night. Factors that reduce total sleep time were age (coefficient -0.19, 95CI -0.33 to 0.06), being an employee (-0.46, -0.85 to -0.06), working time (-0.18, -0.31 to 0.05), smoking ≥5 cigarettes/day (-0.5, -0.95 to -0.20), high stress at work (-0.64, -0.96 to -0.32) and at home (-0.66, -0.97 to -0.35). Being a student (0.61, 0.02 to 1.19), working less than 25h per week (0.57, 0.17 to 0.97) and telework (0.46, 0.02 to 0.89) increased total sleep time. The risk factors of being a short sleeper were age (odds ratio 1.27, 95CI 1.07 to 1.51), being an employee (2.58, 1.36 to 4.89), smoking ≥5 cigarettes/day (2.73, 1.54 to 4.84) and a high level of stress at work (2.64, 1.45 to 4.82) and at home (3.89, 2.25 to 6.63). Physical activity ≥2.5 hours/week tended to decrease the risk of being a short sleeper by 35%. Conclusion: We demonstrated the concomitant impact of sociodemographic, occupational and lifestyle behavior on sleep, which may help to build efficient preventive strategy.
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