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® software. Total sleep time was evaluated using declared bedtime and time of awakening and was analyzed as a quantitative variable and as a qualitative variable. 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.

Influence of Socio-Demographic, Occupational and Lifestyle Variables on Sleep Time

Cocco, Pierluigi;Lecca, Rosamaria;Puligheddu, Monica;Figorilli, Michela;
2025-01-01

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® software. Total sleep time was evaluated using declared bedtime and time of awakening and was analyzed as a quantitative variable and as a qualitative variable. 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.
2025
mental health
occupational variables
sociodemographic variables
total sleep time
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11584/473027
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