Silvia Stringhini1, José Haba-Rubio2, Pedro Marques-Vidal3, Gérard Waeber4, Martin Preisig5, Idris Guessous6, Pascal Bovet7, Peter Vollenweider4, Mehdi Tafti8, Raphael Heinzer2. 1. Institute of Social and Preventive Medicine (IUMSP), Lausanne University Hospital, Lausanne, Switzerland. Electronic address: silvia.stringhini@chuv.ch. 2. Center For Investigation and Research In Sleep, Lausanne University Hospital, Lausanne, Switzerland. 3. Institute of Social and Preventive Medicine (IUMSP), Lausanne University Hospital, Lausanne, Switzerland; Department of Medicine, Internal Medicine, CHUV and Faculty of Biology and Medicine, Lausanne, Switzerland. 4. Department of Medicine, Internal Medicine, CHUV and Faculty of Biology and Medicine, Lausanne, Switzerland. 5. Department of Psychiatry, Lausanne University Hospital, Lausanne, Switzerland. 6. Institute of Social and Preventive Medicine (IUMSP), Lausanne University Hospital, Lausanne, Switzerland; Unit of Population Epidemiology, Division of Primary Care Medicine, Department of Community Medicine, Primary Care and Emergency Medicine, Geneva University Hospitals, Geneva, Switzerland; Department of Epidemiology, Rollins School of Public Health, Emory University, Atlanta, GA, USA. 7. Institute of Social and Preventive Medicine (IUMSP), Lausanne University Hospital, Lausanne, Switzerland. 8. Center For Investigation and Research In Sleep, Lausanne University Hospital, Lausanne, Switzerland; Centre for Integrative Genomics, Lausanne University, Lausanne, Switzerland.
Abstract
OBJECTIVE: To examine the association of socioeconomic status (SES) with subjective and objective sleep disturbances and the role of socio-demographic, behavioural and psychological factors in explaining this association. METHODS: Analyses are based on 3391 participants (53% female, aged 40-81 years) of the follow-up of the CoLaus study (2009-2012), a population-based sample of the city of Lausanne, Switzerland. All participants completed a sleep questionnaire and a sub-sample (N = 1569) underwent polysomnography. RESULTS: Compared with men with a high SES, men with a low SES were more likely to suffer from poor sleep quality [prevalence ratio (PR) for occupational position = 1.68, 95% Confidence Interval (CI): 1.30-2.17], and to have long sleep latency (PR = 4.90, 95%CI: 2.14-11.17), insomnia (PR = 1.47, 95% CI: 1.12-1.93) and short sleep duration (PR = 3.03, 95% CI: 1.78-5.18). The same pattern was observed among women (PR = 1.29 for sleep quality, 2.34 for sleep latency, 2.01 for daytime sleepiness, 3.16 for sleep duration, 95%CIs ranging from 1.00 to 7.51). Use of sleep medications was not patterned by SES. SES differences in sleep disturbances were only marginally attenuated by adjustment for other socio-demographic, behavioural and psychological factors. Results from polysomnography confirmed poorer sleep patterns among participants with low SES (p <0.05 for sleep efficiency/stage shifts), but no SES differences were found for sleep duration. CONCLUSIONS: In this population-based sample, low SES was strongly associated with sleep disturbances, independently of socio-demographic, behavioural, and psychological factors. Further research should establish the extent to which social differences in sleep contribute to socioeconomic differences in health outcomes.
OBJECTIVE: To examine the association of socioeconomic status (SES) with subjective and objective sleep disturbances and the role of socio-demographic, behavioural and psychological factors in explaining this association. METHODS: Analyses are based on 3391 participants (53% female, aged 40-81 years) of the follow-up of the CoLaus study (2009-2012), a population-based sample of the city of Lausanne, Switzerland. All participants completed a sleep questionnaire and a sub-sample (N = 1569) underwent polysomnography. RESULTS: Compared with men with a high SES, men with a low SES were more likely to suffer from poor sleep quality [prevalence ratio (PR) for occupational position = 1.68, 95% Confidence Interval (CI): 1.30-2.17], and to have long sleep latency (PR = 4.90, 95%CI: 2.14-11.17), insomnia (PR = 1.47, 95% CI: 1.12-1.93) and short sleep duration (PR = 3.03, 95% CI: 1.78-5.18). The same pattern was observed among women (PR = 1.29 for sleep quality, 2.34 for sleep latency, 2.01 for daytime sleepiness, 3.16 for sleep duration, 95%CIs ranging from 1.00 to 7.51). Use of sleep medications was not patterned by SES. SES differences in sleep disturbances were only marginally attenuated by adjustment for other socio-demographic, behavioural and psychological factors. Results from polysomnography confirmed poorer sleep patterns among participants with low SES (p <0.05 for sleep efficiency/stage shifts), but no SES differences were found for sleep duration. CONCLUSIONS: In this population-based sample, low SES was strongly associated with sleep disturbances, independently of socio-demographic, behavioural, and psychological factors. Further research should establish the extent to which social differences in sleep contribute to socioeconomic differences in health outcomes.
Authors: Nato Darchia; Nikoloz Oniani; Irine Sakhelashvili; Mariam Supatashvili; Tamar Basishvili; Marine Eliozishvili; Lia Maisuradze; Katerina Cervena Journal: Int J Environ Res Public Health Date: 2018-07-26 Impact factor: 3.390
Authors: Neha A John-Henderson; Benjamin Oosterhoff; Brad Hall; Lester Johnson; Mary Ellen Lafromboise; Melveena Malatare; Emily Salois; Jason R Carter Journal: Sleep Med Date: 2021-07-03 Impact factor: 4.842
Authors: Dusan Petrovic; José Haba-Rubio; Carlos de Mestral Vargas; Michelle Kelly-Irving; Paolo Vineis; Mika Kivimäki; Solja Nyberg; Martina Gandini; Murielle Bochud; Peter Vollenweider; Angelo d'Errico; Henrique Barros; Silvia Fraga; Marcel Goldberg; Marie Zins; Andrew Steptoe; Cyrille Delpierre; Raphael Heinzer; Cristian Carmeli; Marc Chadeau-Hyam; Silvia Stringhini Journal: Cardiovasc Res Date: 2020-07-01 Impact factor: 10.787