Spatial clusters of daytime sleepiness and association with nighttime noise levels in a Swiss general population (GeoHypnoLaus) |
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Authors: | Stéphane Joost José Haba-Rubio Rebecca Himsl Peter Vollenweider Martin Preisig Gérard Waeber Pedro Marques-Vidal Raphaël Heinzer Idris Guessous |
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Affiliation: | 1. Laboratory of Geographic Information Systems (LASIG), School of Architecture, Civil and Environmental Engineering (ENAC), Ecole Polytechnique Fédérale de Lausanne (EPFL), Lausanne, Switzerland;2. Unit of Population Epidemiology, Division of Primary Care Medicine, Department of Community Medicine, Primary Care and Emergency Medicine, Geneva University Hospitals, Geneva, Switzerland;3. GIRAPH Lab (Geographic information for research and analyses in public health), Switzerland;4. Center for Investigation and Research in Sleep, Lausanne University Hospital (CHUV) and Lausanne University, Lausanne, Switzerland;5. Department of Medicine, Internal Medicine, Lausanne University Hospital (CHUV) and Lausanne University, Lausanne, Switzerland;6. Department for Ambulatory Care and Community Medicine, University of Lausanne, Lausanne, Switzerland;g. Department of Psychiatry, Lausanne University Hospital and Lausanne University, Lausanne, Switzerland |
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Abstract: | IntroductionDaytime sleepiness is highly prevalent in the general adult population and has been linked to an increased risk of workplace and vehicle accidents, lower professional performance and poorer health. Despite the established relationship between noise and daytime sleepiness, little research has explored the individual-level spatial distribution of noise-related sleep disturbances. We assessed the spatial dependence of daytime sleepiness and tested whether clusters of individuals exhibiting higher daytime sleepiness were characterized by higher nocturnal noise levels than other clusters.Design and MethodsPopulation-based cross-sectional study, in the city of Lausanne, Switzerland.Sleepiness was measured using the Epworth Sleepiness Scale (ESS) for 3697 georeferenced individuals from the CoLaus|PsyCoLaus cohort (period?=?2009–2012). We used the sonBASE georeferenced database produced by the Swiss Federal Office for the Environment to characterize nighttime road traffic noise exposure throughout the city. We used the GeoDa software program to calculate the Getis-Ord Gi* statistics for unadjusted and adjusted ESS in order to detect spatial clusters of high and low ESS values. Modeled nighttime noise exposure from road and rail traffic was compared across ESS clusters.ResultsDaytime sleepiness was not randomly distributed and showed a significant spatial dependence. The median nighttime traffic noise exposure was significantly different across the three ESS Getis cluster classes (p?0.001). The mean nighttime noise exposure in the high ESS cluster class was 47.6, dB(A) 5.2?dB(A) higher than in low clusters (p?0.001) and 2.1?dB(A) higher than in the neutral class (p?0.001). These associations were independent of major potential confounders including body mass index and neighborhood income level.ConclusionsClusters of higher daytime sleepiness in adults are associated with higher median nighttime noise levels. The identification of these clusters can guide tailored public health interventions. |
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Keywords: | ESS epworth sleepiness scale FOEN Swiss Federal Office for the Environment GIS geographic information systems LISA Local Indicators of Spatial Association Epworth sleepiness scale Traffic noise exposure Spatial clustering GIS General population |
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