A Population-Based Study on Nighttime Road Traffic Noise and Insomnia

Abstract Study Objectives: The aims of the present study were to investigate how nighttime road traffic noise relates to self-reported symptoms of insomnia and sleep medication use. Methods: We used questionnaire data from the population-based study Health and Environment in Oslo (HELMILO) (2009–201...

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Published in:Sleep (New York, N.Y.) Vol. 40; no. 2
Main Authors: Evandt, Jorunn, Oftedal, Bente, Hjertager Krog, Norun, Nafstad, Per, Schwarze, Per E., Marit Aasvang, Gunn
Format: Journal Article
Language:English
Published: US Oxford University Press 01.02.2017
Subjects:
Adult
Aged
Aged, 80 and over
Darkness
Environment
Female
Humans
Hypnotics and Sedatives - therapeutic use
Insomnia
Logistic Models
Male
Middle Aged
Noise pollution
Noise, Transportation - adverse effects
Norway
Odds Ratio
Population
Population-based studies
Self Report
Sleep
Sleep Aids, Pharmaceutical - therapeutic use
Sleep Initiation and Maintenance Disorders - drug therapy
Sleep Initiation and Maintenance Disorders - etiology
Surveys and Questionnaires
Traffic
sleep disturbance
sleep medication use
population-based study
directed acyclic graph
traffic noise
environmental epidemiology
insomnia
ISSN:0161-8105, 1550-9109, 1550-9109
Online Access:Get full text
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Summary:Abstract Study Objectives: The aims of the present study were to investigate how nighttime road traffic noise relates to self-reported symptoms of insomnia and sleep medication use. Methods: We used questionnaire data from the population-based study Health and Environment in Oslo (HELMILO) (2009–2010; n = 13019). The insomnia symptoms difficulties falling asleep, awakenings during the night, and waking up too early in the morning as well as self-reported sleep medication use were included as outcomes. Modeled noise levels (Lnight) were assigned to each participant’s home address. For selecting covariates to the statistical model, we used a directed acyclic graph. The associations between noise and sleep were analyzed using logistic regression models. Results: After adjustment for potential confounders, we found an odds ratio (OR) of 1.05 (95% confidence interval [CI]: 1.01–1.09) for the association between traffic noise and difficulties falling asleep, in the total study population. For the association between traffic noise and awakenings during the night, the OR was 1.04 (95% CI: 1.00–1.08) and for waking up too early, the OR was 1.06 (95% CI: 1.02–1.11). The effect estimates are given per 5-dB increase in traffic noise level (Lnight). Self-reported sleep medication use was not statistically significantly associated with traffic noise exposure. Conclusions: In an adult population from Oslo, traffic noise was associated with difficulties falling asleep and waking up too early. These findings indicate that sleep quantity may be compromised for individuals living in areas highly exposed to nighttime traffic noise.
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ISSN:0161-8105
1550-9109
1550-9109
DOI:10.1093/sleep/zsw055