Abstract
BackgroundNoise has been found to be associated with endocrine changes and cardiovascular disease. Increased cortisol levels and chronic sleep problems due to noise may increase the risk of obesity. ObjectivesWe investigated the relationship between road traffic noise and obesity markers. Furthermore, we explored the modifying role of noise sensitivity, noise annoyance, and sleep disturbances. MethodsWe used data from a population-based study, HUBRO (N=15,085), and its follow-up study HELMILO (N=8410) conducted in Oslo, Norway. Measurements were used to define body mass index (BMI), waist circumference (WC), waist–hip ratio (WHR), and these binary outcomes: BMI≥30kg/m2, WC≥102cm (men)/88cm (women), and WHR≥0.90 (men)/0.85 (women). Modelled levels of road traffic noise (Lden) were assigned to each participant’s home address. Linear and logistic regression models were used to examine the associations. ResultsThe results indicated no significant associations between road traffic noise and obesity markers in the total populations. However, in highly noise sensitive women (n=1106) a 10dB increase in noise level was associated with a slope (=beta) of 1.02 (95% confidence interval (CI): 1.01, 1.03) for BMI, 1.01 (CI: 1.00, 1.02) for WC, and an odds ratio (OR) of 1.24 (CI: 1.01, 1.53) for WHR ≥0.85. The associations appeared weaker in highly noise sensitive men. We found no effect modification of noise annoyance or sleep disturbances. In a sub-population with bedroom facing a road, the associations increased in men (e.g. an OR of 1.25 (CI: 0.88, 1.78) for BMI ≥30kg/m2), but not in women. Among long-term residents the associations increased for BMI ≥30kg/m2 (OR of 1.07 (CI: 0.93, 1.24) in men and 1.10 (CI: 0.97, 1.26) in women), but not for the other outcomes. ConclusionIn an adult urban Scandinavian population, road traffic noise was positively associated with obesity markers among highly noise sensitive women. The associations appeared stronger among men with bedroom facing a street, representing a population with more accurately assigned exposure.
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