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Background: Many studies have demonstrated adverse effects of exposure to aircraft noise on health. Possible biological pathways for these effects include hormonal disturbances. Few studies deal with aircraft noise effects on saliva cortisol in adults, and results are inconsistent. Objective: We aimed to assess the effects of aircraft noise exposure on saliva cortisol levels and its variation in people living near airports. Methods: This study focused on the 1300 residents included in the HYENA and DEBATS cross-sectional studies, with complete information on cortisol sampling. All the participants followed a similar procedure aiming to collect both a morning and an evening saliva cortisol samples. Socioeconomic and lifestyle information were obtained during a face-to-face interview. Outdoor aircraft noise exposure was estimated for each participant's home address. Associations between aircraft noise exposure and cortisol outcomes were investigated a priori for male and female separately, using linear regression models adjusted for relevant confounders. Different approaches were used to characterize cortisol levels, such as morning and evening cortisol concentrations and the absolute and relative variations between morning and evening levels. Results: Statistically significant increases of evening cortisol levels were shown in women with a 10-dB(A) increase in aircraft noise exposure in terms of LA(eq, 16h) (exp(beta) = 1.08; CI95% = 1.00-1.16), L-den (exp(beta) = 1.09; CI95% = 1.01-1.18), L-night (exp(beta) = 1.11; CI95% = 1.02-1.20). A statistically significant association was also found in women between a 10-dB(A) increase in terms of L-night and the absolute variation per hour (exp(beta) = 0.90; CI95% = 0.80-1.00). Statistically significant decreases in relative variation per hour were also evidenced in women, with stronger effects with the L-night (exp(beta) = 0.89; CI95% = 0.83-0.96) than with other noise indicators. The morning cortisol levels were unchanged w

INTRODUCTION: This study aimed to determine the sleepiness-related factors associated with road traffic accidents. METHODS: A population based case-control study was conducted in 2 French agglomerations. 272 road accident cases hospitalized in emergency units and 272 control drivers matched by time of day and randomly stopped by police forces were included in the study. Odds ratios were calculated for the risk of road traffic accidents. RESULTS: As expected, the main predictive factor for road traffic accidents was having a sleep episode at the wheel just before the accident (OR 9.97, CI 95%: 1.57-63.50, p<0.05). The increased risk of traffic accidents was 3.35 times higher in subjects who reported very poor quality sleep during the last 3 months (CI 95%: 1.30-8.63, p<0.05), 1.69 times higher in subjects reporting sleeping 6 hours or fewer per night during the last 3 months (CI 95%: 1.00-2.85, p<0.05), 2.02 times higher in subjects reporting symptoms of anxiety or nervousness in the previous day (CI 95%: 1.03-3.97, p<0.05), and 3.29 times higher in subjects reporting taking more than 2 medications in the last 24 h (CI 95%: 1.14-9.44, p<0.05). Chronic daytime sleepiness measured by the Epworth Sleepiness Scale, expressed heavy snoring and nocturnal leg movements did not explain traffic accidents. CONCLUSION: Physicians should be attentive to complaints of poor sleep quality and quantity, symptoms of anxiety-nervousness and/or drug consumption in regular car drivers.