Objectives Night shift work has been associated with higher breast cancer risk. It has been proposed that night shift workers experience light-induced reduction in melatonin production. Melatonin has direct oncostatic properties and a potential interplay with reproductive hormones. In this cross-sectional study the hypothesis was that night shift workers produce less melatonin and more estrogens and androgens compared to day workers. Changes in the rhythm of hormone production under different individual light exposures were evaluated.
Methods 75 permanent night workers and 42 day workers of both sexes, aged 22–64 years, were recruited from 4 companies in Barcelona, Spain. Levels of 6-sulfatoxymelatonin (melatonin metabolite) and 27 steroid metabolites were measured in urine samples collected from all voids over 24-hours on a working day by all participants. Simultaneously participants wore a data logger that continuously recorded their light exposure. Socio-demographic, occupation and lifestyle information was collected for each participant by interview. Cosinor analysis was performed for 6-sulfatoxymelatonin in every individual to evaluate their circadian rhythm estimating the mesor (midpoint in the full-range), amplitude (difference of the peak value to the mesor) and peak time of production. Geometric means were calculated for each parameter in night and day workers.
Results Sociodemographic and lifestyle characteristics of day and night shift groups were not significantly different. 6-sulfatoxymelatonin production was significantly lower in night compared to day workers ( mesor 10.9 vs 14.2 ng/mg creatinine respectively; amplitude 11.5 vs 18.3 ng/ml creatinine) and peak time was later in night shift workers (6:00 am vs 3:48 am). Mean oestrogen and androgen levels tended to be higher among night workers but differences were not significant.
Conclusions This study indicates potential differences in melatonin and steroid profiles between night and day workers. Results from hormone levels in relation to personal light exposure using nonlinear mixed models will be presented.
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