O-193 Predictors of night shift work adaptation. (14th March 2023)

• Record Type: Journal Article
• Authors: Harding, Barbara N; Espinosa, Ana; Mata, Maria; Vinyals, Gemma Castaño; Pozo, Oscar J; Kogevinas, Manolis; Papantoniou, Kyriaki
• Is Part Of: Occupational and environmental medicine. Volume 80(2023)Supplement 1
• Page Start: A17
• Page End: A17
• Publication Date: 2023-03-14
• Subjects: Medicine, Industrial -- Periodicals; Environmental health -- Periodicals; 616.980305
• DOI: 10.1136/OEM-2023-EPICOH.41
• Languages: English
• ISSNs: 1351-0711

Abstract

Abstract : Introduction: Individuals adapt differently to night shift work, although which factors predict this adaptation require further study. This study explored individual differences in night shift work adaptation using a central circadian clock biomarker among rotating night shift workers. Materials and Methods: This study included 39 male, rotating shift workers from the automotive industry in Barcelona, Spain, sampled twice at the end of a 3-week night-shift (22:00–06:00 hrs) and 3-week day-shift (06:00–14:00 hrs) rotation. Participants collected all urine voids over 24-hours, wore several sensors, and responded to questionnaires during each shift. Cosinor analysis was performed and acrophase (peak time) of melatonin, was extracted. Adaptation was defined as the difference in the individual acrophase after 3 weeks of night shifts compared to the acrophase after 3 weeks of day shifts. We examined whether the following factors, measured during the night shift, were associated with adaption to night shift work: light intensity, sleep duration, time of sleep onset, number of sleep problems, chronotype, meal frequency, and fast length. We used linear models to examine differences in the melatonin acrophase during the night shift compared to the day shift and report associations using beta coefficients from models. Results: Participants were 38 (±8) years of age. Melatonin peak production time was shifted by a median of 8.9 (IQR 6.8–10.4) hours during the night shift. When examining individual predictors of adaptation, we found that light intensity (coeff 2.13, 95%CI, 0.90–3.35 per lux) and sleep duration (coeff 0.70, 95%CI 0.12–1.28 per hour) were associated with night shift work adaptation. Other factors were not associated with adaptation. Conclusion: Light intensity and sleep duration were associated with night shift work adaptation in a slow backward shift work rotation system. These results can inform light and sleep interventions at the workplace to enhance circadian adaptation of shift workers.