Cancer
Working conditions, sleep, and the risk of lung cancer Bernadette van der Linden* Bernadette van der Linden Drinbardha Elshani Arnaud Chiolero Stéphane Cullati
BACKGROUND Lung cancer is important in the working-age population in terms of incidence. Within a life course and eco-social perspective, smoking has been identified as a major cause, but the effects of other factors, including of occupation, are currently not well known. Work occupies large parts of life and working conditions might be a cause of cancer through its impact on stress or sleep disturbances causing suppressed immune function and melatonin dysregulation. Our aim was therefore to assess the effects of working conditions and sleep on lung cancer.
METHODS Data from the UK Biobank were used, a large-scale cohort study including half a million people between 40 and 69 years old at baseline and living in the UK. Incident cancer diagnoses were verified through the linkage with cancer registries. Logistic regression was used to estimate the association of working conditions and sleep with lung cancer risk, adjusted for potential confounders. Further analyses, including of the mediating effect of sleep on the relationship between working conditions and cancer, are ongoing and will be presented.
RESULTS 3923 lung cancers were diagnosed during 15 years of follow-up. Preliminary analyses showed that individuals who worked between 16-30 hours a week and who worked in jobs that never or rarely involved heavy manual or physical work had a lower risk of lung cancer (odds ratio (OR) = 0.78, 95% CI 0.62, 0.98; OR = 0,75, 95% CI 0.59, 0.95, respectively). A longer (OR = 1.64, 95% CI 1.04, 2.59) as well as a shorter (OR = 1.15, 95% CI 1.01, 1.31) than recommended sleep duration and having an evening chronotype (OR = 1.38, 95% CI 1.10, 1.72) were associated with a higher risk of lung cancer.
CONCLUSION Working conditions and sleep characteristics are associated with lung cancer risks. It is important to further understand and study the potential mechanisms behind these associations to help identify occupations and populations at higher risk as well as intervention targets.