Shift work tolerance

• Published in: Occupational medicine (Oxford) Vol. 71; no. 9; pp. 404 - 413
• Main Authors: Degenfellner, J, Schernhammer, E
• Format: Journal Article
• Language: English
• Published: UK Oxford University Press 24-12-2021
• Subjects: Adaptation, Psychological; Genome-Wide Association Study; Humans; Occupational Stress; Resilience, Psychological; Shift Work Schedule - adverse effects; shift work; genetics; Clock genes; in-depth review; personality traits; tolerance
• ISSN: 0962-7480; 1471-8405
• DOI: 10.1093/occmed/kqab138

Abstract
Background
Shift work is widespread due to 24-h work in many occupations. Understanding differences in individual shift work tolerance (SWT) can help develop coping strategies for shift workers.
Aims
This in-depth qualitative review elucidates the architecture of SWT, providing an overview of the research advances in the last decade (2011–2021).
Methods
We searched Google Scholar, PubMed and Medline for different word combinations concerning SWT. Genome-wide association studies (GWAS) for the potential genetic basis of SWT were additionally searched in GWAS Central and GWAS Catalogue.
Results
Eleven new studies were published since 2011, with the proportion of longitudinal studies on SWT having more than doubled in the past decade. They consolidate prior findings (e.g. hardiness most consistently associated with SWT) and discovered additional aspects of SWT like resistance to change and job stress. The 15 large-scale GWAS identified, most of which using UK Biobank (UKB) and 23andMe data, involved mapped genes showing overlap especially within analysis of the same phenotype (e.g. PER2/3 for morningness, PAX8 for sleep duration and LINGO1 for neuroticism). Individual GWAS for additional traits such as resilience have also been published though assessments of gene overlap are not yet possible.
Conclusions
Progress regarding longitudinal studies on SWT has been made though a more consistent definition of SWT remains crucial for future research. Non-genetic studies on SWT suggest several important traits and factors; many of which have now also been explored using GWAS. Such evidence could serve as basis for individualized risk prediction and disease prevention approaches for night-shift workers.