Circadian epidemiology: Structuring circadian causes of disease and practical implications

ABSTRACT

That disruptions of the body’s internal clockwork can lead to negative health consequences, including cancer, is a plausible hypothesis. Yet, despite strong mechanistic and animal support, the International Agency for Research on Cancer (IARC) experts considered epidemiological evidence as limited regarding the carcinogenicity of “shift-work involving circadian disruption” (2007) and “night shift work” (2019). We use directed acyclic graphs (DAGs) to outline a concept of circadian causes that discloses challenges when choosing appropriate exposure variables. On this basis, we propose to move beyond shift-work alone as a direct cause of disease. Instead, quantifying chronodisruption as individual doses can lead to interpretable circadian epidemiology. The hypothesis is that doses of chronodisruption cause disrupted circadian organisation by leading to desynchronization of circadian rhythms. Chronodisruption can be conceptualized as the split physiological nexus of internal and external times. Biological (or internal) night – an individual’s intrinsically favoured sleep time window – could be the backbone of circadian epidemiology. In practice, individual doses that cause disrupted circadian organisation are derived from the intersection of time intervals of being awake and an individual’s biological night. After numerous studies counted work shifts, chronobiology may now advance circadian epidemiology with more specific dose estimation – albeit with greater challenges in measurement (time-dependent individual data) and analysis (time-dependent confounding).

KEYWORDS:

• Causes
• circadian epidemiology
• shift-work
• sleep
• chronodisruption
• adaptation
• entrainment
• dose
• chronotype

Acknowledgments

The authors thank Philip Lewis, University of Cologne, and Charles Poole, University of North Carolina at Chapel Hill, for their insightful discussions regarding facets of chronobiology and epidemiology, respectively. TCE acknowledges stimulating working conditions as a visiting scholar at the UC Berkeley in 2023.

Disclosure statement

No potential conflict of interest was reported by the authors.

Author contributions

TCE: conceptualization, regarding chronobiology and epidemiology: writing, reviewing, and editing;

PM: conceptualization, regarding epidemiology and chronobiology: writing, reviewing, and editing.

Notes

1. We use “Awake” instead of “Sleep” because of the following considerations. The final endpoint of all DAGs is disease. With increasing dose, the risk of disease should increase. Accordingly, we define dose as the length of intersection of being awake and biologic night. If we used length of intersection of sleep and biologic night to define the dose, we would get a negative association between dose and disease; i.e. as dose increases, risk of disease will decrease. This would be unnecessarily confusing.

Additional information

Funding

This work was not supported by any funding.