Dun · Frontiers in oncology 2020 · systematic review and meta-analysis of observational studies · n=57 studies (8,477,849 participants)

Association Between Night-Shift Work and Cancer Risk: Updated Systematic Review and Meta-Analysis.

Cited 95 times in the scientific literature.

Level 3 - non-randomized controlled study

Systematic review and meta-analysis of observational studies

PubMed 32656086 · doi:10.3389/fonc.2020.01006 · record verified 2026-08-26

What was done

The authors conducted a PRISMA-compliant systematic review and meta-analysis (registered in PROSPERO) searching Embase, PubMed, and Web of Science through May 31, 2019. Random-effects models (DerSimonian-Laird method) and dose-response analyses were used to assess the association between night-shift work and the risk of various cancers across 57 observational studies encompassing 8,477,849 participants (mean age 55 years; 2,560,886 men, 4,220,154 women, and 1,696,809 sex unspecified).

What was found

Pooled estimates showed no significant association between night-shift work and the risk of: - Breast cancer: OR 1.009 (95% CI 0.984–1.033) - Prostate cancer: OR 1.027 (95% CI 0.982–1.071) - Ovarian cancer: OR 1.027 (95% CI 0.942–1.113) - Pancreatic cancer: OR 1.007 (95% CI 0.910–1.104) - Colorectal cancer: OR 1.016 (95% CI 0.964–1.068) - Non-Hodgkin lymphoma: OR 1.046 (95% CI 0.994–1.098) - Stomach cancer: OR 1.064 (95% CI 0.971–1.157) Night-shift work was associated with a small statistically significant risk reduction for: - Lung cancer: OR 0.949 (95% CI 0.903–0.996) - Skin cancer: OR 0.916 (95% CI 0.879–0.953) Dose-response analysis showed cancer risk was not significantly elevated with increasing duration or intensity of night-shift exposure.

Why it matters

This updated meta-analysis of over 8 million participants indicates that ever-exposure to night-shift work does not meaningfully increase the risk of common cancers, contradicting earlier concerns regarding circadian disruption and broad cancer risk.

Limits

All included data were observational, making results vulnerable to residual confounding (such as lifestyle factors, socioeconomic status, and smoking) and healthy-worker survivor bias. The abstract does not provide details on between-study heterogeneity, variations in shift definitions across studies, or individual chronotype interactions.

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