Short communication

Scand J Work Environ Health 2018;44(4):432-435    pdf full text

https://doi.org/10.5271/sjweh.3738 | Published online: 22 May 2018, Issue date: 01 Jul 2018

Night shift work and breast cancer risk: what do the meta-analyses tell us?

by Pahwa M, Labrèche F, Demers PA

Objectives This paper aims to compare results, assess the quality, and discuss the implications of recently published meta-analyses of night shift work and breast cancer risk.

Methods A comprehensive search was conducted for meta-analyses published from 2007–2017 that included at least one pooled effect size (ES) for breast cancer associated with any night shift work exposure metric and were accompanied by a systematic literature review. Pooled ES from each meta-analysis were ascertained with a focus on ever/never exposure associations. Assessments of heterogeneity and publication bias were also extracted. The AMSTAR 2 checklist was used to evaluate quality.

Results Seven meta-analyses, published from 2013–2016, collectively included 30 cohort and case–control studies spanning 1996–2016. Five meta-analyses reported pooled ES for ever/never night shift work exposure; these ranged from 0.99 [95% confidence interval (CI) 0.95–1.03, N=10 cohort studies) to 1.40 (95% CI 1.13–1.73, N=9 high quality studies). Estimates for duration, frequency, and cumulative night shift work exposure were scant and mostly not statistically significant. Meta-analyses of cohort, Asian, and more fully-adjusted studies generally resulted in lower pooled ES than case–control, European, American, or minimally-adjusted studies. Most reported statistically significant between-study heterogeneity. Publication bias was not evident in any of the meta-analyses. Only one meta-analysis was strong in critical quality domains.

Conclusions Fairly consistent elevated pooled ES were found for ever/never night shift work and breast cancer risk, but results for other shift work exposure metrics were inconclusive. Future evaluations of shift work should incorporate high quality meta-analyses that better appraise individual study quality.

This article refers to the following text of the Journal: 2013;39(5):431-447