Breast cancer risk by occupation and industry in women and men: Results from the Occupational Disease Surveillance System (ODSS)

Am J Ind Med. 2019 Mar;62(3):205-211. doi: 10.1002/ajim.22942. Epub 2019 Jan 15.

Abstract

Background: The recently established Occupational Disease Surveillance System (ODSS) was used to examine breast cancer risk in women and men by occupation and industry.

Methods: Ontario workers in the ODSS cohort (1983-2016) were followed up for breast cancer diagnosis through the Ontario Cancer Registry. Cox-proportional hazard models were used to calculate age-adjusted hazard ratios (HRs) and 95% confidence intervals (CIs).

Results: A total of 17 865 and 492 cases were identified in working women (W) and men (M), respectively. Elevated risks were observed in management (W: HR = 1.54, 95% CI = 1.40-1.70; M: HR = 2.79, 95% CI = 1.44-5.39), administrative/clerical (W: HR = 1.16, 95% CI = 1.11-1.21; M: HR = 1.45, 95% CI = 1.06-1.99), and teaching (W: HR = 1.54, 95% CI = 1.44-1.63; M: HR = 3.00, 95% CI = 1.49-6.03). Other elevated risks were observed in nursing/health, social sciences, and janitor/cleaning services for both genders.

Conclusions: Common occupational associations in both genders warrant investigation into job-related risk factors, such as sedentary behavior, shift work, ionizing radiation, and chemical exposures.

Keywords: breast cancer; cohort; male breast cancer; occupation; surveillance.

Publication types

  • Research Support, Non-U.S. Gov't

MeSH terms

  • Administrative Personnel / statistics & numerical data
  • Breast Neoplasms / epidemiology*
  • Breast Neoplasms, Male / epidemiology
  • Education / statistics & numerical data
  • Female
  • Housekeeping / statistics & numerical data
  • Humans
  • Industry / statistics & numerical data*
  • Male
  • Nursing / statistics & numerical data
  • Occupational Diseases / epidemiology*
  • Occupations / statistics & numerical data*
  • Ontario / epidemiology
  • Population Surveillance*
  • Registries
  • Risk Assessment
  • Social Sciences / statistics & numerical data