Table 1.
Studies evaluating association between occupational exposure and prostate cancer.
| Author (Year) | Country | Study Size | Occupation | Exposure | Assessment Technique | Adjustment Level | Effect Estimate OR 95%: CI Inf–CI Sup |
|
|---|---|---|---|---|---|---|---|---|
| Cases | Control | |||||||
| Blanc-Lapierre et al. (2017)a [36] | Canada | 328 | 400 | Various | Perceived stress at work | Questionnaire and interviews | Age, ethnicity, education level, family income, respondent status, and site-specific non-occupational and occupational covariates | 1.26 (0.95–1.68) |
| Blanc-Lapierre et al. (2017)b [37] | Canada | 1.933 | 1.994 | Various | Perceived stress at work before age 65 | Questionnaire and interviews | Age, ancestry, first-degree family history of PCa, family income, education, marital status, body mass index, type 2 diabetes, depression treated with medication, alcohol consumption, smoking, physical activity at work, and frequency of fruit and vegetable intake | 1.12 (1.04–1.20) |
| Blanc-Lapierre et al. (2018) [38] | Canada | 1920 | 1989 | Various | Benzene, toluene, xylene (BTX), and styrene | Canadian occupational classification | Age, ancestry, first-degree family history of PCa, household income, education, body mass index, type 2 diabetes, alcohol consumption, smoking, and physical activity at work | BTX 1.27 (1.05–1.35) Styrene 1.19 (0.74–1.91) |
| Doolan et al. (2014) [39] | Australia | 1.436 | 1.436 | Various | Physical activity at work | Questionnaire | Age, family history, and SEIFA index of economic resources | 1.15 (0.95–1.40) |
| Lee et al. (2020) [40] | U.S.A. | 1.119 | 63.912 | Firefighters | Firefighting | Firefighter registry | Age at cancer diagnosis | 1.36 (1.27–1.46) |
| Papantoniou et al. (2015) [25] | Spain | 1.095 | 1.388 | Various | Night shift work (NSW) | Nested data from the MCC-Spain study | Age, center, educational level, family history of prostate cancer, physical activity over the past decade, smoking status, past sun exposure, and daily meat consumption | Ever NSW 1.14 (0.94–1.37) Permanent NSW 1.10 (0.85–1.43) Rotating NSW 1.16 (0.95–1.46) |
| Peremiquel-Trillas et al. (2019) [41] | Spain | 1.095 | 1.480 | Various | Alkylphenolic compounds | Job exposure matrix (JEM) | Age, region, education level, BMI, smoking, alcohol consumption, occupational shift, exposure to pesticides, and exposure to solvents | 1.09 (0.89–1.33) |
| Peters et al. (2016) [42] | Canada | 1.638 | 1.697 | Outdoor workers | Solar ultraviolet radiation | Job exposure matrix (JEM) | Relationship status, smoking, education, and fruit and vegetable consumption | 0.68 (0.51–0.92) |
| Sharma et al. (2015) [43] | Canada | 114 | 2.824 | Farming job | Farm risk | Questionnarie | Residence and family history of cancer | Farming job 1.43 (0.70–2.92) Farm residence 1.86 (1.07–3.25) Insecticide 1.31 (0.55–3.15) Fungicides 0.98 (0.26–3.63) Both pesticides 2.23 (1.15–4.33) Radiation 1.97 (1.04–3.74) |
| Tsai et al. (2015) [44] | U.S.A. | 1.397 | 48.825 | Firefighters | Firefighting | Firefighter registry | Age at cancer diagnosis | 1.45 (1.25–1.69) |
| Wendeu-Foyet et al. (2018) [45] | France | 818 | 875 | Various | Night shift work (NSW) | Questionnaire and interviews | Age, family history of prostate cancer, race, and education level | Evening chronotype 1.83 (1.05–3.19) 20 yr permanent NSW 1.76 (1.13–2.75) >10 h NSW 4.64 (1.78–12.13) ≥6 consecutive nights 2.43 (1.32–4.47) |