Occupation and mammographic density: A population-based study (DDM-Occup)

• Published in: Environmental research 2017-11, Vol.159, p.355-361
• Main Authors: García-Pérez, Javier, Pollán, Marina, Pérez-Gómez, Beatriz, González-Sánchez, Mario, Cortés Barragán, Rosa Ana, Maqueda Blasco, Jerónimo, González-Galarzo, María Carmen, Alba, Miguel Ángel, van der Haar, Rudolf, Casas, Silvia, Vicente, Cándida, Medina, Pilar, Ederra, María, Santamariña, Carmen, Moreno, María Pilar, Casanova, Francisco, Pedraz-Pingarrón, Carmen, Moreo, Pilar, Ascunce, Nieves, García, Montse, Salas-Trejo, Dolores, Sánchez-Contador, Carmen, Llobet, Rafael, Lope, Virginia
• Format: Article
• Language: English
• Subjects: Aged; Breast cancer; Breast Density; Cross-Sectional Studies; DDM-Occup; Female; Humans; Linear Models; Mammographic density; Mammography; Middle Aged; Nurses; Occupation; Occupations - classification; School teachers; Spain
• ISSN: 0013-9351; 1096-0953
• DOI: 10.1016/j.envres.2017.08.028

High mammographic density is one of the main risk factors for breast cancer. Although several occupations have been associated with breast cancer, there are no previous occupational studies exploring the association with mammographic density. Our objective was to identify occupations associated with high mammographic density in Spanish female workers. We conducted a population-based cross-sectional study of occupational determinants of high mammographic density in Spain, based on 1476 women, aged 45–68 years, recruited from seven screening centers within the Spanish Breast Cancer Screening Program network. Reproductive, family, personal, and occupational history data were collected. The latest occupation of each woman was collected and coded according to the 1994 National Classification of Occupations. Mammographic density was assessed from the cranio-caudal mammogram of the left breast using a semi-automated computer-assisted tool. Association between mammographic density and occupation was evaluated by using mixed linear regression models, using log-transformed percentage of mammographic density as dependent variable. Models were adjusted for age, body mass index, menopausal status, parity, smoking, alcohol intake, educational level, type of mammography, first-degree relative with breast cancer, and hormonal replacement therapy use. Screening center and professional reader were included as random effects terms. Mammographic density was higher, although non-statistically significant, among secondary school teachers (eβ = 1.41; 95%CI = 0.98–2.03) and nurses (eβ = 1.23; 95%CI = 0.96–1.59), whereas workers engaged in the care of people (eβ = 0.81; 95%CI = 0.66–1.00) and housewives (eβ = 0.87; 95%CI = 0.79–0.95) showed an inverse association with mammographic density. A positive trend for every 5 years working as secondary school teachers was also detected (p-value = 0.035). Nurses and secondary school teachers were the occupations with the highest mammographic density in our study, showing the latter a positive trend with duration of employment. Future studies are necessary to confirm if these results are due to chance or are the result of a true association whose causal hypothesis is, for the moment, unknown. •Association between occupation and mammographic density in Spain was investigated.•We used mixed linear regression models in a population-based cross-sectional study.•Secondary school teachers and nurses showed the highest mammographic density.•Positi