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Environ Res. 2017 Nov;159:355-361. doi: 10.1016/j.envres.2017.08.028. Epub 2017 Sep 18.

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

Author information

1
Cancer and Environmental Epidemiology Unit, National Center for Epidemiology, Carlos III Institute of Health, Madrid, Spain; Consortium for Biomedical Research in Epidemiology & Public Health (CIBER Epidemiología y Salud Pública - CIBERESP), Spain. Electronic address: jgarcia@isciii.es.
2
Cancer and Environmental Epidemiology Unit, National Center for Epidemiology, Carlos III Institute of Health, Madrid, Spain; Consortium for Biomedical Research in Epidemiology & Public Health (CIBER Epidemiología y Salud Pública - CIBERESP), Spain. Electronic address: mpollan@isciii.es.
3
Cancer and Environmental Epidemiology Unit, National Center for Epidemiology, Carlos III Institute of Health, Madrid, Spain; Consortium for Biomedical Research in Epidemiology & Public Health (CIBER Epidemiología y Salud Pública - CIBERESP), Spain. Electronic address: bperez@isciii.es.
4
Cancer and Environmental Epidemiology Unit, National Center for Epidemiology, Carlos III Institute of Health, Madrid, Spain; Consortium for Biomedical Research in Epidemiology & Public Health (CIBER Epidemiología y Salud Pública - CIBERESP), Spain. Electronic address: mariogonzalez@isciii.es.
5
Escuela Nacional de Medicina del Trabajo, Carlos III Institute of Health, Madrid, Spain. Electronic address: rcortes@isciii.es.
6
Instituto Nacional de Seguridad e Higiene en el Trabajo, Ministerio de Empleo y Seguridad Social, Madrid, Spain. Electronic address: jmaqueda@insht.meyss.es.
7
Center for Research in Occupational Health (CiSAL), Universitat Pompeu Fabra, Barcelona, Spain. Electronic address: mcarmen.gonzalez@upf.edu.
8
Área de Higiene Industrial, PREMAP Seguridad y Salud S.L.U., Barcelona, Spain. Electronic address: mangel_alba@prevencionfremap.es.
9
Departamento I+D+I, MC Mutual, Barcelona, Spain. Electronic address: rvan@mc-mutual.com.
10
Programa de Detección Precoz de Cáncer de Mama, Dirección General de Salud Pública y Participación, Palma, Spain. Electronic address: scasas@dgsanita.caib.es.
11
Programa de Prevención de Cáncer de Mama, Dirección General de Salud Pública, Valencia, Spain. Electronic address: vicente_can@gva.es.
12
Programa de Prevención y Control del Cáncer, Unidad de Biomarcadores y Susceptibilidad, Institut d'Investigació Biomèdica de Bellvitge (IDIBELL), Institut Català d'Oncologia, L'Hospitalet de Llobregat, Spain. Electronic address: pmedina@iconcologia.net.
13
Consortium for Biomedical Research in Epidemiology & Public Health (CIBER Epidemiología y Salud Pública - CIBERESP), Spain; Navarra Breast Cancer Screening Program, Public Health Institute, Pamplona, Spain. Electronic address: mederras@cfnavarra.es.
14
Galicia Breast Cancer Screening Program, Regional Authority of Health, Galicia Regional Government, Corunna, Spain. Electronic address: Carmen.Santamarina.Garcia@sergas.es.
15
Aragon Breast Cancer Screening Program, Aragon Health Service, Zaragoza, Spain. Electronic address: pmorenom@aragon.es.
16
Sección de Promoción de la Salud del Servicio Territorial de Sanidad de Burgos, Dirección General de Salud Pública de la Consejería de Sanidad de Castilla y León, Burgos, Spain. Electronic address: casgomfr@hotmail.com.
17
Sección de Promoción de la Salud del Servicio Territorial de Sanidad de Burgos, Dirección General de Salud Pública de la Consejería de Sanidad de Castilla y León, Burgos, Spain. Electronic address: pedpinca@jcyl.es.
18
Aragon Breast Cancer Screening Program, Aragon Health Service, Zaragoza, Spain. Electronic address: pmoreo@aragon.es.
19
Consortium for Biomedical Research in Epidemiology & Public Health (CIBER Epidemiología y Salud Pública - CIBERESP), Spain; Navarra Breast Cancer Screening Program, Public Health Institute, Pamplona, Spain. Electronic address: nascunce@cfnavarra.es.
20
Programa de Prevención y Control del Cáncer, Unidad de Biomarcadores y Susceptibilidad, Institut d'Investigació Biomèdica de Bellvitge (IDIBELL), Institut Català d'Oncologia, L'Hospitalet de Llobregat, Spain. Electronic address: mgarcia@iconcologia.net.
21
Programa de Prevención de Cáncer de Mama, Dirección General de Salud Pública, Valencia, Spain. Electronic address: salas_dol@gva.es.
22
Programa de Detección Precoz de Cáncer de Mama, Dirección General de Salud Pública y Participación, Palma, Spain. Electronic address: csanchezcontador@dgsanita.caib.es.
23
Institute of Computer Technology, Universitat Politècnica de València, Valencia, Spain. Electronic address: rllobet@iti.upv.es.
24
Cancer and Environmental Epidemiology Unit, National Center for Epidemiology, Carlos III Institute of Health, Madrid, Spain; Consortium for Biomedical Research in Epidemiology & Public Health (CIBER Epidemiología y Salud Pública - CIBERESP), Spain. Electronic address: vicarvajal@isciii.es.

Abstract

INTRODUCTION:

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.

METHODS:

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.

RESULTS:

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).

CONCLUSIONS:

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.

KEYWORDS:

Breast cancer; DDM-Occup; Mammographic density; Nurses; Occupation; School teachers

PMID:
28843166
DOI:
10.1016/j.envres.2017.08.028
[Indexed for MEDLINE]

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