Residential proximity to industrial pollution and mammographic density.


Journal

The Science of the total environment
ISSN: 1879-1026
Titre abrégé: Sci Total Environ
Pays: Netherlands
ID NLM: 0330500

Informations de publication

Date de publication:
10 Jul 2022
Historique:
received: 24 11 2021
revised: 25 02 2022
accepted: 11 03 2022
pubmed: 20 3 2022
medline: 20 5 2022
entrez: 19 3 2022
Statut: ppublish

Résumé

Mammographic density (MD), expressed as percentage of fibroglandular breast tissue, is an important risk factor for breast cancer. Our objective is to investigate the relationship between MD and residential proximity to pollutant industries in premenopausal Spanish women. A cross-sectional study was carried out in a sample of 1225 women extracted from the DDM-Madrid study. Multiple linear regression models were used to assess the association of MD percentage (and their 95% confidence intervals (95%CIs)) and proximity (between 1 km and 3 km) to industries included in the European Pollutant Release and Transfer Register. Although no association was found between MD and distance to all industries as a whole, several industrial sectors showed significant association for some distances: "surface treatment of metals and plastic" (β = 4.98, 95%CI = (0.85; 9.12) at ≤1.5 km, and β = 3.00, 95%CI = (0.26; 5.73) at ≤2.5 km), "organic chemical industry" (β = 6.73, 95%CI = (0.50; 12.97) at ≤1.5 km), "pharmaceutical products" (β = 4.14, 95%CI = (0.58; 7.70) at ≤2 km; β = 3.55, 95%CI = (0.49; 6.60) at ≤2.5 km; and β = 3.11, 95%CI = (0.20; 6.01) at ≤3 km), and "urban waste-water treatment plants" (β = 8.06, 95%CI = (0.82; 15.30) at ≤1 km; β = 5.28; 95%CI = (0.49; 10.06) at ≤1.5 km; β = 4.30, 95%CI = (0.03; 8.57) at ≤2 km; β = 5.26, 95%CI = (1.83; 8.68) at ≤2.5 km; and β = 3.19, 95%CI = (0.46; 5.92) at ≤3 km). Moreover, significant increased MD was observed in women close to industries releasing specific pollutants: ammonia (β = 4.55, 95%CI = (0.26; 8.83) at ≤1.5 km; and β = 3.81, 95%CI = (0.49; 7.14) at ≤2 km), dichloromethane (β = 3.86, 95%CI = (0.00; 7.71) at ≤2 km), ethylbenzene (β = 8.96, 95%CI = (0.57; 17.35) at ≤3 km), and phenols (β = 2.60, 95%CI = (0.21; 5.00) at ≤2.5 km). Our results suggest no statistically significant relationship between MD and proximity to industries as a whole, although we detected associations with various industrial sectors and some specific pollutants, which suggests that MD could have a mediating role in breast carcinogenesis.

Sections du résumé

BACKGROUND BACKGROUND
Mammographic density (MD), expressed as percentage of fibroglandular breast tissue, is an important risk factor for breast cancer. Our objective is to investigate the relationship between MD and residential proximity to pollutant industries in premenopausal Spanish women.
METHODS METHODS
A cross-sectional study was carried out in a sample of 1225 women extracted from the DDM-Madrid study. Multiple linear regression models were used to assess the association of MD percentage (and their 95% confidence intervals (95%CIs)) and proximity (between 1 km and 3 km) to industries included in the European Pollutant Release and Transfer Register.
RESULTS RESULTS
Although no association was found between MD and distance to all industries as a whole, several industrial sectors showed significant association for some distances: "surface treatment of metals and plastic" (β = 4.98, 95%CI = (0.85; 9.12) at ≤1.5 km, and β = 3.00, 95%CI = (0.26; 5.73) at ≤2.5 km), "organic chemical industry" (β = 6.73, 95%CI = (0.50; 12.97) at ≤1.5 km), "pharmaceutical products" (β = 4.14, 95%CI = (0.58; 7.70) at ≤2 km; β = 3.55, 95%CI = (0.49; 6.60) at ≤2.5 km; and β = 3.11, 95%CI = (0.20; 6.01) at ≤3 km), and "urban waste-water treatment plants" (β = 8.06, 95%CI = (0.82; 15.30) at ≤1 km; β = 5.28; 95%CI = (0.49; 10.06) at ≤1.5 km; β = 4.30, 95%CI = (0.03; 8.57) at ≤2 km; β = 5.26, 95%CI = (1.83; 8.68) at ≤2.5 km; and β = 3.19, 95%CI = (0.46; 5.92) at ≤3 km). Moreover, significant increased MD was observed in women close to industries releasing specific pollutants: ammonia (β = 4.55, 95%CI = (0.26; 8.83) at ≤1.5 km; and β = 3.81, 95%CI = (0.49; 7.14) at ≤2 km), dichloromethane (β = 3.86, 95%CI = (0.00; 7.71) at ≤2 km), ethylbenzene (β = 8.96, 95%CI = (0.57; 17.35) at ≤3 km), and phenols (β = 2.60, 95%CI = (0.21; 5.00) at ≤2.5 km).
CONCLUSIONS CONCLUSIONS
Our results suggest no statistically significant relationship between MD and proximity to industries as a whole, although we detected associations with various industrial sectors and some specific pollutants, which suggests that MD could have a mediating role in breast carcinogenesis.

Identifiants

pubmed: 35304152
pii: S0048-9697(22)01671-0
doi: 10.1016/j.scitotenv.2022.154578
pii:
doi:

Substances chimiques

Environmental Pollutants 0

Types de publication

Journal Article

Langues

eng

Sous-ensembles de citation

IM

Pagination

154578

Informations de copyright

Copyright © 2022 Elsevier B.V. All rights reserved.

Déclaration de conflit d'intérêts

Declaration of competing interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper.

Auteurs

Tamara Jiménez (T)

Department of Preventive Medicine, Public Health and Microbiology, Universidad Autónoma de Madrid (UAM), Madrid, Spain.

Marina Pollán (M)

Cancer and Environmental Epidemiology Unit, Department of Epidemiology of Chronic Diseases, National Center for Epidemiology, Instituto de Salud Carlos III (Carlos III Institute of Health), Madrid, Spain; Consortium for Biomedical Research in Epidemiology & Public Health (CIBER en Epidemiología y Salud Pública - CIBERESP), Spain. Electronic address: mpollan@isciii.es.

Alejandro Domínguez-Castillo (A)

Cancer and Environmental Epidemiology Unit, Department of Epidemiology of Chronic Diseases, National Center for Epidemiology, Instituto de Salud Carlos III (Carlos III Institute of Health), Madrid, Spain. Electronic address: a.dominguez@isciii.es.

Pilar Lucas (P)

Cancer and Environmental Epidemiology Unit, Department of Epidemiology of Chronic Diseases, National Center for Epidemiology, Instituto de Salud Carlos III (Carlos III Institute of Health), Madrid, Spain. Electronic address: pmlucas@isciii.es.

María Ángeles Sierra (MÁ)

Cancer and Environmental Epidemiology Unit, Department of Epidemiology of Chronic Diseases, National Center for Epidemiology, Instituto de Salud Carlos III (Carlos III Institute of Health), Madrid, Spain; Consortium for Biomedical Research in Epidemiology & Public Health (CIBER en Epidemiología y Salud Pública - CIBERESP), Spain. Electronic address: masierra@isciii.es.

Nerea Fernández de Larrea-Baz (N)

Cancer and Environmental Epidemiology Unit, Department of Epidemiology of Chronic Diseases, National Center for Epidemiology, Instituto de Salud Carlos III (Carlos III Institute of Health), Madrid, Spain; Consortium for Biomedical Research in Epidemiology & Public Health (CIBER en Epidemiología y Salud Pública - CIBERESP), Spain. Electronic address: nfernandez@isciii.es.

Mario González-Sánchez (M)

Cancer and Environmental Epidemiology Unit, Department of Epidemiology of Chronic Diseases, National Center for Epidemiology, Instituto de Salud Carlos III (Carlos III Institute of Health), Madrid, Spain; Consortium for Biomedical Research in Epidemiology & Public Health (CIBER en Epidemiología y Salud Pública - CIBERESP), Spain. Electronic address: mariogonzalez@isciii.es.

Dolores Salas-Trejo (D)

Consortium for Biomedical Research in Epidemiology & Public Health (CIBER en Epidemiología y Salud Pública - CIBERESP), Spain; Valencian Breast Cancer Screening Program, General Directorate of Public Health, Valencia, Spain; Center for Public Health Research CSISP, FISABIO, Valencia, Spain. Electronic address: salas_dol@gva.es.

Rafael Llobet (R)

Institute of Computer Technology, Universitat Politècnica de València, Valencia, Spain. Electronic address: rllobet@dsic.upv.es.

Inmaculada Martínez (I)

Valencian Breast Cancer Screening Program, General Directorate of Public Health, Valencia, Spain; Center for Public Health Research CSISP, FISABIO, Valencia, Spain. Electronic address: martinez_inm@gva.es.

Marina Nieves Pino (MN)

Servicio de Prevención y Promoción de la Salud, Madrid Salud, Ayuntamiento de Madrid, Madrid, Spain. Electronic address: pinoemn@madrid.es.

Mercedes Martínez-Cortés (M)

Servicio de Prevención y Promoción de la Salud, Madrid Salud, Ayuntamiento de Madrid, Madrid, Spain. Electronic address: martinezcme@madrid.es.

Beatriz Pérez-Gómez (B)

Consortium for Biomedical Research in Epidemiology & Public Health (CIBER en Epidemiología y Salud Pública - CIBERESP), Spain; Department of Epidemiology of Chronic Diseases, National Center for Epidemiology, Instituto de Salud Carlos III (Carlos III Institute of Health), Madrid, Spain. Electronic address: bperez@isciii.es.

Virginia Lope (V)

Cancer and Environmental Epidemiology Unit, Department of Epidemiology of Chronic Diseases, National Center for Epidemiology, Instituto de Salud Carlos III (Carlos III Institute of Health), Madrid, Spain; Consortium for Biomedical Research in Epidemiology & Public Health (CIBER en Epidemiología y Salud Pública - CIBERESP), Spain. Electronic address: vicarvajal@isciii.es.

Javier García-Pérez (J)

Cancer and Environmental Epidemiology Unit, Department of Epidemiology of Chronic Diseases, National Center for Epidemiology, Instituto de Salud Carlos III (Carlos III Institute of Health), Madrid, Spain; Consortium for Biomedical Research in Epidemiology & Public Health (CIBER en Epidemiología y Salud Pública - CIBERESP), Spain. Electronic address: jgarcia@isciii.es.

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