2026-08-29T14:55:38Zhttps://repisalud.isciii.es/rest/oai/request

oai:repisalud.isciii.es:20.500.12105/259312025-12-18T13:01:36Zcom_20.500.12105_2052com_20.500.12105_2051col_20.500.12105_19608

00925njm 22002777a 4500 dc Jiménez, Tamara author Domínguez-Castillo, Alejandro author Fernandez de Larrea-Baz, Nerea author de Lucas, Maria Pilar author Sierra, Maria Angeles author Maeso Martínez, Sergio author Llobet, Rafael author Pino, Marina Nieves author Martínez-Cortés, Mercedes author Perez-Gomez, Beatriz author Pollan-Santamaria, Marina author Lope Carvajal, Virginia author García-Pérez, Javier author 2024 Background: Mammographic density (MD) is a well-established risk factor for breast cancer. Air pollution is a major public health concern and a recognized carcinogen. We aim to investigate the association between MD and exposure to specific air pollutants (SO, CO, NO, NO, NO, PM, PM, and O) in premenopausal females. Methods:This cross-sectional study, carried out in Spain, included 769 participants who attended their gynecological examinations. Hourly concentrations of the pollutants were extracted from the Air Quality Monitoring System of Madrid City over a 3-year period. Individual long-term exposure to pollutants was assessed by geocoding residential addresses and monitoring stations, and applying ordinary kriging to the 3-year annual mean concentrations of each pollutant to interpolate the surface of Madrid. This exposure variable was categorized into quartiles. In a first analysis, we used multiple linear regression models with the log-transformed percent MD as a continuous variable. In a second analysis, we used MD as a dichotomous variable ("high" density (MD > 50%) vs. "low" density (MD ≤ 50%)) and applied multiple logistic regression models to estimate odds ratios (ORs). We also analyzed the correlation among the pollutants, and performed a principal component analysis (PCA) to reduce the dimensionality of this set of eight correlated pollutants into a smaller set of uncorrelated variables (principal components (PCs)). Finally, the initial analyses were applied to the PCs to detect underlying patterns of emission sources. Results: The first analysis detected no association between MD and exposure to any of the pollutants. The second analysis showed non-statistically significant increased risks (OR; IC95%) of high MD were detected in women with higher exposure to SO (1.50; 0.90-2.48), and PM (1.27; 0.77-2.10). In contrast, non-significant ORs < 1 were found in all exposure quartiles for NO (OR = 0.72, OR = 0.68, OR = 0.78), and PM (OR = 0.69, OR = 0.82, OR = 0.72). PCA identified two PCs (PC1: "traffic pollution" and PC2: "natural pollution"), and no association was detected between MD and proximity to these two PCs. Conclusions: In general, our results show a lack of association between residential exposure to specific air pollutants and MD in premenopausal females. Future research is needed to confirm or refute these findings. Jiménez T, Domínguez-Castillo A, Fernández de Larrea-Baz N, Lucas P, Sierra MÁ, Maeso S, Llobet R, Pino MN, Martínez-Cortés M, Pérez-Gómez B, Pollán M, Lope V, García-Pérez J. Mammographic density and exposure to air pollutants in premenopausal women: a cross-sectional study. Environ Health Prev Med. 2024;29:65. doi: 10.1265/ehpm.24-00209. PMID: 39581598; PMCID: PMC11604911. 10.1265/ehpm.24-00209 1347-4715 1342-078X Environmental Health and Preventive Medicine 39581598 https://hdl.handle.net/20.500.12105/25931 Air pollution Breast cancer Breast density Correlation DDM-Madrid Kriging Long-term exposure Principal component analysis Mammographic density and exposure to air pollutants in premenopausal women: a cross-sectional study.