Mammographic density and exposure to air pollutants in premenopausal women: a cross-sectional study.

IF 4 3区 医学 Q1 PUBLIC, ENVIRONMENTAL & OCCUPATIONAL HEALTH Environmental Health and Preventive Medicine Pub Date : 2024-01-01 DOI:10.1265/ehpm.24-00209
Tamara Jiménez, Alejandro Domínguez-Castillo, Nerea Fernández de Larrea-Baz, Pilar Lucas, María Ángeles Sierra, Sergio Maeso, Rafael Llobet, Marina Nieves Pino, Mercedes Martínez-Cortés, Beatriz Pérez-Gómez, Marina Pollán, Virginia Lope, Javier García-Pérez
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Abstract

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 (SO2, CO, NO, NO2, NOx, PM2.5, PM10, and O3) 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 (ORQ4; IC95%) of high MD were detected in women with higher exposure to SO2 (1.50; 0.90-2.48), and PM2.5 (1.27; 0.77-2.10). In contrast, non-significant ORs < 1 were found in all exposure quartiles for NO (ORQ2 = 0.72, ORQ3 = 0.68, ORQ4 = 0.78), and PM10 (ORQ2 = 0.69, ORQ3 = 0.82, ORQ4 = 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.

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绝经前妇女的乳腺密度与空气污染物暴露:一项横断面研究。
背景:乳腺密度(MD)是乳腺癌的一个公认风险因素。空气污染是一个主要的公共健康问题,也是公认的致癌物质。我们旨在研究绝经前女性的乳腺密度与暴露于特定空气污染物(二氧化硫、一氧化碳、一氧化氮、二氧化氮、氮氧化物、PM2.5、PM10 和臭氧)之间的关系:这项横断面研究在西班牙进行,共有 769 人参加了妇科检查。污染物的每小时浓度是从马德里市空气质量监测系统中提取的,为期 3 年。通过对居住地址和监测站进行地理编码,并对每种污染物的 3 年年均浓度应用普通克里金法对马德里地表进行插值,评估了个人长期暴露于污染物的情况。这一暴露变量被分为四等分。在第一项分析中,我们使用多元线性回归模型,将对数变换后的 MD 百分比作为连续变量。在第二项分析中,我们将 MD 作为二分变量("高 "密度(MD > 50%)与 "低 "密度(MD ≤ 50%)),并使用多重逻辑回归模型来估算几率比(OR)。我们还分析了污染物之间的相关性,并进行了主成分分析 (PCA),将这组 8 种相关污染物的维度降低为一组较小的不相关变量(主成分 (PC))。最后,对主成分进行初步分析,以检测排放源的基本模式:第一项分析未发现 MD 与接触任何污染物之间存在关联。第二项分析表明,二氧化硫(1.50;0.90-2.48)和 PM2.5(1.27;0.77-2.10)暴露量较高的女性的高 MD 风险(ORQ4;IC95%)有非统计学意义的显著增加。与此相反,在 NO(ORQ2 = 0.72,ORQ3 = 0.68,ORQ4 = 0.78)和 PM10(ORQ2 = 0.69,ORQ3 = 0.82,ORQ4 = 0.72)的所有暴露四分位数中都发现了不显著的 OR <1。PCA 确定了两个 PC(PC1:"交通污染 "和 PC2:"自然污染"),未发现 MD 与靠近这两个 PC 之间存在关联:总的来说,我们的研究结果表明,绝经前女性的特定空气污染物居住暴露与MD之间没有关联。未来的研究需要证实或反驳这些发现。
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来源期刊
Environmental Health and Preventive Medicine
Environmental Health and Preventive Medicine PUBLIC, ENVIRONMENTAL & OCCUPATIONAL HEALTH -
CiteScore
7.90
自引率
2.10%
发文量
44
审稿时长
10 weeks
期刊介绍: The official journal of the Japanese Society for Hygiene, Environmental Health and Preventive Medicine (EHPM) brings a comprehensive approach to prevention and environmental health related to medical, biological, molecular biological, genetic, physical, psychosocial, chemical, and other environmental factors. Environmental Health and Preventive Medicine features definitive studies on human health sciences and provides comprehensive and unique information to a worldwide readership.
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