Yaghjyan Lusine, Arao Robert, Brokamp Cole, O'Meara Ellen S, Sprague Brian L, Ghita Gabriela, Ryan Patrick
Department of Epidemiology, College of Public Health and Health Professions and College of Medicine, University of Florida, 2004 Mowry Rd, Gainesville, FL, 32610, USA.
Group Health Research Institute, 1730 Minor Ave, Seattle, WA, 98101, USA.
Breast Cancer Res. 2017 Apr 6;19(1):36. doi: 10.1186/s13058-017-0828-3.
Mammographic breast density is a well-established strong risk factor for breast cancer. The environmental contributors to geographic variation in breast density in urban and rural areas are poorly understood. We examined the association between breast density and exposure to ambient air pollutants (particulate matter <2.5 μm in diameter (PM) and ozone (O)) in a large population-based screening registry.
Participants included women undergoing mammography screening at imaging facilities within the Breast Cancer Surveillance Consortium (2001-2009). We included women aged ≥40 years with known residential zip codes before the index mammogram (n = 279,967). Breast density was assessed using the American College of Radiology's Breast Imaging-Reporting and Data System (BI-RADS) four-category breast density classification. PM and O estimates for grids across the USA (2001-2008) were obtained from the US Environmental Protection Agency Hierarchical Bayesian Model (HBM). For the majority of women (94%), these estimates were available for the year preceding the mammogram date. Association between exposure to air pollutants and density was estimated using polytomous logistic regression, adjusting for potential confounders.
Women with extremely dense breasts had higher mean PM and lower O exposures than women with fatty breasts (8.97 vs. 8.66 ug/m and 33.70 vs. 35.82 parts per billion (ppb), respectively). In regression analysis, women with heterogeneously dense vs. scattered fibroglandular breasts were more likely to have higher exposure to PM (fourth vs. first quartile odds ratio (OR) = 1.19, 95% confidence interval (CI) 1.16 - 1.23). Women with extremely dense vs. scattered fibroglandular breasts were less likely to have higher levels of ozone exposure (fourth vs. first quartile OR = 0.80, 95% CI 0.73-0.87).
Exposure to PM and O may in part explain geographical variation in mammographic density. Further studies are warranted to determine the causal nature of these associations.
乳腺钼靶密度是已确定的乳腺癌强风险因素。对于城乡地区乳腺密度地理差异的环境影响因素，人们了解甚少。我们在一个大型的基于人群的筛查登记处研究了乳腺密度与暴露于环境空气污染物（直径小于2.5微米的颗粒物（PM）和臭氧（O））之间的关联。
参与者包括在乳腺癌监测联盟内的影像设施接受钼靶筛查的女性（2001 - 2009年）。我们纳入了在首次钼靶检查前已知居住邮编、年龄≥40岁的女性（n = 279,967）。使用美国放射学会的乳腺影像报告和数据系统（BI - RADS）四类乳腺密度分类法评估乳腺密度。美国各地网格的PM和O估计值（2001 - 2008年）来自美国环境保护局分层贝叶斯模型（HBM）。对于大多数女性（94%），这些估计值可获取钼靶检查日期前一年的数据。使用多分类逻辑回归估计空气污染物暴露与密度之间的关联，并对潜在混杂因素进行调整。
与脂肪型乳房的女性相比，极度致密型乳房的女性平均PM暴露量更高，O暴露量更低（分别为8.97 vs. 8.66微克/立方米和33.70 vs. 35.82十亿分比（ppb））。在回归分析中，与散在纤维腺体型乳房相比，不均匀致密型乳房的女性更有可能有更高的PM暴露（第四分位数与第一分位数比值比（OR） = 1.19，95%置信区间（CI）1.16 - 1.23）。与散在纤维腺体型乳房相比，极度致密型乳房的女性臭氧暴露水平较高的可能性较小（第四分位数与第一分位数OR = 0.80，95% CI 0.73 - 0.87）。
暴露于PM和O可能部分解释了乳腺钼靶密度的地理差异。有必要进一步研究以确定这些关联的因果性质。
