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      Residential particulate matter and distance to roadways in relation to mammographic density: results from the Nurses’ Health Studies

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          Abstract

          Background

          High mammographic density is a strong, well-established breast cancer risk factor. Three studies conducted in various smaller geographic settings reported inconsistent findings between air pollution and mammographic density. We assessed whether particulate matter (PM) exposures (PM 2.5, PM 2.5–10, and PM 10) and distance to roadways were associated with mammographic density among women residing across the United States.

          Methods

          The Nurses’ Health Studies are prospective cohorts for whom a subset has screening mammograms from the 1990s (interquartile range 1990–1999). PM was estimated using spatio-temporal models linked to residential addresses. Among 3258 women (average age at mammogram 52.7 years), we performed multivariable linear regression to assess associations between square-root-transformed mammographic density and PM within 1 and 3 years before the mammogram. For linear regression estimates of PM in relation to untransformed mammographic density outcomes, bootstrapped robust standard errors are used to calculate 95% confidence intervals (CIs). Analyses were stratified by menopausal status and region of residence.

          Results

          Recent PM and distance to roadways were not associated with mammographic density in premenopausal women (PM 2.5 within 3 years before mammogram β = 0.05, 95% CI –0.16, 0.27; PM 2.5–10 β = 0, 95%, CI –0.15, 0.16; PM 10 β = 0.02, 95% CI –0.10, 0.13) and postmenopausal women (PM 2.5 within 3 years before mammogram β = –0.05, 95% CI –0.27, 0.17; PM 2.5–10 β = –0.01, 95% CI –0.16, 0.14; PM 10 β = –0.02, 95% CI –0.13, 0.09). Largely null associations were observed within regions. Suggestive associations were observed among postmenopausal women in the Northeast ( n = 745), where a 10-μg/m 3 increase in PM 2.5 within 3 years before the mammogram was associated with 3.4 percentage points higher percent mammographic density (95% CI –0.5, 7.3).

          Conclusions

          These findings do not support that recent PM or roadway exposures influence mammographic density. Although PM was largely not associated with mammographic density, we cannot rule out the role of PM during earlier exposure time windows and possible associations among northeastern postmenopausal women.

          Electronic supplementary material

          The online version of this article (doi:10.1186/s13058-017-0915-5) contains supplementary material, which is available to authorized users.

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          Most cited references38

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          Exposure measurement error in time-series studies of air pollution: concepts and consequences.

          Misclassification of exposure is a well-recognized inherent limitation of epidemiologic studies of disease and the environment. For many agents of interest, exposures take place over time and in multiple locations; accurately estimating the relevant exposures for an individual participant in epidemiologic studies is often daunting, particularly within the limits set by feasibility, participant burden, and cost. Researchers have taken steps to deal with the consequences of measurement error by limiting the degree of error through a study's design, estimating the degree of error using a nested validation study, and by adjusting for measurement error in statistical analyses. In this paper, we address measurement error in observational studies of air pollution and health. Because measurement error may have substantial implications for interpreting epidemiologic studies on air pollution, particularly the time-series analyses, we developed a systematic conceptual formulation of the problem of measurement error in epidemiologic studies of air pollution and then considered the consequences within this formulation. When possible, we used available relevant data to make simple estimates of measurement error effects. This paper provides an overview of measurement errors in linear regression, distinguishing two extremes of a continuum-Berkson from classical type errors, and the univariate from the multivariate predictor case. We then propose one conceptual framework for the evaluation of measurement errors in the log-linear regression used for time-series studies of particulate air pollution and mortality and identify three main components of error. We present new simple analyses of data on exposures of particulate matter < 10 microm in aerodynamic diameter from the Particle Total Exposure Assessment Methodology Study. Finally, we summarize open questions regarding measurement error and suggest the kind of additional data necessary to address them. Images Figure 1 Figure 2 Figure 3
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            Spatial and Temporal Variation in PM2.5 Chemical Composition in the United States for Health Effects Studies

            Background Although numerous studies have demonstrated links between particulate matter (PM) and adverse health effects, the chemical components of the PM mixture that cause injury are unknown. Objectives This work characterizes spatial and temporal variability of PM2.5 (PM with aerodynamic diameter < 2.5 μm) components in the United States; our objective is to identify components for assessment in epidemiologic studies. Methods We constructed a database of 52 PM2.5 component concentrations for 187 U.S. counties for 2000–2005. First, we describe the challenges inherent to analysis of a national PM2.5 chemical composition database. Second, we identify components that contribute substantially to and/or co-vary with PM2.5 total mass. Third, we characterize the seasonal and regional variability of targeted components. Results Strong seasonal and geographic variations in PM2.5 chemical composition are identified. Only seven of the 52 components contributed ≥ 1% to total mass for yearly or seasonal averages [ammonium (NH4 +), elemental carbon (EC), organic carbon matter (OCM), nitrate (NO3 −), silicon, sodium (Na+), and sulfate (SO4 2−)]. Strongest correlations with PM2.5 total mass were with NH4 + (yearly), OCM (especially winter), NO3 − (winter), and SO4 2− (yearly, spring, autumn, and summer), with particularly strong correlations for NH4 + and SO4 2− in summer. Components that co-varied with PM2.5 total mass, based on daily detrended data, were NH4 +, SO4 2− , OCM, NO3 2−, bromine, and EC. Conclusions The subset of identified PM2.5 components should be investigated further to determine whether their daily variation is associated with daily variation of health indicators, and whether their seasonal and regional patterns can explain the seasonal and regional heterogeneity in PM10 (PM with aerodynamic diameter < 10 μm) and PM2.5 health risks.
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              Insights into the mechanisms and mediators of the effects of air pollution exposure on blood pressure and vascular function in healthy humans.

              Fine particulate matter air pollution plus ozone impairs vascular function and raises diastolic blood pressure. We aimed to determine the mechanism and air pollutant responsible. The effects of pollution on heart rate variability, blood pressure, biomarkers, and brachial flow-mediated dilatation were determined in 2 randomized, double-blind, crossover studies. In Ann Arbor, 50 subjects were exposed to fine particles (150 microg/m(3)) plus ozone (120 parts per billion) for 2 hours on 3 occasions with pretreatments of an endothelin antagonist (Bosentan, 250 mg), antioxidant (Vitamin C, 2 g), or placebo. In Toronto, 31 subjects were exposed to 4 different conditions (particles plus ozone, particles, ozone, and filtered air). In Toronto, diastolic blood pressure significantly increased (2.9 and 3.6 mm Hg) only during particle-containing exposures in association with particulate matter concentration and reductions in heart rate variability. Flow-mediated dilatation significantly decreased (2.0% and 2.9%) only 24 hours after particle-containing exposures in association with particulate matter concentration and increases in blood tumor necrosis factor alpha. In Ann Arbor, diastolic blood pressure significantly similarly increased during all of the exposures (2.5 to 4.0 mm Hg), a response not mitigated by pretreatments. Flow-mediated dilatation remained unaltered. Particulate matter, not ozone, was responsible for increasing diastolic blood pressure during air pollution inhalation, most plausibly by instigating acute autonomic imbalance. Only particles from urban Toronto additionally impaired endothelial function, likely via slower proinflammatory pathways. Our findings demonstrate credible mechanisms whereby fine particulate matter could trigger acute cardiovascular events and that aspects of exposure location may be an important determinant of the health consequences.
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                Author and article information

                Contributors
                617-525-2102 , ncd121@mail.harvard.edu
                jaime.hart@channing.harvard.edu
                kab15@bu.edu
                pkraft@hsph.harvard.edu
                francine.laden@channing.harvard.edu
                rulla.tamimi@channing.harvard.edu
                Journal
                Breast Cancer Res
                Breast Cancer Res
                Breast Cancer Research : BCR
                BioMed Central (London )
                1465-5411
                1465-542X
                23 November 2017
                23 November 2017
                2017
                : 19
                : 124
                Affiliations
                [1 ]ISNI 000000041936754X, GRID grid.38142.3c, Department of Epidemiology, , Harvard T.H. Chan School of Public Health, ; Boston, MA USA
                [2 ]ISNI 0000 0004 0378 8294, GRID grid.62560.37, Channing Division of Network Medicine, Department of Medicine, Brigham and Women’s Hospital and Harvard Medical School, ; Boston, MA USA
                [3 ]ISNI 000000041936754X, GRID grid.38142.3c, Department of Environmental Health, , Harvard T.H. Chan School of Public Health, ; Boston, MA USA
                [4 ]ISNI 0000 0004 1936 7558, GRID grid.189504.1, Slone Epidemiology Center at Boston University, ; Boston, MA USA
                Article
                915
                10.1186/s13058-017-0915-5
                5701365
                29169389
                f1ace6ee-4aa2-4780-87d9-547a4c41e246
                © The Author(s). 2017

                Open AccessThis article is distributed under the terms of the Creative Commons Attribution 4.0 International License ( http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The Creative Commons Public Domain Dedication waiver ( http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated.

                History
                : 16 August 2017
                : 7 November 2017
                Funding
                Funded by: FundRef http://dx.doi.org/10.13039/100000869, Susan G. Komen for the Cure;
                Award ID: IIR13264020
                Award Recipient :
                Funded by: FundRef http://dx.doi.org/http://dx.doi.org/10.13039/100000002, National Institutes of Health;
                Award ID: UM1 CA186107
                Funded by: FundRef http://dx.doi.org/http://dx.doi.org/10.13039/100000002, National Institutes of Health;
                Award ID: UM1 CA176726
                Funded by: FundRef http://dx.doi.org/http://dx.doi.org/10.13039/100000066, National Institute of Environmental Health Sciences;
                Award ID: ES017017
                Funded by: FundRef http://dx.doi.org/10.13039/100000002, National Institutes of Health;
                Award ID: T32 CA09001
                Categories
                Research Article
                Custom metadata
                © The Author(s) 2017

                Oncology & Radiotherapy
                air pollution,particulate matter,mammographic density,epidemiology
                Oncology & Radiotherapy
                air pollution, particulate matter, mammographic density, epidemiology

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