Long-term exposure to particulate air pollution and brachial artery flow-mediated dilation in the Old Order Amish RESEARCH Open Access Long-term exposure to particulate air pollution and brachial artery flow-mediated dilation in the Old Order Amish Shabnam Salimi1†, Jeff D. Yanosky2*†, Dina Huang3, Jessica Montressor-Lopez4, Robert Vogel1, Robert M. Reed5, Braxton D. Mitchell1,6 and Robin C. Puett4 Abstract Background: Atmospheric particulate matter (PM) has been associated with endothelial dysfunction, an early marker of cardiovascular risk. Our aim was to extend this research to a genetically homogenous, geographically stable rural population using location-specific moving-average air pollution exposure estimates indexed to the date of endothelial function measurement. Methods: We measured endothelial function using brachial artery flow-mediated dilation (FMD) in 615 community- dwelling healthy Amish participants. Exposures to PM < 2.5 μm (PM2.5) and PM < 10 μm (PM10) were estimated at participants’ residential addresses using previously developed geographic information system-based spatio-temporal models and normalized. Associations between PM exposures and FMD were evaluated using linear mixed-effects regression models, and polynomial distributed lag (PDL) models followed by Bayesian model averaging (BMA) were used to assess response to delayed effects occurring across multiple months. Results: Exposure to PM10 was consistently inversely associated with FMD, with the strongest (most negative) association for a 12-month moving average (− 0.09; 95% CI: − 0.15, − 0.03). Associations with PM2.5 were also strongest for a 12-month moving average but were weaker than for PM10 (− 0.07; 95% CI: − 0.13, − 0.09). Associations of PM2.5 and PM10 with FMD were somewhat stronger in men than in women, particularly for PM10. Conclusions: Using location-specific moving-average air pollution exposure estimates, we have shown that 12- month moving-average estimates of PM2.5 and PM10 exposure are associated with impaired endothelial function in a rural population. Keywords: Endothelial function, Cardiovascular disease, Air pollution, Particulate matter © The Author(s). 2020 Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article's Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article's Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/. 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 in a credit line to the data. * Correspondence: jyanosky@phs.psu.edu †Shabnam Salimi and Jeff D. Yanosky are Co-first author. 2Department of Public Health Sciences, College of Medicine, The Pennsylvania State University College of Medicine, 90 Hope Drive, Hershey, PA 17033, USA Full list of author information is available at the end of the article Salimi et al. Environmental Health (2020) 19:50 https://doi.org/10.1186/s12940-020-00593-y http://crossmark.crossref.org/dialog/?doi=10.1186/s12940-020-00593-y&domain=pdf http://creativecommons.org/licenses/by/4.0/ http://creativecommons.org/publicdomain/zero/1.0/ mailto:jyanosky@phs.psu.edu Introduction Endothelial cells residing in the inner layer of blood ves- sels are a key determinant of vascular health. Endothelial cell function includes vasoconstriction and vasodilation through nitric oxide release. Endothelial damage results in aggregation of platelets and their adhesion to the vas- cular wall. These processes can lead to thromboses resulting in cardiovascular events (e.g., stoke, incident myocardial infarction, angina, coronary revasculariza- tion, cardiac arrest, cardiovascular (CVD)-associated death [25];); such thrombotic conditions can be ad- dressed medically to prevent cardiovascular events in pa- tients with and without known CVD [36]. Endothelial dysfunction is widely recognized as an initial and revers- ible precursor in the progression of atherogenesis [2]. Through continued oxidation and inflammation, factors contributing to endothelial dysfunction lead to the pro- gression of atherosclerosis. Brachial artery endothelial function is affected by sev- eral established risk factors for CVD, including hyper- tension, homocystinuria, oxidized low density lipoprotein (LDL) cholesterol, tobacco smoking, and oxi- dative stress [6, 7]. Further, brachial artery flow- mediated dilation (FMD), assessed non-invasively with ultrasound, is a broadly used assessment of endothelial function in adults [6, 12, 15, 32, 36]. A substantial body of epidemiologic evidence has linked exposure to particulate matter (PM) air pollution to a wide array of adverse cardiovascular outcomes [1, 3, 4, 10, 13, 17, 19–21, 30, 34], including some effects con- sidered to be directly downstream of impaired endothe- lial function. For example, exposure to PM < 2.5 μm in aerodynamic diameter (PM2.5) has been associated with cardiovascular risk factors including hypertension, sys- temic inflammation, oxidative stress, and established atherosclerosis [4, 31]. Though results from some earlier studies were inconsistent ([4] and references therein), two recent epidemiologic studies that used PM air pollu- tion exposure modeling similar to that in the present analysis have reported associations between long-term PM2.5 exposure and brachial artery FMD [13, 34]. Wilker et al. used a 1-year average of spatio-temporal PM2.5 model predictions from the year 2001, with 50 m spatial resolution, as a surrogate for long-term exposure. Krishnan et al. applied a hierarchical spatio-temporal universal kriging model of two-week average PM2.5 levels, taking a 1-year average of model predictions for the year 2000. Neither of these analyses used moving av- erages specific to the date of FMD measurement, nor did they report on whether results were sensitive to the selected averaging period of 1 year as compared to shorter or longer averaging times (with the exception that Krishnan et al. evaluated 1 and 2 days prior to FMD measurement). Also, neither of these analyses was performed in a primarily rural population. We sought to address these gaps using a genetically homogenous, geo- graphically stable population. We hypothesized that ele- vated PM exposures result in detrimental effects on endothelial function assessed by FMD. Our objective was to determine whether and over what averaging period long-term exposure to PM2.5 and PM < 10 μm in aerodynamic diameter (PM10) were associated with FMD in a community-based sample of 615 healthy indi- viduals from an Amish community in Lancaster County, PA. Methods Study design We performed a retrospective cohort study of partici- pants recruited into the Heredity and Phenotype Inter- vention (HAPI) Heart Study [16]. The HAPI Heart Study was conducted among the Amish community in Lancaster County, PA and designed to identify potential genetic and environmental risk factors of CVD [16]. Relevant to the present study, the Lancaster Amish are characterized by high levels of physical activity, homo- geneity of socioeconomic status and lifestyle, limited use of prescription medications, and relative geographic sta- bility. Further details of the HAPI Heart Study are avail- able elsewhere [16]. Briefly, the HAPI Heart Study was a community-wide study of clinically healthy individuals aged 20 years and older with the following major exclu- sions: currently pregnant or < 6 months post-partum, blood pressure at the time of screening > 180/105 mmHg, and unable or unwilling to safely discontinue medications potentially affecting study outcomes (pre- scription medication use has been documented to be lower among this population than the general popula- tion [24]). A total of 868 participants were enrolled in the HAPI Study from 2003 to 2006, of whom endothelial function was assessed on the exam day by FMD in 615 participants (some of whom in family groups) in the present analysis. Demographic, health behavior (e.g., smoking and eating habits), and family and medical history infor- mation was obtained through interviews by a study nurse and Amish liaison in participant homes. Body mass index (BMI) and FMD were measured at the Amish Research Clinic in Lancaster County, PA. All study participants provided written informed consent prior to data collection, and the HAPI Heart Study protocol was approved by the Institutional Review Board at the University of Maryland. The protocol for the present air pollution ancillary study was ap- proved by the Institutional Review Boards at the University of Maryland and Pennsylvania State University. Salimi et al. Environmental Health (2020) 19:50 Page 2 of 9 Brachial artery FMD Endothelial function was measured by brachial artery re- activity test (BART) to assess FMD using standardized procedures based on the International Brachial Artery Task Force and on expert guidelines [5, 9, 33]. All partici- pants were fasting overnight (8–12 h) and were abstinent from food, caffeine, alcohol, and smoking. All medications (vasoactive and other), vitamins, and supplements were discontinued for 7 days prior to the study. Base brachial artery diameter (BAD) and blood vel- ocity were measured in the left brachial artery above the antecubital fossa using 11 mHz ultrasound (Phillips HDI 5000CV) with participants sitting supine for 15 min prior to the measurement. Then, using a standard sphygmo- manometer cuff above the antecubital fossa, inflation was applied by 20 mmHg above systolic blood pressure for 5 min to occlude blood flow to the brachial artery and induce ischemia. Following the fast deflation of the cuff to induce post-ischemic hyperemia, the blood vel- ocity and brachial artery diameter were recorded. All images were measured in a blinded fashion by a trained technician and manually analyzed by a cardiolo- gist as a single reader of the records. Percent FMD was computed as: ðMaxAD−BADBAD Þ�100% , where MaxAD is the maximum brachial artery diameter. Shear stress and response to shear stress Vascular endothelial cells are exposed to blood velocity- mediated shear stress. Shear stress is the product of blood viscosity by shear rate: Shear stress ¼ η V r η = Blood viscosity; V = Blood velocity; r = Brachial ar- tery diameter. Assuming blood viscosity is constant, an increase in blood velocity leads to an increase in wall shear stress, which then evokes endothelial cell-mediated nitric oxide release and vessel dilation to decrease the shear stress. In the context of endothelial dysfunction, however, dilation following increased blood flow is impaired and response to shear stress is low [11]. After brachial artery occlusion, blood velocity increases which results in shear stress: Shear stress � Post occlusion blood velocity BAD The vasodilation (MaxAD) following cuff deflation and hyperemia occurs as the response to the shear stress [11]: Response to Shear Stress � Post occlusion blood velocity MaxAD The units of shear stress and response to shear stress were cm S− 1 mm− 1. Particulate air pollution exposure assessment Residential addresses collected at the time of interview were geocoded using ArcGIS 9.3 software (ESRI, Red- lands, California). Long-term exposures to PM2.5 and PM10 were estimated by applying previously-developed GIS-based spatio-temporal generalized additive mixed models (GAMMs) of PM2.5 and PM10 monthly-average mass concentrations, respectively [18, 35], at the partici- pant’s geocoded residential addresses. These spatio- temporal models included 1) monthly spatial smooth terms and 2) smooth regression terms of a) GIS-based covariates and b) time-varying meteorological covariates. The models were developed using PM2.5 and PM10 mon- itoring data collected across the conterminous US from 1999 to 2011 (2018 and 2044 monitoring sites, respect- ively). Exposure models were validated using cross- validation and had high predictive performance (cross- validation R2’s of 0.77 and 0.58 for PM2.5 and PM10, re- spectively). Monthly exposure estimates specific to the residential location of each participant were averaged over a 12-month time period prior to the date of FMD measurement (the month prior to FMD measurement and the 11 months before that) for use in our a priori analysis. Also, in subsequent analyses, moving averages over time periods of 1, 6, 24, 36, 60, and 84 months were generated. Monthly exposure estimates were used to construct sets of polynomial distributed lag (PDL) basis coefficients [26]. Statistical analysis Linear mixed-effect regression models were used to evaluate associations between PM2.5 and PM10 exposure metrics with endothelial function measured by brachial artery FMD. Analyses were conducted using SAS version 9.4 (Cary, North Carolina) and Mixed Models Analysis for Pedigrees (MMAP website [14, 29]); mixed-effect models included a random effect for family structure to allow for the relatedness of participants within the Amish community. Statistical tests were 2-sided and p- values< 0.05 were considered statistically significant. In our regression models, we evaluated age, BMI, BAD, sex, age by sex, smoking (current, ever, never), season of the year (four seasons based on calendar month), serum cholesterol, serum triglyceride, and hypertension as po- tential confounders. We repeated the above analyses ex- cluding BAD from the model. We also performed the above analyses stratified by age (younger than 50 vs. 50 years and older) by sex. Using interaction terms to assess effect modification, we evaluated: 1) age by sex 2) PM2.5 or PM10 by age, 3) PM2.5 or PM10 by sex, and 4) PM2.5 or PM10 by sex and age < 50 using interaction terms. We Salimi et al. Environmental Health (2020) 19:50 Page 3 of 9 did not evaluate PM2.5 or PM10 by smoking interactions because none of our female participants were ever- smokers. Because shear stress induces release of nitric oxide from endothelial cells resulting in response to shear stress, we evaluated associations of PM2.5 and PM10 with shear stress and response to shear stress with adjustment for BAD and the other covariates mentioned above. As a priori hypotheses, we first fit models using 12- month moving-averages of PM2.5 and PM10 exposures. Next, in subsequent exploratory analyses, we evaluated other averaging periods (1, 6, 24, 36, 60, 84 months). The steps in our model development process were as follows: First, we fit crude models for a given averaging period for PM2.5 and PM10, then added potential confounders to these models, and next evaluated effect modification. To evaluate the assumption of a constant effect (i.e., one that does not taper off in time) of PM2.5 or PM10 ex- posure over a given averaging period, we performed PDL models followed by Bayesian model averaging (BMA) [27]. In exploratory analyses, we first identified the averaging period with the largest absolute value of effect among the fully adjusted moving-average models. We then fit PDL models from 0 to 5th order using the number of months in the averaging period selected above as the lag period. We then used BMA to calculate the probability-weighted average of the coefficients, given the data, from the resulting 6 PDL models. All final models were performed using linear mixed-effects models to account for family structure among partici- pants (referred to as “polygenic mixed-effects models”). To compare the strength of associations of endothelial function measures between PM2.5 and PM10, we normal- ized the PM exposure variables by subtracting their re- spective mean and dividing by their respective standard deviation. All results presented are based on normalized exposures, except those in Table S3. Results Study population Participant characteristics are presented in Table 1. The mean age in our study population was 43.5 years (SD: 13.9) and 43.7% were women. Among men, 20.5% were current smokers and 25.7% were ever smokers; in con- trast none of the women reported smoking. Few partici- pants reported a history of hypertension (3.7%), high cholesterol (16.8%), diabetes mellitus (0.8%), or heart at- tack (1.0%). FMD measures were approximately nor- mally distributed with a mean value of 10.5% (SD: 5.8). Mean PM2.5 and PM10 12-month moving averages were 18.2 μg m− 3 (SD: 1.1; interquartile range (IQR): 1.6) and 15.0 μg m− 3 (SD: 1.2; IQR: 1.6), respectively. Distribu- tions of the PM2.5 and PM10 exposure metrics and add- itional summary statistics are shown in Fig. 1. Associations of PM2.5 and PM10 with FMD and shear stress measures Table 2 shows associations of PM2.5 and PM10 exposure with FMD across all participants and for men and Table 1 Characteristics of study participants Clinical characteristic Mean (SD) or N (%) Across all Men Women Number of participants 615 (100%) 346 (56.3%) 269 (43.7%) Age at examination (years) 43.5 (13.9) 42.5 (13.7) 44.9 (14.1) Current smokers 71 (11.5%) 71 (20.5%) 0 (0%) Ever smokers (not currently smoking) 89 (14.4%) 89 (25.7%) 0 (0%) Never smokers 455 (74.0%) 186 (53.8%) 269 (100%) Body mass index (kg m−2) 26.3(4.1) 25.5 (3.2) 27.3 (4.8) Hypertension (diagnosed) 82 (13.3%) 42 (12.4%) 40 (14.9%) High cholesterol (self-report) 103 (16.8%) 53 (15.3%) 50 (18.6%) Diabetes mellitus (self-report) 5 (0.8%) 3 (0.9%) 2 (0.7%) Myocardial infarction (self-report) 6 (1.0%) 4 (1.2%) 2 (0.7%) Vascular measures Baseline brachial artery diameter (BAD; mm) 3.7 (0.7) 4.1 (0.4) 3.1 (0.4) Flow-mediated dilation (FMD; %) 10.5 (5.8) 8.4 (4.9) 13.2 (5.9) Shear stress (cm S−1 mm−1) 22.2 (7.5) 20.5 (6.1) 24.4 (8.6) Pre-occlusive blood velocity (cm S−1) 7.8 (6.5) 9.5 (6.7) 5.6 (5.5) Post-occlusive blood velocity (cm S−1) 79.5 (23.4) 82.9 (21.5) 74.9 (25.3) Response to shear stress (cm S−1 mm− 1) 20 (6.6) 18.9 (5.5) 21.5 (7.5) Salimi et al. Environmental Health (2020) 19:50 Page 4 of 9 Fig. 1 Distributions and summary statistics of the 12-month moving average PM2.5 and PM10 exposures, prior to normalization Table 2 Associations of PM2.5 and PM10 exposure metrics and FMD (%), across all participants and by sex, for increases in normalized PM2.5 or PM10 exposure, in fully adjusted models Particulate air pollution metrics (normalized) Across all Men Women β SE p-value 95% CI β SE p-value 95% CI β SE p-value 95% CI PM2.5 12-month moving-average* −0.07 0.03 0.03 −0.13, − 0.09 −0.09 0.04 0.04 − 0.16, − 0.01 −0.07 0.05 0.2 −0.17, 0.03 PM10 12-month moving-average* −0.09 0.03 0.007 −0.15, − 0.03 −0.16 0.05 0.001 −0.26, − 0.06 −0.06 0.05 0.2 −0.16, 0.04 *All models adjusted for age, sex, age by sex interaction, smoking (except in models for women only because there were no ever smokers), BMI, season, year, hypertension, and base brachial artery diameter Salimi et al. Environmental Health (2020) 19:50 Page 5 of 9 women separately with effect sizes for a normalized change in PM exposure (calculated by subtracting the mean and dividing by the SD). To afford comparisons with other studies, we also present these associations for a 10 μg m− 3 increment in PM2.5 or PM10 exposure in Table S3. Regression models were adjusted for age, BMI, and BAD as linear variables, and sex, smoking (current, ever, never), season of the year (four seasons based on calendar month), and hypertension as categorical vari- ables. For neither PM2.5 nor PM10 was there significant evidence for a PM by sex interaction (p > 0.10). PM2.5. Associations for PM2.5 were strongest (i.e., fur- thest from zero), among the averaging periods consid- ered, for a 12-month moving average. There was a significant inverse association between long-term expos- ure to PM2.5 and FMD: For a one unit increase in nor- malized 12-month moving-average PM2.5, FMD decreased by 0.07 (95% CI: − 0.13, − 0.09; p = 0.03) in our polygenic mixed-effects model. We repeated the analyses excluding BAD from the model and the effect sizes were identical. In sex-stratified analyses, PM2.5 was significantly asso- ciated with FMD in men (β = − 0.09; 95% CI: − 0.16, − 0.01; p = 0.04), but not in women (β = − 0.07; 95% CI: − 0.17, 0.03; p = 0.2) (Table 2). We also performed sex and age-stratified analyses: Associations remained moder- ately larger in men than in women and were larger in older (≥ 50 years) as compared to younger (< 50 years) individuals, though none were statistically significant in these subgroups (Table S2). PM2.5 was not significantly associated with response to shear stress in the total population (p > 0.4), or in sub- analyses of men only or women only (p > 0.3 for both) (Table 3). PM10. As for PM2.5, associations for PM10 were stron- gest (i.e., furthest from zero), among the averaging pe- riods considered, for a 12-month moving average. There was a significant inverse association between long-term exposure to PM10 and FMD. This association was stron- ger than that for PM2.5 for the equivalent averaging period. For a one unit increase in normalized 12-month moving-average PM10, FMD decreased by 0.09 (95% CI: − 0.15, − 0.03; p = 0.007) in our polygenic mixed-effects model. There was no evidence of effect modification in associations between 12-month moving-average PM10 and FMD by age or sex (p > 0.05 for each). However, the association between FMD and PM10 was stronger and more significant in men (β = − 0.16; 95% CI: − 0.26, − 0.06; p = 0.001) than in women (β = − 0.06, 95% CI: − 0.16, 0.04; p = 0.2) (Table 2). In age- and sex-stratified analyses, PM10 was more strongly associated with FMD in men than in women in both younger and older individuals. Only in the sub- group of men younger than age 50 years did the associ- ation between PM10 and FMD achieve statistical significance (β = − 0.16; 95%CI: − 0.25, − 0.04; p = 0.005) (Table S2). PM10 was marginally associated with response to shear stress (β = 0.07; 95% CI: − 0.01, 0.14; p = 0.08) in the total study population, and in sex-stratified analyses the effect size was considerably larger in women compared to men, although in neither sex did the association achieve statistical significance (β = 0.11; p = 0.08 in women and β = 0.01; p = 0.8 in men) (Table 3). Time course of effect of PM2.5 and PM10 on FMD Because associations of PM2.5 and PM10 moving aver- ages were strongest for the time period 12 months prior to the date of FMD measurement, a 12-month lag period was selected for PDL models. Results from these PDL models and subsequent BMA showed that 98.4% and 98.2% of the posterior probability corresponded to the zero-order model (equivalent to the moving-average) for PM2.5 and PM10, respectively (Table S1). The next most influential model was the first-order, or linear decay model, which contributed only 1.6 and 1.8% for PM2.5 and PM10, respectively. Weighted coefficients from BMA of these six models, for both PM2.5 and PM10 did not in- dicate substantial non-linearity or even linear decay in the response to lagged exposures over the prior 12 months (Figure S1). Discussion In our study population, significant inverse associations were observed between long-term residential PM2.5 and PM10 levels and endothelial function measured by bra- chial artery FMD. Though associations were suggestive of stronger PM2.5 and PM10 effects in men than in women, interaction terms were non-significant. These trends persisted in age- and sex-stratified analyses, for Table 3 Associations of PM2.5 and PM10 exposure metrics and response to shear stress (cm S −1 mm− 1), across all participants and by sex, for increases in normalized PM2.5 or PM10, in fully adjusted models Particulate air pollution metrics (normalized) Across all Men Women β SE p-value 95% CI β SE p-value 95% CI β SE p-value 95% CI PM2.5 12-month moving-average* 0.03 0.03 0.4 −0.04, 0.11 − 0.02 0.04 0.7 −0.10, 0.06 0.07 0.06 0.3 −0.05, 0.19 PM10 12-month moving-average* 0.07 0.04 0.08 −0.01, 0.14 0.01 0.05 0.8 −0.08, 0.10 0.11 0.06 0.08 −0.01, 0.22 *All models adjusted for age, sex, age by sex interaction, smoking (except in models for women only because there were no ever smokers), BMI, season, year, hypertension, and base brachial artery diameter Salimi et al. Environmental Health (2020) 19:50 Page 6 of 9 which associations between PM2.5 and PM10 and FMD were stronger in men than in women, for both those < 50 years and greater. One explanation for stronger associations of PM2.5 and PM10 with FMD in men as compared to women is that Amish men have higher levels of physical ac- tivity than Amish women, as we have previously shown using 7-day accelerometer counts [23]. If this physical ac- tivity occurs largely outdoors, it is plausible that their per- sonal exposure would be more highly correlated with ambient PM levels. Another explanation is that Amish women are non-smokers and have less outdoor activity. Finally, our results suggest greater effects of PM2.5 and PM10 on FMD among older adults (> 50 years), which may indicate increased susceptibility. However, because these interactions were not statistically significant, this conclusion requires replication in a larger sample size. In contrast to FMD, a stronger association between PM10 and response to shear stress was observed among women compared to men, suggesting greater nitric oxide bioavailability among women. For both PM2.5 and PM10, the data indicated selection of a 12-month averaging period was appropriate. Earlier or later exposures to PM2.5 or PM10 within the prior 12- month period did not substantially affect FMD re- sponses, as evidenced by the overwhelming dominance of the zero-order PDL models for both PM2.5 and PM10. Results indicated stronger associations with PM10 com- pared to PM2.5 for equivalent averaging periods, except in the women only group for which associations were non-significant (Table 2). One possible explanation is compositional differences in PM10 vs. PM2.5. Another is that we measured endothelial function in the brachial ar- tery, which is a relatively large blood vessel, whereas PM2.5 may exert the majority of its influence on smaller vasculature. Finally, the spatial misalignment of the PM2.5 and PM10 monitors may have contributed to ex- posure errors. The largest source of these errors appears primarily due to the apparent underestimation of PM10 levels at a PM10 monitor near to many of the participant residences; in contrast PM2.5 monitors were farther away and reported higher levels. We note that PM2.5 accounts for the majority of the mass of PM10 in most areas of the US [28]. Despite the limitation imposed by this spatial error, we believe the estimates of association for PM2.5 and PM10 in our study are valid because consistent, sys- tematic overestimation of measured PM2.5 levels is not ex- pected to change the rank-ordering of PM2.5 exposure values; similarly, for underestimation of PM10. However, dose-response interpretations based on this analysis should be viewed with caution. Future research on PM ef- fects on endothelial function using personal exposure monitoring for PM2.5 and PM10 to further clarify differ- ences in toxicity based on particle size fraction and/or composition is warranted. Compared to previous studies, our results for PM2.5 are consistent in direction but larger in magnitude of ef- fect (Table S3). One explanation is that our exposure as- sessment approach better described gradients in exposure resulting in less misclassification. Additionally, differences in time-activity patterns, with Amish men spending more time outside than participants in other studies, may have affected our results. Wilker et al. [34] conducted an analysis of long-term PM2.5 exposure and FMD among participants of the Framingham Offspring and Third Generation Cohorts (n = 5112) and reported a smaller effect size compared to ours (over an approxi- mated 10 μg m− 3 increment: (10/1.99)*(− 0.16) = − 0.8% in FMD vs. our result of − 4.0% (Table S3)). In Krishnan et al. [13], an analysis among members of the Multi- Ethnic Study of Atherosclerosis and Air Pollution study (n = 3040), authors also reported an effect size for long-term PM2.5 and FMD smaller than the present analysis (over an approximated 10 μg m− 3 increment: (10/3.0)*(− 0.3) = − 1.0% in FMD vs. our result of − 4.0%). Both of these studies used average PM2.5 levels over one calendar-year as surrogates of long-term exposure, and thus did not average over the spe- cific 12-months prior to FMD measurement (i.e., over a “moving-window”). As stated above, our analysis supports the use of a 12-month moving-average period, when avail- able, with regard to studies of health effects of PM2.5 and PM10 on FMD. Although the underlying biological mechanism of these effects is not currently well understood, it has been postulated that exposure to PM2.5 may regulate endothe- lial function through altered expression or function of the enzyme nitric oxide synthase which results in re- duced bioavailability of endothelium-derived nitric oxide, a key component of vascular homeostasis [22]. Recent animal studies have elucidated the role of endo- thelial progenitor cells in this process [8]. Our results generally showed stronger, albeit not significantly, asso- ciations of PM10 exposure with response to shear stress in women than in men, which is consistent with greater resiliency of women to PM-induced endothelial dysfunc- tion, perhaps attributable to protective hormonal effects or absence of smoking in women. Our study has several strengths. The homogeneity of the study population with regard to lifestyle and behav- ioral factors such as physical activity, diet, and formal education reduces the possibility that observed PM air pollution-FMD relationships are confounded by these factors. To our knowledge, this is the first study of air pollution and endothelial function in a genetically homogenous, rural population of clinically healthy indi- viduals. Moreover, FMD was measured by a single well- trained sonographer and data was obtained by a single cardiologist using high quality-control standards. In addition, we used GIS-based spatio-temporal exposure Salimi et al. Environmental Health (2020) 19:50 Page 7 of 9 models to predict time-varying (i.e., monthly) PM2.5 and PM10 exposure estimates specific to each participant’s residential address and used this data to calculate expos- ure metrics based on the FMD exam date. Limitations of our study include a lack of racial/ethnic variability such that our findings are not generalizable to other ethnicities. Also, our exposure estimates were found to contain exposure error such that PM2.5 esti- mates were sometimes slightly higher than PM10 esti- mates, limiting conclusions regarding the relative toxicity of PM2.5 as compared to PM10 from these data. Moreover, exposures to PM2.5 and PM10 were based on monthly averages, preventing our analyses from address- ing acute exposures to PM2.5 or PM10. This study provides support for associations between long-term exposure to both PM2.5 and PM10 with bra- chial artery FMD. This effect manifested maximally over the time course of approximately 12 months for both PM2.5 and PM10. Associations with FMD were stronger (i.e., more negative) for PM10 than for PM2.5. Results were suggestive of stronger associations in men than women, though these interactions did not reach statis- tical significance. The findings bolster the existing evi- dence regarding the effects of PM air pollution on CVD risk and suggest long-term exposures to PM2.5 and PM10 are plausible early risk factors of cardiovascular events. Supplementary information Supplementary information accompanies this paper at https://doi.org/10. 1186/s12940-020-00593-y. Additional file 1 : Table S1. Polynomial distributed lag (PDL) model posterior probabilities obtained from Bayesian model averaging (BMA) for zero-order through 5th order models using 12 lag periods, for PM2.5 and PM10. Table S2. Associations of PM2.5 and PM10 exposure metrics and FMD stratified by age (less than 50 years vs. 50 years and older) and sex for increases in normalized PM2.5 and PM10 exposure in fully adjusted models. Table S3. Associations of PM2.5 and PM10 exposure metrics and FMD across all participants and by sex for a 10 μg m− 3 increment in PM2.5 and PM10 exposure in fully adjusted models. Figure S1. Effect esti- mates from the six PDL models (zero-order through 5th order) weighted using BMA as discussed in main text, for: A) PM2.5 and B) PM10. The month prior to FMD measurement (lag zero) and 11 months prior are shown, as well as the cumulative effect over all 12 lag periods. Abbreviations BMA: Bayesian model averaging; FMD: Flow-mediated dilation; PM2.5: Particulate matter < 2.5 μm; PM10: Particulate matter < 10 μm Acknowledgements The authors thank Dr. Joel Schwartz for sharing SAS code for the BMA analysis and Dr. Duanping Liao for sharing the SAS code for the PDL models. Authors’ contributions JDY performed data analyses and was the lead writer. SS contributed to the data collection and processing, performed data analyses, reviewed the manuscript, and participated in revisions. DH contributed to the analysis, reviewed the manuscript, and participated in revisions. JML contributed to the analysis, reviewed the manuscript, and participated in revisions. RV conceived of the study and reviewed the manuscript. RMR contributed to the analysis, reviewed the manuscript, and participated in revisions. BDM conceived of the study, coordinated study personnel, contributed to the analysis, reviewed the manuscript, and participated in revisions. RCP conceived of the study, coordinated study personnel, contributed to the analysis, reviewed the manuscript, and participated in revisions. The authors read and approved the final manuscript. Funding This research was supported by NIH grants U01 HL072515 and P30 DK072488 and by a University of Maryland seed grant entitled “Ambient Air Pollution and Metabolic Syndrome in the Lancaster County Amish”. Also, SS was supported by NIH grant number K01AG059898-01A1. Availability of data and materials Supporting data is not available due to confidentiality constraints involved with human subject’s research. Ethics approval and consent to participate Informed consent was obtained from study participants and approval was obtained from the IRB’s of both the University of Maryland and the Penn State College of Medicine. Consent for publication The authors consent to publication. Competing interests The authors declare that they have no conflicts of interest. 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Predictive value of brachial flow-mediated dilation for incident cardiovascular events in a population-based study: the multi-ethnic study of atherosclerosis. Circulation. 2009;120(6):502–9. Publisher’s Note Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations. Salimi et al. Environmental Health (2020) 19:50 Page 9 of 9 http://edn.som/umaryland.edu/mmap/index.php http://edn.som/umaryland.edu/mmap/index.php https://doi.org/10.1080/10473289.1997.10464074n Abstract Background Methods Results Conclusions Introduction Methods Study design Brachial artery FMD Shear stress and response to shear stress Particulate air pollution exposure assessment Statistical analysis Results Study population Associations of PM2.5 and PM10 with FMD and shear stress measures Time course of effect of PM2.5 and PM10 on FMD Discussion Supplementary information Abbreviations Acknowledgements Authors’ contributions Funding Availability of data and materials Ethics approval and consent to participate Consent for publication Competing interests Author details References Publisher’s Note