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Ambient air pollution, including traffic-related air pollution (TRAP), increases cardiovascular disease risk, possibly through vascular alterations. Limited information exists about in-vehicle TRAP exposure and vascular changes. This randomized crossover trial aimed to determine via particle filtration the effect of on-roadway TRAP exposure on blood pressure and retinal vasculature. Visual Abstract. Blood Pressure Effect of Traffic-Related Air Pollution: Ambient air pollution, including traffic-related air pollution (TRAP), increases cardiovascular disease risk, possibly through vascular alterations. Limited information exists about in-vehicle TRAP exposure and vascular changes. This randomized crossover trial aimed to determine via particle filtration the effect of on-roadway TRAP exposure on blood pressure and retinal vasculature. Background: Ambient air pollution, including traffic-related air pollution (TRAP), increases cardiovascular disease risk, possibly through vascular alterations. Limited information exists about in-vehicle TRAP exposure and vascular changes. Objective: To determine via particle filtration the effect of on-roadway TRAP exposure on blood pressure and retinal vasculature. Design: Randomized crossover trial. (ClinicalTrials.gov: NCT05454930) Setting: In-vehicle scripted commutes driven through traffic in Seattle, Washington, during 2014 to 2016. Participants: Normotensive persons aged 22 to 45 years (n = 16). Intervention: On 2 days, on-road air was entrained into the vehicle. On another day, the vehicle was equipped with high-efficiency particulate air (HEPA) filtration. Participants were blinded to the exposure and were randomly assigned to the sequence. Measurements: Fourteen 3-minute periods of blood pressure were recorded before, during, and up to 24 hours after a drive. Image-based central retinal arteriolar equivalents (CRAEs) were measured before and after. Brachial artery diameter and gene expression were also measured and will be reported separately. Results: Mean age was 29.7 years, predrive systolic blood pressure was 122.7 mm Hg, predrive diastolic blood pressure was 70.8 mm Hg, and drive duration was 122.3 minutes (IQR, 4 minutes). Filtration reduced particle count by 86%. Among persons with complete data (n = 13), at 1 hour, mean diastolic blood pressure, adjusted for predrive levels, order, and carryover, was 4.7 mm Hg higher (95% CI, 0.9 to 8.4 mm Hg) for unfiltered drives compared with filtered drives, and mean adjusted systolic blood pressure was 4.5 mm Hg higher (CI, −1.2 to 10.2 mm Hg). At 24 hours, adjusted mean diastolic blood pressure (unfiltered) was 3.8 mm Hg higher (CI, 0.02 to 7.5 mm Hg) and adjusted mean systolic blood pressure was 1.1 mm Hg higher (CI, −4.6 to 6.8 mm Hg). Adjusted mean CRAE (unfiltered) was 2.7 μm wider (CI, −1.5 to 6.8 μm). Limitations: Imprecise estimates due to small sample size; seasonal imbalance by exposure order. Conclusion: Filtration of TRAP may mitigate its adverse effects on blood pressure rapidly and at 24 hours. Validation is required in larger samples and different settings. Primary Funding Source: U.S. Environmental Protection Agency and National Institutes of Health. [ABSTRACT FROM AUTHOR]

• Focus: Dementia incidence and exposure to traffic-related air pollution (TRAP). • Study design: Community-based prospective cohort study in Seattle, WA, age 65+. • Exposure: predicted UFP, BC, and NO 2 from an extensive monitoring campaign. • Result: No evidence of a greater hazard of dementia incidence with TRAP exposures. • Conclude: Sensitivity and secondary analyses were in agreement; replication needed. While epidemiologic evidence links higher levels of exposure to fine particulate matter (PM 2.5) to decreased cognitive function, fewer studies have investigated links with traffic-related air pollution (TRAP), and none have examined ultrafine particles (UFP, ≤100 nm) and late-life dementia incidence. To evaluate associations between TRAP exposures (UFP, black carbon [BC], and nitrogen dioxide [NO 2 ]) and late-life dementia incidence. We ascertained dementia incidence in the Seattle-based Adult Changes in Thought (ACT) prospective cohort study (beginning in 1994) and assessed ten-year average TRAP exposures for each participant based on prediction models derived from an extensive mobile monitoring campaign. We applied Cox proportional hazards models to investigate TRAP exposure and dementia incidence using age as the time axis and further adjusting for sex, self-reported race, calendar year, education, socioeconomic status, PM 2.5 , and APOE genotype. We ran sensitivity analyses where we did not adjust for PM 2.5 and other sensitivity and secondary analyses where we adjusted for multiple pollutants, applied alternative exposure models (including total and size-specific UFP), modified the adjustment covariates, used calendar year as the time axis, assessed different exposure periods, dementia subtypes, and others. We identified 1,041 incident all-cause dementia cases in 4,283 participants over 37,102 person-years of follow-up. We did not find evidence of a greater hazard of late-life dementia incidence with elevated levels of long-term TRAP exposures. The estimated hazard ratio of all-cause dementia was 0.98 (95 % CI: 0.92–1.05) for every 2000 pt/cm3 increment in UFP, 0.95 (0.89–1.01) for every 100 ng/m3 increment in BC, and 0.96 (0.91–1.02) for every 2 ppb increment in NO 2. These findings were consistent across sensitivity and secondary analyses. We did not find evidence of a greater hazard of late-life dementia risk with elevated long-term TRAP exposures in this population-based prospective cohort study. [ABSTRACT FROM AUTHOR]

• Maternal PM 2.5 exposure is associated with placental gene expression. • Differentially expressed genes have broad functions including signaling. • Maternal PM 2.5 exposure can interact with fetal sex on placental gene expression. While strong evidence supports adverse maternal and offspring consequences of air pollution, mechanisms that involve the placenta, a key part of the intrauterine environment, are largely unknown. Previous studies of air pollution and placental gene expression were small candidate gene studies that rarely considered prenatal windows of exposure or the potential role of offspring sex. We examined overall and sex-specific associations of prenatal exposure to fine particulate matter (PM 2.5) with genome-wide placental gene expression. Participants with placenta samples, collected at birth, and childhood health outcomes from CANDLE (Memphis, TN) (n = 776) and GAPPS (Seattle, WA) (n = 205) cohorts of the ECHO-PATHWAYS Consortium were included in this study. PM 2.5 exposures during trimesters 1, 2, 3, and the first and last months of pregnancy, were estimated using a spatiotemporal model. Cohort-specific linear adjusted models were fit for each exposure window and expression of >11,000 protein coding genes from paired end RNA sequencing data. Models with interaction terms were used to examine PM 2.5 -offspring sex interactions. False discovery rate (FDR < 0.10) was used to correct for multiple testing. Mean PM 2.5 estimate was 10.5–10.7 μg/m3 for CANDLE and 6.0–6.3 μg/m3 for GAPPS participants. In CANDLE, expression of 13 (11 upregulated and 2 downregulated), 20 (11 upregulated and 9 downregulated) and 3 (2 upregulated and 1 downregulated) genes was associated with PM 2.5 in the first trimester, second trimester, and first month, respectively. While we did not find any statistically significant association, overall, between PM 2.5 and gene expression in GAPPS, we found offspring sex and first month PM 2.5 interaction for DDHD1 expression (positive association among males and inverse association among females). We did not observe PM 2.5 and offspring sex interactions in CANDLE. In CANDLE, but not GAPPS, we found that prenatal PM 2.5 exposure during the first half of pregnancy is associated with placental gene expression. [ABSTRACT FROM AUTHOR]

• Low-cost sensors for fine particulate are appealing for use in epidemiology. • Different sensors have different performance characteristics. • With adequate calibration and caveats, one model's results are precise and reliable. • Calibration should be performed cautiously, preferably using region-specific model. • Low-cost sensors may be useful for exposure assessment in epidemiological studies. Low-cost air monitoring sensors are an appealing tool for assessing pollutants in environmental studies. Portable low-cost sensors hold promise to expand temporal and spatial coverage of air quality information. However, researchers have reported challenges in these sensors′ operational quality. We evaluated the performance characteristics of two widely used sensors, the Plantower PMS A003 and Shinyei PPD42NS, for measuring fine particulate matter compared to reference methods, and developed regional calibration models for the Los Angeles, Chicago, New York, Baltimore, Minneapolis-St. Paul, Winston-Salem and Seattle metropolitan areas. Duplicate Plantower PMS A003 sensors demonstrated a high level of precision (averaged Pearson′s r = 0.99), and compared with regulatory instruments, showed good accuracy (cross-validated R2 = 0.96, RMSE = 1.15 µg/m3 for daily averaged PM 2.5 estimates in the Seattle region). Shinyei PPD42NS sensor results had lower precision (Pearson′s r = 0.84) and accuracy (cross-validated R2 = 0.40, RMSE = 4.49 µg/m3). Region-specific Plantower PMS A003 models, calibrated with regulatory instruments and adjusted for temperature and relative humidity, demonstrated acceptable performance metrics for daily average measurements in the other six regions (R2 = 0.74–0.95, RMSE = 2.46–0.84 µg/m3). Applying the Seattle model to the other regions resulted in decreased performance (R2 = 0.67–0.84, RMSE = 3.41–1.67 µg/m3), likely due to differences in meteorological conditions and particle sources. We describe an approach to metropolitan region-specific calibration models for low-cost sensors that can be used with caution for exposure measurement in epidemiological studies. [ABSTRACT FROM AUTHOR]