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BACKGROUND: It remains unclear whether in utero and childhood exposure to air pollution affects pubertal development, particularly age of menarche in girls. OBJECTIVE: The aim of this study was to determine whether residential ambient particulate matter (PM) exposure in utero and during childhood is associated with age of menarche. METHODS: We studied 5,201 girls in the Growing Up Today Study 2 (2004-present) who were 10-17 y of age at enrollment (47.7% premenarchal; 52.3% postmenarchal). Exposure to three size fractions of PM [fine PM with aerodynamic diameter ≤ 2.5 μm (PM2.5), PM with aerodynamic diameters between 2.5 μm and 10 μm (PM2.5-10), and PM with aerodynamic diameter 10 μm (PM10)] was assigned based on maternal residential address, updated every 2 y, using nationwide spatiotemporal models. We estimated average PM exposure in utero, and time-varying windows: annual average exposure in the prior 1 and 2 y and cumulative average from birth. Age of menarche was self-reported on three surveys administered in 2004, 2006, and 2008. We calculated hazard ratios (HR) for menarche for an interquartile range (IQR) increase in PM exposure using Cox proportional hazard models adjusting for potential confounders. RESULTS: Girls attained menarche at 12.3 y of age on average. In the adjusted model, higher residential exposure to ambient PM2.5 during all time windows was associated with earlier age of menarche. The HRs of menarche for each IQR (4 μg/m³) increase in exposure to PM2.5 during the in utero period, 1 y prior to menarche, and throughout childhood were 1.03 [95% confidence interval (CI): 1.00, 1.06], 1.06 (95% CI: 1.02, 1.10) and 1.06 (95% CI: 1.02, 1.10), respectively. Effect estimates for PM10 exposure were similar, albeit attenuated, for all time windows. PM2.5-10 exposure was not associated with age of menarche. DISCUSSION: Among a large, nationwide, prospective cohort of U.S. girls, higher exposure to PM2.5 and PM10 in utero and throughout childhood was associated with an earlier age of menarche. Our results suggest that PM2.5 and PM10 may have endocrine-disrupting properties that could lead to altered timing of menarche. [ABSTRACT FROM AUTHOR]

BACKGROUND: Several studies have evaluated whether the distribution of natural environments differs between marginalized and privileged neighborhoods. However, most studies restricted their analyses to a single or handful of cities and used different natural environment measures. OBJECTIVES: We evaluated whether natural environments are inequitably distributed based on socioeconomic status (SES) and race/ethnicity in the contiguous United States. METHODS: We obtained SES and race/ethnicity data (2015–2019) for all U.S. Census tracts. For each tract, we calculated the Normalized Different Vegetation Index (NDVI) for 2020, NatureScore (a proprietary measure of the quantity and quality of natural elements) for 2019, park cover for 2020, and blue space for 1984–2018. We used generalized additive models with adjustment for potential confounders and spatial autocorrelation to evaluate associations of SES and race/ethnicity with NDVI, NatureScore, park cover, and odds of containing blue space in all tracts (푛=71,532) and in urban tracts (푛=45,338). To compare effect estimates, we standardized NDVI, NatureScore, and park cover so that beta coefficients presented a percentage increase or decrease of the standard deviation (SD). RESULTS: Tracts with higher SES had higher NDVI, NatureScore, park cover, and odds of containing blue space. For example, urban tracts in the highest median household income quintile had higher NDVI [44.8% of the SD (95% CI: 42.8, 46.8)] and park cover [16.2% of the SD (95% CI: 13.5, 19.0)] compared with urban tracts in the lowest median household income quintile. Across all tracts, a lower percentage of non-Hispanic White individuals and a higher percentage of Hispanic individuals were associated with lower NDVI and NatureScore. In urban tracts, we observed weak positive associations between percentage non-Hispanic Black and NDVI, NatureScore, and park cover; we did not find any clear associations for percentage Hispanics. DISCUSSION: Multiple facets of the natural environment are inequitably distributed in the contiguous United States. [ABSTRACT FROM AUTHOR]

BACKGROUND: Communities with lower socioeconomic status and higher prevalence of racial/ethnic minority populations are often more exposed to environmental pollutants. Although studies have shown associations between aircraft noise and property values and various health outcomes, little is known about how aircraft noise exposures are sociodemographically patterned. OBJECTIVE: Our aim was to describe characteristics of populations exposed to aviation noise by race/ethnicity, education, and income in the United States. METHODS: Aircraft noise contours characterized as day-night average sound level (DNL) were developed for 90 U.S. airports in 2010 for DNL ≥45 dB(A) in 1-dB(A) increments. We compared characteristics of exposed U.S. Census block groups at three thresholds (≥45, ≥55, and ≥65 dB(A)), assigned on the basis of the block group land area being =50% within the threshold, vs. unexposed block groups near study airports. Comparisons were made across block group race/ethnicity, education, and income categories within the study areas (푛 ≥ 4,031-74,253). We performed both multinomial and other various multivariable regression approaches, including models controlling for airport and models with random intercepts specifying within-airport effects and adjusting for airport-level means. RESULTS: Aggregated across multiple airports, block groups with a higher Hispanic population had higher odds of being exposed to aircraft noise. For example, the multinomial analysis showed that a 10-percentage point increase in a block group’s Hispanic population was associated with an increased odds ratio of 39% (95% CI: 25%, 54%) of being exposed to =65 dB(A) compared with block groups exposed to <45 dB(A). Block groups with higher proportions of residents with only a high school education had higher odds of being exposed to aircraft noise. Results were robust across multiple regression approaches; however, there was substantial heterogeneity across airports. DISCUSSION: These results suggest that across U.S. airports, there is indication of sociodemographic disparities in noise exposures. [ABSTRACT FROM AUTHOR]

BACKGROUND: Atrial fibrillation (AF) is associated with substantial morbidity and mortality. Short-term exposures to air pollution have been associated with AF triggering; less is known regarding associations between long-term air pollution exposures and AF incidence. OBJECTIVES: Our objectivewas to assess the association between long-term exposures to air pollution and distance to road on incidence of AF in a cohort of U.S.women. METHODS: We assessed the association of high resolution spatiotemporal model predictions of long-term exposures to particulate matter (PM10 and PM2.5), sulfur dioxide (SO2), nitrogen dioxide (NO2), and distance to major roads with incidence of AF diagnosis, identified through Medicare linkage, among 83,117 women in the prospective Women's Health Initiative cohort, followed from enrollment in Medicare through December 2012, incidence of AF, or death. Using time-varying Cox proportional hazards models adjusted for age, race/ethnicity, study component, body mass index, physical activity, menopausal hormone therapy, smoking, diet quality, alcohol consumption, educational attainment, and neighborhood socioeconomic status, we estimated the relative risk of incident AF in association with each pollutant. METHODS: We assessed the association of high resolution spatiotemporal model predictions of long-term exposures to particulate matter (PM10 and PM2.5), sulfur dioxide (SO2), nitrogen dioxide (NO2), and distance to major roads with incidence of AF diagnosis, identified through Medicare linkage, among 83,117 women in the prospective Women's Health Initiative cohort, followed from enrollment in Medicare through December 2012, incidence of AF, or death. Using time-varying Cox proportional hazards models adjusted for age, race/ethnicity, study component, body mass index, physical activity, menopausal hormone therapy, smoking, diet quality, alcohol consumption, educational attainment, and neighborhood socioeconomic status, we estimated the relative risk of incident AF in association with each pollutant. RESULTS: A total of 16,348 incident AF cases were observed over 660,236 person-years of follow-up. Most exposure–response associations were nonlinear. NO2 was associated with risk of AF in multivariable adjusted models [Hazard Ratio (HR)=1.18; 95% confidence interval (CI): 1.13, 1.24, comparing the top to bottom quartile, 푝-for-trend= <0.0001]. Women living closer to roadways were at higher risk of AF (e.g., HR=1.07; 95% CI: 1.01, 1.13 for living within 50 m of A3 roads, compared with =1,000 m, 푝-for-trend=0.02), but we did not observe adverse associations with exposures to PM10, PM2.5, or SO2. There were adverse associations with PM10 (top quartile HR=1.10; 95% CI: 1.05, 1.16, 푝-for-trend= <0.0001) and PM2.5 (top quartile HR=1.09; 95% CI: 1.03, 1.14, 푝-for-trend=0:002) in sensitivity models adjusting for census region. DISCUSSION: In this study of postmenopausal women, NO2 and distance to road were consistently associated with higher risk of AF. [ABSTRACT FROM AUTHOR]

Background: Personal and indoor air pollution monitors represent two ways to assess acute air pollution exposures; however, few reproductive epidemiology studies have incorporated these tools.Objective: To provide an overview of the unique challenges and opportunities that arise when measuring acute exposure to air pollution in two ongoing reproductive epidemiology studies.Methods: The Air Pollution, In Vitro Fertilization (IVF), and Reproductive Outcomes (AIR) Study recruits women undergoing IVF to wear a personal particulate matter (PM) air pollution monitor (AirBeam2©) for the 72-hour period following the start of controlled ovarian stimulation. The Reproductive Effects of Chemicals and Air Pollutants (RECAP) Study recruits men across the United States to place an air pollution monitor (emmET) in their home for 3 months, use a smartphone application, and provide a semen sample. We highlight the key issues identified in implementing exposure assessment for both studies.Results: The main advantages of using the AirBeam2© personal monitor are as follows: (a) the low cost, (b) the ability to collect multiple size fractions of PM data every second, (c) the portability, (d) its capability to track GPS location, and (e) the ability for the participant to observe their real-time exposure information. The limited battery life, incompatibility with iOS-based smartphones, and frequent connection issues that arise between the AirBeam2© and smartphone are the main disadvantages. The main advantages of the emmET are the ability to measure multiple air pollutants at a high level of accuracy, collect data for a long period of time without burdening the participant, and ship monitors to participants around the country without the need for in-person set-up by trained technicians; however, the monitor only measures the indoor home environment.Conclusions: Novel methods can be utilised to characterise short-term air pollution exposure in reproductive epidemiology studies and represent an exciting area for future research. [ABSTRACT FROM AUTHOR]

Study Question: Is there an association between air pollution exposures and the risk of spontaneous abortion (SAB)?Summary Answer: Higher exposure to particulate matter (PM) air pollution above and beyond a woman's average exposure may be associated with greater risk of SAB, particularly among women experiencing at least one SAB during follow-up.What Is Known Already: There is sufficient biologic plausibility to suggest that air pollution adversely affects early pregnancy outcomes, particularly pregnancy loss; however, the evidence is limited.Study Design, Size, Duration: Our prospective cohort study included 19 309 women in the Nurses' Health Study II who contributed a total of 35 025 pregnancies between 1990 and 2008. We also conducted a case-crossover analysis among 3585 women (11 212 pregnancies) with at least one SAB and one live birth during follow-up.Participants/materials, Setting, Methods: Proximity to major roadways and exposure to PM <10 microns (PM10), 2.5-10 microns (PM2.5-10) and <2.5 microns (PM2.5) were determined for residential addresses between 1989 and 2007. Pregnancy outcomes were self-reported biannually throughout follow-up and comprehensively in 2009. Multivariable log-binomial regression models with generalized estimating equations were used to estimate the risk ratios and 95% CIs of SAB. Conditional logistic regression was used for the case-crossover analysis.Main Results and the Role Of Chance: During the 19 years of follow-up, 6599 SABs (18.8% of pregnancies) were reported. In the main analysis, living closer to a major roadway and average exposure to PM10, PM10-2.5 or PM2.5 in the 1 or 2 years prior to pregnancy were not associated with an increased risk of SAB. However, small positive associations between PM exposures and SAB were observed when restricting the analysis to women experiencing at least one SAB during follow-up. In the case-crossover analysis, an increase in PM10 (per 3.9 μg/m3), PM2.5-10 (per 2.3 μg/m3) and PM2.5 (per 2.0 μg/m3) in the year prior to pregnancy was associated with 1.12 (95% CI 1.06, 1.19), 1.09 (95% CI 1.03, 1.14) and 1.10 (95% CI 1.04, 1.17) higher odds of SAB, respectively.Limitations, Reasons For Caution: We did not have information on the month or day of SAB, which precluded our ability to examine specific windows of susceptibility or acute exposures. We also used ambient air pollution exposures as a proxy for personal exposure, potentially leading to exposure misclassification.Wider Implications Of the Findings: In our case-crossover analysis (but not in the entire cohort) we observed positive associations between exposure to all size fractions of PM exposure and risk of SAB. This may suggest that changes in PM exposure confer greater risk of SAB or that women with a history of SAB are a particularly vulnerable subgroup.Study Funding/competing Interest(s): The authors are supported by the following NIH grants UM1CA176726, R00ES026648 and P30ES000002. The authors have no actual or potential competing financial interests to disclose. [ABSTRACT FROM AUTHOR]

BACKGROUND: Particulate matter (PM) air pollution has been associated with decreased pulmonary function, but the exposure-response relationship in chronic obstructive pulmonary disease (COPD) patients is uncertain, and most studies have only focused on exposures to ambient pollution. OBJECTIVES: We aimed to assess associations between pulmonary function and indoor and ambient PM = 2:5 lm (PM2:5) and black carbon (BC). METHODS: Between November 2012 and December 2014, 125 patients with COPD (mean age, 73.4 y) who were not currently smoking and without known indoor BC sources were recruited. Indoor BC and PM2:5 were measured in each home for a week in each season, up to four times a year, followed by in-person spirometry pre- and post-bronchodilator. Ambient exposures were available from a central site monitor. Multivariable adjusted mixed effects regression models were used to assess associations scaled per interquartile range (IQR) of exposure. RESULTS: There were 367 study visits; the median (IQR) indoor BC and PM2:5 were 0.19 (0.22) lg=m3 and 6.67 (5.80) lg=m3, respectively. Increasing indoor exposures to BC were associated with decreases in pre-bronchodilator forced expiratory volume in 1 s ðFEV1Þ and forced vital capacity (FVC), and FEV1=FVC. For example, in multivariable adjusted models, each IQR increase in indoor BC from the weekly integrated filter was associated with a 17:87mL [95% confidence interval (CI): -33:76, -1:98] decrease in pre-bronchodilator FEV1. Increases in indoor PM2:5 were associated with decreases in FEV1 and FVC of smaller magnitude than those for indoor BC; however, the results were less precise. Ambient BC was not associated with pre-bronchodilator pulmonary function, ambient PM2:5 was only associated with decreases in FVC and increases in FEV1=FVC, and neither indoor nor ambient BC or PM2:5 were associated with post-bronchodilator pulmonary function. CONCLUSIONS: Low-level exposures to indoor BC and PM2:5, but not ambient exposures, were consistently associated with decreases in prebronchodilator pulmonary function. There was no association between exposures and post-bronchodilator pulmonary function. [ABSTRACT FROM AUTHOR]

BACKGROUND: Long-term noise exposure is associated with cardiovascular disease (CVD), including acute cardiovascular events such as myocardial infarction and stroke. However, longitudinal cohort studies in the U.S. of long-term noise and CVD are almost exclusively from Europe and few modeled nighttime noise, when an individual is likely at home or asleep, separately from daytime noise. We aimed to examine the prospective association of outdoor long-term nighttime and daytime noise from anthropogenic sources with incident CVD using a U.S.-based, nationwide cohort of women. METHODS: We linked L50 nighttime and L50 daytime anthropogenic modeled noise estimates from a U.S. National Parks Service model (L50: sound pressure levels exceeded 50 percent of the time) to geocoded residential addresses of 114,116 participants in the Nurses’ Health Study. We used time-varying Cox proportional hazards models to estimate risk of incident CVD, coronary heart disease (CHD), and stroke associated with long-term average (14-y measurement period) noise exposure, adjusted for potential individual- and area-level confounders and CVD risk factors (1988–2018; biennial residential address updates; monthly CVD updates). We assessed effect modification by population density, region, air pollution, vegetation cover, and neighborhood socioeconomic status, and explored mediation by self-reported average nightly sleep duration. RESULTS: Over 2,548,927 person-years, there were 10,331 incident CVD events. In fully adjusted models, the hazard ratios for each interquartile range increase in L50 nighttime noise (3.67 dBA) and L50 daytime noise (4.35 dBA), respectively, were 1.04 (95% CI: 1.02, 1.06) and 1.04 (95% CI: 1.02, 1.07). Associations for total energy-equivalent noise level (Leq) measures were stronger than for the anthropogenic statistical L50 noise measures. Similar associations were observed for CHD and stroke. Interaction analyses suggested that associations of L50 nighttime and L50 daytime noise with CVD did not differ by prespecified effect modifiers. We found no evidence that inadequate sleep (<5 h/night) mediated associations of L50 nighttime noise and CVD. DISCUSSION: Outdoor L50 anthropogenic nighttime and daytime noise at the residential address was associated with a small increase in CVD risk in a cohort of adult female nurses. [ABSTRACT FROM AUTHOR]

Background Emerging data from animal and human studies suggest that traffic-related air pollution adversely affects early pregnancy outcomes; however evidence is limited. Objective We examined whether residential proximity to major roadways and traffic, as proxies for traffic-related air pollution, are associated with in vitro fertilization (IVF) outcomes. Methods This analysis included 423 women enrolled in the Environment and Reproductive Health (EARTH) Study, a prospective cohort study, who underwent 726 IVF cycles (2004–2017). Using geocoded residential addresses collected at study entry, we calculated the distance to nearest major roadway and the traffic density within a 100 m radius. IVF outcomes were abstracted from electronic medical records. We used multivariable generalized linear mixed models to evaluate the associations between residential proximity to major roadways and traffic density and IVF outcomes adjusting for maternal age, body mass index, race, education level, smoking status, and census tract median income. Results Closer residential proximity to major roadways was statistically significantly associated with lower probability of implantation and live birth following IVF. The adjusted percentage of IVF cycles resulting in live birth for women living ≥400 m from a major roadway was 46% (95% CI 36, 56%) compared to 33% (95% CI 26, 40%) for women living <50 m (p-for-comparison, 0.04). Of the intermediate outcomes, there were suggestive associations between living closer to major roadways and slightly higher estradiol trigger concentrations (p-trend = 0.16) and lower endometrial thickness (p-trend = 0.06). Near-residence traffic density was not associated with outcomes of IVF. Conclusion Closer residential proximity to major roadways was related to reduced likelihood of live birth following IVF. [ABSTRACT FROM AUTHOR]

Background Urban sound levels are a ubiquitous environmental stressor and have been shown to be associated with a wide variety of health outcomes. While much is known about the predictors of A-weighted sound pressure levels in the urban environment, far less is known about other frequencies. Objective To develop a series of spatial-temporal sound models to predict A-weighted sound pressure levels, low, mid, and high frequency sound for Boston, Massachusetts. Methods Short-term sound levels were gathered at n = 400 sites from February 2015 – February 2016. Spatial and meteorological attributes at or near the sound monitoring site were obtained using publicly available data and a portable weather station. An elastic net variable selection technique was used to select predictors of A-weighted, low, mid, and high frequency sound. Results The final models for low, mid, high, and A-weighted sound levels explained 59 – 69% of the variability in each measure. Similar to other A-weighted models, our sound models included transportation related variables such as length of roads and bus lines in the surrounding area; distance to road and rail lines; traffic volume, vehicle mix, residential and commercial land use. However, frequency specific models highlighted additional predictors not included in the A-weighted model including temperature, vegetation, impervious surfaces, vehicle mix, and density of entertainment establishments and restaurants. Conclusions Building spatial temporal models to characterize sound levels across the frequency spectrum using an elastic net approach can be a promising tool for noise exposure assessments within the urban soundscape. Models of sound's character may give us additional important sound exposure metrics to be utilized in epidemiological studies. [ABSTRACT FROM AUTHOR]

In recent years, significant attention has been given to polycyclic aromatic hydrocarbons (PAHs) exposures given their mutagenic and carcinogenic properties. However, levels of exposure and the key determinants of exposure are not well defined for the trucking industry. We measured ultrafine particle characteristics at 10 trucking terminals of varying operating size and location in the Northeast region of the United States using particle concentration counter and a surface area analyzer. Multivariate mixed-effects linear regression models were used to assess determinants of the concentration of total bound PAHs (tPAH), the total aerosol active surface area (AS), and the ratio tPAH/AS overall and individually within docks, trucking cabs, and administrative offices. Associations between PAH measures with integrated measures of elemental carbon (EC), organic carbon (OC), and particulate matter (PM)2.5 were assessed by Spearman rank correlation. In adjusted models, tPAH, AS, and tPAH/AS average concentrations (95% confidence interval) were significantly higher in truck cabs compared to office locations (1.26 (ng m-3) (1.18, 1.35); 0.99 (mm² mm-3) (0.91, 1.08); 0.26 (ng mm-2) (0.18, 0.33), respectively). In the loading dock, AS concentrations were significantly higher than in the office (0.67 (0.61, 0.71), while the tPAH/AS was not (-0.63 (-0.67, -0.58). In each location, average tPAH concentrations were moderately but significantly correlated with EC (r = 0.47-0.63) and with tPAH/AS (r = 0.34-0.40) in the truck cabs and loading docks. In conclusion, key predictors of tPAH, AS, and tPAH/AS within the trucking industry are work location (in particular truck cabs and terminal docks) and terminal characteristics (size). The association of tPAH and tPAH/AS with EC concentrations in dockworkers and pick-up and delivery drivers is consistent with occupational exposure attributable to vehicle exhaust. Therefore, measurement of tPAH, AS, and tPAH/AS to characterize ultrafine particles and bound PAH concentrations provide additional information regarding exposures in the trucking industry not captured by integrated measures by EC, OC, and PM2.5. [ABSTRACT FROM AUTHOR]

Introduction: Urban environments are associated with a higher risk of adverse mental health outcomes; however, it is unclear which specific components of the urban environment drive these associations.Methods: Using data collected in 2002-2009 from 73,225 low-income, racially diverse individuals across the Southeastern U.S., analyses evaluated the cross-sectional relationship between a walkability index and depression. Walkability was calculated from population density, street connectivity, and destination count in the 1,200-meter area around participants' homes, and depression was measured using the Center for Epidemiologic Studies Depression Scale for depression symptomatology and questionnaire responses regarding doctor-diagnosed depression and antidepressant use. Data were analyzed in 2015.Results: Participants living in neighborhoods with the highest walkability index had 6% higher odds of moderate or greater depression symptoms (score ≥15, 95% CI=0.99, 1.14), 28% higher odds of doctor-diagnosed depression (95% CI=1.20, 1.36), and 16% higher odds of current antidepressant use (95% CI=1.08, 1.25), compared with those in the lowest walkability index. Higher walkability was associated with higher odds of depression symptoms in the most deprived neighborhoods only, whereas walkability was associated with lower odds of depression symptoms in the least deprived neighborhoods.Conclusions: Living in a more walkable neighborhood was associated with modestly higher levels of doctor-diagnosed depression and antidepressant use, and walkability was associated with greater depression symptoms in neighborhoods with higher deprivation. Although dense urban environments may provide opportunities for physical activity, they may also increase exposure to noise, air pollution, and social stressors that could increase levels of depression. [ABSTRACT FROM AUTHOR]

Background: Ultraviolet B (UV-B) radiation plays a multifaceted role in human health, inducing DNA damage and representing the primary source of vitamin D for most humans; however, current U.S. UV exposure models are limited in spatial, temporal, and/or spectral resolution. Area-to-point (ATP) residual kriging is a geostatistical method that can be used to create a spatiotemporal exposure model by downscaling from an area- to point-level spatial resolution using fine-scale ancillary data. Methods: A stratified ATP residual kriging approach was used to predict average July noon-time erythemal UV (UVEry) (mW/m2) biennially from 1998 to 2012 by downscaling National Aeronautics and Space Administration (NASA) Total Ozone Mapping Spectrometer (TOMS) and Ozone Monitoring Instrument (OMI) gridded remote sensing images to a 1 km spatial resolution. Ancillary data were incorporated in random intercept linear mixedeffects regression models. Modeling was performed separately within nine U.S. regions to satisfy stationarity and account for locally varying associations between UVEry and predictors. Cross-validation was used to compare ATP residual kriging models and NASA grids to UV-B Monitoring and Research Program (UVMRP) measurements (gold standard). Results: Predictors included in the final regional models included surface albedo, aerosol optical depth (AOD), cloud cover, dew point, elevation, latitude, ozone, surface incoming shortwave flux, sulfur dioxide (SO2), year, and interactions between year and surface albedo, AOD, cloud cover, dew point, elevation, latitude, and SO2. ATP residual kriging models more accurately estimated UVEry at UVMRP monitoring stations on average compared to NASA grids across the contiguous U.S. (average mean absolute error [MAE] for ATP, NASA: 15.8, 20.3; average root mean square error [RMSE]: 21.3, 25.5). ATP residual kriging was associated with positive percent relative improvements in MAE (0.6-31.5%) and RMSE (3.6-29.4%) across all regions compared to NASA grids. Conclusions: ATP residual kriging incorporating fine-scale spatial predictors can provide more accurate, high-resolution UVEry estimates compared to using NASA grids and can be used in epidemiologic studies examining the health effects of ambient UV. [ABSTRACT FROM AUTHOR]

Background: Exposure to air pollution, including traffic-related pollutants, has been associated with a variety of adverse health outcomes, including increased cardiopulmonary morbidity and mortality, and increased lung cancer risk. Methods: To better understand the cellular responses induced by air pollution exposures, we performed genomewide gene expression microarray analysis using whole blood RNA sampled at three time-points across the work weeks of 63 non-smoking employees at 10 trucking terminals in the northeastern US. We defined genes and gene networks that were differentially activated in response to PM2.5 (particulate matter ≤ 2.5 microns in diameter) and elemental carbon (EC) and organic carbon (OC). Results: Multiple transcripts were strongly associated (padj < 0.001) with pollutant levels (48, 260, and 49 transcripts for EC, OC, and PM2.5, respectively), including 63 that were statistically significantly correlated with at least two out of the three exposures. These genes included many that have been implicated in ischemic heart disease, chronic obstructive pulmonary disease (COPD), lung cancer, and other pollution-related illnesses. Through the combination of Gene Set Enrichment Analysis and network analysis (using GeneMANIA), we identified a core set of 25 interrelated genes that were common to all three exposure measures and were differentially expressed in two previous studies assessing gene expression attributable to air pollution. Many of these are members of fundamental cancer-related pathways, including those related to DNA and metal binding, and regulation of apoptosis and also but include genes implicated in chronic heart and lung diseases. Conclusions: These data provide a molecular link between the associations of air pollution exposures with health effects. [ABSTRACT FROM AUTHOR]

BACKGROUND: Green, natural environments may ameliorate adverse environmental exposures (e.g., air pollution, noise, and extreme heat), increase physical activity and social engagement, and lower stress. OBJECTIVES: We aimed to examine the prospective association between residential greenness and mortality. METHODS: Using data from the U.S.-based Nurses' Health Study prospective cohort, we defined cumulative average time-varying seasonal greenness surrounding each participant's address using satellite imagery [Normalized Difference Vegetation Index (NDVI)]. We followed 108,630 women and observed 8,604 deaths between 2000 and 2008. RESULTS: In models adjusted for mortality risk factors (age, race/ethnicity, smoking, and individual-and area-level socioeconomic status), women living in the highest quintile of cumulative average greenness (accounting for changes in residence during follow-up) in the 250-m area around their home had a 12% lower rate of all-cause nonaccidental mortality [95% confidence interval (CI); 0.82, 0.94] than those in the lowest quintile. The results were consistent for the 1,250-m area, although the relationship was slightly attenuated. These associations were strongest for respiratory and cancer mortality. The findings from a mediation analysis suggested that the association between greenness and mortality may be at least partly mediated by physical activity, particulate matter < 2.5 µm, social engagement, and depression. CONCLUSIONS: Higher levels of green vegetation were associated with decreased mortality. Policies to increase vegetation may provide opportunities for physical activity, reduce harmful exposures, increase social engagement, and improve mental health. Planting vegetation may mitigate the effects of climate change; in addition, evidence of an association between vegetation and lower mortality rates suggests it also might be used to improve health. [ABSTRACT FROM AUTHOR]

Systemic inflammation may serve as a biological mechanism linking air pollution to poor health but supporting evidence from studies of long-term pollutant exposure and inflammatory cytokines is inconsistent. We studied associations between multiple particulate matter (PM) and gaseous air pollutants and pro- and anti-inflammatory cytokines within two nationwide cohorts of men and women. Data were obtained from 16,151 women in the Nurses' Health Study and 7,930 men in the Health Professionals' Follow-up Study with at least one measure of circulating adiponectin, C-Reactive Protein (CRP), Interleukin-6 (IL-6) or soluble tumor necrosis-factor receptor-2 (sTNFR-2). Exposure to PM with aerodynamic diameter ≤2.5, 2.5–10, and ≤10 μm (PM 2.5 , PM 2.5 - 10 , PM 10) and nitrogen dioxide (NO 2) was estimated using spatio-temporal models and were linked to participants' addresses at the time of blood draw. Averages of the 1-, 3-, and 12-months prior to blood draw were examined. Associations between each biomarker and pollutant were estimated from linear regression models adjusted for individual and contextual covariates. In adjusted models, we observed a 2.72% (95% CI: 0.43%, 5.95%), 3.11% (−0.12%, 6.45%), and 3.67% (0.19%, 7.26%) increase in CRP associated with a 10 μg/m3 increase in 1-, 3-, and 12- month averaged NO 2 in women. Among men, there was a statistically significant 5.96% (95% CI: 0.07%, 12.20%), 6.99% (95% CI: 0.29%, 14.15%), and 8.33% (95% CI: 0.35%, 16.94%) increase in CRP associated with a 10 μg/m3 increase in 1-, 3-, and 12-month averaged PM 2.5-10 , respectively. Increasing PM 2.5-10 was associated with increasing IL-6 and sTNFR-2 among men over shorter exposure durations. There were no associations with exposures to PM 2.5 or PM 10 , or with adiponectin. Findings were robust to sensitivity analyses restricting to disease-free controls and non-movers. Across multiple long-term pollutant exposures and inflammatory markers, associations were generally weak. Focusing on specific pollutant-inflammatory mechanisms may clarify pathways. • Evidence of long-term impacts of pollutants on inflammation is mixed. • Blood inflammation markers were assessed in two nationwide cohorts. • Modeled pollutant estimates were linked to addresses within 12-months of blood draw. • Higher NO 2 exposure was associated with increasing CRP in women. • Higher PM 2.5-10 exposure was suggestively associated with increasing CRP in men. [ABSTRACT FROM AUTHOR]

BACKGROUND: Pulmonary embolism (PE) is the most serious manifestation of venous thromboembolism and a leading cause of sudden death. Several studies have suggested associations of venous thromboembolism with short-term particulate matter (PM) exposure; evidence on long-term PM and traffic exposure is mixed. OBJECTIVES: We examined the association of long-term exposure to PM2.5, PM2.5-10, and PM10 (PM with diameter of ≤ 2.5, 2.5-10, and < 10 μm) and distance to roadways with overall incident PE and with PE subtypes in a cohort of U.S. women. METHODS: The study included 115,745 women from the Nurses' Health Study, followed from 1992 through 2008. Incident PE cases were self-reported biennially. Nonidiopathic PE were cases for which the medical record revealed an underlying health condition related to PE (i.e., surgery, trauma, or malignancy); idiopathic PE were cases with no such history. We used spatiotemporal models combining spatial smoothing and geographic covariates to quantify exposure at residential addresses, and Cox proportional hazards models to calculate hazard ratios (HR) and 95% confidence intervals (CIs). RESULTS: PM2.5 averaged over 1 month (HR = 1.22; 95% CI: 1.04, 1.44) or 12 months (HR = 1.17; 95% CI: 0.93, 1.48) was associated with incident PE, after adjusting for known risk factors and PM2.5-10. Equivalent analyses restricted to PE subtypes showed a positive association for PM2.5 with nonidiopathic PE, but not with idiopathic PE. We did not find evidence of an association between distance to roadways and PE risk. CONCLUSIONS: We provide evidence that PM in the prior 1 and 12 months is associated with PE risk. Our results also suggest that women with underlying health conditions may be more susceptible to PE after PM exposure. [ABSTRACT FROM AUTHOR]

Background Features of neighborhoods associated with walkability (i.e., connectivity, accessibility, and density) may also be correlated with levels of ambient air pollution, which would attenuate the health benefits of walkability. Objectives We examined the relationship between neighborhood walkability and ambient air pollution in a cross-sectional analysis of a cohort study spanning the entire United States using residence-level exposure assessment for ambient air pollution and the built environment. Methods Using data from the Nurses’ Health Study, we used linear regression to estimate the association between a neighborhood walkability index, combining neighborhood intersection count, business count, and population density (defined from Census data, info USA business data, and StreetMap USA data), and air pollution, defined from a GIS-based spatiotemporal PM 2.5 model. Results After adjustment for Census tract median income, median home value, and percent with no high school education, the highest tertile of walkability index, intersection count, business count, and population density was associated with a with 1.58 (95% CI 1.54, 1.62), 1.20 (95% CI 1.16, 1.24), 1.31 (95% CI 1.27, 1.35), and 1.84 (95% CI 1.80, 1.88) µg/m 3 higher level of PM 2.5 respectively, compared to the lowest tertile. Results varied somewhat by neighborhood socioeconomic status and greatly by region. Conclusions This nationwide analysis showed a positive relationship between neighborhood walkability and modeled air pollution levels, which were consistent after adjustment for neighborhood-level socioeconomic status. Regional differences in the air pollution-walkability relationship demonstrate that there are factors that vary from region to region that allow for walkable neighborhoods with low levels of air pollution. [ABSTRACT FROM AUTHOR]

Background: The International Agency for Research on Cancer (IARC) recently declared air pollution carcinogenic to humans. However, no study of air pollution and lung cancer to date has incorporated adjustment for exposure measurement error, and few have examined specific histological subtypes. Objectives: Our aim was to assess the association of air pollution and incident lung cancer in the Netherlands Cohort Study on Diet and Cancer and the impact of measurement error on these associations. Methods: The cohort was followed from 1986 through 2003, and 3,355 incident cases were identified. Cox proportional hazards models were used to estimate hazard ratios and 95% confidence intervals, for long-term exposures to nitrogen dioxide (NO2), black smoke (BS), PM2.5 (particulate matter with diameter ≤ 2.5 μm), and measures of roadway proximity and traffic volume, adjusted for potential confounders. Information from a previous validation study was used to correct the effect estimates for measurement error. Results: We observed elevated risks of incident lung cancer with exposure to BS [hazard ratio (HR) = 1.16; 95% CI: 1.02, 1.32, per 10 μg/m3], NO2 (HR = 1.29; 95% CI: 1.08, 1.54, per 30 μg/m3), PM2.5 (HR = 1.17; 95% CI: 0.93, 1.47, per 10 μg/m3), and with measures of traffic at the baseline address. The exposures were positively associated with all lung cancer subtypes. After adjustment for measurement error, the HRs increased and the 95% CIs widened [HR = 1.19 (95% CI: 1.02, 1.39) for BS and HR = 1.37 (95% CI: 0.86, 2.17) for PM2.5]. Conclusions: These findings add support to a growing body of literature on the effects of air pollution on lung cancer. In addition, they highlight variation in measurement error by pollutant and support the implementation of measurement error corrections when possible. [ABSTRACT FROM AUTHOR]

Background: Epidemiologic studies of postnatal PCB exposure and behavior have not reported consistent evidence of adverse associations, possibly because of challenges in exposure estimation. We previously developed a pharmacokinetic model to improve estimation of children's PCB exposure. Objectives: We aimed to assess whether estimated serum PCB levels in infancy are associated with attention deficit/hyperactivity disorder (ADHD)-related behaviors at 8 years of age among children whose cord serum PCB levels were previously shown to be associated with ADHDrelated behaviors. Methods: We used a pharmacokinetic model to estimate monthly serum polychlorinated biphenyl (PCB)-153 levels in 441 infants (ages 1-12 months) based on parameters such as breastfeeding and cord serum PCB‑153 levels. Behavior was evaluated at age 8 using the Conners' Rating Scale for Teachers (CRS-T). Associations between PCB‑153 levels and ADHD-related CRS-T indices were assessed using multivariable quantile regression at the 50th and 75th percentiles of CRS-T scores, where higher percentiles reflect more adverse behaviors. Results: Cord serum PCB-153 levels (median, 38 ng/g lipids) were associated with ADHD-related behaviors, although statistical significance was observed with quantile regression models only at the 75th percentile. Associations with postnatal exposure estimates were attenuated. For example, hyperactive-impulsive behavior scores at age 8 years were 0.9 points (95% CI: 0.2, 2.5), 0.5 points (95% CI: 0.3, 2.3), and 0.3 points (95% CI: -0.2, 1.5) higher in association with interquartile range increases in serum PCB-153 at birth, 2 months, and 12 months of age, respectively. Conclusions: Associations between estimated postnatal PCB-153 exposures and ADHD-related behaviors at 8 years of age were weaker than associations with PCB-153 concentrations measured in cord serum at birth. [ABSTRACT FROM AUTHOR]

• Neighborhood socioeconomic status is associated with lower inflammation. • Concentration of high-income residents is associated with lower inflammation. • Higher neighborhood greenness is associated with lower inflammation in women. • Neighborhood context may affect inflammation independently of lifestyles. Neighborhood deprivation is linked with inflammation, which may explain poorer health across populations. Behavioral risk factors are assumed to largely mediate these relationships, but few studies have examined this. We examined three neighborhood contextual factors that could exert direct effects on inflammation: (1) neighborhood socioeconomic status, (2) an index of concentration at extremes (that measures segregation), and (3) surrounding vegetation (greenness). Using blood samples and addresses collected from prospective cohorts of 7,930 male (1990–1994) and 16,183 female (1986–1990) health professionals with at least one inflammatory marker, we prospectively linked neighborhood contextual factors to inflammatory biomarkers (adiponectin, C-reactive protein, interleukin-6, soluble tumor necrosis factor receptor-2). Log-transformed, z-scaled component measures were used to calculate an inflammation score. Neighborhood socioeconomic status and index of concentration of extremes were obtained from the 1990 decennial census and linked to participant addresses. Surrounding greenness was assessed from satellite data and focal statistics were applied to generate exposures within 270 m and 1230 m of the participants' address. We fit multiple linear regression models adjusting for demographic, clinical, and behavioral risk factors. Higher neighborhood socioeconomic status was associated with lower inflammation score in women (β for interquartile range increase = −27.7%, 95% CI: −34.9%, −19.8%) and men (β = −21.2%, 95% CI: −31.0%, −10.1%). Similarly, participants in neighborhoods with higher concentrations of high-income households were associated with lower inflammation score in women (β = −27.8%, 95% CI: −35.8%, −18.7%) and men (β = -16.4%, 95% CI: −29.7%, −0.56%). Surrounding greenness within 270 m of each participant's address was associated with lower inflammation score in women (β = -18.9%, 95% CI: −28.9%, −7.4%) but not men. Results were robust to sensitivity analyses to assess unmeasured confounding and selection bias. Our findings support the hypothesis that adverse neighborhood environments may contribute to inflammation through pathways independent of behavioral risk factors, including psychosocial stress and toxic environments. [ABSTRACT FROM AUTHOR]

Background: Long-term exposure to particulate matter less than 2.5 μm in diameter (PM2.5) has been consistently associated with risk of all-cause mortality. The methods used to assess exposure, such as area averages, nearest monitor values, land use regressions, and spatio-temporal models in these studies are subject to measurement error. However, to date, no study has attempted to incorporate adjustment for measurement error into a long-term study of the effects of air pollution on mortality. Methods: We followed 108,767 members of the Nurses' Health Study (NHS) 2000-2006 and identified all deaths. Biennial mailed questionnaires provided a detailed residential address history and updated information on potential confounders. Time-varying average PM2.5 in the previous 12-months was assigned based on residential address and was predicted from either spatio-temporal prediction models or as concentrations measured at the nearest USEPA monitor. Information on the relationships of personal exposure to PM2.5 of ambient origin with spatio-temporal predicted and nearest monitor PM2.5 was available from five previous validation studies. Time-varying Cox proportional hazards models were used to estimate hazard ratios (HRs) and 95 percent confidence intervals (95%CI) for each 10 μg/m3 increase in PM2.5. Risk-set regression calibration was used to adjust estimates for measurement error. Results: Increasing exposure to PM2.5 was associated with an increased risk of mortality, and results were similar regardless of the method chosen for exposure assessment. Specifically, the multivariable adjusted HRs for each 10 μg/m3 increase in 12-month average PM2.5 from spatio-temporal prediction models were 1.13 (95%CI:1.05, 1.22) and 1.12 (95%CI:1.05, 1.21) for concentrations at the nearest EPA monitoring location. Adjustment for measurement error increased the magnitude of the HRs 4-10% and led to wider CIs (HR = 1.18; 95%CI: 1.02, 1.36 for each 10 μg/m3 increase in PM2.5 from the spatio-temporal models and HR = 1.22; 95%CI: 1.02, 1.45 from the nearest monitor estimates). Conclusions: These findings support the large body of literature on the adverse effects of PM2.5, and suggest that adjustment for measurement error be considered in future studies where possible. [ABSTRACT FROM AUTHOR]

Background: Sudden cardiac death (SCD) is a major source of mortality and is the first manifestation of heart disease for the majority of cases. Thus, there is a definite need to identify risk factors for SCD that can be modified at the population level. Exposure to traffic, measured by residential roadway proximity, has been shown to be associated with an increased risk of cardiovascular disease. Our objective was to determine whether roadway proximity was associated with an increased risk of SCD and to compare that risk with the risk of other coronary heart disease outcomes.Methods and Results: A total of 523 cases of SCD were identified over 26 years of follow-up among 107 130 members of the prospective Nurses' Health Study. We calculated residential distance to roadways at all residential addresses from 1986 to 2012. In age- and race-adjusted models, women living within 50 m of a major roadway had an elevated risk of SCD (hazard ratio=1.56; 95% confidence interval, 1.18-2.05). The association was attenuated but still statistically significant after controlling for potential confounders and mediators (hazard ratio=1.38; 95% confidence interval, 1.04-1.82). The equivalent adjusted hazard ratios for nonfatal myocardial infarction and fatal coronary heart disease were 1.08 (95% confidence interval, 0.96-1.23) and 1.24 (95% confidence interval, 1.03-1.50), respectively.Conclusions: Among this sample of middle-aged and older women, roadway proximity was associated with elevated and statistically significant risks of SCD and fatal coronary heart disease, even after controlling for other cardiovascular risk factors. [ABSTRACT FROM AUTHOR]

Background--Sudden cardiac death (SCD) is a major source of mortality and is the first manifestation of heart disease for the majority of cases. Thus, there is a definite need to identify risk factors for SCD that can be modified at the population level. Exposure to traffic, measured by residential roadway proximity, has been shown to be associated with an increased risk of cardiovascular disease. Our objective was to determine whether roadway proximity was associated with an increased risk of SCD and to compare that risk with the risk of other coronary heart disease outcomes. Methods and Results--A total of 523 cases of SCD were identified over 26 years of follow-up among 107 130 members of the prospective Nurses' Health Study. We calculated residential distance to roadways at all residential addresses from 1986 to 2012. In age- and race-adjusted models, women living within 50 m of a major roadway had an elevated risk of SCD (hazard ratio=1.56; 95% confidence interval, 1.18-2.05). The association was attenuated but still statistically significant after controlling for potential confounders and mediators (hazard ratio=1.38; 95% confidence interval, 1.04-1.82). The equivalent adjusted hazard ratios for nonfatal myocardial infarction and fatal coronary heart disease were 1.08 (95% confidence interval, 0.96-1.23) and 1.24 (95% confidence interval, 1.03-1.50), respectively. Conclusions--Among this sample of middle-aged and older women, roadway proximity was associated with elevated and statistically significant risks of SCD and fatal coronary heart disease, even after controlling for other cardiovascular risk factors. [ABSTRACT FROM AUTHOR]

Background: A body of literature has suggested an elevated risk of lung cancer associated with particulate matter and traffic-related pollutants. Objective: We examined the relation of lung cancer incidence with long-term residential exposures to ambient particulate matter and residential distance to roadway, as a proxy for traffic-related exposures. Methods: For participants in the Nurses’ Health Study, a nationwide prospective cohort of women, we estimated 72‑month average exposures to PM2.5, PM2.5–10, and PM10 and residential distance to road. Follow-up for incident cases of lung cancer occurred from 1994 through 2010. Cox proportional hazards models were adjusted for potential confounders. Effect modification by smoking status was examined. Results: During 1,510,027 person-years, 2,155 incident cases of lung cancer were observed among 103,650 participants. In fully adjusted models, a 10‑μg/m3 increase in 72‑month average PM10 [hazard ratio (HR) = 1.04; 95% CI: 0.95, 1.14], PM2.5 (HR = 1.06; 95% CI: 0.91, 1.25), or PM2.5-10 (HR = 1.05; 95% CI: 0.92, 1.20) was positively associated with lung cancer. When the cohort was restricted to never-smokers and to former smokers who had quit at least 10 years before, the associations appeared to increase and were strongest for PM2.5 (PM10: HR = 1.15; 95% CI: 1.00, 1.32; PM2.5: HR = 1.37; 95% CI: 1.06, 1.77; PM2.5-10: HR = 1.11; 95% CI: 0.90, 1.37). Results were most elevated when restricted to the most prevalent subtype, adenocarcinomas. Risks with roadway proximity were less consistent. Conclusions: Our findings support those from other studies indicating increased risk of incident lung cancer associated with ambient PM exposures, especially among never- and long-term former smokers. [ABSTRACT FROM AUTHOR]

[Display omitted] • Diesel exhaust pollutants were evaluated for workers in the US trucking industry. • Metabolomic alterations were associated with elemental carbon and organic carbon. • No metabolites were associated with PM 2.5 exposure. • Exposure-associated metabolites were related to oxidative stress and nitric oxide production. • Gene and metabolite networks support associations with cardiopulmonary disease. Exposure to traffic-related pollutants, including diesel exhaust, is associated with increased risk of cardiopulmonary disease and mortality; however, the precise biochemical pathways underlying these effects are not known. To investigate biological response mechanisms underlying exposure to traffic related pollutants, we used an integrated molecular response approach that included high-resolution metabolomic profiling and peripheral blood gene expression to identify biological responses to diesel exhaust exposure. Plasma samples were collected from 73 non-smoking males employed in the US trucking industry between February 2009 and October 2010, and analyzed using untargeted high-resolution metabolomics to characterize metabolite associations with shift- and week-averaged levels of elemental carbon (EC), organic carbon (OC) and particulate matter with diameter ≤ 2.5 μm (PM 2.5). Metabolic associations with EC, OC and PM 2.5 were evaluated for biochemical processes known to be associated with disease risk. Annotated metabolites associated with exposure were then tested for relationships with the peripheral blood transcriptome using multivariate selection and network correlation. Week-averaged EC and OC levels, which were averaged across multiple shifts during the workweek, resulted in the greatest exposure-associated metabolic alterations compared to shift-averaged exposure levels. Metabolic changes associated with EC exposure suggest increased lipid peroxidation products, biomarkers of oxidative stress, thrombotic signaling lipids, and metabolites associated with endothelial dysfunction from altered nitric oxide metabolism, while OC exposures were associated with antioxidants, oxidative stress biomarkers and critical intermediates in nitric oxide production. Correlation with whole blood RNA gene expression provided additional evidence of changes in processes related to endothelial function, immune response, inflammation, and oxidative stress. We did not detect metabolic associations with PM 2.5. This study provides an integrated molecular assessment of human exposure to traffic-related air pollutants that includes diesel exhaust. Metabolite and transcriptomic changes associated with exposure to EC and OC are consistent with increased risk of cardiovascular diseases and the adverse health effects of traffic-related air pollution. [ABSTRACT FROM AUTHOR]

Solar ultraviolet radiation (UV) is a critical environmental factor for dermal conversion of vitamin D, which is suggested to support reproductive health. However, current epidemiological studies have reported conflicting results on the associations between vitamin D levels and ovarian reserve. Further, few studies have considered UV exposure and reproductive aging, which is closely related to declined ovarian reserve. We sought to examine the associations of long-term UV exposure and age at natural menopause in a large, nationwide, prospective cohort. Participants in the Nurses' Health Study II (NHS II) who were premenopausal at age 40 were included and followed through 2015. Erythemal UV radiation from a high-resolution geospatial model was linked to the participants' residential histories. Early-life UV was estimated using the reported state of residence at birth, age 15, and age 30. We used time-varying Cox proportional hazards models to estimate the hazard ratio (HR) and 95% confidence intervals (CIs) for natural menopause, adjusting for potential confounders and predictors of menopause. A total of 63,801 women reported natural menopause across the 1,051,185 person-years of follow-up among 105,631 eligible participants. We found very modest associations with delayed menopause for long-term UV exposure (adjusted HR comparing highest to lowest quartile of cumulative average UV: 0.96, 95% CI: 0.94, 0.99). There was a suggestive inverse association between UV at age 30 with menopause (adjusted HR comparing highest to lowest quartile: 0.97, 95% CI: 0.95, 1.00) but not with UV at birth and age 15. Solar UV exposure in adulthood was modestly associated with later onset of menopause. Although consistent with previous findings on vitamin D intake and menopause in the same population, these weak associations found in this study may not be of clinical relevance. [ABSTRACT FROM AUTHOR]

Previous studies evaluating the association of prenatal exposure to diethylstilbestrol (DES), a potent endocrine disruptor, with incidence of uterine leiomyomata (UL) have had conflicting results. We evaluated the association between prenatal DES exposure and incident UL in women in the Nurses' Health Study II from 1989 to 2009. Women were aged 25–42 years at enrollment and had a prenatal exposure window corresponding to DES use. The analytical sample was larger than previous studies and included 102,164 premenopausal women with intact uteri, no prior history of UL or cancer, and prenatal DES exposure. Multivariable-adjusted Cox proportional hazard models were used to estimate the relationship between DES exposure and UL risk. During 1,273,342 person-years of follow-up, there were 11,831 incident cases of UL. Women with prenatal exposure to DES had a higher incidence of UL compared with unexposed women, with an adjusted hazard ratio of 1.12 (95% confidence interval: 0.98, 1.27). Risk was strongest for women exposed to DES in the first trimester, when exposure corresponds to early stages of fetal Müllerian development (adjusted hazard ratio = 1.21, 95% confidence interval: 1.02, 1.43). These results suggest that first-trimester DES exposure may be associated with an increased risk of UL, but they must be interpreted with concern for detection and recall biases. [ABSTRACT FROM AUTHOR]

Background: Particulate matter and proximity to large roadways may promote disease mechanisms, including systemic inflammation, hormonal alteration, and vascular proliferation, that may contribute to the development and severity of endometriosis. Objective: Our goal was to determine the association of air pollution exposures during adulthood, including distance to road, particulate matter < 2.5 μm, between 2.5 and 10 μm, and < 10 μm, (PM2.5, PM10-2.5, PM10), and timing of exposure with risk of endometriosis in the Nurses' Health Study II. Methods: Proximity to major roadways and outdoor levels of PM2.5, PM10-2.5, and PM10 were determined for all residential addresses from 1993 to 2007. Multivariable-adjusted time-varying Cox proportional hazard models were used to estimate the relation between these air pollution exposures and endometriosis risk. Results: Among 84,060 women, 2,486 incident cases of surgically confirmed endometriosis were identified over 710,230 person-years of follow-up. There was no evidence of an association between endometriosis risk and distance to road or exposure to PM2.5, PM10-2.5, or PM10 averaged over follow-up or during the previous 2- or 4-year period. Conclusions: Traffic and air pollution exposures during adulthood were not associated with incident endometriosis in this cohort of women. [ABSTRACT FROM AUTHOR]

• PM 2.5 and NO 2 were positively associated with CVD hospitalization. • Ozone was only positively associated with CVD hospitalization at low exposure levels. • Associations of PM 2.5 were stronger with higher greenness. • Associations of PM 2.5 were stronger with lower temperature, specific humidity and O x. Studies have observed associations between long-term air pollution and cardiovascular disease hospitalization. Little is known, however, about effect modification of these associations by greenness, temperature and humidity. We constructed an open cohort consisting of all fee-for-service Medicare beneficiaries, aged ≥ 65, living in the contiguous US from 2000 through 2016 (~63 million individuals). We assigned annual average PM 2.5 , NO 2 and ozone zip code concentrations. Cox-equivalent Poisson models were used to estimate associations with first cardiovascular disease (CVD), coronary heart disease (CHD) and cerebrovascular disease (CBV) hospitalization. PM 2.5 and NO 2 were both positively associated with CVD, CHD and CBV hospitalization, after adjustment for potential confounders. Associations were substantially stronger at the lower end of the exposure distributions. For CVD hospitalization, the hazard ratio (HR) of PM 2.5 was 1.041 (1.038, 1.045) per IQR increase (4.0 µg/m3) in the full study population and 1.327 (1.305, 1.350) per IQR increase for a subgroup with annual exposures always below 10 µg/m3 PM 2.5. Ozone was only positively associated with CVD, CHD and CBV hospitalization for the low-exposure subgroup (<40 ppb). Associations of PM 2.5 were stronger in areas with higher greenness, lower ozone and O x , lower summer and winter temperature and lower summer and winter specific humidity. PM 2.5 and NO 2 were positively associated with CVD, CHD and CBV hospitalization. Associations were more pronounced at low exposure levels. Associations of PM 2.5 were stronger with higher greenness, lower ozone and O x , lower temperature and lower specific humidity. [ABSTRACT FROM AUTHOR]

Background: Experimental evidence suggests that inhaled particles from vehicle exhaust have systemic effects on inflammation, endothelial activation and oxidative stress. In the present study we assess the relationships of short-term exposures with inflammatory endothelial activation and oxidative stress biomarker levels in a population of trucking industry workers.Methods: Blood and urine samples were collected pre and post-shift, at the beginning and end of a workweek from 67 male non-smoking US trucking industry workers. Concurrent measurements of microenvironment concentrations of elemental and organic carbon (EC & OC), and fine particulate matter (PM2.5) combined with time activity patterns allowed for calculation of individual exposures. Associations between daily and first and last-day average levels of exposures and repeated measures of intercellular and vascular cell adhesion molecule-1 (ICAM-1 & VCAM-1), interleukin 6 (IL-6) and C-reactive protein (CRP) blood levels and urinary 8-Hydroxy-2'-Deoxyguanosine (8-OHdG) were assessed using linear mixed effects models for repeated measures.Results: There was a statistically significant association between first and last-day average PM2.5 and 8-OHdG (21% increase, 95% CI: 2, 42%) and first and last-day average OC and IL-6 levels (18% increase 95% CI: 1, 37%) per IQR in exposure. There were no significant findings associated with EC or associations suggesting acute cross-shift effects.Conclusion: Our findings suggest associations between weekly average exposures of PM2.5 on markers of oxidative stress and OC on IL-6 levels. [ABSTRACT FROM AUTHOR]

BACKGROUND: The association of all-cause mortality and cardiovascular outcomes with air pollution exposures has been well established in the literature. The number of studies examining chronic exposures in cohorts is growing, with more recent studies conducted among women finding risk estimates of greater magnitude. Questions remain regarding sex differences in the relationship of chronic particulate matter (PM) exposures with mortality and cardiovascular outcomes. OBJECTIVES: In this study we explored these associations in the all-male Health Professionals Follow-Up Study prospective cohort. METHODS: The same spatiotemporal exposure estimation models, similar outcomes, and biennially updated covariates were used as those previously applied in the female Nurses' Health Study cohort. RESULTS: Among 17,545 men residing in the northeastern and midwestern United States, there were 2,813 deaths, including 746 cases of fatal coronary heart disease (CHD). An interquartile range change (4 µg/m3) in average exposure to PM ≤ 2.5 µm in diameter in the 12 previous months was not associated with all-cause mortality [hazard ratio (HR) = 0.94; 95% confidence interval (CI), 0.87-1.00] or fatal CHD (HR = 0.99; 95% CI, 0.87-1.13) in fully adjusted models. Findings were similar for separate models of exposure to PM ≤10 µm in diameter and PM between 2.5 and 10 µm in diameter and for copollutant models. CONCLUSIONS: Among this cohort of men with high socioeconomic status living in the midwestern and northeastern United States, the results did not support an association of chronic PM exposures with all-cause mortality and cardiovascular outcomes in models with time-varying covariates. Whether these findings suggest sex differences in susceptibility or the protective impact of healthier lifestyles and higher socioeconomic status requires additional investigation. [ABSTRACT FROM AUTHOR]

BACKGROUND: Despite considerable epidemiologic evidence about the health effects of chronic exposure to vehicle exhaust, efforts at defining the extent of risk have been limited by the lack of historical exposure measurements suitable for use in epidemiologic studies and for risk assessment. OBJECTIVES: We sought to reconstruct exposure to elemental carbon (EC), a marker of diesel and other vehicle exhaust exposure, in a large national cohort of U.S. trucking industry workers. METHODS: We identified the predictors of measured exposures based on a statistical model and used this information to extrapolate exposures across the cohort nationally. These estimates were adjusted for changes in work-related conditions over time based on a previous exposure assessment of this industry, and for changes in background levels based on a trend analysis of historical air pollution data, to derive monthly estimates of EC exposure for each job and trucking terminal combination between 1971 and 2000. RESULTS: Occupational exposure to EC declined substantially over time, and we found significant variability in estimated exposures both within and across job groups, trucking terminals, and regions of the United States. Average estimated EC exposures during a typical work shift ranged from < 1 µg/m3 in the lowest exposed category in the 1990s to > 40 &micro:g/m3 for workers in the highest exposed jobs in the 1970s. CONCLUSIONS: Our results provide a framework for understanding changes over time in exposure to EC in the U.S. trucking industry. Our assessment should minimize exposure misclassification by capturing variation among terminals and across U.S. regions, and changes over time. [ABSTRACT FROM AUTHOR]

Background: The etiology of rheumatoid arthritis (RA) remains largely unknown, although epidemiologic studies suggest genetic and environmental factors may play a role. Geographic variation in incident RA has been observed at the regional level. Objective: Spatial analyses are a useful tool for confirming existing exposure hypotheses or generating new ones. To further explore the association between location and RA risk, we analyzed individuallevel data from U.S. women in the Nurses' Health Study, a nationwide cohort study. Methods: Participants included 461 incident RA cases and 9,220 controls with geocoded addresses; participants were followed from 1988 to 2002. We examined spatial variation using addresses at baseline in 1988 and at the time of case diagnosis or the censoring of controls. Generalized additive models (GAMs) were used to predict a continuous risk surface by smoothing on longitude and latitude while adjusting for known risk factors. Permutation tests were conducted to evaluate the overall importance of location and to identify, within the entire study area, those locations of statistically significant risk. Results: A statistically significant area of increased RA risk was identified in the northeast United States (p-value = 0.034). Risk was generally higher at northern latitudes, and it increased slightlywhen we used the nurses' 1988 locations compared with those at the time of diagnosis or censoring. Crude and adjusted models produced similar results. Conclusions: Spatial analyses suggest women living in higher latitudes may be at greater risk for RA. Further, RA risk may be greater for locations that occur earlier in residential histories. These results illustrate the usefulness of GAM methods in generating hypotheses for future investigation and supporting existing hypotheses. [ABSTRACT FROM AUTHOR]

Background: Although the smoking rate in the United States is declining because of an increase of smoke-free laws, among blue-collar workers it remains higher than that among many other occupational groups. Objectives: We evaluated the factors influencing workplace secondhand smoke (SHS) exposures in the U.S. unionized trucking industry. Method s: From 2003 through 2005, we measured workplace SHS exposure among 203 nonsmoking and 61 smoking workers in 25 trucking terminals. Workers in several job groups wore personal vapor-phase nicotine samplers on their lapels for two consecutive work shifts and completed a workplace SHS exposure questionnaire at the end of the personal sampling. Results: Median nicotine level was 0.87 μg/m³ for nonsmokers and 5.96 μg/m³ for smokers. As expected, smokers experienced higher SHS exposure duration and intensity than did nonsmokers. For nonsmokers, multiple regression analyses indicated that self-reported exposure duration combined with intensity, lack of a smoking policy as reported by workers, having a nondriver job, and lower educational level were independently associated with elevated personal nicotine levels (model R² = 0.52). Nondriver job and amount of active smoking were associated with elevated personal nicotine level in smokers, but self-reported exposure, lack of a smoking policy, and lower educational level were not. Conclusions: Despite movements toward smoke-free laws, this population of blue-collar workers was still exposed to workplace SHS as recently as 2005. The perceived (reported by the workers), rather than the official (reported by the terminal managers), smoking policy was associated with measured SHS exposure levels among the nonsmokers. Job duties and educational level might also be important predictors of workplace SHS exposure. [ABSTRACT FROM AUTHOR]

BACKGROUND: Epidemiologic studies of air pollution have demonstrated a link between long-term air pollution exposures and mortality. However, many have been limited to city-specific average pollution measures or spatial or land-use regression exposure models in small geographic areas. OBJECTIVES: Our objective was to develop nationwide models of annual exposure to particulate matter < 10 μm in diameter (PM10) and nitrogen dioxide during 1985?2000. METHODS: We used generalized additive models (GAMs) to predict annual levels of the pollutants using smooth spatial surfaces of available monitoring data and geographic information system-derived covariates. Model performance was determined using a cross-validation (CV) procedure with 10% of the data. We also compared the results of these models with a commonly used spatial interpolation, inverse distance weighting. RESULTS: For PM10, distance to road, elevation, proportion of low-intensity residential, high-intensity residential, and industrial, commercial, or transportation land use within 1 km were all statistically significant predictors of measured PM10 (model R2 = 0.49, CV R2 = 0.55). Distance to road, population density, elevation, land use, and distance to and emissions of the nearest nitrogen oxides-emitting power plant were all statistically significant predictors of measured NO2 (model R2 = 0.88, CV R2 = 0.90). The GAMs performed better overall than the inverse distance models, with higher CV R2 and higher precision. CONCLUSIONS: These models provide reasonably accurate and unbiased estimates of annual exposures for PM10 and NO2. This approach provides the spatial and temporal variability necessary to describe exposure in studies assessing the health effects of chronic air pollution. [ABSTRACT FROM AUTHOR]

BACKGROUND: The relationship of fine particulate matter < 2.5 μm in diameter (PM2.5) air pollution with mortality and cardiovascular disease is well established, with more recent long-term studies reporting larger effect sizes than earlier long-term studies. Some studies have suggested the coarse fraction, particles between 2.5 and 10 μm (PM10 2.5), may also be important. With respect to mortality and cardiovascular events, questions remain regarding the relative strength of effect sizes for chronic exposure to fine and coarse particles. OBJECTIVES: We examined the relationship of chronic PM2.5 and PM10 2.5 exposures with all-cause mortality and fatal and nonfatal incident coronary heart disease (CHD), adjusting for time-varying covariates. Methods: The current study included women from the Nurses' Health Study living in metropolitan areas of the northeastern and midwestern United States. Follow-up was from 1992 to 2002. We used geographic information systems-based spatial smoothing models to estimate monthly exposures at each participant's residence. RESULTS: We found increased risk of all-cause mortality [hazard ratio (HR), 1.26; 95% confidence interval (CI), 1.02-1.54] and fatal CHD (HR = 2.02; 95% CI, 1.07-3.78) associated with each 10-μg/m3 increase in annual PM2.5 exposure. The association between fatal CHD and PM10 2.5 was weaker. CONCLUSIONS: Our findings contribute to growing evidence that chronic PM2.5 exposure is associated with risk of all-cause and cardiovascular mortality. [ABSTRACT FROM AUTHOR]

Background: Rheumatoid arthritis (RA) is a chronic systemic inflammatory disease that affects approximately 1% of the adult population, and to date, genetic factors explain < 50% of the risk. Particulate air pollution, especially of traffic origin, has been linked to systemic inflammation in many studies. Objectives: We examined the association of distance to road, a marker of traffic pollution exposure, and incidence of RA in a prospective cohort study. Methods: We studied 90,297 U.S. women in the Nurses' Health Study. We used a geographic information system to determine distance to road at the residence in 2000 as a measure of traffic exposure. Using Cox proportional hazard models, we examined the association of distance to road and incident RA (1976-2004) with adjustment for a large number of potential confounders. Results: In models adjusted for age, calendar year, race, cigarette smoking, parity, lactation, menopausal status and hormone use, oral contraceptive use, body mass index, physical activity, and census-tract-level median income and house value, we observed an elevated risk of RA [hazard ratio (HR) = 1.31; 95% confidence interval (CI), 0.98-1.74] in women living within 50 m of a road, compared with those women living 200 m or farther away. We also observed this association in analyses among nonsmokers (HR = 1.62; 95% CI, 1.04-2.52), nonsmokers with rheumatoid factor (RF)-negative RA (HR = 1.77; 95% CI, 0.93-3.38), and nonsmokers with RF-positive RA (HR = 1.51; 95% CI, 0.82-2.77). We saw no elevations in risk in women living 50-200 m from the road. Conclusions: The observed association between exposure to traffic pollution and RA suggests that pollution from traffic in adulthood may be a newly identified environmental risk factor for RA. [ABSTRACT FROM AUTHOR]

COVID-19 is an infectious disease that has killed more than 555,000 people in the US. During a time of social distancing measures and increasing social isolation, green spaces may be a crucial factor to maintain a physically and socially active lifestyle while not increasing risk of infection. We evaluated whether greenness was related to COVID-19 incidence and mortality in the US. We downloaded data on COVID-19 cases and deaths for each US county up through June 7, 2020, from Johns Hopkins University, Center for Systems Science and Engineering Coronavirus Resource Center. We used April–May 2020 Normalized Difference Vegetation Index (NDVI) data, to represent the greenness exposure during the initial COVID-19 outbreak in the US. We fitted negative binomial mixed models to evaluate associations of NDVI with COVID-19 incidence and mortality, adjusting for potential confounders such as county-level demographics, epidemic stage, and other environmental factors. We evaluated whether the associations were modified by population density, proportion of Black residents, median home value, and issuance of stay-at-home orders. An increase of 0.1 in NDVI was associated with a 6% (95% Confidence Interval: 3%, 10%) decrease in COVID-19 incidence rate after adjustment for potential confounders. Associations with COVID-19 incidence were stronger in counties with high population density and in counties with stay-at-home orders. Greenness was not associated with COVID-19 mortality in all counties; however, it was protective in counties with higher population density. Exposures to NDVI were associated with reduced county-level incidence of COVID-19 in the US as well as reduced county-level COVID-19 mortality rates in densely populated counties. • Greenness was inversely associated with county-level COVID-19 incidence. • Associations with COVID-19 incidence were stronger in densely populated counties. • Greenness was associated with county-level mortality in densely populated counties. [ABSTRACT FROM AUTHOR]

BACKGROUND: Occupational and population-based studies have related exposure to fine particulate air pollution, and specifically particulate matter from vehicle exhausts, to cardiovascular diseases and lung cancer OBJECTIVES: We have established a large retrospective cohort to assess mortality in the unionized U.S. trucking industry. To provide insight into mortality patterns associated with job-specific exposures, we examined rates of cause-specific mortality compared with the general U.S. population. METHODS: We used records from four national trucking companies to identify 54,319 male employees employed in 1985. Cause-specific mortality was assessed through 2000 using the National Death Index. Expected numbers of all and cause-specific deaths were calculated stratifying by race, 10-year age group, and calendar period using U.S. national reference rates. Standardized mortality ratios (SMRs) and 95% confidence intervals (CIs) were calculated for the entire cohort and by job title. RESULTS: As expected in a working population, we found a deficit in overall and all-cancer mortality, likely due to the healthy worker effect. In contrast, compared with the general U.S. population, we observed elevated rates for lung cancer, ischemic heart disease, and transport-related accidents. Lung cancer rates were elevated among all drivers (SMR = 1.10; 95% Cl, 1.02-1.19) and dockworkers (SMR = 1.10; 95% Cl, 0.94-1.30); ischemic heart disease was also elevated among these groups of workers [drivers, SMR = 1.49 (95% Cl, 1.40-1.59); dockworkers, SMR = 1.32 (95% Cl, 1.15-1.52)], as well as among shop workers (SMR = 1.34; 95% C1, 1.05-1.72). CONCLUSIONS: In this detailed assessment of specific job categories in the U.S. trucking industry, we found an excess of mortality due to lung cancer and ischemic heart disease, particularly among drivers. [ABSTRACT FROM AUTHOR]

Diesel exhaust is a mixture of combustion gases and ultrafine particles coated with organic compounds. There is concern whether exposure can result in or worsen obstructive airway diseases, but there is only limited information to assess this risk. U.S. railroad workers have been exposed to diesel exhaust since diesel locomotives were introduced after World War II, and by 1959, 95% of the locomotives were diesel. We conducted a case-control study of railroad worker deaths between 1981 and 1982 using U.S. Railroad Retirement Board job records and next-of-kin smoking, residential, and vitamin use histories. There were 536 cases with chronic obstructive pulmonary disease (COPD) and 1,525 controls with causes of death not related to diesel exhaust or fine particle exposure. After adjustment for age, race, smoking, U.S. Census region of death, vitamin use, and total years off work, engineers and conductors with diesel-exhaust exposure from operating trains had an increased risk of COPD mortality. The odds of COPD mortality increased with years of work in these jobs, and those who had worked ? 16 years as an engineer or conductor after 1959 had an odds ratio of 1.61 (95% confidence interval, 1.12–2.30). These results suggest that diesel-exhaust exposure contributed to COPD mortality in these workers. Further study is needed to assess whether this risk is observed after exposure to exhaust from later-generation diesel engines with modern emission controls. [ABSTRACT FROM AUTHOR]

Aircraft noise exposure is linked to cardiovascular disease risk. One understudied candidate pathway is obesity. This study investigates the association between aircraft noise and obesity among female participants in two prospective Nurses' Health Study (NHS and NHSII) cohorts. Aircraft day-night average sound levels (DNL) were estimated at participant residential addresses from modeled 1 dB (dB) noise contours above 44 dB for 90 United States (U.S.) airports in 5-year intervals 1995–2010. Biennial surveys (1994–2017) provided information on body mass index (BMI; dichotomized, categorical) and other individual characteristics. Change in BMI from age 18 (BMI18; tertiles) was also calculated. Aircraft noise exposures were dichotomized (45, 55 dB), categorized (<45, 45–54, ≥55 dB) or continuous for exposure ≥45 dB. Multivariable multinomial logistic regression using generalized estimating equations were adjusted for individual characteristics and neighborhood socioeconomic status, greenness, population density, and environmental noise. Effect modification was assessed by U.S. Census region, climate boundary, airline hub type, hearing loss, and smoking status. At baseline, the 74,848 female participants averaged 50.1 years old, with 83.0%, 14.8%, and 2.2% exposed to <45, 45–54, and ≥55 dB of aircraft noise, respectively. In fully adjusted models, exposure ≥55 dB was associated with 11% higher odds (95% confidence interval [95%CI]: −1%, 24%) of BMIs ≥30.0, and 15% higher odds (95%CI: 3%, 29%) of membership in the highest tertile of BMI18 (ΔBMI 6.7 to 71.6). Less-pronounced associations were observed for the 2nd tertile of BMI18 (ΔBMI 2.9 to 6.6) and BMI 25.0–29.9 as well as exposures ≥45 versus <45 dB. There was evidence of DNL-BMI trends (p trends ≤ 0.02). Stronger associations were observed among participants living in the West, arid climate areas, and among former smokers. In two nationwide cohorts of female nurses, higher aircraft noise exposure was associated with higher BMI, adding evidence to an aircraft noise-obesity-disease pathway. [ABSTRACT FROM AUTHOR]

In this issue of the Journal, Villeneuve et al. (Am J Epidemiol. 2014;179(4):443–451) present epidemiologic evidence supporting the literature on the adverse effects of air pollution on risk of lung cancer. They found that ambient exposure to volatile organic compounds, especially when measured at longer time scales, was associated with increased odds of lung cancer in citizens of Toronto, Ontario, Canada, between 1997 and 2002. Specifically, in fully adjusted models, they observed that an interquartile-range increase in benzene concentration was associated with an odds ratio of 1.51 (95% confidence interval: 1.13, 2.01) using exposure at the time of interview. The odds ratio increased to 1.84 (95% confidence interval: 1.26, 2.68) when time-weighted exposure at all previous addresses was considered. They obtained similar results for exposure to nitrogen dioxide. These findings add weight to the substantial (and rapidly growing) body of literature on the relation of air pollution with lung cancer risk, as well as illustrate important aspects of the effects of different exposure assessment choices and potential sources of key interest. [ABSTRACT FROM PUBLISHER]

• Long-term exposure to ambient PM was associated with decreased leukocyte mtDNAcn. • MtDNAcn may be influenced by the concentration, duration and size of PM exposure. • Husband's education and season modified the association between PM 2.5 and mtDNAcn. Ambient particulate matter (PM) has been associated with mitochondrial damage and dysfunction caused by excessive oxidative stress, but the associations between long-term PM exposure and leukocyte mitochondrial DNA copy number (mtDNAcn), a biomarker of mitochondrial dysfunction due to oxidative stress, are less studied. To investigate the associations between short-, intermediate- and long-term exposure (1-, 3- and 12-months) to different size fractions of PM (PM 2.5 , PM 2.5-10 and PM 10) and leukocyte mtDNAcn in a cross-sectional study. The associations between each of the PM exposure metrics with z scores of log-transformed mtDNAcn were examined using generalized linear regression models in 2758 female participants from the Nurses' Health Study (NHS). Monthly exposures to PM were estimated from spatio-temporal prediction models matched to each participants' address history. Potential effect modification by selected covariates was examined using multiplicative interaction terms and subgroup analyses. In single-size fraction models, increases in all size fractions of PM were associated with decreases in mtDNAcn, although only models with longer averages of PM 2.5 reached statistical significance. For example, an interquartile range (IQR) increase in 12-month average ambient PM 2.5 (5.5 μg/m3) was associated with a 0.07 [95% confidence interval (95% CI): −0.13, −0.01; p -value = 0.02] decrease in mtDNAcn z score in both basic- and multivariable-adjusted models. Associations for PM 2.5 were stronger after controlling for PM 2.5-10 in two size-fraction models. Our study suggests that long-term exposure to ambient PM 2.5 is associated with decreased mtDNAcn in healthy women. [ABSTRACT FROM AUTHOR]

Aim Design Methods Results Conclusion Impact Reporting Method Patient or Public Contribution Quantify disparities and identify correlates and predictors of ‘wellness’ supplement use among nurses during the first year of the pandemic.Longitudinal secondary analysis of Nurses' Health Studies 2 and 3 and Growing Up Today Study data.Sample included 36,518 total participants, 12,044 of which were nurses, who completed surveys during the first year of the COVID‐19 pandemic (April 2020 to April 2021). Analyses were conducted in March 2023. Modified Poisson models were used to estimate disparities in ‘wellness’ supplement use between nurses and non‐healthcare workers and, among nurses only, to quantify associations with workplace‐related predictors (occupational discrimination, PPE access, workplace setting) and psychosocial predictors (depression/anxiety, county‐level COVID‐19 mortality). Models included race/ethnicity, gender identity, age and cohort as covariates.Nurses were significantly more likely to use all types of supplements than non‐healthcare workers. Lacking personal protective equipment and experiencing occupational discrimination were significantly associated with new immune supplement use. Depression increased the risk of using weight loss, energy and immune supplements.Nurses' disproportionate use of ‘wellness’ supplements during the COVID‐19 pandemic may be related to workplace and psychosocial stressors. Given well‐documented risks of harm from the use of ‘wellness’ supplements, the use of these products by nurses is of concern.‘Wellness’ supplements promoting weight loss, increased energy, boosted immunity and cleansing of organs are omnipresent in today's health‐focused culture, though their use has been associated with harm. This is of added concern among nurses given their risk of COVID‐19 infection at work. Our study highlighted the risk factors associated with use of these products (lacking PPE and experiencing occupational discrimination). Findings support prior research suggesting a need for greater public health policy and education around the use of ‘wellness’ supplements.STROBE guidelines were followed throughout manuscript.No patient or public contribution was involved. [ABSTRACT FROM AUTHOR]

Background: The metabolic changes that ultimately lead to gestational diabetes mellitus (GDM) likely begin before pregnancy. Cannabis use might increase the risk of GDM by increasing appetite or promoting fat deposition and adipogenesis. Objectives: We aimed to assess the association between preconception cannabis use and GDM incidence. Methods: We analysed individual‐level data from eight prospective cohort studies. We identified the first, or index, pregnancy (lasting ≥20 weeks of gestation with GDM status) after cannabis use. In analyses of pooled individual‐level data, we used logistic regression to estimate study‐type‐specific odds ratios (OR) and 95% confidence intervals (CI), adjusting for potential confounders using random effect meta‐analysis to combine study‐type‐specific ORs and 95% CIs. Stratified analyses assessed potential effect modification by preconception tobacco use and pre‐pregnancy body mass index (BMI). Results: Of 17,880 participants with an index pregnancy, 1198 (6.7%) were diagnosed with GDM. Before the index pregnancy, 12.5% of participants used cannabis in the past year. Overall, there was no association between preconception cannabis use in the past year and GDM (OR 0.97, 95% CI 0.79, 1.18). Among participants who never used tobacco, however, those who used cannabis more than weekly had a higher risk of developing GDM than those who did not use cannabis in the past year (OR 2.65, 95% CI 1.15, 6.09). This association was not present among former or current tobacco users. Results were similar across all preconception BMI groups. Conclusions: In this pooled analysis of preconception cohort studies, preconception cannabis use was associated with a higher risk of developing GDM among individuals who never used tobacco but not among individuals who formerly or currently used tobacco. Future studies with more detailed measurements are needed to investigate the influence of preconception cannabis use on pregnancy complications. [ABSTRACT FROM AUTHOR]

Understanding how environmental and social stressors cluster is critical to explaining and addressing health disparities. It remains unclear how these stressors cluster at fine spatial resolution in low to medium-income, urban households. We explored patterns of environmental and social exposures at the household-level and potential predictors of these joint exposures in two environmental justice communities in the Greater Boston area. We recruited 150 households in Chelsea, MA and the Dorchester neighborhood of Boston, MA, between 2016 and 2019 and collected data on two domains: environmental and social stressor. For each domain, we fit Latent Class Analysis (LCA) models to exposure data to assess intra-domain variability, and cross-classified the resultant classes to identify joint exposure profiles. We compared differences in the distribution of these profiles by participants' demographic and household characteristics using χ 2, Fisher's exact, Analysis of Variance, and Kruskal-Wallis tests. We identified two latent classes in each domain: High environmental (n = 90; 60.4%), Low environmental (n = 59; 39.6%), High Social (n = 31; 20.8%), and Low Social (n = 118; 79.2%). Cross-classification yielded four joint exposure profiles: Both Low (n = 46, 30.9%); Both High (n = 18, 12.1%); High environmental-Low Social (n = 72, 48.3%); and Low environmental-High Social (n = 13, 8.7%). Significant group differences were found by housing type (e.g., single-family vs. multi-family) (Fisher's exact p = 0.0016), housing tenure (p = 0.0007), and study site (p < 0.0001). We also observed differences by race/ethnicity, income, and education: households that were Hispanic/Latinx, below the poverty level, and with lower education were more likely to be in the Both High group. Our analyses confirmed that environmental and social stressors cluster in socially disadvantaged households. Housing type, housing tenure, and location of the residence were also strong predictors of cluster membership, with renter and multi-family residents at risk of high exposures to environmental and social stressors. • We explored 20 stressors at household-level in two EJ communities with latent class analysis. • Socially disadvantaged households were more likely to experience joint exposures. • In addition, housing and neighborhood factors were strong indicators of joint exposure profiles. [ABSTRACT FROM AUTHOR]

The Preconception Period Analysis of Risks and Exposures Influencing Health and Development (PrePARED) Consortium creates a novel resource for addressing preconception health by merging data from numerous cohort studies. In this paper, we describe our data harmonization methods and results. Individual-level data from 12 prospective studies were pooled. The crosswalk-cataloging-harmonization procedure was used. The index pregnancy was defined as the first postbaseline pregnancy lasting more than 20 weeks. We assessed heterogeneity across studies by comparing preconception characteristics in different types of studies. The pooled data set included 114,762 women, and 25,531 (22%) reported at least 1 pregnancy of more than 20 weeks' gestation during the study period. Babies from the index pregnancies were delivered between 1976 and 2021 (median, 2008), at a mean maternal age of 29.7 (standard deviation, 4.6) years. Before the index pregnancy, 60% of women were nulligravid, 58% had a college degree or more, and 37% were overweight or obese. Other harmonized variables included race/ethnicity, household income, substance use, chronic conditions, and perinatal outcomes. Participants from pregnancy-planning studies had more education and were healthier. The prevalence of preexisting medical conditions did not vary substantially based on whether studies relied on self-reported data. Use of harmonized data presents opportunities to study uncommon preconception risk factors and pregnancy-related events. This harmonization effort laid the groundwork for future analyses and additional data harmonization. [ABSTRACT FROM AUTHOR]