Heavy-metal associated breast cancer and colorectal cancer hot spots and their demographic and socioeconomic characteristics.

PURPOSE: Cancer registries offer an avenue to identify cancer clusters across large populations and efficiently examine potential environmental harms affecting cancer. The role of known metal carcinogens (i.e., cadmium, arsenic, nickel, chromium(VI)) in breast and colorectal carcinogenesis is largely unknown. Historically marginalized communities are disproportionately exposed to metals, which could explain cancer disparities. We examined area-based metal exposures and odds of residing in breast and colorectal cancer hotspots utilizing state tumor registry data and described the characteristics of those living in heavy metal-associated cancer hotspots. METHODS: Breast and colorectal cancer hotspots were mapped across Kentucky, and area-based ambient metal exposure to cadmium, arsenic, nickel, and chromium(VI) were extracted from the 2014 National Air Toxics Assessment for Kentucky census tracts. Among colorectal cancer (n = 56,598) and female breast cancer (n = 77,637) diagnoses in Kentucky, we used logistic regression models to estimate Odds Ratios (ORs) and 95% Confidence Intervals to examine the association between ambient metal concentrations and odds of residing in cancer hotspots, independent of individual-level and neighborhood risk factors. RESULTS: Higher ambient metal exposures were associated with higher odds of residing in breast and colorectal cancer hotspots. Populations in breast and colorectal cancer hotspots were disproportionately Black and had markers of lower socioeconomic status. Furthermore, adjusting for age, race, tobacco and neighborhood factors did not significantly change cancer hotspot ORs for ambient metal exposures analyzed. CONCLUSION: Ambient metal exposures contribute to higher cancer rates in certain geographic areas that are largely composed of marginalized populations. Individual-level assessments of metal exposures and cancer disparities are needed.

Traffic-Related Air Pollution and Ultrasound Parameters of Fetal Growth in Eastern Massachusetts.

Previous studies have examined the association between prenatal nitrogen dioxide (NO2)-a traffic emissions tracer-and fetal growth based on ultrasound measures. Yet, most have used exposure assessment methods with low temporal resolution, which limits the identification of critical exposure windows given that pregnancy is relatively short. Here, we used NO2 data from an ensemble model linked to residential addresses at birth to fit distributed lag models that estimated the association between NO2 exposure (resolved weekly) and ultrasound biometric parameters in a Massachusetts-based cohort of 9,446 singleton births from 2011-2016. Ultrasound biometric parameters examined included biparietal diameter (BPD), head circumference, femur length, and abdominal circumference. All models adjusted for sociodemographic characteristics, time trends, and temperature. We found that higher NO2 was negatively associated with all ultrasound parameters. The critical window differed depending on the parameter and when it was assessed. For example, for BPD measured after week 31, the critical exposure window appeared to be weeks 15-25; 10-parts-per-billion higher NO2 sustained from conception to the time of measurement was associated with a lower mean z score of -0.11 (95% CI: -0.17, -0.05). Our findings indicate that reducing traffic emissions is one potential avenue to improving fetal and offspring health.

Influence of Neighborhood Social and Natural Environment on Prostate Tumor Histology in a Cohort of Male Health Professionals.

Adverse neighborhood social and natural (green space) environments may contribute to the etiology of prostate cancer (CaP), but mechanisms are unclear. We examined associations between neighborhood environment and prostate intratumoral inflammation in 967 men diagnosed with CaP with available tissue samples from 1986-2009 in the Health Professionals Follow-up Study. Exposures were linked to work or residential addresses in 1988. We estimated indices of neighborhood socioeconomic status (nSES) and segregation (Index of Concentration at the Extremes (ICE)) using US Census tract-level data. Surrounding greenness was estimated using seasonal averaged Normalized Difference Vegetation Index (NDVI) data. Surgical tissue underwent pathological review for acute and chronic inflammation, corpora amylacea, and focal atrophic lesions. Adjusted odds ratios (aORs) for inflammation (ordinal) and focal atrophy (binary) were estimated using logistic regression. No associations were observed for acute or chronic inflammation. Each interquartile-range increase in NDVI within 1,230 m of the participant's work or home address (aOR = 0.74, 95% confidence interval (CI): 0.59, 0.93), in ICE-income (aOR = 0.79, 95% CI: 0.61, 1.04), and in ICE-race/income (aOR = 0.79, 95% CI: 0.63, 0.99) was associated with lower odds of postatrophic hyperplasia. Interquartile-range increases in nSES (aOR = 0.76, 95% CI: 0.57, 1.02) and ICE-race/income (aOR = 0.73, 95% CI: 0.54, 0.99) were associated with lower odds of tumor corpora amylacea. Histopathological inflammatory features of prostate tumors may be influenced by neighborhood.

Mobile Source Benzene Regulations and Risk of Childhood and Young Adult Hematologic Cancers in Alaska: A Quasi-experimental Study.

BACKGROUND: We aimed to evaluate the impact of the EPA's Mobile Source Air Toxics rules (MSAT), which targeted benzene emissions, on childhood and young adult leukemia and lymphoma incidence in Alaska. METHODS: MSAT was implemented in 2011 and produced a dramatic decline in ambient benzene in Alaska. Due to previous benzene-related regulations enacted in the continental United States, MSAT had relatively modest impacts in other states. This created quasi-experimental conditions leveraged in this study. Using 2-year state-level incidence rates of childhood and young adult leukemia and lymphoma for each US state 2001-2018, we examined MSAT-attributable changes in incidence by applying a difference-in-differences approach. RESULTS: We found evidence of a substantial reduction associated with MSAT in incidence of childhood and young adult lymphoma (-1.23 [-1.84, -0.62] cases per 100,000), but not in leukemia (-0.13 [-0.77, 0.51] cases per 100,000). CONCLUSIONS: Our findings are consistent with the hypothesis that MSAT, which reduced benzene levels in Alaska, led to a decline in lymphoma incidence in children and young adults.

Environmental Exposures and Anti-Müllerian Hormone: A Mixture Analysis in the Nurses' Health Study II.

BACKGROUND: Previous studies have linked environmental exposures with anti-Müllerian hormone (AMH), a marker of ovarian reserve. However, associations with multiple environment factors has to our knowledge not been addressed. METHODS: We included a total of 2,447 premenopausal women in the Nurses' Health Study II (NHSII) who provided blood samples during 1996-1999. We selected environmental exposures linked previously with reproductive outcomes that had measurement data available in NHSII, including greenness, particulate matter, noise, outdoor light at night, ultraviolet radiation, and six hazardous air pollutants (1,3-butadiene, benzene, diesel particulate matter, formaldehyde, methylene chloride, and tetrachloroethylene). For these, we calculated cumulative averages from enrollment (1989) to blood draw and estimated associations with AMH in adjusted single-exposure models, principal component analysis (PCA), and hierarchical Bayesian kernel machine regression (BKMR). RESULTS: Single-exposure models showed negative associations of AMH with benzene (percentage reduction in AMH per interquartile range [IQR] increase = 5.5%, 95% confidence interval [CI] = 1.0, 9.8) and formaldehyde (6.1%, 95% CI = 1.6, 10). PCA identified four major exposure patterns but only one with high exposure to air pollutants and light at night was associated with lower AMH. Hierarchical BKMR pointed to benzene, formaldehyde, and greenness and suggested an inverse joint association with AMH (percentage reduction comparing all exposures at the 75th percentile to median = 8.2%, 95% CI = 0.7, 15.1). Observed associations were mainly among women above age 40. CONCLUSIONS: We found exposure to benzene and formaldehyde to be consistently associated with lower AMH levels. The associations among older women are consistent with the hypothesis that environmental exposures accelerate reproductive aging.

Methodological Challenges in Spatial and Contextual Exposome-Health Studies.

The concept of the exposome encompasses the totality of exposures from a variety of external and internal sources across an individual's life course. The wealth of existing spatial and contextual data makes it appealing to characterize individuals' external exposome to advance our understanding of environmental determinants of health. However, the spatial and contextual exposome is very different from other exposome factors measured at the individual-level as spatial and contextual exposome data are more heterogenous with unique correlation structures and various spatiotemporal scales. These distinctive characteristics lead to multiple unique methodological challenges across different stages of a study. This article provides a review of the existing resources, methods, and tools in the new and developing field for spatial and contextual exposome-health studies focusing on four areas: (1) data engineering, (2) spatiotemporal data linkage, (3) statistical methods for exposome-health association studies, and (4) machine- and deep-learning methods to use spatial and contextual exposome data for disease prediction. A critical analysis of the methodological challenges involved in each of these areas is performed to identify knowledge gaps and address future research needs.

Minute level smartphone derived exposure to greenness and consumer wearable derived physical activity in a cohort of US women.

BACKGROUND: Inconsistent results have been found in the literature on associations of greenness, or vegetation quantity, and physical activity. However, few studies have assessed associations between mobility-based greenness and physical activity from mobile health data from smartphone and wearable devices with fine spatial and temporal resolution. METHODS: We assessed mobility-based greenness exposure and wearable accelerometer data from participants in the US-based prospective Nurses' Health Study 3 cohort Mobile Health (mHealth) Substudy (2018-2020). We recruited 500 female participants with instructions to wear devices over four 7-day sampling periods equally spaced throughout the year. After restriction criteria there were 337 participants (mean age 36 years) with n = 639,364 unique observations. Normalized Difference Vegetation Index (NDVI) data were derived from 30 m x 30 m Landsat-8 imagery and spatially joined to GPS points recorded every 10 min. Fitbit proprietary algorithms provided physical activity summarized as mean number of steps per minute, which we averaged during the 10-min period following a GPS-based greenness exposure assessment. We utilized Generalized Additive Mixed Models to examine associations (every 10 min) between greenness and physical activity adjusting for neighborhood and individual socioeconomic status, Census region, season, neighborhood walkability, daily mean temperature and precipitation. We assessed effect modification through stratification and interaction models and conducted sensitivity analyses. RESULTS: Mean 10-min step count averaged 7.0 steps (SD 14.9) and greenness (NDVI) averaged 0.3 (SD 0.2). Contrary to our hypotheses, higher greenness exposure was associated non-linearly with lower mean steps per minute after adjusting for confounders. We observed statistically significant effect modification by Census region and season. DISCUSSION: We utilized objective physical activity data at fine temporal and spatial scales to present novel estimates of the association between mobility-based greenness and step count. We found higher levels of greenness were inversely associated with steps per minute.

Effects of long-term average temperature on cardiovascular disease hospitalizations in an American elderly population.

BACKGROUND: Short-term exposure to high or low temperatures is associated with increased mortality and morbidity. Less is known about effects of long-term exposure to high or low temperatures. Prolonged exposure to high or low temperatures might contribute to pathophysiological mechanisms, thereby influencing the development of diseases. Our aim was to evaluate associations of long-term temperature exposure with cardiovascular disease (CVD) hospitalizations. METHODS: We constructed an open cohort consisting of all fee-for-service Medicare beneficiaries, aged ≥65, living in the contiguous US from 2000 through 2016 (∼61.6 million individuals). We used data from the 4 km Gridded Surface Meteorological dataset to assess the summer (June-August) and winter (December-February) average daily maximum temperature for each year for each zip code. Cox-equivalent Poisson models were used to estimate associations with first CVD hospitalization, after adjustment for potential confounders. We performed stratified analyses to assess potential effect modification by sex, age, race, Medicaid eligibility and relative humidity. RESULTS: Higher summer average and lower winter average temperatures were associated with an increased risk of CVD hospitalization. We found a HR of 1.068 (95% CI: 1.063, 1.074) per IQR increase (5.2 °C) for summer average temperature and a HR of 1.022 (95% CI: 1.017, 1.028) per IQR decrease (11.7 °C) for winter average temperature. Positive associations of higher summer average temperatures were strongest for individuals aged <75 years, Medicaid eligible, and White individuals. Positive associations of lower winter average temperatures were strongest for individuals aged <75 years and Black individuals, and individuals living in low relative humidity areas. CONCLUSIONS: Living in areas with high summer average temperatures or low winter average temperatures could increase the risk of CVD hospitalizations. The magnitude of the associations of summer and winter average temperatures differs by demographics and relative humidity levels.

Associations between air pollution, residential greenness, and glycated hemoglobin (HbA1c) in three prospective cohorts of U.S. adults.

BACKGROUND: While studies suggest impacts of individual environmental exposures on type 2 diabetes (T2D) risk, mechanisms remain poorly characterized. Glycated hemoglobin (HbA1c) is a biomarker of glycemia and diagnostic criterion for prediabetes and T2D. We explored associations between multiple environmental exposures and HbA1c in non-diabetic adults. METHODS: HbA1c was assessed once in 12,315 women and men in three U.S.-based prospective cohorts: the Nurses' Health Study (NHS), Nurses' Health Study II (NHSII), and Health Professionals Follow-up Study (HPFS). Residential greenness within 270 m and 1,230 m (normalized difference vegetation index, NDVI) was obtained from Landsat. Fine particulate matter (PM2.5) and nitrogen dioxide (NO2) were estimated from nationwide spatiotemporal models. Three-month and one-year averages prior to blood draw were assigned to participants' addresses. We assessed associations between single exposure, multi-exposure, and component scores from Principal Components Analysis (PCA) and HbA1c. Fully-adjusted models built on basic models of age and year at blood draw, BMI, alcohol use, and neighborhood socioeconomic status (nSES) to include diet quality, race, family history, smoking status, postmenopausal hormone use, population density, and season. We assessed interactions between environmental exposures, and effect modification by population density, nSES, and sex. RESULTS: Based on HbA1c, 19% of participants had prediabetes. In single exposure fully-adjusted models, an IQR (0.14) higher 1-year 1,230 m NDVI was associated with a 0.27% (95% CI: 0.05%, 0.49%) lower HbA1c. In basic component score models, a SD increase in Component 1 (high loadings for 1-year NDVI) was associated with a 0.19% (95% CI: 0.04%, 0.34%) lower HbA1c. CI's crossed the null in multi-exposure and fully-adjusted component score models. There was little evidence of associations between air pollution and HbA1c, and no evidence of effect modification. CONCLUSIONS: Among non-diabetic adults, environmental exposures were not consistently associated with HbA1c. More work is needed to elucidate biological pathways between the environment and prediabetes.

Solar and geomagnetic activity enhance the effects of air pollutants on atrial fibrillation.

AIMS: Cardiac arrhythmias have been associated with intense solar and geomagnetic activity (SGA) and exposures to air pollution. METHODS AND RESULTS: We examined whether oscillations of SGA can modify the effect of hourly exposures to air pollutants on atrial fibrillation ≥30 s (AF) risk in patients with dual-chamber implantable cardioverter-defibrillators. The effects of SGA on ambient particulate matter <2.5 µm (PM2.5), black carbon (BC), ultrafine particles (PN), and associations with AF were assessed. Measures of SGA included solar wind proton density (SW), total interplanetary magnetic field strength (IMF), and Kp index, a measure of global geomagnetic activity. Overall time lags between 0 and 24 h, periods of increased SGA (>50th percentile in IMF, SW, and Kp index) enhanced the effects of all three air pollutants on AF, while during periods of reduced SGA the associations were considerably weaker or absent. During periods of intense SW 6 h prior to an AF event, the odds ratio (OR) for PM2.5 exposure per interquartile range (IQR) of 5.6 µg/m3 was 1.7 [95% confident interval (CI) 1.3-2.3, P = 0.0001]. For periods of reduced SW, the OR for PM2.5 exposure per IQR was 1.2 (95% CI 0.9-1.5; P = 0.27). There were similar effects for PN and BC exposures. In patients with multiple AF events per hour, the associations with air pollutants during intense SGA were even greater. CONCLUSION: The effects of air pollutants up to 24 h before AF events were enhanced during periods of increased SGA. Our results suggest that these effects may account for variation in AF risk.

Ultraviolet radiation and age at natural menopause in a nationwide, prospective US cohort.

BACKGROUND: 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. OBJECTIVES: We sought to examine the associations of long-term UV exposure and age at natural menopause in a large, nationwide, prospective cohort. METHODS: 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. RESULTS: 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. CONCLUSIONS: 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.

Emissions of dioxins and dioxin-like compounds and incidence of hepatocellular carcinoma in the United States.

Ambient dioxin exposure from industrial sources, excluding exposures from occupations and accidental releases/contamination, may be associated with risk of developing hepatocellular carcinoma (HCC). The objective of this study was to examine the association between county-level ambient dioxin air emissions from industrial sources and HCC risk in the US. We obtained information on 90,359 incident HCC cases diagnosed between 2000 and 2016 from population-based cancer registries across the US in the Surveillance, Epidemiology, and End Results (SEER) database. Dioxin emissions from 1987 to 2007 from a nationwide spatial database of historical dioxin-emitting facilities were linked to the SEER county of residence at diagnosis using a geographic information system (GIS). Poisson regression with robust variance estimation was used to calculate incidence rate ratios (IRRs) and 95% confidence intervals (CIs) for the association between county-level dioxin emissions and HCC rates adjusting for individual-level age at diagnosis, sex, race/ethnicity, year of diagnosis, SEER registry, and county-level information on health conditions, lifestyle factors, and socioeconomic status. There was no association between dioxin emissions based on the number of dioxin-emitting facilities within a county or average annual emissions within a county and HCC risk. In analyses by facility type, there were positive associations between county-level dioxin emissions from coal-fired power plants (adjusted IRR 1.09, 95% CI 1.01-1.17), but not with the number of these facilities. Similarly, positive associations for industrial boilers and sewage sludge incinerators were evident, but not consistent across both exposure metrics. Future research should incorporate individual-level data to further explore the findings suggested by these ecologic analyses.

Impacts of long-term ambient particulate matter and gaseous pollutants on circulating biomarkers of inflammation in male and female health professionals.

BACKGROUND: 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. OBJECTIVE: 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. METHODS: 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 (PM2.5, PM2.5-10, PM10) and nitrogen dioxide (NO2) 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. RESULTS: 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 NO2 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 PM2.5-10, respectively. Increasing PM2.5-10 was associated with increasing IL-6 and sTNFR-2 among men over shorter exposure durations. There were no associations with exposures to PM2.5 or PM10, or with adiponectin. Findings were robust to sensitivity analyses restricting to disease-free controls and non-movers. CONCLUSIONS: Across multiple long-term pollutant exposures and inflammatory markers, associations were generally weak. Focusing on specific pollutant-inflammatory mechanisms may clarify pathways.

Long-term aircraft noise exposure and risk of hypertension in the Nurses' Health Studies.

BACKGROUND: Aircraft noise can affect populations living near airports. Chronic exposure to aircraft noise has been associated with cardiovascular disease, including hypertension. However, previous studies have been limited in their ability to characterize noise exposures over time and to adequately control for confounders. OBJECTIVES: The aim of this study was to examine the association between aircraft noise and incident hypertension in two cohorts of female nurses, using aircraft noise exposure estimates with high spatial resolution over a 20-year period. METHODS: We obtained contour maps of modeled aircraft noise levels over time for 90 U.S. airports and linked them with geocoded addresses of participants in the Nurses' Health Study (NHS) and Nurses' Health Study II (NHS II) to assign noise exposure for 1994-2014 and 1995-2013, respectively. We used time-varying Cox proportional hazards models to estimate hypertension risk associated with time-varying noise exposure (dichotomized at 45 and 55 dB(A)), adjusting for fixed and time-varying confounders. Results from both cohorts were pooled via random effects meta-analysis. RESULTS: In meta-analyses of parsimonious and fully-adjusted models with aircraft noise dichotomized at 45 dB(A), hazard ratios (HR) for hypertension incidence were 1.04 (95% CI: 1.00, 1.07) and 1.03 (95% CI: 0.99, 1.07), respectively. When dichotomized at 55 dB(A), HRs were 1.10 (95% CI: 1.01, 1.19) and 1.07 (95% CI: 0.98, 1.15), respectively. After conducting fully-adjusted sensitivity analyses limited to years in which particulate matter (PM) was obtained, we observed similar findings. In NHS, the PM-unadjusted HR was 1.01 (95% CI: 0.90, 1.14) and PM-adjusted HR was 1.01 (95% CI: 0.89, 1.14); in NHS II, the PM-unadjusted HR was 1.08 (95% CI: 0.96, 1.22) and the PM-adjusted HR was 1.08 (95% CI: 0.95, 1.21). Overall, in these cohorts, we found marginally suggestive evidence of a positive association between aircraft noise exposure and hypertension.

PM2.5 Constituents and Onset of Gestational Diabetes Mellitus: Identifying Susceptible Exposure Windows.

Fine particulate matter (PM2.5) has been linked to gestational diabetes mellitus (GDM). However, PM2.5 is a complex mixture with large spatiotemporal heterogeneities, and women with early-onset GDM (i.e., diagnosed before 24th gestation week) have distinct maternal characteristics and a higher risk of worse health outcomes compared with those with late-onset GDM (i.e., diagnosed in or after 24th gestation week). We aimed to examine differential impacts of PM2.5 and its constituents on early- vs. late-onset GDM, and to identify corresponding susceptible exposure windows. We leveraged statewide linked electronic health records and birth records data in Florida in 2012-2017. Exposures to PM2.5 and its constituents (i.e., sulfate [SO4 2-], ammonium [NH4 +], nitrate [NO3 -], organic matter [OM], black carbon [BC], mineral dust [DUST], and sea-salt [SS]) were spatiotemporally linked to pregnant women based on their residential histories. Cox proportional hazards models and multinomial logistic regression were used to examine the associations of PM2.5 and its constituents with GDM and its onsets. Distributed non-linear lag models were implemented to identify susceptible exposure windows. Exposures to PM2.5, SO4 2-, NH4 +, and BC were statistically significantly associated with higher hazards of GDM. Exposures to PM2.5 during weeks 1-12 of gestation were positively associated with GDM. Associations of early-onset GDM with PM2.5 in the 1st and 2nd trimesters, SO4 2- in the 1st and 2nd trimesters, and NO3 - in the preconception and 1st trimester were considerably stronger than observations for late-onset GDM. Our findings suggest there are differential associations of PM2.5 and its constituents with early- vs. late-onset GDM, with different susceptible exposure windows. This study helps better understand the impacts of air pollution on GDM accounting for its physiological heterogeneity.

Exposure to Air Pollution and Particle Radioactivity With the Risk of Ventricular Arrhythmias.

BACKGROUND: Individuals are exposed to air pollution and ionizing radiation from natural sources through inhalation of particles. This study investigates the association between cardiac arrhythmias and short-term exposures to fine particulate matter (particulate matter ≤2.5 µm aerodynamic diameter; PM2.5) and particle radioactivity. METHODS: Ventricular arrhythmic events were identified among 176 patients with dual-chamber implanted cardioverter-defibrillators in Boston, Massachusetts between September 2006 and June 2010. Patients were assigned exposures based on residential addresses. Daily PM2.5 levels were estimated at 1-km×1-km grid cells from a previously validated prediction model. Particle gross ß activity was used as a surrogate for particle radioactivity and was measured from several monitoring sites by the US Environmental Protection Agency's monitoring network. The association of the onset of ventricular arrhythmias (VA) with 0- to 21-day moving averages of PM2.5 and particle radioactivity (2 single-pollutant models and a 2-pollutant model) before the event was examined using time-stratified case-crossover analyses, adjusted for dew point and air temperatures. RESULTS: A total of 1,050 VA were recorded among 91 patients, including 123 sustained VA among 25 of these patients. In the single-pollutant model of PM2.5, each interquartile range increase in daily PM2.5 levels for a 21-day moving average was associated with 39% higher odds of a VA event (95% CI, 12%-72%). In the single-pollutant model of particle radioactivity, each interquartile range increase in particle radioactivity for a 2-day moving average was associated with 13% higher odds of a VA event (95% CI, 1%-26%). In the 2-pollutant model, for the same averaging window of 21 days, each interquartile range increase in daily PM2.5 was associated with an 48% higher odds of a VA event (95% CI, 15%-90%), and each interquartile range increase of particle radioactivity with a 10% lower odds of a VA event (95% CI, -29% to 14%). We found that with higher levels of particle radioactivity, the effect of PM2.5 on VAs is reduced. CONCLUSIONS: In this high-risk population, intermediate (21-day) PM2.5 exposure was associated with higher odds of a VA event onset among patients with known cardiac disease and indication for implanted cardioverter-defibrillator implantation independently of particle radioactivity.

Guidance to Reduce the Cardiovascular Burden of Ambient Air Pollutants: A Policy Statement From the American Heart Association.

In 2010, the American Heart Association published a statement concluding that the existing scientific evidence was consistent with a causal relationship between exposure to fine particulate matter and cardiovascular morbidity and mortality, and that fine particulate matter exposure is a modifiable cardiovascular risk factor. Since the publication of that statement, evidence linking air pollution exposure to cardiovascular health has continued to accumulate and the biological processes underlying these effects have become better understood. This increasingly persuasive evidence necessitates policies to reduce harmful exposures and the need to act even as the scientific evidence base continues to evolve. Policy options to mitigate the adverse health impacts of air pollutants must include the reduction of emissions through action on air quality, vehicle emissions, and renewable portfolio standards, taking into account racial, ethnic, and economic inequality in air pollutant exposure. Policy interventions to improve air quality can also be in alignment with policies that benefit community and transportation infrastructure, sustainable food systems, reduction in climate forcing agents, and reduction in wildfires. The health care sector has a leadership role in adopting policies to contribute to improved environmental air quality as well. There is also potentially significant private sector leadership and industry innovation occurring in the absence of and in addition to public policy action, demonstrating the important role of public-private partnerships. In addition to supporting education and research in this area, the American Heart Association has an important leadership role to encourage and support public policies, private sector innovation, and public-private partnerships to reduce the adverse impact of air pollution on current and future cardiovascular health in the United States.

County-level exposures to greenness and associations with COVID-19 incidence and mortality in the United States.

BACKGROUND: 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. OBJECTIVES: We evaluated whether greenness was related to COVID-19 incidence and mortality in the US. METHODS: 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. RESULTS: 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. DISCUSSION: 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.

The influence of fine particulate matter on the association between residential greenness and ovarian reserve.

BACKGROUND: Natural vegetation, or greenness, is thought to improve health through its ability to buffer and reduce harmful environmental exposures as well as relieve stress, promote physical activity, restore attention, and increase social cohesion. In concert, these effects could help mitigate the detrimental effects of air pollution on reproductive aging in women. METHODS: Our analysis included 565 women attending the Massachusetts General Hospital Fertility Center (2004-2014) who had a measured antral follicle count (AFC), a marker of ovarian reserve. We calculated peak residential greenness in the year prior to AFC using 250 m2 normalized difference vegetation index (NDVI) from the Terra and Aqua satellites operated by the United States National Aeronautics and Space Administration. Validated spatiotemporal models estimated daily residential exposure to particulate matter <2.5 µm (PM2.5) for the 3 months prior to AFC. Poisson regression models with robust standard errors were used to estimate the association between peak greenness, average PM2.5 exposure, and AFC adjusted for age, BMI, smoking status, education, year, and season. RESULTS: Women in our study had a mean age of 35.2 years with a standard deviation (SD) of 4.3 years (min: 20 years, max: 45 years). The peak residential NDVI ranged from 0.07 to 0.92 with a SD of 0.18. There was no statistically significant association between peak residential greenness and AFC; however, higher exposure to PM2.5 was associated with lower AFC (-6.2% per 2 µg/m3 [1 SD increase] 95% CI -11.8, -0.3). There was a significant interaction between exposure to PM2.5 and peak greenness on AFC (P-interaction: 0.03). Among women with an average PM2.5 exposure of 7 µg/m3, a SD increase in residential peak greenness was associated with a 5.6% (95% CI -0.4, 12.0) higher AFC. Conversely, among women with a PM2.5 exposure of 12 µg/m3, a SD increase in residential peak greenness was associated with a 5.8% (95% CI -13.1, 2.1) lower AFC. CONCLUSIONS: Residing in an area with high levels of greenness may slow reproductive aging in women only when exposure to PM2.5 is low.