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.

Association between Outdoor Light at Night and Prostate Cancer in the Health Professionals Follow-up Study.

BACKGROUND: Circadian disruption is a potential risk factor for advanced prostate cancer, and light at night (LAN) exposure may disrupt circadian rhythms. We evaluated whether outdoor LAN increases the risk of prostate cancer. METHODS: We prospectively followed 49,148 participants in the Health Professionals Follow-up Study from 1986 through 2016. We estimated baseline and cumulative time-varying outdoor LAN with ∼1 km2 resolution using data from the US Defense Meteorological Satellite Program's Operational Linescan System, which was assigned to participants' geocoded addresses. Participants reside in all 50 U.S. states and reported a work or home address. We used multivariable Cox models to estimate HRs and 95% confidence intervals (CI) for the association between outdoor LAN and risk of overall (7,175 cases) and fatal (915 cases) prostate cancer adjusting for individual and contextual factors. RESULTS: There was no association between the interquartile range increase in cumulative LAN and total (HR, 1.02; 95% CI, 0.98-1.06) or fatal (HR, 1.05; 95% CI, 0.96-1.15) prostate cancer in adjusted models. However, there was a positive association between baseline LAN and total prostate cancer among non-movers (HR, 1.06; 95% CI, 1.00-1.14) including among highly screened participants (HR, 1.11; 95% CI, 1.01-1.23). CONCLUSIONS: There was a suggestive positive association between baseline outdoor LAN and total prostate cancer. Additional studies with different measures of outdoor LAN and in more diverse populations are necessary. IMPACT: To our knowledge, this is the first longitudinal cohort study exploring the relationship between outdoor LAN and prostate cancer.

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.

Association of Tropical Cyclones With County-Level Mortality in the US.

Importance: Tropical cyclones have a devastating effect on society, but a comprehensive assessment of their association with cause-specific mortality over multiple years of study is lacking. Objective: To comprehensively evaluate the association of county-level tropical cyclone exposure and death rates from various causes in the US. Design, Setting, and Participants: A retrospective observational study using a Bayesian conditional quasi-Poisson model to examine how tropical cyclones were associated with monthly death rates. Data from 33.6 million deaths in the US were collected from the National Center for Health Statistics over 31 years (1988-2018), including residents of the 1206 counties in the US that experienced at least 1 tropical cyclone during the study period. Exposures: Tropical cyclone days per county-month, defined as number of days in a month with a sustained maximal wind speed 34 knots or greater. Main Outcomes and Measures: Monthly cause-specific county-level death rates by 6 underlying causes of death: cancers, cardiovascular diseases, infectious and parasitic diseases, injuries, neuropsychiatric conditions, and respiratory diseases. The model yielded information about the association between each additional cyclone day per month and monthly county-level mortality compared with the same county-month in different years, up to 6 months after tropical cyclones, and how these estimated associations varied by age, sex, and social vulnerability. The unit of analysis was county-month. Results: There were 33 619 393 deaths in total (16 691 681 females and 16 927 712 males; 8 587 033 aged 0-64 years and 25 032 360 aged 65 years or older) from the 6 causes recorded in 1206 US counties. There was a median of 2 tropical cyclone days experienced in total in included US counties. Each additional cyclone day was associated with increased death rates in the month following the cyclone for injuries (3.7% [95% credible interval {CrI}, 2.5%-4.9%]; 2.0 [95% CrI, 1.3-2.7] additional deaths per 1 000 000 for 2018 monthly age-standardized median rate [DPM]; 54.3 to 56.3 DPM), infectious and parasitic diseases (1.8% [95% CrI, 0.1%-3.6%]; 0.2 [95% CrI, 0.0-0.4] additional DPM; 11.7 to 11.9 DPM), respiratory diseases (1.3% [95% CrI, 0.2%-2.4%]; 0.6 [95% CrI, 0.1-1.1] additional DPM; 44.9 to 45.5 DPM), cardiovascular diseases (1.2% [95% CrI, 0.6%-1.7%]; 1.5 [95% CrI, 0.8-2.2] additional DPM; 129.6 to 131.1 DPM), neuropsychiatric conditions (1.2% [95% CrI, 0.1%-2.4%]; 0.6 [95% CrI, 0.1-1.2] additional DPM; 52.1 to 52.7 DPM), with no change for cancers (-0.3% [95% CrI, -0.9% to 0.3%]; -0.3 [95% CrI, -0.9 to 0.3] additional DPM; 100.4 to 100.1 DPM). Conclusions and Relevance: Among US counties that experienced at least 1 tropical cyclone from 1988-2018, each additional cyclone day per month was associated with modestly higher death rates in the months following the cyclone for several causes of death, including injuries, infectious and parasitic diseases, cardiovascular diseases, neuropsychiatric conditions, and respiratory diseases.

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.

Associations of long-term exposure to environmental noise and outdoor light at night with age at natural menopause in a US women cohort.

Previous studies have suggested noise, especially at night time, and light at night (LAN) could cause neuroendocrine disturbance and circadian disruption, which may lead to ovarian follicle atresia and earlier onset of menopause. However, no study to date has directly investigated the associations of exposure to these factors and menopausal age. METHODS: Premenopausal women from the Nurses' Health Study II (NHS II) were followed from age 40 through 2015. Median daytime and nighttime anthropogenic noise and outdoor LAN exposure were measured from a geospatial prediction model and satellite images, respectively, at residential addresses throughout the follow-up. Time-varying Cox proportional hazard models were used to calculate the hazard ratios and 95% confidence intervals, adjusting for individual lifestyle, reproductive history, and neighborhood socioeconomic factors. Possible effect modification by region, smoking status, body mass index, race/ethnicity, history of rotating shift work, and census tract population density and median income was examined. RESULTS: A total of 63,380 of 105,326 women self-reported natural menopause during 1,043,298 person-years of follow-up. No associations were found for noise (both daytime and nighttime) and outdoor LAN exposure with age at natural menopause (hazard ratios = 0.99-1.00) in the fully adjusted models. Sensitivity analyses showed similar null associations. No meaningful effect modification was found for region, smoking status, body mass index, race/ethnicity, history of rotating shift work, and census tract socioeconomic measures in stratified analyses. CONCLUSION: No associations were found between environmental noise and outdoor LAN exposure in mid-adulthood and menopausal age in this cohort of US women.

Long-term exposure to particulate matter and roadway proximity with age at natural menopause in the Nurses' Health Study II Cohort.

Evidence has shown associations between air pollution and traffic-related exposure with accelerated aging, but no study to date has linked the exposure with age at natural menopause, an important indicator of reproductive aging. In this study, we sought to examine the associations of residential exposure to ambient particulate matter (PM) and distance to major roadways with age at natural menopause in the Nurses' Health Study II (NHS II), a large, prospective female cohort in US. A total of 105,996 premenopausal participants in NHS II were included at age 40 and followed through 2015. Time-varying residential exposures to PM10, PM2.5-10, and PM2.5 and distance to roads was estimated. We calculated hazard ratios (HR) and 95% confidence intervals (CIs) for natural menopause using Cox proportional hazard models adjusting for potential confounders and predictors of age at menopause. We also examined effect modification by region, smoking, body mass, physical activity, menstrual cycle length, and population density. There were 64,340 reports of natural menopause throughout 1,059,229 person-years of follow-up. In fully adjusted models, a 10 µg/m3 increase in the cumulative average exposure to PM10 (HR: 1.02, 95% CI: 1.00, 1.04), PM2.5-10 (HR: 1.03, 95% CI: 1.00, 1.05), and PM2.5 (HR: 1.03, 95% CI: 1.00, 1.06) and living within 50 m to a major road at age 40 (HR: 1.03, 95%CI: 1.00, 1.06) were associated with slightly earlier menopause. No statistically significant effect modification was found, although the associations of PM were slightly stronger for women who lived in the West and for never smokers. To conclude, we found exposure to ambient PM and traffic in midlife was associated with slightly earlier onset of natural menopause. Our results support previous evidence that exposure to air pollution and traffic may accelerate reproductive aging.

Exposure to air pollution and COVID-19 mortality in the United States: A nationwide cross-sectional study.

OBJECTIVES: United States government scientists estimate that COVID-19 may kill tens of thousands of Americans. Many of the pre-existing conditions that increase the risk of death in those with COVID-19 are the same diseases that are affected by long-term exposure to air pollution. We investigated whether long-term average exposure to fine particulate matter (PM 2.5 ) is associated with an increased risk of COVID-19 death in the United States. DESIGN: A nationwide, cross-sectional study using county-level data. DATA SOURCES: COVID-19 death counts were collected for more than 3,000 counties in the United States (representing 98% of the population) up to April 22, 2020 from Johns Hopkins University, Center for Systems Science and Engineering Coronavirus Resource Center. MAIN OUTCOME MEASURES: We fit negative binomial mixed models using county-level COVID-19 deaths as the outcome and county-level long-term average of PM 2.5 as the exposure. In the main analysis, we adjusted by 20 potential confounding factors including population size, age distribution, population density, time since the beginning of the outbreak, time since state issuance of the stay-at-home order, hospital beds, number of individuals tested, weather, and socioeconomic and behavioral variables such as obesity and smoking. We included a random intercept by state to account for potential correlation in counties within the same state. We conducted more than 68 additional sensitivity analyses. RESULTS: We found that an increase of only 1 µg/m 3 in PM 2.5 is associated with an 8% increase in the COVID-19 death rate (95% confidence interval [CI]: 2%, 15%). The results were statistically significant and robust to secondary and sensitivity analyses. CONCLUSIONS: A small increase in long-term exposure to PM 2.5 leads to a large increase in the COVID-19 death rate. Despite the inherent limitations of the ecological study design, our results underscore the importance of continuing to enforce existing air pollution regulations to protect human health both during and after the COVID-19 crisis. The data and code are publicly available so our analyses can be updated routinely.

A causal inference framework for cancer cluster investigations using publicly available data.

Often, a community becomes alarmed when high rates of cancer are noticed, and residents suspect that the cancer cases could be caused by a known source of hazard. In response, the US Centers for Disease Control and Prevention recommend that departments of health perform a standardized incidence ratio (SIR) analysis to determine whether the observed cancer incidence is higher than expected. This approach has several limitations that are well documented in the existing literature. In this paper we propose a novel causal inference framework for cancer cluster investigations, rooted in the potential outcomes framework. Assuming that a source of hazard representing a potential cause of increased cancer rates in the community is identified a priori, we focus our approach on a causal inference estimand which we call the causal SIR (cSIR). The cSIR is a ratio defined as the expected cancer incidence in the exposed population divided by the expected cancer incidence for the same population under the (counterfactual) scenario of no exposure. To estimate the cSIR we need to overcome two main challenges: 1) identify unexposed populations that are as similar as possible to the exposed one to inform estimation of the expected cancer incidence under the counterfactual scenario of no exposure, and 2) publicly available data on cancer incidence for these unexposed populations are often available at a much higher level of spatial aggregation (e.g. county) than what is desired (e.g. census block group). We overcome the first challenge by relying on matching. We overcome the second challenge by building a Bayesian hierarchical model that borrows information from other sources to impute cancer incidence at the desired level of spatial aggregation. In simulations, our statistical approach was shown to provide dramatically improved results, i.e., less bias and better coverage, than the current approach to SIR analyses. We apply our proposed approach to investigate whether trichloroethylene vapor exposure has caused increased cancer incidence in Endicott, New York.

ESTIMATING POPULATION AVERAGE CAUSAL EFFECTS IN THE PRESENCE OF NON-OVERLAP: THE EFFECT OF NATURAL GAS COMPRESSOR STATION EXPOSURE ON CANCER MORTALITY.

Most causal inference studies rely on the assumption of overlap to estimate population or sample average causal effects. When data suffer from non-overlap, estimation of these estimands requires reliance on model specifications, due to poor data support. All existing methods to address non-overlap, such as trimming or down-weighting data in regions of poor data support, change the estimand so that inference cannot be made on the sample or the underlying population. In environmental health research settings, where study results are often intended to influence policy, population-level inference may be critical, and changes in the estimand can diminish the impact of the study results, because estimates may not be representative of effects in the population of interest to policymakers. Researchers may be willing to make additional, minimal modeling assumptions in order to preserve the ability to estimate population average causal effects. We seek to make two contributions on this topic. First, we propose a flexible, data-driven definition of propensity score overlap and non-overlap regions. Second, we develop a novel Bayesian framework to estimate population average causal effects with minor model dependence and appropriately large uncertainties in the presence of non-overlap and causal effect heterogeneity. In this approach, the tasks of estimating causal effects in the overlap and non-overlap regions are delegated to two distinct models, suited to the degree of data support in each region. Tree ensembles are used to non-parametrically estimate individual causal effects in the overlap region, where the data can speak for themselves. In the non-overlap region, where insufficient data support means reliance on model specification is necessary, individual causal effects are estimated by extrapolating trends from the overlap region via a spline model. The promising performance of our method is demonstrated in simulations. Finally, we utilize our method to perform a novel investigation of the causal effect of natural gas compressor station exposure on cancer outcomes. Code and data to implement the method and reproduce all simulations and analyses is available on Github (https://github.com/rachelnethery/overlap).

Flavored little cigar smoke induces cytotoxicity and apoptosis in airway epithelia.

Addition of flavors reduces the harsh taste of tobacco, facilitating the initiation and maintenance of addiction among youths. Flavored cigarettes (except menthol) are now banned. However, the legislation on little cigars remains unclear and flavored little cigars are currently available for purchase. Since inhaled tobacco smoke directly exerts toxic effects on the lungs, we tested whether non-flavored and flavored little cigar smoke exposure had the potential for harm in cultured pulmonary epithelia. We cultured Calu-3 lung epithelia on both 96-well plates and at the air-liquid interface and exposed them to smoke from non-flavored Swisher Sweets and flavored (sweet cherry, grape, menthol, peach and strawberry) Swisher Sweets little cigars. Irrespective of flavor, acute little cigar smoke exposure (10×35 ml puffs) significantly increased cell death and decreased the percentage of live cells. Chronic exposure (10×35 ml puffs per day for 4 days) of smoke to Calu-3 cultures significantly increased lactate dehydrogenase release, further indicating toxicity. To determine whether this exposure was associated with increased cell death/apoptosis, a protein array was used. Chronic exposure to smoke from all types of little cigars induced the activation of the two major apoptosis pathways, namely the intrinsic (mitochondrial-mediated) and the extrinsic (death receptor-mediated) pathways. Both flavored and non-flavored little cigar smoke caused similar levels of toxicity and activation of apoptosis, suggesting that flavored and non-flavored little cigars are equally harmful. Hence, the manufacture, advertisement, sale and use of both non-flavored and flavored little cigars should be strictly controlled.

Flavored e-cigarette liquids reduce proliferation and viability in the CALU3 airway epithelial cell line.

E-cigarettes are generally thought of as a safer smoking alternative to traditional cigarettes. However, little is known about the effects of e-cigarette liquids (e-liquids) on the lung. Since over 7,000 unique flavors have been identified for purchase in the United States, our goal was to conduct a screen that would test whether different flavored e-liquids exhibited different toxicant profiles. We tested the effects of 13 different flavored e-liquids [with nicotine and propylene glycol/vegetable glycerin (PG/VG) serving as controls] on a lung epithelial cell line (CALU3). Using the 3-(4,5-dimethylthiazol-2-yl)-2,5-diphenyltetrazolium bromide (MTT) assay as an indicator of cell proliferation/viability, we demonstrated a dose-dependent decrease of MTT metabolism by all flavors tested. However, a group of four flavors consistently showed significantly greater toxicity compared with the PG/VG control, indicating the potential for some flavors to elicit more harmful effects than others. We also tested the aerosolized "vapor" from select e-liquids on cells and found similar dose-dependent trends, suggesting that direct e-liquid exposures are a justifiable first-pass screening approach for determining relative e-liquid toxicity. We then identified individual chemical constituents for all 13 flavors using gas chromatography-mass spectrometry. These data revealed that beyond nicotine and PG/VG, the 13 flavored e-liquids have diverse chemical constituents. Since all of the flavors exhibited some degree of toxicity and a diverse array of chemical constituents with little inhalation toxicity available, we conclude that flavored e-liquids should be extensively tested on a case-by-case basis to determine the potential for toxicity in the lung and elsewhere.