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.

Aircraft noise exposure and body mass index among female participants in two Nurses' Health Study prospective cohorts living around 90 airports in the United States.

OBJECTIVE: 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. METHODS: 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. RESULTS: 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 (ptrends ≤ 0.02). Stronger associations were observed among participants living in the West, arid climate areas, and among former smokers. DISCUSSION: 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.

Association of Residential Exposure to Hazardous Air Pollutants with Risk of Non-Hodgkin Lymphoma and Multiple Myeloma.

BACKGROUND: Certain hazardous air pollutants (HAP) are known or suspected to pose immunological or cancer risk to humans, but evidence is limited from the general population. METHODS: We assessed associations between residential exposure to HAPs at the census tract level and incident non-Hodgkin lymphoma (NHL) and multiple myeloma in the Nurses' Health Study (NHS, 1986-2012) and NHSII (1989-2019). We used the covariate-adjusted proportional hazards model to estimate hazard ratios (HR) of NHL, major NHL subtypes, and multiple myeloma per interquartile range increase in exposure to a given HAP and pooled the cohort-specific estimates using fixed-effects meta-analyses. RESULTS: There were 810 NHL and 158 multiple myeloma cases in NHS (1,700,707 person-years) and 379 NHL and 59 multiple myeloma cases in NHSII (2,820,772 person-years). Most HRs approximated unity. Meta-analyses did not show consistent evidence of associations between any HAP exposure and risk of NHL or multiple myeloma. CONCLUSIONS: Exposure to HAPs was not consistently associated with risks of NHL or multiple myeloma in these nationwide prospective cohorts of women. IMPACT: This is the first nationwide study assessing associations between residential HAP exposures and risk of lymphoid malignances in prospective cohorts and focuses on women, who have frequently been underrepresented in (primarily occupational) studies of exposure to HAPs.

Advancing Social and Environmental Research in Cancer Registries Using Geomasking for Address-Level Data.

Understanding the social and environmental causes of cancer in the United States, particularly in marginalized communities, is a major research priority. Population-based cancer registries are essential for advancing this research, given their nearly complete capture of incident cases within their catchment areas. Most registries limit the release of address-level geocodes linked to cancer outcomes to comply with state health departmental regulations. These policies ensure patient privacy, uphold data confidentiality, and enhance trust in research. However, these restrictions also limit the conduct of high-quality epidemiologic studies on social and environmental factors that may contribute to cancer burden. Geomasking refers to computational algorithms that distort locational data to attain a balance between effectively "masking" the original address location while faithfully maintaining the spatial structure in the data. We propose that the systematic deployment of scalable geomasking algorithms could accelerate research on social and environmental contributions across the cancer continuum by reducing measurement error bias while also protecting privacy. We encourage multidisciplinary teams of registry officials, geospatial analysts, cancer researchers, and others engaged in this form of research to evaluate and apply geomasking procedures based on feasibility of implementation, accuracy, and privacy protection to accelerate population-based research on social and environmental causes of cancer.

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.

Estimation of life's essential 8 score with incomplete data of individual metrics.

Background: The American Heart Association's Life's Essential 8 (LE8) is an updated construct of cardiovascular health (CVH), including blood pressure, lipids, glucose, body mass index, nicotine exposure, diet, physical activity, and sleep health. It is challenging to simultaneously measure all eight metrics at multiple time points in most research and clinical settings, hindering the use of LE8 to assess individuals' overall CVH trajectories over time. Materials and methods: We obtained data from 5,588 participants in the Nurses' Health Studies (NHS, NHSII) and Health Professionals Follow-up Study (HPFS), and 27,194 participants in the 2005-2016 National Health and Nutrition Examination Survey (NHANES) with all eight metrics available. Individuals' overall cardiovascular health (CVH) was determined by LE8 score (0-100). CVH-related factors that are routinely collected in many settings (i.e., demographics, BMI, smoking, hypertension, hypercholesterolemia, and diabetes) were included as predictors in the base models of LE8 score, and subsequent models further included less frequently measured factors (i.e., physical activity, diet, blood pressure, and sleep health). Gradient boosting decision trees were trained with hyper-parameters tuned by cross-validations. Results: The base models trained using NHS, NHSII, and HPFS had validated root mean squared errors (RMSEs) of 8.06 (internal) and 16.72 (external). Models with additional predictors further improved performance. Consistent results were observed in models trained using NHANES. The predicted CVH scores can generate consistent effect estimates in associational studies as the observed CVH scores. Conclusions: CVH-related factors routinely measured in many settings can be used to accurately estimate individuals' overall CVH when LE8 metrics are incomplete.

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.

Associations between Etiologic or Prognostic Tumor Tissue Markers and Neighborhood Contextual Factors in Male Health Professionals Diagnosed with Prostate Cancer.

BACKGROUND: There is growing evidence that unfavorable neighborhood contexts may influence prostate cancer progression. Whether these associations may be explained in part by differences in tumor-level somatic alterations remain unclear. METHODS: Data on tumor markers (PTEN, p53, ERG, and SPINK1) were obtained from 1,157 participants with prostate cancer in the Health Professionals Follow-up Study. Neighborhood greenness, socioeconomic status, and the income Index of Concentration at Extremes were obtained from satellite and census data and linked to participants' address at diagnosis and at study enrollment. Exposures were scaled to an interquartile range and modeled as tertiles. Bivariate associations between tertiles of neighborhood factors and tumor markers were assessed in covariate adjusted logistic regression models to estimate ORs and 95% confidence intervals. RESULTS: There was no association between any of the neighborhood contextual factors and PTEN, p53, ERG, or SPINK1 in bivariate or multivariable adjusted models. Results were generally consistent when modeling exposure using exposure at diagnosis or at study enrollment. CONCLUSIONS: In this multilevel study of men with prostate cancer, we found no evidence of associations between neighborhood context and tumor tissue markers. IMPACT: Our results provide some of the first empirical data in support of the hypothesis that prostate cancer risk conferred by tumor tissue markers may arise independently of underlying neighborhood context. Prospective studies in more diverse populations are needed to confirm these findings.

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.

Estimation of Life's Essential 8 Score with Incomplete Data of Individual Metrics.

Background: The American Heart Association's Life's Essential 8 (LE8) is an updated construct of cardiovascular health (CVH), including blood pressure, lipids, glucose, body mass index, nicotine exposure, diet, physical activity, and sleep health. It is challenging to simultaneously measure all eight metrics at multiple time points in most research and clinical settings, hindering the use of LE8 to assess individuals' overall CVH trajectories over time. Methods and Results: We obtained data from 5,588 participants in the Nurses' Health Studies (NHS, NHSII) and Health Professional's Follow-up Study (HPFS), and 27,194 participants in the 2005-2016 National Health and Nutrition Examination Survey (NHANES) with all eight metrics available. Individuals' overall cardiovascular health (CVH) was determined by LE8 score (0-100). CVH-related factors that are routinely collected in many settings (i.e., demographics, BMI, smoking, hypertension, hypercholesterolemia, and diabetes) were included as predictors in the base models of LE8 score, and subsequent models further included less frequently measured factors (i.e., physical activity, diet, blood pressure, and sleep health). Gradient boosting decision trees were trained with hyper-parameters tuned by cross-validations. The base models trained using NHS, NHSII, and HPFS had validated root mean squared errors (RMSEs) of 8.06 (internal) and 16.72 (external). Models with additional predictors further improved performance. Consistent results were observed in models trained using NHANES. The predicted CVH scores can generate consistent effect estimates in associational studies as the observed CVH scores. Conclusions: CVH-related factors routinely measured in many settings can be used to accurately estimate individuals' overall CVH when LE8 metrics are incomplete. Clinical Perspective: What Is New?: Life's Essential 8 (LE8) has great potential to assess and promote cardiovascular health (CVH) across life course, however, it is challenging to simultaneously collect all eight metrics at multiple time points in most research and clinical settings.We demonstrated that CVH-related factors routinely collected in many research and clinical settings can be used to accurately estimate individuals' overall CVH across time even when LE8 metrics are incomplete.What Are the Clinical Implications?: The approach introduced in this study provides a cost-effective and feasible way to estimate individuals' overall CVH.It can be used to track individuals' CVH trajectories in clinical settings.

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 Ultraviolet B Radiation and Risk of Systemic Lupus Erythematosus Among Women in the Nurses' Health Studies.

OBJECTIVE: Ultraviolet (UV) radiation exposure is associated with photosensitivity, rashes, and flares in systemic lupus erythematosus (SLE). However, it is not known whether UV exposure increases risk of developing SLE. We examined UV exposure and SLE risk in a large prospective cohort. METHODS: The Nurses' Health Study (NHS) enrolled 121,700 US female nurses in 1976; in 1989, 116,429 nurses were enrolled in NHS II. Biennial questionnaires collected lifestyle and medical data. Self-reported incident SLE by American College of Rheumatology classification criteria was confirmed by medical record review. Ambient UV exposure was estimated by linking geocoded residential addresses with a spatiotemporal UV exposure model. Cox models estimated hazard ratios (HRs) and 95% confidence intervals (95% CIs) across tertiles of time-varying cumulative average UV. We examined SLE risk overall and stratified by anti-Ro/La antibodies and by cutaneous manifestations from 1976 through 2014 (NHS)/2015 (NHS II), adjusting for confounders. RESULTS: With 6,054,665 person-years of exposure, we identified 297 incident SLE cases; the mean ± SD age at diagnosis was 49.8 ± 10.6 years. At diagnosis, 16.8% of women had +anti-Ro/La, and 80% had either +anti-Ro/La or ≥1 cutaneous manifestation. Compared with the lowest UV exposure tertile, risk of overall SLE was increased, but not significantly (HR 1.28 [95%CI 0.96-1.70]). Women in the highest tertile had increased risk of malar rash (HR 1.62 [95% CI 1.04-2.52]). CONCLUSION: Cumulative UV exposure was not associated with SLE risk. Higher UV exposure, however, was associated with increased risk of malar rash at presentation. UV exposure may trigger SLE onset with malar rash among susceptible women.

Using follicular fluid metabolomics to investigate the association between air pollution and oocyte quality.

BACKGROUND AND AIM: Our objective was to use metabolomics in a toxicological-relevant target tissue to gain insight into the biological processes that may underlie the negative association between air pollution exposure and oocyte quality. METHODS: Our study included 125 women undergoing in vitro fertilization at an academic fertility center in Massachusetts, US (2005-2015). A follicular fluid sample was collected during oocyte retrieval and untargeted metabolic profiling was conducted using liquid chromatography with ultra-high-resolution mass spectrometry and two chromatography columns (C18 and HILIC). Daily exposure to nitrogen dioxide (NO2), ozone, fine particulate matter, and black carbon was estimated at the women's residence using spatiotemporal models and averaged over the period of ovarian stimulation (2-weeks). Multivariable linear regression models were used to evaluate the associations between the air pollutants, number of mature oocytes, and metabolic feature intensities. A meet-in-the-middle approach was used to identify overlapping features and metabolic pathways. RESULTS: Of the air pollutants, NO2 exposure had the largest number of overlapping metabolites (C18: 105; HILIC: 91) and biological pathways (C18: 3; HILIC: 6) with number of mature oocytes. Key pathways of overlap included vitamin D3 metabolism (both columns), bile acid biosynthesis (both columns), C21-steroid hormone metabolism (HILIC), androgen and estrogen metabolism (HILIC), vitamin A metabolism (HILIC), carnitine shuttle (HILIC), and prostaglandin formation (C18). Three overlapping metabolites were confirmed with level-1 or level-2 evidence. For example, hypoxanthine, a metabolite that protects against oxidant-induced cell injury, was positively associated with NO2 exposure and negatively associated with number of mature oocytes. Minimal overlap was observed between the other pollutants and the number of mature oocytes. CONCLUSIONS: Higher exposure to NO2 during ovarian stimulation was associated with many metabolites and biologic pathways involved in endogenous vitamin metabolism, hormone synthesis, and oxidative stress that may mediate the observed associations with lower oocyte quality.

Exposure to natural vegetation in relation to mammographic density in a Massachusetts-based clinical cohort.

Inverse associations between natural vegetation exposure (i.e., greenness) and breast cancer risk have been reported; however, it remains unknown whether greenness affects breast tissue development or operates through other mechanisms (e.g., body mass index [BMI] or physical activity). We examined the association between greenness and mammographic density-a strong breast cancer risk factor-to determine whether greenness influences breast tissue composition independent of lifestyle factors. Methods: Women (n = 2,318) without a history of breast cancer underwent mammographic screening at Brigham and Women's Hospital in Boston, Massachusetts, from 2006 to 2014. Normalized Difference Vegetation Index (NDVI) satellite data at 1-km2 resolution were used to estimate greenness at participants' residential address 1, 3, and 5 years before mammogram. We used multivariable linear regression to estimate differences in log-transformed volumetric mammographic density measures and 95% confidence intervals (CIs) for each 0.1 unit increase in NDVI. Results: Five-year annual average NDVI was not associated with percent mammographic density in premenopausal (ß = -0.01; 95% CI = -0.03, 0.02; P = 0.58) and postmenopausal women (ß = -0.02; 95% CI = -0.04, 0.01; P = 0.18). Results were similar for 1-year and 3-year NDVI measures and in models including potential mediators of BMI and physical activity. There were also no associations between greenness and dense volume and nondense volume. Conclusions: Greenness exposures were not associated with mammographic density. Impact: Prior observations of a protective association between greenness and breast cancer may not be driven by differences in breast tissue composition, as measured by mammographic density, but rather other mechanisms.

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.

Impact of neighborhood socioeconomic status, income segregation, and greenness on blood biomarkers of inflammation.

BACKGROUND: 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). METHODS: 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. RESULTS: Higher neighborhood socioeconomic status was associated with lower inflammation score in women (ß for interquartile range increase = -27.7%, 95% CI: -34.9%, -19.8%) and men (ß = -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 (ß = -27.8%, 95% CI: -35.8%, -18.7%) and men (ß = -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 (ß = -18.9%, 95% CI: -28.9%, -7.4%) but not men. Results were robust to sensitivity analyses to assess unmeasured confounding and selection bias. DISCUSSION: 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.

Residential ultraviolet radiation and breast cancer risk in a large prospective cohort.

BACKGROUND: Ambient ultraviolet (UV) radiation has been increasing due to climate change. While this may result in adverse health consequences such as an increased incidence of skin cancer, UV radiation is also a source of vitamin D, which has been hypothesized to be protective for breast cancer risk. METHODS: Using a spatiotemporal kriging model, we estimated residential UV exposure levels for the enrollment addresses (2003-2009) of breast cancer-free women aged 35-74 years participating in the Sister Study and living in the contiguous United States (N = 48,450). Cox proportional hazards models were used to estimate adjusted hazard ratios (HRs) and 95% confidence intervals (95% CIs) for the risk associated with UV exposure levels (mW/m2) categorized in quintiles. We examined the association for breast cancer overall (invasive and ductal carcinoma in situ) and by estrogen receptor (ER) status of the tumor. We considered effect modification by regular (≥4 times/week) vitamin D supplement use. RESULTS: Over a median of 10.5 years of follow up, 3,510 incident breast cancer diagnoses were reported. We found no evidence of an association between living in areas with higher levels of UV radiation and overall breast cancer risk (HRQ5 vs. Q1 = 1.00, 95% CI: 0.90, 1.11). Higher UV levels were inversely associated with the risk of ER- breast cancer (HRQ5 vs. Q1 = 0.73, 95% CI: 0.55-0.99), but not ER+ (HR Q5 vs. Q1 = 1.04, 95% CI: 0.92-1.18). For ER- breast cancer, the inverse association was only evident in women who did not regularly take vitamin D supplements (HRQ5 vs. Q1 = 0.52, 95% CI: 0.33-0.81) compared with those who did regularly take vitamin D supplements (HRQ5 vs. Q1 = 1.02, 95% CI: 0.68-1.54; p-for-heterogeneity = 0.12). CONCLUSIONS: The findings from this study support a role for UV exposure and vitamin D in the etiology of ER- breast cancer.

Intake of fruits and vegetables according to pesticide residue status in relation to all-cause and disease-specific mortality: Results from three prospective cohort studies.

BACKGROUND: Intake of conventionally grown fruits and vegetables (FVs) is an important route of exposure to pesticide residues in the general population. However, whether health risk stemming from exposure to pesticides through diet could offset benefits of consuming FVs is unclear. OBJECTIVE: We assessed the association of FV intake, classified according to their pesticide residue status, with total and cause-specific mortality. METHODS: We followed 137,378 women (NHS, 1998-2019, and NHSII, 1999-2019) and 23,502 men (HPFS, 1998-2020) without cardiovascular disease, cancer, or diabetes at baseline. FV intake was assessed using validated food frequency questionnaires and categorized as having high- or low-pesticide-residues using data from the USDA Pesticide Data Program. Cox proportional hazards models were used to estimate hazard ratios (HRs) and 95% confidence intervals (CI) for total and cause-specific mortality associated with high- and low-pesticide-residue FV intake. RESULTS: A total of 27,026 deaths, including 4,318 from CVD and 6,426 from cancer, were documented during 3,081,360 person-years of follow-up. In multivariable-adjusted analyses, participants who consumed ≥4 servings/day of low-pesticide-residue FVs had 36% (95% CI: 32%-41%) lower mortality risk compared to participants who consumed <1 serving/day. The corresponding estimate for high-pesticide residue FV intake was 0.93 (95% CI: 0.81-1.07). This pattern was similar across the three most frequent causes of death (cardiovascular disease, cancer and respiratory diseases). CONCLUSIONS: High-pesticide-residue FV intake was unrelated whereas low-pesticide residue FV intake was inversely related to all-cause mortality, suggesting that exposure to pesticide residues through diet may offset the beneficial effect of FV intake on mortality.

Integrated molecular response of exposure to traffic-related pollutants in the US trucking industry.

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 (PM2.5). Metabolic associations with EC, OC and PM2.5 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 PM2.5. 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.

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.