Association of residential exposure to hazardous air pollutants with risk of non-Hodgkin lymphoma and multiple myeloma.

BACKGROUND: Certain hazardous air pollutants (HAPs) 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 (MM) in the Nurses' Health Study (NHS, 1986-2012) and NHSII (1989-2019). We used covariate-adjusted proportional hazards models to estimate hazard ratios (HRs) of NHL, major NHL subtypes, and MM 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 MM cases in NHS (1,700,707 person-years), and 379 NHL and 59 MM 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 MM. CONCLUSIONS: Exposure to HAPs was not consistently associated with risks of NHL or MM 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.

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.

Associations of fine particulate matter with incident cardiovascular disease; comparing models using ZIP code-level and individual-level fine particulate matter and confounders.

BACKGROUND: PM2.5 has been positively associated with cardiovascular disease (CVD) incidence. Most evidence has come from cohorts and administrative databases. Cohorts typically have extensive information on potential confounders and residential-level exposures. Administrative databases are usually more representative but typically lack information on potential confounders and often only have exposures at coarser geographies (e.g., ZIP code). The weaknesses in both types of studies have been criticized for potentially jeopardizing the validity of their findings for regulatory purposes. METHODS: We followed 101,870 participants from the US-based Nurses' Health Study (2000-2016) and linked residential-level PM2.5 and individual-level confounders, and ZIP code-level PM2.5 and confounders. We used time-varying Cox proportional hazards models to examine associations with CVD incidence. We specified basic models (adjusted for individual-level age, race and calendar year), individual-level confounder models, and ZIP code-level confounder models. RESULTS: Residential- and ZIP code-level PM2.5 were strongly correlated (Pearson r = 0.88). For residential-level PM2.5, the hazard ratio (HR, 95 % confidence interval) per 5 µg/m3 increase was 1.06 (1.01, 1.11) in the basic and 1.04 (0.99, 1.10) in the individual-level confounder model. For ZIP code-level PM2.5, the HR per 5 µg/m3 was 1.04 (0.99, 1.08) in the basic and 1.02 (0.97, 1.08) in the ZIP code-level confounder model. CONCLUSION: We observed suggestive positive, but not statistically significant, associations between long-term PM2.5 and CVD incidence, regardless of the exposure or confounding model. Although differences were small, associations from models with individual-level confounders and residential-level PM2.5 were slightly stronger than associations from models with ZIP code-level confounders and PM2.5.

Timing and duration of dog walking and dog owner's chronotype in relation to incident depression risk among middle to older-aged female nurses.

BACKGROUND: We examined associations between dog ownership, morning dog walking and its timing and duration, and depression risk in female nurses, exploring effect modification by chronotype. We hypothesized that dog ownership and morning walking with the dog are associated with lower odds of depression, and that the latter is particularly beneficial for evening chronotypes by helping them to synchronize their biological clock with the solar system. METHODS: 26,169 depression-free US women aged 53-72 from the Nurses' Health Study 2 (NHS2) were prospectively followed from 2017-2019. We used age- and multivariable-adjusted logistic regression models to estimate odds ratios (ORs) and 95% confidence intervals (95%CIs) for depression according to dog ownership, and morning dog walking, duration, and timing. RESULTS: Overall, there was no association between owning a dog (ORvs_no_pets = 1.12, 95%CI = 0.91-1.37), morning dog walking (ORvs_not = 0.87, 95%CI = 0.64-1.18), or the duration (OR>30min vs. ≤15mins = 0.68, 95%CI = 0.35-1.29) or timing of morning dog walks (ORafter9am vs. before7am = 1.06, 95%CI = 0.54-2.05) and depression. Chronotype of dog owners appeared to modify these associations. Compared to women of the same chronotype but without pets, dog owners with evening chronotypes had a significantly increased odds of depression (OR = 1.60, 95%CI = 1.12-2.29), whereas morning chronotypes did not (OR = 0.94, 95%CI = 0.71-1.23). Further, our data suggested that evening chronotypes benefited more from walking their dog themselves in the morning (OR = 0.75, 95%CI = 0.46-1.23, Pintx = 0.064;) than morning chronotypes. CONCLUSIONS: Overall, dog ownership was not associated with depression risk though it was increased among evening chronotypes. Walking their dog in the morning might help evening chronotypes to lower their odds of depression, though more data are needed to confirm this finding.

Association between Noise and Cardiovascular Disease in a Nationwide U.S. Prospective Cohort Study of Women Followed from 1988 to 2018.

BACKGROUND: Long-term noise exposure is associated with cardiovascular disease (CVD), including acute cardiovascular events such as myocardial infarction and stroke. However, longitudinal cohort studies in the U.S. of long-term noise and CVD are almost exclusively from Europe and few modeled nighttime noise, when an individual is likely at home or asleep, separately from daytime noise. We aimed to examine the prospective association of outdoor long-term nighttime and daytime noise from anthropogenic sources with incident CVD using a U.S.-based, nationwide cohort of women. METHODS: We linked L50 nighttime and L50 daytime anthropogenic modeled noise estimates from a U.S. National Parks Service model (L50: sound pressure levels exceeded 50 percent of the time) to geocoded residential addresses of 114,116 participants in the Nurses' Health Study. We used time-varying Cox proportional hazards models to estimate risk of incident CVD, coronary heart disease (CHD), and stroke associated with long-term average (14-y measurement period) noise exposure, adjusted for potential individual- and area-level confounders and CVD risk factors (1988-2018; biennial residential address updates; monthly CVD updates). We assessed effect modification by population density, region, air pollution, vegetation cover, and neighborhood socioeconomic status, and explored mediation by self-reported average nightly sleep duration. RESULTS: Over 2,548,927 person-years, there were 10,331 incident CVD events. In fully adjusted models, the hazard ratios for each interquartile range increase in L50 nighttime noise (3.67 dBA) and L50 daytime noise (4.35 dBA), respectively, were 1.04 (95% CI: 1.02, 1.06) and 1.04 (95% CI: 1.02, 1.07). Associations for total energy-equivalent noise level (Leq) measures were stronger than for the anthropogenic statistical L50 noise measures. Similar associations were observed for CHD and stroke. Interaction analyses suggested that associations of L50 nighttime and L50 daytime noise with CVD did not differ by prespecified effect modifiers. We found no evidence that inadequate sleep (<5 h/night) mediated associations of L50 nighttime noise and CVD. DISCUSSION: Outdoor L50 anthropogenic nighttime and daytime noise at the residential address was associated with a small increase in CVD risk in a cohort of adult female nurses. https://doi.org/10.1289/EHP12906.

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.

Air Pollution and Temperature: a Systematic Review of Ubiquitous Environmental Exposures and Sudden Cardiac Death.

PURPOSE OF REVIEW: Environmental exposures have been associated with increased risk of cardiovascular mortality and acute coronary events, but their relationship with out-of-hospital cardiac arrest (OHCA) and sudden cardiac death (SCD) remains unclear. SCD is an important contributor to the global burden of cardiovascular disease worldwide. RECENT FINDINGS: Current literature suggests a relationship between environmental exposures and cardiovascular disease, but their relationship with OHCA/SCD remains unclear. A literature search was conducted in PubMed, Embase, Web of Science, and Global Health. Of 5138 studies identified by our literature search, this review included 30 studies on air pollution, 42 studies on temperature, 6 studies on both air pollution and temperature, and 1 study on altitude exposure and OHCA/SCD. Particulate matter air pollution, ozone, and both hot and cold temperatures are associated with increased risk of OHCA/SCD. Pollution and other exposures related to climate change play an important role in OHCA/SCD incidence.

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.

Exposure to Particulate Matter Air Pollution and Age of Menarche in a Nationwide Cohort of U.S. Girls.

BACKGROUND: It remains unclear whether in utero and childhood exposure to air pollution affects pubertal development, particularly age of menarche in girls. OBJECTIVE: The aim of this study was to determine whether residential ambient particulate matter (PM) exposure in utero and during childhood is associated with age of menarche. METHODS: We studied 5,201 girls in the Growing Up Today Study 2 (2004-present) who were 10-17 y of age at enrollment (47.7% premenarchal; 52.3% postmenarchal). Exposure to three size fractions of PM [fine PM with aerodynamic diameter ≤2.5µm (PM2.5), PM with aerodynamic diameters between 2.5µm and 10µm (PM2.5-10), and PM with aerodynamic diameter 10µm (PM10)] was assigned based on maternal residential address, updated every 2 y, using nationwide spatiotemporal models. We estimated average PM exposure in utero, and time-varying windows: annual average exposure in the prior 1 and 2 y and cumulative average from birth. Age of menarche was self-reported on three surveys administered in 2004, 2006, and 2008. We calculated hazard ratios (HR) for menarche for an interquartile range (IQR) increase in PM exposure using Cox proportional hazard models adjusting for potential confounders. RESULTS: Girls attained menarche at 12.3 y of age on average. In the adjusted model, higher residential exposure to ambient PM2.5 during all time windows was associated with earlier age of menarche. The HRs of menarche for each IQR (4 µg/m3) increase in exposure to PM2.5 during the in utero period, 1 y prior to menarche, and throughout childhood were 1.03 [95% confidence interval (CI): 1.00, 1.06], 1.06 (95% CI: 1.02, 1.10) and 1.06 (95% CI: 1.02, 1.10), respectively. Effect estimates for PM10 exposure were similar, albeit attenuated, for all time windows. PM2.5-10 exposure was not associated with age of menarche. DISCUSSION: Among a large, nationwide, prospective cohort of U.S. girls, higher exposure to PM2.5 and PM10 in utero and throughout childhood was associated with an earlier age of menarche. Our results suggest that PM2.5 and PM10 may have endocrine-disrupting properties that could lead to altered timing of menarche. https://doi.org/10.1289/EHP12110.

Long-term exposure to summer specific humidity and cardiovascular disease hospitalizations in the US Medicare population.

INTRODUCTION: Most climate-health studies focus on temperature; however, less is known about health effects of exposure to atmospheric moisture. Humid air limits sweat evaporation from the body and can in turn exert strain on the cardiovascular system. We evaluated associations of long-term exposure to summer specific humidity with cardiovascular disease (CVD), coronary heart disease (CHD) and cerebrovascular disease (CBV) hospitalization. METHODS: We built an open cohort consisting of âˆ¼63 million fee-for-service Medicare beneficiaries, aged ≥65, living in the contiguous US (2000-2016). We assessed zip code level summer average specific humidity and specific humidity variability, based on daily estimates from the Gridded Surface Meteorological dataset (∼4km spatial resolution). To estimate associations of summer specific humidity with first CVD, CHD, and CBV hospitalization, we used Cox-equivalent Poisson models adjusted for individual and area-level socioeconomic status indicators, temperature, and winter specific humidity. RESULTS: Higher summer average specific humidity was associated with an increased risk of CVD, CHD, and CBV hospitalization. We found hazard ratios (HRs) of 1.07 (95%CI: 1.07, 1.08) for CVD hospitalization, 1.08 (95%CI: 1.08, 1.09) for CHD hospitalization, and 1.07 (95%CI: 1.07, 1.08) for CBV hospitalization per IQR increase (4.0 g of water vapor/kg of dry air) in summer average specific humidity. Associations of summer average specific humidity were strongest for beneficiaries eligible for Medicaid and for beneficiaries with an unknown or other race. Higher summer specific humidity variability was also associated with increased risk of CVD, CHD, and CBV hospitalization. Associations were not affected by adjustment for temperature and regions of the US, as well as exclusion of potentially prevalent cases. CONCLUSION: Long-term exposure to higher summer average specific humidity and specific humidity variability were positively associated with CVD hospitalization. As global warming could increase humidity levels, our findings are important to assess potential health impacts of climate change.

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.

Associations between long-term aircraft noise exposure, cardiovascular disease, and mortality in US cohorts of female nurses.

There is limited research examining aircraft noise and cardiovascular disease (CVD) risk. The objective of this study was to investigate associations of aircraft noise with CVD among two US cohorts, the Nurses' Health Study (NHS) and Nurses' Health Study II (NHSII). Methods: Between 1994 and 2014, we followed 57,306 NHS and 60,058 NHSII participants surrounding 90 airports. Aircraft noise was modeled above 44 A-weighted decibels (dB(A)) and linked to geocoded addresses. Based on exposure distributions, we dichotomized exposures at 50 dB(A) and tested sensitivity of this cut-point by analyzing aircraft noise as categories (<45, 45-49, 50-54, ≥55) and continuously. We fit cohort-specific Cox proportional hazards models to estimate relationships between time-varying day-night average sound level (DNL) and CVD incidence and CVD and all-cause mortality, adjusting for fixed and time-varying individual- and area-level covariates. Results were pooled using random effects meta-analysis. Results: Over 20 years of follow-up, there were 4529 CVD cases and 14,930 deaths. Approximately 7% (n = 317) of CVD cases were exposed to DNL ≥50 dB(A). In pooled analyses comparing ≥50 with <50 dB(A), the adjusted hazard ratio for CVD incidence was 1.00 (95% confidence interval: 0.89, 1.12). The corresponding adjusted hazard ratio for all-cause mortality was 1.02 (95% confidence interval: 0.96, 1.09). Patterns were similar for CVD mortality in NHS yet underpowered. Conclusions: Among participants in the NHS and NHSII prospective cohorts who generally experience low exposure to aircraft noise, we did not find adverse associations of aircraft noise with CVD incidence, CVD mortality, or all-cause mortality.

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.

Exposure to Noise and Cardiovascular Disease in a Nationwide US Prospective Cohort Study of Women.

Background: Long-term noise exposure is associated with cardiovascular disease (CVD), including acute cardiovascular events such as myocardial infarction and stroke. However, longitudinal cohort studies of long-term noise and CVD are almost exclusively from Europe, and few modelled nighttime and daytime noise separately. We aimed to examine the prospective association of outdoor long-term nighttime and daytime noise from anthropogenic sources with incident CVD using a US-based, nationwide cohort of women. Methods: We linked L50 (median) nighttime and L50 daytime modelled anthropogenic noise estimates from a US National Park Service model to geocoded residential addresses of 114,116 participants in the Nurses' Health Study. We used time-varying Cox proportional hazards models to estimate risk of incident CVD, coronary heart disease (CHD), and stroke associated with long-term average noise exposure, adjusted for potential individual- and area-level confounders and CVD risk factors (1988-2018). We assessed effect modification by population density, region, air pollution, vegetation cover, and neighborhood socioeconomic status, and explored mediation by self-reported average nightly sleep duration. Results: Over 2,544,035 person-years, there were 10,331 incident CVD events. In fully-adjusted models, the hazard ratios for each interquartile range increase in L50 nighttime noise (3.67 dBA) and L50 daytime noise (4.35 dBA), respectively, were 1.04 (95% CI 1.02, 1.06) and 1.04 (95% CI 1.02, 1.07). Similar associations were observed for CHD and stroke. Stratified analyses suggested that associations of nighttime and daytime noise with CVD did not differ by prespecified effect modifiers. We found no evidence that inadequate sleep (< 5 hours per night) mediated associations of noise and CVD. Discussion: Outdoor median nighttime and daytime noise at the residential address was associated with a small increase in CVD risk in a cohort of adult female nurses.

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.

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.

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.