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BACKGROUND: Midlife residential exposure to greenspace may slow cognitive decline by increasing opportunities for physical activity and social connection, restoring attention, or reducing stress or adverse environmental exposures. However, prospective studies on the association between greenness and cognitive decline are sparse. OBJECTIVE: We investigated the prospective association between greenness at midlife and cognitive decline later in life. We explored effect measure modification by apolipoprotein E (APOE)-E4 carrier status, neighborhood socioeconomic status (NSES), and rural/urban regions. METHODS: The Nurses' Health Study (N = 121,700) started in 1976 with married female nurses, 30-55 years of age, located across 11 US states. We examined 16,962 nurses who were enrolled in a substudy starting in 1995-2001 (mean age = 74 y) through 2008. We assessed average summer residential greenness in a 270-m buffer using Landsat Normalized Difference Vegetation Index data from 1986-1994. Starting in 1995-2001, participants underwent up to four repeated measures of five cognitive tests. A global composite score was calculated as the average of all z-scores for each task to evaluate overall cognition. We used linear mixed models to evaluate the association of average greenness exposure at midlife with cognitive decline in later life, adjusted for age, education, NSES, and depression. RESULTS: In adjusted models, higher midlife greenness exposure [per interquartile range (IQR): 0.18] was associated with a 0.004-unit (95% CI: 0.001, 0.006) slower annual rate of cognitive decline. For comparison, we found that 1 year of age is related to a -0.006 mean annual difference for global cognition in the full sample; thus, higher midlife greenness appeared equivalent to slowing cognitive decline by ~ 8 months. In analysis exploring gene--environment interactions, we found that among APOE-E4 carriers, an IQR increase in greenness was associated with a rate of decline that was slower by 0.01 units of global composite score (95% CI: 0.0004, 0.02). This association was attenuated among APOE-E4 noncarriers. We did not observe associations between greenness and baseline or annual rate of cognitive decline of verbal memory. DISCUSSION: Higher midlife greenness exposure is associated with slower cognitive decline later in life. Future research is necessary to confirm these findings. https://doi.org/10.1289/EHP13588, Introduction Literature has suggested that Alzheimer's disease and related dementia (ADRD), the seventh leading cause of death in the United States, (1) may begin [greater than or equal to]20 y [...]

BACKGROUND: Parametric g-computation is an attractive analytic framework to study the health effects of air pollution. Yet, the ability to explore biologically relevant exposure windows within this framework is underdeveloped. OBJECTIVES: We outline a novel framework for how to incorporate complex lag-responses using distributed lag models (DLMs) into parametric g-computation analyses for survival data. We call this approach "g-survival-DLM" and illustrate its use examining the association between [PM.sub.2.5] during pregnancy and the risk of preterm birth (PTB). METHODS: We applied the g-survival-DLM approach to estimate the hypothetical static intervention of reducing average [PM.sub.2.5] in each gestational week by 20% on the risk of PTB among 9,403 deliveries from Beth Israel Deaconess Medical Center, Boston, Massachusetts, 2011-2016. Daily [PM.sub.2.5] was taken from a 1-km grid model and assigned to address at birth. Models were adjusted for sociodemographics, time trends, nitrogen dioxide, and temperature. To facilitate implementation, we provide a detailed description of the procedure and accompanying R syntax. RESULTS: There were 762 (8.1%) PTBs in this cohort. The gestational week-specific median [PM.sub.2.5] concentration was relatively stable across pregnancy at ~7[micro]g/[m.sup.3]. We found that our hypothetical intervention strategy changed the cumulative risk of PTB at week 36 (i.e., the end of the preterm period) by -0.009 (95% confidence interval: -0.034, 0.007) in comparison with the scenario had we not intervened, which translates to about 86 fewer PTBs in this cohort. We also observed that the critical exposure window appeared to be weeks 5-20. DISCUSSION: We demonstrate that our g-survival-DLM approach produces easier-to-interpret, policy-relevant estimates (due to the g-computation); prevents immortal time bias (due to treating PTB as a time-to-event outcome); and allows for the exploration of critical exposure windows (due to the DLMs). In our illustrative example, we found that reducing fine particulate matter [particulate matter (PM) with aerodynamic diameter, Introduction Pregnant individuals and their fetuses are particularly susceptible to environmental pollutants. (1) Yet, identifying whether environmental exposures cause preterm birth (PTB)--for which the long-term sequelae have been well established [...]

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 [L.sub.50] nighttime and [L.sub.50] daytime anthropogenic modeled noise estimates from a U.S. National Parks Service model ([L.sub.50]: 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 [L.sub.50] nighttime noise (3.67 dBA) and [L.sub.50] 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 ([L.sub.eq]) measures were stronger than for the anthropogenic statistical [L.sub.50] noise measures. Similar associations were observed for CHD and stroke. Interaction analyses suggested that associations of [L.sub.50] nighttime and [L.sub.50] daytime noise with CVD did not differ by prespecified effect modifiers. We found no evidence that inadequate sleep ( DISCUSSION: Outdoor [L.sub.50] 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, Introduction Noise, or unwanted sound exposure, is the second largest environmental cause of health problems, after air pollution, and has been associated with multiple adverse outcomes, such as annoyance, sleep [...]

Introduction In epidemiological studies, greenness exposure is often measured by calculating the mean satellite-derived Normalized Difference Vegetation Index (NDVI) within circular buffers around residential addresses. (1,2) These buffers can range [...]

BackgroundDioxins are persistent organic pollutants generated from industrial combustion processes such as waste incineration. To date, results from epidemiologic studies of dioxin exposure and breast cancer risk have been mixed.ObjectivesTo prospectively examine the association between ambient dioxin exposure using a nationwide spatial database of industrial dioxin-emitting facilities and invasive breast cancer risk in the Nurses' Health Study II (NHSII).MethodsNHSII includes female registered nurses in the US who have completed self-administered biennial questionnaires since 1989. Incident invasive breast cancer diagnoses were self-reported and confirmed by medical record review. Dioxin exposure was estimated based on residential proximity, duration of residence, and emissions from facilities located within 3, 5, and 10 km around geocoded residential addresses updated throughout follow-up. Cox regression models adjusted for breast cancer risk factors were used to calculate hazard ratios (HRs) and 95% confidence intervals (CIs).ResultsFrom 1989 to 2013, 3840 invasive breast cancer cases occurred among 112,397 participants. There was no association between residential proximity to any dioxin facilities (all facilities combined) and breast cancer risk overall. However, women who resided within 10 km of any municipal solid waste incinerator (MSWI) compared to none had increased breast cancer risk (adjusted HR = 1.15, 95% CI: 1.03, 1.28), with stronger associations noted for women who lived within 5 km (adjusted HR = 1.25, 95% CI: 1.04, 1.52). Positive associations were also observed for longer duration of residence and higher dioxin emissions from MSWIs within 3, 5, and 10 km. There were no clear differences in patterns of association for ER + vs. ER-breast cancer or by menopausal status.DiscussionResults from this study support positive associations between dioxin exposure from MSWIs and invasive breast cancer risk.

The rapid pace of the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2; COVID-19) pandemic presents challenges to the real-time collection of population-scale data to inform near-term public health needs as well as future investigations. We established the COronavirus Pandemic Epidemiology (COPE) consortium to address this unprecedented crisis on behalf of the epidemiology research community. As a central component of this initiative, we have developed a COVID Symptom Study (previously known as the COVID Symptom Tracker) mobile application as a common data collection tool for epidemiologic cohort studies with active study participants. This mobile application collects information on risk factors, daily symptoms, and outcomes through a user-friendly interface that minimizes participant burden. Combined with our efforts within the general population, data collected from nearly 3 million participants in the United States and United Kingdom are being used to address critical needs in the emergency response, including identifying potential hot spots of disease and clinically actionable risk factors. The linkage of symptom data collected in the app with information and biospecimens already collected in epidemiology cohorts will position us to address key questions related to diet, lifestyle, environmental, and socioeconomic factors on susceptibility to COVID-19, clinical outcomes related to infection, and long-term physical, mental health, and financial sequalae. We call upon additional epidemiology cohorts to join this collective effort to strengthen our impact on the current health crisis and generate a new model for a collaborative and nimble research infrastructure that will lead to more rapid translation of our work for the betterment of public health.

BackgroundEvidence of geographic disparities in breast cancer incidence within the U.S. and spatial analyses can provide insight into the potential contribution of environmental exposures or other geographically-varying factors to these disparities.MethodsWe applied generalized additive models (GAMs) to smooth geocoded residential coordinates while adjusting for covariates. Our analysis included 3,478 breast cancer cases among 24,519 control women from the Nurses' Health Study II (NHSII). We first examined associations with residential location during adolescence (high school address) or early adulthood (address in 1991). We then assessed the contribution from known individual-level risk factors, measures of socioeconomic status (SES), and occupational and environmental factors that vary spatially and have been linked to breast cancer. Secondary analyses by estrogen receptor (ER) and menopausal status were also conducted.ResultsWe identified geographic patterns of breast cancer risk associated with location during adolescence, with increased risk apparent in Michigan, the Northwest, and the New York City area, that shifted to southern New England when addresses during early adulthood were analyzed. Similar results were observed after adjustment for individual- and area-level factors, although spatial associations were no longer statistically significant.ConclusionBreast cancer risk is not spatially uniform across the U.S. and incidence patterns varied depending on the timing during life of the residence considered. Geographic disparities persisted even after accounting for established and suspected breast cancer risk factors, suggesting that unmeasured environmental or lifestyle risk factors may explain geographic variation in risk in different parts of the country.

Ultraviolet (UV) radiation exposure, the primary source of vitamin D for most people, may reduce breast cancer risk. To date, epidemiologic studies have shown inconsistent results. The Nurses' Health Study II is a U.S. nationwide prospective cohort of female registered nurses. A UV exposure model was linked with geocoded residential address histories. Early-life UV exposure was estimated based on the state of residence at birth, age 15, and age 30. Self-reported breast cancer was confirmed from medical records. Time-varying Cox regression models adjusted for established breast cancer risk factors were used to calculate hazard ratios (HRs) and 95% confidence intervals (CIs). From 1989 to 2013, 3,959 invasive breast cancer cases occurred among 112,447 participants. Higher UV exposure during adulthood was not associated with invasive breast cancer risk overall (adjusted HR comparing highest to lowest quintile = 1.00, 95% CI: 0.90, 1.11, p for trend = 0.64) or according to estrogen receptor (ER) status. There were suggestive inverse associations between ER- breast cancer and early-life UV exposure at birth (adjusted HR = 0.94, 95% CI: 0.88, 1.01 per interquartile range increase [15.7 mW/m2]), age 15 (adjusted HR = 0.96, 95% CI: 0.89, 1.04 per 18.0 mW/m2), and age 30 (adjusted HR = 0.90, 95% CI: 0.82, 1.00 per 27.7 mW/m2). Ambient UV exposure during adulthood was not associated with risk of invasive breast cancer overall or by ER status. However, we observed suggestive inverse associations between early-life UV exposure and ER- breast cancer risk.

BackgroundFindings from a recent prospective cohort study in California suggested increased risk of breast cancer associated with higher exposure to certain carcinogenic and estrogen-disrupting hazardous air pollutants (HAPs). However, to date, no nationwide studies have evaluated these possible associations. Our objective was to examine the impacts of mammary carcinogen and estrogen disrupting HAPs on risk of invasive breast cancer in a nationwide cohort.MethodsWe assigned HAPs from the US Environmental Protection Agency's 2002 National Air Toxics Assessment to 109,239 members of the nationwide, prospective Nurses' Health Study II (NHSII). Risk of overall invasive, estrogen receptor (ER)-positive (ER+), and ER-negative (ER-) breast cancer with increasing quartiles of exposure were assessed in time-varying multivariable proportional hazards models, adjusted for traditional breast cancer risk factors.ResultsA total of 3321 invasive cases occurred (2160 ER+, 558 ER-) during follow-up 1989-2011. Overall, there was no consistent pattern of elevated risk of the HAPs with risk of breast cancer. Suggestive elevations were only seen with increasing 1,2-dibromo-3-chloropropane exposures (multivariable adjusted HR of overall breast cancer = 1.12, 95% CI: 0.98-1.29; ER+ breast cancer HR = 1.09; 95% CI: 0.92, 1.30; ER- breast cancer HR = 1.14; 95% CI: 0.81, 1.61; each in the top exposure quartile compared to the lowest).ConclusionsExposures to HAPs during adulthood were not consistently associated with an increased risk of overall or estrogen-receptor subtypes of invasive breast cancer in this nationwide cohort of women.

BACKGROUND: Parametric g-computation is an attractive analytic framework to study the health effects of air pollution. Yet, the ability to explore biologically relevant exposure windows within this framework is underdeveloped. OBJECTIVES: We outline a novel framework for how to incorporate complex lag-responses using distributed lag models (DLMs) into parametric g-computation analyses for survival data. We call this approach “g-survival-DLM” and illustrate its use examining the association between PM2.5 during pregnancy and the risk of preterm birth (PTB). METHODS: We applied the g-survival-DLM approach to estimate the hypothetical static intervention of reducing average PM2.5 in each gestational week by 20% on the risk of PTB among 9,403 deliveries from Beth Israel Deaconess Medical Center, Boston, Massachusetts, 2011–2016. Daily PM2.5 was taken from a 1-km grid model and assigned to address at birth. Models were adjusted for sociodemographics, time trends, nitrogen dioxide, and temperature. To facilitate implementation, we provide a detailed description of the procedure and accompanying R syntax. RESULTS: There were 762 (8.1%) PTBs in this cohort. The gestational week-specific median PM2.5concentration was relatively stable across pregnancy at ~7μg/m³. We found that our hypothetical intervention strategy changed the cumulative risk of PTB at week 36 (i.e., the end of the preterm period) by -0.009 (95% confidence interval: -0.034, 0.007) in comparison with the scenario had we not intervened, which translates to about 86 fewer PTBs in this cohort. We also observed that the critical exposure window appeared to be weeks 5–20. DISCUSSION: We demonstrate that our g-survival-DLM approach produces easier-to-interpret, policy-relevant estimates (due to the g-computation); prevents immortal time bias (due to treating PTB as a time-to-event outcome); and allows for the exploration of critical exposure windows (due to the DLMs). In our illustrative example, we found that reducing fine particulate matter [particulate matter (PM) with aerodynamic diameter ≤2.5 μm (PM2.5)] during gestational weeks 5-20 could potentially lower the risk of PTB. [ABSTRACT FROM AUTHOR]

Background: Sleep disruption is linked with chronic disease, and aircraft noise can disrupt sleep. However, there are few investigations of aircraft noise and sleep in large cohorts. Objectives: We examined associations between aircraft noise and self-reported sleep duration and quality in the Nurses' Health Study, a large prospective cohort. Methods: Aircraft nighttime equivalent sound levels (Lnight) and day-night average sound levels (DNL) were modeled around 90 U.S. airports from 1995 to 2015 in 5-y intervals using the Aviation Environmental Design Tool and linked to geocoded participant residential addresses. Lnight exposure was dichotomized at the lowest modeled level of 45 A-weighted decibels [dB(A)] and at multiple cut points for DNL. Multiple categories of both metrics were compared with Results: In 35,226 female nurses averaging 66.1 years of age at baseline, prevalence of short sleep duration and poor sleep quality were 29.6% and 13.1%, respectively. In multivariable models, exposure to Lnight [greater than or equal to]45 dB(A) was associated with 23% [95% confidence interval (CI): 7%, 40%] greater odds of short sleep duration but was not associated with poor sleep quality (9% lower odds; 95% CI: -30%, 19%). Increasing categories of Lnight and DNL [greater than or equal to]45 dB(A) suggested an exposure-response relationship for short sleep duration. We observed higher magnitude associations among participants living in the West, near major cargo airports, and near water-adjacent airports and among those reporting no hearing loss. Discussion: Aircraft noise was associated with short sleep duration in female nurses, modified by individual and airport characteristics. https://doi.org/10.1289/EHP10959, Introduction Sleep is an essential, natural process needed for healthy brain and general body functioning. (1) Disruption of sleep can cause drowsiness and poor concentration and adversely affect the metabolic, [...]

Exposure to ambient fine particulate matter (PM2.5) is a major global health concern. Quantitative estimates of attributable mortality are based on disease-specific hazard ratio models that incorporate risk information from multiple PM2.5 sources (outdoor and indoor air pollution from use of solid fuels and secondhand and active smoking), requiring assumptions about equivalent exposure and toxicity. We relax these contentious assumptions by constructing a PM2.5-mortality hazard ratio function based only on cohort studies of outdoor air pollution that covers the global exposure range. We modeled the shape of the association between PM2.5 and nonaccidental mortality using data from 41 cohorts from 16 countries-the Global Exposure Mortality Model (GEMM). We then constructed GEMMs for five specific causes of death examined by the global burden of disease (GBD). The GEMM predicts 8.9 million [95% confidence interval (CI): 7.5-10.3] deaths in 2015, a figure 30% larger than that predicted by the sum of deaths among the five specific causes (6.9; 95% CI: 4.9-8.5) and 120% larger than the risk function used in the GBD (4.0; 95% CI: 3.3-4.8). Differences between the GEMM and GBD risk functions are larger for a 20% reduction in concentrations, with the GEMM predicting 220% higher excess deaths. These results suggest that PM2.5 exposure may be related to additional causes of death than the five considered by the GBD and that incorporation of risk information from other, nonoutdoor, particle sources leads to underestimation of disease burden, especially at higher concentrations.

BackgroundRadon and its decay products, a source of ionizing radiation, are primarily inhaled and can deliver a radiation dose to breast tissue, where they may continue to decay and emit DNA damage-inducing particles. Few studies have examined the relationship between radon and breast cancer.MethodsThe Nurses' Health Study II (NHSII) includes U.S. female registered nurses who completed biennial questionnaires since 1989. Self-reported breast cancer was confirmed from medical records. County-level radon exposures were linked with geocoded residential addresses updated throughout follow-up. Time-varying Cox regression models adjusted for established breast cancer risk factors were used to calculate hazard ratios (HRs) and 95% confidence intervals (CIs).ResultsFrom 1989 to 2013, 3966 invasive breast cancer cases occurred among 112,639 participants. Increasing radon exposure was not associated with breast cancer risk overall (adjusted HR comparing highest to lowest quintile = 1.06, 95% CI: 0.94, 1.21, p for trend = 0.30). However, women in the highest quintile of exposure (≥74.9 Bq/m3) had a suggested elevated risk of ER-/PR- breast cancer compared to women in the lowest quintile (

Data indicate that the prevalence of autism spectrum disorder (ASD) may be increasing and that it varies geographically. We investigated associations between residential location and ASD in the children of Nurses' Health Study II (United States) participants in order to generate hypotheses about social and environmental factors related to etiology or diagnosis. Analyses included data on 13,507 children born during 1989-1999 (486 with ASD). We explored relationships between ASD and residential location both at birth and at age 6 years (i.e., closer to average age at diagnosis). Generalized additive models were used to predict ASD odds across the United States. Children born in New England were 50% more likely to be diagnosed with ASD compared with children born elsewhere in the United States. Patterns were not explained by geographic variation in maternal age, birth year, child's sex, community income, or prenatal exposure to hazardous air pollutants, indicating that spatial variation is not attributable to these factors. Using the residential address at age 6 years produced similar results; however, areas of significantly decreased ASD odds were observed in the Southeast, where children were half as likely to have ASD. These results may indicate that diagnostic factors are driving spatial patterns; however, we cannot rule out the possibility that other environmental factors are influencing distributions.

Background: Several studies have evaluated whether the distribution of natural environments differs between marginalized and privileged neighborhoods. However, most studies restricted their analyses to a single or handful of cities and used different natural environment measures. Objectives: We evaluated whether natural environments are inequitably distributed based on socioeconomic status (SES) and race/ethnicity in the contiguous United States. Methods: We obtained SES and race/ethnicity data (2015-2019) for all U.S. Census tracts. For each tract, we calculated the Normalized Different Vegetation Index (NDVI) for 2020, NatureScore (a proprietary measure of the quantity and quality of natural elements) for 2019, park cover for 2020, and blue space for 1984-2018. We used generalized additive models with adjustment for potential confounders and spatial autocorrelation to evaluate associations of SES and race/ethnicity with NDVI, NatureScore, park cover, and odds of containing blue space in all tracts (n = 71,532) and in urban tracts (n = 45,338). To compare effect estimates, we standardized NDVI, NatureScore, and park cover so that beta coefficients presented a percentage increase or decrease of the standard deviation (SD). Results: Tracts with higher SES had higher NDVI, NatureScore, park cover, and odds of containing blue space. For example, urban tracts in the highest median household income quintile had higher NDVI [44.8% of the SD (95% CI: 42.8, 46.8)] and park cover [16.2% of the SD (95% CI: 13.5, 19.0)] compared with urban tracts in the lowest median household income quintile. Across all tracts, a lower percentage of non- Hispanic White individuals and a higher percentage of Hispanic individuals were associated with lower NDVI and NatureScore. In urban tracts, we observed weak positive associations between percentage non-Hispanic Black and NDVI, NatureScore, and park cover; we did not find any clear associations for percentage Hispanics. Discussion: Multiple facets of the natural environment are inequitably distributed in the contiguous United States. https://doi.org/10.1289/EHP11164, Introduction Of all high- and middle-income countries, the United States has among the highest income-related disparities in self-reported health and health care measures. (1) Health disparities have been attributed to [...]

We aimed to investigate the associations between maternal intake of folate, vitamin B12, B6, B2, methionine, choline, phosphatidylcholine and betaine during the period surrounding pregnancy and offspring weight outcomes from birth to early adulthood. These associations were examined among 2454 mother–child pairs from the Nurses' Health Study II and Growing Up Today Study. Maternal energy-adjusted nutrient intakes were derived from food frequency questionnaires. Birth weight, body size at age 5 and repeated BMI measurements were considered. Overweight/obesity was defined according to the International Obesity Task Force (<18 years) and World Health Organization guidelines (18+ years). Among other estimands, we report relative risks (RRs) for offspring ever being overweight with corresponding 95% confidence intervals across quintiles of dietary factors, with the lowest quintile as the reference. In multivariate-adjusted models, higher maternal intakes of phosphatidylcholine were associated with a higher risk of offspring ever being overweight (RRQ5vsQ1 = 1.16 [1.01–1.33] p-trend: 0.003). The association was stronger among offspring born to mothers with high red meat intake (high red meat RRQ5vsQ1 = 1.50 [1.14–1.98], p-trend: 0.001; low red meat RRQ5vsQ1 = 1.05 [0.87–1.27], p-trend: 0.46; p-interaction = 0.13). Future studies confirming the association between a higher maternal phosphatidylcholine intake during pregnancy and offspring risk of being overweight or obese are needed. [ABSTRACT FROM AUTHOR]

BackgroundThere is increasing concern that environmental exposures, such as air pollution, may be related to increasing rates of breast cancer; however, results from cohort studies have been mixed. We examined the association between particulate matter (PM) and measures of distance to roadway with the risk of incident breast cancer in the prospective nationwide Nurses' Health Study II (NHSII) cohort.MethodsIncident invasive breast cancer from 1993 to 2011 (N = 3,416) was assessed among 115,921 women in the NHSII cohort. Time-varying Cox proportional hazards models were used to calculate HRs and 95% confidence intervals (95% CI) for increases in ambient exposures to PM10, PM2.5-10, and PM2.5 and residential roadway proximity categories.ResultsIn multivariable adjusted models, there was little evidence of an increased risk of breast cancer (or any of the receptor-specific subtypes) overall or by menopausal status with PM exposure. There was, however, a suggestion of increased risks among women living

BackgroundOccupational cohort studies are often challenged by the Healthy Worker Survivor Effect, which may bias standard methods of analysis. G-estimation of structural failure time models is an approach for reducing this type of bias. Accelerated failure time models have recently been applied in an occupational cohort but cumulative failure time models have not.MethodsWe used g-estimation of a cumulative failure time model to assess the effect of working as a long-haul driver on ischaemic heart disease mortality in a cohort of 30 448 men employed in the unionised US trucking industry in 1985. Exposure was defined by job title and based on work records. We also applied g-estimation of an accelerated failure time model as a sensitivity analysis and approximated HRs from both models to compare them.ResultsThe risk ratio (RR) obtained from the cumulative failure time model, comparing the observed risk under no intervention to the risk had nobody ever been exposed as a long-haul driver, was 1.09 (95% CI 1.02 to 1.16). The RR comparing the risk had everyone been exposed as long-haul driver for 8 years to the risk had nobody ever been exposed was 1.20 (95% CI 1.04 to 1.46). After HR approximations, accelerated failure time model results were similar.ConclusionsThe cumulative failure time model can effectively control time-varying confounding by Healthy Worker Survivor Effect, and provides an easily interpretable effect estimate. RRs estimated from the cumulative failure time model indicate an elevated ischaemic heart disease mortality risk for long-haul drivers in the US trucking industry.

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

Abstract Background Previous studies have suggested associations of adult exposures to secondhand smoke (SHS) with respiratory symptoms, but no study has focused on blue-collar industrial environments. We assessed the association between SHS and respiratory symptoms in 1,562 non-current smoking U.S. trucking industry workers. Methods Information on SHS exposure and respiratory health was obtained by questionnaire. Multiple logistic regression analyses were used to assess the associations of recent and lifetime exposures to SHS with chronic phlegm, chronic cough, and any wheeze, defined by American Thoracic Society criteria. Results In analyses adjusted for age, gender, race, childhood SHS exposure, former smoking, pack-years of smoking and years since quitting, body mass index, job title, region of the country, and urban residence, recent exposures to SHS were associated with all three respiratory symptoms (odds ratio (OR) = 1.46; 95% confidence interval (CI) = 1.00-2.13) for chronic cough, 1.55 (95% CI = 1.08-2.21) for chronic phlegm, and 1.76 (95% CI = 1.41-2.21) for any wheeze). Workplace exposure was the most important recent exposure. Childhood exposure to SHS was also associated with all three symptoms, but only statistically significantly for chronic phlegm (OR = 1.84; 95% CI = 1.24-2.75). Additional years of living with a smoker were associated with an increased risk, but there was no evidence of a dose–response, except for chronic phlegm. Conclusions In this group of trucking industry workers, childhood and recent exposures to SHS were related to respiratory symptoms.