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Background Despite the growing and widespread use of glyphosate, a broad-spectrum herbicide and desiccant, very few studies have evaluated the extent and amount of human exposure. Objective We review documented levels of human exposure among workers in occupational settings and the general population. Methods We conducted a review of scientific publications on glyphosate levels in humans; 19 studies were identified, of which five investigated occupational exposure to glyphosate, 11 documented the exposure in general populations, and three reported on both. Results Eight studies reported urinary levels in 423 occupationally and para-occupationally exposed subjects; 14 studies reported glyphosate levels in various biofluids on 3298 subjects from the general population. Average urinary levels in occupationally exposed subjects varied from 0.26 to 73.5 μg/L; environmental exposure urinary levels ranged from 0.16 to 7.6 μg/L. Only two studies measured temporal trends in exposure, both of which show increasing proportions of individuals with detectable levels of glyphosate in their urine over time. Conclusions The current review highlights the paucity of data on glyphosate levels among individuals exposed occupationally, para-occupationally, or environmentally to the herbicide. As such, it is challenging to fully understand the extent of exposure overall and in vulnerable populations such as children. We recommend further work to evaluate exposure across populations and geographic regions, apportion the exposure sources (e.g., occupational, household use, food residues), and understand temporal trends.

Keywords: Agricultural workers, Heat strain, Heat stress, Heat education

National-scale empirical models for air pollution can include hundreds of geographic variables. The impact of model parsimony (i.e., how model performance differs for a large versus small number of covariates) has not been systematically explored. We aim to (1) build annual-average integrated empirical geographic (IEG) regression models for the contiguous U.S. for six criteria pollutants during 1979-2015; (2) explore systematically the impact on model performance of the number of variables selected for inclusion in a model; and (3) provide publicly available model predictions. We compute annual-average concentrations from regulatory monitoring data for PM10, PM2.5, NO2, SO2, CO, and ozone at all monitoring sites for 1979-2015. We also use ~350 geographic characteristics at each location including measures of traffic, land use, land cover, and satellite-based estimates of air pollution. We then develop IEG models, employing universal kriging and summary factors estimated by partial least squares (PLS) of geographic variables. For all pollutants and years, we compare three approaches for choosing variables to include in the PLS model: (1) no variables, (2) a limited number of variables selected from the full set by forward selection, and (3) all variables. We evaluate model performance using 10-fold cross-validation (CV) using conventional and spatially-clustered test data. Models using 3 to 30 variables selected from the full set generally have the best performance across all pollutants and years (median R2 conventional [clustered] CV: 0.66 [0.47]) compared to models with no (0.37 [0]) or all variables (0.64 [0.27]). Concentration estimates for all Census Blocks reveal generally decreasing concentrations over several decades with local heterogeneity. Our findings suggest that national prediction models can be built by empirically selecting only a small number of important variables to provide robust concentration estimates. Model estimates are freely available online.

Long-term ozone ([Formula: see text]) exposure is associated with cardiovascular mortality, but little is known about the associations between [Formula: see text] and subclinical arterial disease. We studied the longitudinal association of exposure to [Formula: see text] and progression of key subclinical arterial markers in adults: intima-media thickness of common carotid artery ([Formula: see text]), carotid plaque (CP) burden, and coronary artery calcification (CAC). CAC was measured one to four times at baseline and at follow-up exams (1999–2012) by computed tomography (CT) in 6,619 healthy adults, recruited at age 45-84 y without cardiovascular disease (CVD), over a mean of 6.5 y (standard deviation: 3.5 y). [Formula: see text] and CP burden were quantified in 3,392 participants using carotid artery ultrasound imaging acquired over a mean of 9 y (1.7 y). Over 91% and 89% participants had at least one follow-up [Formula: see text] and CAC measurement, respectively. Residence-specific [Formula: see text] concentrations were estimated by a validated spatiotemporal model spanning from 1999 to 2012. This model relied on comprehensive monitoring data and geographical variables to predict individualized long-term average concentrations since baseline. Linear mixed models and logistic regression model were used to evaluate relationships of long-term average exposure to [Formula: see text] with longitudinal change in [Formula: see text], CAC, and CP formation, respectively. Mean progression rates of [Formula: see text] and CAC were [Formula: see text] and [Formula: see text]. CP formation was identified in 55% of the subjects. A [Formula: see text] increase in long-term average [Formula: see text] exposure was associated with a [Formula: see text] [95% confidence interval (CI): 1.4, 9.7] greater increase in [Formula: see text] over 10 y. A [Formula: see text] increase in [Formula: see text] was also associated with new CP formation [odds ratio (OR): 1.2 (95% CI: 1.1, 1.4)] but not CAC progression [[Formula: see text] (95% CI: [Formula: see text], 2)]. Associations were robust in the analysis with extended covariate adjustment, including copollutants, i.e., nitrogen oxides ([Formula: see text]) and particulate matter with diameter [Formula: see text] ([Formula: see text]). Over almost a decade of follow-up, outdoor [Formula: see text] concentrations were associated with increased rate of carotid wall thickness progression and risk of new plaque formation, suggesting arterial injury in this cohort. https://doi.org/10.1289/EHP3325.

Background Wildfire events are increasing in prevalence in the western United States. Research has found mixed results on the degree to which exposure to wildfire smoke is associated with an increased risk of mortality. Methods We tested for an association between exposure to wildfire smoke and non-traumatic mortality in Washington State, USA. We characterized wildfire smoke days as binary for grid cells based on daily average PM 2.5 concentrations, from June 1 through September 30, 2006–2017. Wildfire smoke days were defined as all days with assigned monitor concentration above a PM 2.5 value of 20.4 μg/m 3 , with an additional set of criteria applied to days between 9 and 20.4 μg/m 3 . We employed a case-crossover study design using conditional logistic regression and time-stratified referent sampling, controlling for humidex. Results The odds of all-ages non-traumatic mortality with same-day exposure was 1.0% (95% CI: − 1.0 - 4.0%) greater on wildfire smoke days compared to non-wildfire smoke days, and the previous day’s exposure was associated with a 2.0% (95% CI: 0.0–5.0%) increase. When stratified by cause of mortality, odds of same-day respiratory mortality increased by 9.0% (95% CI: 0.0–18.0%), while the odds of same-day COPD mortality increased by 14.0% (95% CI: 2.0–26.0%). In subgroup analyses, we observed a 35.0% (95% CI: 9.0–67.0%) increase in the odds of same-day respiratory mortality for adults ages 45–64. Conclusions This study suggests increased odds of mortality in the first few days following wildfire smoke exposure. It is the first to examine this relationship in Washington State and will help inform local and state risk communication efforts and decision-making during future wildfire smoke events.

Background Disparities in cancer incidence and mortality have been observed by measures of area-level socioeconomic status (SES); however, the extent to which these disparities are explained by individual SES is unclear. Methods Participants included 60 756 men and women in the VITamins And Lifestyle (VITAL) study cohort, aged 50–76 years at baseline (2000–2002) and followed through 2010. We constructed a block group SES index using the 2000 US Census and fit Cox proportional hazards models to estimate the association between area-level SES (by quintile) and total and site-specific cancer incidence and total cancer mortality, with and without household income and individual education in the models. Results Lower area-level SES was weakly associated with higher total cancer incidence and lower prostate cancer risk, but was not associated with risk of breast cancer. Compared with the highest-SES areas, living in the lowest-SES areas was associated with higher lung (HR: 2.21, 95% CI 1.69 to 2.90) and colorectal cancer incidence (HR: 1.52, 95% CI 1.11 to 2.09) and total cancer mortality (HR: 1.68, 95% CI 1.47 to 1.93). Controlling for individual education and household income weakened the observed associations, but did not eliminate them (lung cancer HR: 1.43, 95% CI 1.07 to 1.91; colorectal cancer HR: 1.35, 95% CI 0.97 to 1.88; cancer mortality HR: 1.28, 95% CI 1.11 to 1.48). Conclusions Area-level socioeconomic disparities exist for several cancer outcomes. These differences are not fully explained by individual SES, suggesting area-level factors may play a role.

Recent research suggests that heat exposure may increase the risk of traumatic injuries. Published heat-related epidemiological studies have relied upon exposure data from individual weather stations. To evaluate the association between heat exposure and traumatic injuries in outdoor agricultural workers exposed to ambient heat and internal heat generated by physical activity using modeled ambient exposure data. A case-crossover study using time-stratified referent selection among 12,213 outdoor agricultural workers with new Washington State Fund workers' compensation traumatic injury claims between 2000 and 2012 was conducted. Maximum daily Humidex exposures, derived from modeled meteorological data, were assigned to latitudes and longitudes of injury locations on injury and referent dates. Conditional logistic regression was used to estimate odds ratios of injury for a priori daily maximum Humidex categories. The mean of within-stratum (injury day and corresponding referent days) standard deviations of daily maximum Humidex was 4.8. The traumatic injury odds ratio was 1.14 (95% confidence interval 1.06, 1.22), 1.15 (95% confidence interval 1.06, 1.25), and 1.10 (95% confidence interval 1.01, 1.20) for daily maximum Humidex of 25-29, 30-33, and ≥34, respectively, compared to < 25, adjusted for self-reported duration of employment. Stronger associations were observed during cherry harvest duties in the June and July time period, compared to all duties over the entire study period. Agricultural workers laboring in warm conditions are at risk for heat-related traumatic injuries. Combined heat-related illness and injury prevention efforts should be considered in high-risk populations exposed to warm ambient conditions in the setting of physical exertion.

Cohort studies of the relationship between air pollution exposure and chronic health effects require predictions of exposure over long periods of time. We developed a unified modeling approach for predicting fine particulate matter, nitrogen dioxide, oxides of nitrogen, and black carbon (as measured by light absorption coefficient) in six U.S. metropolitan regions from 1999 through early 2012 as part of the Multi-Ethnic Study of Atherosclerosis and Air Pollution (MESA Air). We obtained monitoring data from regulatory networks and supplemented those data with study-specific measurements collected from MESA Air community locations and participants' homes. In each region, we applied a spatiotemporal model that included a long-term spatial mean, time trends with spatially varying coefficients, and a spatiotemporal residual. The mean structure was derived from a large set of geographic covariates that was reduced using partial least-squares regression. We estimated time trends from observed time series and used spatial smoothing methods to borrow strength between observations. Prediction accuracy was high for most models, with cross-validation R2 (R2CV) > 0.80 at regulatory and fixed sites for most regions and pollutants. At home sites, overall R2CV ranged from 0.45 to 0.92, and temporally adjusted R2CV ranged from 0.23 to 0.92. This novel spatiotemporal modeling approach provides accurate fine-scale predictions in multiple regions for four pollutants. We have generated participant-specific predictions for MESA Air to investigate health effects of long-term air pollution exposures. These successes highlight modeling advances that can be adopted more widely in modern cohort studies.

Objectives The primary objective of this study was to assess the relationship between heat exposure and occupational traumatic injuries among construction workers. Methods We assessed the relationship between humidex, a measure of apparent temperature, and Washington State Fund workers' compensation injuries among outdoor construction workers using a case-crossover design with time-stratified referent selection. Warm month (March-October) adult outdoor construction traumatic injury claims from 2000-2012 were spatiotemporally joined with high-resolution meteorological data. We used conditional logistic regression with linear splines to assess the association between maximum daily humidex and injuries. Results There were 63 720 occupational traumatic injury claims in construction that met our eligibility criteria during the study period. The traumatic injury odds ratio (OR) was 1.005 [95% confidence interval (CI) 1.003-1.007] per one °C change in humidex. In the spline analyses, we observed a nearly linear association of humidex with the risk of a traumatic injury. Effect estimates were higher among younger (18-24 years) and older (>54 years) workers, workers with lower extremity injuries, workers with less job experience, smaller employers, workers working in Western Washington, and time of injury before 12:30 hours, although CI of effect estimates overlapped in stratified analysis categories. Conclusions In this study of Washington outdoor construction workers, increasing maximum daily humidex was associated with increasing traumatic injury risk. Further work should explore mechanisms of the association between heat exposure and traumatic injuries. Injury prevention efforts targeted at construction should address heat-related risk factors. In addition, heat awareness campaigns should address outcomes beyond heat-related illness.

In this prospective study of more than 65,000 women, fine particulate air pollution was found to be associated with an increased risk of cardiovascular events and death from cardiovascular causes. These observations add to the growing evidence that air pollution, especially fine particulate matter, has important adverse health consequences. Fine particulate air pollution was found to be associated with an increased risk of cardiovascular events and death from cardiovascular causes. Exposure to air pollution has been associated with death and hospitalization from cardiovascular causes. 1 Uncertainty remains about the magnitude of these associations, the mechanisms, and the effects of long-term exposure to pollutants, as compared with short-term exposure. Although previous studies of daily increases in exposure to pollution have assessed both fatal and nonfatal events, 2 studies investigating long-term exposure — estimating average exposure during years of follow-up — have evaluated mortality only on the basis of death certificates. 3 – 8 The increase in mortality associated with long-term exposure to air pollution is larger than that seen in studies of short-term exposure, and . . .