Population-level Exposure Research Articles

Population-Level Exposure to PM2.5, NO2, Greenness (NDVI), Accessible Greenspace, Road Noise, and Rail Noise in England

Air pollution, greenspace and noise are interrelated environmental factors with the potential to influence human health outcomes. Research has measured these exposures in diverse ways across the globe, but no study has yet performed a country-wide analysis of air pollution, greenspace, and noise in England. This study examined cross-sectional PM2.5, NO2, greenness, accessible greenspace, road noise, and rail noise exposure data at all residential postcodes in England (n = 1,227,681). Restricted cubic spline models were fitted between each environmental exposure and a measure of socioeconomic status, the Index of Multiple Deprivation (IMD) rank. Population-weighted exposures by IMD deciles, urbanicity, and region were subsequently estimated. Restricted cubic spline models were also fitted between greenness and each other environmental exposure in the study. The results show some evidence of inequalities in exposure to air pollutants, greenspace, and noise across England. Notably, there is a socioeconomic gradient in greenness, NO2, PM2.5, and road noise in London. In addition, NO2, PM2.5, and road noise exposure decrease as greenness increases in urban areas. Concerningly, almost all air pollution estimates in our study exceed international health guidelines. Further research is needed to elucidate the socioeconomic patterns and health impacts of air pollution, greenspace, and noise over time.

Trends in NHANES Biomonitored Exposures in California and the United States following Enactment of California's Proposition 65.

The prevalence of toxic chemicals in US commerce has prompted some states to adopt laws to reduce exposure. One with broad reach is California's Proposition 65 (Prop 65), which established a list of chemicals that cause cancer, developmental harm, or reproductive toxicity. The law is intended to discourage businesses from using these chemicals and to minimize consumer exposure. However, a key question remains unanswered: Has Prop 65 reduced population-level exposure to the listed chemicals? We used national biomonitoring data from the Centers for Disease Control and Prevention (CDC) to evaluate the impact of Prop 65 on population-level exposures. We evaluated changes in blood and urine concentrations of 37 chemicals (including phthalates, phenols, VOCs, metals, PAHs, and PFAS), among US National Health and Nutrition Examination Survey (NHANES) participants in relation to the time of chemicals' Prop 65 listing. Of these, 11 were listed prior to, 11 during, and 4 after the biomonitoring period. The remaining 11 were not listed but were closely related to a Prop 65-listed chemical. Where biomonitoring data were available from before and after the date of Prop 65 listing, we estimated the change in concentrations over time for Californians compared with non-Californians, using a difference-in-differences model. We used quantile regression to estimate changes in exposure over time, as well as differences between Californians and non-Californians at the 25th, 75th, and 95th percentiles. We found that concentrations of biomonitored chemicals generally declined nationwide over time irrespective of their inclusion on the Prop 65 list. Median bisphenol A (BPA) concentrations decreased 15% after BPA's listing on Prop 65, whereas concentrations of the nonlisted but closely related bisphenol S (BPS) increased 20% over this same period, suggesting chemical substitution. Californians generally had lower levels of biomonitored chemicals than the rest of the US population. Our findings suggest that increased scientific and regulatory attention, as well as public awareness of the harms of Prop 65-listed chemicals, prompted changes in product formulations that reduced exposure to those chemicals nationwide. Trends in bisphenols and several phthalates suggest that manufacturers replaced some listed chemicals with closely related but unlisted chemicals, increasing exposure to the substitutes. Our findings have implications for the design of policies to reduce toxic exposures, biomonitoring programs to inform policy interventions, and future research into the regulatory and market forces that affect chemical exposure. https://doi.org/10.1289/EHP13956.

Carbonated Beverage, Fruit Drink, and Water Consumption and Risk of Acute Stroke: the INTERSTROKE Case-Control Study.

Cold beverage intake (carbonated drinks, fruit juice/drinks, and water) may be important population-level exposures relevant to stroke risk and prevention. We sought to explore the association between intake of these beverages and stroke. INTERSTROKE is an international matched case-control study of first stroke. Participants reported beverage intake using food frequency questionnaires or were asked "How many cups do you drink each day of water?" Multivariable conditional logistic regression estimated odds ratios (OR) and 95% confidence intervals (CI) for associations with stroke. We include 13,462 cases and 13,488 controls; mean age was 61.7±13.4 years and 59.6% (n=16,010) were male. After multivariable adjustment, carbonated beverages were linearly associated with ischemic stroke (OR 2.39 [95% CI 1.64-3.49]); only consumption once/day was associated with intracerebral hemorrhage (ICH) (OR 1.58 [95% CI 1.23-2.03]). There was no association between fruit juice/drinks and ischemic stroke, but increased odds of ICH for once/day (OR 1.37 [95% CI 1.08-1.75)] or twice/day (OR 3.18 [95% CI 1.69-5.97]). High water intake (>7 cups/day) was associated ischemic stroke (OR 0.82 [95% CI 0.68-0.99]) but not ICH. Associations differed by Eugeographical region-increased odds for carbonated beverages in some regions only; opposing directions of association of fruit juices/drinks with stroke in selected regions. Carbonated beverages were associated with increased odds of ischemic stroke and ICH, fruit juice/drinks were associated with increased odds of ICH, and high water consumption was associated with reduced odds of ischemic stroke, with important regional differences. Our findings suggest optimizing water intake, minimizing fruit juice/drinks, and avoiding carbonated beverages.

Agent-based modelling of evacuation scenarios for a landslide-generated tsunami in Milford Sound, New Zealand

Agent-based modelling is a useful tool for evacuation planning as it can increase understanding of the factors affecting potential evacuation outcomes. In New Zealand, Milford Sound has been shown to have a high risk from landslide-generated tsunami, with an estimated 1-in-1000-year wave runup of ∼17 m arriving on shore within 2–7 min. With an annual average of >1500 people visiting a day, there is potential for widespread loss of life. However, the number of people present varies substantially with time of day and season, yet how this affects the ability to evacuate remains unknown. This research developed an agent-based model to understand how many people can be safely evacuated in Milford Sound and explored how the number of people initially exposed affected the evacuation outcome alongside the effect of potential changes to evacuation messaging. Assuming a 17 m wave, the results suggest that currently no one can safely evacuate before the shortest wave arrival time regardless of the number of people present. Altering evacuation messaging results in minimal gains, with only ∼5 % of the exposed population reaching safety in time. This work demonstrates the importance of evacuation modelling for understanding risk in isolated tourism destinations where the population exposure can fluctuate dramatically across multiple timescales. Accounting for changing population exposure is essential to understand whether evacuation is a suitable risk treatment and can provide valuable information for determining safe levels of population exposure in locations with high hazard but limited evacuation options.

Challenges and Approaches to Establishing Multi-Pathogen Serosurveillance: Findings from the 2023 Serosurveillance Summit.

Multiplex-based serological surveillance is a valuable but underutilized tool to understand gaps in population-level exposure, susceptibility, and immunity to infectious diseases. Assays for which blood samples can be tested for antibodies against several pathogens simultaneously, such as multiplex bead immunoassays, can more efficiently integrate public health surveillance in low- and middle-income countries. On March 7-8, 2023 a group of experts representing research institutions, multilateral organizations, private industry, and country partners met to discuss experiences, identify challenges and solutions, and create a community of practice for integrated, multi-pathogen serosurveillance using multiplex bead assay technologies. Participants were divided into six working groups: 1) supply chain; 2) laboratory assays; 3) seroepidemiology; 4) data analytics; 5) sustainable implementation; and 6) use case scenarios. These working groups discussed experiences, challenges, solutions, and research needs to facilitate integrated, multi-pathogen serosurveillance for public health. Several solutions were proposed to address challenges that cut across working groups.

Co-occurrence of wildfire smoke and extreme heat events in British Columbia, 2010-2022: Spatiotemporal patterns in population-level exposure

Co-occurrence of wildfire smoke and extreme heat events in British Columbia, 2010-2022: Spatiotemporal patterns in population-level exposure

A review of spatial-temporal data sources for estimating population-level exposures to oil and gas development in the United States

A review of spatial-temporal data sources for estimating population-level exposures to oil and gas development in the United States

Discordant performance of mpox serological assays

BackgroundSince July 23, 2022, global mpox cases reached 92,546, with over 31,000 in the United States. Asymptomatic carriage is a critical mechanism influencing the global dissemination of mpox. Seroprevalence studies are crucial for determining the epidemic's true burden, but uncertainties persist in serologic assay performance and how smallpox vaccination may influence assay interpretation. ObjectivesOur study aimed to assess the performance of several diagnostic assays among mpox-positive, vaccinated, and pre-outbreak negative control samples. This investigation sought to enhance our understanding and management of future mpox outbreaks. Study designSerum samples from 10 mpox-positive, five vaccinated uninfected, and 137 pre-outbreak controls were obtained for serological testing. The mpox-positive samples were obtained around 100 days post symptom onset, and vaccinated patients were sampled approximately 90 days post-vaccination. Multiple diagnostic assays were employed, including four commercial ELISAs (Abbexa, RayBioTech, FineTest, ProteoGenix) and a multiplex assay (MesoScale Diagnostics (MSD)) measuring five mpox and five smallpox antigens. ResultsThree commercial ELISA kits had low specificity (<50 %). The Proteogenix ELISA targeting the E8L antigen had a 94 % sensitivity and 87 % specificity. The E8L antigen on the MSD assay exhibited the greatest distinction between exposure groups, with 98 % sensitivity and 93 % specificity. ConclusionsNone of the assays could distinguish between mpox-positive and vaccinated samples. The MSD assay targeting the MPXV E8L antigen demonstrated the greatest differentiation between mpox-positive and pre-outbreak negative samples. Our findings underscore the imperative to identify sensitive and specific assays to monitor population-level mpox exposure and infection.

SARS-CoV-2 seroprevalence in people living with HIV in South Sudan

ObjectivesThe burden of SARS-CoV-2 infection in people living with HIV (PLHIV) in South Sudan is unknown. MethodsWe conducted a cross-sectional seroprevalence survey of SARS-CoV-2 immunoglobulin (Ig) G antibodies and other diseases of public health importance (strongyloidiasis, toxoplasmosis) in PLHIV in South Sudan during April 1, 2020-April 30, 2022. We used a multiplex SARS-CoV-2 immunoassay to detect IgG antibodies targeting the SARS-CoV-2 spike, receptor binding domain, and nucelocapsid (N) proteins, and antigens for other pathogens (Strongyloides stercoralis and Toxoplasma gondii). ResultsAmong 3518 samples tested, seroprevalence of IgG antibodies to SARS-CoV-2 spike protein and receptor binding domain 591 and nucleocapsid ranged from 1.4% (95% confidence interval [CI]: 0.9-2.1%) in April-June 2020 to 53.3% (95% CI: 49.5-57.1%) in January-March 2022. The prevalence of S. stercoralis IgG ranged between 27.3% (95% CI: 23.4-31.5%) in October-December 2021 and 47.2% (95% CI: 37.8-56.8%) in July-September 2021, and, for T. gondii IgG, prevalence ranged from 15.5% (95% CI: 13.3-17.9%) in April-June 2020 to 36.2% (95% CI: 27.4-46.2%) July-September 2021. ConclusionsBy early 2022, PLHIV in South Sudan had high rates of SARS-CoV-2 seropositivity. Surveillance of diseases of global health concern in PLHIV is crucial to estimate population-level exposure and inform public health responses.

A comparison of population-level exposure and equity tradeoffs across strategies to reduce fine particulate matter emissions from transportation sources in the northeastern US

BackgroundMany climate mitigation policies to reduce transportation emissions have public health benefits related to ambient air pollution. However, few health analyses consider the equity implications of alternative policies. Equity can be conceptualized in many different ways that may be relevant to communities, decision-makers, and other stakeholders. ObjectivesTo evaluate alternative transportation emissions reduction scenarios across the northeastern United States considering population exposure reductions and multiple equity constructs. MethodsWe developed four quantitative indicators reflecting equity constructs that aligned with stakeholder perspectives, including racial/ethnic exposure inequities, proportion of benefits in environmental justice communities, distribution of benefits among participating states, and rural/urban share of benefits. We analyzed numerous transportation emissions reduction scenarios for directly emitted fine particulate matter (primary PM2.5) covering 12 Northeast states and the District of Columbia. We used the Community Multiscale Air Quality model with the decoupled direct method to estimate the reduction in population-weighted primary PM2.5 exposure and the impact on equity for each scenario. ResultsScenarios that yielded greater reductions in population-weighted primary PM2.5 exposure generally emphasized emissions reductions in urban areas or states with large urban centers, with a more than threefold difference in benefits across scenarios. The higher exposure-benefit scenarios typically also had greater reductions in racial/ethnic exposure inequities but led to higher between-state or rural/urban inequality. Scenarios that targeted uniform percentage emission reductions from light or heavy-duty trucks best addressed rural/urban inequalities but led to the smallest reductions in racial/ethnic inequity. ConclusionThere are intrinsic tradeoffs among equity constructs, where focusing resources on distributing benefits across states or between urban and rural populations could come at the expense of less reduction in racial/ethnic exposure inequities or in environmental justice communities. Future health benefits analyses should incorporate multiple equity indicators that reflect different stakeholder perspectives and articulate the underlying constructs and tradeoffs.

Tea and coffee consumption and risk of acute stroke: The INTERSTROKE Study.

Stroke is a leading global cause of death and disability. Daily tea/coffee intake is consumed by > 50% of populations and may represent an important population-level exposure. Therefore, it is first essential that we better understand the associations between the tea/coffee intake and stroke. This research aims to generate hypotheses about the global associations between tea and coffee intake and stroke. These insights will identify interventions for stroke prevention that can be further explored using alternative study designs. INTERSTROKE is a large international matched case-control study of first stroke from 32 countries. Participants were asked "how many cups do you drink each day?" of coffee, green tea, black tea, and other tea. Multivariable conditional logistic regression was used to estimate odds ratios (ORs) and 95% confidence intervals (CIs) for associations between intake and stroke. We included 13,462 cases and 13,488 controls from INTERSTROKE; mean age was 61.7 (13.4) years and 59.6% (n = 16,010) were male. Overall, 19.4% (n = 5239) did not consume tea/coffee, 47.0% (n = 12,666) consumed tea only, 14.9% (n = 4024) consumed coffee alone, and 18.6% (n = 5021) consumed both, with significant regional variations. After multivariable adjustment, there was no association between low/moderate coffee intake and stroke, but high consumption (> 4/day) was associated with higher odds of all stroke (OR = 1.37 (95% CI = 1.06-1.77)) or ischemic stroke (OR = 1.32 (95% CI = 1.00-1.74)). Tea consumption was associated with lower odds of all (OR = 0.81 (95% CI = 0.69-0.94) for highest intake) or ischemic stroke (OR = 0.81 (95% CI = 0.68-0.98) for highest intake). High coffee consumption was associated with higher odds of all or ischemic stroke; low-moderate coffee had no association with stroke. In contrast, tea consumption was associated with lower odds of stroke. These associations suggest that individuals consider avoiding high coffee consumption (⩾ five cups/day) to impact future stroke risk. The design and rationale of INTERSTROKE was published previously. Individual participant data, or other documents are not available.

Insights into brominated flame retardant neurotoxicity: mechanisms of hippocampal neural cell death and brain region-specific transcriptomic shifts in mice.

Brominated flame retardants (BFRs) reduce flammability in a wide range of products including electronics, carpets, and paint, but leach into the environment to result in continuous, population-level exposure. Epidemiology studies have correlated BFR exposure with neurological problems, including alterations in learning and memory. This study investigated the molecular mechanisms mediating BFR-induced cell death in hippocampal cells and clarified the impact of hexabromocyclododecane (HBCD) exposure on gene transcription in the hippocampus, dorsal striatum, and frontal cortex of male mice. Exposure of hippocampus-derived HT-22 cells to various flame retardants, including tetrabromobisphenol-A (current use), HBCD (phasing out), or 2,2',4,4'-tetrabromodiphenyl ether (BDE-47, phased out) resulted in time, concentration, and chemical-dependent cellular and nuclear morphology alterations, alterations in cell cycle and increases in annexin V staining. All 3 BFRs increased p53 and p21 expression; however, inhibition of p53 nuclear translocation using pifthrin-α did not decrease cell death. Transcriptomic analysis upon low (10 nM) and cytotoxic (10 μM) BFR exposure indicated that HBCD and BDE-47 altered genes mediating autophagy-related pathways. Further evaluation showed that BFR exposure increased LC3-II conversion and autophagosome/autolysosome formation, and co-exposure with the autophagy inhibitor 3-methyladenine (3-MA) attenuated cytotoxicity. Transcriptomic assessment of select brain regions from subchronically HBCD-exposed male mice demonstrated alteration of genes mediating vesicular transport, with greater impact on the frontal cortex and dorsal striatum compared with the dorsal and ventral hippocampus. Immunoblot analysis demonstrated no increases in cell death or autophagy markers, but did demonstrate increases in the SNARE binding complex protein SNAP29, specifically in the dorsal hippocampus. These data demonstrate that BFRs can induce chemical-dependent autophagy in neural cells in vitro and provide evidence that BFRs induce region-specific transcriptomic and protein expression in the brain suggestive of changes in vesicular trafficking.

Wastewater-based epidemiology methodology to investigate human exposure to bisphenol A, bisphenol F and bisphenol S.

Wastewater-based epidemiology (WBE) has become an invaluable tool for tracking the evolution of use or exposure of/to numerous substances. Bisphenols, commonly utilized in manufacturing plastic goods, have been categorized as endocrine disrupting chemicals, underscoring the critical need for real-time data on their local-level exposure to safeguard public health. In this study, we have developed a novel analytical method and WBE framework for the assessment of population-level exposure to bisphenol A (BPA) and its most prominent substitutes, bisphenols F and S (BPF and BPS), through the determination their Phase II metabolites in wastewater by WBE. Stability and exclusivity tests denoted that glucuronides are not stable in sewage, whereas sulfate metabolites are good biomarkers. Therefore, a solid-phase extraction followed by liquid chromatography-tandem mass spectrometry method was developed for the bisphenols’ monosulfates and BPA bissulfate. The analytical method was validated with three different wastewater matrices, providing trueness (as recovery) in the 79–112 % range with relative standard deviations < 12 %, and method quantification limits below 2 ng L−1 for monosulfates, but higher (35 ng L−1) for BPA bissulfate. Subsequently, the method was applied to 24h-composite raw wastewater samples collected over a week in 4 different locations in Spain and Portugal. BPA bissulfate was not detected, but the three monosulfate metabolites of each bisphenol were positively detected in the samples, being the metabolite of BPA the most prevalent, followed by those of BPF and BPS. Community-wide BPA intake was then estimated to be higher than the European Food Safety Agency (EFSA) tolerable daily intake (TDI) of 2 × 10−4 µg kg−1day−1 in all locations. In the case of BPF and BPS, there is not enough metabolism data or even established limit, but they would also surpass safe levels in several locations if a similar metabolism and TDI would be assumed. This innovative method could be used to a larger set of wastewater-treatment plants as an early-warning approach on human exposure to bisphenols.

Evaluating Population-Level Interventions and Exposures for Suicide Prevention.

Evaluations of interventions targeting the population level are an essential component of the policy development cycle. Pre-post designs are widespread in suicide prevention research but have several significant limitations. To inform future evaluations, our aim is to explore the three most frequently used approaches for assessing the association between population-level interventions or exposures and suicide - the pre-post design, the difference-in-difference design, and Poisson regression approaches. The pre-post design and the difference-in-difference design will only produce unbiased estimates of an association if there are no underlying time trends in the data and there is no additional confounding from other sources. Poisson regression approaches with covariates for time can control for underlying time trends as well as the effects of other confounding factors. Our recommendation is that the default position should be to model the effects of population-level interventions or exposures using regression methods that account for time effects. The other designs should be seen as fall-back positions when insufficient data are available to use methods that control for time effects.

Reducing air pollution does not necessarily reduce related adults' mortality burden: Variations in 177 countries with different economic levels

Prolonged exposure to PM2.5 is associated with increased mortality. However, reducing air pollution concentrations does not necessarily reduce the related burden of deaths. Here, we aim to estimate the variations in PM2.5-related mortality due to contributions from key factors – PM2.5 concentration, population exposure, and healthcare levels – for 177 countries from 2000 to 2018 at the 1-km grid scale according to the Global Mortality Exposure Model (GEMM) model. We find that global reductions in PM2.5-related deaths mainly come from high and upper-middle income countries, where lowered air pollutant concentration and better healthcare can offset mortality burdens caused by increasing exposed populations. Changes in population exposure to PM2.5 contribute the most (54 %) to change in global related deaths over the examined period, followed by changes in healthcare (−42 %) and pollution concentrations (4 %). The impacts vary across countries and regions within them due to other drivers, which are significantly influenced by development status. Policies aiming at reducing PM2.5 associated health risks need to account for country-specific balances of these key socioeconomic drivers.

Profiling population-wide exposure to environmental chemicals: A case study of naphthalene

Long-term exposure to environmental chemicals can detrimentally impact human health, and understanding the relationship between age distribution and levels of external and internal exposure is crucial. Nonetheless, existing methods for assessing population-wide exposure across age groups are limited. To bridge this research gap, we introduced a modeling approach designed to assess both chronic external and internal exposure to chemicals at the population level. The external and internal exposure assessments were quantified in terms of the average daily dose (ADD) and steady-state blood concentration of the environmental chemical, respectively, which were categorized by age and gender groups. The modeling process was presented within a spreadsheet framework, affording users the capability to execute population-wide exposure analyses across a spectrum of chemicals. Our simulation outcomes underscored a salient trend: younger age groups, particularly infants and children, exhibited markedly higher ADD values and blood concentrations of environmental chemicals compared to their older counterparts. This observation is due to the elevated basal metabolic rate per unit of body weight characteristic of younger individuals, coupled with their diminished biotransformation kinetics of xenobiotics within their livers. These factors collectively contribute to increased intake rates of environmental chemicals per unit of body weight through air and food consumption, along with heightened bioaccumulation of these chemicals within their bodies (e.g., blood). Furthermore, we augmented the precision of the external and internal exposure assessment by incorporating the age distribution across the population. The simulation outcomes unveiled that, to estimate the central tendency of the population's exposure levels, employing the baseline value group (age group 21–30) or the surrogate age of 25 serves as a simple yet dependable approach. However, for comprehensive population protection, our recommendation aligns with conducting exposure assessments for the younger age groups (age group 0–11). Future studies should integrate individual-level exposure assessment, analyze vulnerable population groups, and refine population structures within our developed model.

Two-Stage Machine Learning-Based Approach to Predict Points of Departure for Human Noncancer and Developmental/Reproductive Effects.

Chemical points of departure (PODs) for critical health effects are crucial for evaluating and managing human health risks and impacts from exposure. However, PODs are unavailable for most chemicals in commerce due to a lack of in vivo toxicity data. We therefore developed a two-stage machine learning (ML) framework to predict human-equivalent PODs for oral exposure to organic chemicals based on chemical structure. Utilizing ML-based predictions for structural/physical/chemical/toxicological properties from OPERA 2.9 as features (Stage 1), ML models using random forest regression were trained with human-equivalent PODs derived from in vivo data sets for general noncancer effects (n = 1,791) and reproductive/developmental effects (n = 2,228), with robust cross-validation for feature selection and estimating generalization errors (Stage 2). These two-stage models accurately predicted PODs for both effect categories with cross-validation-based root-mean-squared errors less than an order of magnitude. We then applied one or both models to 34,046 chemicals expected to be in the environment, revealing several thousand chemicals of moderate concern and several hundred chemicals of high concern for health effects at estimated median population exposure levels. Further application can expand by orders of magnitude the coverage of organic chemicals that can be evaluated for their human health risks and impacts.

Cancer incidence trends in New York State and associations with common population-level exposures 2010–2018: an ecological study

The impact of common environmental exposures in combinations with socioeconomic and lifestyle factors on cancer development, particularly for young adults, remains understudied. Here, we leveraged environmental and cancer incidence data collected in New York State at the county level to examine the association between 31 exposures and 10 common cancers (i.e., lung and bronchus, thyroid, colorectal, kidney and renal pelvis, melanoma, non-Hodgkin lymphoma, and leukemia for both sexes; corpus uteri and female breast cancer; prostate cancer), for three age groups (25–49, 50–69, and 70–84 year-olds). For each cancer, we stratified by age group and sex, and applied regression models to examine the associations with multiple exposures simultaneously. The models included 642,013 incident cancer cases during 2010–2018 and found risk factors consistent with previous reports (e.g., smoking and physical inactivity). Models also found positive associations between ambient air pollutants (ozone and PM2.5) and prostate cancer, female breast cancer, and melanoma of the skin across multiple population strata. Additionally, the models were able to better explain the variation in cancer incidence data among 25–49 year-olds than the two older age groups. These findings support the impact of common environmental exposures on cancer development, particularly for younger age groups.

(Non)targeted Chemical Analysis and Risk Assessment of Organic Contaminants in Darkibor Kale Grown at Rural and Urban Farms.

This study investigated the presence and human hazards associated with pesticides and other anthropogenic chemicals identified in kale grown in urban and rural environments. Pesticides and related compounds (i.e., surfactants and metabolites) in kale samples were evaluated using a nontargeted data acquisition for targeted analysis method which utilized a pesticide mixture containing >1,000 compounds for suspect screening and quantification. We modeled population-level exposures and assessed noncancer hazards to DEET, piperonyl butoxide, prometon, secbumeton, terbumeton, and spinosyn A using nationally representative estimates of kale consumption across life stages in the US. Our findings indicate even sensitive populations (e.g., pregnant women and children) are not likely to experience hazards from these select compounds were they to consume kale from this study. However, a strictly nontargeted chemical analytical approach identified a total of 1,822 features across all samples, and principal component analysis revealed that the kale chemical composition may have been impacted by agricultural growing practices and environmental factors. Confidence level 2 compounds that were ≥5 times more abundant in the urban samples than in rural samples (p < 0.05) included chemicals categorized as "flavoring and nutrients" and "surfactants" in the EPA's Chemicals and Products Database. Using the US-EPA's Cheminformatics Hazard Module, we identified that many of the nontarget compounds have predicted toxicity scores of "very high" for several end points related to human health. These aspects would have been overlooked using traditional targeted analysis methods, although more information is needed to ascertain whether the compounds identified through nontargeted analysis are of environmental or human health concern. As such, our approach enabled the identification of potentially hazardous compounds that, based on their hazard assessment score, merit follow-up investigations.

A scalar-on-quantile-function approach for estimating short-term health effects of environmental exposures.

Environmental epidemiologic studies routinely utilize aggregate health outcomes to estimate effects of short-term (eg, daily) exposures that are available at increasingly fine spatial resolutions. However, areal averages are typically used to derive population-level exposure, which cannot capture the spatial variation and individual heterogeneity in exposures that may occur within the spatial and temporal unit of interest (eg, within a day or ZIP code). We propose a general modeling approach to incorporate within-unit exposure heterogeneity in health analyses via exposure quantile functions. Furthermore, by viewing the exposure quantile function as a functional covariate, our approach provides additional flexibility in characterizing associations at different quantile levels. We apply the proposed approach to an analysis of air pollution and emergency department (ED) visits in Atlanta over 4 years. The analysis utilizes daily ZIP code-level distributions of personal exposures to 4 traffic-related ambient air pollutants simulated from the Stochastic Human Exposure and Dose Simulator. Our analyses find that effects of carbon monoxide on respiratory and cardiovascular disease ED visits are more pronounced with changes in lower quantiles of the population's exposure. Software for implement is provided in the R package nbRegQF.