The role of age and sex in non-linear dilution adjustment of spot urine arsenic.

BACKGROUND: Previous research introduced V-PFCRC as an effective spot urinary dilution adjustment method for various metal analytes, including the major environmental toxin arsenic. V-PFCRC normalizes analytes to 1 g/L creatinine (CRN) by adopting more advanced power-functional corrective equations accounting for variation in exposure level. This study expands on previous work by examining the impacts of age and sex on corrective functions. METHODS: Literature review of the effects of sex and age on urinary dilution and the excretion of CRN and arsenic. Data analysis included a Data Set 1 of 5,752 urine samples and a partly overlapping Data Set 2 of 1,154 combined EDTA blood and urine samples. Both sets were classified into age bands, and the means, medians, and interquartile ranges for CRN and TWuAs in uncorrected (UC), conventionally CRN-corrected (CCRC), simple power-functional (S-PFCRC), sex-aggregated (V-PFCRC SA), and sex-differentiated V-PFCRC SD modes were compared. Correlation analyses assessed residual relationships between CRN, TWuAs, and age. V-PFCRC functions were compared across three numerically similar age groups and both sexes. The efficacy of systemic dilution adjustment error compensation was evaluated through power-functional regression analysis of residual CRN and the association between arsenic in blood and all tested urinary result modes. RESULTS: Significant sex differences in UC and blood were neutralized by CCRC and reduced by V-PFCRC. Age showed a positive association with blood arsenic and TWuAs in all result modes, indicating factual increments in exposure. Sex-differentiated V-PFCRC best matched the sex-age kinetics of blood arsenic. V-PFCRC formulas varied by sex and age and appeared to reflect urinary osmolality sex-age-kinetics reported in previous research. V-PFCRC minimized residual biases of CRN on TWuAs across all age groups and sexes, demonstrating improved standardization efficacy compared to UC and CCRC arsenic. INTERPRETATION: Sex differences in UC and CCRC arsenic are primarily attributable to urinary dilution and are effectively compensated by V-PFCRC. While the sex and age influence on V-PFCRC formulas align with sex- and age-specific urinary osmolality and assumed baseline vasopressor activities, their impact on correction validity for entire collectives is minimal. CONCLUSION: The V-PFCRC method offers a robust correction for urinary arsenic dilution, significantly reducing systemic dilution adjustment errors. Its application in various demographic contexts enhances the accuracy of urinary biomarker assessments, benefiting clinical and epidemiological research. V-PFCRC effectively compensates for sex differences in urinary arsenic. Age-related increases in TWuAs are exposure-related and should be additionally accounted for by algebraic normalization, covariate models, or standard range adjustments.

Emulating Near-Roadway Exposure to Traffic-Related Air Pollution via Real-Time Emissions from a Major Freeway Tunnel System.

Epidemiological and toxicological studies continue to demonstrate correlative and causal relationships between exposure to traffic-related air pollution and various metrics of adverse pulmonary, cardiovascular, and neurological health effects. The key challenge for in vivo studies is replicating real-world, near-roadway exposure dynamics in laboratory animal models that mimic true human exposures. The advantage of animal models is the accelerated time scales to show statistically significant physiological and/or behavioral response. This work describes a novel exposure facility adjacent to a major freeway tunnel system that provides a platform for real-time chronic exposure studies. The primary conclusion is that particulate matter (PM) concentrations at this facility are routinely well below the National Ambient Air Quality Standards (NAAQS), but studies completed to date still demonstrate significant neurological and cardiovascular effects. Internal combustion engines produce large numbers of ultrafine particles that contribute negligible mass to the atmosphere relative to NAAQS regulated PM2.5 but have high surface area and mobility in the body. It is posited here that current federal and state air quality standards are thus insufficient to fully protect human health, most notably the developing and aging brain, due to regulatory gaps for ultrafine particles.

Statistical interpretation of environmental influencing parameters on COVID-19 during the lockdown in Delhi, India.

The novel coronavirus disease is known as COVID-19, which is declared as a pandemic by the World Health Organization during March 2020. In this study, the COVID-19 connection with various weather parameters like temperature, wind speed, and relative humidity is investigated and the future scenario of COVID-19 is predicted based on the Gaussian model (GM). This study is conducted in Delhi, the capital city of India, during the lowest mobility rate due to strict lockdown nationwide for about two months from March 15 to May 17, 2020. Spearman correlation is applied to obtain the interconnection of COVID-19 cases with weather parameters. Based on statistical analysis, this has been observed that the temperature parameter shows a significant positive trend during the period of study. The number of confirmed cases of COVID-19 is fitted with respect to the number of days by using the Gaussian curve and it is estimated on the basis of the model that maximum cases will go up to 123,886 in number. The maximum number of cases will be observed during the range of 166 ± 36 days. It is also estimated by using the width of the fitted GM that it will take minimum of 10 months for the complete recovery from COVID-19. Additionally, the linear regression technique is used to find the trend of COVID-19 cases with temperature and it is estimated that with an increase in temperature by 1 °C, 30 new COVID-19 cases on daily basis will be expected to observe. This study is believed to be a preliminary study and to better understand the concrete relationship of coronavirus, at least one complete cycle is essential to investigate. The laboratory-based study is essential to be done to support the present field-based study. Henceforth, based on preliminary studies, significant inputs are put forth to the research community and government to formulate thoughtful strategies like medical facilities such as ventilators, beds, testing centers, quarantine centers, etc., to curb the effects of COVID-19.

Do individuals with asthma experience airway hyper-responsiveness after exposure to nitrogen dioxide?

The current 100 ppb short-term National Ambient Air Quality Standard for NO2, and EPA's determination of a causal association for respiratory effects, are based in part on controlled human exposure studies evaluating airway hyper-responsiveness (AHR). A meta-analysis by Goodman et al. (2009) found increased AHR at 100 ppb NO2 but no clear concentration-response relationship up to 600 ppb, and an overall lack of an AHR effect for studies involving exercise or exposure to allergens. Several factors have been suggested to explain why effects on AHR are observed while people are at rest, but not during exercise or after exposure to allergens. These include an exercise-induced refractory period; partial reversal of bronchospasm from use of forced expiration maneuvers; and greater airway responsiveness of participants exposed to NO2 at rest. We reviewed the scientific evidence to determine whether there is biological support for these factors and found that none sufficiently explained the lack of an effect during exercise or after exposure to allergens. In the absence of either a consistent concentration-response or a plausible explanation for the paradoxical AHR findings, the biological significance of these findings is uncertain and provides equivocal support for NO2 as a causal factor of AHR at these exposure levels.

Are the elements of the proposed ozone National Ambient Air Quality Standards informed by the best available science?

The United States Environmental Protection Agency (US EPA) issues National Ambient Air Quality Standards (NAAQS) for six criteria pollutants, including ozone. Each standard has four elements: an indicator, level, averaging time, and form. Ozone levels (i.e., air concentrations) alone in scientific studies are not directly comparable to the "level" element of the NAAQS because the standard considers the level in the context of its relation to the remaining elements. Failure to appreciate this has led to misunderstandings regarding NAAQS that would be health-protective. This can be seen with controlled human ozone exposure studies, which often involved small numbers of people exercising quasi-continuously for a long duration at an intensity not common in the general population (and unlikely achievable by most sensitive individuals), under worst-case exposure profiles. In addition, epidemiology studies have used different averaging times and have had methodological limitations that may have biased results. Such considerations can make it difficult to compare ozone levels and results across studies and to appropriately apply them in a NAAQS evaluation. Relating patterns and circumstances of exposure, and exposure measurements, to all elements of the NAAQS can be challenging, but if US EPA fully undertook this, it would be evident that available evidence does not indicate that proposed lower ozone standards would be more health protective than the current one.

Do group responses mask the effects of air pollutants on potentially sensitive individuals in controlled human exposure studies?

To establish primary National Ambient Air Quality Standards (NAAQS) for criteria air pollutants such as nitrogen dioxide (NO2), ozone (O3), and sulfur dioxide (SO2), US EPA relies in part on controlled human exposure studies. It has been suggested that evaluating average responses for all participants in these studies may not reflect the responses of sensitive participants in these studies. To evaluate this, we identified controlled exposure studies with multiple exposure concentrations or durations that provided individual-level lung function data. Based on individual lung function responses at specific exposure concentrations and the slope of individual concentration-response curves, we identified 12 participants out of a total of 208 participants in 12 studies who were potentially sensitive to O3, SO2, or sulfuric acid (H2SO4). We did not identify any participants sensitive to NO2. All of these participants were found to be potentially sensitive only at concentrations that were well above the NAAQS (SO2), above likely ambient concentrations (H2SO4), or at concentrations at which the study reported significant lung function effects for all participants (O3). Based on our analysis, average responses for all participants combined adequately reflect lung function responses for potentially sensitive study participants at concentrations in the range of the current NAAQS.

Biomarkers after Controlled Inhalation Exposure to Exhaust from Hydrogenated Vegetable Oil (HVO).

Hydrogenated vegetable oil (HVO) is a renewable diesel fuel used to replace petroleum diesel. The organic compounds in HVO are poorly characterized; therefore, toxicological properties could be different from petroleum diesel exhaust. The aim of this study was to evaluate the exposure and effective biomarkers in 18 individuals after short-term (3 h) exposure to HVO exhaust and petroleum diesel exhaust fumes. Liquid chromatography tandem mass spectrometry was used to analyze urinary biomarkers. A proximity extension assay was used for the measurement of inflammatory proteins in plasma samples. Short-term (3 h) exposure to HVO exhaust (PM1 ~1 µg/m3 and ~90 µg/m3 for vehicles with and without exhaust aftertreatment systems, respectively) did not increase any exposure biomarker, whereas petroleum diesel exhaust (PM1 ~300 µg/m3) increased urinary 4-MHA, a biomarker for p-xylene. HVO exhaust from the vehicle without exhaust aftertreatment system increased urinary 4-HNE-MA, a biomarker for lipid peroxidation, from 64 ng/mL urine (before exposure) to 141 ng/mL (24 h after exposure, p < 0.001). There was no differential expression of plasma inflammatory proteins between the HVO exhaust and control exposure group. In conclusion, short-term exposure to low concentrations of HVO exhaust did not increase urinary exposure biomarkers, but caused a slight increase in lipid peroxidation associated with the particle fraction.

Lung physiology and controlled exposure study design.

Controlled human inhalation exposure ( CHIE) studies provide a unique opportunity to conduct formal experiments to examine the human health effects of airborne pollutants. Lung function, easily measured using spirometry, is a common physiological variable often utilized in these studies. By design, CHIE studies only induce mild and reversible acute effects, which may or may not predict adverse effects that may develop under chronic exposure conditions. There is substantial inter- and intra-individual variability in functional capacity and symptoms such as chest tightness and dyspnea, which are complex variables that are affected by individual perception, physiological lung impairment, and other variables (e.g., concomitant health conditions, and level of conditioning/fitness). Thus, the design of the CHIE study and physiological and environmental factors of study participants can affect each CHIE study's results. Researchers can address many of these critical issues in the problem formulation phase of CHIE studies, utilizing existing information on the expected effects of the substance of interest and possible modes of action. Thoughtful design and interpretation of CHIE studies will increase their utility for evaluating and setting environmental health policy.

Risk assessment for irritating chemicals - Derivation of extrapolation factors.

Irritation of the eyes and the upper respiratory tract are important endpoints for setting guide values for chemicals. To optimize the use of the often-limited data, we analysed controlled human exposure studies (CHS) with 1-4 h inhalation of the test substance, repeated dose inhalation studies in rodents, and Alarie-Tests and derived extrapolation factors (EF) for exposure duration, inter- and intraspecies differences. For the endpoint irritating effects in the respiratory tract in rodents, geometric mean (GM) values of 1.9 were obtained for the EF for subacute→subchronic (n = 16), 2.1 for subchronic→chronic (n = 40), and 2.9 for subacute→chronic (n = 10) extrapolation. Based on these data we suggest an EF of 2 for subchronic→chronic and of 4 for subacute→chronic extrapolation. In CHS, exposure concentration determines the effects rather than exposure duration. Slight reversible effects during 4 h exposure indicate that an EF of 1 can be considered for assessing chronic exposures. To assess species extrapolation, 10 chemicals were identified with both, reliable rat inhalation studies and CHS. The GM of the ratio between the No Observed Adverse Effect Concentration (NOAEC) in rats and humans was 2.3 and increased to 3.6 when expanding the dataset to all available EF (n = 25). Based on these analyses, an EF of 3 is suggested to extrapolate from a NOAEC in a chronic rat study to a NOAEC in a CHS. The analysis of EFs for the extrapolation from a 50% decrease in respiratory frequency in the Alarie test in mice (RD50) to a NOAEC in a CHS resulted in a GM of 40, for both, the reliable (n = 11) and the overall dataset (n = 19). We propose to use the RD50 from the Alarie test for setting guide values and to use 40 as EF. Efs for intraspecies differences in the human population must account for susceptible persons, most importantly for persons with chemical intolerance (CI), who show subjective signs of irritation at low concentrations. The limited data available do not justify to deviate from an EF of 10 - 20 as currently used in different regulatory settings.

Air pollution and resistance to inhaled glucocorticoids: Evidence, mechanisms and gaps to fill.

Substantial evidence indicates that cigarette smoke exposure induces resistance to glucocorticoids, the primary maintenance medication in asthma treatment. Modest evidence also suggests that air pollution may reduce the effectiveness of these critical medications. Cigarette smoke, which has clear parallels with air pollution, has been shown to induce glucocorticoid resistance in asthma and it has been speculated that air pollution may have similar effects. However, the literature on an association of air pollution with glucocorticoid resistance is modest to date. In this review, we detail the evidence for, and against, the effects of air pollution on glucocorticoid effectiveness, focusing on results from epidemiology and controlled human exposure studies. Epidemiological studies indicate a correlation between increased air pollution exposure and worse asthma symptoms. But these studies also show a mix of beneficial and harmful effects of glucocorticoids on spirometry and asthma symptoms, perhaps due to confounding influences, or the induction of glucocorticoid resistance. We describe mechanisms that may contribute to reductions in glucocorticoid responsiveness following air pollution exposure, including changes to phosphorylation or oxidation of the glucocorticoid receptor, repression by cytokines, or inflammatory pathways, and epigenetic effects. Possible interactions between air pollution and respiratory infections are also briefly discussed. Finally, we detail a number of therapies that may boost glucocorticoid effectiveness or reverse resistance in the presence of air pollution, and comment on the beneficial effects of engineering controls, such as air filtration and asthma action plans. We also call attention to the benefits of improved clean air policy on asthma. This review highlights numerous gaps in our knowledge of the interactions between air pollution and glucocorticoids to encourage further research in this area with a view to reducing the harm caused to those with airways disease.

Air pollution and DNA methylation: effects of exposure in humans.

Air pollution exposure is estimated to contribute to approximately seven million early deaths every year worldwide and more than 3% of disability-adjusted life years lost. Air pollution has numerous harmful effects on health and contributes to the development and morbidity of cardiovascular disease, metabolic disorders, and a number of lung pathologies, including asthma and chronic obstructive pulmonary disease (COPD). Emerging data indicate that air pollution exposure modulates the epigenetic mark, DNA methylation (DNAm), and that these changes might in turn influence inflammation, disease development, and exacerbation risk. Several traffic-related air pollution (TRAP) components, including particulate matter (PM), black carbon (BC), ozone (O3), nitrogen oxides (NOx), and polyaromatic hydrocarbons (PAHs), have been associated with changes in DNAm; typically lowering DNAm after exposure. Effects of air pollution on DNAm have been observed across the human lifespan, but it is not yet clear whether early life developmental sensitivity or the accumulation of exposures have the most significant effects on health. Air pollution exposure-associated DNAm patterns are often correlated with long-term negative respiratory health outcomes, including the development of lung diseases, a focus in this review. Recently, interventions such as exercise and B vitamins have been proposed to reduce the impact of air pollution on DNAm and health. Ultimately, improved knowledge of how exposure-induced change in DNAm impacts health, both acutely and chronically, may enable preventative and remedial strategies to reduce morbidity in polluted environments.

Excretion of Urinary Metabolites of the Phthalate Esters DEP and DEHP in 16 Volunteers after Inhalation and Dermal Exposure.

Phthalate esters are suspected endocrine disruptors that are found in a wide range of applications. The aim of this study was to determine the excretion of urinary metabolites in 16 individuals after inhalation and/or dermal exposure to 100⁻300 µg/m³ of deuterium-labelled diethyl phthalate (D4-DEP) and bis(2-ethylhexyl) phthalate (D4-DEHP). Dermal exposure in this study represents a case with clean clothing acting as a barrier. After inhalation, D4-DEP and D4-DEHP metabolites were excreted rapidly, though inter-individual variation was high. D4-DEP excretion peaked 3.3 h (T½ of 2.1 h) after combined inhalation and dermal exposure, with total excreted metabolite levels ranging from 0.055 to 2.351 nmol/nmol/m³ (nmol of urinary metabolites per phthalates air concentration in (nmol/m³)). After dermal exposure to D4-DEP, metabolite excretion peaked 4.6 h (T½ of 2.7 h) after exposure, with excreted metabolite levels in between 0.017 and 0.223 nmol/nmol/m³. After combined inhalation and dermal exposure to D4-DEHP, the excretion of all five analysed metabolites peaked after 4.7 h on average (T½ of 4.8 h), and metabolite levels ranged from 0.072 to 1.105 nmol/nmol/m³ between participants. No dermal uptake of particle phase D4-DEHP was observed. In conclusion, the average excreted levels of metabolites after combined inhalation and dermal exposure to D4-DEP was three times higher than after combined exposure to D4-DEHP; and nine times higher than after dermal exposure of D4-DEP. This study was made possible due to the use of novel approaches, i.e., the use of labelled phthalate esters to avoid the background concentration, and innovative technique of phthalate generation, both in the particle and the gas phase.

Modeling spatial distribution of population for environmental epidemiological studies: Comparing the exposure estimates using choropleth versus dasymetric mapping.

Precise population information is critical for identifying more accurate environmental exposures for air pollution impacts analysis. Basically, there are two methods for estimating spatial distribution of population, choropleth and dasymetric mapping. While the choropleth approach accounts for linear distribution of population over area based on census tract units, the dasymetric model accounts for a more heterogeneous population density by quantifying the association between the area-class map data categories and values of the statistical surface as encoded in the census dataset. Environmental epidemiological studies have indicated the dasymetric mapping as a more accurate approach to estimate and characterize population densities in large urban areas. However, investigations that have attempted to compare the exposure estimates from choropleth versus dasymetric mapping in environmental health analysis are still missing. This paper addresses this gap and compares the impact of using choropleth and dasymetric mapping in different exposure metrics. We compare the impact of using choropleth and dasymetric mapping in three case studies, defined here as case study A (relationship between urban structure types and health), case study B (PM2.5 emissions and human exposure), and case study C (distance-decays of mortality risk related to PM2.5 emitted by traffic along major highways). These case studies represent previous investigations performed by our research group where spatial distribution of population was an essential input for analysis. Our findings indicate that the method used to estimate spatial distribution of population impacts significantly the exposure estimates. We observed that the choropleth mapping overestimated exposure for the case study A and B, while for the case study C the exposure was underestimated by the choropleth approach. Our findings show that the dasymetric model is a preferred method for creating spatially-explicit information about population distribution for health exposure studies. The results presented here can be useful for the environmental health community to more accurately assess the relationship between environmental factors and health risks.

A method for quantification of volatile organic compounds in blood by SPME-GC-MS/MS with broader application: From non-occupational exposure population to exposure studies.

Humans are continuously exposed to volatile organic compounds (VOCs) as these chemicals are ubiquitously present in most indoor and outdoor environments. In order to assess recent exposure to VOCs for population-based studies, VOCs are measured in the blood of participants. This work describes an improved method to detect 12 VOCs by head-space solid-phase microextraction gas chromatography coupled with isotope-dilution mass spectrometry in selected reaction monitoring mode (SPME-GC-MS/MS). This method was applied to the analysis of trihalomethanes, styrene, trichloroethylene, tetrachloroethylene and BTEX (benzene, toluene, ethylbenzene, m-xylene, p-xylene, o-xylene) in a population-based biomonitoring study (Canadian Health Measures Survey). The method showed good linearity (>0.990) in the range of 0.010-10µg/L and detection limits between 0.007 and 0.027µg/L, precision better than 25% and good accuracy (±25%) based on proficiency testing materials. Quality Control data among runs over a 7 month period showed %RSD between 14 and 25% at low levels (∼0.03µg/L) and between 9 and 23% at high levels (∼0.4µg/L). The method was modified to analyze samples from a pharmacokinetic study in which 5 healthy volunteers were exposed to single, binary and quaternary mixtures of CTEX (chloroform, ethylbenzene, toluene and m-xylene), thus the expected concentration in blood was 1 order of magnitude higher than those found in the general population. The method was modified by reducing the sample size (from 3g to 0.5g) and increasing the upper limit of the concentration range to 395µg/L. Good linearity was found in the range of 0.13-395µg/L for toluene and ethylbenzene and 0.20-609µg/L for m/p-xylene. Quality control data among runs over the period of the study (n=13) were found to vary between 7 and 25%.