In the United States, approximately 3% of infants are diagnosed with a major birth defect each year. Whereas prevention efforts have led to decreases in some birth defects, the cause of approximately 70% of birth defects remains unknown. More recently, there has been increasing concern regarding exposures to environmental agents, such as air pollution during pregnancy, and the risk of birth defects. Over the past decade, there has been an increase in research studies examining the association between air pollution and birth defects. The results have been inconsistent, with some studies reporting that higher levels of exposure from the same pollutant increase the risk of birth defects, whereas others report no risk or even a decrease in risk. These inconsistencies may arise from differences in exposure assessment methods across epidemiological studies. A comprehensive series of sensitivity analyses were conducted to evaluate the impact of different exposure estimation decisions on the adjusted measures of associations between ambient air pollution exposure and birth defects. For each of six decisions – spatial scale, spatial limit, temporal scale, temporal limit, data aggregation sequence, and weighting scheme – two alternative choices were considered, and maternal exposure to PM2.5 and benzene were estimated for each ‘sensitivity case' (unique combination of choices across all decisions). For each sensitivity case, adjusted prevalence ratios (aPRs) and 95% confidence intervals (CI) were estimated from multivariable regression models comparing each exposure quartile to the first quartile; each measure of association represented the associations between either benzene or PM2.5 and one of the birth defects under study. To then evaluate the impact of selecting alternative choices for each exposure assessment decision, three metrics were used: 1) the percent difference in the aPR point estimates between alternative choices for a specific decision (calculated for each sensitivity case pairing); 2) the percent of sensitivity cases in which the aPR 95% CIs for alternative choices for a specific decision overlapped (i.e., were not statistically significantly different); and 3) the percent of sensitivity cases in which there was agreement in the substantive conclusion of the association between exposure (pollutant) and outcome (defect), the conclusion being either statistically significant increased risk, statistically significant decreased risk, or no statistically significant difference in risk. Second, a retrospective cohort study was conducted to investigate the association between maternal exposure to ambient benzene and PM2.5 and the risk of musculoskeletal birth defects in offspring. For both analyses, data on singleton infants born from 2000 to 2013 were obtained from the Florida Birth Defects Registry and air pollution data were obtained from the Environmental Protection Agency Air Quality System database. Exposure estimates were calculated for all birth defect cases and non-affected births during etiologically relevant time windows and multivariable regression models were used to obtain aPRs and 99% CIs comparing each quartile of exposure to the first. For PM2.5, across all exposure-outcome pairs under study, the alternative choices for the decision of spatial scale resulted in the largest median percent difference in aPRs (e.g., between county and block group) when results were aggregated for all quartiles. This was followed by the temporal scale and spatial limit decisions. For benzene, spatial limit resulted in largest median percent difference in aPRs, followed by spatial scale and temporal scale. However, for both pollutants, when evaluating the agreement in aPRs between alternative choices on the direction and significance of the association (i.e., statistically significant increase, decrease, or no risk), the decision of spatial limit resulted in the lowest percent agreement (biggest impact). Temporal limit had the second lowest percent agreement for PM2.5, whereas spatial scale had the second lowest for benzene. Finally, the metric assessing the level of overlap in 95% CIs for the measures of association was inconsequential, suggesting little impact of any exposure assessment decision, and doing little to differentiate between the relative impacts of each decision. That is because, for all exposure-outcome pairs, when comparing alternative choices for each decision, there was 100% overlapping intervals (i.e., no aPRs were statistically significantly different from each other). Lastly, exposure assessment decisions impacted the analytic sample sizes, with some decisions resulting in a three-fold difference in the sample size alone. Mothers of singleton infants exposed to higher levels of ambient PM2.5 were more likely than mothers with lower exposure levels to give birth to an infant with isolated anomalies of the skull and face bones, any rib and sternum anomalies, any skull and face anomalies, any spine anomaly, and other congenital anomalies of lower limb including pelvic girdle. Higher PM2.5 exposure was also associated with an increased risk of non-isolated anomalies of skull and face bones, any skull and face anomalies, and reduction deformities of the upper limb. Exposure to higher levels of benzene was associated with an increased risk of isolated congenital hip dislocation and congenital valgus deformities of feet as well as multiple inverse associations. The findings presented here indicate that measures of association between maternal pollutant exposures (PM2.5 and benzene) and selected birth defect outcomes in offspring are sensitive to exposure assessment decisions, with some decisions more impactful than others. The findings can be used, not only to explain the lack of consistency in results across existing epidemiological studies, but to guide decision-making in future studies. This study also adds to the growing body of epidemiological studies suggesting an association between specific air pollutants and birth defects. In the current political climate, it is important that researchers continue to provide evidence of the detrimental health effects of air pollution in order to circumvent change in current policies established to regulate and reduce pollution emissions.

Earlier retrospective noise exposure assessments for use in epidemiological research were not adequately characterized because they did not properly account for use of hearing protection devices (HPD) which would result in potential misclassification. Exposure misclassification has been shown to attenuate exposure-outcomes relations. In the case of already subtle relationships such as noise and cardiovascular diseases, this would potentially annihilate any association. We investigated two approaches using Workers’ Compensation Board (WorkSafe BC) audiometric surveillance data to (i) re-assess the noise exposure in a cohort of lumber mill workers in British Columbia using data on the use of HPD and the determinants of their use available through WorkSafe BC, and (ii) test the validity of the new exposure measures by testing their predictions of noise-induced hearing loss, a well-established association. Work history, noise exposure measurements, and audiometric surveillance data were merged together, forming job-exposure-audiometric information for each of 13,147 lumber mill workers. Correction factors specific to each type and class of HPD were determined based on research and standards. HPD-relevant correction factors were created using 1) deterministic methods and self-reported HPD use after filling gaps in the exposure history, or 2) a model of the determinants of use of HPD, then adjusting noise estimates according to the methods’ predictions and attenuation factors. For both methods, the HPD-adjusted and unadjusted noise exposure estimates were cumulated across all jobs each worker held in a cohort-participating lumber mill. Finally, these noise metrics were compared by examining how well each predicted hearing loss. Analyses controlled for gender, age, race as well as medical and non-occupational risk factors. Both methods led to a strengthening of the noise-hearing loss relationships compared to methods using HPD-unadjusted noise estimates. The method based on the modeling of HPD use had the best performance with a four-fold increase in the slope compared to the unadjusted noise-hearing loss slope. Accounting for HPD use in noise exposure assessment is necessary since we have shown that misclassification attenuated the exposure-response relationships. Exposure-response analyses subsequent to exposure reassessment provide predictive validity and gives confidence in the exposure adjustment methods. / Medicine, Faculty of / Population and Public Health (SPPH), School of / Graduate

This thesis quantified risks of lead (Pb), cadmium (Cd), and mercury (Hg) in the diet of First Nations peoples residing on-reserve in the province of Ontario, Canada. Data was obtained from the 2011-2012 First Nations Food, Nutrition, and Environment Study (FNFNES) and Health Canada to construct total diet studies and probabilistic assessments. Results indicated that the majority of the population is at low risk of exceeding the reference values for these contaminants. Average exposures of Pb and Hg were higher than the general Canadian population (1.7 and 1.6 times greater, respectively), whereas Cd was 59% lower than the Canadian average. The upper percentiles of the population exposure distributions were characterized for contributing food items to assist risk management strategies. For cadmium exposures, smokers had elevated exposures compared to non-smokers. Women of childbearing age had lower dietary MeHg exposures than the total population and were largely below the reference value.

This paper provides a risk assessment of pertinent toxic contaminants in the tailings of the Iron King Mine using a model of aeolian transport fated in human alveolar lung. Here, we studied particulate matter of tailings that are 10 microns (𝜇𝑚) or less in diameter (𝑃𝑀₁₀) because these is most hazardous fraction. We used in-vitro bioaccessibility and in-vivo Microtox® data to determine the relationships between chronic inhalation of these tailings. Our data suggest that arsenic and zinc are the two principle drivers for toxicity of the Iron King Mine’s PM₁₀ tailings and that arsenic will solubilize in human alveolar biofluids at the expense of other noteworthy elemental contaminants in the tailings. The principle contaminant of concern for chronic exposure is arsenic, due to its increased bioaccessibility over time. Our data show that synthetic lung fluid (SLF) mitigates the toxic effects of arsenic, despite its increase in bioaccessibility over time. Therefore, we suggest a buffering mechanism of phosphate competition with arsenate to explain this mitigation of toxicity in SLF. We conclude that public health risk of chronic inhalation of IKM PM₁₀ tailings may be less severe than would otherwise be suggested by high concentrations of toxic contamination in the tailings impoundment.

The repair of automobiles is a critical aspect in vehicle ownership and is potential source of volatile toxic compounds being brought into a home when repairs are conducted in an attached garage. The goal of this study was to assess the impact of the repair of automobiles in an attached garage on the exposure of the home mechanic and degradation of indoor air. Five common automotive tasks were performed in two garages with the garage door either opened 30.5 centimeters (n=5) or closed (n=4). The exposure to the home mechanic, the behavior of contaminants within the garage, and infiltration of contaminants in the home were the determinants of interest. Integrative sampling incorporating charcoal sorbent sampling tubes analyzed by gas chromatography and directs reading photo ionization detectors were used to assess exposure. The tasks with the greatest contributions to the home mechanic’s exposure were found to be brake pad replacement and oil change; these generated 95th percentile concentrations of 51.2 ppm and 12.8 ppm, respectively, with the garage door closed. In contrast, the tasks of refueling and shock replacement had 95th percentile contributions of 0.85 ppm and 2.99 ppm, respectively, in the closed garage. Equations were fitted to the aggregated concentrations during decay to estimate general ventilation (Q/V) in a closed garage. The contaminants within the garage were not found to infiltrate into the home as the average concentrations within the home never exceeded 1 ppm. It was found that automotive repair work in a closed garage may constitute up to 18% of threshold limit value of toluene over a 105 minute exposure at home. Automotive repair inside an attached garage has the potential to make a significant contribution to a mechanic’s daily exposure and should be incorporated into occupational exposure assessments of volatile organic compounds.

The most commonly used exposure assessment for heat stress is based on Wet Bulb Globe Temperature (WBGT), and the limits are based on empirical relationships that demonstrate a sustainable exposure. The ISO 7933 (2017) describes Predicted Heat Strain (PHS), which is a rational model for heat stress assessment that is used to assess time-limited exposures. Investigators have examined PHS validity under a variety of time-limited conditions. The purpose of this paper is to evaluate if PHS can predict sustainable exposures. The data used for this study were from two previous heat stress studies using a progressive heat stress protocol. The studies included 29 participants wearing four different ensembles (woven clothing, particle barrier, water barrier, and vapor barrier coveralls) at three levels of metabolic rate and relative humidity. Each trial provided data for a fully compensable (sustainable) exposure and an uncompensable (time-limited) exposure. The heat stress data from each condition were used to see if PHS demonstrated a steady-state response indicating a sustainable exposure. From the analysis, the sensitivity and specificity respectively for the ensemble types were: 1.00 and 0.18 for woven clothing, 0.95 and 0.60 for particle barrier, 0.91 and 0.83 for water barrier, 0.91 and 0.80 for vapor barrier, and 0.94 and 0.65 for all ensembles. The data show that while the sensitivity of PHS (correctly identifying unsustainable conditions) is good for the different ensembles, PHS specificity (correctly identifying sustainable exposures) was weak. From an occupational health and safety perspective, using PHS to identify sustainable exposures leads to protective decisions.

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Exposure assessment is a critical step in air quality-related epidemiological studies. Accurate estimates of exposure within urban areas are a vital input to models that aim to assess the health effects of air quality among populations of interest. In this study, I have derived and applied a novel approach for capturing the distribution of air quality in Arlington, VA and Washington DC using mobile monitoring. The main objectives of this study are: 1. Deploy a year-long sampling campaign in the Washington DC region to capture the within-city variability of air quality for Particle Number Concentration (PNC), fine particulate matter (PM2.5), and Black Carbon (BC) using mobile monitoring. 2. Derive a method for selecting the best representative mobile monitoring routes to capture within-city spatial patterns of air quality. The end-use of the monitoring campaign described here is as an input for Land Use Regression (LUR) models. 3. Collect unconventional data to characterize the built environment, e.g., videos, sound, etc., that could be employed to improve the LUR models beyond conventional approaches. This study describes the data collection effort that was deployed for a year to characterize annual average concentrations at different locations across the Washington DC region. My thesis describes the challenges experienced and lessons learned during the data collection phase. The goal of this thesis is to describe the data collected and the methods used to sample the DC region. This effort is a component of a larger project that will later use these observations in LUR models. The central site used for measurement of background concentration had a lower concentration median when compared with the median concentration measured on bike. The median PM2.5 concentration at the central site was observed to be 5.2 μg/m3 and the median PNC at the central site was observed to be 6,365 #/cm3. The Arlington PM2.5 concentration was 1 μg/m3 and the Washington DC concentration PM2.5 was 0.3 μg/m3 higher than the background median concentration. Also, the Particle Number Concentration (PNC) was 222 #/cm3 more and the Washington DC PNC was 2,139 #/cm3 higher than the median background concentration. / Many studies have shown that living in polluted air has long-term negative impacts on human health. These negative impacts include premature death, lung disease, heart disease, blood disease, and other complications. Due to these impacts, it is critical to know the level of air pollution within cities to identify areas that have elevated concentrations. The measurement of air quality is challenging because of the low number of monitors available due to cost. Reference grade air quality monitors are often very costly. In this study, I have developed an approach for using a bike to collect mobile measurements of particulate air pollutants in the Washington DC area. I collected one year of data at a fixed site in Arlington and four seasons of data from the bike mobile monitoring campaign. After analyzing the data, I observed that the fixed station showed lower concentration when compared with the data collected by bicycle. I have also suggested improvements in the mobile monitoring method and developed an approach for joining these data with outputs from computer vision models to describe the built environment.