Mountain Scholar :: Browsing by Author "Magzamen, Sheryl, committee member"

Browsing by Author "Magzamen, Sheryl, committee member"

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Open Access
Assessing community-wide health impacts of natural disasters: studies of a severe flood in Beijing and tropical cyclones in the United States
(Colorado State University. Libraries, 2018) Yan, Meilin, author; Anderson, G. Brooke, advisor; Peel, Jennifer L., advisor; Magzamen, Sheryl, committee member; Wilson, Ander, committee member
Death and injury tolls occurring during natural disasters have traditionally been estimated using a disaster surveillance approach, where each death or injury is considered case-by-case to determine if it can be attributed to the disaster. This approach may not always capture the overall community-wide health effects associated with disaster exposure, especially in cases where much of the excess morbidity and mortality result from outcomes common outside of disaster periods (e.g., heart attacks, respiratory problems) rather than well-characterized disaster-related risks that are rarer outside of storm events (e.g., drowning, carbon monoxide poisoning, trauma). The goal of this dissertation is to examine the community-wide impacts of natural disasters on some common health outcomes. To achieve this goal, we assessed the community-wide health risks from exposure to two types of climate-related natural disasters, a severe flood and tropical cyclones, as compared with matched unexposed days in the same community. Our results can provide new evidence on how natural disasters affect human health, contributing to and complementing the large base of existing literature generated using a disaster surveillance approach. Mortality risk of a severe flood. On July 21–22, 2012, Beijing, China, suffered its heaviest rainfall in 60 years, which caused heavy flooding throughout Beijing. We conducted a matched analysis comparing mortality rates on the peak flood day and the four following days to similar unexposed days in previous years (2008–2011), controlling for potential confounders, to estimate the relative risks (RRs) of daily mortality among Beijing residents associated with this flood. Compared to the matched unexposed days, mortality rates were substantially higher during the flood period for all-cause, circulatory, and accidental mortality, with the highest risks observed on the peak flood day. No evidence of increased risk of respiratory mortality was observed in this study. We estimated a total of 79 excess deaths among Beijing residents on July 21–22, 2012; by contrast, only 34 deaths were reported among Beijing residents in a study estimating the flood's fatality toll using a traditional surveillance approach. Results were robust to study design and modeling choices. Our results indicate considerable impacts of this flood on public health, and that much of this impact may come from increased risk of non-accidental deaths. To our knowledge, this is the first study analyzing the community-wide changes in mortality rates during the 2012 flood in Beijing, and one of the first to do so for any major flood worldwide. This study offers critical evidence in assessing flood-related health impacts, as urban flooding is expected to become more frequent and severe in China. Health risk of tropical cyclones. To measure storm exposure, we separately considered five metrics—distance to storm track; cumulative rainfall; maximum sustained wind speed; flooding; and tornadoes. For mortality outcomes, we used community vital records for 78 large eastern United States (U.S.) communities, 1988–2005, to estimate the risks of storm exposure on four mortality outcomes. For emergency hospitalization outcomes, we used Medicare claims for 180 eastern US counties, 1999–2010, to estimate storm-related risks on emergency hospitalizations from cardiovascular and respiratory disease among Medicare beneficiaries. We compared the health outcome rates across the study population (all community residents for the mortality analysis; community Medicare beneficiaries for the hospitalization analysis) on storm-exposed days versus similar unexposed days within each community. For each combination of exposure metric and health outcome, we estimated storm-associated health risks for a window from two days before to seven days after the day of storm's closest approach. For the mortality analysis, 92 Atlantic Basin tropical cyclones were considered based on U.S. landfall or close approach, with 70 communities exposed to at least one storm; for the hospitalization analysis, 74 storms were considered for 175 exposed counties. Under the wind-based exposure metric, we found substantially elevated risk for all mortality outcomes considered compared with matched unexposed days, with risk typically highest on the day of the storm's closest approach. When excluding the ten most severe storm events based on wind exposures, however, we did not observe significantly increased risk for the remaining storm exposures on any mortality outcomes. Among Medicare beneficiaries, the cumulative risks of respiratory hospitalizations were increased under all storm exposure metrics considered, for all storm exposures and across all exposed counties; these risks remained significantly elevated even when the ten most severe storm exposures (based on wind exposure) were excluded. Our findings on community-wide health risks from tropical cyclones add important insights to results from disaster surveillance: first, the impacts of tropical cyclones on non-accidental mortality can, in some cases, be much greater than identified in case-by-case surveillance studies; second, there is strong evidence that risks of Medicare emergency hospital admissions due to non-injury morbidity are elevated during the storm exposure period; and third, intense wind exposure can characterize many of the tropical cyclone exposures with particularly high risk on non-accidental mortality, as well as respiratory hospitalizations in the elderly.
Embargo
Assessment and intervention strategies for agricultural inhalation exposures in occupational and community environments
(Colorado State University. Libraries, 2024) Erlandson, Grant, author; Schaeffer, Joshua, advisor; Magzamen, Sheryl, committee member; Abdo, Zaid, committee member; Martenies, Sheena, committee member
Agriculture represents an industry vital to the U.S. economy, supplying the public with nutritious food and providing millions of workers with employment. Also characterized as one of the most hazardous industries for workers, agricultural environments contain a variety of inhalation hazards capable of impacting the health of workers and adjacent community residents. Agricultural inhalation hazards include airborne organic and inorganic dusts; livestock associated gases, pesticides, bacteria, viruses, and antibiotics. This study will focus on (1) bioaerosol exposures in dairy operations and (2) inorganic dust pesticide exposures from agricultural applications. In dairy environments, workers are regularly exposed to high levels of organic dust (bioaerosols) and their inflammatory constituents (e.g., endotoxin, muramic acid, and β-glucans). Dairy bioaerosol exposure is associated with increased prevalence of respiratory disease (e.g., asthma, rhinitis, and chronic obstructive pulmonary disease) in dairy workers. While bioaerosol exposure in dairy environments has been well characterized in previous research, efforts to identify hygienic interventions that control exposure remain unsuccessful. In crop production agriculture, it is well documented that workers are exposed to high levels of pesticides associated with adverse health outcomes (e.g., respiratory and neurologic diseases). Further, in agricultural adjacent community environments, where lower chronic pesticide exposures are found, there is mounting evidence linking adverse health effects (e.g., adult and iii childhood cancers, neurologic and respiratory diseases, and birth outcomes) in residents to exposure from agricultural pesticide applications. However, weak and sometimes inconsistent associations previously reported highlight the limitations of current community exposure assessment techniques used for pesticides. For specific Aim 1, we pilot tested a novel low-cost nasal rinse intervention to modulate airway inflammation in ten bioaerosol exposed dairy workers. Dairy workers were randomly split into treatment (n = 5) and control (n = 5) groups and administered saline nasal rinses before and after their shift for five consecutive days. Treatment group participants received pre-shift hypertonic saline rinses while the control group received normotonic saline rinses. Both received normotonic rinses post-shift. Pro and anti-inflammatory cytokines were measured from recovered saline rinses. Linear mixed model results indicated treatment group participants experienced significantly higher concentrations of anti- (IL-10) and pro-inflammatory cytokines (IL-6 and IL-8) than the control group (p < 0.02, p <0.04, and p < 0.01 respectively). This study demonstrates the capacity of hypertonic saline nasal rinses to successfully upregulate anti-inflammatory cytokine production. However, conflicting upregulation of pro-inflammatory markers cloud interpretations of efficacy. For Aim 2, we further evaluated the immunomodulatory effects of hypertonic saline rinses vs. normotonic saline rinses longitudinally (2-5 shifts) in 45 bioaerosol exposed dairy workers. However, in this aim, treatment group participants received hypertonic rinses pre- and post-shift and 16S sequencing was added to analyses to capture potential washout effects on microbial diversity. No significant differences were observed between group or day for any of the measured markers or microbiome diversity metrics. Yet, non-significant increases in anti-inflammatory IL-10 concentrations across the study period were observed independent of iv treatment group suggesting the rinse itself may be more impactful than tonicity. This study provided mixed but encouraging results that justify further research on nasal rinses as an intervention in bioaerosol exposed dairy workers. For Aim 3, we evaluated the agreement between three exposure assessment techniques used to estimate residential organophosphate (OP) exposure in agricultural adjacent communities located in the Central Valley of California. OP exposure was estimated from household dust samples, California Pesticide Use Report (CPUR) pesticide use modeling, and urinary DAP metabolites across two sampling campaigns. Simple correlation tests revealed moderate correlations (ρs = 0.46) between household dust and use model exposure estimates. Estimates from urinary DAP metabolites exhibited low to no correlation with the other two estimates. Linear mixed model results also indicated no association between urinary DAP metabolites and household dust or use model estimates. This study illustrates a lack of agreement between community pesticide exposure assessment techniques regularly used in research and motivates the development of more robust assessment techniques.
Open Access
ATV mortality in the United States, 2011-2013
(Colorado State University. Libraries, 2015) Lagerstrom, Elise, author; Gilkey, David, advisor; Rosecrance, John, advisor; Magzamen, Sheryl, committee member; Stallones, Lorann, committee member
The purpose of this study is to examine contributing factors of ATV injuries and deaths through application of the Agent-Host-Environment epidemiological model. By analyzing the associations between contributing factors and classifying these factors based on the model, appropriate intervention strategies may be identified. All US incident reports of ATV fatalities and injuries between 2011 and 2013 were obtained from the Consumer Product Safety Commission (CPSC). Each report was read and coded based on information available in the narrative incident report. Each coded variable was classified as relating to a section of the epidemiologic triangle: agent, host, or environment. Descriptive statistics were obtained for the coded variables and Chi-Square Automatic Interaction Detector (CHAID) analysis was performed in order to identify associations between predictor variables. A total of 1,230 incident reports were obtained and, after data cleansing, a total 1,193 fatality reports remained. While only 12% of cases occurred on farms, the calculated incidence rate in the farming population (.62 per 100,000 population/year) is higher than the overall incident rate in the United States (.13 per 100,000 population/year). Descriptive statistics showed low helmet use (11.85% of fatal cases) and high use of alcohol and drugs (84.2% of fatal cases). The CHAID results showed significant associations between all types of variables: agent, host, and environment. The present study provides nationwide statistics on ATV fatalities, approaching risk factor analysis with regard to the agent-host-environment epidemiological model. The three aspects of the epidemiologic triangle each contribute, and build upon each other, to create the combination of risk factors that lead to a fatal event. By modeling and categorizing risk it is possible to develop targeted solutions to the root cause of the hazard. Through use of legislation and training, many host-related risk factors can be controlled, use of engineering controls can mitigate risk due to the agent and/or physical environment, and use of targeted marketing strategies and education may be able to limit risk due to the social environment.
Open Access
Autonomous low-cost ozone sensors: development, calibration, and application to study exposure and spatial gradients
(Colorado State University. Libraries, 2022) Giardina, Dylan M., author; Jathar, Shantanu, advisor; Magzamen, Sheryl, committee member; Volckens, John, committee member; Bechara, Samuel, committee member
Ozone (O3), a criteria pollutant and atmospheric oxidant, is not routinely measured in rural and remote environments and hence exposure to ozone pollution in these regions remains poorly understood. In this work, we built, calibrated, and deployed five low-cost, autonomous ozone sensor systems (called MOOS) in Northern Colorado, a region that is non-compliant for O3 during the summertime. Each MOOS included the following components: (i) an Aeroqual SM50, a heated metal oxide ozone sensor, mounted inside a custom radiation shield, (ii) a power system that consisted of a 30 W solar panel, 108 Wh lithium-ion battery, and charge controller, (iii) a Particle Boron to acquire, process, and transmit data to the Cloud, and (iv) an environmental sensor to measure temperature, relative humidity, and pressure. In a three-week long collocated study, we found that all MOOS, calibrated using 48 hours of reference data, compared well against reference monitors with a measurement error between 4-6 parts per billion by volume (ppbv). Manufacturer- and laboratory-based calibrations over- and under-estimated ozone levels at higher and lower ozone mixing ratios, respectively. When deployed in Northern Colorado for an additional three weeks to measure O3 exposure and study O3 trends across an urban-rural gradient, we found that the MOOS, calibrated using data from the collocated study and calibrated using 48 hours of reference data in the field, demonstrated good sensor performance (RMSE of 3.98 - 8.80 ppbv and MBE of 0.22 - 3.82 ppbv). Compared to the collocated study, the field study resulted in larger measurement errors for all five MOOS (RMSE of 3.66 - 4.00 versus RMSE of 3.98 - 8.80). Furthermore, there was modest variability in the field performance across the different MOOS (RMSE < 5 ppbv) that could not be explained by environmental differences between the different sites (e.g., proximity of the MOOS to the reference monitor, land use type, temperature). We found that MOOS were able to capture 100% of non-compliant O3 days during the collocated study and between 25-87% of non-compliant O3 days during the field study depending on the calibration approach used. Furthermore, both reference monitors and MOOS deployed along the east-west corridor in Northern Colorado were able to capture the negative, west-east O3 gradients observed in previous aircraft and modeling studies. Overall, our study indicates that the MOOS shows promise as a low-cost O3 sensor that could be used to supplement routine ambient monitoring and characterize regional ozone pollution.
Open Access
Bayesian methods for environmental exposures: mixtures and missing data
(Colorado State University. Libraries, 2022) Hoskovec, Lauren, author; Wilson, Ander, advisor; Magzamen, Sheryl, committee member; Hoeting, Jennifer, committee member; Cooley, Dan, committee member
Air pollution exposure has been linked to increased morbidity and mortality. Estimating the association between air pollution exposure and health outcomes is complicated by simultaneous exposure to multiple pollutants, referred to as a multipollutant mixture. In a multipollutant mixture, exposures may have both independent and interactive effects on health. In addition, observational studies of air pollution exposure often involve missing data. In this dissertation, we address challenges related to model choice and missing data when studying exposure to a mixture of environmental pollutants. First, we conduct a formal simulation study of recently developed methods for estimating the association between a health outcome and exposure to a multipollutant mixture. We evaluate methods on their performance in estimating the exposure-response function, identifying mixture components associated with the outcome, and identifying interaction effects. Other studies have reviewed the literature or compared performance on a single data set; however, none have formally compared such a broad range of new methods in a simulation study. Second, we propose a statistical method to analyze multiple asynchronous multivariate time series with missing data for use in personal exposure assessments. We develop an infinite hidden Markov model for multiple time series to impute missing data and identify shared time-activity patterns in exposures. We estimate hidden states that represent latent environments presenting a unique distribution of a mixture of environmental exposures. Through our multiple imputation algorithm, we impute missing exposure data conditional on the hidden states. Finally, we conduct an individual-level study of the association between long-term exposure to air pollution and COVID-19 severity in a Denver, Colorado, USA cohort. We develop a Bayesian multinomial logistic regression model for data with partially missing categorical outcomes. Our model uses Polya-gamma data augmentation, and we propose a visualization approach for inference on the odds ratio. We conduct one of the first individual-level studies of air pollution exposure and COVID-19 health outcomes using detailed clinical data and individual-level air pollution exposure data.
Open Access
Blending model output with satellite-based and in-situ observations to produce high-resolution estimates of population exposure to wildfire smoke
(Colorado State University. Libraries, 2016) Lassman, William, author; Pierce, Jeffrey, advisor; Fischer, Emily, committee member; Schumacher, Russ, committee member; Magzamen, Sheryl, committee member; Pfister, Gabriele, committee member
In the western US, emissions from wildfires and prescribed fire have been associated with degradation of regional air quality. Whereas atmospheric aerosol particles with aerodynamic diameters less than 2.5 μm (PM 2.5 ) have known impacts on human health, there is uncertainty in how particle composition, concentrations, and exposure duration impact the associated health response. Due to changes in climate and land-management, wildfires have increased in frequency and severity, and this trend is expected to continue. Consequently, wildfires are expected to become an increasingly important source of PM 2.5 in the western US. While composition and source of the aerosol is thought to be an important factor in the resulting human health-effects, this is currently not well-understood; therefore, there is a need to develop a quantitative understanding of wildfire-smoke-specific health effects. A necessary step in this process is to determine who was exposed to wildfire smoke, the concentration of the smoke during exposure, and the duration of the exposure. Three different tools are commonly used to assess exposure to wildfire smoke: in-situ measurements, satellite-based observations, and chemical-transport model (CTM) simulations, and each of these exposure-estimation tools have associated strengths and weakness. In this thesis, we investigate the utility of blending these tools together to produce highly accurate estimates of smoke exposure during the 2012 fire season in Washington for use in an epidemiological case study. For blending, we use a ridge regression model, as well as a geographically weighted ridge regression model. We evaluate the performance of the three individual exposure-estimate techniques and the two blended techniques using Leave-One-Out Cross-Validation. Due to the number of in-situ monitors present during this time period, we find that predictions based on in-situ monitors were more accurate for this particular fire season than the CTM simulations and satellite-based observations, so blending provided only marginal improvements above the in-situ observations. However, we show that in hypothetical cases with fewer surface monitors, the two blending techniques can produce substantial improvement over any of the individual tools.
Open Access
Characterizing mold VOCs in residential structures impacted by flood
(Colorado State University. Libraries, 2024) Murphy, Molly, author; Schaeffer, Joshua, advisor; Magzamen, Sheryl, committee member; Carter, Ellison, committee member
Mold growth is a health concern for people re-entering their homes after a flooding event. Mold exposure can be hazardous, especially for people with asthma. Mold produces volatile organic compounds (VOCs) as it grows, and those VOCs can be used to detect the presence of mold. While VOC profiles of mold have been constructed in laboratory settings, there has been little work with samples directly from the field. VOC samples were taken from the homes of 55 Houston residents. 33 homes had been flooded, and 22 had not. The VOCs were analyzed using GCMS and identified using a NIST library of mass spectra. The VOCs found in flooded homes were compared to VOCs found in unflooded homes. There was a difference in VOCs identified, and the concentration of those VOCs, in flooded versus non-flooded homes, and some of those VOCs have been previously associated with mold growth. However, the origin of those VOCs is still not clear. Further work should include associating the VOCs found with the maximum water levels in the flooded homes, and with health data collected from the participants.
Open Access
Comparison of indoor air quality between building type in campus buildings
(Colorado State University. Libraries, 2018) Erlandson, Grant, author; Schaeffer, Joshua, advisor; Carter, Ellison, committee member; Magzamen, Sheryl, committee member; Reynolds, Stephen, committee member
The average American spends an estimated 90% of their time indoors on any given day. Rapid urbanization is also sweeping the country leading to ever increasing time spent in the built environment. Human exposure to the surrounding environment accounts for 90% of all disease. The air we breathe represents a major component of that exposure and becomes increasingly relevant as more time is spent indoors. Many studies have set out to characterize and improve indoor air quality in various settings from the workplace to schools. However, few have investigated higher education and its shift toward green, sustainable buildings. The objective of this research was to evaluate the effects of building type and occupancy on indoor air quality in higher education buildings. We measured LEED certified, retrofitted, and conventional building types on a college campus for particulate matter, formaldehyde, carbon dioxide, and nitrogen oxides. For each building type, we conducted multi-zonal, 48 hour measurements during times when the buildings were occupied and unoccupied. Statistically significant differences in two size fractions of particulate matter were observed between building types. Carbon dioxide and particulate matter concentrations were significantly higher during occupied sampling when compared to unoccupied. Results from this study suggest that occupancy status has a larger impact on indoor air quality in campus buildings than building type.
Open Access
Development of a combustion system for fecal materials
(Colorado State University. Libraries, 2017) Flagge, Maxwell, author; Marchese, Anthony, advisor; Mizia, John, committee member; Jathar, Shantanu, committee member; Magzamen, Sheryl, committee member
CSU is working with Research Triangle Institute on the Reinvent the Toilet Challenge (RTTC) to develop a fecal matter combustion system. The proposed system will dry, pelletize and combust fecal matter from a community bathroom in a net zero energy consumption process. This technology has the potential to reduce disease by improving sanitation in rural villages that lack modern plumbing. This research is aimed at helping the 2.5 billion individuals in the world who lack modern plumbing and sanitation facilities. Many villages have nothing more than a concrete pit for defecation, and some individuals have no alternative to open defecation, which creates a huge potential for disease transmission. If individuals could safely burn away their fecal material without using any external energy or resources, the instances of sanitation-related disease could be greatly reduced. In this project, CSU's primary tasks are the optimization and automation of fecal combustion technology. The current combustor design is a modified continuous feed downdraft gasifier. Through a series of tests and measurements, several modifications and improvements have been made to the combustor and its control system, allowing the system to burn fecal materials cleanly and efficiently, while ensuring the destruction of any disease-causing pathogens or bacteria.
Open Access
Estimating spatiotemporal trends in wildfire smoke concentrations in the western United States
(Colorado State University. Libraries, 2018) O'Dell, Katelyn, author; Pierce, Jeffrey R., advisor; Fischer, Emily V., advisor; Ford, Bonne, committee member; Magzamen, Sheryl, committee member
The United States (US) has seen significant improvements in seasonal air quality over the past several decades. However, particulate air quality in summer over the majority of the western US has seen little improvement in recent decades. Particulate matter with diameters < 2.5 microns (PM2.5) is a large component of ambient air quality that is associated with negative health effects and visibility degradation. Wildfires are a major summer source of PM2.5 in the western US. While anthropogenic-related sources of PM2.5 have decreased across the US, wildfires have increased in both frequency and burn area since the 1980s. It is currently uncertain how this increase in wildfires has impacted seasonal air quality trends and how the health effects of wildfire-emitted PM2.5 may differ from anthropogenic-sourced PM2.5. We do not directly address the latter uncertainty, but rather focus on improving smoke-exposure estimates, which are a critical, yet challenging, component to understanding the health effects of wildfire-emitted PM2.5. In this thesis, we use a combination of satellite estimates, surface observations, and chemical transport models to distinguish wildfire smoke PM2.5 from non-wildfire-smoke PM2.5 during the summer in the US. We update the record of seasonal trends in PM2.5 observed at surface monitors and provide the first estimates of trends in wildfire smoke-specific PM2.5. We find continued decreases in total-PM2.5 in most seasons and regions of the US. In the summer in heavily fire-impacted regions of the western US, we find non-decreasing total-PM2.5 while wildfire smoke-specific PM2.5 has increased and non-wildfire-smoke PM2.5 has decreased. We test the application of blended smoke exposure models, which use multiple data sources as input variables (e.g. satellite-derived aerosol optical depth, chemical transport models, etc.), across the full western US. We incorporate a novel dataset into the model, Facebook posts, which have been shown to correlate well with surface PM2.5 concentrations during the western US wildfire season. We find the blended smoke exposure model performs well across the western US (R2 = 0.66). However, the Facebook dataset is well correlated with interpolated surface monitors (another input variable) and thus does not significantly improve blended smoke-exposure estimates in the western US.
Open Access
Excessive weight gain and gestational diabetes melitus (GDM), hypertensive states, and Cesarean deliveries among Wyoming women
(Colorado State University. Libraries, 2016) Chance, Alicia, author; Bachand, Annette, advisor; Reif, John, committee member; Melby, Chris, committee member; Magzamen, Sheryl, committee member
Background The proportion of women gaining more weight during pregnancy has become an increasing public health issue. Recent data show that nationally, about half of pregnant women gain more weight than the current Institute of Medicine guidelines. Further, over gaining during pregnancy can lead to a number of adverse outcomes for both the mother as well as the fetus. In this study our aim was to determine if, and to what extent, excessive gestational weight gain increased the risk of gestational diabetes mellitus, hypertensive conditions and incidence of Cesarean deliveries among Wyoming women. Methods Birth certificates from all Wyoming residence were collected between January 2006 and August 2010. More than 36,000 records were obtained. Logistic regression models were used, to evaluate the associations between excessive weight gain and gestational diabetes, hypertensive conditions and cesarean deliveries. Confounders and effect modifiers were also assessed. Results Among the entire population we found that 49% gained more weight than recommended. Further, 2% had gestational diabetes, 4.9% had a hypertensive condition and 25% had a cesarean delivery. We found that women who were classified as having excessive weight gain were not significantly more likely to have an increased risk of gestational diabetes. Women with excessive weight gain were 2 times more likely to have a hypertensive state (OR: 2.148; 95% CI: 1.85-2.49) and were 30% more likely to have a Cesarean delivery (OR: 1.29; 95% CI: 1.22-1.37). None of our 16 potential confounders, identified a priori, were identified to significantly affect this relationship. Several interaction variables were significantly associated. When the endpoint of interest was hypertension there were two interactions that were associated. Among women who had excessive weight gain, women who had adequate plus prenatal care, compared to women with adequate were 50% more likely to have a hypertensive condition. Among women who had excessive weight gain, women who were American Indian, compared to white were half as likely to have a hypertensive condition. When the endpoint of interest was Cesarean deliveries there were three interactions that were associated. Among women who had excessive weight gain, women who had three or more children, compared to women who had none were 20% less likely to have a Cesarean delivery. Among women who had excessive weight gain, women who were had less than a high school level of education, compared to women with a college level of education were 20% less likely to have a Cesarean delivery. Lastly, among women who had excessive weight gain, women who were classified as a race of other, compared to white women were 25% more likely to have a Cesarean delivery. Conclusion The results from this study show that excessive weight gain is associated with twice the risk of having a hypertensive condition and 30% increased risk in having a Cesarean delivery. These results add to the accumulating body of evidence to help explain the risk of excessive weight gain and how optimal gain depends on maternal characteristics.
Open Access
Health-relevant pollutants in US landscape fire smoke: abundance, health impacts, and influence on indoor and outdoor air quality
(Colorado State University. Libraries, 2021) O'Dell, Katelyn, author; Pierce, Jeffrey R., advisor; Fischer, Emily V., advisor; Collett, Jeffrey L., Jr., committee member; Ford, Bonne, committee member; Magzamen, Sheryl, committee member
Landscape (wild, prescribed, and agricultural) fires have a significant impact on air quality in the United States (US). As anthropogenic emissions decline and emissions from landscape fires increase across the coming century, the relative importance of landscape fire smoke on US air quality and health will increase. Landscape fire smoke is a complex mixture of multiple gas- and particle-phase pollutants, which are harmful to human health. The health impacts of landscape fire smoke may differ from urban pollution as the seasonal and spatial distribution, particle size distribution and composition, and relative abundance of gas-phase species in landscape fire smoke are different from urban pollution sources. Epidemiology studies of smoke events, which often rely on particulate matter (PM) concentrations as a smoke exposure tracer, show smoke negatively impacts respiratory health. The contribution of gas-phase hazardous air pollutants (HAPs) to the health impacts of smoke has yet to be directly quantified. In addition, the implications of episodic landscape fire emissions on the sub-national temporal and spatial distribution of health events are not well characterized. Finally, a majority of the work on the health and air quality impacts of landscape fire smoke has focused on outdoor air. Recent works have shown that landscape fire smoke can impact indoor air quality, but there is large heterogeneity in both smoke events and the indoor environments impacted by smoke events. To date, no study of US wildfire smoke influence on indoor air quality has analyzed indoor fine particulate matter (PM2.5) concentrations across multiple western US cities during multiple extreme smoke events. In the first chapter of this dissertation, we combine aircraft-based in-situ smoke plume observations with interpolated regulatory surface monitor observations to quantify the health risk of HAPs in US smoke. Using observations from the Western Wildfire Experiment for Cloud Chemistry, Aerosol Absorption, and Nitrogen (WE-CAN), a 2018 aircraft-based field campaign that measured HAPs and PM in western US wildfire smoke plumes, we identify the relationships be- tween HAPs and associated health risks, PM, and smoke age. We find the ratios between acute, chronic noncancer, and chronic cancer HAPs health risk and PM in smoke decrease as a function of smoke age by up to 72% from fresh (<1 day of aging) to old (>3 days of aging) smoke. We show that acrolein, formaldehyde, benzene, and hydrogen cyanide are the dominant contributors to gas-phase HAPs risk in smoke plumes. We use ratios of HAPs to PM along with annual average smoke-specific PM to estimate current and potential future smoke HAPs risks. Next, we use a health impact assessment with observation-based smoke PM2.5 to determine the sub-national distribution of mortality and the sub-national and sub-annual distribution of morbidity attributable to US smoke PM2.5 from 2006-2018. We estimate disability-adjusted life years (DALYs) for PM2.5 and 18 gas-phase HAPs in smoke using the HAPs to PM ratios developed in Chapter 2. Although the majority of large landscape fires occur in the western US, we find the majority of mortality (74%) and morbidity (on average 75% across 2006-2018) attributable to smoke PM2.5 occurs outside the West due to a higher population density in the East. Across the US, smoke-attributable morbidity predominantly occurs in spring and summer. The number of DALYs associated with smoke PM2.5 are approximately three orders of magnitude higher than DALYs associated with gas-phase smoke HAPs. These results indicate that awareness and mitigation of landscape fire smoke exposure is important across the US, not just in regions in proximity to large wildfires. Finally, we use a large low-cost sensor network of indoor and outdoor PM2.5 monitors to characterize the relationship between indoor and outdoor air quality during smoke events. We identify smoke-impacted regions of the western US with a high density of co-located (distance < 1000 m) indoor and outdoor PurpleAir monitors. In these regions, we calculate indoor PM2.5/outdoor PM2.5 ratios on smoke-impacted and smoke-free days and find this ratio is < 1 (indoor PM2.5 less than outdoor PM2.5) at 98% of the monitor pairs for smoke-impacted days, compared to 54% on smoke- free days. On smoke-impacted days, indoor PM2.5 concentrations increase as outdoor PM2.5 Air Quality Index (AQI) increases by 25% per AQI bin, on average. However, the ratio of indoor PM2.5 to outdoor PM2.5 decreases by 28% per AQI bin. These results show that landscape fire smoke influences indoor air quality across many indoor environments in multiple cities, and this impact increases with smoke event intensity. In addition, this work highlights the utility of low-cost monitoring in quantifying indoor air quality during smoke events. However, we show that the present distribution of these indoor monitors suggests a bias towards census tracts of lower social vulnerability.
Embargo
Investigating the association between public health system structure and system effectiveness
(Colorado State University. Libraries, 2024) Orr, Jason, author; Golicic, Susan, advisor; Bradley, Thomas, committee member; Miller, Erika, committee member; Gutilla, Molly, committee member; Magzamen, Sheryl, committee member
Public health systems in the United States face significant challenges due to their complexity and variability. This dissertation follows a three-paper format and examines these systems through a comprehensive analysis, using systems approaches, latent transition analysis (LTA), and ordinal regression to uncover patterns and inform improvements in public health governance and service delivery. The first essay (Chapter 2) explores the application of systems approaches to the design and improvement of public health systems. A scoping review was conducted, revealing a paucity of literature on the use of "hard" systems methodologies like systems analysis and engineering in public health. The findings highlight the potential for systems approaches to enhance the efficiency, effectiveness, and equity of public health services. However, the limited engagement by public health practitioners and the lack of depth in existing literature indicate significant gaps that need to be addressed to fully leverage systems science in public health governance and service delivery. Building on the literature review, the second essay (Chapter 3) introduces a novel typology of local health departments (LHDs) using LTA based on the National Association of County and City Health Officials (NACCHO) Profile study data. The LTA identified six distinct latent statuses of LHDs, characterized by variables such as governance centrality, colocation, and integration. This typology provides a robust framework for understanding the structural and operational diversity of LHDs, offering insights into how these factors influence public health outcomes. The final essay (Chapter 4) applies ordinal regression analyses to explore the relationship between the latent statuses of LHDs and various community health outcomes. Initial analyses using a cumulative logit model indicated a violation of the proportional odds assumption, necessitating a shift to a generalized logit model. This approach revealed significant predictors of latent statuses, such as poor physical health days, preventable hospital stays, and life expectancy. The findings underscore the complexity of public health systems and the need for careful selection of statistical models to accurately capture these dynamics. The study provides actionable insights for public health policy and strategic planning, highlighting areas for future research and potential interventions to optimize public health system design and operations. This dissertation underscores the importance of systems approaches in understanding and improving public health systems. By leveraging advanced statistical models and exploring the structural characteristics of LHDs, it contributes to a deeper understanding of the factors influencing public health governance and service delivery. The findings offer a foundation for future research and policy development aimed at enhancing the efficiency and effectiveness of public health systems to better serve communities.
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Low-cost devices for occupational and environmental exposure assessment
(Colorado State University. Libraries, 2018) Quinn, Casey, author; Volckens, John, advisor; Henry, Charles, advisor; Magzamen, Sheryl, committee member; Anderson, Georgiana Brooke, committee member; Reynolds, Stephen, committee member
The measurement of chemical and physical stressors in occupational and environmental settings traditionally requires sophisticated equipment, trained professionals, and laboratory-based analyses. These requirements are cost and time prohibitive and, thus, limit the quantity and frequency of exposure monitoring. This dissertation focuses on the development of low-cost monitoring tools for evaluation of air and water quality. Water Quality Assessment Metal contamination of natural and drinking water systems poses hazards to public and environmental health. Quantifying metal concentrations in water typically requires sample collection in the field followed by expensive laboratory analysis that can take days to weeks to obtain results. The first portion of this was to develop a low-cost, field-deployable method to quantify trace levels of copper in drinking water by coupling solid-phase extraction/preconcentration with a microfluidic paper-based analytical device. This method has the advantages of being hand-powered (instrument-free) and using a simple 'read by eye' quantification motif (based on color distance). Tap water samples collected across Fort Collins, CO were tested with this method and validated against ICP-MS. We demonstrate the ability to quantify the copper content of tap-water within 30% of a reference technique at levels ranging from 20 to 500,000 ppb. The application of this technology, which should be sufficient as a rapid screening tool, can lead to faster, more cost-effective detection of soluble metals in water systems. Air Quality Assessment Personal monitors for air quality are expensive and cumbersome, which hinders epidemiologic and occupational exposure assessments. The Automated Microenvironmental Aerosol Sampler (AMAS) is a low-cost, wearable device containing four filter-pump assemblies designed to measure personal exposure particulate matter air pollution. This novel device collects size-selective samples of particulate matter from within distinct personal microenvironments (i.e. at home, at work, and in transit). The AMAS uses on-board sensors (GPS, light intensity, temperature, pressure, and acceleration) coupled with an algorithm (developed and described in to this work) to determine when an individual enters a given microenvironment and then initiates sampling through one of three filter assemblies. Low-cost devices capable of in-field quantification of pollutant hazards can allow researchers to afford more monitoring and analysis equipment and increase the size of epidemiology and industrial hygiene cohorts.
Open Access
Occupational injury prevention among loggers in the Intermountain region of the United States
(Colorado State University. Libraries, 2018) Lagerstrom, Elise, author; Rosecrance, John, advisor; Magzamen, Sheryl, committee member; Brazile, William, committee member; Stallones, Lorann, committee member
Despite advances in harvesting techniques, commercial logging continues to be one of the most dangerous occupations in the United States (US). In 2015, logging workers had the highest rate of fatal work injuries of all US industries (Bureau of Labor Statistics, 2017). In 2016, the nationwide fatality rate for the logging industry was 100.1 per 100,000 full-time equivalent workers (FTE), almost 30 times higher than the nationwide fatality rate for all occupations combined (U.S. Bureau of Labor Statistics, 2017). Logging in the Intermountain (Montana and Idaho, USA) region is especially dangerous due to steep terrain, weather conditions, and remote work locations. To date, there are very few studies which provide an analysis of logging safety and none which focus on the specific challenges and risks present in the Intermountain region. The specific aims and objectives of this proposal are consistent with the recommended strategic goals outlined in the National Occupational Research Agenda (NORA). Strategic goals six and seven in the NORA are to reduce the number, rate and severity of traumatic injuries and deaths involving hazards of forestry and to improve the health and well-being of forestry workers by reducing occupational causes or contributing factors to acute and chronic illness and disease (NORA Agricultural Forestry and Fishing Sector Council, 2008). The Systematic Approach to Training provided the overall model for this project. Several other models and methodology were also used to create an intervention program focused on logging workers operating in the Intermountain region of the United States. The intervention program consisted of an emergency first-aid training program that provided didactic instruction, relevant examples, and practical skills to respond to emergencies, which commonly occur in the logging industry. The justification of the need for an emergency first-aid training program in the logging industry was primarily based mixed methods analysis of five-years of workers' compensation data and focus groups with 63 professional loggers (Study 1). We then investigated the demographics and self-reported work-related musculoskeletal symptoms among a cohort of 743 loggers in Montana (Study 2). We also conducted a study to quantify safety climate and identify the determinants of safety climate (Study 3). A Systematic Approach to Training was then used to develop, implement, and evaluate an emergency first-aid training program that specifically addresses the challenges and hazards of the logging industry (Study 4). Approximately 7-months following the emergency first-aid training a qualitative analysis was conducted to evaluate the longer-term effects of the training program and identify curriculum improvements (Study 5).
Embargo
Pathogens, pulmonary function, and the nasal microbiome of dairy workers
(Colorado State University. Libraries, 2024) Seidel, James, author; Schaeffer, Joshua, advisor; Magzamen, Sheryl, committee member; Abdo, Zaid, committee member; Valley, Morgan, committee member
Dairy workers are exposed to bioaerosols that are diverse in both size (0-100 µm in aerodynamic diameter) and inflammatory constituents (e.g. endotoxins, muramic acid, and β-glucans). Bioaerosol exposure at dairies is associated with a higher prevalence of chronic obstructive pulmonary disease (COPD), chronic bronchitis, asthma, respiratory pneumonitis, and asthma-like reductions in pulmonary function. More recently, opportunistic pathogens present at dairies such as the novel influenza D virus (IDV), influenza A (IAV), and livestock-associated Methicillin-resistant Staphylococcus aureus (MRSA) have also been a focus of research, as these pathogens can infect workers and pose a public health risk through community spread. Intrinsic factors such as genetics and childhood exposures likely play a major role in exposure response and respiratory disease pathology, but little research has been focused on the nasal microbiome's role in pathogen exposure and cross-shift changes of pulmonary function. From a longitudinal (2-5 working shifts) cohort of dairy workers in the High Plains Region of the US, this research analyzed pathogens found in the nares of dairy workers via pre- and post-shift nasal lavages. The same nasal lavages underwent targeted 16S rRNA gene sequencing to quantify the bacterial communities that comprise the nasal microbiome. Spirometry was also performed on dairy workers pre- and post-shift to measure cross-shift changes in pulmonary function. Overall, 32.1% (n=237) of nasal lavages tested positive for Methicillin-susceptible Staphylococcus aureus (MSSA), 11.4% tested positive for MRSA, 17.3% for IDV, 2.5% for IAV, and 1.3% for influenzas C virus (ICV). Only 1 of the original 31 participants never tested positive for a pathogen during their workweek. Differences in nasal microbiome characteristics emerged based on pathogen positivity, and differential abundance analysis revealed significant differences in genera based on the positivity of both bacterial and viral pathogens. The dairy workers in this study also experienced decreases in cross-shift pulmonary function. The average decrease in forced expiratory volume in one second (FEV1) over 108 working shift was -74.4 ml, and the average decrease of forced vital capacity (FVC) was -92.5 ml. Significant differences in microbiome characteristics did emerge based on post-shift and cross-shift spirometry performances, and taxonomic differences were noted in participants performing poorly on cross-shift FVC. The nasal microbiomes of workers also underwent community state typing, and participants in CST3 showed the most resilience to cross-shift changes in lung function. This research also investigated the efficacy of a hypertonic saline nasal lavage in improving cross-shift changes in pulmonary function. From a cohort of 44 dairy workers, 22 workers received pre- and post-shift hypertonic saline nasal lavages with an osmotic concentration of 400 milliosmole (mOsm). The 22 participants in the control group received pre- and post-shift normotonic saline (308 mOsm) nasal lavages. Based on constructed mixed linear models, the treatment improved cross-shift outcomes of the forced expiratory flow at 25-75% of the vital capacity (FEF25-75%), but had little effect on FEV1 and FVC. The use of a pre- and post-shift lavage of any osmolarity, however, appeared to reduce the burden of cross-shift pulmonary function decline often experienced by dairy workers. For the first time, this research showed that both viral and bacterial pathogens are present in the nares of US dairy workers. This work also identified the nasal microbiome characteristics that may play a role in pathogen exposure and cross-shift lung function outcomes. The use of a saline nasal lavage as an intervention was also explored, and the intervention appeared to improve cross-shift pulmonary function outcomes.
Open Access
Public health considerations for a potential Lyme disease vaccine in the United States: cost of illness, vaccine acceptability, and net costs of a vaccination program
(Colorado State University. Libraries, 2021) Hook, Sarah A., author; Peel, Jennifer, advisor; Anderson, Brooke, committee member; Bayham, Jude, committee member; Magzamen, Sheryl, committee member
To view the abstract, please see the full text of the document.
Open Access
Shades of risk: a mixed-methods approach to designing and testing a new hurricane map graphic
(Colorado State University. Libraries, 2023) Rosen, Zoey, author; Long, Marilee, advisor; Abrams, Katie, committee member; Sivakumar, Gayathri, committee member; Magzamen, Sheryl, committee member; Most, David, committee member
Map graphics are a popular tool for hazard risk communication, layered with numerical, verbal, and visual information to describe an uncertain threat. In the hurricane context, graphics are used to communicate the probability of different threats over a forecasting period. While hurricane graphics have been studied in the past, they have not been analyzed from the design phase through to the intended audience. Additionally, hurricane graphics have not been designed with colorblind-friendly accessibility in mind. This dissertation presents the results of a three-phase, mixed methods study: (a) graphic development, (b) testing with expert user groups, and (c) testing with a public sample. In the development phase (a), I used the best practices for using probability language, color schemes, and localization into map graphics from literature in forecasting, communication, universal design, and emergency management. Additionally, I held informal interviews with professionals from the National Hurricane Center to develop the prototype with their recommendations for the design. In the first testing phase b, I interviewed 19 expert users (emergency managers and meteorologists) from Florida and Louisiana about their preferences for and feedback on the design elements of a new hurricane graphic, as well as if there were individual characteristics that influenced how accurate they were in interpreting wind exceedance data, such as risk perception, confidence, experience, spatial cognition, and numeracy levels. In phase c, I tested the wind exceedance graphic prototypes using a public sample (n = 624) from Louisiana and Florida to gather data on the accuracy of their interpretations for the graphic, again measuring confidence, experience, spatial cognition, and numeracy levels, as well as their design preferences and risk perceptions. The results of the two testing phases (b and c) center around how accurate experts and the public were with interpreting the graphic, as well as if there were other factors that influenced this accuracy, such as spatial cognition or numeracy. Additionally, the results describe both groups' design preferences, risk perceptions of the color schemes and overlays, and how experts think about vulnerability when using the graphic. In both groups, numeracy and spatial cognition were found to predict accuracy of interpretation for a wind exceedance graphic prototype. Likewise, both confidence and experience were found to have a positive relationship with accuracy. Regarding the design choices, both experts and the public preferred a yellow-to-red scheme, though experts thought the yellow-to-red scheme presented the hazard as riskier and the public thought the reds-only was riskier. Adding overlays to the graphic, such as interstates or city landmarks, helped the participants to orient themselves on the map. Experts and the public preferred that there were overlays added to the graphic and scored this version of the graphic as risker than a version without any overlays. The addition of the overlays prompted expert users to think more about the risk and vulnerability of the people in those areas on the map. Vulnerability was conceptualized from both a physical and social standpoint by the experts and applied to how they would use the wind exceedance graphic in a briefing to communicate to their community partners. Overall, this research provides a model for how hazard risk map graphics can be studied from design through implementation. Additionally, I captured how experts think about vulnerability in their communities when shown a forecast map graphic. The conclusion of this dissertation also provides practical recommendations for experts who want to apply the universal design aspects into new hurricane graphics.
Open Access
Simulation modeling as a tool for the control of Foot-and-Mouth Disease (FMD) in endemic regions
(Colorado State University. Libraries, 2019) Zaheer, Muhammad Usman, author; Rao, Sangeeta, advisor; Salman, Mo D., advisor; Steneroden, Katie, committee member; Weber, Steve, committee member; Magzamen, Sheryl, committee member
To view the abstract, please see the full text of the document.
Open Access
Spatiotemporal variability of peroxy acyl nitrates (PANs) over megacities from satellite observations
(Colorado State University. Libraries, 2023) Shogrin, Madison J., author; Fischer, Emily V., advisor; Payne, Vivienne H., committee member; Pierce, Jeffrey, committee member; Miller, Steven, committee member; Magzamen, Sheryl, committee member
Peroxy acyl nitrates (PANs) are photochemical pollutants with implications for health and atmospheric oxidation capacity. PANs are formed via the oxidation of non-methane volatile organic compounds (NMVOCs) in the presence of nitrogen oxide radicals (NOx = NO + NO2). PANs serve as reservoir species and sources for NOx in outflow regions of megacities, facilitating O3 production downwind. While urban environments are large sources of PANs, in-situ observations in urban areas are generally limited. Here we use satellite measurements of PANs from the Tropospheric Emission Spectrometer (TES) and the S-NPP Cross-Track Infrared Sounder (CrIS) to evaluate the spatiotemporal variability of PANs over and surrounding 9 megacities: Mexico City, Beijing, Los Angeles, Tokyo, São Paulo, Delhi, Mumbai, Lagos, and Karachi. We use monthly mean values of PANs to determine the seasonal cycle within the urban center of megacities. We find pronounced seasonal cycles of PANs in megacities and seasonal maxima in PANs correspond to seasonal peaks in local photochemical activity. Local fire activity can explain some of the observed interannual variability in PANs over and around megacities. We use S-NPP CrIS data to probe the spatial outflow pattern of PANs produced within urban Mexico City during the month with the largest mixing ratios of PANs (April). Peak outflow in April occurs to the northeast of the city and over the mountains south of the city. Outflow to the northwest appears infrequent. CrIS is used to further explore changes in PANs associated with substantial declines in megacity NOx in response to the COVID-19 pandemic. We only identify two cities over which PANs changed significantly in response to NOx perturbations: Beijing and Los Angeles. This work demonstrates that the space-based observations provided by CrIS and TES can increase understanding of the spatiotemporal variability and sensitivity to precursor emissions of PANs over and around global megacities.