Publications by authors named "Sheryl Magzamen"

69 Publications

Joint effects of ambient air pollution and maternal smoking on neonatal adiposity and childhood BMI trajectories in the Healthy Start study.

Environ Epidemiol 2021 Jun 5;5(3):e142. Epub 2021 May 5.

Department of Epidemiology, Colorado School of Public Health, Aurora, Colorado.

Coexposure to air pollution and tobacco smoke may influence early-life growth, but few studies have investigated their joint effects. We examined the interaction between fetal exposure to maternal smoking and ozone (O) or fine particulate matter (PM) on birth weight, neonatal adiposity, and body mass index (BMI) trajectories through age 3 years.

Methods: Participants were 526 mother-child pairs, born ≥37 weeks. Cotinine was measured at ~27 weeks gestation. Whole pregnancy and trimester-specific O and PM were estimated via. inverse-distance weighted interpolation from stationary monitors. Neonatal adiposity (fat mass percentage) was measured via. air displacement plethysmography. Child weight and length/height were abstracted from medical records. Interaction was assessed by introducing cotinine (<31.5 vs. ≥31.5 ng/mL [indicating active smoking]), O/PM (low [tertiles 1-2] vs. high [tertile 3]), and their product term in linear regression models for birth weight and neonatal adiposity and mixed-effects models for BMI trajectories.

Results: The rate of BMI growth among offspring jointly exposed to maternal smoking and high PM (between 8.1 and 12.7 μg/m) in the third trimester was more rapid than would be expected due to the individual exposures alone (0.8 kg/m per square root year; 95% CI = 0.1, 1.5; for interaction = 0.03). We did not detect interactions between maternal smoking and O or PM at any other time on birth weight, neonatal adiposity, or BMI trajectories.

Conclusions: Although PM was generally below the EPA annual air quality standards of 12.0 μg/m, exposure during the third trimester may influence BMI trajectories when combined with maternal smoking.
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http://dx.doi.org/10.1097/EE9.0000000000000142DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC8196098PMC
June 2021

Sociodemographic Characteristics and Physical Activity in Patients with COPD: A 3-Month Cohort Study.

COPD 2021 May 10:1-13. Epub 2021 May 10.

Department of Medicine, University of Washington, Seattle, WA, USA.

Decreased physical activity (PA) is associated with morbidity and mortality in COPD patients. In this secondary analysis of data from a 12-week longitudinal study, we describe factors associated with PA in COPD. Participants completed the Physical Activity Checklist (PAC) daily for a 7- to 8-day period. PA was measured monthly using the Physical Activity Scale for the Elderly (PASE). At three different time points, daily step count was measured for one week with an Omron HJ-720ITC pedometer. The 35 participants were primarily male (94%) and White (91%), with an average age of 66.5 years and FEV 44.9% predicted. Common activities reported on the PAC were walking (93%), preparing a meal (89%), and traveling by vehicle (96%). PA measured by both PASE score ( = 0.01) and average daily step count ( = 0.04) decreased during follow-up. In repeated measures multivariable modeling, participants living with others had a higher daily step count (ß = 942 steps, = 0.01) and better PASE scores (ß = 46.4, < 0.001). Older age was associated with decreased step count (ß = -77 steps, < 0.001) whereas White race was associated with lower PASE scores (ß = -55.4, < 0.001) compared to non-White race. Other demographic factors, quality of life, and medications were not associated with PA. A better understanding of the role of social networks and social support may help develop interventions to improve PA in COPD.
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http://dx.doi.org/10.1080/15412555.2021.1920902DOI Listing
May 2021

Exposure to ambient air pollution during pregnancy and inflammatory biomarkers in maternal and umbilical cord blood: The Healthy Start study.

Environ Res 2021 Jun 20;197:111165. Epub 2021 Apr 20.

Department of Epidemiology, Colorado School of Public Health, University of Colorado Anschutz Medical Campus, Aurora, CO, USA; Lifecourse Epidemiology of Adiposity and Diabetes (LEAD) Center, University of Colorado Anschutz Medical Campus, Aurora, CO, USA.

Background: Air pollution exposure during pregnancy has been associated with adverse pregnancy and birth outcomes. Inflammation has been proposed as a potential link. We estimated associations between air pollution exposure during pregnancy and inflammatory biomarkers in maternal and cord blood. We evaluated whether maternal inflammation was associated with infant outcomes.

Methods: Among 515 mother-infant dyads in the Healthy Start study (2009-2014), trimester-long, 7- and 30-day average concentrations of particulate matter ≤2.5 μm (PM) and ozone (O) during pregnancy were estimated, using inverse-distance-weighted interpolation. Inflammatory biomarkers were measured in maternal blood in mid-pregnancy (C-reactive protein [CRP], Interleukin [IL]-6, and tumor necrosis factor-α [TNFα]) and in cord blood at delivery (CRP, IL-6, IL-8, IL-10, monocyte chemoattractant protein-1 [MCP-1], and TNFα). We used linear regression to estimate associations between pollutants and inflammatory biomarkers and maternal inflammatory biomarkers and infant weight and body composition.

Results: There were positive associations between PM during certain exposure periods and maternal IL-6 and TNFα. There were negative associations between recent O and maternal CRP, IL-6, and TNFα and positive associations between trimester-long O exposure and maternal inflammatory biomarkers, though some 95% confidence intervals included the null. Patterns were inconsistent for associations between PM and O and cord blood inflammatory biomarkers. No consistent associations between maternal inflammatory biomarkers and infant outcomes were identified.

Conclusions: Air pollution exposure during pregnancy may impact maternal inflammation. Further investigations should examine the health consequences for women and infants of elevated inflammatory biomarkers associated with air pollution exposure during pregnancy.
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http://dx.doi.org/10.1016/j.envres.2021.111165DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC8216209PMC
June 2021

Model choice for estimating the association between exposure to chemical mixtures and health outcomes: A simulation study.

PLoS One 2021 25;16(3):e0249236. Epub 2021 Mar 25.

Department of Statistics, Colorado State University, Fort Collins, CO, United states of America.

Challenges arise in researching health effects associated with chemical mixtures. Several methods have recently been proposed for estimating the association between health outcomes and exposure to chemical mixtures, but a formal simulation study comparing broad-ranging methods is lacking. We select five recently developed methods and evaluate their performance in estimating the exposure-response function, identifying active mixture components, and identifying interactions in a simulation study. Bayesian kernel machine regression (BKMR) and nonparametric Bayes shrinkage (NPB) were top-performing methods in our simulation study. BKMR and NPB outperformed other contemporary methods and traditional linear models in estimating the exposure-response function and identifying active mixture components. BKMR and NPB produced similar results in a data analysis of the effects of multipollutant exposure on lung function in children with asthma.
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http://journals.plos.org/plosone/article?id=10.1371/journal.pone.0249236PLOS
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7993848PMC
March 2021

A Spatiotemporal Prediction Model for Black Carbon in the Denver Metropolitan Area, 2009-2020.

Environ Sci Technol 2021 03 17;55(5):3112-3123. Epub 2021 Feb 17.

Department of Environmental and Radiological Health Sciences, Colorado State University, Fort Collins, Colorado 80523-1019, United States.

Studies on health effects of air pollution from local sources require exposure assessments that capture spatial and temporal trends. To facilitate intraurban studies in Denver, Colorado, we developed a spatiotemporal prediction model for black carbon (BC). To inform our model, we collected more than 700 weekly BC samples using personal air samplers from 2018 to 2020. The model incorporated spatial and spatiotemporal predictors and smoothed time trends to generate point-level weekly predictions of BC concentrations for the years 2009-2020. Our results indicate that our model reliably predicted weekly BC concentrations across the region during the year in which we collected data. We achieved a 10-fold cross-validation of 0.83 and a root-mean-square error of 0.15 μg/m for weekly BC concentrations predicted at our sampling locations. Predicted concentrations displayed expected temporal trends, with the highest concentrations predicted during winter months. Thus, our prediction model improves on typical land use regression models that generally only capture spatial gradients. However, our model is limited by a lack of long-term BC monitoring data for full validation of historical predictions. BC predictions from the weekly spatiotemporal model will be used in traffic-related air pollution exposure-disease associations more precisely than previous models for the region have allowed.
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http://dx.doi.org/10.1021/acs.est.0c06451DOI Listing
March 2021

Tropical Cyclone Exposures and Risks of Emergency Medicare Hospital Admission for Cardiorespiratory Diseases in 175 Urban United States Counties, 1999-2010.

Epidemiology 2021 05;32(3):315-326

From the Department of Environmental and Radiological Health Sciences, Colorado State University, Fort Collins, CO.

Background: Although injuries experienced during hurricanes and other tropical cyclones have been relatively well-characterized through traditional surveillance, less is known about tropical cyclones' impacts on noninjury morbidity, which can be triggered through pathways that include psychosocial stress or interruption in medical treatment.

Methods: We investigated daily emergency Medicare hospitalizations (1999-2010) in 180 US counties, drawing on an existing cohort of high-population counties. We classified counties as exposed to tropical cyclones when storm-associated peak sustained winds were ≥21 m/s at the county center; secondary analyses considered other wind thresholds and hazards. We matched storm-exposed days to unexposed days by county and seasonality. We estimated change in tropical cyclone-associated hospitalizations over a storm period from 2 days before to 7 days after the storm's closest approach, compared to unexposed days, using generalized linear mixed-effect models.

Results: For 1999-2010, 175 study counties had at least one tropical cyclone exposure. Cardiovascular hospitalizations decreased on the storm day, then increased following the storm, while respiratory hospitalizations were elevated throughout the storm period. Over the 10-day storm period, cardiovascular hospitalizations increased 3% (95% confidence interval = 2%, 5%) and respiratory hospitalizations increased 16% (95% confidence interval = 13%, 20%) compared to matched unexposed periods. Relative risks varied across tropical cyclone exposures, with strongest association for the most restrictive wind-based exposure metric.

Conclusions: In this study, tropical cyclone exposures were associated with a short-term increase in cardiorespiratory hospitalization risk among the elderly, based on a multi-year/multi-site investigation of US Medicare beneficiaries ≥65 years.
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http://dx.doi.org/10.1097/EDE.0000000000001337DOI Listing
May 2021

Modelling the domestic poultry population in the United States: A novel approach leveraging remote sensing and synthetic data methods.

Geospat Health 2020 12 10;15(2). Epub 2020 Dec 10.

Colorado State University, Department of Environmental and Radiological Health Sciences, Fort Collins, CO.

Comprehensive and spatially accurate poultry population demographic data do not currently exist in the United States; however, these data are critically needed to adequately prepare for, and efficiently respond to and manage disease outbreaks. In response to absence of these data, this study developed a national-level poultry population dataset by using a novel combination of remote sensing and probabilistic modelling methodologies. The Farm Location and Agricultural Production Simulator (FLAPS) (Burdett et al., 2015) was used to provide baseline national-scale data depicting the simulated locations and populations of individual poultry operations. Remote sensing methods (identification using aerial imagery) were used to identify actual locations of buildings having the characteristic size and shape of commercial poultry barns. This approach was applied to 594 U.S. counties with > 100,000 birds in 34 states based on the 2012 U.S. Department of Agriculture (USDA), National Agricultural Statistics Service (NASS), Census of Agriculture (CoA). The two methods were integrated in a hybrid approach to develop an automated machine learning process to locate commercial poultry operations and predict the number and type of poultry for each operation across the coterminous United States. Validation illustrated that the hybrid model had higher locational accuracy and more realistic distribution and density patterns when compared to purely simulated data. The resulting national poultry population dataset has significant potential for application in animal disease spread modelling, surveillance, emergency planning and response, economics, and other fields, providing a versatile asset for further agricultural research.
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http://dx.doi.org/10.4081/gh.2020.913DOI Listing
December 2020

Challenges to the Application of Spatially Explicit Stochastic Simulation Models for Foot-and-Mouth Disease Control in Endemic Settings: A Systematic Review.

Comput Math Methods Med 2020 21;2020:7841941. Epub 2020 Nov 21.

Animal Population Health Institute, Department of Clinical Sciences, College of Veterinary Medicine and Biomedical Sciences, Colorado State University, Fort Collins CO 80523, USA.

Simulation modeling has become common for estimating the spread of highly contagious animal diseases. Several models have been developed to mimic the spread of foot-and-mouth disease (FMD) in specific regions or countries, conduct risk assessment, analyze outbreaks using historical data or hypothetical scenarios, assist in policy decisions during epidemics, formulate preparedness plans, and evaluate economic impacts. Majority of the available FMD simulation models were designed for and applied in disease-free countries, while there has been limited use of such models in FMD endemic countries. This paper's objective was to report the findings from a study conducted to review the existing published original research literature on spatially explicit stochastic simulation (SESS) models of FMD spread, focusing on assessing these models for their potential use in endemic settings. The goal was to identify the specific components of endemic FMD needed to adapt these SESS models for their potential application in FMD endemic settings. This systematic review followed the PRISMA guidelines, and three databases were searched, which resulted in 1176 citations. Eighty citations finally met the inclusion criteria and were included in the qualitative synthesis, identifying nine unique SESS models. These SESS models were assessed for their potential application in endemic settings. The assessed SESS models can be adapted for use in FMD endemic countries by modifying the underlying code to include multiple cocirculating serotypes, routine prophylactic vaccination (RPV), and livestock population dynamics to more realistically mimic the endemic characteristics of FMD. The application of SESS models in endemic settings will help evaluate strategies for FMD control, which will improve livestock health, provide economic gains for producers, help alleviate poverty and hunger, and will complement efforts to achieve the Sustainable Development Goals.
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http://dx.doi.org/10.1155/2020/7841941DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7700052PMC
November 2020

The joint effect of ambient air pollution and agricultural pesticide exposures on lung function among children with asthma.

Environ Res 2020 11 18;190:109903. Epub 2020 Jul 18.

Department of Environmental and Radiological Health Sciences, Colorado State University, Fort Collins, CO, USA.

Background: Ambient environmental pollutants have been shown to adversely affect respiratory health in susceptible populations. However, the role of simultaneous exposure to multiple diverse environmental pollutants is poorly understood.

Objective: We applied a multidomain, multipollutant approach to assess the association between pediatric lung function measures and selected ambient air pollutants and pesticides.

Methods: Using data from the US EPA and California Pesticide Use Registry, we reconstructed three months prior exposure to ambient air pollutants ((ozone (O), nitrogen dioxide (NO), particulate matter with a median aerodynamic diameter < 2.5 μm (PM) and <10 μm (PM)) and pesticides (organophosphates (OP), carbamates (C) and methyl bromide (MeBr)) for 153 children with mild intermittent or mild persistent asthma from the San Joaquin Valley of California, USA. We implemented Bayesian kernel machine regression (BKMR) to estimate the association between simultaneous exposures to air pollutants and pesticides and lung function measures (forced expiratory volume in 1 s (FEV), forced vital capacity (FVC), and forced expiratory flow between 25% and 75% of vital capacity (FEF)).

Results: In BKMR analysis, the overall effect of mixtures (pollutants and pesticides) was associated with reduced FEV and FVC, particularly when all the environmental exposures were above their 60th percentile. For example, the effect of the overall mixture at the 70th percentile (compared to the median) was a -0.12SD (-50 mL, 95% CI: -180 mL, 90 mL) change in the FEV and a -0.18SD (-90 mL, 95% CI: -240 mL, 60 mL) change in the FVC. However, 95% credible intervals around all of the joint effect estimates contained the null value.

Conclusion: At this agricultural-urban interface, we observed results from multipollutant analyses, suggestive of adverse effects on some pediatric lung function measures following a cumulative increase in ambient air pollutants and agricultural pesticides. Given the uncertainty in effect estimates, this approach should be explored in larger studies.
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http://dx.doi.org/10.1016/j.envres.2020.109903DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7529969PMC
November 2020

Application of the Environmental Relative Moldiness Index in Indoor Marijuana Grow Operations.

Ann Work Expo Health 2020 08;64(7):728-744

Department of Environmental and Radiological Health Sciences, Colorado State University, Fort Collins, CO, USA.

Objectives: Indoor marijuana grow operations (IMGOs) are increasing due to legalization of recreational and medicinal cannabis at the state level. However, the potential exposures of IMGO workers have not been well studied. Mold exposure has been identified as a major occupational health concern. Mold-specific quantitative polymerase chain reaction (MSQPCR) can provide quantitative exposure data for fungi at the species level. The purpose of this study was to characterize the airborne fungal burden using MSQPCR and to evaluate the applicability of an airborne Environmental Relative Moldiness Index (ERMI) in IMGOs.

Methods: Air and dust samples were collected inside and outside the IMGOs and then analyzed via MSQPCR. These data were then used to calculate IMGO-specific ERMI scores. Culturable air samples were collected on agar plates and analyzed via microscopy. Differences were evaluated between indoor and outdoor concentrations, as well as between air and dust samples. The agreement between MSQPCR and culture-based methods was also evaluated.

Results: Based on the geometric means for non-zero values of each fungal species across all IMGOs, the total airborne concentration was approximately 9100 spore equivalent (SE) m-3 with an interquartile range (IQR) of 222 SE m-3. The indoor/outdoor ratio of geometric means across all 36 species per IMGO ranged from 0.4 to 6.2. Significantly higher indoor concentrations of fungal species, including Aspergillus spp., were observed. An average airborne ERMI score of 7 (IQR = 7.6) indicated a relatively high burden of mold across a majority of operations. The ERMI scores were driven by the high concentrations of Group 1 species with a mean of 15.8 and an IQR of 13. There were 63 additional species identified in the culturable air samples not included in the ERMI.

Conclusions: High concentrations of airborne fungi were identified in IMGOs. Our evaluation of the ERMI based on MSQPCR as a rapid diagnostic and risk assessment tool for industrial hygienists in the IMGO setting is equivocal. ERMI did not identify all relevant fungal species associated with this specific occupational environment. We identified several issues with using the ERMI calculation. At this time, the catalog of fungal species needs to optimized for the occupational setting to ensure adequate coverage, especially for those species expected to be found in this burgeoning industry. Further research is necessary to elucidate the link between the ERMI score of airborne samples, worker exposure and health effects in grows to generate an acceptable index score for use in occupational exposure assessments.
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http://dx.doi.org/10.1093/annweh/wxaa071DOI Listing
August 2020

Genome-wide association analysis of canine T zone lymphoma identifies link to hypothyroidism and a shared association with mast-cell tumors.

BMC Genomics 2020 Jul 6;21(1):464. Epub 2020 Jul 6.

Department of Microbiology, Immunology and Pathology, College of Veterinary Medicine and Biomedical Sciences, Colorado State University, Fort Collins, CO, USA.

Background: T zone lymphoma (TZL), a histologic variant of peripheral T cell lymphoma, represents about 12% of all canine lymphomas. Golden Retrievers appear predisposed, representing over 40% of TZL cases. Prior research found that asymptomatic aged Golden Retrievers frequently have populations of T zone-like cells (phenotypically identical to TZL) of undetermined significance (TZUS), potentially representing a pre-clinical state. These findings suggest a genetic risk factor for this disease and caused us to investigate potential genes of interest using a genome-wide association study of privately-owned U.S. Golden Retrievers.

Results: Dogs were categorized as TZL (n = 95), TZUS (n = 142), or control (n = 101) using flow cytometry and genotyped using the Illumina CanineHD BeadChip. Using a mixed linear model adjusting for population stratification, we found association with genome-wide significance in regions on chromosomes 8 and 14. The chromosome 14 peak included four SNPs (Odds Ratio = 1.18-1.19, p = .3 × 10-5.1 × 10) near three hyaluronidase genes (SPAM1, HYAL4, and HYALP1). Targeted resequencing of this region using a custom sequence capture array identified missense mutations in all three genes; the variant in SPAM1 was predicted to be damaging. These mutations were also associated with risk for mast cell tumors among Golden Retrievers in an unrelated study. The chromosome 8 peak contained 7 SNPs (Odds Ratio = 1.24-1.42, p = 2.7 × 10-7.5 × 10) near genes involved in thyroid hormone regulation (DIO2 and TSHR). A prior study from our laboratory found hypothyroidism is inversely associated with TZL risk. No coding mutations were found with targeted resequencing but identified variants may play a regulatory role for all or some of the genes.

Conclusions: The pathogenesis of canine TZL may be related to hyaluronan breakdown and subsequent production of pro-inflammatory and pro-oncogenic byproducts. The association on chromosome 8 may indicate thyroid hormone is involved in TZL development, consistent with findings from a previous study evaluating epidemiologic risk factors for TZL. Future work is needed to elucidate these mechanisms.
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http://dx.doi.org/10.1186/s12864-020-06872-9DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7339439PMC
July 2020

Associations Between Bioaerosol Exposures and Lung Function Changes Among Dairy Workers in Colorado.

J Occup Environ Med 2020 06;62(6):424-430

Department of Environmental and Radiological Health Sciences, Colorado State University, Fort Collins, Colorado (Martenies, Schaeffer, Erlandson, Bradford, Reynolds, Magzamen), Division of Allergy and Immunology, Department of Medicine, University of Nebraska Medical Center, Omaha, NE (Poole), Department of Statistics, Colorado State University, Fort Collins, Colorado (Wilson, Weller), Department of Epidemiology, Colorado School of Public Health, Colorado (Magzamen) and High Plains Intermountain Center for Agricultural Health and Safety, Fort Collins, Colorado (Schaeffer, Bradford, Reynolds, Magzamen).

Objective: Limited studies have examined effects of bioaerosols on the respiratory health of dairy workers; previous findings have been inconsistent across populations.

Methods: Using a repeated measures design, exposures to dust, bioaerosols, and ozone were assessed and pre- and post-shift spirometry was performed for dairy workers (n = 36). Workers completed 1 to 8 visits. Linear mixed effect models estimated associations between air pollutant constituents and changes in spirometry.

Results: There was an association between higher dust exposures and increased peak expiratory flow rate. However, for all other outcomes there was no association with the exposures considered.

Conclusions: Relationships between bioaerosol exposures and respiratory health in dairy workers remain unclear. Future studies should increase sample sizes, include repeated measures designs, vary the timing of spirometry measurements, and include markers for Gram positive bacteria such as muramic acid or peptidoglycan.
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http://dx.doi.org/10.1097/JOM.0000000000001856DOI Listing
June 2020

Health and Environmental Justice Implications of Retiring Two Coal-Fired Power Plants in the Southern Front Range Region of Colorado.

Geohealth 2019 Sep 26;3(9):266-283. Epub 2019 Sep 26.

Department of Environmental and Radiological Health Sciences Colorado State University Fort Collins CO USA.

Despite improvements in air quality over the past 50 years, ambient air pollution remains an important public health issue in the United States. In particular, emissions from coal-fired power plants still have a substantial impact on both nearby and regional populations. Of particular concern is the potential for this impact to fall disproportionately on low-income communities and communities of color. We conducted a quantitative health impact assessment to estimate the health benefits of the proposed decommissioning of two coal-fired electricity generating stations in the Southern Front Range region of Colorado. We estimated changes in exposures to fine particulate matter and ozone using the Community Multiscale Air Quality model and predicted avoided health impacts and related economic values. We also quantitatively assessed the distribution of these benefits by population-level socioeconomic status. Across the study area, decommissioning the power plants would result in 2 (95% CI: 1-3) avoided premature deaths each year due to reduced PM exposures and greater reductions in hospitalizations and other morbidities. Health benefits resulting from the modeled shutdowns were greatest in areas with lower educational attainment and other economic indicators. Our results suggest that decommissioning these power plants and replacing them with zero-emissions sources could have broad public health benefits for residents of Colorado, with larger benefits for those that are socially disadvantaged. Our results also suggested that researchers and decision makers need to consider the unique demographics of their study areas to ensure that important opportunities to reduce health disparities associated with point-source pollution.
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http://dx.doi.org/10.1029/2019GH000206DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7007175PMC
September 2019

Correction: Dynamic classification of personal microenvironments using a suite of wearable, low-cost sensors.

J Expo Sci Environ Epidemiol 2020 Nov;30(6):1032

Department of Environmental and Radiological Health Sciences, Colorado State University, Fort Collins, CO, 80523, USA.

The original version of this Article featured an incorrect supplementary figure file. This error has been rectified in the PDF and HTML versions of this Article.
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http://dx.doi.org/10.1038/s41370-020-0217-3DOI Listing
November 2020

Community-wide Mortality Rates in Beijing, China, During the July 2012 Flood Compared with Unexposed Periods.

Epidemiology 2020 05;31(3):319-326

From the Department of Environmental & Radiological Health Sciences, Colorado State University.

Background: On 21-22 July 2012, Beijing, China, suffered its heaviest rainfall in 60 years. Two studies have estimated the fatality toll of this disaster using a traditional surveillance approach. However, traditional surveillance can miss disaster-related deaths, including a substantial number of deaths from natural causes triggered by disaster exposure. Here, we investigated community-wide mortality risk during this flood compared with rates in unexposed reference periods.

Methods: We compared community-wide mortality rates on the peak flood day and the four following days to seasonally matched nonflood 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.

Results: On 21 July 2012, the flood-associated RRs were 1.34 (95% confidence interval = 1.11, 1.61) for all-cause, 1.37 (1.01, 1.85) for circulatory, and 4.40 (2.98, 6.51) for accidental mortality, compared with unexposed periods. We observed no evidence of increased risk of respiratory mortality. For the flood period of 21-22 July 2012, we estimated a total of 79 excess deaths among Beijing residents; by contrast, only 34 deaths were reported among Beijing residents in a study using a traditional surveillance approach.

Conclusions: To our knowledge, this is the first study analyzing 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 on flood-related health impacts, as urban flooding is expected to become more frequent and severe in China.
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http://dx.doi.org/10.1097/EDE.0000000000001182DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7138731PMC
May 2020

Prenatal exposure to traffic and ambient air pollution and infant weight and adiposity: The Healthy Start study.

Environ Res 2020 03 10;182:109130. Epub 2020 Jan 10.

Department of Epidemiology, Colorado School of Public Health, University of Colorado Anschutz Medical Campus, Aurora, CO, USA; Lifecourse Epidemiology of Adiposity and Diabetes (LEAD) Center, University of Colorado Anschutz Medical Campus, Aurora, CO, USA; Department of Pediatrics, School of Medicine, University of Colorado Anschutz Medical Campus, Aurora, CO, USA.

Background: Prenatal exposures to ambient air pollution and traffic have been associated with adverse birth outcomes, and may also lead to an increased risk of obesity. Obesity risk may be reflected in changes in body composition in infancy.

Objective: To estimate associations between prenatal ambient air pollution and traffic exposure, and infant weight and adiposity in a Colorado-based prospective cohort study.

Methods: Participants were 1125 mother-infant pairs with term births. Birth weight was recorded from medical records and body composition measures (fat mass, fat-free mass, and adiposity [percent fat mass]) were evaluated via air displacement plethysmography at birth (n = 951) and at ~5 months (n = 574). Maternal residential address was used to calculate distance to nearest roadway, traffic density, and ambient concentrations of fine particulate matter (PM) and ozone (O) via inverse-distance weighted interpolation of stationary monitoring data, averaged by trimester and throughout pregnancy. Adjusted linear regression models estimated associations between exposures and infant weight and body composition.

Results: Participants were urban residents and diverse in race/ethnicity and socioeconomic status. Average ambient air pollutant concentrations were generally low; the median, interquartile range (IQR), and range of third trimester concentrations were 7.3 μg/m (IQR: 1.3, range: 3.3-12.7) for PM and 46.3 ppb (IQR: 18.4, range: 21.7-63.2) for 8-h maximum O Overall there were few associations between traffic and air pollution exposures and infant outcomes. Third trimester O was associated with greater adiposity at follow-up (2.2% per IQR, 95% CI 0.1, 4.3), and with greater rates of change in fat mass (1.8 g/day, 95% CI 0.5, 3.2) and adiposity (2.1%/100 days, 95% CI 0.4, 3.7) from birth to follow-up.

Conclusions: We found limited evidence of an association between prenatal traffic and ambient air pollution exposure and infant body composition. Suggestive associations between prenatal ozone exposure and early postnatal changes in body composition merit further investigation.
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http://dx.doi.org/10.1016/j.envres.2020.109130DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7394733PMC
March 2020

The association between wildfire smoke exposure and asthma-specific medical care utilization in Oregon during the 2013 wildfire season.

J Expo Sci Environ Epidemiol 2020 07 12;30(4):618-628. Epub 2020 Feb 12.

Department of Environmental and Radiological Health Sciences, Colorado State University, 1681 Campus Delivery, Fort Collins, CO, 80523, USA.

Wildfire smoke (WFS) increases the risk of respiratory hospitalizations. We evaluated the association between WFS and asthma healthcare utilization (AHCU) during the 2013 wildfire season in Oregon. WFS particulate matter ≤ 2.5 μm in diameter (PM) was estimated using a blended model of in situ monitoring, chemical transport models, and satellite-based data. Asthma claims and place of service were identified from Oregon All Payer All Claims data from 1 May 2013 to 30 September 2013. The association with WFS PM was evaluated using time-stratified case-crossover designs. The maximum WFS PM concentration during the study period was 172 µg/m. A 10 µg/m increase in WFS increased risk in asthma diagnosis at emergency departments (odds ratio [OR]: 1.089, 95% confidence interval [CI]: 1.043-1.136), office visit (OR: 1.050, 95% CI: 1.038-1.063), and outpatient visits (OR: 1.065, 95% CI: 1.029-1.103); an association was observed with asthma rescue inhaler medication fills (OR: 1.077, 95% CI: 1.065-1.088). WFS increased the risk for asthma morbidity during the 2013 wildfire season in Oregon. Communities impacted by WFS could see increases in AHCU for tertiary, secondary, and primary care.
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http://dx.doi.org/10.1038/s41370-020-0210-xDOI Listing
July 2020

Dynamic classification of personal microenvironments using a suite of wearable, low-cost sensors.

J Expo Sci Environ Epidemiol 2020 11 14;30(6):962-970. Epub 2020 Jan 14.

Department of Environmental and Radiological Health Sciences, Colorado State University, Fort Collins, CO, 80523, USA.

Human exposure to air pollution is associated with increased risk of morbidity and mortality. However, personal air pollution exposures can vary substantially depending on an individual's daily activity patterns and air quality within their residence and workplace. This work developed and validated an adaptive buffer size (ABS) algorithm capable of dynamically classifying an individual's time spent in predefined microenvironments using data from global positioning systems (GPS), motion sensors, temperature sensors, and light sensors. Twenty-two participants in Fort Collins, CO were recruited to carry a personal air sampler for a 48-h period. The personal sampler was retrofitted with a GPS and a pushbutton to complement the existing sensor measurements (temperature, motion, light). The pushbutton was used in conjunction with a traditional time-activity diary to note when the participant was located at "home", "work", or within an "other" microenvironment. The ABS algorithm predicted the amount of time spent in each microenvironment with a median accuracy of 99.1%, 98.9%, and 97.5% for the "home", "work", and "other" microenvironments. The ability to classify microenvironments dynamically in real time can enable the development of new sampling and measurement technologies that classify personal exposure by microenvironment.
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http://dx.doi.org/10.1038/s41370-019-0198-2DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7358126PMC
November 2020

Prenatal Exposure to Tobacco and Offspring Neurocognitive Development in the Healthy Start Study.

J Pediatr 2020 03 20;218:28-34.e2. Epub 2019 Nov 20.

Department of Epidemiology, Colorado School of Public Health, Aurora, CO; Lifecourse Epidemiology of Adiposity and Diabetes (LEAD) Center, Colorado School of Public Health, Aurora, CO; Department of Pediatrics, University of Colorado School of Medicine, Aurora, CO.

Objective: To explore the associations between prenatal exposure to tobacco and neurocognitive development, in the absence of prematurity or low birth weight.

Study Design: We followed mother-child pairs within Healthy Start through 6 years of age. Children were born at ≥37 weeks of gestation with a birth weight of ≥2500 g. Parents completed the Third Edition Ages and Stages Questionnaire (n = 246) and children completed a subset of the National Institutes of Health Toolbox Cognition Battery (n = 200). The Ages and Stages Questionnaire domains were dichotomized as fail/monitor and pass. Maternal urinary cotinine was measured at approximately 27 weeks of gestation. Separate logistic regression models estimated associations between prenatal exposure to tobacco (cotinine below vs above the limit of detection) and the Ages and Stages Questionnaire domains. Separate linear regression models estimated associations between prenatal exposure to tobacco and fully corrected T-scores for inhibitory control, cognitive flexibility, and receptive language, as assessed by the National Institutes of Health Toolbox. A priori covariates included sex, maternal age, maternal education, daily caloric intake during pregnancy, race/ethnicity, household income, maternal psychiatric disorders, and, in secondary models, postnatal exposure to tobacco.

Results: Compared with unexposed offspring, exposed offspring were more likely to receive a fail/monitor score for fine motor skills (OR, 3.9; 95% CI, 1.5-10.3) and decreased inhibitory control (B: -3.0; 95% CI, -6.1 to -0.7). After adjusting for postnatal exposure, only the association with fine motor skills persisted.

Conclusions: Prenatal and postnatal exposures to tobacco may influence neurocognitive development, in the absence of preterm delivery or low birth weight. Increased developmental screening may be warranted for exposed children.
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http://dx.doi.org/10.1016/j.jpeds.2019.10.056DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7042047PMC
March 2020

Combined environmental and social exposures during pregnancy and associations with neonatal size and body composition: the Healthy Start study.

Environ Epidemiol 2019 Apr;3(2)

Environmental and Radiological Health Sciences, Colorado State University, Fort Collins, CO USA.

Background: Prenatal environmental and social exposures have been associated with decreased birth weight. However, the effects of combined exposures in these domains are not fully understood. Here we assessed multi-domain exposures for participants in the Healthy Start study (Denver, CO) and tested associations with neonatal size and body composition.

Methods: In separate linear regression models, we tested associations between neonatal outcomes and three indices for exposures. Two indices were developed to describe exposures to environmental hazards (ENV) and social determinants of health (SOC). A third index combined exposures in both domains (CE = ENV/10 × SOC/10). Index scores were assigned to mothers based on address at enrollment. Birth weight and length were measured at delivery, and weight-for-length z-scores were calculated using a reference distribution. Percent fat mass was obtained by air displacement plethysmography.

Results: Complete data were available for 897 (64%) participants. Median (range) ENV, SOC, and CE values were 31.9 (7.1-63.2), 36.0 (2.8-75.0), and 10.9 (0.4-45.7), respectively. After adjusting for potential confounders, 10-point increases in SOC and CE were associated with 27.7 g (95%CI: 12.4 - 42.9 g) and 56.3 g (19.4 - 93.2 g) decreases in birth weight, respectively. SOC and CE were also associated with decreases in % fat mass.

Conclusions: Combined exposures during pregnancy were associated with lower birth weight and % fat mass. Evidence of a potential synergistic effect between ENV and SOC suggests a need to more fully consider neighborhood exposures when assessing neonatal outcomes.
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http://dx.doi.org/10.1097/EE9.0000000000000043DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC6775643PMC
April 2019

Characterization of Indoor Air Quality on a College Campus: A Pilot Study.

Int J Environ Res Public Health 2019 07 30;16(15). Epub 2019 Jul 30.

Department of Environmental and Radiological Health Sciences, Colorado State University, Fort Collins, CO 80523, USA.

Recent construction trends on college campuses have demonstrated a shift to designing buildings with features focused on sustainability. However, few studies have investigated indoor air quality in institutions of higher education, particularly in sustainably designed buildings. The objective of this study was to evaluate the association of building and occupancy on indoor air quality within and between higher education buildings. We measured particulate matter, formaldehyde, carbon dioxide, and nitrogen oxides in LEED certified, retrofitted, and conventional building types on a college campus. Three size fractions of particulate matter were measured in each building. We conducted multi-zonal, 48-h measurements when the buildings were occupied and unoccupied. Outdoor particulate matter was significantly higher (PM2.5 = 4.76, PM4 = 17.1, and PM100 = 21.6 µg/m) than in classrooms (PM2.5 = 1.7, PM4 = 4.2, and PM100 = 6.7 µg/m) and common areas (PM2.5 = 1.3, PM4 = 4.2, and PM100 = 4.8 µg/m; all < 0.001). Additionally, concentrations of carbon dioxide and particulate matter were significantly higher ( < 0.05) during occupied sampling. The results suggest that occupancy status and building zone are major predictors of indoor air quality in campus buildings, which can, in turn, increase the concentration of contaminants, potentially impacting occupant health and performance. More research is warranted to reveal building features and human behaviors contributing to indoor exposures.
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http://dx.doi.org/10.3390/ijerph16152721DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC6695958PMC
July 2019

Characterizing the joint effects of pesticide exposure and criteria ambient air pollutants on pediatric asthma morbidity in an agricultural community.

Environ Epidemiol 2019 Jun 19;3(3):e046. Epub 2019 Jun 19.

Department of Environmental and Radiological Health Sciences, Colorado State University, Fort Collins, Colorado.

Background: Environmental contributions to pediatric asthma morbidity have been studied extensively in urban settings; exposures characteristic of agricultural and rural communities have received less attention despite a comparable burden of morbidity.

Methods: We obtained repeated urine samples (n = 139) from 16 school-age children with asthma in the Yakima Valley of Washington State between July and October 2012. Biomarkers of organophosphate (OP) pesticide exposure (dialkyl phosphates [DAPs]) and asthma exacerbation (leukotriene E4 [LTE4]) were analyzed in samples. Corresponding 24-hour average particulate matter <2.5 μg (PM) and maximum 8-hour ozone concentration data for the study period were available from local monitoring stations. We evaluated the independent and multi-pollutant associations between LTE4 and exposure to ambient air pollutants and DAPs using generalized estimating equations. For multi-domain and multi-pollutant models, we created categorized pollution combination levels and estimated the relative health impact of exposure to pollutant mixtures.

Results: In single-pollutant models, an interquartile range increase in exposures to DAPs was associated with increase in LTE4 levels (β: 4.1 [0.6-7.6] pg/mg). PM and ozone were also associated with increase in LTE4, though confidence intervals contained the null value. Increase in LTE4 levels was consistently associated with increase in median-dichotomized multi-pollutant combination exposures; the highest effect estimates were observed with joint highest (vs. the lowest) category of the three-pollutant exposure (PM, ozone, and OP; β: 53.5, 95% confidence interval = 24.2, 82.8 pg/mg).

Conclusion: Concurrent short-term exposure to criteria air pollutants and OPs in an agricultural community was associated with an increase in a marker of asthma morbidity.
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http://dx.doi.org/10.1097/EE9.0000000000000046DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC6571181PMC
June 2019

A national burden assessment of estimated pediatric asthma emergency department visits that may be attributed to elevated ozone levels associated with the presence of smoke.

Environ Monit Assess 2019 Jun 28;191(Suppl 2):269. Epub 2019 Jun 28.

Colorado School of Public Health, Colorado State University, Fort Collins, CO, USA.

Asthma is the most common pediatric disease in the USA. It has been consistently demonstrated that asthma symptoms are exacerbated by exposure to ozone. Ozone (O) is a secondary pollutant produced when volatile organic compounds (VOCs) are oxidized in the atmosphere in the presence of nitrogen oxides (NO). At ground level, elevated ozone is typically formed as a result of human activities. However, wildfires represent an additional source of ozone precursors. Recent evidence suggests that smoke can increase ozone concentrations. We estimated the number of excess asthma-related emergency department (ED) visits in children with asthma that may be attributed to elevated ozone associated with smoke (EOAS) in the USA. We conducted a quantitative burden assessment (BA) using a Monte Carlo approach to estimate the median number of excess pediatric asthma ED visits that may be attributed to EOAS among children with asthma in the continental USA between 2005 and 2014, as well as 95% confidence bounds (95% CB). We estimated that a median of 2403 (95% CB 235-5382) pediatric asthma ED visits could be attributed to EOAS exposure between 2005 and 2014 in the continental USA. Furthermore, the impact of EOAS on estimated asthma ED visits was greatest in the eastern half of the continental USA. We found a significant increase in pediatric asthma ED visits that may be attributed to exposure to EOAS. EOAS may have a measurable negative impact on children with asthma in the USA.
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http://dx.doi.org/10.1007/s10661-019-7420-5DOI Listing
June 2019

Association of Organophosphate Pesticide Exposure and a Marker of Asthma Morbidity in an Agricultural Community.

J Agromedicine 2020 01 25;25(1):106-114. Epub 2019 May 25.

Department of Environmental and Radiological Health Sciences, Colorado State University, Fort Collins, CO, USA.

: We explored the short-term impact of pesticide exposure on asthma exacerbation among children with asthma in an agricultural community.: We obtained repeated urine samples from a subset of 16 school-age children with asthma (n = 139 samples) as part of the Aggravating Factors of Asthma in a Rural Environment (AFARE) study cohort. Biomarkers of organophosphate (OP) pesticide exposure (dialkylphosphates (DAPs)), and asthma exacerbation (leukotriene E4 (uLTE4)) were assessed in urine samples. We used generalized estimating equations to examine the association of summed measures of creatinine-adjusted DAPs (total dimethyl alkylphosphate (EDM), total diethyl alkylphosphate (EDE), and total dialkylphosphate pesticides (EDAP)) and uLTE4 concentration, adjusting for multiple confounders, yielding beta-coefficients with 95% CIs.: A total of 139 observations were obtained from the 16 children over the study period, the total number of samples per subject ranged from 1 to 12 (median: 10.5). The geometric mean (GM) of creatinine-adjusted EDE, EDM, and EDAP in this population were 81.0, 71.8 and 168.0 nmol/g, respectively. Increase in uLTE4 levels was consistently associated with increased exposures to DAPs (interquartile range in μg/g): β: 8.7 (95%CI: 2.8, 14.6); β: 1.1 (0.5, 1.7); β: 4.1 (0.7, 7.5).: This study suggests that short-term OP exposure is associated with a higher risk of asthma morbidity, as indicated by increased uLTE4 levels in this cohort of children with asthma in an agricultural community. Additional studies are required to confirm these adverse effects, and explore the mechanisms underlying this relationship.
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http://dx.doi.org/10.1080/1059924X.2019.1619644DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC6875607PMC
January 2020

Associations of environment, health history, T-zone lymphoma, and T-zone-like cells of undetermined significance: A case-control study of aged Golden Retrievers.

J Vet Intern Med 2019 Mar 21;33(2):764-775. Epub 2019 Jan 21.

Department of Microbiology, Immunology and Pathology, College of Veterinary Medicine and Biomedical Sciences, Colorado State University, Fort Collins, Colorado.

Background: T-zone lymphoma (TZL), an indolent disease in older dogs, comprises approximately 12% of lymphomas in dogs. TZL cells exhibit an activated phenotype, indicating the disease may be antigen-driven. Prior research found that asymptomatic aged Golden Retrievers (GLDRs) commonly have populations of T-zone-like cells (phenotypically identical to TZL) of undetermined significance (TZUS).

Objective: To evaluate associations of inflammatory conditions, TZL and TZUS, using a case-control study of GLDRs.

Animals: TZL cases (n = 140), flow cytometrically diagnosed, were identified through Colorado State University's Clinical Immunology Laboratory. Non-TZL dogs, recruited through either a database of owners interested in research participation or the submitting clinics of TZL cases, were subsequently flow cytometrically classified as TZUS (n = 221) or control (n = 147).

Methods: Health history, signalment, environmental, and lifestyle factors were obtained from owner-completed questionnaires. Odds ratios (ORs) and 95% confidence intervals (95% CIs) were estimated using multivariable logistic regression, obtaining separate estimates for TZL and TZUS (versus controls).

Results: Hypothyroidism (OR, 0.3; 95% CI, 0.1-0.7), omega-3 supplementation (OR, 0.3; 95% CI, 0.1-0.6), and mange (OR, 5.5; 95% CI, 1.4-21.1) were significantly associated with TZL. Gastrointestinal disease (OR, 2.4; 95% CI, 0.98-5.8) had nonsignificantly increased TZL odds. Two shared associations for TZL and TZUS were identified: bladder infection or calculi (TZL OR, 3.5; 95% CI, 0.96-12.7; TZUS OR, 5.1; 95% CI, 1.9-13.7) and eye disease (TZL OR, 2.3; 95% CI, 0.97-5.2; TZUS OR, 1.9; 95% CI, 0.99-3.8).

Conclusions And Clinical Importance: These findings may elucidate pathways involved in TZUS risk and progression from TZUS to TZL. Further investigation into the protective association of omega-3 supplements is warranted.
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http://dx.doi.org/10.1111/jvim.15405DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC6430877PMC
March 2019

Temporal and geographic distribution of weather conditions favorable to airborne spread of foot-and-mouth disease in the coterminous United States.

Prev Vet Med 2018 Dec 23;161:41-49. Epub 2018 Oct 23.

Colorado State University, Department of Environmental and Radiological Health Sciences, 1681 Campus Delivery, Fort Collins, CO 80523-1681, USA. Electronic address:

Foot-and-mouth disease (FMD) is a highly infectious viral disease of cloven-hoofed animals. FMD outbreaks have the potential to cause significant economic consequences, and effective control strategies are needed to minimize the damage to livestock systems and the economy. Although not the predominant route of infection, airborne transmission has been implicated in previous outbreaks. Under favorable weather conditions, airborne spread of FMD can make the rapid containment of an outbreak more difficult. Our objective was to identify seasonal and geographic differences in patterns of conditions favorable to airborne FMD spread in the United States. Data from a national network of surface weather stations were examined for three study years (December 2011-November 2012, December 2012-November 2013, December 2014-November 2015). Weather conditions were found to be most frequently favorable to airborne spread during the winter (December, January, February). Geographically, conditions were most frequently favorable to airborne FMD spread in the upper Midwestern United States, a region where swine and cattle populations are common. Across study years, conditions for airborne FMD spread were more frequently favorable when weather conditions were generally mild with few extremes with respect to temperature and precipitation (e.g., 2014-2015). However, national patterns in risk areas for airborne FMD spread were similar across study years even though the degree of risk differed based on variations in weather patterns among study years. Our findings suggest that airborne transmission could contribute to FMD spread between livestock premises in the event of an outbreak in the coterminous United States, and that some geographic areas are at an increased risk particularly in seasons with conducive weather conditions. To our knowledge, this is the first study to characterize the risk of airborne FMD spread on a national scale in the United States. The findings presented here can be used to enhance preparedness and surveillance activities by identifying specific geographic areas in the United States where airborne spread is most likely to be a risk factor for transmission during an outbreak.
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http://dx.doi.org/10.1016/j.prevetmed.2018.10.016DOI Listing
December 2018

Fetal exposure to maternal active and secondhand smoking with offspring early-life growth in the Healthy Start study.

Int J Obes (Lond) 2019 04 19;43(4):652-662. Epub 2018 Oct 19.

Department of Epidemiology, Colorado School of Public Health, Aurora, CO, USA.

Background: Previous studies have modeled the association between fetal exposure to tobacco smoke and body mass index (BMI) growth trajectories, but not the timing of catch-up growth. Research on fetal exposure to maternal secondhand smoking is limited.

Objectives: To explore the associations between fetal exposure to maternal active and secondhand smoking with body composition at birth and BMI growth trajectories through age 3 years.

Methods: We followed 630 mother-child pairs enrolled in the Healthy Start cohort through age 3 years. Maternal urinary cotinine was measured at ~ 27 weeks gestation. Neonatal body composition was measured using air displacement plethysmography. Child weight and length/height were abstracted from medical records. Linear regression models examined the association between cotinine categories (no exposure, secondhand smoke, active smoking) with weight, fat mass, fat-free mass, and percent fat mass at birth. A mixed-effects regression model estimated the association between cotinine categories and BMI.

Results: Compared to unexposed offspring, birth weight was significantly lower among offspring born to active smokers (-343-g; 95% CI: -473, -213), but not among offspring of women exposed to secondhand smoke (-47-g; 95% CI: -130, 36). There was no significant difference in the rate of BMI growth over time between offspring of active and secondhand smokers (p = 0.58). Therefore, our final model included a single growth rate parameter for the combined exposure groups of active and secondhand smokers. The rate of BMI growth for the combined exposed group was significantly more rapid (0.27 kg/m per year; 95% CI: 0.05, 0.69; p < 0.01) than the unexposed.

Conclusions: Offspring prenatally exposed to maternal active or secondhand smoking experience rapid and similar BMI growth in the first three years of life. Given the long-term consequences of rapid weight gain in early childhood, it is important to encourage pregnant women to quit smoking and limit their exposure to secondhand smoke.
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http://dx.doi.org/10.1038/s41366-018-0238-3DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC6445676PMC
April 2019

Personal Exposure to PM Black Carbon and Aerosol Oxidative Potential using an Automated Microenvironmental Aerosol Sampler (AMAS).

Environ Sci Technol 2018 10 21;52(19):11267-11275. Epub 2018 Sep 21.

Department of Environmental and Radiological Health Sciences , Colorado State University , Fort Collins , Colorado 80523 , United States.

Traditional methods for measuring personal exposure to fine particulate matter (PM) are cumbersome and lack spatiotemporal resolution; methods that are time-resolved are limited to a single species/component of PM. To address these limitations, we developed an automated microenvironmental aerosol sampler (AMAS), capable of resolving personal exposure by microenvironment. The AMAS is a wearable device that uses a GPS sensor algorithm in conjunction with a custom valve manifold to sample PM onto distinct filter channels to evaluate home, school, and other (e.g., outdoors, in transit, etc.) exposures. Pilot testing was conducted in Fresno, CA where 25 high-school participants ( n = 37 sampling events) wore an AMAS for 48-h periods in November 2016. Data from 20 (54%) of the 48-h samples collected by participants were deemed valid and the filters were analyzed for PM black carbon (BC) using light transmissometry and aerosol oxidative potential (OP) using the dithiothreitol (DTT) assay. The amount of inhaled PM was calculated for each microenvironment to evaluate the health risks associated with exposure. On average, the estimated amount of inhaled PM BC (μg day) and OP [(μM min) day] was greatest at home, owing to the proportion of time spent within that microenvironment. Validation of the AMAS demonstrated good relative precision (8.7% among collocated instruments) and a mean absolute error of 22% for BC and 33% for OP when compared to a traditional personal sampling instrument. This work demonstrates the feasibility of new technology designed to quantify personal exposure to PM species within distinct microenvironments.
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http://dx.doi.org/10.1021/acs.est.8b02992DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC6203932PMC
October 2018

Detection of Viruses from Bioaerosols Using Anion Exchange Resin.

J Vis Exp 2018 08 22(138). Epub 2018 Aug 22.

Department of Animal Science, University of Wyoming;

This protocol demonstrates a customized bioaerosol sampling method for viruses. In this system, anion exchange resin is coupled with liquid impingement-based air sampling devices for efficacious concentration of negatively-charged viruses from bioaerosols. Thus, the resin serves as an additional concentration step in the bioaerosol sampling workflow. Nucleic acid extraction of the viral particles is then performed directly from the anion exchange resin, with the resulting sample suitable for molecular analyses. Further, this protocol describes a custom-built bioaerosol chamber capable of generating virus-laden bioaerosols under a variety of environmental conditions and allowing for continuous monitoring of environmental variables such as temperature, humidity, wind speed, and aerosol mass concentration. The main advantage of using this protocol is increased sensitivity of viral detection, as assessed via direct comparison to an unmodified conventional liquid impinger. Other advantages include the potential to concentrate diverse negatively-charged viruses, the low cost of anion exchange resin (~$0.14 per sample), and ease of use. Disadvantages include the inability of this protocol to assess infectivity of resin-adsorbed viral particles, and potentially the need for the optimization of the liquid sampling buffer used within the impinger.
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http://dx.doi.org/10.3791/58111DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC6231709PMC
August 2018

Optimizing community-level surveillance data for pediatric asthma management.

Prev Med Rep 2018 Jun 8;10:55-61. Epub 2018 Feb 8.

Department of Environmental and Radiological Health Sciences, Colorado State University, Fort Collins, CO, USA.

Community-level approaches for pediatric asthma management rely on locally collected information derived primarily from two sources: claims records and school-based surveys. We combined claims and school-based surveillance data, and examined the asthma-related risk patterns among adolescent students. Symptom data collected from school-based asthma surveys conducted in Oakland, CA were used for case identification and determination of severity levels for students (high and low). Survey data were matched to Medicaid claims data for all asthma-related health care encounters for the year prior to the survey. We then employed recursive partitioning to develop classification trees that identified patterns of demographics and healthcare utilization associated with severity. A total of 561 students had complete matched data; 86.1% were classified as high-severity, and 13.9% as low-severity asthma. The classification tree consisted of eight subsets: three indicating high severity and five indicating low severity. The risk subsets highlighted varying combinations of non-specific demographic and socioeconomic predictors of asthma prevalence, morbidity and severity. For example, the subset with the highest class-prior probability (92.1%) predicted high-severity asthma and consisted of students without prescribed rescue medication, but with at least one in-clinic nebulizer treatment. The predictive accuracy of the tree-based model was approximately 66.7%, with an estimated 91.1% of high-severity cases and 42.3% of low-severity cases correctly predicted. Our analysis draws on the strengths of two complementary datasets to provide community-level information on children with asthma, and demonstrates the utility of recursive partitioning methods to explore a combination of features that convey asthma severity.
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http://dx.doi.org/10.1016/j.pmedr.2018.02.004DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC5984210PMC
June 2018