School of Public Health
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The collections in this community comprise faculty research works, as well as graduate theses and dissertations.
Note: Prior to July 1, 2007, the School of Public Health was named the College of Health & Human Performance.
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Item Global Population Exposed to Extreme Events in the 150 Most Populated Cities of the World: Implications for Public Health(MDPI, 2021-02-01) Li, Linze; Jiang, Chengsheng; Murtugudde, Raghu; Liang, Xin-Zhong; Sapkota, AmirClimate change driven increases in the frequency of extreme heat events (EHE) and extreme precipitation events (EPE) are contributing to both infectious and non-infectious disease burden, particularly in urban city centers. While the share of urban populations continues to grow, a comprehensive assessment of populations impacted by these threats is lacking. Using data from weather stations, climate models, and urban population growth during 1980–2017, here, we show that the concurrent rise in the frequency of EHE, EPE, and urban populations has resulted in over 500% increases in individuals exposed to EHE and EPE in the 150 most populated cities of the world. Since most of the population increases over the next several decades are projected to take place in city centers within low- and middle-income countries, skillful early warnings and community specific response strategies are urgently needed to minimize public health impacts and associated costs to the global economy.Item Climate change, extreme events, and increased risk of salmonellosis: foodborne diseases active surveillance network (FoodNet), 2004-2014(Springer Nature, 2021-09-18) Morgado, Michele E.; Jiang, Chengsheng; Zambrana, Jordan; Upperman, Crystal Romeo; Mitchell, Clifford; Boyle, Michelle; Sapkota, Amy R.; Sapkota, AmirInfections with nontyphoidal Salmonella cause an estimated 19,336 hospitalizations each year in the United States. Sources of infection can vary by state and include animal and plant-based foods, as well as environmental reservoirs. Several studies have recognized the importance of increased ambient temperature and precipitation in the spread and persistence of Salmonella in soil and food. However, the impact of extreme weather events on Salmonella infection rates among the most prevalent serovars, has not been fully evaluated across distinct U.S. regions. To address this knowledge gap, we obtained Salmonella case data for S. Enteriditis, S. Typhimurium, S. Newport, and S. Javiana (2004-2014; n = 32,951) from the Foodborne Diseases Active Surveillance Network (FoodNet), and weather data from the National Climatic Data Center (1960-2014). Extreme heat and precipitation events for the study period (2004-2014) were identified using location and calendar day specific 95th percentile thresholds derived using a 30-year baseline (1960-1989). Negative binomial generalized estimating equations were used to evaluate the association between exposure to extreme events and salmonellosis rates. We observed that extreme heat exposure was associated with increased rates of infection with S. Newport in Maryland (Incidence Rate Ratio (IRR): 1.07, 95% Confidence Interval (CI): 1.01, 1.14), and Tennessee (IRR: 1.06, 95% CI: 1.04, 1.09), both FoodNet sites with high densities of animal feeding operations (e.g., broiler chickens and cattle). Extreme precipitation events were also associated with increased rates of S. Javiana infections, by 22% in Connecticut (IRR: 1.22, 95% CI: 1.10, 1.35) and by 5% in Georgia (IRR: 1.05, 95% CI: 1.01, 1.08), respectively. In addition, there was an 11% (IRR: 1.11, 95% CI: 1.04-1.18) increased rate of S. Newport infections in Maryland associated with extreme precipitation events. Overall, our study suggests a stronger association between extreme precipitation events, compared to extreme heat, and salmonellosis across multiple U.S. regions. In addition, the rates of infection with Salmonella serovars that persist in environmental or plant-based reservoirs, such as S. Javiana and S. Newport, appear to be of particular significance regarding increased heat and rainfall events.Item Travel patterns during pregnancy: comparison between Global Positioning System (GPS) tracking and questionnaire data(Springer Nature, 2013-10-09) Wu, Jun; Jiang, Chengsheng; Jaimes, Guillermo; Bartell, Scott; Dang, Andy; Baker, Dean; Delfino, Ralph JMaternal exposures to traffic-related air pollution have been associated with adverse pregnancy outcomes. Exposures to traffic-related air pollutants are strongly influenced by time spent near traffic. However, little is known about women’s travel activities during pregnancy and whether questionnaire-based data can provide reliable information on travel patterns during pregnancy. Examine women’s in-vehicle travel behavior during pregnancy and examine the difference in travel data collected by questionnaire and global positioning system (GPS) and their potential for exposure error. We measured work-related travel patterns in 56 pregnant women using a questionnaire and one-week GPS tracking three times during pregnancy (<20 weeks, 20–30 weeks, and >30 weeks of gestation). We compared self-reported activities with GPS-derived trip distance and duration, and examined potentially influential factors that may contribute to differences. We also described in-vehicle travel behavior by pregnancy periods and influences of demographic and personal factors on daily travel times. Finally, we estimated personal exposure to particle-bound polycyclic aromatic hydrocarbon (PB-PAH) and examined the magnitude of exposure misclassification using self-reported vs. GPS travel data.Subjects overestimated both trip duration and trip distance compared to the GPS data. We observed moderately high correlations between self-reported and GPS-recorded travel distance (home to work trips: r = 0.88; work to home trips: r = 0.80). Better agreement was observed between the GPS and the self-reported travel time for home to work trips (r = 0.77) than work to home trips (r = 0.64). The subjects on average spent 69 and 93 minutes traveling in vehicles daily based on the GPS and self-reported data, respectively. Longer daily travel time was observed among participants in early pregnancy, and during certain pregnancy periods in women with higher education attainment, higher income, and no children. When comparing self-reported vs. GPS data, we found that estimated personal exposure to PB-PAH did not differ remarkably at the population level, but the difference was large at an individual level. Self-reported home-to-work data overestimated both trip duration and trip distance compared to GPS data. Significant differences in PAH exposure estimates were observed at individual level using self-reported vs. GPS data, which has important implications in air pollution epidemiological studies.Item Spatial disparity in the distribution of superfund sites in South Carolina: an ecological study(Springer Nature, 2013-11-06) Burwell-Naney, Kristen; Zhang, Hongmei; Samantapudi, Ashok; Jiang, Chengsheng; Dalemarre, Laura; Rice, LaShanta; Williams, Edith; Wilson, SacobyAccording to the US Environmental Protection Agency (EPA), Superfund is a federal government program implemented to clean up uncontrolled hazardous waste sites. Twenty-six sites in South Carolina (SC) have been included on the National Priorities List (NPL), which has serious human health and environmental implications. The purpose of this study was to assess spatial disparities in the distribution of Superfund sites in SC. The 2000 US census tract and block level data were used to generate population characteristics, which included race/ethnicity, socioeconomic status (SES), education, home ownership, and home built before 1950. Geographic Information Systems (GIS) were used to map Superfund facilities and develop choropleth maps based on the aforementioned sociodemographic variables. Spatial methods, including mean and median distance analysis, buffer analysis, and spatial approximation were employed to characterize burden disparities. Regression analysis was performed to assess the relationship between the number of Superfund facilities and population characteristics. Spatial coincidence results showed that of the 29.5% of Blacks living in SC, 55.9% live in Superfund host census tracts. Among all populations in SC living below poverty (14.2%), 57.2% were located in Superfund host census tracts. Buffer analyses results (0.5mi, 1.0mi, 5.0mi, 0.5km, 1.0km, and 5.0km) showed a higher percentage of Whites compared to Blacks hosting a Superfund facility. Conversely, a slightly higher percentage of Blacks hosted (30.2%) a Superfund facility than those not hosting (28.8%) while their White counterparts had more equivalent values (66.7% and 67.8%, respectively). Regression analyses in the reduced model (Adj. R2 = 0.038) only explained a small percentage of the variance. In addition, the mean distance for percent of Blacks in the 90th percentile for Superfund facilities was 0.48mi. Burden disparities exist in the distribution of Superfund facilities in SC at the block and census tract levels across varying levels of demographic composition for race/ethnicity and SES.Item Being overburdened and medically underserved: assessment of this double disparity for populations in the state of Maryland(Springer Nature, 2014-04-04) Wilson, Sacoby; Zhang, Hongmei; Jiang, Chengsheng; Burwell, Kristen; Rehr, Rebecca; Murray, Rianna; Dalemarre, Laura; Naney, CharlesEnvironmental justice research has shown that many communities of color and low-income persons are differentially burdened by noxious land uses including Toxic Release Inventory (TRI) facilities. However, limited work has been performed to assess how these populations tend to be both overburdened and medically underserved. We explored this “double disparity” for the first time in Maryland. We assessed spatial disparities in the distribution of TRI facilities in Maryland across varying levels of sociodemographic composition using 2010 US Census Health Professional Shortage Area (HPSA) data. Univariate and multivariate regression in addition to geographic information systems (GIS) were used to examine relationships between sociodemographic measures and location of TRI facilities. Buffer analysis was also used to assess spatial disparities. Four buffer categories included: 1) census tracts hosting one or more TRI facilities; 2) tracts located more than 0 and up to 0.5 km from the closest TRI facility; 3) tracts located more than 0.5 km and up to 1 km from a TRI facility; and 4) tracts located more than 1 km and up to 5 km from a TRI facility. We found that tracts with higher proportions of non-white residents and people living in poverty were more likely to be closer to TRI facilities. A significant increase in income was observed with an increase in distance between a census tract and the closest TRI facility. In general, percent non-white was higher in HPSA tracts that host at least one TRI facility than in non-HPSA tracts that host at least one TRI facility. Additionally, percent poverty, unemployment, less than high school education, and homes built pre-1950 were higher in HPSA tracts hosting TRI facilities than in non-HPSA tracts hosting TRI facilities. We found that people of color and low-income groups are differentially burdened by TRI facilities in Maryland. We also found that both low-income groups and persons without a high school education are both overburdened and medically underserved. The results of this study provide insight into how state agencies can better address the double disparity of disproportionate environmental hazards and limited access to health care resources facing vulnerable communities in Maryland.Item Exposure to extreme heat and precipitation events associated with increased risk of hospitalization for asthma in Maryland, U.S.A.(Springer Nature, 2016-04-27) Soneja, Sutyajeet; Jiang, Chengsheng; Fisher, Jared; Upperman, Crystal Romeo; Mitchell, Clifford; Sapkota, AmirSeveral studies have investigated the association between asthma exacerbations and exposures to ambient temperature and precipitation. However, limited data exists regarding how extreme events, projected to grow in frequency, intensity, and duration in the future in response to our changing climate, will impact the risk of hospitalization for asthma. The objective of our study was to quantify the association between frequency of extreme heat and precipitation events and increased risk of hospitalization for asthma in Maryland between 2000 and 2012. We used a time-stratified case-crossover design to examine the association between exposure to extreme heat and precipitation events and risk of hospitalization for asthma (ICD-9 code 493, n = 115,923). Occurrence of extreme heat events in Maryland increased the risk of same day hospitalization for asthma (lag 0) by 3 % (Odds Ratio (OR): 1.03, 95 % Confidence Interval (CI): 1.00, 1.07), with a considerably higher risk observed for extreme heat events that occur during summer months (OR: 1.23, 95 % CI: 1.15, 1.33). Likewise, summertime extreme precipitation events increased the risk of hospitalization for asthma by 11 % in Maryland (OR: 1.11, 95 % CI: 1.06, 1.17). Across age groups, increase in risk for asthma hospitalization from exposure to extreme heat event during the summer months was most pronounced among youth and adults, while those related to extreme precipitation event was highest among ≤4 year olds. Exposure to extreme heat and extreme precipitation events, particularly during summertime, is associated with increased risk of hospitalization for asthma in Maryland. Our results suggest that projected increases in frequency of extreme heat and precipitation event will have significant impact on public health.Item Association between community socioeconomic factors, animal feeding operations, and campylobacteriosis incidence rates: Foodborne Diseases Active Surveillance Network (FoodNet), 2004–2010(Springer Nature, 2016-07-22) Rosenberg Goldstein, Rachel E.; Cruz-Cano, Raul; Jiang, Chengsheng; Palmer, Amanda; Blythe, David; Ryan, Patricia; Hogan, Brenna; White, Benjamin; Dunn, John R.; Libby, Tanya; Tobin-D’Angelo, Melissa; Huang, Jennifer Y.; McGuire, Suzanne; Scherzinger, Karen; Ting Lee, Mei-Ling; Sapkota, Amy R.Campylobacter is a leading cause of foodborne illness in the United States. Campylobacter infections have been associated with individual risk factors, such as the consumption of poultry and raw milk. Recently, a Maryland-based study identified community socioeconomic and environmental factors that are also associated with campylobacteriosis rates. However, no previous studies have evaluated the association between community risk factors and campylobacteriosis rates across multiple U.S. states. We obtained Campylobacter case data (2004–2010; n = 40,768) from the Foodborne Diseases Active Surveillance Network (FoodNet) and socioeconomic and environmental data from the 2010 Census of Population and Housing, the 2011 American Community Survey, and the 2007 U.S. Census of Agriculture. We linked data by zip code and derived incidence rate ratios using negative binomial regression models. Community socioeconomic and environmental factors were associated with both lower and higher campylobacteriosis rates. Zip codes with higher percentages of African Americans had lower rates of campylobacteriosis (incidence rate ratio [IRR]) = 0.972; 95 % confidence interval (CI) = 0.970,0.974). In Georgia, Maryland, and Tennessee, three leading broiler chicken producing states, zip codes with broiler operations had incidence rates that were 22 % (IRR = 1.22; 95 % CI = 1.03,1.43), 16 % (IRR = 1.16; 95 % CI = 0.99,1.37), and 35 % (IRR = 1.35; 95 % CI = 1.18,1.53) higher, respectively, than those of zip codes without broiler operations. In Minnesota and New York FoodNet counties, two top dairy producing areas, zip codes with dairy operations had significantly higher campylobacteriosis incidence rates (IRR = 1.37; 95 % CI = 1.22, 1.55; IRR = 1.19; 95 % CI = 1.04,1.36). Community socioeconomic and environmental factors are important to consider when evaluating the relationship between possible risk factors and Campylobacter infection.Item Frequency of Extreme Heat Event as a Surrogate Exposure Metric for Examining the Human Health Effects of Climate Change(PLOS (Public Library of Science), 2015-12-07) Upperman, Crystal Romeo; Parker, Jennifer; Jiang, Chengsheng; He, Xin; Murtugudde, Raghuram; Sapkota, AmirEpidemiological investigation of the impact of climate change on human health, particularly chronic diseases, is hindered by the lack of exposure metrics that can be used as a marker of climate change that are compatible with health data. Here, we present a surrogate exposure metric created using a 30-year baseline (1960–1989) that allows users to quantify long-term changes in exposure to frequency of extreme heat events with near unabridged spatial coverage in a scale that is compatible with national/state health outcome data. We evaluate the exposure metric by decade, seasonality, area of the country, and its ability to capture long-term changes in weather (climate), including natural climate modes. Our findings show that this generic exposure metric is potentially useful to monitor trends in the frequency of extreme heat events across varying regions because it captures long-term changes; is sensitive to the natural climate modes (ENSO events); responds well to spatial variability, and; is amenable to spatial/temporal aggregation, making it useful for epidemiological studies.