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 Racial and Sex Differences between Urinary Phthalates and Metabolic Syndrome among U.S. Adults: NHANES 2005–2014(MDPI, 2021-06-26) Ghosh, Rajrupa; Haque, Mefruz; Turner, Paul C.; Cruz-Cano, Raul; Dallal, Cher M.Phthalates, plasticizers ubiquitous in household and personal care products, have been associated with metabolic disturbances. Despite the noted racial differences in phthalate exposure and the prevalence of metabolic syndrome (MetS), it remains unclear whether associations between phthalate metabolites and MetS vary by race and sex. A cross-sectional analysis was conducted among 10,017 adults from the National Health and Nutritional Examination Survey (2005–2014). Prevalence odds ratios (POR) and 95% confidence intervals (CIs) were estimated for the association between 11 urinary phthalate metabolites and MetS using weighted sex and race stratified multivariable logistic regression. Higher MCOP levels were significantly associated with increased odds of MetS among women but not men, and only remained significant among White women (POR Q4 vs. Q1 = 1.68, 95% CI: 1.24, 2.29; p-trend = 0.001). Similarly, the inverse association observed with MEHP among women, persisted among White women only (POR Q4 vs. Q1 = 0.53, 95% CI: 0.35, 0.80; p-trend = 0.003). However, ΣDEHP metabolites were associated with increased odds of MetS only among men, and this finding was limited to White men (POR Q4 vs. Q1 = 1.54, 95% CI: 1.01, 2.35; p-trend = 0.06). Among Black men, an inverse association was observed with higher MEP levels (POR Q4 vs. Q1 = 0.43, 95% CI: 0.24, 0.77; p-trend = 0.01). The findings suggest differential associations between phthalate metabolites and MetS by sex and race/ethnicity.Item El Niño Southern Oscillation, monsoon anomaly, and childhood diarrheal disease morbidity in Nepal(Oxford University Press, 2022-03-29) Adams, Nicholas; Dhimal, Meghnath; Mathews, Shifali; Iyer, Veena; Murtugudde, Raghu; Liang, Xin-Zhong; Haider, Muhiuddin; Cruz-Cano, Raul; Thu, Dang Thi Anh; Hashim, Jamal Hisham; Gao, Chuansi; Wang, Yu-Chun; Sapkota, AmirClimate change is adversely impacting the burden of diarrheal diseases. Despite significant reduction in global prevalence, diarrheal disease remains a leading cause of morbidity and mortality among young children in low- and middle-income countries. Previous studies have shown that diarrheal disease is associated with meteorological conditions but the role of large-scale climate phenomena such as El Niño-Southern Oscillation (ENSO) and monsoon anomaly is less understood. We obtained 13 years (2002–2014) of diarrheal disease data from Nepal and investigated how the disease rate is associated with phases of ENSO (El Niño, La Niña, vs. ENSO neutral) monsoon rainfall anomaly (below normal, above normal, vs. normal), and changes in timing of monsoon onset, and withdrawal (early, late, vs. normal). Monsoon season was associated with a 21% increase in diarrheal disease rates (Incident Rate Ratios [IRR]: 1.21; 95% CI: 1.16–1.27). El Niño was associated with an 8% reduction in risk while the La Niña was associated with a 32% increase in under-5 diarrheal disease rates. Likewise, higher-than-normal monsoon rainfall was associated with increased rates of diarrheal disease, with considerably higher rates observed in the mountain region (IRR 1.51, 95% CI: 1.19–1.92). Our findings suggest that under-5 diarrheal disease burden in Nepal is significantly influenced by ENSO and changes in seasonal monsoon dynamics. Since both ENSO phases and monsoon can be predicted with considerably longer lead time compared to weather, our findings will pave the way for the development of more effective early warning systems for climate sensitive infectious diseases.Item Racial and Sex Differences between Urinary Phthalates and Metabolic Syndrome among U.S. Adults: NHANES 2005–2014(MDPI, 2021-06-26) Ghosh, Rajrupa; Haque, Mefruz; Turner, Paul C.; Cruz-Cano, Raul; Dallal, Cher M.Phthalates, plasticizers ubiquitous in household and personal care products, have been associated with metabolic disturbances. Despite the noted racial differences in phthalate exposure and the prevalence of metabolic syndrome (MetS), it remains unclear whether associations between phthalate metabolites and MetS vary by race and sex. A cross-sectional analysis was conducted among 10,017 adults from the National Health and Nutritional Examination Survey (2005–2014). Prevalence odds ratios (POR) and 95% confidence intervals (CIs) were estimated for the association between 11 urinary phthalate metabolites and MetS using weighted sex and race stratified multivariable logistic regression. Higher MCOP levels were significantly associated with increased odds of MetS among women but not men, and only remained significant among White women (POR Q4 vs. Q1 = 1.68, 95% CI: 1.24, 2.29; p-trend = 0.001). Similarly, the inverse association observed with MEHP among women, persisted among White women only (POR Q4 vs. Q1 = 0.53, 95% CI: 0.35, 0.80; p-trend = 0.003). However, SDEHP metabolites were associated with increased odds of MetS only among men, and this finding was limited to White men (POR Q4 vs. Q1 = 1.54, 95% CI: 1.01, 2.35; p-trend = 0.06). Among Black men, an inverse association was observed with higher MEP levels (POR Q4 vs. Q1 = 0.43, 95% CI: 0.24, 0.77; p-trend = 0.01). The findings suggest differential associations between phthalate metabolites and MetS by sex and race/ethnicity.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 Mentholation affects the cigarette microbiota by selecting for bacteria resistant to harsh environmental conditions and selecting against potential bacterial pathogens(Springer Nature, 2017-02-15) Chopyk, Jessica; Chattopadhyay, Suhana; Kulkarni, Prachi; Claye, Emma; Babik, Kelsey R.; Reid, Molly C.; Smyth, Eoghan M.; Hittle, Lauren E.; Paulson, Joseph N.; Cruz-Cano, Raul; Pop, Mihai; Buehler, Stephanie S.; Clark, Pamela I.; Sapkota, Amy R.; Mongodin, Emmanuel F.There is a paucity of data regarding the microbial constituents of tobacco products and their impacts on public health. Moreover, there has been no comparative characterization performed on the bacterial microbiota associated with the addition of menthol, an additive that has been used by tobacco manufacturers for nearly a century. To address this knowledge gap, we conducted bacterial community profiling on tobacco from user- and custom-mentholated/non-mentholated cigarette pairs, as well as a commercially-mentholated product. Total genomic DNA was extracted using a multi-step enzymatic and mechanical lysis protocol followed by PCR amplification of the V3-V4 hypervariable regions of the 16S rRNA gene from five cigarette products (18 cigarettes per product for a total of 90 samples): Camel Crush, user-mentholated Camel Crush, Camel Kings, custom-mentholated Camel Kings, and Newport Menthols. Sequencing was performed on the Illumina MiSeq platform and sequences were processed using the Quantitative Insights Into Microbial Ecology (QIIME) software package. In all products, Pseudomonas was the most abundant genera and included Pseudomonas oryzihabitans and Pseudomonas putida, regardless of mentholation status. However, further comparative analysis of the five products revealed significant differences in the bacterial compositions across products. Bacterial community richness was higher among non-mentholated products compared to those that were mentholated, particularly those that were custom-mentholated. In addition, mentholation appeared to be correlated with a reduction in potential human bacterial pathogens and an increase in bacterial species resistant to harsh environmental conditions. Taken together, these data provide preliminary evidence that the mentholation of commercially available cigarettes can impact the bacterial community of these products.Item Logic minimization and rule extraction for identification of functional sites in molecular sequences(2012-08-16) Cruz-Cano, Raul; Lee, Mei-Ling Ting; Leung, Ming-YingBackground Logic minimization is the application of algebraic axioms to a binary dataset with the purpose of reducing the number of digital variables and/or rules needed to express it. Although logic minimization techniques have been applied to bioinformatics datasets before, they have not been used in classification and rule discovery problems. In this paper, we propose a method based on logic minimization to extract predictive rules for two bioinformatics problems involving the identification of functional sites in molecular sequences: transcription factor binding sites (TFBS) in DNA and O-glycosylation sites in proteins. TFBS are important in various developmental processes and glycosylation is a posttranslational modification critical to protein functions. Methods In the present study, we first transformed the original biological dataset into a suitable binary form. Logic minimization was then applied to generate sets of simple rules to describe the transformed dataset. These rules were used to predict TFBS and O-glycosylation sites. The TFBS dataset is obtained from the TRANSFAC database, while the glycosylation dataset was compiled using information from OGLYCBASE and the Swiss-Prot Database. We performed the same predictions using two standard classification techniques, Artificial Neural Networks (ANN) and Support Vector Machines (SVM), and used their sensitivities and positive predictive values as benchmarks for the performance of our proposed algorithm. SVM were also used to reduce the number of variables included in the logic minimization approach. Results For both TFBS and O-glycosylation sites, the prediction performance of the proposed logic minimization method was generally comparable and, in some cases, superior to the standard ANN and SVM classification methods with the advantage of providing intelligible rules to describe the datasets. In TFBS prediction, logic minimization produced a very small set of simple rules. In glycosylation site prediction, the rules produced were also interpretable and the most popular rules generated appeared to correlate well with recently reported hydrophilic/hydrophobic enhancement values of amino acids around possible O-glycosylation sites. Experiments with Self-Organizing Neural Networks corroborate the practical worth of the logic minimization method for these case studies. Conclusions The proposed logic minimization algorithm provides sets of rules that can be used to predict TFBS and O-glycosylation sites with sensitivity and positive predictive value comparable to those from ANN and SVM. Moreover, the logic minimization method has the additional capability of generating interpretable rules that allow biological scientists to correlate the predictions with other experimental results and to form new hypotheses for further investigation. Additional experiments with alternative rule-extraction techniques demonstrate that the logic minimization method is able to produce accurate rules from datasets with large numbers of variables and limited numbers of positive examples.