Epidemiology Commons^™

Clostridioides (Clostridium) Difficile In Children And Adolescents In The Community In Cambodia, Lengsea Eng, Paul Turner, Kefyalew Addis Alene, Deirdre A. Collins, Su Chen Lim, Pisey Tan, Sona Soeng, Dylorng Hun, Sotera Yohn, Sarim Vong, Archie C.A. Clements, Thomas V. Riley

Research outputs 2022 to 2026

Background: Clostridioides (Clostridium) difficile transmission between community and healthcare settings has been increasingly reported. We aimed to identify the prevalence and molecular epidemiology of C. difficile colonising adolescents and non-hospitalised children in Cambodia. Methods: Stool samples were collected from 266 students at the University of Health Sciences (UHS) in Phnom Penh, between July and August 2022, and 246 children ≥1 year old visiting the outpatient department (OPD) at Angkor Hospital for Children in Siem Reap, between January and August 2022. C. difficile culture, toxin gene detection and PCR ribotyping were performed. Results: Overall, C. difficile was recovered from 07/266 specimens …

A Simple, Interpretable Machine Learning Model Based On Clinical Factors Accurately Predicts Incident Dysplasia Or Malignancy In Barrett's Esophagus, Ashwin Rao, Jasmine Haydel, Samuel Ma, Aaron P Thrift, Theresa Nguyen-Wenker, Hashem B El-Serag

Faculty, Staff and Students Publications

Purpose: Identifying patients likely to develop dysplasia or malignancy is critical for effective surveillance in patients with Barrett's Esophagus (BE). However, current predictive models are limited. We evaluated the performance of machine learning (ML) models in predicting incident dysplasia or malignancy in a cohort of veteran patients with BE.

Methods: We analyzed data from 598 patients newly diagnosed with non-dysplastic BE (NDBE), BE indefinite for dysplasia (BE-IND), and BE with non-persistent low-grade dysplasia (LGD) at the Michael DeBakey Veterans Affairs Medical Center from November 1990 to January 2019 with follow-up through January 2024. Progressors were patients who developed persistent LGD, …

Noncommunicable Diseases (Hypertension Or Diabetes Mellitus) Among Private University Lecturers And Related Factors, Ummi Kalsum, Melati Puti Andini, Hendra Dhermawan Sitanggang, Helmi Suryani Nasution

Kesmas

Excessive workload, lack of rest, poor diet, stress, and insufficient physical activity are some contributing factors to a high risk of noncommunicable diseases (NCDs) for lecturers. This study aimed to develop a predictive model for the risk of NCDs among lecturers at a private university in Jambi City, Indonesia. A cross-sectional design was used, and the sample included 93 lecturers who met the inclusion criteria. The independent variables were workload, rest pattern, diet, physical activity, stress, smoking, and family history. The dependent variable was NCDs (hypertension or diabetes mellitus), measured through interviews based on a doctor's diagnosis. Data analysis was …

Association Between Sociocultural Factors, Obesity, And Depression In The Hispanic/Latino Population, Maia Junco

Walden Dissertations and Doctoral Studies

The increasing prevalence of obesity and mental health disparities among Hispanic/Latino populations in the United States underscores the need to understand how sociocultural factors shape physical and psychological health. The purpose of this study was to examine how acculturation, diet quality, and fiber intake affect BMI and depressive symptoms over time. The study was guided by acculturation theory and the biopsychosocial model. The study used longitudinal secondary data from the Hispanic Community Health Study/Study of Latinos (HCHS/SOL) with a sample of N=8,816, including adults who completed examination visits, 1 (2008–2011) and 2 (2014–2017). Path analysis was conducted to assess direct …

An Experimental Investigation Of Federal Messaging On Public Support For Enforcement- And Treatment-Based Approaches For Opioid Overdose Prevention In South Carolina, Lídia Gual-Gonzalez, Hunter M. Boehme, Peter Baker, Melissa Nolan Ph.D., Mph

Faculty Publications

Background

As the opioid overdose crisis continues to produce excessive morbidity and mortality in the United States, government agencies have applied various approaches to prevent overdoses, including law-enforcement efforts (e.g., arresting people who use drugs, interrupting drug traffickers, etc.) and treatment-based approaches (e.g., naloxone, medications for opioid use disorder, etc.). Public perception and support of these approaches are relevant for informing policy, allocating resources, and effectively implementing community interventions to prevent drug-related harms.

Methods

Using an embedded informational survey design, we experimentally assessed whether public support for strategies to prevent overdose in South Carolina is influenced by language from federal …

Mediation Analysis To Investigate Differences In Prostate Cancer Diagnosis Stage Through Environmental Risk Factors In Louisiana, Nubaira Rizvi, Randy Hamilton, Xiao-Cheng Wu, Michael D. Celestin, Tung-Sung Tseng, Qingzhao Yu

School of Public Health Faculty Publications

Prostate Cancer (PCa) is the most commonly diagnosed cancer and the second leading cause of cancer death among men. In Louisiana (LA), Black men are disproportionately diagnosed at later stages compared to White men. This study explores environmental risk factors as potential intermediate variables linking race to cancer diagnosis stage. The Louisiana Tumor Registry data included 24,647 male patients diagnosed with PCa in LA between 2010 and 2018. Among them, 15,875 (64.40%) were Caucasian American (CA) and 8772 (35.59%) African American (AA). Mediation analysis using multiple additive regression trees (MART) identified possible intermediate variables that potentially explain the observed disparity. …

Multiscale Modeling And Dynamic Mutational Profiling Of Binding Energetics And Immune Escape For Class I Antibodies With Sars-Cov-2 Spike Protein: Dissecting Mechanisms Of High Resistance To Viral Escape Against Emerging Variants, Mohammed Alshahrani, Vedant Parikh, Brandon Foley, Gennady M. Verkhivker

Mathematics, Physics, and Computer Science Faculty Articles and Research

The rapid evolution of SARS-CoV-2 has underscored the need for a detailed understanding of antibody binding mechanisms to combat immune evasion by emerging variants. In this study, we investigated the interactions between Class I neutralizing antibodies—BD55-1205, BD-604, OMI-42, P5S-1H1, and P5S-2B10—and the receptor-binding domain (RBD) of the SARS-CoV-2 spike protein using multiscale modeling, which combined molecular simulations with the ensemble-based mutational scanning of the binding interfaces and binding free energy computations. A central theme emerging from this work is that the unique binding strength and resilience to immune escape of the BD55-1205 antibody are determined by leveraging a broad epitope …

Infectious Scleritis: A Comprehensive Narrative Review Of Epidemiology, Clinical Characteristics, And Management Strategies, Hamidreza Ghanbari, Masoud Rahimi, Ali Momeni, Kiana Hassanpour, Nikoo Bayan, Karen E. Lee, Alex Hansen, Ali R. Djalilian, Christopher J. Rapuano, Mohammad Soleimani

Wills Eye Hospital Papers

This study aims to provide an update on infectious scleritis (IS). A comprehensive search was conducted using Google Scholar, Scopus, and PubMed. IS is a rare but critical condition that presents significant diagnostic challenges and often leads to poor visual outcomes. It accounts for approximately 5%-10% of scleritis cases and warrants significant attention due to its delayed diagnosis. Ocular surgery is the primary contributor to IS, accounting for a substantial proportion of cases ranging from 58% to 83%, followed by trauma contributing to approximately 10% of cases. IS can be caused by various microorganisms, including bacteria (86%-87%), fungi (11%-13%), viruses, …

Predicting Dietary Behavior In Obese Adult Diabetics Using Social Cognitive Theory, Precious Mueller

Walden Dissertations and Doctoral Studies

Predicting Dietary Behavior in Obese Adult Diabetics Using Social Cognitive Theory by Precious Mueller MA, University of Phoenix, 2009 BS, University of Iowa, 2006 Dissertation Submitted in Partial Fulfillment of the Requirements for the Degree of Doctor of Philosophy Public Health Walden University November 2024 “ Diabetes mellitus Type II is a prevalent and serious condition affecting millions globally, particularly among obese adults. The association between dietary behaviors and diabetes management is critical, as it directly impacts health outcomes and quality of life for affected individuals. This study aims to identify the determinants of dietary behaviors that influence Type II …

A Cancer Education Needs Assessment: Informing Middle-Aged Female Patients About The Relationships Between Obesity And Women’S Health Concerns In The Reproductive System, Breast, And Endometrial Health, Batul Mirza

MUSC Theses and Dissertations

Obesity significantly impacts women’s health, particularly among middle-aged women, by increasing the risk of hormone-sensitive cancers such as breast, endometrial, and reproductive system cancers. This study examines the educational needs of this demographic group regarding obesity-related cancer risks and explores effective intervention strategies. Obesity-induced mechanisms – hormonal imbalances, chronic inflammation, and insulin resistance – drive cancer susceptibility, emphasizing the need for targeted health education. The study employs a qualitative design, which includes interviews with subject matter experts (SMEs) and surveys of middle-aged women. The goal is to assess awareness, perceived barriers, and preferred learning methods. Findings suggest that with many …

Predicting Sleep And Sleep Stage In Children Using Actigraphy And Heartrate Via A Long Short-Term Memory Deep Learning Algorithm: A Performance Evaluation, Robert Weaver Med, Phd, James White, Olivia Finnegan, Hongpeng Yang, Zifei Zhong, Keagan Kiely, Catherine Jones, Yan Tong, Srihari Nelakuditi, Rahul Ghosal, David E. Brown, Russell R. Pate Ph.D., Gregory J. Welk, Massimiliano De Zambotti, Yuan Wang, Sarah Burkart, Elizabeth L. Adams Phd, Bridget Armstrong, Michael Beets Med, Mph, Phd

Faculty Publications

Children's ambulatory sleep is commonly measured via actigraphy. However, traditional actigraphy measured sleep (e.g., Sadeh algorithm) struggles to predict wake (i.e., specificity, values typically < 70) and cannot predict sleep stages. Long short-term memory (LSTM) is a machine learning algorithm that may address these deficiencies. This study evaluated the agreement of LSTM sleep estimates from actigraphy and heartrate (HR) data with polysomnography (PSG). Children (N = 238, 5–12 years,52.8% male, 50% Black 31.9% White) participated in an overnight laboratory polysomnography. Participants were referred be-cause of suspected sleep disruptions. Children wore an ActiGraph GT9X accelerometer and two of three consumer wearables(i.e., Apple Watch Series 7, Fitbit Sense, Garmin Vivoactive 4) on their non-dominant wrist during the polysomnogram. LSTM estimated sleep versus wake and sleep stage (wake, not-REM, REM) using raw actigraphy and HR data for each 30-s epoch. Logistic regression and random forest were also estimated as a benchmark for performance with which to compare the LSTM results. A 10-fold cross-validation technique was employed, and confusion matrices were constructed. Sensitivity and specificity were calculated to assess the agreement between research-grade and consumer wearables with the criterion polysomnography. For sleep versus wake classification, LSTM outperformed logistic regression and random forest with accuracy ranging from 94.1to 95.1, sensitivity ranging from 94.9 to 95.9 across different devices, and specificity ranging from 84.5 to 89.6. The addition of HR improved the prediction of sleep stages but not binary sleep versus wake. LSTM is promising for predicting sleep and sleep staging from actigraphy data, and HR may improve sleep stage prediction.

Analyzing Environmental Health: Air Pollution And Human Health Using Geospatial Data Science, Yanhong Huang

Geography ETDs

Air pollution from industrial emissions and wildfire smoke poses growing threats to public health. This dissertation employs geospatial data science to examine these challenges through three interrelated studies. The first study investigates the relationship between maternal residential exposure to industrial pollutants and low birth weight, identifying five chemicals as significant risk factors. The second study assesses the impact of industrial air pollution on lung and bronchus cancer survival, finding that exposure to 1,1,1-trichloroethane and cobalt is associated with reduced survival. The third study explores disparities in wildfire smoke PM_2.5 exposure and its association with asthma exacerbations. Results show disparities …

Spatial Proximity Of Immune Cell Pairs To Cancer Cells In The Tumor Microenvironment As Biomarkers For Patient Stratification, Jian-Rong Li, Xingxin Pan, Yupei Lin, Yanding Zhao, Yanhong Liu, Yong Li, Christopher I Amos, Chao Cheng

Faculty, Staff and Students Publications

Background/objectives: The tumor microenvironment (TME) plays a critical role in cancer progression by shaping immune responses and influencing patient outcomes. We hypothesized that the relative proximity of specific immune cell pairs to cancer cells within the TME could help predict their pro- or anti-tumor functions and reflect clinically relevant immune dynamics.

Methods: We analyzed imaging mass cytometry (IMC) data from lung adenocarcinoma (LUAD) and triple-negative breast cancer (TNBC) cohorts. For each immune cell pair, we calculated a relative distance (RD) score, which quantifies the spatial difference in proximity to cancer cells. We assessed the prognostic and predictive significance of these …

The Need For Targeted Prevention And Screening In Gastrointestinal Cancer Disparities, Jason C. Lin, John C. Lin, Joy Zhao

Division of Gastroenterology and Hepatology Faculty Papers

No abstract provided.

Cannabis And Covid: An Interrupted Time Series Analysis Of Their Impact On Mental Health-Related Hospital Visits In Rural Arizona (2016-2023), Jennifer Megan Suter

Walden Dissertations and Doctoral Studies

Arizona’s rural communities face shortages in mental health care services. In 2020, the nearly simultaneous onset of the COVID-19 pandemic and the legalization of recreational cannabis introduced overlapping public health stressors that may have disproportionately affected these vulnerable populations. However, their combined impact on rural mental health remains understudied. This three-manuscript dissertation employed interrupted time series analyses to assess how these events influenced monthly hospital visits for schizophrenia, psychosis, cannabis-induced psychosis, and suicidal behaviors among rural Arizona adults aged 21 and older. A total of 16,468 records from the Arizona State Inpatient and Emergency Department Databases (SID and SEDD) met …

Latent Tuberculosis Infection Treatment Adherence Among Black/African American People Living In Houston, Texas, Napoleon Ayibo Wokoma

Walden Dissertations and Doctoral Studies

Early detection and treatment of latent tuberculosis infection (LTBI) is crucial in preventing active TB and supporting elimination efforts. However, adherence to LTBI treatment is challenging, especially among racial and ethnic minorities, with Black/African Americans showing particularly low rates. A quantitative retrospective chart review was conducted to examine sociodemographic factors affecting LTBI adherence in Black/African American individuals and to evaluate various adherence strategies. Using the health belief model, 435 deidentified secondary data records were analyzed from the Houston Health Department from 2012 to 2022, covering both native and foreign-born Black/African American patients undergoing LTBI treatment. Descriptive and inferential statistics, including …

Exploring Sex-Specific Clinical Features In Chinese Patients With Takotsubo Syndrome, Hong-Yi Duan, Ling-Lin Wang, Ling-Chun Lyu, Zhen-Hua Shi, Xiao-Ping Lin, Zheng-Yang Yu, Guo-Hua Fan, Jing Chen, Xin-Hong Yang, Wei Deng, Chang-Wu Xu, Yan Huang, Qing Zhou, Jin-Ling Chen, Hong-Ning Song, Dong Hu, Jin-Qiu Liu, Hector Barajas-Martinez, Charles Antzelevitch, Kan Liu, Hong Jiang, Dan Hu

Department of Medicine Faculty Papers

BACKGROUND: Takotsubo syndrome (TTS) is considered as a transient acute heart failure syndrome predominant in females. However, data on Chinese TTS patients are limited. Therefore, this study aimed to investigate the clinical characteristics of Chinese TTS patients, identify prognostic markers.

METHODS: A total of 258 TTS patients were enrolled. Data on clinical characteristics and in-hospital major adverse cardiovascular events (MACE) were collected and analyzed. The latter included severe heart failure, shock, malignant arrhythmia, and death.

RESULTS: The average age of TTS patients was 59.3 ± 19.2 years. Female patients accounted for 68.9%. MACE occurred in 41.4% of patients during hospitalization. …

Modeling, Analysis, And Prediction Of Covid-19 Dynamics With Interacting Subpopulations And Implicit Behavior Using Physics-Informed Neural Networks, Naima Aubry-Romero, Alonso Ogueda-Oliva, Padmanabhan Seshaiyer

Spora: A Journal of Biomathematics

In this paper, we consider an extended SEIR compartmental model that incorporates young and old interacting subpopulations, allowing for cross-group transmission dynamics. Implicit behavioral changes are included to determine the influence of social behavior on coronavirus transmission dynamics. The basic reproduction number, the average number of secondary cases of infection produced by a single primary case, is derived for both the explicit and implicit model using the next-generation matrix method. We solve the associated differential equation systems and estimate useful parameters in the explicit model using physics-informed neural networks (PINNs). Our results point to how the PINNs approach offers an …

Evaluating Nutrition, Exercise, And Education, On Mental Health And Quality Of Life In Menopause, Jill R. Stone

Walden Dissertations and Doctoral Studies

Physical inactivity, poor nutrition, and a lack of understanding of menopause adversely affect mental health and quality of life in women entering menopause. Metabolic changes during this period can lead to an increase in visceral fat, loss of muscle mass, depression, and anxiety. These metabolic changes are linked to a higher risk for cardiovascular disease, type two diabetes, and metabolic syndrome. This cross-sectional quantitative study, guided by the health belief model, explored the contribution of adopting specific nutrition strategies, exercise, and education in women during menopause transition to help manage mental health (as measured by depression and tension), and quality …

Vitamin D Status And Risk For Breast Cancer In Kenya, Ronald Wasike, Victor Mobegi, Esther Maina, Francis Makokha, Robert Armstrong, Annastacia Mbithi

General Surgery, East Africa

Background: Vitamin D plays a critical role in bone metabolism, calcium regulation, and various cellular processes, including those linked to cancer. The biologically active form, 1,25-dihydroxyvitamin D [1,25(OH)2D], works through the Vitamin D Receptor (VDR). Polymorphisms in VDR and related genes have been associated with cancer risk, including breast cancer. This case-control study aimed to investigate the relationship between serum vitamin D levels and breast cancer among Kenyan women.

Methods: Serum 25-hydroxyvitamin D [25(OH)D] levels were measured in 112 breast cancer patients and 106 controls using electrochemiluminescence.

Results: Results indicated that 81.2% of participants had deficient or insufficient vitamin D …