Biostatistics Commons^™

Circulating Levels Of Insulin-Like Growth Factor I (Igf-I) And Risk Ofmultiple Myeloma: An Observational And Mendelian Randomisation Study, Yolanda Benavente, Sara Hermosa, Nikos Papadimitriou, Alyssa I. Clay-Gilmour Ph.D., Elizabeth E. Brown, Jonathan N. Hofmann, Nathaniel Rothman, Qing Lan, Sonja I. Berndt, Demetrius Albanes, Mark Purdue, Mitchell J. Machiela, Stephen J. Chanock, Parveen Bhatti, Wendy Cozen, Aaron Norman, Susan L. Slager, James R. Cerhan, Vincent Rajkumar, Shaji J. Kumar, Et. Al.

Faculty Publications

Evidence for an association between insulin-like growth factors (IGF) and multiple myeloma (MM) is inconsistent. We examined total IGF-I concentrations and risk of MM by combining baseline serological data among UK Biobank participants (n = 444 187; 732 incident MM) with a two-sample Mendelian randomisation (MR) analysis using identified genetic variants associated with circulating total IGF-I and IGF-binding protein 3 (IGFBP-3) in the InterLymph consortium (2434 MM and their 2567 controls). Finally, additional lymphoid neoplasm (LN) subtypes were included for comparison with the main hypothesis. Circulating IGF-I level was positively associated with MM risk Hazard ratio-HR-per one standard deviation-SD-increase …

Adverse Childhood Experiences, Positive Childhood Experiences, And Digital Media Use Among Children And Adolescents In The United States, Elizabeth L. Crouch, Emma Boswell, Monique J. Brown Ph.D., Kevin J. Bennett

Publications

No abstract provided.

Home-Based Digital Technologies To Support Aging-In-Place For Rural African American People With Alzheimer Disease And Their Care Partners: Protocol For A Mixed Methods Feasibility Study, Otis Owens, Rahul Ghosal Ph.D., Zachary Beattie, Jeffrey Kaye, Jiajia Zhang Ph.D., Nora Mattek, Joel Steele, Thomas Riley, Nicole Sharma, Larry Frye, Leonardo Bonilha, Sue E. Levkoff Scd, Msw, Sm

Faculty Publications

Background:

Rural, low-income African American people have the highest Alzheimer disease and related dementia (ADRD) incidence and prevalence rates but have the least access to formal dementia care. To support individuals living with ADRD, growing evidence suggests that remote monitoring technologies can augment existing care by facilitating the completion of activities of daily living (ADLs) and maintaining communication between individuals living with ADRD and their care partners. Despite the success of remote technologies, no studies have investigated the usability, acceptability, and feasibility of these technologies among rural, lower-income African American people living with ADRD and their care partners. Understanding the …

Smarter Disease Detection From Electronic Health Record Data: An End-To-End Ai-Augmented Pipeline For Computable Phenotyping, Dylan Owens

Statistical Science Theses and Dissertations

Electronic Health Records (EHR) contain a wealth of structured and unstructured patient data that can be leveraged for computable phenotyping, the process of algorithmically identifying patient cohorts with specific diseases or conditions. Traditional rule-based phenotyping approaches, while interpretable, often struggle with scalability, portability across institutions, and effective use of unstructured clinical narratives. Recent advances in large language models (LLMs) present new opportunities for synthesizing complex free-text information into concise, clinically meaningful representations. However, integrating LLMs into phenotyping workflows requires careful design to maintain transparency, interpretability, and measurable uncertainty—features essential for clinical adoption and downstream applications such as decision support.

We …

Spatiotemporal Modeling Of Maternal Mortality In South Carolina 2018-2023, Leah Wood, Ray Bai, Emily Mann

Senior Theses

Maternal death serves as a public health indicator due to fact that it is considered preventable with the availability of modern biomedicine, however, it persists broadly throughout the United States. Current literature outlines national trends in maternal mortality with complicating, preexisting conditions, and structural upstream factors often cited as being the largest contributors to increased risk. This study utilizes publicly available, county-level data for maternal death in addition to demographic and descriptive data in order to estimate maternal mortality rates in each of South Carolina’s 46 counties from 2018 to 2023. In order to address sparsity in the outcome variable …

Glucodensity Functional Profiles Outperform Traditional Continuous Glucose Monitoring Metrics, Marcos Matabuena, Rahul Ghosal Ph.D., Javier Enrique Aguilar, Ayya Keshet, Robert Wagner, Carmen Fernández Merino, Juan Sánchez Castro, Vadim Zipunnikov, Jukka-Pekka Onnela, Francisco Gude

Faculty Publications

Continuous glucose monitoring (CGM) data have revolutionized the management of type 1 diabetes, particularly when integrated with insulin pumps to mitigate clinical events such as hypoglycemia. Recently, there has been growing interest in utilizing CGM devices in clinical studies involving healthy and diabetic populations. However, efficiently exploiting the high temporal resolution of CGM profiles remains a significant challenge. Numerous indices—such as time–in–range metrics and glucose variability measures–have been proposed, but evidence suggests these metrics overlook critical aspects of dynamic glucose homeostasis. As an alternative method, this paper explores the clinical value of glucodensity metrics in capturing glucose dynamics—specifically the speed …

Heuristic Weight Initialization For Transfer Learning In Classification Problems, Musulmon Lolaev, Anand Paul, Jeonghong Kim

School of Public Health Faculty Publications

Transfer learning is the predominant method for adapting pre-trained models on another task to new domains while preserving their internal architectures and augmenting them with requisite layers in Deep Neural Network models. Training intricate pre-trained models on a sizable dataset requires significant resources to fine-tune hyperparameters carefully. Most existing initialization methods mainly focus on gradient flow-related problems, such as gradient vanishing or exploding, or other existing approaches that require extra models that do not consider our setting, which is more practical. To address these problems, we suggest employing gradient-free heuristic methods to initialize the weights of the final new-added fully …

Effect Of Vitamin D Supplementation During Pregnancy And Lactation On The Development Of Infants Born To Tanzanian Women Living With Hiv: A Secondary Analysis Of A Randomised Controlled Trial, Temiwunmi Shobanke, Alfa Muhihi, Nandita Perumal Phd, Nzovu Ulenga, Fadhlun M. Alwy Al-Beity, Christopher P. Duggan, Wafaie W. Fawzi, Karim P. Manji, Christopher R. Sudfeld

Faculty Publications

Background Infants born to pregnant women living with HIV (WLHIV) are at greater risk for morbidity and mortality and may also have poorer developmental outcomes as compared with infants who are not exposed to HIV. Nutrition interventions in pregnancy may affect developmental outcomes.

Objectives This study evaluated the effect of maternal vitamin D supplementation on infant development outcomes.

Design We conducted a secondary analysis of a randomised, triple-blind, placebo-controlled trial of maternal vitamin D supplementation from June 2015 to October 2019.

Setting Antenatal care clinics in Dar es Salaam, Tanzania.

Participants Pregnant WLHIV and their offspring.

Interventions Daily 3000 IU …

The Inflammatory Potential Of Diet In Adults With Knee Osteoarthritis: Sex-Specific Associations With Quality Of Life, Sleep, Fatigue And Mental Health, Lynette Law, Joshua J. Heerey, Brooke L. Devlin, Peter Brukner, Alysha M. De Livera, James Hébert Scd, Sherry Price, Nathan P. White, Adam G. Culvenor

Faculty Publications

Background:

Knee osteoarthritis (OA) is a disabling condition—characterized by pain, stiffness, and impaired quality of life—that affects more females than males. Chronic systemic inflammation is a key feature of knee OA and can be modulated by diet. We evaluated the sex-specific relationship between the inflammatory potential of diet and health-related quality of life (HRQOL), sleep quality, energy and fatigue levels, and psychological distress in individuals with knee OA.

Methods:

This cross-sectional study analyzed baseline data from 144 participants (64% female) aged 45–85 years with symptomatic knee OA enrolled in the FEAST (eFEct of an Anti-inflammatory diet for knee oSTeoarthritis) randomized …

Bayesian Survival Analysis For High-Dimensional Compositional Data, Zhenying Ding

All ETDs from UAB

Survival analysis integrating microbiome and clinical data offers powerful insights into human health. The microbiome influences immunity, inflammation, and cancer outcomes. Combining microbial profiles with clinical factors like tumor stage, treatment, and demographics enhances understanding of how host-microbe interactions affect survival. To analyze these complex datasets, advanced statistical methods, including Bayesian models, penalized Cox proportional hazards models, and machine learning techniques are employed. These approaches can uncover novel biomarkers and therapeutic targets, leading to personalized treatment strategies that optimize patient survival. However, challenges arise due to the compositionality, high-dimensionality, and phylogenetic relation between taxa in microbiome data. In this dissertation, …

Bayesian Mediation Analyses For Zero-Inflated Data, Jinhong Cui

All ETDs from UAB

Mediation analysis is a fundamental tool in causal inference, enabling researchers to disentangle the pathways through which an exposure affects an outcome via intermediate variables (mediators). It has been widely applied in social sciences, psychology, and healthcare-related studies. Traditionally, mediation analysis has been conducted within the linear structural equation modeling (LSEM) framework. However, recent advances have shifted attention toward the counterfactual framework due to its flexibility in defining causal effects and its capacity to accommodate non-linear relationships, parametric and non-parametric models. Building on this foundation, methodological developments in mediation analysis have expanded to address more complex data structures, such as …

Access To Information On Toddler Family Development Program And Family Participation In Child Growth And Development, Dita Dhammayanti, Demsa Simbolon, Lissa Ervina, Yusran Fauzi

Kesmas

The comprehension of the Toddler Family Development (TFD) Program among families in Indonesia remains limited, likely due to insufficient access to information and low participation rates. Limited participation can negatively affect a family’s ability to support optimal child growth and development. This study examined the relationship between access to information on the TFD Program and family participation in child growth and development. Using secondary data from the 2019 Program Performance and Accountability Survey in Indonesia, the cross-sectional analysis included 21,497 respondents. The results revealed an association between access to information on the TFD Program and family participation in child growth …

Exploring Stunting In South Kalimantan Province Using R Programming-Based Data Visualization, Muhammad Hudaya, Wahyudin Nor, Mellani Yuliastina, Muhammad Nordiansyah

Kesmas

South Kalimantan Province continues to face the challenge of relatively high stunting prevalence despite being endowed with abundant coal resources that could serve as a source of funding for public health. Therefore, this study aimed to examine differences in stunting prevalence among cities, mining districts, and non-mining districts in South Kalimantan to raise stakeholder awareness of disparities across these regional types. This study was conducted between April and December 2024, using secondary data obtained from the Indonesian Ministry of Health and the South Kalimantan Provincial Government. R programming was used to process the data, generate visualizations, and perform analysis of …

Understanding User Needs In Health Crisis Risk Monitoring Information System Development: A Lesson From Tasikmalaya District, Indonesia, Arief Tarmansyah Iman, Hari Kusnanto, Ariani Arista Putri Pertiwi

Kesmas

A health crisis risk monitoring information system needs to be developed, especially during the pre-disaster phase; therefore, understanding the needs of prospective users is crucial. This study aimed to investigate the needs of potential users regarding the development of this system. This study employed a qualitative, exploratory approach to gather user needs from stakeholders through interviews (n = 7) and one focus group discussion (n = 12). The data were audio-recorded, transcribed verbatim, and then thematically analyzed using qualitative content analysis. The need for information was related to disaster preparedness and its preferred format. The system should be targeted, multiplatform, …

Low Economic Level And The Risk Of Overweight Among Indonesian Junior And Senior High School Students, Ariyanto Nugroho, Purwo Setiyo Nugroho, Amarin Yudhana, Sri Sunarti

Kesmas

Overweight and obesity among Indonesian adolescents have emerged as a pressing public health issue, reflecting global trends. This study examines the relationship between economic status and overweight prevalence among junior and senior high school students in Indonesia, using secondary data from the Global School-based Health Survey (GSHS). This study analyzed data from 9,977 students aged 11–18 years through a cross-sectional design and binary logistic regression, adjusting for dietary habits, physical activity, and sedentary behavior. Overall, 14.7% of students were overweight; the prevalence was notably higher among low-income students (27.4%) compared to high-income groups (14.2%). Students from lower economic backgrounds were …

Spatial Patterns In Electronic Health Record Data-Based Predictive Modeling: A Case Study Of Prenatal Care And Preeclampsia, Abigail Lewis

McKelvey School of Engineering Graduate Student Theses & Dissertations

The electronic health record (EHR) documents interactions between patients and healthcare systems and is widely used for secondary research on health outcomes due to broad adoption. While EHR data support efficient clinical informatics research, they are subject to biases stemming from healthcare seeking behavior, health system attributes, and individual or environmental characteristics. Place-based characteristics, in particular, strongly influence when and how patients access care and shape health outcomes. These biases in EHR data can affect predictive modeling pipelines which leverage them, contributing to variation in model performance across groups. In healthcare, where predictive models are increasingly used to guide care, …

Rna’S Symphony: Harmonizing Splice Junctions And Exon Counts For A Novel Approach To Differential Splicing Analysis, Jelard Aquino

UNLV Theses, Dissertations, Professional Papers, and Capstones

Alternative Splicing (AS) plays a critical role in transcriptome complexity and cell-type-specific gene regulation, yet its analysis remains methodologically fragmented, especially in the context of noisy and sparse single-cell RNA sequencing (scRNA-seq) data. This dissertation addresses key computational challenges in AS detection by evaluating existing tools, developing integrative frameworks, and proposing new strategies for improving analysis accuracy in both bulk and single-cell contexts. In chapter 1, I present a comprehensive literature review of computational tools designed for detecting and quantifying AS from bulk and scRNA-seq data. This review outlines major methodological paradigms, including exon-based and splice junction-based approaches, and evaluates …

Empowering Science With The World's First High Accuracy And High Throughput Functional Assay, Christopher Giacoletto

UNLV Theses, Dissertations, Professional Papers, and Capstones

Understanding the functional consequences of genetic mutations remains a central challenge in modern biology, with far-reaching implications for human health and disease. While early systematic methods like alanine scanning and phage display provided foundational insights into protein structure and function, the emergence of high-throughput approaches—such as Multiplexed Assays of Variant Effect (MAVEs)—and predictive tools powered by artificial intelligence have vastly expanded our ability to profile mutational landscapes. However, these methods are often constrained by trade-offs between accuracy, scalability, and biological relevance.This dissertation presents the development and application of the GigaAssay, the world’s first high-throughput functional assay capable of delivering both …

An Evidence-Based Intervention To Increase Trypanosoma Cruzi, A Neglected Parasitic Infection, Diagnosis In Rural And Moderate-Size-City Us Clinics, M K. Lynn, Hunter M. Boehme, Jeffrey Hall, Patrick Kent, Alain H. Litwin, Quang H. Pham, Melissa Nolan Ph.D., Mph, Prisma Chagas Team

Faculty Publications

Background

Chagas disease is a chronic, insidious parasitic infection (Trypanosoma cruzi) that slowly develops to irreversible organomegaly over several decades. The disease is traditionally acquired in endemic Latin American countries during childhood; < 1% of foreign-born adult residents in the United States have been diagnosed or treated with this potentially fatal disease. Low physician knowledge is a primary factor leading to misdiagnosis.

Methods

Starting in April 2022, a 4-part T cruzi clinical education intervention began, which included (i) 2 grand rounds presentations to >100 internal medicine providers; (ii) implementation of a “clinical Chagas champions program” incorporating 14 key clinical staff at varying departments and administrative levels educated on their specific role related to T cruzi screening, diagnosis confirmation, clinical management, and medical billing; ( …

Changes In Mental Health Care Utilisation Before And During The Covid-19 Pandemic Among People Living With Hiv In The Usa: A Retrospective Cohort Study Using The All Of Us Dataset, Atena Pasha, Shan Qiao, Jiajia Zhang Ph.D., Ruilie Cai, Buwei He, Xueying Yang, Chen Liang Ph.D., Sharon Weissman, Xiaoming Li Ph.D.

Faculty Publications

Introduction Despite the profound impact of the COVID-19 pandemic on people living with HIV (PLWH) mental health, large-scale, real-world data on mental healthcare utilisation and associated factors among PLWH remain limited. This study explores mental healthcare utilisation and associated factors among PLWH during the COVID-19 pandemic.

Methods Using a retrospective cohort design, we identified and included 4575 PLWH through computational phenotyping based on relevant Observational Medical Outcomes Partnership Common Data Model concept sets from the All of Us programme between March 2018 and March 2022. Mental healthcare utilisation was measured using the yearly count of mental healthcare visits and compared …