Richard M. Fairbanks School of Public Health Theses and Dissertations

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Mineral Intake, Dietary Quality, and Body Adiposity in Relation to Pancreatic Cancer Risk in the Prostate, Lung, Colorectal, and Ovarian Cancer Screening Trial
(2022-08) Hoyt, Margaret Leeann; Zhang, Jianjun; Song, Yiqing; Gao, Sujuan; O'Palka, Jacquelynn
Pancreatic cancer is the third leading cause of cancer-related deaths and is projected to rank second by 2030 in the United States. However, the etiology of this malignancy remains elusive, with family history, chronic pancreatitis, type 2 diabetes, and cigarette smoking as only established risk factors. Therefore, it is urgent and important to identify risk factors, especially modifiable ones (e.g. diet), for the primary prevention of this lethal disease. In this dissertation, we have investigated the associations of mineral intake, dietary quality, and body adiposity with the risk of pancreatic cancer among participants in the Prostate, Lung, Colorectal, and Ovarian Cancer (PLCO) Screening Trial. Calcium, magnesium, and phosphorus are essential minerals that modulate energy metabolism and glucose homeostasis and may thus be involved in pancreatic carcinogenesis. In the first manuscript, we found that total calcium intake was associated with a reduced risk of pancreatic cancer. In addition, a significant linear inverse association was observed for total magnesium intake. The Healthy Eating Index, 2015 (HEI-2015) and the Dietary Quality Index- revised (DQI-R) have been developed to assess the overall quality or patterns of diet. In the second manuscript, we did not find significant associations between HEI-2015 or DQI-R scores and pancreatic cancer risk. However, a higher intake of some score components (i.e., calcium, vegetables, and whole grains) conferred a lower risk. Although mounting biological mechanisms have linked overweight and obesity to the development of pancreatic cancer, it is largely unclear whether prediagnostic body mass index (BMI) trajectory is associated with the risk of this disease. In the third manuscript, we revealed that prediagnostic adulthood BMI trajectory was not associated with pancreatic cancer risk, but a suggestively or significantly increased risk were identified for individuals who were overweight at age 20 or obese at age 50, compared with those who had a normal weight at the two respective time points. Taken together, the findings of research presented in this dissertation contribute to an improved understanding of the crucial roles of diet and adiposity in the etiology of pancreatic cancer, which may offer some new avenues for the prevention of this intractable malignancy.
The Effects of Healthcare Service Disruptions on the Community, Healthcare Services and Access to Care
(2022-08) Mills, Carol Ann; Blackburn, Justin; Holmes, Ann M.; Unroe, Kathleen; Yeager, Valerie A.
Access to healthcare services is important for improving health outcomes, preventing and managing illness, and achieving health equity. The geographic maldistribution of physicians has a negative impact on rural areas compared to urban, particularly as it relates to access to healthcare. Rural hospitals have been closing or converting to another form of healthcare service at an increasing rate, adding another element to the existing complexities in rural access to care. Although a hospital closure in any location may have a considerable impact on the community, the closure of a rural hospital may have disproportionately more substantial implications for the economy and employment, health outcomes, and access to care. The contributing factors preceding rural hospital closures have been studied, but less is known about the full impact of rural hospital closures on the community. There is some evidence of shortages in healthcare providers and services, and therefore communities may employ multiple strategies to mitigate the shortages and provide services, including utilizing telehealth/virtual services. This dissertation proposes to examine the effects of rural hospital closures on the community, healthcare services, access to care, and provide a qualitative assessment of telehealth as a strategy to bridge gaps in provider access. This dissertation includes three studies: 1) a systematic review of the literature to examine the impact of rural hospital closures on the community; 2) an empirical study that utilizes a generalized difference in difference design with county and year fixed effects to estimate the relationship between rural hospital closures and nursing homes; and 3) a qualitative study exploring the perceptions and experiences of the nurses that piloted a virtual care support project, providing insights into crucial elements important to the implementation of similar models and the role of telehealth in bridging healthcare workforce gaps.
Electronic Health Record (EHR) Data Quality and Type 2 Diabetes Mellitus Care
(2022-06) Wiley, Kevin Keith, Jr.; Vest, Joshua; Blackburn, Justin; De Groot, Mary; Menachemi, Nir; Mendonca, Eneida
Due to frequent utilization, high costs, high prevalence, and negative health outcomes, the care of patients managing type 2 diabetes mellitus (T2DM) remains an important focus for providers, payers, and policymakers. The challenges of care delivery, including care fragmentation, reliance on patient self-management behaviors, adherence to care management plans, and frequent medical visits are well-documented in the literature. T2DM management produces numerous clinical data points in the electronic health record (EHR) including laboratory test values and self-reported behaviors. Recency or absence of these data may limit providers’ ability to make effective treatment decisions for care management. Increasingly, the context in which these data are being generated is changing. Specifically, telehealth usage is increasing. Adoption and use of telehealth for outpatient care is part of a broader trend to provide care at-a-distance, which was further accelerated by the COVID-19 pandemic. Despite unknown implications for patients managing T2DM, providers are increasingly using telehealth tools to complement traditional disease management programs and have adapted documentation practices for virtual care settings. Evidence suggests the quality of data documented during telehealth visits differs from that which is documented during traditional in-person visits. EHR data of differential quality could have cascading negative effects on patient healthcare outcomes. The purpose of this dissertation is to examine whether and to what extent levels of EHR data quality are associated with healthcare outcomes and if EHR data quality is improved by using health information technologies. This dissertation includes three studies: 1) a cross-sectional analysis that quantifies the extent to which EHR data are timely, complete, and uniform among patients managing T2DM with and without a history of telehealth use; 2) a panel analysis to examine associations between primary care laboratory test ages (timeliness) and subsequent inpatient hospitalizations and emergency department admissions; and 3) a panel analysis to examine associations between patient portal use and EHR data timeliness.
Systematic Exploration of Associations Between Select Neural and Dermal Diseases in a Large Healthcare Database
(2022-03) Kirbiyik, Uzay; Dixon, Brian E.; Nan, Hongmei; Grannis, Shaun J.; Janga, Sarath Chandra; Zou, Jian
In the age of big data, better use of large, real-world datasets is needed, especially ultra-large databases that leverage health information exchange (HIE) systems to gather data from multiple sources. Promising as this process is, there have been challenges analyzing big data in healthcare due to big data attributes, mainly regarding volume, variety, and velocity. Thus, these health data require not only computational approaches but also context-based controls.In this research, we systematically examined associations among select neural and dermal conditions in an ultra-large healthcare database derived from an HIE, in which computational approaches with epidemiological measures were used. After a systematic cleaning, a binary logistic model-based methodology was used to search for associations, controlling for race and gender. Age groups were chosen using an algorithm to find the highest incidence rates for each condition pair. A binomial test was conducted to check for significant temporal direction among conditions to infer cause and effect. Gene-disease association data were used to evaluate the association among the conditions and assess the shared genetic background. The results were adjusted for multiple testing, and network graphs of significant associations were created. Findings among methodologies were compared to each other and with prior studies in the literature. In the results, seemingly distant neural and dermal conditions had an extensive number of associations. Controlling for race and gender tightened these associations, especially for racial factors affecting dermal conditions, like melanoma, and gender differences on conditions like migraine. Temporal and gene associations helped explain some of the results, but not all. Network visualizations summarized results, highlighting central conditions and stronger associations. Healthcare data are confounded by many factors that hide associations of interest. Triangulating associations with separate analyses helped with the interpretation of results. There are still numerous confounders in these data that bias associations. Aside from what is known, our approach with limited variables may inform hypothesis generation. Using additional variables with controlled-computational methods that require minimal external input may provide results that can guide healthcare, health policy, and further research.
Epidemiological Analysis of SARS-CoV-2: Three Papers Examining Health Status, Response Bias, and Strategies for Engagment
(2022-02) Duszynski, Thomas J.; Wessel, Jennifer; Dixon, Brian E.; Li, Xin; Menachemi, Nir
The emergence of the global SARS-CoV-2 pandemic created tremendous impact on humanity beginning in late 2019. Public health researchers at Indiana University Richard M. Fairbanks School of Public Health responded by conducting research into the etiological profile of the virus, including a large Indiana state-wide population-based prevalence study in early 2020. Methods Data on demographics, tobacco use, health status, and reasons for participating in the population prevalence study were used to conduct three retrospective cross-sectional studies. The first study assessed the association of self-reported health and tobacco behaviors with COVID-19 infection (n=8,241). The second study used successive wave analysis to assess nonresponse bias (n=3,658). Finally, participants demographics were characterized by who responded to text, email, phone calls, or postcards and by the number of prompts needed to elicit participation (n= 3,658). Results The first study found self-identified health status of those reporting “poor, “fair” or good” had a higher risk of past or current infections compared to “very good” or “excellent” health status (P <0.02). Positive smoking status was inversely associated with SARS-CoV-2 infection (p <0.001). When assessing the sample for non-response bias (n=3,658), 40.9% responded in wave 1 of recruitment, 34.1% in wave 2 and 25.0% in wave 3 for an overall participation rate of 23.6%. There were no significant differences in response by waves and demographics, being recently exposed or reasons for participating. In the final study, compared to males, females made up 54.6% of the sample and responded at a higher rate to postcards (8.2% vs. 7.5%) and text/emails (28.1 vs. 24.6%, 2= 7.43, p 0.025); and responded at a higher percentage after 1 contact (21.4 vs. 17.9%, 2 = 7.6, p 0.023). Conclusion This research contributed to the scientific understanding of the etiological picture of SARS-CoV-2. Additionally, the current study used a novel method that public health practitioners can easily implement to detect non-response bias in primary data collection without advanced statistical methods. Finally, the current study allows researchers to focus not only on the modality of inviting participants, but the frequency of invitations needed to secure specific populations, reducing time and resources.
Measurements of Rurality and Their Effect on Mental Illness and Substance Use
(2021-12) Danek, Robin Lynn; Menachemi, Nir; Blackburn, Justin; Greene, Marion; Mazurenko, Olena
According to the US government, nearly 1 in 5 Americans live in rural areas. In general, rural Americans have poor health outcomes, including higher rates of chronic disease, mental illness and certain types of substance use. A variety of different methods are used to assess rurality in health services research, making it challenging to precisely quantify the prevalence of mental illness and substance use in this population, as well as compare study conclusions. As policymakers become increasingly interested in addressing health disparities between urban and rural populations, it is important to assess and evaluate the different methods used to define rurality itself and determine how those methods affect estimates of depression and substance use, so that true disparities can be accurately captured and addressed. This dissertation will identify current definitions and methods used to measure rurality among published studies and then employ various identified methods to quantify the effect of measurement choice on prevalence of mental illness and substance use in rural populations. The dissertation will follow a three publishable paper model that will include a literature review and two empirical studies using secondary data as described below. For Paper 1, I identify peer-reviewed studies from HSR journals that use any method to measure rurality in their analysis. I analyze whether geographic units and methods used to classify rurality differ by focus area including costs, quality, and access to care. For paper 2, I quantify the impact of different measurements of rurality have on estimates for hospitalizations for depression and substance use. Using 5 different measurements of rurality, I calculate the levels of agreement as well as examine how characteristics of patients with depression or substance use disorder differ based on the definition of rurality used. In paper 3, I examine differences in the relationship between unmet mental health need and subsequent drug use in individuals with a history of depression. Using the National Survey on Drug Use and Health and a pooled crosssectional study design, I examine drug use by alcohol, marijuana, and prescription opioid use. Additionally, I compare self-medication and substance use in individuals by geographic location.
Factors and Outcomes Associated with Dental Care Use Among Medicaid-Enrolled Adults
(2021-12) Taylor, Heather Lynn; Blackburn, Justin; Menachemi, Nir; Holmes, Ann; Schleyer, Titus; Sen, Bisakha
Poor oral health is associated with pain, decreased chewing function, negative social perceptions, and reduced quality of life. Low-income adults disproportionally have worse oral health and use dental services at lower rates than higher-income adults. This disparity is associated with individual demographic and socioeconomic factors, cost and coverage barriers, as well as the supply and location of dental providers. Although the full causal pathway remains elusive, evidence suggests an association with poor oral health and an exacerbation of chronic diseases symptoms. Thus, adequate provision of dental care has important population health implications. Despite this importance, dental care use among low-income adults is particularly underexplored. Furthermore, existing research lacks robust methodological designs to mitigate bias from unobserved confounders. Dental coverage for low-income adults through Medicaid is emerging as a way to provide services to this population. However, given state budget constraints, comprehensive public dental benefits are uncommon or at risk of being cut. Therefore, it is important to quantify the individual and economic value of dental care use among adult Medicaid enrollees. This dissertation examines factors and outcomes associated with dental care use among Medicaid-enrolled adults in Indiana. This dissertation includes three studies 1) a pooled cross-sectional analysis that measures the association of individual and community level factors with dental care use, 2) a repeated measures study with individual fixed effects to examine whether receipt of preventive dental care is associated with fewer subsequent non-preventive dental visits and lower total annual dental expenditures, and 3) an empirical study that utilizes an instrumental variable estimation method to examine the effect of preventive dental visits on medical and pharmacy expenditures. Overall, this dissertation attempts to understand the correlates of dental care use, the effectiveness of preventive dental care, and the association between preventive dental care and medical expenditures.
Utilization Patterns of Lymph Node Dissection in Endometrial Cancer Patients Without Distant Metastasis in the United States
(2021-06) Alyea, Jennifer Marie; Dixon, Brian E.; Song, Yiqing; Zhang, Jianjun; Hess, Lisa M.; Method, Michael W.
Endometrial cancer is the most common gynecologic cancer in the United States, and patients with early-stage endometrioid adenocarcinoma have a favorable prognosis. Over the past decade, the gynecologic oncology community has debated whether potential harms of systematic lymph node dissection (LND) outweigh potential benefits for these patients. To minimize number of nodes removed, sentinel lymph node dissection (SLND) is under investigation as an alternative. However, ongoing uncertainty of LND/SLND best practices may result in variations in disease management and discrepant outcomes. Methods Three retrospective cohort studies examined LND/SLND use in patients with endometrioid adenocarcinoma. Two examined temporal and geographic variations, respectively, utilizing the Surveillance, Epidemiology, and End Results (SEER) 18 dataset for the years 2004 through 2015. The third used the SEER-Medicare dataset from 2003 through 2016 to quantify and compare the risk of developing 6-month post-surgical lymphedema, lymphocele, hemorrhage, ileus, infection, thrombosis, and all-cause death by number of lymph nodes removed (0, 1-4, 5-9, or 10+). Results Time trend analyses found LND increased from 2004 through 2008, followed by a significant decline through 2015. SLND was rare and did not increase significantly. Significant geographic variation existed for LND use but not SLND. Per 1,000 patients, analyses of 6-month post-surgical complications found 6.5 experienced lymphedema, 3.9 experienced lymphocele, 15.7 experienced hemorrhage, 28.7 experienced ileus, 37.1 experienced infection, 18.6 experienced thrombosis, and 19.8 died. Controlling for size of primary tumor, tumor grade, comorbidities, race/ethnicity, age at diagnosis, adjuvant chemotherapy, and radiotherapy, adjusted hazard ratios (HRs) and 95% confidence intervals (CIs) showed greater risk for ileus (HR: 1.53; 95% CI: 1.24-1.90), infection (HR: 1.52; 95% CI: 1.25-1.83), and thrombosis (HR: 1.41; 95% CI: 1.09-1.82) when comparing removal of 10+ nodes versus 0 nodes. Conclusion Overall, these studies found significant temporal and geographic variation in LND, as well as increasing risk of post-surgical complications associated with increasing numbers of lymph nodes removed. Should continued research into SLND find strong evidence that it effectively detects cancer spread, patients may benefit through decreased risk of post-surgical ileus, infection, and thrombosis.
The Role of Social Workers in Addressing Patients' Unmet Social Needs in the Primary Care Setting
(2021-04) Bako, Abdulaziz Tijjani; Vest, Joshua R.; Blackburn, Justin; Walter-McCabe, Heather; Kasthurirathne, Suranga; Menachemi, Nir
Unmet social needs pose significant risk to both patients and healthcare organizations by increasing morbidity, mortality, utilization, and costs. Health care delivery organizations are increasingly employing social workers to address social needs, given the growing number of policies mandating them to identify and address their patients’ social needs. However, social workers largely document their activities using unstructured or semi-structured textual descriptions, which may not provide information that is useful for modeling, decision-making, and evaluation. Therefore, without the ability to convert these social work documentations into usable information, the utility of these textual descriptions may be limited. While manual reviews are costly, time-consuming, and require technical skills, text mining algorithms such as natural language processing (NLP) and machine learning (ML) offer cheap and scalable solutions to extracting meaningful information from large text data. Moreover, the ability to extract information on social needs and social work interventions from free-text data within electronic health records (EHR) offers the opportunity to comprehensively evaluate the outcomes specific social work interventions. However, the use of text mining tools to convert these text data into usable information has not been well explored. Furthermore, only few studies sought to comprehensively investigate the outcomes of specific social work interventions in a safety-net population. To investigate the role of social workers in addressing patients’ social needs, this dissertation: 1) utilizes NLP, to extract and categorize the social needs that lead to referral to social workers, and market basket analysis (MBA), to investigate the co-occurrence of these social needs; 2) applies NLP, ML, and deep learning techniques to extract and categorize the interventions instituted by social workers to address patients’ social needs; and 3) measures the effects of receiving a specific social work intervention type on healthcare utilization outcomes.
Health of Indiana Firefighters
(2020-12) Muegge, Carolyn Marie; Song, Yiqing; Zollinger, Terrell W.; Wessel, Jennifer; Monahan, Patrick O.
Background: Firefighters are exposed to carcinogens, toxic agents, and other risks for cancer and cardiovascular disease. Research shows that aero-digestive and genitourinary cancers are in excess among firefighters compared to the general population. Studies examining excess cardiovascular mortality are inconsistent. Limited data exist on chronic disease mortality, risk factor profiles, and barriers to a healthy lifestyle among firefighters at the local level. Purpose: This project examines the relationship between firefighting and chronic disease mortality, determines trajectories of cardiovascular risk factors in a cohort of new firefighters, and studies the relationship between barriers to weight management and firefighter health characteristics. Methods: This study used death certificate data from the Indiana State Department of Health and clinical data from a large occupational medical practice serving firefighters. Regression techniques were used to examine excess mortality among firefighters compared to non-firefighters, evaluate changes in cardiovascular disease risk factors among new firefighters over time, and explore correlates of risk factors and barriers to weight management among overweight and obese firefighters. Results: The odds of death due to malignant cancers were significantly higher among firefighters than non-firefighters (OR, 1.19; 95% CI, 1.08-1.30). Body mass index, total cholesterol, LDL cholesterol, and triglyceride levels increased significantly (p<0.001) while HDL cholesterol levels decreased (p<0.001) from baseline during the first 10 years of the firefighter’s career. Overweight firefighters who were “ready to begin a weight management program” were more likely to identify ‘‘lack of knowledge about weight management,’’ ‘‘lack of access to exercise opportunities,’’ and ‘‘eating helps me cope with stress’’ as barriers, and report a greater number of barriers to weight management. Older firefighters were less likely to identify or report one or more barriers to weight management. Conclusion: These studies suggest the importance of early-career and targeted cardiometabolic health and cancer prevention strategies to reduce chronic disease morbidity and mortality among firefighters.

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