Effect of SDoH on Hypertension and Depressive Symptoms among Older Adults in Ghana- An Insight from the WHO SAGE Surverys
Faculty Mentor: Dr. Prince Amegbor | Graduate Student Mentor: Warsame Mead
Ghana, like many countries in sub-Saharan Africa, has experienced a notable demographic shift towards an aging population in recent decades. Despite traditionally being characterized by a youthful populace, there has been a remarkable increase in the number of older adults within the country over the past forty years. Census data reveal a substantial rise, from approximately 200,000 in 1960 to 1.6 million in 2010. Projections indicate a continued surge, with expectations of reaching 2.4 million by 2030 and a staggering 4.8 million by 2050, constituting about 7.2% of the total population. It is increasingly recognized that social determinants play a pivotal role in shaping the health and well-being of individuals, particularly in aging populations. Existing research highlights a significant prevalence of depressive disorders among older adults globally, with estimates ranging from 1% to 12% for major depressive symptoms and 8% to 16% for clinically significant depressive symptoms. In this project, we will harness data from the World Health Organization (WHO) Study on Global Ageing and Adult Health (SAGE) survey Waves 1 and 2 to delve into the correlation between social determinants of health (SDOH) and age-related health outcomes, specifically focusing on depressive symptoms and hypertension. Our aim is to explore how various social factors intersect with these health outcomes and potentially moderate their associations. By leveraging rigorous quantitative methods, we seek to unravel the intricate interplay between SDOH, depressive symptoms, and hypertension among older adults in Ghana.
PQAR Students: Camryn Dixon, Angelin Hernandez, Annika Venegas
AIRE Lab: Predicting and Responding to an Emerging Syndemic of HIV, TB, and Diabetes in Sub-Saharan Africa
Faculty Mentor: Dr. Mari Armstrong-Hough | Graduate Student Mentor: Katie Parrotte
Type 2 diabetes prevalence is growing in low- and middle-income countries. At the same time, low-resource settings face continuing high burdens of infectious diseases, most notably HIV/AIDS and TB. Diabetes mellitus (DM) is thought to increase the risk of developing active TB more than three-fold and increase the risk of TB treatment failure three- to five-fold. With increasing numbers of people living with diabetes in countries with high TB burden, at elevated risk of developing active disease, TB transmission dynamics may be shifting and new high-risk groups may be emerging. Characterizing the relationships between population aging, diabetes, and TB outcomes in low-income contexts could provide the basis for targeted interventions aimed at those at highest risk of developing and transmitting TB.
The students will carry out a cross-sectional analysis of data from our TB-DM cohort study. The study enrolled 285 patients initiating treatment for TB in Kampala, Uganda. At baseline, the study collected demographic data, social data (including psychosocial variables and measures of food insecurity), clinical data (including history of diabetes, hypertension, hyperlipidemia, and other NCDs), and fingerprick blood samples for random blood glucose and hemoglobin A1c. Uncontrolled diabetes as measured by either blood glucose or A1c is a known risk factor for TB treatment failure. As the population ages in Uganda, more patients are appearing in TB clinics with uncontrolled diabetes. The students will produce statistics describing the study population, examining its age structure, and testing the association of age with hemoglobin A1c. In adjusted analyses, they will examine the patient characteristics associated with higher hemoglobin A1c.
PQAR Students: Gabriel Hawthorne, Princess Isi-Obuseh, Dirk Tolson III
Exploring the Role of Inflammation in the Link Between Social Experiences and Aging
Faculty Mentor: Dr. Adolfo Cuevas | Graduate Student Mentor: Cindy Patippe
Chronic systemic inflammation is a marker of aging and early mortality. It also offers a unique insight into the physiological responses of our lived experiences. This summer, trainees will work with the Midlife in the United States study—a rich dataset that contains a wide range of psychological and social experiences and biological markers of middle-aged adults nationwide. This dataset presents an exciting opportunity to investigate how social factors like discrimination, loneliness, resilience, and purpose in life intersect with various inflammatory markers. Throughout the summer, trainees will not only sharpen their statistical skills but also gain profound insights into the factors shaping the aging process.
PQAR Students: Haley King, Carlos Rubin de Celis, Madison Simmons
Identifying Powerful Features for Alzheimer's Disease Detection through Multi-View Imaging Genetics Data
Faculty Mentor: Dr. Hai Shu | Graduate Student Mentor: Taehyo Kim
Alzheimer’s disease (AD), the most prevalent form of dementia, accounts for about 60-80% of all dementia cases. The detection of AD can be enhanced through the use of multi-view data, which encompasses various types of data (views) collected from the same subjects. AD is closely associated with brain structural atrophy, metabolic changes, and pathological protein deposits, along with genetic risk factors. These complex features are not fully captured by a single data view and are typically assessed using combined brain imaging and genomic data. This project aims to conduct a comparative study of data integration methods, focusing on canonical correlation analysis (CCA)-type methods, applied to AD-related imaging and genomic data. The goal is to identify significant AD-related brain regions and genetic markers. We will utilize MRI, PET, and GWAS data from both AD patients and cognitively normal individuals, sourced from the Alzheimer’s Disease Neuroimaging Initiative.
PQAR Students: Cheyene Henry, Donjhai Holland, Armando Lemus