Population and Community Health Sciences (PCHS)

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Scientific Expertise:

Implementation science, social and behavioral epidemiology, cancer health disparities, psycho-oncology, biopsychosocial factors affecting cancer survivorship in vulnerable populations, Latino health, physician-patient communication, health disparities research methods, community-engaged research, survey development, mixed methods (quantitative & qualitative).

Research and Programmatic Interests:

Her studies have focused on eliminating health inequalities related to cancer treatment and survivorship, self-care behaviors and physician-patient communication. Her goal is to develop effective socio-behavioral interventions to address these disparities, while contributing to the advancement of scientific methods for their study. Her research falls into three interrelated categories: (1) cancer control in underserved populations; (2) interpersonal processes of care; and (3) health disparities research methods.

Research Projects:

Conducted Community-Based Randomized Controlled Trials (RCTs) of a Peer-Delivered Cognitive-Behavioral Stress Management Intervention for Urban and Rural Latinas with Breast Cancer called Nuevo Amanecer.

• This program of research focuses on involving affected health disparity communities in the design and implementation of evidence-based interventions, and utilizing community assets to facilitate implementation and sustainability. These studies demonstrate the potential of training community health workers and peers to deliver evidence-based interventions to reduce health disparities.

Developing and Testing mHealth and Coaching Interventions to Improve Symptom Management among Ethnically Diverse, Low-Income Cancer Survivors through Cognitive-Behavioral Stress Management and/or Walking.

• We have conducted user-centered pilot testing to test alternative, lower cost modes of delivering evidence-based interventions to address health disparities. Some of these involve using technology (mobile phone applications) combined with the human touch (telephone coaching by culturally congruent coach) as an alternative to higher cost in-person delivery.

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Scientific Expertise:

Health education, behavior, mHealth, and communication.

Research and Programmatic Interests:

Interests include leveraging health information technologies to improve minority health and reduce health disparities. Specifically, Dr. El-Toukhy conducts epidemiologic research on tobacco use to inform the design and implementation of mHealth smoking cessation interventions, and examines disparities in the adoption and integration of health information technologies within hospitals and its impact on reducing health disparities in patient outcomes.

Research Projects:

SmokeFree Smoking Cessation Interventions .

• We examine differences in dropout, engagement, and abstinence outcomes among users of SmokeFree text messaging interventions by race/ethnicity. SmokeFree consists of U.S. national smoking cessation interventions that are publicly available through the National Cancer Institute’s SmokeFree.Gov initiative. We examine these outcomes in SmokeFreeTXT that targets the general population of smokers, SmokeFreeTeens that target adolescent smokers, SmokeFreeMom that targets pregnant women who smoke, and SmokeFreeEsp that targets Latino smokers.

QuitGuide mHealth Just-in-Time Smoking Cessation Interventions

• We aim to develop and assess the efficacy of a just-in-time mHealth smoking cessation intervention targeting young adult smokers of low socioeconomic status using the National Cancer Institute’s QuitGuide mobile application. For the intervention development and evaluation, first, we conduct formative studies to determine the acceptability and feasibility of intervention components. Second, we conduct a pilot to obtain baseline data on the app use and cessation outcomes followed by a proof-of-concept study to determine if the fully optimized intervention produces a meaningful effect on smoking cessation. Lastly, we conduct an optimization experiment to determine the main and interaction effects of intervention components followed by a randomized controlled trial to evaluate the optimized intervention against standard care.

Electronic Health Records (EHR): Access among Vulnerable Populations

• We examine patient characteristics associated with electronic health records access, facilitators of use, and use. We also examine the extent of knowledge and use of electronic health records functions among vulnerable populations. Finally, to evaluate outcomes, we examine micro- and macro-level factors (including availability of electronic health records) associated with the quality of patient-clinician communication and with screening for five types of cancer.

Electronic Health Records (EHR): Automatic Referral of High-Risk Populations

• We determine the acceptability, feasibility, and reach of an EHR-based auto referral electronic messaging system that refers adults who smoke cigarettes or drink alcohol at risky levels to behavioral change mobile applications. The proximal outcome is a clinically meaningful increase in the proportion of a hospital’s at-risk patient population who click on a link to behavioral change mobile apps in an auto-referral message.

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Scientific Expertise:

Applied community-based system dynamics and group model building, geospatial analyses, social and behavioral epidemiology, cancer health disparities, community-engaged research.

Research and Programmatic Interests:

Interests include cancer prevention and control, cancer survivorship, breast cancer health disparities, access to health care services, social determinants of health, global health, health promotion, group model building, community-based system dynamics and community-based participatory research, rural-urban differences in cancer diagnosis, treatment and survivorship.

Research Projects:

Latent Class Analysis of Acculturation on Syndemic Cardiometabolic Risk and Telomere Length among South Asians in the U.S.: A Person-Centered Approach to Examine Risk Profiles.

• Latent class analysis (LCA) will be used to examine the impact of multiple risk factors on cardiometabolic health and identify intervenable elements. LCA refers to a technique to identify unobservable—or latent—subgroups within a population or subpopulation. LCA will allow us to use a person-centered approach to assess the constellation of acculturation factors, health determinants, disease clusters, and biomarkers to identify risk subgroups associated with telomere length and sociodemographic factors.

Geospatial Analysis to Understand the Influence of Social Networks on Health in the Mediators of Atherosclerosis in South Asians Living in America (MASALA) Study

• This study utilizes Geographic Information Systems (GIS) analysis to examine spatial characteristics of social links and the frequency, quality and duration of social interactions with network members based on survey questions from the MASALA study. Multivariate logistic regression will be used to assess associations between geographic access, quality of social interactions and health consequences. Subgroup analysis will examine whether associations differ by geographic location (cities).

Assessing Differences by Birthplace in Associations of Family History on Breast Cancer Related Health Behaviors: The Sister Study

• We will examine the effects of socio-demographic (race/ethnicity household income, educational level, health insurance, marital status), health status, healthcare access and neighborhood factors on nutrition/eating, physical activity, smoking status, alcohol consumption, and body mass index among diverse sisters of women who have been diagnosed with breast cancer.

Community of Mine

• This study seeks to understand the key neighborhood features that foster or impede acculturation and cardiometabolic risk among Hispanics/Latinos in San Diego. Additionally, we will identify acculturation subgroups by sociodemographic characteristics, socioeconomic status, and environmental factors using latent class analysis.

Person-Centered and Geospatial Analysis of Surveillance, Epidemiology, End and Results (SEER) and Tennessee Department of Health (TDH) Cancer Datasets

• Mapping regional and demographic variations of lung cancer incidence in Tennessee, 2005–2015, to explore the spatial distribution of incidence and identify regional differences, while controlling for smoking rate and demographic variables.
• Spatiotemporal mapping of colorectal cancer (CRC) survivorship across space and over time (SEER).
• Using latent class analysis to identify the patterns of highest risk in treatment delay among CRC patients while accounting for subgroup differences in sociodemographic and health insurance characteristics.
• A population-based evaluation of delay in surgical invasive cancer treatment delay among breast and prostate cancer patients.

Acculturation and Telomere Length among Hispanic/Latinos: A Latent Class Analysis Using the National Health and Nutrition Examination Survey (NHANES)

• We will use LCA to assess the impact of multiple acculturation factors on mean telomere length among Hispanic/Latino subgroups

Household Environmental Factors and Child Health Outcomes: A Latent Class Analysis (LCA) of the Tanzania Demographic and Health Survey

• We will explore mothers’ experiences with interpersonal violence as a risk factor for poor antenatal care. The focus of this research is on interpersonal violence (IPV) regarding HIV testing during antenatal care (ANC) visits.

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Scientific Expertise:

Neighborhoods, activity space, food and built environments, spatiotemporal methodologies, intensive longitudinal analyses, health disparities, environmental exposures, nutrition, physical activity, climate change.

Research and Programmatic Interests:

Interests include examining the role of environmental exposures in health disparities. Specifically, conducting observational and intervention research projects focused on social inequities and health with a goal of identifying effective approaches and informing policy to improve health and eliminate racial, ethnic, and socioeconomic health disparities. Projects done by Dr. Zenk’s lab use a contextual and spatial lens to analyze data on community environments and examine impacts of these exposures on health and health behaviors.

Research Projects:

UrbanHEAT

• Climate change-related increases in urban heat have been shown in observational data and are predicted to get more extreme. Climate and environmental justice research has shown that urban neighborhoods with large racial and ethnic minority populations or high poverty rates experience higher temperatures, largely related to fewer resources such as parks, street trees, and cooling street construction materials. In addition, residents move throughout urban spaces over the course of days, weeks, and seasons, and that movement has rarely been accounted for in exposure studies. Much heat-health research has measured exposure at the macro level and thus fails to account for variability in exposure within and between persons across time. To close these gaps, we are collecting data using wearable monitors, ecological momentary assessment surveys, and environmental modeling to understand the role of heat exposures in health behaviors and outcomes at individual and community levels.

SchoolHEAT

• This project expanded on recognition of neighborhood-based disparities in heat to include school environments. School environments are critical for children’s physical activity and learning, and also have health-relevant impacts on diet, sleep, and mental health. This project synthesizes a number of different data sources including school catchment areas and satellite imagery to analyze heat exposure at elementary schools across the 48 contiguous states and the District of Columbia and examine disparities in heat exposures between neighborhoods with different socio-economic and racial composition.

Low Income Home Energy Assistance Program (LIHEAP) Evaluation

• As temperatures rise due to the increasing effects of climate change, the ability for people to cool their homes has become a necessity. LIHEAP is a multi-billion-dollar government program with an initial charge to provide financial support to households related to heating costs. In response to rising temperatures and increased frequency of heat waves, LIHEAP agencies have dedicated programmatic funds to include financial assistance for cooling as well. Using LIHEAP state program data, electronic medical record (EMR) data, and weather data we are evaluating this program for its ability to reduce heat exposure-related morbidity.

Intramural and Extramural Collaborations

• We collaborate with a wide variety of research groups (e.g., Socio-Spatial Determinants of Health Laboratory, Section of Sensory Science and Metabolism, Jackson Heart Study) contributing expertise on environmental measurement and interpretation.