Events
Join us for our next Network for Healthy Populations-BBDC Joint Clinical and Population Research-in-Progress Rounds on Monday, January 20, 2025, at 12 p.m. EDT.
The objectives of these ‘research-in-progress’ rounds are:
- To support trainees and new faculty to present their research/early data for knowledge sharing
- To allow trainees and new faculty to receive feedback on their data and methods from their peers
- To strengthen and support relationships across NHP and BBDC’s research network
Analysis of the influence of Neighbourhood Walkability on the Presence of Chronic Diseases among Arab, Racialized, immigrants, and Canadian-born populations in Canada
Presented by Ibrahim Ghanem (PhD Candidate, Supervised by Professor Kathi Wilson)
Neighbourhood environments play a critical role in shaping health outcomes and disparities through influencing access to resources, social networks, and opportunities for physical activity. Despite of the projected growth of the Arab population in Canada, there remains a significant gap in understanding their health status and the conditions of the neighbourhoods they reside in. This study examines the impact of neighbourhood walkability on the presence of diabetes, heart diseases, and their risk factors (Angina, Asthma, and high blood pressure), among Arab population in Canada’s metropolitan areas. Acknowledging the complexity of this relationship, the study also investigates mediators such as neighborhood social settings (e.g., ethnic enclaves and high presence of racialized population, and community cohesion), urban typologies (Urban versus rural), and acculturation.
Objective walkability metrics will be derived from the Canadian Urban Environmental Health Research Consortium’s (CANUE) Active Living Environment (ALE) indicators. Individual lifestyle and health data will be sourced from the Canadian Community Health Survey (CCHS), while neighbourhood material deprivation will be obtained from the Ontario Marginalization Index. Social acculturation, representing agreement with Canadian values, and upward social mobility, representing socioeconomic status, will be computed using custom 2021 Statistics Canada and the General Social Survey datasets, respectively. Using pedestrian networks, a neighbourhood will be operationalized as a 15-minutes walking buffer around the postal codes of CCHS participants. Multilevel modeling will be employed to examine associations between the objective walkability scores and dependent variables representing health outcomes. The models will control potential for confounding factors such as age, gender, BMI, and income. Separate models will be developed to account for variations across sub-population groups, such as immigrants and non-immigrants.
This research will contribute to a better understanding of how neighbourhoods influence chronic disease outcomes among racialized populations. The findings are expected to inform urban planning and public health policies that address the needs of diverse populations in Canada.
Objectives:
- Provide an overview about the topic and the theoretical framework guiding the analysis
- Present the methodology for examining potential individual and neighbourhood features that may mediate the relationship between a neighbourhood predictor and health outcomes.
- Present the methodology for examining the phenomenon of the Healthy Immigrant Effect (HIE) among Arab immigrants in Canada.
Ibrahim Ghanem, is a Ph.D. student at University of Toronto Mississauga, Department of Geography, Geomatics and Environment. He holds a master’s degree in Spatial Analysis from Toronto Metropolitan University, and his research interests include examining access of marginalized communities to social and health-promoting resources (i.e. food environment and bike-share programs), immigrants’ health, and contextual determinants of health. His research is mainly about bridging the gap between quantitative geography and solutions for creating healthier and inclusive neighbourhoods. At this seminar, Ghanem will share his research on leveraging multiple neighbourhood-level and individual-level datasets to investigate the impact of neighbourhood walkability on the health outcomes of the Arab population in Canada.
Advanced Data Science Methods to Examine Trends and Predict Risk of Multimorbidity in Individuals with Asthma in Ontario
Presented by: Ijeoma Itanyi (Ph.D. Candidate, Co-supervised by Dr. Karen Tu and Dr. Laura Rosella)
One in three Canadians live with multimorbidity (the co-occurrence of two or more chronic conditions in one person), and this proportion has increased over time, particularly among younger adults. Multimorbidity is emerging earlier in the life course, constituting a huge challenge to population health and health systems because it requires more complex healthcare plans and places a substantial burden on affected individuals, their caregivers, and the health system. Asthma, the third most common chronic disease in Canada, usually starts earlier in the life course, therefore people with asthma may be at a higher risk of accumulating other chronic conditions. Cross sectional studies have shown a higher prevalence of other chronic conditions in people with asthma compared to those without asthma, however, there is a lack of longitudinal studies specifically investigating this relationship. Furthermore, chronic conditions that accumulate in people with asthma have not been well characterized in Canada. There is an urgent need to go beyond addressing single diseases to characterize chronic conditions which occur together in an individual to inform targeted interventions at the population level. The availability of population-based longitudinal data and the proliferation of advanced data science and machine learning methods provide the opportunity to comprehensively investigate the burden and pattern of multimorbidity in people with asthma, so that preventive strategies can be instituted earlier in the life course. With the rising costs of healthcare, it is critical to identify and accurately predict population segments with higher healthcare needs and strategically allocate scarce resources for targeted interventions.
Objectives:
This project aims to determine the burden of multimorbidity and predict its risk in people with asthma. Specifically, among adults with asthma in Ontario, I aim to:
- Describe the prevalence and pattern of multimorbidity between 2013 and 2022.
- Develop and internally validate a machine learning prediction model for the 5-year risk of multimorbidity.
Ijeoma Itanyi, is a Ph.D. Candidate in Epidemiology, specializing in data science and artificial intelligence at the Dalla Lana School of Public Health, University of Toronto. She holds a medical degree, a Master of Public Health degree, and completed residency and fellowship in Community Health and Preventive Medicine. Prior to starting the PhD program, she was a Senior Lecturer in Epidemiology and Community Medicine at the University of Nigeria, where she led large-scale community-based research projects and played a pivotal role in establishing a national research infrastructure for clinical and implementation research.
Her research focuses on applying epidemiologic and implementation science methods to evaluate health disparities, inform public health policy, and deliver tailored health interventions. At this seminar, she will share her research on using longitudinal population health data to investigate the burden and risk of multimorbidity in people with asthma to inform targeted population-level health interventions.
Registration is now open!
Join us for our next Network for Healthy Populations-BBDC Joint Clinical and Population Research-in-Progress Rounds on Monday, May 12, 2025, at 12 p.m. EDT.
The objectives of these ‘research-in-progress’ rounds are:
- To support trainees and new faculty to present their research/early data for knowledge sharing
- To allow trainees and new faculty to receive feedback on their data and methods from their peers
- To strengthen and support relationships across NHP and BBDC’s research network
Presenters:
Mary Anne Panoyan (PhD Candidate, Co-supervised by Professor Esteban Parra and Assistant Professor Daniel Felsky)
Sonya Grewal (MSc, Supervisor: Dr. Yvonne Bombard)
Registration for this event will open soon!