Tell us about yourself in a paragraph or two: What is your name, and what are you studying? Where are you from? What was your dream job as a kid? What’s your favourite thing to do outside of school/work?
I am Ogochukwu Kelechi Onyeso, a physiotherapist, researcher, and educator with a deep interest in aging, mobility, and population health. I am a PhD candidate in Population Studies in Health at the University of Lethbridge, in Alberta, and a fellow of the Consortium on Analytics for Data-Driven Decision-Making (CAnD3). My academic background includes a Bachelor of Medical Rehabilitation with a major in physiotherapy and a Master’s in Orthopaedics, Sports, and Recreational Physiotherapy. Originally from Nigeria, I have over a decade of clinical experience and more than 40 publications in international journals. My research spans health services, social determinants of health, geriatric rehabilitation, mobility, musculoskeletal disorders, and public health.
As a child, I admired priests, doctors, and engineers, drawn to the idea of community work, helping people heal, and technological inventions. Over time, my passion for health care led me to physiotherapy, where I could directly impact people’s mobility and independence. Outside of academia, I enjoy playing sports, hiking, and spending time in nature, especially near water, coulees, and forests, where I find peace and inspiration.
What interested you about the CLSA?
As a researcher deeply interested in population health, aging, and life course studies, the CLSA data is an invaluable resource. The CLSA provides a comprehensive data bank for researchers interested in modelling health trajectories. It has a large, nationally representative sample and at least three waves of data collection in addition to the baseline, allowing for sophisticated analyses that are inappropriate with smaller samples or cross-sectional studies.
What type of research are you doing with CLSA data? Have you published? If so, what are the findings (in lay terms)?
My CLSA research focused on sociodemographic determinants of mobility decline. The CLSA offers objective physical performance measures, such as the timed-up-and-go (TUG) and 4-meter walk test (4MWT), alongside detailed sociodemographic data. This enabled me to investigate how sociodemographic factors were associated with the observed mobility decline over a six-year follow-up period. The study is published in BMC Geriatrics.
Key findings include a high prevalence of clinically significant mobility limitation (gait speed less than 1m/s) among the cohort. Moreover, modifiable and non-modifiable sociodemographic factors such as older age, female gender, non-Caucasian ethnicity, lower income, lower education, being retired, having no spouse, and living in certain provinces were all associated with a greater decline in mobility.
Since mobility is a key predictor of health and quality of life among older adults, these results highlight the need to review both federal and provincial policies on aging through a deeper lens of social determinants of health and social justice. The World Health Organization (WHO) initiatives, such as the Decade of Healthy Aging and Age-Friendly Cities, are vital resources that could offer policymakers models for equitable resource allocation to support mobility and healthy aging.
What is the most interesting or surprising thing you’ve learned from your work with the CLSA? How do you think the CLSA will help you grow as a student or in your future?
One of the most unexpected insights from my research was the powerful link between socioeconomic status and mobility decline. While we often assume that aging or medical conditions are the primary drivers of mobility decline, my findings reinforced the idea that social and economic disadvantages can accelerate this process.
This research also helped me develop expertise in longitudinal data analysis, statistical modelling, and population health research. Through the CLSA, I refined my skills in mixed-design repeated measures ANOVA (analysis of variance), multivariate longitudinal regression, and visualization tools that are essential for understanding complex health trajectories. These skills will be invaluable as I continue to study aging-related health outcomes and contribute to evidence-based policy-making.
How do you think the findings using CLSA data will be useful to you, or others, in the future?
In my PhD research, I took a multi-methods approach, combining a systematic review and meta-analysis with data from the CLSA and a longitudinal study from Nigeria. I also conducted a qualitative study among older adults in Canada and Nigeria to validate the findings.
These studies have far-reaching implications for policymakers, health-care providers, and community organizations working to support older adults. My research emphasizes that addressing social and economic inequalities would lead to improved and equitable mobility experiences among older adults. Specifically, policies should address socio-cultural constructed biases such as the intersectionality of ageism, sexism, and racism by encouraging non-discriminatory social and economic spaces. Authorities should improve health-care access for rural populations, promote physical activity literacy and opportunities, make public spaces more accessible, and provide financial and housing support for the vulnerable.
This study is a strong foundation for my future work in life-course social determinants of health and policy advocacy. I hope to contribute to policies that promote healthy aging and reduce mobility-related disabilities among older adults by generating evidence through research. Ultimately, my goal is to ensure that research translates into meaningful action, so that every older adult, regardless of their background, has the opportunity to maintain independence and quality of life as they age.
Do you have any idea about what kind of job you’d like to do when you finish school?
I am interested in a career that bridges research, policy, and clinical practice in geriatrics and population health. Whether through academia, clinical physiotherapy, or research institutions, I aim to contribute to improving health-care systems for aging populations. I am particularly passionate about translating data-driven insights into practical interventions that enhance mobility and functional independence in older adults.
What is a non-career related thing that you are grateful for because of your work with the CLSA?
Beyond research, working with CLSA data has given me a greater appreciation for Canada’s diverse population. The study includes participants from various ethnic and cultural backgrounds, all of whom bring unique experiences to the aging process.
I have also been fortunate to receive recognition from colleagues, organizations, and media outlets interested in my research. Presenting my findings at conferences and workshops has opened doors for meaningful conversations and collaborations. I believe that my selection to the CAnD3 fellowship is related to my work with the CLSA.
Most importantly, this research has reshaped how I think about mobility in everyday life. It has encouraged me to prioritize physical activity, social engagement, and long-term health planning, not just for myself, but in discussions with family, friends, and the communities I work with. Preventive health strategies are essential at every stage of life, and I hope my work continues to inspire positive change.
