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?
My name is Shawn Hakimi and I am from Aurora, Ontario. I have also lived in other areas throughout Ontario, namely Caledon and Kingston. I am a PhD candidate in the School of Kinesiology and Health Studies at Queen’s University, working under the supervision of Dr. Mark Rosenberg. My research practice is situated at the nexus of physical activity epidemiology and gerontology.
I completed my undergrad at Queen’s University in Physical and Health Education (BPHE) and Environmental Science (BScH), and my Master’s at Karolinska Institute in Sweden in global public health. Prior to beginning my doctoral studies, I worked at Public Health Ontario, Queen’s University, and internationally for a non-governmental organization.
As a child, my dream job was to be on a SWAT team. Once I realized that wasn’t for me, I started to develop a passion for health sciences and research. Outside of school and work, I enjoy spending time with my family and friends, being outdoors and staying active.
What interested you about the CLSA?
I learned about the CLSA during the second year of my PhD when I came across the CLSA Cohort Profile in the International Journal of Epidemiology. Reading that article really sparked my interest and together with my supervisor, I applied for CLSA data access. Having worked with large epidemiological datasets previously, the CLSA stood out because of its longitudinal study design and the array of study variables available to researchers.
What type of research are you doing with CLSA data? Have you published? If so, what are the findings (in lay terms)?
In broad terms, my research focuses on movement behaviour (i.e., physical activity, sedentary time, sleep, etc.) and healthy aging. More specifically, I am using a burgeoning statistical technique called compositional data analysis to evaluate the interrelationships between these behaviours and their collective impact. I am also studying the effects of reallocating time between movement behaviours on key health outcomes among older Canadians.
Currently, I have a manuscript under review with the Canadian Journal on Aging. The manuscript examines the associations between movement behaviours and quality of life in older Canadian adults 65 years of age and older. We found that relative time spent in sedentary behaviour was associated with reduced quality of life, while relative time spent in sleep was associated with improved quality of life. To some extent, physical activity was associated with improved quality of life. Time substitution modelling showed that replacing time spent in sedentary behaviour with physical activity or sleep improved quality of life for older Canadians.
Another manuscript I am finalizing for submission examines associations between movement behaviours and depression outcomes in older Canadians. In that analysis, we found that moderate-to-vigorous physical activity, but not light-intensity physical activity, reduced depression symptoms in older Canadians and that time spent sedentary increased these symptoms.
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?
Perhaps the most surprising thing I learned from my work with CLSA data, is the breadth and richness of variables available that have been rigorously gathered in a methodologically sound manner. The CLSA helped me grow as a student and researcher by honing my research and data analysis skills through the use of different statistical techniques and study designs. This opportunity has given me the valuable skills and tools necessary to become a leader in my field.
How do you think the findings using CLSA data will be useful to you, or others, in the future?
The Canadian older adult population is an understudied demographic. Given that this population is rapidly expanding, it’s important that researchers be prepared to offer relevant and timely evidence aimed at improving older adult health outcomes to policy and decision-makers.
I believe the results from my research will help inform health-promoting initiatives for the older adult population. Specifically, the findings highlighting the unique movement behaviour requirements and needs of this population will help guide practitioners.
Do you have any idea about what kind of job you’d like to do when you finish school?
After I finish school, I would like return to the public health field and help lead a population movement behaviour research program at the provincial level. I also would like to complete post-doctoral studies and I am currently looking for opportunities and collaborations that will lead me in this direction.
What is a non-career related thing that you are grateful for because of your work with the CLSA?
Through my research with CLSA data, I am grateful for the meaningful contributions I’ve been able to make to the movement science and gerontological fields helping to promote healthy aging
