2019 Research In Progress

The health paradox of physical activity

Lin Yan

150 minutes of weekly exercise is recommended for health promotion and cancer prevention. However, this does not distinguish between exercise performed during one’s leisure time, and the extended physical exertion performed by someone with a physically demanding job.

This study aims to examine the joint impact of occupational and leisure-time physical activity on cancer risk in a large cohort of more than 30,000 individuals from Alberta’s Tomorrow Project.

Such information could be used to:

1) Develop specific guidelines for workplace physical activity

2) Facilitate epidemiological study design among Manitoba workers on the physical activity paradox (particularly within the newly launched Manitoba Tomorrow Project)

3) Plan and evaluate strategies to prevent cancer specific diseases among specific occupational groups

Predict Onset of Breast Cancer

Russell Greiner

This study aims to use machine learning “survival prediction” tools on data from the ATP database to develop a new personalized prediction model. This model, using data from healthy women as well as those with breast cancer in the ATP database, can help understand the impact of modifiable risk factors on the onset of breast cancer.

Characteristics associated with loss-to-follow up in the Alberta’s Tomorrow Project (ATP) cohort 20 years into follow-up

Erin Faught

The goal of this research is to understand the demographics of participants that are actively engaged in the Alberta’s Tomorrow Project (ATP) longitudinal cohort study, as well as to understand the characteristics that may be associated with those that are not.

A participant may be lost to contact by ATP for any number of reasons- they may simply no longer be interested in responding to requests for data, they may have moved, become ill, or potentially passed away.

The information gathered in this study will be used internally at ATP to develop targeted strategies to re-engage individuals who are lost-to-follow-up, or to potentially recruit new participants if a certain subgroup is disproportionately lost and unable to be re-engaged.

Comparative Effectiveness Research in the Canadian Partnership for Tomorrow Cohort

Sasha Bernatsky

Comparative effectiveness research compares existing therapies to understand which treatment works best for which patients, and, conversely, which treatments pose the greatest potential harms.

The ‘Canadian Network for Advanced Interdisciplinary Methods for comparative effectiveness research’ (CAN-AIM) team aims to respond to queries on the drug safety and efficacy of medications on conditions such as hypertension, diabetes, rheumatoid arthritis, rheumatic diseases and inflammatory bowel disease, and cancer. The team is working with the provincial directors of British Columbia, Alberta, Ontario, Quebec, and the Atlantic provinces contributing to the Canadian Partnership for Tomorrow’s Health (CanPath).

Evaluating cancer risk factors in the Canadian Partnership for Tomorrow Project

Rachel Murphy

Two of the most commonly diagnosed cancers in Canada are of the lung and prostate. Many diagnosed cancers may be prevented through lifestyle changes, including changes to diet and physical activity levels.

The link between lifestyle and cancer is poorly understood. Only age, race and family history are well-known risk factors for prostate cancer and little is known about modifiable risk factors for lung cancer beyond smoking.

This project aims to carry out a series of studies to identify the lifestyle, environmental, and genetic factors that may increase the risk that a person will be diagnosed with lung or prostate cancer.

Using data from the Canadian Partnership for Tomorrow’s Health (of which ATP is a part), this project will investigate known and potentially new risk factors for prostate and lung cancer collected from physical measurements, questionnaires, and blood samples, including medical history, lifestyle (diet, body size, sleep, physical activity), and environmental factors (e.g. exposure to toxins). Statistical modeling will be used to identify new risk factors that may help identify people who are at risk of developing cancer. This information will inform the design of interventions to prevent these cancers in the future and improve the health of Canadians.

Prospective healthcare cost-analysis and cross-sectional analysis of impact of health behavior on healthcare use in a Canada-wide prospective cohort – Canadian Partnership for Tomorrow Project

Jason Xu

The large sample size of the Canadian Partnership for Tomorrow’s Health (CanPath), of which ATP is a part, forms an ideal platform for developing risk prediction models in the Canadian population for major chronic diseases, such as cancer, cardiovascular disease, and Type 2 diabetes.

In this study, linkage with health administrative data makes it possible to perform healthcare cost analysis based on the health outcome predictions and service use. Machine learning will be applied to build a prediction model and 10-fold cross validation will be employed for model validation.

The validated model-based cost analysis can then provide evidence to inform decision making, such as healthcare resource allocation. It can underscore the importance of resourcing for population-level disease prevention efforts. With the algorithm proposed in this study, we can also directly assess the impact of these adherence behaviors on healthcare costs.

The impact of neighborhood form on clinical health measures

Gavin McCormack

Population level interventions, such as those that involve designing and developing health supportive built environments, are needed to reduce the incidence of modifiable chronic health conditions including clinical risk factors for cardiovascular disease. However, the extent to which the neighborhood built environment, and in particular walkability, translate into better cardiovascular health for residents remains unknown.

The primary objective of this study is to determine the extent to which the neighborhood built environment is associated with cardiovascular-related clinical and physical risk factors (blood glucose, cholesterol, blood pressure, and weight status) in adults. The findings from this study have the potential to inform urban planning policy and public health interventions.