Publications

These publications are examples of research made possible with data from CanPath and its regional cohorts.

2022

Personalized breast cancer onset prediction from lifestyle and health history information

Authors: Shi-Ang Qi, Neeraj Kumar, Jian-Yi Xu, Jaykumar Patel, Sambasivarao Damaraju, Grace Shen-Tu, Russell Greiner

This article proposes a method for predicting when a woman will develop breast cancer (Bca) based on health and lifestyle history using data from 18,288 women in Alberta’s Tomorrow Project. Their approach produced seven actionable lifestyle features that a woman can modify to show how the model can predict the effects of such changes. This method can be used to identify interventions for those with a greater likelihood of developing BCa.

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2022

Patterns and predictors of adherence to breast cancer screening recommendations in Alberta’s Tomorrow Project

Authors: Olivia K Loewen, Navjot Sandila, Grace Shen-Tu, Jennifer E Vena, Huiming Yang, Kara Patterson, Jian-Yi Xu

This study examined screening patterns in almost 5,000 women in Alberta’s Tomorrow Project. Most participants were up-to-date with screening at enrollment and follow-up, but 21.6% were not up-to-date at follow-up, and 3.2% had never participated. Having a family doctor was the strongest predictor of regular screening, while current smokers were less likely to be regular screeners. The study highlights the importance of promoting awareness of screening recommendations and the role of family doctors in encouraging screening.

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2022

Association of dairy consumption patterns with the incidence of type 2 diabetes: Findings from Alberta’s Tomorrow Project

Authors: Emad Yuzbashian, Mohammadreza Pakseresht, Jennifer Vena, Catherine B Chan

Researchers investigated the relationship between dairy consumption and the risk of developing type 2 diabetes (T2D) with data from Alberta’s Tomorrow Project (ATP). 15,016 women and 8,615 men completed a food-frequency questionnaire and were followed up over time to determine T2D incidence. They found that higher consumption of whole milk, regular cheese, and non-fat milk was associated with decreased risk of incident T2D only in men. The study suggests that combining different dairy products might be good for men’s health.

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2022

Harnessing the power of data linkage to enrich the cancer research ecosystem in Canada

Authors: Robin Urquhart, Philip Awadalla, Parveen Bhatti, Trevor Dummer, Simon Gravel, Jennifer Vena, Riaz Alvi, Philippe Broet, Cynthia Kendell, Victoria Kirsh, Guillaume Lettre, Kimberly Skead, Grace Shen-Tu, Ellen Sweeney, Donna Turner

This abstract discusses a project aimed at linking cancer registry and administrative health data to Canada’s largest population health study, the Canadian Partnership for Tomorrow’s Health (CanPath). The project seeks to enrich the cancer research ecosystem in Canada by providing researchers with a comprehensive dataset that includes genetics, environment, lifestyle, and behaviour data. The linked data will be made available through a cloud-based solution called the CanPath Data Safe Haven, which is accessible to researchers through secure access. The project will address concerns related to the accessibility of cancer data in Canada, bring more value to existing data, and support an enhanced understanding of the impacts of cancer on marginalized populations.

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2022

Development and validation of a hypertension risk prediction model and construction of a risk score in a Canadian population

Authors: Mohammad Ziaul Islam Chowdhury, Alexander A Leung, Khokan C Sikdar, Maeve O'Beirne, Hude Quan, Tanvir C Turin

This study evaluates different machine learning algorithms and compares their predictive performance with conventional models to predict hypertension incidence using data from 18,322 Alberta’s Tomorrow Project participants. The study found little difference in predictive performance between the machine learning algorithms and the conventional Cox PH model. The results suggest that conventional regression-based models can perform similarly to machine learning algorithms with good predictive accuracy in a moderate dataset with a reasonable number of features.

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2022

Associations between neighbourhood street connectivity and sedentary behaviours in Canadian adults: Findings from Alberta’s Tomorrow Project

Authors: Vikram Nichani, Mohammad Javad Koohsari, Koichiro Oka, Tomoki Nakaya, Ai Shibata, Kaori Ishii, Akitomo Yasunaga, Jennifer E Vena, Gavin R McCormack

Researchers aimed to estimate associations between street connectivity, based on space syntax-derived street integration, and sedentary behaviours. Using data from 14,758 Alberta’s Tomorrow Project participants, they found that connectivity was positively related to various measures of sitting time and negatively associated with motor vehicle travel time.

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2022

Developing a Socioeconomic Status Index for Chronic Disease Prevention Research in Canada

Authors: Elham Khodayari Moez, Katerina Maximova, Shannon Sim, Ambikaipakan Senthilselvan, Roman Pabayo

Researchers developed a socioeconomic status (SES) index and assessed its associations with smoking amongst 17,371 Alberta’s Tomorrow Project participants. They found that their index was negatively related to smoking intensity.

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2022

Cross-sectional and longitudinal associations between the built environment and walking: effect modification by socioeconomic status

Authors: Chelsea D Christie, Christine M Friedenreich, Jennifer E Vena, Liam Turley, Gavin R McCormack

Using data from 703 Alberta’s Tomorrow Project participants, researchers found that changes to the built environment are not associated with changes in walking amongst adults after relocation. They also had weak findings that changes in walkability due to relocation may more strongly affect walking for adults with lower socioeconomic status.

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2022

Anti-Hyperglycemic Medication Adherence and Health Services Utilization in People with Diabetes: A Longitudinal Study of Alberta’s Tomorrow Project

Authors: Ming Ye, Jennifer E Vena, Jeffrey A Johnson, Grace Shen-Tu, Dean T Eurich

This study aimed to describe how time-varying anti-hyperglycemic medication adherence relates to healthcare utilization for those with diabetes. Using data from Alberta’s Tomorrow Project participants, researchers found that poor drug adherence related to higher healthcare utilization in the short term but less over the long term.

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2022

A dietary carbohydrate – gut Parasutterella – human fatty acid biosynthesis metabolic axis in obesity and type 2 diabetes

Authors: Lea Henneke, Kristina Schlicht, Nadia A. Andreani, Tim Hollstein, Tobias Demetrowitsch, Carina Knappe, Katharina Hartmann, Julia Jensen-Kroll, Nathalie Rohmann, Daniela Pohlschneider, Corinna Geisler, Dominik M. Schulte, Ute Settgast, Kathrin Türk, Johannes Zimmermann, Christoph Kaleta, John F. Baines, Jane Shearer, Shrushti Shah, Grace Shen-Tu, Karin Schwarz, Andre Franke, Stefan Schreiber, Matthias Laudes

This study aimed to characterize Parasutterella, a gut bacteria, in a European cohort. 438 participants from Alberta’s Tomorrow Project were included to validate the results of this study. Researchers found that this bacteria have a role in type 2 diabetes and obesity.

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