Publications

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

2023

Associations between neighborhood walkability and walking following residential relocation: Findings from Alberta’s Tomorrow Project

Authors: Gavin R McCormack, Mohammad Javad Koohsari, Jennifer E Vena, Koichiro Oka, Tomoki Nakaya, Jonathan Chapman, Ryan Martinson, Graham Matsalla

This study aimed to estimate whether changes in neighbourhood walkability resulting from residential relocation were associated with leisure, transportation, and total walking levels. Using data from 5,977 urban adults (non-movers, movers to less walkability, and movers to more walkability), researchers found that time spent walking at follow-up was lower among those who moved to less walkable neighbourhoods, suggesting that relocating to less walkable neighbourhoods could negatively affect health.

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2023

A comparison of machine learning algorithms and traditional regression-based statistical modeling for predicting hypertension incidence in a Canadian population

Authors: Mohammad Ziaul Islam Chowdhury, Alexander A Leung, Robin L Walker, 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

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

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

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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2022

Health-Related and Behavioral Factors Associated With Lung Cancer Stage at Diagnosis: Observations From Alberta’s Tomorrow Project

Authors: Michelle L. Aktary, Monica Ghebrial, Qinggang Wang, Lorraine Shack, Paula J. Robson, Karen A. Kopciuk

This study examined sociodemographic characteristics and health-related factors and their associations with subsequent lung cancer stage at diagnosis. Using data from 221 Alberta’s Tomorrow Project participants, researchers found that a history of sunburn in the past year and more prostate-specific antigen tests were protective against late-stage lung cancer diagnosis, whereas physical activity increased late-stage cancer diagnosis odds.

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2022

Pre-diagnosis lifestyle, health history and psychosocial factors associated with stage at breast cancer diagnosis – Potential targets to shift stage earlier

Authors: Qinggang Wang, Michelle L. Aktary, John J. Spinelli, Lorraine Shack, Paula J.Robson, Karen A. Kopciuk

This study aimed to examine associations between risk factors for breast cancer diagnosis, prior to and and at diagnosis. Some protective factors include older age at diagnosis, high household income, parity, smoking, spending time in the sun (high ultraviolet), having a mammogram, and high daily protein intake. Factors that increase risk of later stage at diagnosis include comorbidities, stressful situations, and high daily caloric intake.

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2022

Lifestyle factors and lung cancer risk among never smokers in the Canadian Partnership for Tomorrow’s Health (CanPath)

Authors: Rachel Murphy, Maryam Darvishian, Jia Qi, Yixian Chen, Quincy Chu, Jennifer Vena, Trevor J B Dummer, Nhu Le, Ellen Sweeney, Vanessa DeClercq, Scott A Grandy, Melanie R Keats, Yunsong Cui, Philip Awadalla, Darren R Brenner, Parveen Bhatti

Data from 950 CanPath participants were analyzed to understand why 15-25% of lung cancers occur in never smokers. Researchers found a link between lung cancer risk, sleep, and fruit and vegetable intake amongst never smokers.

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2022

Evaluation of Adiposity and Cognitive Function in Adults

Authors: Sonia S. Anand, Matthias G. Friedrich, Douglas S. Lee, Phillip Awadalla, J. P. Després, Dipika Desai, Russell J. de Souza, Trevor Dummer, Grace Parraga, Eric Larose, Scott A. Lear, Koon K. Teo, Paul Poirier, Karleen M. Schulze, Dorota Szczesniak, Jean-Claude Tardif, Jennifer Vena, Katarzyna Zatonska, Salim Yusuf, Eric E. Smith, the Canadian Alliance of Healthy Hearts and Minds (CAHHM), the Prospective Urban and Rural Epidemiological (PURE) Study Investigators

Researchers sought to undercover the association between adipose tissue (amount and distribution) and cognitive scores. Using data from 9,189 participants, they found that higher visceral adipose tissue and body fat percentage correlated with increased vascular brain injuries and cardiovascular risk factors, as well as lower cognitive scores.

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