Publications

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

2023

The contributions of neighbourhood design in promoting metabolic health

Authors: Mohammad Javad Koohsari, Akitomo Yasunaga, Koichiro Oka, Tomoki Nakaya, Yukari Nagai, Jennifer E. Vena, Gavin R. McCormack

Using data from 6,718 Alberta’s Tomorrow Project participants, the researchers assessed associations between neighbourhood built environment and metabolic syndrome, or the presence of at least three clinical risk factors among lipid levels, blood pressure, and waist circumference. They found that neighbourhoods with more points of interest and greater overall active living environment-friendliness were associated with fewer metabolic syndrome risk factors and lower odds of metabolic syndrome. Higher dwelling density was also linked to having fewer metabolic syndrome risk factors.

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2023

Development and external validation of partial proportional odds risk prediction models for cancer stage at diagnosis among males and females in Canada

Authors: Timofei Biziaev, Michelle L. Aktary, Qinggang Wang, Thierry Chekouo, Parveen Bhatti, Lorraine Shack, Paula J. Robson, Karen A. Kopciuk

This study examined health patterns in Alberta’s Tomorrow Project participants before cancer diagnosis to find factors related to cancers caught early versus late. The researchers found factors then tested them in a similar group from the British Columbia Generations Project.

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2023

Time spent in the sun and the risk of developing non-Hodgkin lymphoma: a Canadian cohort study

Authors: Dylan E. O'Sullivan, Troy W. R. Hillier, Darren R. Brenner, Cheryl E. Peters, Will D. King

This study’s objective was to explore the relationship of sun behaviour patterns with non-Hodgkin lymphoma (NHL) risk. Using data from 79,803 Alberta’s Tomorrow Project, CARTaGENE, and Ontario Health Study participants, the researchers found a protective effect of moderate time spent in the sun on NHL risk

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2023

Urban design and cardio-metabolic risk factors

Authors: Mohammad Javad Koohsari, Koichiro Oka, Tomoki Nakaya, Jennifer Vena, Tyler Williamson, Hude Quan, Gavin R. McCormack

This study aimed to estimate associations between neighbourhood built environment metrics and cardiovascular health. Using data from 7171 Alberta’s Tomorrow Project participants, researchers found that a new measure of neighbourhood design showed lower blood pressure in men and lower risk of being overweight or obese in men and women, whereas traditional measures did not show this association.

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2023

Non-fasting lipids and cardiovascular disease in those with and without diabetes in Alberta’s Tomorrow Project: A prospective cohort study

Authors: Olivia R. Weaver, Ming Ye, Jennifer E. Vena, Dean T. Eurich, Spencer D. Proctor

This study’s objective was to assess the relationship of non-fasting remnant cholesterol (RC) with cardiovascular disease (CVD) in those with and without diabetes using data from 13,631 Alberta’s Tomorrow Project participants. Researchers found that elevated non-fasting RC was associated with increased CVD risk in middle and older-aged adults without diabetes.

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2023

Mental health service use and associated predisposing, enabling and need factors in community living adults and older adults across Canada

Authors: Helen-Maria Vasiliadis, Jessica Spagnolo, Marie-Josée Fleury, Jean-Philippe Gouin, Pasquale Roberge, Mary Bartram, Sébastien Grenier, Grace Shen-Tu, Jennifer E. Vena, JianLi Wang

The authors utilized data from the CanPath COVID-19 health survey (May to December 2020) to conduct multivariate logistic regression analysis to determine the association between mental health service use (MHSU) and predisposing, enabling, and need factors — derived from Andersen’s model of healthcare-seeking behaviour — among five regional cohorts. Among the 45,542 adults in the study population, 6.3% of respondents reported MHSU and need factors were consistently associated with MHSU.

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2023

Physical activity-induced alterations of the gut microbiota are BMI dependent

Authors: Shrushti Shah, Chunlong Mu, Shirin Moossavi, Grace Shen-Tu, Kristina Schlicht, Nathalie Rohmann, Corinna Geisler, Matthias Laudes, Andre Franke, Thomas Züllig, Harald Köfeler, Jane Shearer

Researchers assessed physical activity and hand-grip strength’s role in gut microbiome composition in middle-aged adults with normal and overweight body mass index. Data from 443 participants from Alberta’s Tomorrow Project suggest that BMI plays a significant role in modelling PA-induced changes in gut microbiota.

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2023

Impact of Comorbidity on Hospitalization and Emergency Room Visits in Adults 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

Using data from Alberta’s Tomorrow Project, Ye et al. investigated the impact of comorbidities on hospitalization and emergency room visits in people with diabetes. Over the 5-year study period, the authors observed a significant association between the number of comorbidities and increased healthcare utilization among the 2,110 cases in the study population.

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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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