Impact of Comorbidity on Hospitalization and Emergency Room Visits in Adults With Diabetes: A Longitudinal Study of Alberta’s Tomorrow Project
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.
Mental health, cancer risk, and the mediating role of lifestyle factors in the CARTaGENE cohort study
This study investigates the associations between depression, anxiety, and cancer risk and the mediating effects of lifestyle. Using data from 34,571 CARTaGENE participants, researchers found positive links between mental health disorders, all cancers, and lung cancer risk, except for anxiety and lung cancer in women, where associations were lower when adjusting for sociodemographics, health and lifestyle. The study also found that smoking affected the relationship between mental health disorders and cancer risk. Overall, the study suggests that lifestyle factors, like smoking, may be important in understanding the relationship between mental health and cancer risk.
Circulating microRNA expression signatures accurately discriminate myalgic encephalomyelitis from fibromyalgia and comorbid conditions
Researchers examined the levels of 11 specific molecules called miRNAs in individuals with myalgic encephalomyelitis/chronic fatigue syndrome (ME/CFS), fibromyalgia (FM), and those with both conditions (ME/CFS + FM), as well as in healthy controls. Using samples from 38 CARTaGENE participants and other sources, they found distinct patterns of these miRNAs that can help differentiate between ME/CFS, FM, and ME/CFS + FM, indicating that these miRNAs could serve as potential biomarkers to aid in the accurate diagnosis of these complex illnesses.
Food environment trajectories: a sequence analysis from the CARTaGENE cohort
Researchers sought to categorize how people’s access to food changes over time based on their socioeconomic situations. Using data from 38,627 CARTaGENE participants from urban areas in Quebec, the findings revealed five patterns of food access, with those unable to work, living in larger households, and in low-income households having higher odds of experiencing limited access to food stores over time.
Molecular Genetic Characteristics of FANCI, a Proposed New Ovarian Cancer Predisposing Gene
Researchers investigated the genetic characteristics of the FANCI gene, which has been linked to an increased risk of ovarian cancer. Using data from 171 CARTaGENE participants and other sources, they confirmed that a specific FANCI variant is associated with ovarian cancer and discovered potential genetic links to other cancer types.
Associations between neighborhood walkability and walking following residential relocation: Findings from Alberta’s Tomorrow Project
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.
Examining the influence of built environment on sleep disruption
Researchers sought to understand if modifying aspects of the built environment improved sleep. Using data from 28,385 BC Generations Project participants, they found that increased light-at-night, air pollution (SO2), and living <100 m from a main roadway were associated with insufficient sleep. Greenness had a positive effect on sleep.
A comparison of machine learning algorithms and traditional regression-based statistical modeling for predicting hypertension incidence in a Canadian population
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.
Agreement between self-report and administrative health data on occurrence of non-cancer chronic disease among participants of the BC generations project
Linked self-reported chronic disease history data to a Chronic Disease Registry (CDR) that applied algorithms to administrative health data to ascertain diagnoses of multiple chronic diseases in the Province of British Columbia.
Personalized breast cancer onset prediction from lifestyle and health history information
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.