Publications by authors named "Grace Shen-Tu"

Background: A plant-focused, healthy dietary pattern, such as the Mediterranean diet enriched with dietary fiber, polyphenols, and polyunsaturated fats, is well known to positively influence the gut microbiota. Conversely, a processed diet high in saturated fats and sugars negatively impacts gut diversity, potentially leading to weight gain, insulin resistance, and chronic, low-grade inflammation. Despite this understanding, the mechanisms by which the Mediterranean diet impacts the gut microbiota and its associated health benefits remain unclear.

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Background: Metabolomics offers a promising approach to identify biomarkers for timely intervention and enhanced screening of individuals at increased risk of developing breast cancer.

Methods: We conducted a study of 593 female breast cancer cases and 593 matched controls nested in two prospective cohort studies. Mass spectrometry, without liquid chromatography, was used to conduct untargeted metabolomics profiling of serum samples collected, on average, 5.

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Recent clinical trials suggest benefit of anti-hyperglycemic drugs on kidney outcomes. However, there is a paucity of information available on the real-world impact.We aimed to study the real-world impact of anti-hyperglycemic drugs (metformin, sodium-glucose cotransporter-2 (SGLT-2) inhibitors, dipeptidyl peptidase-4 (DPP-4) inhibitors, and glucagon-like peptide-1receptor (GLP-1R) agonists) using a cohort of patients with incident diabetes derived from the Alberta Tomorrow Project (ATP) database.

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Purpose: To characterize the association between metformin use and risk of total joint replacement in patients with diabetes using data from Alberta's Tomorrow Project (ATP), a population-based cohort study of chronic diseases in Alberta, Canada.

Methods: The ATP participants with incidence of diabetes after enrollment were included and followed up to March 31, 2021. Metformin use, including daily doses, was measured by a time-varying approach during the follow-up.

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Background: Effective mental healthcare coverage (EMHC) is an important health system performance indicator of a population's mental healthcare needs. This study aims to assess the factors and healthcare costs associated with the receipt of EMHC for anxiety and depression.

Methods: This study draws on data from participants from Alberta's Tomorrow Project with moderate or severe symptoms of anxiety and depression during the first wave of the COVID-19 pandemic (2020) with available medico-administrative and complete data [n = 720].

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Objective: The objective is to characterize the impact of COVID-19 on major healthcare for diabetes, including hospitalization, emergency department (ED) visits and primary care visits in Alberta, Canada.

Methods: Participants from Alberta's Tomorrow Project (ATP) with pre-existing diabetes prior to 1 April 2018 were included and followed up to 31 March 2021. A time-segmented regression model was used to characterize the impact of COVID-19 on healthcare utilization after adjusting for seasonality, socio-demographic factors, lifestyle behaviors and comorbidity profile of patients.

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Human gut microbiota are recognized as critical players in both metabolic disease and drug metabolism. However, medication-microbiota interactions in cardiometabolic diseases are not well understood. To gain a comprehensive understanding of how medication intake impacts the gut microbiota, we investigated the association of microbial structure with the use of single or multiple medications in a cohort of 134 middle-aged adults diagnosed with cardiometabolic disease, recruited from Alberta's Tomorrow Project.

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Oral iron supplementation is the first-line treatment for addressing iron deficiency, a concern particularly relevant to women who are susceptible to sub-optimal iron levels. Nevertheless, the impact of iron supplementation on the gut microbiota of middle-aged women remains unclear. To investigate the association between iron supplementation and the gut microbiota, healthy females aged 40-65 years ( = 56, BMI = 23 ± 2.

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Aim: To characterize the impact of the COVID-19 pandemic on diabetes diagnosis using data from Alberta's Tomorrow Project (ATP), a population-based cohort study of chronic diseases in Alberta, Canada.

Materials And Methods: The ATP participants who were free of diabetes on 1 April 2018 were included in the study. A time-segmented regression model was used to compare incidence rates of diabetes before the COVID-19 pandemic, during the first two COVID-19 states of emergency, and in the period when the state of emergency was relaxed, after adjusting for seasonality, sociodemographic factors, socioeconomic status, and lifestyle behaviours.

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Article Synopsis
  • The study investigates changes in moderate or severe symptoms of anxiety and depression in Canadians aged 35 and older from before to during the COVID-19 pandemic, using data from two health surveys.
  • Researchers categorized changes in mental health symptoms as no symptoms, remitted, incident, or persistent, analyzing factors like age, gender, income, and health behaviors that might influence these changes.
  • Findings reveal that various sociodemographic and health-related factors impacted mental health during the pandemic, highlighting the need for ongoing public health initiatives and policies that address mental health disparities and socioeconomic barriers.
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Background: Scarce are the studies focusing on initiation of new mental health service use (MHSU) and distinguishing individuals who have sought services but have been unsuccessful in accessing these.

Aims: Assessing the factors associated with initiating new MHSU as compared to no MHSU due to self-reported no need, no MHSU due to health system and personal barriers and MHSU using resources already in place.

Methods: The sample included participants ( = 16,435) in the five established regional cohorts of the Canadian Partnership for Tomorrow's Health (CanPath) who responded to the CanPath COVID-19 health surveys (May-December 2020 and January-June 2021).

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An Individual Survival Distribution (ISD) models a patient's personalized survival probability at all future time points. Previously, ISD models have been shown to produce accurate and personalized survival estimates (for example, time to relapse or to death) in several clinical applications. However, off-the-shelf neural-network-based ISD models are usually opaque models due to their limited support for meaningful feature selection and uncertainty estimation, which hinders their wide clinical adoption.

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Objective: Our aim in this study was to characterize the impact of comorbidities, including number and types, on hospitalization and emergency room (ER) visits in people with diabetes.

Methods: Incident cases of diabetes from Alberta's Tomorrow Project with >24 months of follow-up were included. Comorbidities, classified by Elixhauser conditions, were updated every 12 months after diagnosis.

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Objectives: Using Andersen's model of health care seeking behavior, we examined the predisposing, enabling, and need factors associated with mental health service use (MHSU) during the first wave of the COVID-19 pandemic across Canada.

Methods: The sample included n = 45,542 participants in the 5 established regional cohorts of the Canadian Partnership for Tomorrow's Health (CanPath) and who responded to the CanPath COVID-19 health survey (May-December 2020), with complete data on MHSU. Multivariable logistic regression analyses were carried out to study MHSU as a function of predisposing, enabling, and need factors.

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Physical inactivity is one of the leading causes of chronic metabolic disease including obesity. Increasing physical activity (PA) has been shown to improve cardiometabolic and musculoskeletal health and to be associated with a distinct gut microbiota composition in trained athletes. However, the impact of PA on the gut microbiota is inconclusive for individuals performing PA in their day-to-day life.

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We propose a method to predict when a woman will develop breast cancer (BCa) from her lifestyle and health history features. To address this objective, we use data from the Alberta's Tomorrow Project of 18,288 women to train Individual Survival Distribution (ISD) models to predict an individual's Breast-Cancer-Onset (BCaO) probability curve. We show that our three-step approach-(1) filling missing data with multiple imputations by chained equations, followed by (2) feature selection with the multivariate Cox method, and finally, (3) using MTLR to learn an ISD model-produced the model with the smallest L1-Hinge loss among all calibrated models with comparable C-index.

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Article Synopsis
  • Breast cancer screening is crucial for reducing mortality and improving survival rates, and understanding adherence patterns is key for effective health strategies.
  • A study involving 4,972 women in Alberta revealed that 79.3% were up-to-date with screening at enrollment, but that number dropped to 75.2% at follow-up, with various classifications of adherence identified.
  • Having a family doctor significantly increases the likelihood of regular screening, while current smokers tend to be non-regular screeners, indicating the need for awareness initiatives to boost adherence to screening recommendations.*
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Background: Little is known about the long-term (>2 years) relationship between the time-varying drug adherence and healthcare utilization for patients with diabetes.

Objective: To characterize the relationship between time-varying anti-hyperglycemic medication adherence and healthcare utilization in patients with diabetes, using data from Alberta's Tomorrow Project, a population-based cohort study in Alberta, Canada.

Methods: Incident cases of diabetes with at least 24 months of follow-up were included in the study.

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Recent rodent microbiome experiments suggest that besides . are important in type 2 diabetes and obesity development. In the present translational human study, we aimed to characterize in our European cross-sectional FoCus cohort (n = 1,544) followed by validation of the major results in an independent Canadian cohort (n = 438).

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Introduction: Alberta's Tomorrow Project (ATP) is the largest population-based prospective cohort study of cancer and chronic diseases in Alberta, Canada. The ATP cohort data were primarily self-reported by participants on lifestyle behaviors and disease risk factors at the enrollment, which lacks sufficient and accurate data on chronic disease diagnosis for longer-term follow-up.

Objectives: To characterize the occurrence rate and trend of chronic diseases in the ATP cohort by linking with administrative healthcare data.

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Current cancer prevention recommendations advise limiting red meat intake to <500 g/week and avoiding consumption of processed meat, but do not differentiate the source of processed meat. We examined the associations of processed meat derived from red v. non-red meats with cancer risk in a prospective cohort of 26 218 adults who reported dietary intake using the Canadian Diet History Questionnaire.

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We investigated the association of social jetlag (misalignment between the internal clock and socially required timing of activities) and prostate cancer incidence in a prospective cohort in Alberta, Canada. Data were collected from 7455 cancer-free men aged 35-69 years enrolled in Alberta's Tomorrow Project (ATP) from 2001-2007. In the 2008 survey, participants reported usual bed- and wake-times on weekdays and weekend days.

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Recently, we introduced a novel measure of "average life span shortened" (ALSS) to improve comparability of premature mortality over time. In this study, we applied this novel measure to examine trends in premature mortality caused by hematological cancers in Canada from 1980 to 2015. Mortality data for Hodgkin lymphoma, non-Hodgkin lymphoma, multiple myeloma, and leukemia were obtained from the World Health Organization mortality database.

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Purpose: Limited evidence exists on the comprehension and use of Nutrition Facts tables (NFt) among adolescents and young adults. This study provides an account of how young people engage with, understand, and apply nutrition information on the current and modified versions of the NFt to compare and choose foods.

Methods: Participants aged 16-24 years (n = 26) were asked to "think aloud" while viewing either the current or 1 of 5 modified NFts and completing a behavioural task.

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