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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., Results: Among 43 705 ATP participants free of diabetes (65.5% females, age 60.4 ± 9.5 years in 2018), the rate of diabetes was 4.75 per 1000 person-year (PY) during the COVID-19 pandemic (up to 31 March 2021), which was 32% lower (95% confidence interval [CI] 21%, 42%; p < 0.001) than pre-pandemic (6.98 per 1000 PY for the period 1 April 2018 to 16 March 2020). In multivariable regression analysis, the first COVID-19 state of emergency (first wave) was associated with an 87.3% (95% CI -98.6%, 13.9%; p = 0.07) reduction in diabetes diagnosis; this decreasing trend was sustained to the second COVID-19 state of emergency and no substantial rebound (increase) was observed when the COVID-19 state of emergency was relaxed., Conclusions: The COVID-19 public health emergencies had a negative impact on diabetes diagnosis in Alberta. The reduction in diabetes diagnosis was likely due to province-wide health service disruptions during the COVID-19 pandemic. Systematic plans to close the post-COVID-19 diagnostic gap are required in diabetes to avoid substantial downstream sequelae of undiagnosed disease., (© 2023 The Authors. Diabetes, Obesity and Metabolism published by John Wiley & Sons Ltd.)

Aims: Non-fasting remnant cholesterol (RC) is a novel marker of cardiovascular disease (CVD) risk, however, data on this relationship in Canadians with diabetes (at high risk of CVD) is lacking. The objective of this analysis was to determine the relationship of RC with CVD in individuals with and without diabetes in the Alberta's Tomorrow Project (ATP) cohort., Methods: Non-fasting lipid data collected as part of the ATP was linked to administrative health records (October 2000-March 2015) to ascertain incident CVD and prevalent diabetes. Participants without prevalent CVD or incident diabetes and who had complete, non-negative non-fasting lipid data collected with triglycerides <4.5 mmol/L were included (n = 13,631). The relationship between non-fasting RC and incident CVD diagnoses was assessed by Cox proportional hazards regression, after stratification by diabetes status., Results: Participants were 69.8% women with a mean age of 61.6 ± 9.7 years, and 6.5% had prevalent diabetes. Non-fasting RC was higher in participants with diabetes compared to those without (mean 0.94 ± 0.41 mmol/L vs. 0.77 ± 0.38 mmol/L, p < 0.0001) and was associated with increased risk of incident CVD among those without diabetes (adjusted hazard ratio (aHR) 1.22, 95% CI 1.03-1.43, p = 0.02). Although a similar trend was observed in participants with diabetes it did not reach statistical significance (aHR 1.31, 95% CI 0.84-2.05, p = 0.23)., Conclusions: Elevated non-fasting RC predicted increased CVD risk in middle and older-aged adults without diabetes; similar trends were observed in participants with diabetes and require further testing in a larger sample., (© 2023 The Authors. Diabetic Medicine published by John Wiley & Sons Ltd on behalf of Diabetes UK.)

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. A generalized estimating equation model was used to examine the association (by incidence rate ratio [IRR]) between time-varying comorbidity profile and hospitalization and ER visits per year of follow-up after adjusting for sociodemographic factors, lifestyle behaviours, and historic health-care utilization in the previous 5 years., Results: Among 2,110 incident cases of diabetes (51.0% females; median age at diagnosis: 59.5 years; median follow-up: 7.19 years), the average number of Elixhauser comorbidities was 1.9±1.6 in the first year of diagnosis and 3.3±2.0 in year 15 after diagnosis. The number of comorbidities in the previous year was positively associated with risk of hospitalization (IRR=1.33 [95% confidence interval {CI}: 1.04 to 1.70] and 2.14 [95% CI: 1.67 to 2.74] for 1 or 2 and ≥2 comorbidities, respectively) and ER visits (IRR=1.31 [95% CI: 1.15 to 1.50] and 1.62 [95% CI: 1.41 to 1.87] for 1 or 2 and ≥2 comorbidities, respectively) in the subsequent year. Cardiovascular diseases, peripheral vascular diseases, cancer, liver disease, fluid and electrolyte disorders, and depression were the conditions most typically associated with increased health-care utilization., Conclusions: The number of comorbidities was a major risk factor of health-care utilization for people with diabetes. Vascular diseases, cancer, and conditions closely related to diabetic frailty (e.g. fluid and electrolyte disorders and depression) were the main drivers of hospital care and ER visits., (Copyright © 2023 Canadian Diabetes Association. Published by Elsevier Inc. All rights reserved.)

Objectives: To characterise the sex-specific difference in the association between anthropometric changes and risk of diabetes in the general population in Canada., Setting and Participants: From 2000 to 2008, Alberta's Tomorrow Project (ATP) invited Alberta's residents aged 35-69 years to a prospective cohort study. A total of 19 655 diabetes-free ATP participants having anthropometrics measured at the baseline and follow-ups were included., Design and Outcome Measures: A longitudinal study design was used to examine the association between anthropometric changes and risk of diabetes and the sex difference in this association. Changes in weight, body mass index (BMI), waist circumference (WC) and waist-hip-ratio (WHR) were calculated as the difference between baseline and follow-up measures. Diabetes cases were identified using the Canadian National Diabetes Surveillance System algorithm with administrative healthcare data (2000-2015) linked to the ATP cohort. The sex-specific association between anthropometric changes and incidence of diabetes were examined by multivariable Cox regression models., Results: Changes in weight, BMI, WC and WHR over time were positively associated with incidence of diabetes in both men and women. The sex difference in risk of diabetes associated with 1 standard deviation (SD) increase in anthropometrics was 0.07 (95% CI -0.02 to 0.14) for weight, 0.08 (95% CI -0.03 to 0.17) for BMI, 0.07 (95% CI -0.02 to 0.15) for WC and 0.09 (95% CI 0.03 to 0.13) for WHR. Similar results were found in sex difference in the associations with changes per 5% and changes per categories (5% loss, ±5%, 5% gain)., Conclusions: The positive association between anthropometric changes and risk of diabetes was generally stronger in men than in women. However, this sex-specific difference of approximately 10% of the total risk associated with anthropometric changes had limited significance. For population-based public health programmes aiming to control obesity and incidence of diabetes, it may not be necessary to set up sex-specific goals for anthropometric reduction., Competing Interests: Competing interests: None declared., (© Author(s) (or their employer(s)) 2019. Re-use permitted under CC BY-NC. No commercial re-use. See rights and permissions. Published by BMJ.)

Aims: Previous observational studies using administrative health records have suggested an increased risk of diabetes with use of antibiotics. However, unmeasured confounding factors may explain these results. This study characterized the association between systemic use of antibiotics and risk of diabetes in a cohort of adults in Canada, accounting for both clinical and self-reported disease risk factors., Materials and Methods: In this nested case-control study, we used data from Alberta's Tomorrow Project (ATP), a longitudinal cohort study in Canada, and the linked administrative health records (2000-2015). Incident cases of diabetes were matched with up to 8 age and sex-matched controls per case. Conditional logistic regression was used to examine the association between antibiotic exposures and incident diabetes after sequentially adjusting for important clinical and lifestyle factors., Results: This study included 1676 cases of diabetes and 13 401 controls. Although 17.9% of cases received more than 5 courses of antibiotics, compared to 13.8% of controls (P < .0001), the association between antibiotic use and risk of diabetes was progressively reduced as important clinical and lifestyle factors were accounted for. In fully adjusted models, compared to participants with 0 to 1 courses of antibiotics, participants receiving more antibiotics had no increased risk of diabetes [Odds Ratio, 0.97 (0.83-1.13) for 2 to 4 courses and 0.98 (0.82-1.18) for ≥5 courses]., Conclusions: After adjustment for clinical and difficult-to-capture lifestyle data, we found no association between systemic use of antibiotics and risk of diabetes. Our results suggest that those positive associations observed in previous studies using only administrative records might have been confounded., (© 2017 John Wiley & Sons Ltd.)

Although obesity is a known risk factor for diabetes, the impact of body mass index (BMI) changes over time, especially BMI reduction, on diabetes development is less than clear. The objective of this study is to characterize the association between BMI changes over time and incidence of diabetes in a cohort of adults in Alberta. From 2000 to 2008, Alberta's Tomorrow Project (ATP) enrolled participants aged 35-69 to a population-based prospective cohort study. BMI was calculated from self-reported height and weight; change in BMI (∆BMI) was calculated as the difference between baseline and follow-up measurements. Diabetes cases were identified using the Canadian National Diabetes Surveillance System algorithm applied to linked administrative data (2000-2015). Multivariable Cox regression was used to examine the association between ∆BMI and incidence of diabetes. In a subset of the ATP cohort (n=19,164), 1168 incident cases of diabetes were identified during 198,853person-years of follow-up. Overall, BMI increase was associated with increased risk and BMI reduction was associated with reduced risk of diabetes. Particularly, compared to minimal BMI change (±5%), moderate (5%-10%) reduction in BMI was associated with 34% (95% CI: 12%-51%) reduction in risk of diabetes in participants with obesity; whereas 10% or greater increase in BMI was associated with an increased risk of diabetes of 64% or more in participants with overweight and obesity; in participants with normal and underweight, BMI changes was not apparently associated with risk of diabetes. Public health programs promoting weight loss, even at a moderate extent, would reduce risk of diabetes., (Copyright © 2017 Elsevier Inc. All rights reserved.)