Habitudes de vie et contrôle glycémique chez des adultes atteints de diabète de type 1 : des barrières envers l’activité physique au calcul des glucides

Le diabète de type 1 (DT1) est une maladie complexe qui requiert une implication importante des patients pour contrôler leur glycémie et ainsi prévenir les complications et comorbidités. L’activité physique (AP) régulière et une attention constante pour les glucides ingérés sont des adjuvants essentiels au traitement insulinique. Nous avons démontré que le questionnaire BAPAD-1, spécifiquement développé pour des adultes atteints de DT1, est un outil valide (validité prédictive, fiabilité interne et reproductibilité) pour définir des barrières associées à l’AP. Bien que le niveau de barrières envers l’AP soit faible, la crainte de l’hypoglycémie est la barrière la plus importante chez cette population. L’adoption d’un mode de vie actif est associée à un profil corporel favorable. Les adultes, avec un DT1 et non diabétique, qui maintiennent un bon niveau d’AP, soit un ratio entre la dépense énergétique totale et celle au repos ≥ 1.7, ont une masse grasse, un indice de masse corporelle et un tour de taille significativement inférieurs à ceux d’adultes moins actifs. Le niveau d’AP peut être estimé au moyen d’un moniteur d’AP comme le SenseWear Armband™. Afin de compléter les études de validation de cet outil, nous avons évalué et démontré la reproductibilité des mesures. Toutefois, la dépense énergétique est sous-estimée durant les 10 premières minutes d’une AP d’intensité modérée sur ergocycle. L’utilisation de cet appareil est donc justifiée pour une évaluation de la dépense énergétique sur de longues périodes. Le calcul des glucides est une méthode largement utilisée pour évaluer la quantité d’insuline à injecter lors des repas. Nous avons évalué dans un contexte de vie courante, sans révision de la technique, la précision des patients pour ce calcul. L’erreur moyenne est de 15,4 ± 7,8 g par repas, soit 20,9 ± 9,7 % du contenu glucidique. L’erreur moyenne est positivement associée à de plus grandes fluctuations glycémiques mesurées via un lecteur de glucose en continu. Une révision régulière du calcul des glucides est probablement nécessaire pour permettre un meilleur contrôle glycémique. Nous avons développé et testé lors d’un essai clinique randomisé contrôlé un programme de promotion de l’AP (PEP-1). Ce programme de 12 semaines inclut une séance hebdomadaire en groupe ayant pour but d’initier l’AP, d’établir des objectifs et d’outiller les adultes atteints de DT1 quant à la gestion de la glycémie à l’AP. Bien que n’ayant pas permis d’augmenter la dépense énergétique, le programme a permis un maintien du niveau d’AP et une amélioration de la condition cardio-respiratoire et de la pression artérielle. À la fin du programme, une plus grande proportion de patients connaissait la pharmacocinétique de l’insuline et une plus grande variété de méthodes pour contrer l’hypoglycémie associée à l’AP était utilisée. En conclusion, le diabète de type 1 engendre des défis quotidiens particuliers. D’une part, le calcul des glucides est une tâche complexe et son imprécision est associée aux fluctuations glycémiques quotidiennes. D’autre part, l’adoption d’un mode de vie actif, qui est associée à un meilleur profil de composition corporelle, est limitée par la crainte des hypoglycémies. Le programme PEP-1 offre un support pour intégrer l’AP dans les habitudes de vie des adultes avec un DT1 et ainsi améliorer certains facteurs de risque cardio-vasculaire.Type 1 diabetes (T1D) is a complex disease requiring continuous self-management. Physical activity (PA) and carbohydrate counting are essential counterparts to insulin therapy for blood glucose control in order to prevent complications and comorbidities. We have demonstrated the validity (predictive validity, internal validity and reproducibility) of the BAPAD-1 scale to assess perceived barriers associated with PA practice. Fear of hypoglycemia is the strongest perceived barrier among adults with T1D. An active lifestyle, as described by a physical activity level (ratio of total over resting energy expenditure) ≥ 1.7, is associated with a better body composition compared to less active adults. Adults who are more active show significantly less fat mass, smaller body mass index and smaller waist circumference. Motion sensors, like the SenseWear Armband™, are useful to estimate PA level. To complement prior validation studies, we evaluated and confirmed the reproducibility of the SenseWear Armband™ measurements. However, we also observed that energy expenditure is underestimated at the onset of moderate intensity ergocycling. Thus, this motion sensor should be used to evaluate energy expenditure over long periods of time rather than short length exercise. Carbohydrate counting is a widely used method to evaluate prandial insulin doses. We evaluated, in a real-life setting without prior method revision, the accuracy of adults with T1D for carbohydrate estimation. The mean meal error was 15.4 ± 7.8 g or 20.9 ± 9.7 % of total carbohydrate content. The mean meal error was positively associated with larger daily glucose fluctuations measured by a continuous glucose monitoring system. Regular educational tips regarding carbohydrate counting may be necessary to improve glycemic control. In order to improve PA practice, we developed and tested in a randomized controlled trial a PA promotion program (PAP-1). This 12-week program includes a weekly group session designed for PA initiation, goal setting and improving knowledge about glycemic control during PA. Even if the program failed to improve total energy expenditure, participants improved their cardiorespiratory fitness and blood pressure. At the end of the program, a larger proportion of the participants were knowledgeable of insulin pharmacokinetics and they used more various methods to prevent hypoglycemia related to PA. In conclusion, type 1 diabetes obtrudes many daily challenges. On one hand, carbohydrate counting is a complex job and its inaccuracy is associated with glycemic fluctuations. On the other hand, even if having an active lifestyle is associated with a better body composition, fear of hypoglycaemia may impede PA practice. The PAP-1 program offers support to adults with T1D to adopt an active lifestyle and thus improve some cardivascular risk factors

Correlates of sitting time in adults with type 2 diabetes

Abstract Background: Studies suggest a relationship between sitting time and cardiovascular disease mortality. Our aim was to identify socio-demographic, contextual, and clinical (e.g., body composition, diabetes duration) correlates of self-reported sitting time among adults with type 2 diabetes, a clinical population at high risk for cardiovascular disease. We sought to determine if there was an inverse relationship between sitting and step counts in a diabetes cohort in whom we had previously identified low step counts with further lowering in fall/winter. Methods: The cohort included 198 adults (54 % men; age 60.0 SD 11.5 years; Body mass index 30.4 SD 5.6 kg/

Non-severe hypoglycemia in type 1 diabetes: a randomized crossover trial comparing two quantities of oral carbohydrates at different insulin-induced hypoglycemia ranges

AimsNon-severe hypoglycemia (NS-H) is challenging for people living with type 1 diabetes (PWT1D) and often results from relative iatrogenic hyper-insulinemia. Current guidelines recommend a one-size-fits-all approach of 15–20 g of simple carbohydrates (CHO) every 15 min regardless of the triggering conditions of the NS-H event. We aimed to test different amounts of CHO to treat insulin-induced NS-H at various glucose ranges.MethodsThis is a randomized, four-way, crossover study involving PWT1D, testing NS-H treatment outcomes with 16 g vs. 32 g CHO at two plasma glucose (PG) ranges: A: 3.0–3.5 mmol/L and B: <3.0 mmol/L. Across all study arms, participants consumed an additional 16 g of CHO if PG was still <3.0 mmol/L at 15 min and <4.0 mmol/L at 45 min post-initial treatment. Subcutaneous insulin was used in a fasting state to induce NS-H. Participants had frequent venous sampling of PG, insulin, and glucagon levels.ResultsParticipants (n = 32; 56% female participants) had a mean (SD) age of 46.1 (17.1) years, had HbA1c at 54.0 (6.8 mmol/mol) [7.1% (0.9%)], and had a diabetes duration of 27.5 (17.0) years; 56% were insulin pump users. We compared NS-H correction parameters between 16 g and 32 g of CHO for range A, 3.0–3.5 mmol/L (n = 32), and range B, <3.0 mmol/L (n = 29). Change in PG at 15 min for A: 0.1 (0.8) mmol/L vs. 0.6 (0.9) mmol/L, p = 0.02; and for B: 0.8 (0.9) mmol/L vs. 0.8 (1.0) mmol/L, p = 1.0. Percentage of participants with corrected episodes at 15 min: (A) 19% vs. 47%, p = 0.09; (B) 21% vs. 24%, p = 1.0. A second treatment was necessary in (A) 50% vs. 15% of participants, p = 0.001; (B) 45% vs. 34% of participants, p = 0.37. No statistically significant differences in insulin and glucagon parameters were observed.ConclusionsNS-H, in the context of hyper-insulinemia, is difficult to treat in PWT1D. Initial consumption of 32 g of CHO revealed some advantages at the 3.0–3.5 mmol/L range. This was not reproduced at lower PG ranges since participants needed additional CHO regardless of the amount of initial consumption.Clinical trial registrationClinicalTrials.gov, identifier NCT03489967

Correlates of sitting time in adults with type 2 diabetes

Studies suggest a relationship between sitting time and cardiovascular disease mortality. Our aim was to identify socio-demographic, contextual, and clinical (e.g., body composition, diabetes duration) correlates of self-reported sitting time among adults with type 2 diabetes, a clinical population at high risk for cardiovascular disease. We sought to determine if there was an inverse relationship between sitting and step counts in a diabetes cohort in whom we had previously identified low step counts with further lowering in fall/winter

Relative Validation of an Artificial Intelligence–Enhanced, Image-Assisted Mobile App for Dietary Assessment in Adults: Randomized Crossover Study

BackgroundThorough dietary assessment is essential to obtain accurate food and nutrient intake data yet challenging because of the limitations of current methods. Image-based methods may decrease energy underreporting and increase the validity of self-reported dietary intake. Keenoa is an image-assisted food diary that integrates artificial intelligence food recognition. We hypothesized that Keenoa is as valid for dietary assessment as the automated self-administered 24-hour recall (ASA24)–Canada and better appreciated by users. ObjectiveWe aimed to evaluate the relative validity of Keenoa against a 24-hour validated web-based food recall platform (ASA24) in both healthy individuals and those living with diabetes. Secondary objectives were to compare the proportion of under- and overreporters between tools and to assess the user’s appreciation of the tools. MethodsWe used a randomized crossover design, and participants completed 4 days of Keenoa food tracking and 4 days of ASA24 food recalls. The System Usability Scale was used to assess perceived ease of use. Differences in reported intakes were analyzed using 2-tailed paired t tests or Wilcoxon signed-rank test and deattenuated correlations by Spearman coefficient. Agreement and bias were determined using the Bland-Altman test. Weighted Cohen κ was used for cross-classification analysis. Energy underreporting was defined as a ratio of reported energy intake to estimated resting energy expenditure <0.9. ResultsA total of 136 participants were included (mean 46.1, SD 14.6 years; 49/136, 36% men; 31/136, 22.8% with diabetes). The average reported energy intakes (kcal/d) were 2171 (SD 553) in men with Keenoa and 2118 (SD 566) in men with ASA24 (P=.38) and, in women, 1804 (SD 404) with Keenoa and 1784 (SD 389) with ASA24 (P=.61). The overall mean difference (kcal/d) was −32 (95% CI −97 to 33), with limits of agreement of −789 to 725, indicating acceptable agreement between tools without bias. Mean reported macronutrient, calcium, potassium, and folate intakes did not significantly differ between tools. Reported fiber and iron intakes were higher, and sodium intake lower, with Keenoa than ASA24. Intakes in all macronutrients (r=0.48-0.73) and micronutrients analyzed (r=0.40-0.74) were correlated (all P<.05) between tools. Weighted Cohen κ scores ranged from 0.30 to 0.52 (all P<.001). The underreporting rate was 8.8% (12/136) with both tools. Mean System Usability Scale scores were higher for Keenoa than ASA24 (77/100, 77% vs 53/100, 53%; P<.001); 74.8% (101/135) of participants preferred Keenoa. ConclusionsThe Keenoa app showed moderate to strong relative validity against ASA24 for energy, macronutrient, and most micronutrient intakes analyzed in healthy adults and those with diabetes. Keenoa is a new, alternative tool that may facilitate the work of dietitians and nutrition researchers. The perceived ease of use may improve food-tracking adherence over longer periods

Effect of diabetes technologies on the fear of hypoglycaemia among people living with type 1 diabetes: a systematic review and meta-analysisResearch in context

Summary: Background: Fear of hypoglycaemia (FOH) significantly disrupts the daily management of type 1 diabetes (T1D) and increases the risk of complications. Recent technological advances can improve glucose metrics and reduce hypoglycaemia frequency, yet their impact on FOH is unclear. This systematic review and meta-analysis (SRMA) aimed to synthesize the current literature to understand the impact of diabetes technologies on FOH in T1D. Methods: In this SRMA, we searched PubMed, Medline, Scopus, and Web of Science from inception up to May 21st, 2023 for studies assessing the effect of using real-time or intermittently scanned continuous glucose monitors (rtCGM or isCGM); insulin pumps (CSII); and their combinations on FOH as the primary outcome, measured using the Hypoglycaemia Fear Survey (HFS; including total, worries [HFS-W], and behaviours [HFS-B] scores), in non-pregnant adults with T1D. Data was extracted by the first and second authors. Results were pooled using a random-effects model based on study design (RCT and non-RCT), with subgroup analysis based on the type of technology, reported change in hypoglycaemia frequency, and duration of use. Risk of bias was evaluated with Cochrane and Joanna Briggs Institute tools. This study is registered with PROSPERO, CRD42021253618. Findings: A total of 51 studies (n = 8966) were included, 22 of which were RCTs. Studies on rtCGM and CSII reported lower FOH levels with ≥8 weeks of use. Studies on CSII and rtCGM combinations reported lower FOH levels after ≥13 weeks of automated insulin delivery (AID) use or 26 weeks of sensor-augmented pump (SAP) use. The meta-analysis showed an overall lower FOH with technologies, specifically for the HFS-W subscale. The RCT meta-analysis showed lower HFS-W scores with rtCGM use (standard mean difference [95%CI]: −0.14 [−0.23, −0.05], I2 = 0%) and AID (−0.17 [−0.33, −0.01], I2 = 0%). Results from non-RCT studies show that SAP users (−0.33 [−0.38, −0.27], I2 = 0%) and rtCGM users (−0.38 [−0.61, −0.14], I2 = 0%) had lower HFS-W. Interpretation: We found consistent, yet small to moderate, effects supporting that diabetes technologies (specifically rtCGM, SAP, and AID) may reduce hypoglycaemia-related worries in adults with T1D. Current literature, however, has limitations including discrepancies in baseline characteristics and limited, mainly descriptive, statistical analysis. Thus, future studies should assess FOH as a primary outcome, use validated surveys, and appropriate statistical analysis to evaluate the clinical impacts of technology use beyond just glucose metrics. Funding: Canadian Institutes of Health Research, Juvenile Diabetes Research Foundation Ltd

Associations of free sugars from solid and liquid sources with cardiovascular disease: a retrospective cohort analysis

Abstract Background The World Health Organization recommends a 10% total energy (TE%) limit for free sugars (i.e., added sugars and naturally occurring sugars in fruit juice, honey, and syrups) based on evidence linking higher intakes with overweight and dental caries. Evidence for cardiovascular disease (CVD) is limited. Impacts may differ by sex, age group, and solid vs. liquid sources; liquids may stimulate more adverse CVD profiles (due to their rapid absorption in the body along along with triggering less satiety). We examined associations of consuming total free sugars ≥ 10 TE% with CVD within four sex and age-defined groups. Given roughly equal free sugar intakes from solid and liquid sources, we also evaluated source-specific associations of free sugars ≥ 5 TE% thresholds. Methods In this retrospective cohort study, we estimated free sugars from 24-h dietary recall (Canadian Community Health Survey, 2004–2005) in relationship to nonfatal and fatal CVD (Discharge Abstract and Canadian Mortality Databases, 2004–2017; International Disease Classification-10 codes for ischemic heart disease and stroke) through multivariable Cox proportional hazards models adjusted for overweight/obesity, health behaviours, dietary factors, and food insecurity. We conducted analyses in separate models for men 55 to 75 years, women 55 to 75 years, men 35 to 55 years, and women 35 to 55 years. We dichotomized total free sugars at 10 TE% and source-specific free sugars at 5 TE%. Results Men 55 to 75 years of age had 34% higher CVD hazards with intakes of free sugars from solid sources ≥ 5 TE% vs. below (adjusted HR 1.34, 95% CI 1.05- 1.70). The other three age and sex-specific groups did not demonstrate conclusive associations with CVD. Conclusions Our findings suggest that from a CVD prevention standpoint in men 55 to 75 years of age, there may be benefits from consuming less than 5 TE% as free sugars from solid sources

Adaptation of an Adult Web Application for Type 1 Diabetes Self-management to Youth Using the Behavior Change Wheel to Tailor the Needs of Health Care Transition: Qualitative Interview Study

BackgroundYouth (aged 14-24 years) living with type 1 diabetes (T1D) encounter increased challenges in their diabetes self-management (DSM), especially during the transition to adult care. Although DSM education and support are imperative, there is insufficient information on how web-based digital tools tailored to their demands can be developed. ObjectiveOn the basis of the Behavior Change Wheel, this study aims to identify, among youth living with T1D, the needs and factors influencing their DSM in the context of health care transition and to inform the adaptation (content and features) of an adult self-guided web application (Support). MethodsInternet-based semistructured individual interviews based on a phenomenological study design were conducted with 21 youths, and transcripts were analyzed using an inductive approach with concept mapping. ResultsFactors influencing T1D self-management were categorized into barriers and facilitators and then as external or internal. Features influencing the accessibility to information, increasing the sense of support, and use of the tool were positively accepted. Features unrelated to their expectations of digital tool use or difficulty navigating were viewed negatively. Participants expressed an interest in reliable, practical, and novel educational content. Although youth considered the information provided by medical professionals to be important, peer exchange was deemed necessary to obtain a practical perspective and real-life examples. ConclusionsCompared with the adult population, in addition to tailored content and a simplified information search process, when building a DSM education and support digital tool for youth, features should be selected to encourage supervised peer exchange