The diabEAT Study: Insulin dElivery Technologies And eaTing Behaviours in People With Type 1 Diabetes

Обзор

Type 1 diabetes is an autoimmune health condition that requires daily injections of insulin. Insulin allows the body to use energy from carbohydrates in food. Disordered eating behaviours, like restricting food intake to lose body weight, are more common in women and people with type 1 diabetes, compared to those without because they must practice carbohydrate counting. Carbohydrate counting means identifying, measuring, and planning carbohydrate intake to match insulin dosage. New technologies, such as automated insulin delivery (AID) systems adjust insulin delivery in a blood sugar responsive manner. AID is rapidly replacing conventional insulin delivery like injections or non-automated insulin pumps since it reduces management burden and improves blood sugar levels. It is not known if AID reduces food management and disordered eating behaviours. This study aims to: 1. investigate the relationship between AID and eating behaviours according to gender for youth (12 to 17 years), and adults (18 years and older). 2. Determine the limit of carbohydrate counting inaccuracy to maintain stable blood sugar levels according to insulin delivery method (AID, injections, or pumps). It is hypothesized that those who use AID will have lower disordered eating behaviours and will maintain stable blood sugar levels while allowing for higher carbohydrate counting inaccuracy. This will be a cross-sectional cohort study of people with type 1 diabetes who are 12 years of age or over. Participants will be recruited through the BETTER registry and social medias across Canada. This research is needed to improve nutrition guidelines for type 1 diabetes in the context of new technologies like AID. Evidence from this study may reduce food management burden, lower the risk of disordered eating behaviours, and prevent eating disorders and medical complications.

Подробное описание

Introduction: Type 1 diabetes occurs when the pancreas cannot produce insulin and a person must be given insulin exogenously. Managing this health condition involves strict diet planning including carbohydrate counting (i.e. identifying and counting carbohydrates to match insulin dose). In addition, to high food management burden, frequent bodyweight monitoring, and weight gain related to insulin usage, makes people living with type 1 diabetes more susceptible to disordered eating behaviours (like intentional food restriction), compared to those without. Automated insulin delivery systems (AID), which automatically adjusts insulin as a response to continuously measured blood glucose levels has shown to improve quality of life, and improve glycemic levels, however it's impact on eating behaviours and diet is unknown. There is also a need to determine the carbohydrate counting inaccuracy threshold to maintain glycemic stability depending on the type of delivery system used (AID vs. Not).

Objectives:

1. Determine the relationship between AID and eating behaviours 2. Determine the carbohydrate counting inaccuracy threshold to maintain glycemic stability and understand whether AID use modifies this relationship.

Methods: This is an observational cross-section analysis of people with type 1 diabetes.

Eligibility criteria included: those living with type 1 diabetes for more than 1 year, using at least 2 insulin injections per day or using an insulin pump, who were living in Canada, 12 years of age or older, and using their current insulin delivery system for 3 months or more.

Participants are excluded if they were pregnant/currently breastfeeding and did not speak English or French.

Demographic, and diabetes-related information (including AID use), are determined through an initial questionnaire, which takes about 15 minutes to complete. Disordered eating behaviours were determined through validated questionnaires. The Three Factor Eating Questionnaire (TFEQR-21) identified behaviours such as cognitive restraint (score ranged from 6 to 24), emotional eating (score ranged from 6 to 24), and uncontrolled eating (score ranged from 9 to 36). The Diabetes Eating Problem Survey Revised (DEPS-R) identified DEBs specific to diabetes (score ranged from 0 to 80 with \> 20 representing those at risk of DEB). The Teruel Orthorexia Scale (TOS) identified orthorexia nervosa behaviours defined as an obsession with healthy eating which may lead to emotional impairments (score ranged from 0 to 24).

Dietary intake information will be collected through a 4 day picture food journal (3 weekdays and 1 weekend) application called Keenoa and analyzed by a Registered Dietitian.

Glycemic outcomes such as glucose time in range (TIR), which measures the amount of time glucose levels are between 3.9-10.0mmol/L, and Coefficient Variation, were reported through a 14 day CGM report (Clarity, Dexcom, Medtronic).

Physical activity will be measured through an Actigraph GT3X for 8 days.

Descriptive analysis will be completed at enrollment, to determine the mean (SD) socio-demographic information, eating behaviour scores and dietary intake (macro/micronutrient profile) by insulin delivery system (AID and injections/insulin pumps).

Multivariate linear regression will be used to determine the relationship between AID compared to injections/insulin pumps and disordered eating behaviour scores.

Secondly, carbohydrate counting inaccuracy will be determined by comparing participant reported carbohydrate counts measured in mean (SD) grams per meal to RD measured carbohydrate counts by analyzing 4-day dietary reports, as generated by Keenoa.

Carbohydrate counting inaccuracy threshold will be determined through multivariate linear regression by exploring the relationship between percent carbohydrate counting inaccuracy and % of glucose Time in Range and Coefficient Variation. Type of insulin delivery will be used as an effect modifier to determine how this relationship is modified by AID and injections/insulin pumps.

Вмешательства

• Устройство Automated Insulin Delivery (AID) Systems
  AID automatically adjusts insulin delivery by using continuously measured blood glucose levels. AID use will be determined through the initial questionnaire through the following questions: Do you currently use the pump as an automated insulin delivery system (connected to a CGM with automated insulin adjustments)? Yes, a commercial AID with control IQ (Tandem) or SmartGuard (Medtronic) Yes, a non-commercial open-source do-it yourself AID (e.g., Loop) No, they use it as a manual (non-automated)
• Поведенческое Carbohydrate Counting Inaccuracy Percentage
  Carbohydrate counting inaccuracy: will be determined by subtracting the estimated carbohydrates (by participant) by the actual amount of carbohydrate (through diet analysis) divided by the actual amount of carbohydrate, multiplied by 100, to determined the percentage. Estimated carbohydrate counts will be entered at each meal and snack by the participant in a daily log provided to the participant. Carbohydrate amounts will be collected through a 4-day food diary through the phone application Kee

Первичные конечные точки

• Disordered Eating Behaviours [Срок оценки: Collected at one time point per participant at the time of survey completion. The study has an observational, cross-sectional design from April 2024 to estimated May 2026.]
• Diabetes Disordered Eating Behaviours [Срок оценки: Collected at one time point per participant at the time of survey completion. The study has an observational, cross-sectional design from April 2024 to estimated May 2026]
• Orthorexia Eating Behaviours [Срок оценки: Collected at one time point per participant at the time of survey completion. The study has an observational, cross-sectional design from April 2024 to estimated May 2026]

Вторичные конечные точки (2)

• Glucose Time In Range (TIR) [Срок оценки: Collected at one time point per participant at the time of survey completion. The study has an observational, cross-sectional design from April 2024 to estimated May 2026.]
• Coefficient of Variation (CV) [Срок оценки: Collected at one time point per participant at the time of survey completion. The study has an observational, cross-sectional design from April 2024 to estimated May 2026.]

Критерии участия

Критерии включения

• 12 years of age or older
• Living in Canada
• Living with type 1 diabetes for more than 1 year
• Using at least 2 insulin injections per day or using an insulin pump
• Using current insulin delivery system for 3 months or more

Критерии исключения

• Are pregnant or currently are breastfeeding
• Don't speak French or English
• Does not have a smart phone (to download applications)

Критерии приведены из реестра в оригинале (на английском). Окончательную оценку соответствия проводит исследовательский центр.

Здоровые добровольцы: Да

Дизайн исследования

Модель наблюдения

Когортное

Центры проведения

Канада · 1 центр

• McGill University — Montreal

Публикации

• Aiello EM, Deshpande S, Ozaslan B, Wolkowicz KL, Dassau E, Pinsker JE, Doyle FJ. Review of Automated Insulin Delivery Systems for Individuals with Type 1 Diabetes: Tailored Solutions for Subpopulations. Curr Opin Biomed Eng. 2021 Sep;19:100312. doi: 10.1016/j.cobme.2021.100312. Epub 2021 Jun 18. PMID 34368518
• Bell KJ, Barclay AW, Petocz P, Colagiuri S, Brand-Miller JC. Efficacy of carbohydrate counting in type 1 diabetes: a systematic review and meta-analysis. Lancet Diabetes Endocrinol. 2014 Feb;2(2):133-40. doi: 10.1016/S2213-8587(13)70144-X. Epub 2013 Oct 25. PMID 24622717
• Boughton CK, Hovorka R. Automated Insulin Delivery in Adults. Endocrinol Metab Clin North Am. 2020 Mar;49(1):167-178. doi: 10.1016/j.ecl.2019.10.007. Epub 2019 Dec 16. PMID 31980116
• Brazeau AS, Mircescu H, Desjardins K, Leroux C, Strychar I, Ekoe JM, Rabasa-Lhoret R. Carbohydrate counting accuracy and blood glucose variability in adults with type 1 diabetes. Diabetes Res Clin Pract. 2013 Jan;99(1):19-23. doi: 10.1016/j.diabres.2012.10.024. Epub 2012 Nov 10. PMID 23146371
• Bryant EJ, Thivel D, Chaput JP, Drapeau V, Blundell JE, King NA. Development and validation of the Child Three-Factor Eating Questionnaire (CTFEQr17). Public Health Nutr. 2018 Oct;21(14):2558-2567. doi: 10.1017/S1368980018001210. Epub 2018 May 15. PMID 29759100
• Builes-Montano CE, Ortiz-Cano NA, Ramirez-Rincon A, Rojas-Henao NA. Efficacy and safety of carbohydrate counting versus other forms of dietary advice in patients with type 1 diabetes mellitus: a systematic review and meta-analysis of randomised clinical trials. J Hum Nutr Diet. 2022 Dec;35(6):1030-1042. doi: 10.1111/jhn.13017. Epub 2022 May 11. PMID 35436364
• Cappelleri JC, Bushmakin AG, Gerber RA, Leidy NK, Sexton CC, Lowe MR, Karlsson J. Psychometric analysis of the Three-Factor Eating Questionnaire-R21: results from a large diverse sample of obese and non-obese participants. Int J Obes (Lond). 2009 Jun;33(6):611-20. doi: 10.1038/ijo.2009.74. Epub 2009 Apr 28. PMID 19399021
• Castle JR, El Youssef J, Wilson LM, Reddy R, Resalat N, Branigan D, Ramsey K, Leitschuh J, Rajhbeharrysingh U, Senf B, Sugerman SM, Gabo V, Jacobs PG. Randomized Outpatient Trial of Single- and Dual-Hormone Closed-Loop Systems That Adapt to Exercise Using Wearable Sensors. Diabetes Care. 2018 Jul;41(7):1471-1477. doi: 10.2337/dc18-0228. Epub 2018 May 11. PMID 29752345

Идентификаторы

NCT: NCT07348432 · 23-07-045

Первоисточники (государственные реестры)

• ClinicalTrials.gov (NIH, США)

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