Insulin Dependent Diabetes MellitusNCT07348432
The diabEAT Study: Insulin dElivery Technologies And eaTing Behaviours in People With Type 1 Diabetes
An observational study of Insulin Dependent Diabetes Mellitus and Feeding and Eating Disorders, run by McGill University at 1 site in Canada.
Trial summary
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… Read more about this study
- Who is it for?
- Ages 12 years and olderHealthy volunteers can take part
- Conditions the study is for
- Insulin Dependent Diabetes Mellitus, Feeding and Eating Disorders, Eating Behavior
- What is being tested?
- Automated Insulin Delivery (AID) Systems and Carbohydrate Counting Inaccuracy Percentage
- Type of treatment
- Injection or infusion, Medical device, Lifestyle or therapy programme
- How many people
- 106 participants
- Where
- 1 siteCanada
- Study dates
- 29 Jul 2024to 30 Apr 2027
- Phase
- Observational
Key requirements
Who can take part, as listed by the sponsor. Only the study team can confirm whether you are eligible, so take this list to your doctor.
- Ages 12 years and older
- All sexes
- Healthy volunteers accepted
- Child, Adult, Older adult
Study population: People living with type 1 diabetes
Who may be able to join
- 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
Who cannot join
- Are pregnant or currently are breastfeeding
- Don't speak French or English
- Does not have a smart phone (to download applications)
Trial locations and contacts
1 site in 1 country. Contact the study team or a site near you to ask about taking part.
Canada1 site, 1 recruiting
- Recruiting
McGill University
Montreal, Quebec, H9X 3V9
Anne-Sophie Brazeau, PhD
About this study
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.
Read the detailed description
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:
- Determine the relationship between AID and eating behaviours
- 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.
- Conditions
- Insulin Dependent Diabetes Mellitus, Feeding and Eating Disorders, Eating Behavior, Type 1 Diabetes, Autoimmune Diseases, Endocrine System Diseases
- Being tested
- Automated Insulin Delivery (AID) Systems, Carbohydrate Counting Inaccuracy Percentage
- Keywords
- Automated Insulin Delivery, Disordered Eating Behaviours, Nutrition, Type 1 Diabetes
- Medical subject headings
- Diabetes Mellitus, Type 1, Feeding and Eating Disorders, Feeding Behavior, Autoimmune Diseases, Endocrine System Diseases
What participants receive
What participants receive. In a randomised study each person is assigned to one group by chance.
Automated Insulin Delivery (AID) SystemsDevice
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) pump or with a suspend on low functionality (e.g., Basal IQ) I prefer not to answer I don't know
The type of AID system (hybrid, advanced hybrid, etc.) will also be confirmed.
The exposure variable will be coded as a binary-categorical variable of AID use (yes or no) with no representing all other non-AID insulin pumps or injections.
Carbohydrate Counting Inaccuracy PercentageBehavioural
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 Keenoa (carb count from the app will be blinded to the participant), and reviewed by a research assistant with education in dietetics.
What is being measured
The primary outcome is the main question the study is designed to answer.
Disordered Eating Behaviours
The primary outcome variable disordered eating behaviours will be measured through the Three Factor Eating Questionnaire-Revised 21 (TFEQ) in adults. The primary outcome for youth (12 to 17y) is the Child Three Factor Eating Questionnaire 17, which is an adapted questionnaire from the TFEQ.
TFEQ refers to current dietary practice and measures 3 different aspects of eating behaviour: cognitive dietary restraint (conscious restriction of food intake) score ranges from 6 to 24, uncontrolled eating (tendency to eat more than usual due to loss of control over intake accompanied by subjective feelings of hunger) score ranges from 9 to 36, and emotional eating (inability to resist emotional cues) score ranges from 6 to 24. Higher scores in the respective scales indicate greater level of restrained, uncontrolled, or emotional eating.
Measured: 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
The Diabetes Eating Problem Survey (DEPS-R) is a 16-item questionnaire for youth and adults over the age of 12 years. It refers to disordered eating behaviours specific to people with type 1 diabetes. The score ranges from 0 to 80, with a higher score indicating higher risk of disordered eating.
Measured: 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
The Teruel Orthorexia Scale is a 17-item questionnaire, that is validated in both English and French. It measures 'healthy orthorexia' behaviours as well as behaviours related to 'orthorexia nervosa'. Healthy orthorexia describes individuals who have a high interest in healthy eating, but in a non-pathological dimension of orthorexia. This sub scales score ranges from 0 to 27. Orthorexia nervosa includes behaviours that are related to healthy eating that may cause malnutrition, emotional distress, and social impairment. This subscale ranges from 0 to 24. A higher score represents more orthorexia symptoms.
Measured: 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
Secondary outcomes (2)
Glucose Time In Range (TIR)
Time in Range (TIR) (%): glucose TIR is the percentage of time that glucose levels are between 3.9 and 10.0 mmol/L. A higher TIR indicates improved glycemic levels. Guidelines recommend a TIR greater than 70% for most PwT1D.
Measured: 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)
Coefficient of Variation (CV) is determined by dividing the standard deviation of blood glucose levels over a 14-day period, by the total mean glucose and multiplying by 100 to obtain a percentage. This value reflects the variability of glucose levels. A higher CV value indicates more glycemic variability.
Measured: 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.
Timeline
From the start of the study to its completion; the mark is today. Estimated dates are the sponsor’s plan.
- First posted16 Jan 2026
- Study start29 Jul 2024
- Primary completion31 Oct 2026 (estimated)
- Study completion30 Apr 2027 (estimated)
Resources
- Official record on ClinicalTrials.govThe registry entry this page is built from, with its full change history.
- Publications (28)Papers the sponsor has linked to this study.
- Other trials for Insulin Dependent Diabetes MellitusStudies of the same condition, open and under way.
- What the trial phases meanHow a treatment moves from first tests in people to approval.
More details
For doctors and researchers: how the study is designed, who runs it, and its registry IDs.
Study design
- Study type
- Observational
- Observational model
- Cohort
- Time perspective
- Cross-sectional
- Enrolment
- 106 participants (estimated)
Sponsor and investigators
- Lead sponsor
- McGill University
- Sponsor type
- University, hospital or other
- Collaborators
- Laval University, Université de Montréal, University of Windsor
- Responsible party
- Principal investigator, Anne-Sophie Brazeau, McGill University
- Investigators
- Anne-Sophie Brazeau, PhD, Principal investigator, McGill University
IDs, dates and publications
- ClinicalTrials.gov ID
- NCT07348432
- Sponsor's protocol ID
- 23-07-045
- Status last verified
- Jan 2026
- First submitted
- 22 Sep 2025
- Last updated
- 9 Oct 2026
- Results posted
- No
- FDA-regulated drug
- No
- FDA-regulated device
- No
- Individual data sharing
- No: Deidentified data may be shared to other researchers upon request in order to ensure the study results are reproducible.
Publications
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.
PubMed 34368518Bell 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.
PubMed 24622717Boughton 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.
PubMed 31980116Brazeau 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.
PubMed 23146371Bryant 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.
PubMed 29759100Builes-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.
PubMed 35436364Cappelleri 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.
PubMed 19399021Castle 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.
PubMed 29752345Dong D, Jackson T, Wang Y, Chen H. Spontaneous regional brain activity links restrained eating to later weight gain among young women. Biol Psychol. 2015 Jul;109:176-83. doi: 10.1016/j.biopsycho.2015.05.003. Epub 2015 May 21.
PubMed 26004091Frappier I, Jacob R, Panahi S, Larose D, Bryant EJ, Chaput JP, Thivel D, Drapeau V. Translation and validation of the Child Three-Factor Eating Questionnaire (CTFEQr17) in French-speaking Canadian children and adolescents. Public Health Nutr. 2022 Mar;25(3):543-553. doi: 10.1017/S136898002100392X. Epub 2021 Sep 10.
PubMed 34503600Fuchs J, Hovorka R. Closed-loop control in insulin pumps for type-1 diabetes mellitus: safety and efficacy. Expert Rev Med Devices. 2020 Jul;17(7):707-720. doi: 10.1080/17434440.2020.1784724. Epub 2020 Jul 3.
PubMed 32569476Gagnon C, Aimé A, Bélanger C. French Validation of the Diabetes Eating Problem Survey-Revised (DEPS-R). Can J Diabetes. 2013;37(1):60. doi:10.1016/j.jcjd.2013.03.009
Hays NP, Roberts SB. Aspects of eating behaviors "disinhibition" and "restraint" are related to weight gain and BMI in women. Obesity (Silver Spring). 2008 Jan;16(1):52-8. doi: 10.1038/oby.2007.12.
PubMed 18223612Hanlan ME, Griffith J, Patel N, Jaser SS. Eating Disorders and Disordered Eating in Type 1 Diabetes: Prevalence, Screening, and Treatment Options. Curr Diab Rep. 2013 Sep 12:10.1007/s11892-013-0418-4. doi: 10.1007/s11892-013-0418-4. Online ahead of print.
PubMed 24022608Kahkoska AR, Mayer-Davis EJ, Hood KK, Maahs DM, Burger KS. Behavioural implications of traditional treatment and closed-loop automated insulin delivery systems in Type 1 diabetes: applying a cognitive restraint theory framework. Diabet Med. 2017 Nov;34(11):1500-1507. doi: 10.1111/dme.13407. Epub 2017 Sep 11.
PubMed 28626906