- ICH GCP
- US Clinical Trials Registry
- Clinical Trial NCT07278063
Impact of Dietary Fat and Menstrual Cycle Phases in Type 1 Diabetes (DIABETEXX/3)
Effect of Gender and Meal Composition on the Postprandial Glycemic Response in People With Type 1 Diabetes: Impact of Fat Content and Menstrual Cycle Phases
This clinical trial aims to evaluate how variations in dietary fat content and hormonal status influence postprandial glycemic response in individuals with type 1 diabetes (T1D), with a special focus on women. The main objective is to clarify the impact of both factors individually and their interaction, which could inform more personalized strategies for insulin adjustment, optimizing glycemic control, and improving patient outcomes.
The main objective is to investigate the effects of low-fat versus high-fat meals, sex, menstrual cycle phases, and their interaction on postprandial glycemic control in adults with T1D treated with advanced hybrid closed-loop (AHCL) insulin delivery systems.
Specifically, the study will:
- Compare postprandial glycemic responses after standardized low and high-fat meals in men and women with T1D.
- Assess the differences in postprandial glycemic responses between early follicular and late luteal phases in women, using standardized meals with low and high fat content.
- Identify sex-related differences in glycemic response after equivalent meals.
This research addresses the unmet clinical need for precise, tailored postprandial insulin dosing recommendations, especially among women whose insulin sensitivity fluctuates with menstrual phases. The results may contribute to sex-specific predictive models in AHCL systems, reducing acute complications and improving overall quality of life.
This is a randomized controlled crossover trial in which each participant serves as her/his own control. Fifty adults will be enrolled: 25 women and 25 men. Women will undergo four mixed-meal tests in random order:
- low-fat given during the early follicular phase,
- high-fat given during the early follicular phase,
- low-fat given during the late luteal phase,
- high-fat given during the late luteal phase. The menstrual phase will be confirmed with home-based hormonal monitoring devices that function with urine sample and use a single-use test wand (MIRA system).
Men will complete two mixed-meal tests (low-fat and high-fat), in randomized order.
All meals will be standardized for carbohydrate content and matched in other macronutrients, except for fat (with a 30-40g difference), administered after an 8-hour fast. The day of the mixed meal test, AHCL systems will be switched from automatic to manual mode just before eating to standardize the prandial insulin dose and to avoid differences in insulin infusion rates in the postprandial state due to algorithm compensations. Continuous glucose monitoring (CGM) and hourly capillary glucose testing will measure the postprandial response. Additional fasting blood samples will assess metabolic, hormonal, and lipid markers. Optional gastric emptying studies may be performed to exclude confounding gastroparesis in selected patients.
Participants will be recruited from the endocrinology outpatient unit of La Fe Polytechnic University Hospital . The projected recruitment period is from December 2025 to July 2027, with mixed-meal tests and data collection occurring between January 2026 and December 2027. Women are expected to complete the protocol in 6 weeks (4 tests), while men will require about 2 weeks (2 tests).
At baseline, participants will undergo blood tests to rule out endocrine disorders and confirm sex hormone status. Women participating in the study will use the MIRA home device to monitor their hormonal levels, allowing them to accurately determine and record the phases of their menstrual cycle as part of the study protocol. During meal tests, CGM (Freestyle Libre 3) will be used uniformly among subjects.
The study dependent variables will be the following:
- Postprandial glucose area under the curve - AUC_PG_5h
- Mean glucose level - MG
- Continuous glucose monitoring metrics - TIR, TAR, TBR
- Postprandial glucose standard deviation - SD
- Postprandial glucose coefficient of variation - CV
- Mean amplitude of glycemic excursions - MAGE
- Mean of daily differences (MODD)
Independent variables are
- Type of food: Meals with either low or high fat content.
- Sex and Hormonal status: men; women during the early follicular phase; women during the late luteal phase.
If successful, this study will inform the development of more sophisticated, individualized insulin dosing algorithms and AHCL system improvements, especially for women with T1D. Results may lead to more effective management strategies, reduced GV, lower incidence of complications, and increased quality of life. Insights may directly support the personalization of diabetes care and improve gender equity in treatment standards.
Study Overview
Status
Conditions
Intervention / Treatment
Detailed Description
Each female participant will initiate the protocol with the first mixed meal test during the luteal phase, using the MIRA home device to monitor their hormonal levels. This approach is intended to guarantee accurate assessment of menstruation, and assures the realization of the second mixed meal test in the subsequent follicular phase without interruption in all enrolled subjects..
The meaning of starting in the luteal phase is to avoid potential delays or absence of the menstrual cycle that could occur if randomization began in the follicular phase, which could render the planned sequence infeasible.
Randomization will be performed regarding the type of mixed meal administered: either high-fat or low-fat. Block randomization will be employed: 50% of participants commence with the low-fat meal, while the remaining 50% begin with the high-fat meal. This method is used to maintain balance between groups and to reduce allocation bias throughout the study.
The sample size calculation for this study was based on prior research evaluating postprandial glucose responses and the impact of menstrual cycle phases. Differences in glucose and glucose area under the curve (AUC) from mixed meals with varying fat content, as well as between menstrual phases, informed expected effect sizes. Assuming an intra-subject standard deviation of 25 mg/dl, a correlation of 0.5 between repeated measures, and an expected interaction effect of 20 mg/dl, a total of 50 participants (25 women and 25 men) is needed to achieve 80% statistical power with an alpha of 0.05. This ensures adequate power to detect meaningful differences in the postprandial glucose response measured by AUC according to meal fat content and menstrual cycle phase.
The study keeps the advanced hybrid closed-loop (AHCL) system active during the baseline period to maintain usual insulin delivery and ensure similar glucose concentrations just before the meal test and also during the previous hours. At the time of the mixed meal test, the system is switched to open-loop mode to standardize insulin dosing across all participants. This will prevent the pump from making automated insulin corrections to glucose excursions during the test, which would compensate, at least partially, the possible differences induced by the factors object of the investigation. The HCL systems will be maintained in the open-loop (manual) configuration from time 0 (prandial bolus administration) to the end of the study 5h after. The prandial insulin dose will be based on the usual individual insulin to carbohydrate ratio, while basal insulin will be infused at the planned safety mode rates (those rates programmed by the physician at which the systems infuse when it shift from the automatic to the manual mode). Importantly, both parameters (insulin to carbohydrate ratio and manual basal rates) will be optimized for each patient before the commencement of the meal tests and kept constant during the study participation.
This approach will help ensure similar preprandial glycemia between subjects, avoids confounding factors introduced by adaptive insulin delivery and will allow accurate assessment of the effects of meal composition and hormonal status on postprandial glucose response. Maintaining insulin dosing standardization is essential to isolate the variables under study without interference from the AHCL system's automatic glucose adjustments.
Study Type
Enrollment (Estimated)
Phase
- Not Applicable
Contacts and Locations
Study Contact
- Name: Paolo Rossetti, Medicine
- Phone Number: +34608109913
- Email: rossetti_paolo@gva.es
Study Contact Backup
- Name: Olga Seguí, Medicine
- Phone Number: +34680705127
- Email: oseguicot@gmail.com
Study Locations
-
-
Valencia
-
Valencia, Valencia, Spain, 46026
- Hospital la Fé
-
Contact:
- Paolo Rossetti, Medicine
- Phone Number: +34608109918
- Email: prossetti73@gmail.com
-
Principal Investigator:
- Paolo Rossetti, Medicine
-
Contact:
- Olga Seguí, Medicine
- Phone Number: +34680705127
- Email: oseguicot@gmail.com
-
Sub-Investigator:
- Olga Seguí, Medicine
-
-
Participation Criteria
Eligibility Criteria
Ages Eligible for Study
- Adult
Accepts Healthy Volunteers
Description
Inclusion Criteria:
- Patients with a confirmed diagnosis of type 1 diabetes mellitus for more than 2 years, in treatment with AHCL (Advanced Hybrid Closed Loop) system treatment for at least 6 months.
- Both sexes.
- Metabolic control with HbA1c <8%.
- BMI between 18.5 and 29.99 (normal weight to overweight).
- For women: regular menstrual cycles (21-35 days in length with variation between cycles of <4 days) and no use of hormonal contraceptive treatment.
Exclusion Criteria:
- Diagnosis of diabetic gastroparesis.
- Presence of hypogonadism, anovulation, hyperandrogenism, hyperprolactinemia, pregnancy, or decompensated chronic diseases.
- Use of oral medications that alter glucose metabolism.
Study Plan
How is the study designed?
Design Details
- Primary Purpose: Treatment
- Allocation: Randomized
- Interventional Model: Crossover Assignment
- Masking: Single
Arms and Interventions
Participant Group / Arm |
Intervention / Treatment |
|---|---|
|
Other: Female1
Female patients in early follicular phase
|
The patients will eat a standardized meal designed to evaluate how their blood glucose responds to food intake under controlled conditions. This meal contains a balanced proportion of carbohydrates, proteins, and a low fat content.
The patients will eat a standardized meal designed to evaluate how their blood glucose responds to food intake under controlled conditions.
This meal contains a balanced proportion of carbohydrates, proteins, and a high fat content.
|
|
Other: Female2
Female patients in late luteal phase
|
The patients will eat a standardized meal designed to evaluate how their blood glucose responds to food intake under controlled conditions. This meal contains a balanced proportion of carbohydrates, proteins, and a low fat content.
The patients will eat a standardized meal designed to evaluate how their blood glucose responds to food intake under controlled conditions.
This meal contains a balanced proportion of carbohydrates, proteins, and a high fat content.
|
|
Other: Male
Male patients
|
The patients will eat a standardized meal designed to evaluate how their blood glucose responds to food intake under controlled conditions. This meal contains a balanced proportion of carbohydrates, proteins, and a low fat content.
The patients will eat a standardized meal designed to evaluate how their blood glucose responds to food intake under controlled conditions.
This meal contains a balanced proportion of carbohydrates, proteins, and a high fat content.
|
What is the study measuring?
Primary Outcome Measures
Outcome Measure |
Measure Description |
Time Frame |
|---|---|---|
|
Postprandial glucose area under the curve (AUC_PG_5h)
Time Frame: 5 hours after each mixed-meal test.
|
Postprandial glucose effect of the interaction between fat intake and hormonal condition. Difference in the area under de curve during 5 hour period as a function of the fat content of the meal and the hormonal condition, expressed in mg·h/dL: Post prandial AUC_PG_5h in female subjects, follicular phase, low fat: FFL_AUC_PG_5h Post prandial AUC_PG_5h in female subjects, follicular phase, high fat: FFH_AUC_PG_5h Post prandial AUC_PG_5h in female subjects, luteal phase, low fat: FLL_AUC_PG_5h Post prandial AUC_PG_5h in female subjects, luteal phase, high fat: FLH_AUC_PG_5h Post prandial AUC_PG_5h in male subjects, low fat: ML_AUC_PG_5h Post prandial AUC_PG_5h in male subjects, high fat: MH_AUC_PG_5h |
5 hours after each mixed-meal test.
|
Secondary Outcome Measures
Outcome Measure |
Measure Description |
Time Frame |
|---|---|---|
|
Mean glucose level (MG)
Time Frame: 5 hours after mixed-meal test.
|
Derived from CGM data, expressed in milligrams per deciliter (mg/dL).
|
5 hours after mixed-meal test.
|
|
Time in range (TIR)
Time Frame: 5 hours after mixed-meal test
|
Derived from CGM data.
Expressed as a percentage (%) of the time or readings with glucose values within the target range, typically between 70-180 mg/dL
|
5 hours after mixed-meal test
|
|
Time above range (TAR)
Time Frame: 5 hours after mixed-meal test
|
Derived from CGM data.
Expressed as a percentage (%) of the time or readings when glucose exceeds 180 mg/dL
|
5 hours after mixed-meal test
|
|
Time below range (TBR)
Time Frame: 5 hours after mixed-meal test
|
Derived from CGM data.
Expressed as a percentage (%) of the time or readings when glucose falls below 70 mg/dL
|
5 hours after mixed-meal test
|
|
Postprandial glucose standard deviation (SD)
Time Frame: 5 hours after mixed-meal test.
|
Derived from CGM data, expressed in milligrams per deciliter (mg/dL)
|
5 hours after mixed-meal test.
|
|
Glycemic coefficient of variation (CV)
Time Frame: 5 hours after mixed-meal test
|
Derived from CGM data, expressed as a percentage (%), calculated as (SD / mean glucose) × 100
|
5 hours after mixed-meal test
|
|
Mean amplitude of glycemic excursions (MAGE)
Time Frame: 5 hours post each mixed-meal
|
Derived from CGM data, expressed in milligrams per deciliter (mg/dL)
|
5 hours post each mixed-meal
|
|
Mean of daily differences (MODD)
Time Frame: 24-hour continuous glucose monitoring period before and after the mixed meal
|
Calculated from CGM data as the average of absolute differences between glucose values at the same time on consecutive days, expressed in milligrams per deciliter (mg/dL).
|
24-hour continuous glucose monitoring period before and after the mixed meal
|
Collaborators and Investigators
Publications and helpful links
General Publications
- Zeevi D, Korem T, Zmora N, Israeli D, Rothschild D, Weinberger A, Ben-Yacov O, Lador D, Avnit-Sagi T, Lotan-Pompan M, Suez J, Mahdi JA, Matot E, Malka G, Kosower N, Rein M, Zilberman-Schapira G, Dohnalova L, Pevsner-Fischer M, Bikovsky R, Halpern Z, Elinav E, Segal E. Personalized Nutrition by Prediction of Glycemic Responses. Cell. 2015 Nov 19;163(5):1079-1094. doi: 10.1016/j.cell.2015.11.001.
- Horowitz M, O'Donovan D, Jones KL, Feinle C, Rayner CK, Samsom M. Gastric emptying in diabetes: clinical significance and treatment. Diabet Med. 2002 Mar;19(3):177-94. doi: 10.1046/j.1464-5491.2002.00658.x.
- Tatulashvili S, Baptiste Julla J, Sritharan N, Rezgani I, Levy V, Bihan H, Riveline JP, Cosson E. Ambulatory Glucose Profile According to Different Phases of the Menstrual Cycle in Women Living With Type 1 Diabetes. J Clin Endocrinol Metab. 2022 Sep 28;107(10):2793-2800. doi: 10.1210/clinem/dgac443.
- Vetrani C, Calabrese I, Cavagnuolo L, Pacella D, Napolano E, Di Rienzo S, Riccardi G, Rivellese AA, Annuzzi G, Bozzetto L. Dietary determinants of postprandial blood glucose control in adults with type 1 diabetes on a hybrid closed-loop system. Diabetologia. 2022 Jan;65(1):79-87. doi: 10.1007/s00125-021-05587-0. Epub 2021 Oct 23.
- Monroy G, Picon-Cesar MJ, Garcia-Aleman J, Tinahones FJ, Martinez-Montoro JI. Glycemic Control Across the Menstrual Cycle in Women with Type 1 Diabetes Using the MiniMed 780G Advanced Hybrid Closed-Loop System: The 780MENS Prospective Study. Diabetes Technol Ther. 2025 May;27(5):395-401. doi: 10.1089/dia.2024.0522. Epub 2025 Jan 16.
- Mesa A, Sola C, Vinagre I, Roca D, Granados M, Pueyo I, Cabre C, Conget I, Gimenez M. Impact of an Advanced Hybrid Closed-Loop System on Glycemic Control Throughout the Menstrual Cycle in Women with Type 1 Diabetes Prone to Hypoglycemia. Diabetes Technol Ther. 2024 Sep;26(9):667-672. doi: 10.1089/dia.2023.0571. Epub 2024 May 10.
- Levy CJ, O'Malley G, Raghinaru D, Kudva YC, Laffel LM, Pinsker JE, Lum JW, Brown SA; iDCL Trial Research Group. Insulin Delivery and Glucose Variability Throughout the Menstrual Cycle on Closed Loop Control for Women with Type 1 Diabetes. Diabetes Technol Ther. 2022 May;24(5):357-361. doi: 10.1089/dia.2021.0431. Epub 2022 Feb 21.
- Trout KK, Rickels MR, Schutta MH, Petrova M, Freeman EW, Tkacs NC, Teff KL. Menstrual cycle effects on insulin sensitivity in women with type 1 diabetes: a pilot study. Diabetes Technol Ther. 2007 Apr;9(2):176-82. doi: 10.1089/dia.2006.0004.
- Brown SA, Jiang B, McElwee-Malloy M, Wakeman C, Breton MD. Fluctuations of Hyperglycemia and Insulin Sensitivity Are Linked to Menstrual Cycle Phases in Women With T1D. J Diabetes Sci Technol. 2015 Oct 14;9(6):1192-9. doi: 10.1177/1932296815608400.
- Herranz L, Saez-de-Ibarra L, Hillman N, Gaspar R, Pallardo LF. [Glycemic changes during menstrual cycles in women with type 1 diabetes]. Med Clin (Barc). 2016 Apr 1;146(7):287-91. doi: 10.1016/j.medcli.2015.11.044. Epub 2016 Feb 18. Spanish.
- Barata DS, Adan LF, Netto EM, Ramalho AC. The effect of the menstrual cycle on glucose control in women with type 1 diabetes evaluated using a continuous glucose monitoring system. Diabetes Care. 2013 May;36(5):e70. doi: 10.2337/dc12-2248. No abstract available.
- Goldner WS, Kraus VL, Sivitz WI, Hunter SK, Dillon JS. Cyclic changes in glycemia assessed by continuous glucose monitoring system during multiple complete menstrual cycles in women with type 1 diabetes. Diabetes Technol Ther. 2004 Aug;6(4):473-80. doi: 10.1089/1520915041705875.
- Gamarra E, Trimboli P. Menstrual Cycle, Glucose Control and Insulin Sensitivity in Type 1 Diabetes: A Systematic Review. J Pers Med. 2023 Feb 20;13(2):374. doi: 10.3390/jpm13020374.
- Concepcion Zavaleta MJ, Gonzales Yovera JG, Moreno Marreros DM, Rafael Robles LDP, Palomino Taype KR, Soto Galvez KN, Arriola Torres LF, Coronado Arroyo JC, Concepcion Urteaga LA. Diabetic gastroenteropathy: An underdiagnosed complication. World J Diabetes. 2021 Jun 15;12(6):794-809. doi: 10.4239/wjd.v12.i6.794.
- Aigner L, Becker B, Gerken S, Quast DR, Meier JJ, Nauck MA. Day-to-Day Variations in Fasting Plasma Glucose Do Not Influence Gastric Emptying in Subjects With Type 1 Diabetes. Diabetes Care. 2021 Feb;44(2):479-488. doi: 10.2337/dc20-1660. Epub 2020 Dec 7.
- Mashali G, Kaul A, Khoury J, Corsiglia J, Dolan LM, Shah AS. Screening for Gastric Sensory Motor Abnormalities in Pediatric Patients With Type 1 Diabetes. Endocr Pract. 2023 Mar;29(3):168-173. doi: 10.1016/j.eprac.2022.12.014. Epub 2022 Dec 23.
- Bartholome R, Salden B, Vrolijk MF, Troost FJ, Masclee A, Bast A, Haenen GR. Paracetamol as a Post Prandial Marker for Gastric Emptying, A Food-Drug Interaction on Absorption. PLoS One. 2015 Sep 9;10(9):e0136618. doi: 10.1371/journal.pone.0136618. eCollection 2015.
- Cai Y, Li M, Zhang L, Zhang J, Su H. The effect of the modified fat-protein unit algorithm compared with that of carbohydrate counting on postprandial glucose in adults with type-1 diabetes when consuming meals with differing macronutrient compositions: a randomized crossover trial. Nutr Metab (Lond). 2023 Oct 16;20(1):43. doi: 10.1186/s12986-023-00757-w.
- Smith TA, Smart CE, Fuery MEJ, Howley PP, Knight BA, Harris M, King BR. In children and young people with type 1 diabetes using Pump therapy, an additional 40% of the insulin dose for a high-fat, high-protein breakfast improves postprandial glycaemic excursions: A cross-over trial. Diabet Med. 2021 Jul;38(7):e14511. doi: 10.1111/dme.14511. Epub 2021 Feb 3.
- Gillingham MB, Marak MC, Riddell MC, Calhoun P, Gal RL, Patton SR, Jacobs PG, Castle JR, Clements MA, Doyle FJ, Rickels MR, Martin CK. The Association Between Diet Quality and Glycemic Outcomes Among People with Type 1 Diabetes. Curr Dev Nutr. 2024 Mar 26;8(4):102146. doi: 10.1016/j.cdnut.2024.102146. eCollection 2024 Apr.
- Colasanto A, Savastio S, Pozzi E, Gorla C, Coisson JD, Arlorio M, Rabbone I. The Impact of Different Types of Rice and Cooking on Postprandial Glycemic Trends in Children with Type 1 Diabetes with or without Celiac Disease. Nutrients. 2023 Mar 29;15(7):1654. doi: 10.3390/nu15071654.
- Lodefalk M, Aman J, Bang P. Effects of fat supplementation on glycaemic response and gastric emptying in adolescents with Type 1 diabetes. Diabet Med. 2008 Sep;25(9):1030-5. doi: 10.1111/j.1464-5491.2008.02530.x.
- Abdou M, Hafez MH, Anwar GM, Fahmy WA, Abd Alfattah NM, Salem RI, Arafa N. Effect of high protein and fat diet on postprandial blood glucose levels in children and adolescents with type 1 diabetes in Cairo, Egypt. Diabetes Metab Syndr. 2021 Jan-Feb;15(1):7-12. doi: 10.1016/j.dsx.2020.11.020. Epub 2020 Nov 26.
- Wolpert HA, Atakov-Castillo A, Smith SA, Steil GM. Dietary fat acutely increases glucose concentrations and insulin requirements in patients with type 1 diabetes: implications for carbohydrate-based bolus dose calculation and intensive diabetes management. Diabetes Care. 2013 Apr;36(4):810-6. doi: 10.2337/dc12-0092. Epub 2012 Nov 27.
- Garonzi C, Forsander G, Maffeis C. Impact of Fat Intake on Blood Glucose Control and Cardiovascular Risk Factors in Children and Adolescents with Type 1 Diabetes. Nutrients. 2021 Jul 29;13(8):2625. doi: 10.3390/nu13082625.
- Bell KJ, Fio CZ, Twigg S, Duke SA, Fulcher G, Alexander K, McGill M, Wong J, Brand-Miller J, Steil GM. Amount and Type of Dietary Fat, Postprandial Glycemia, and Insulin Requirements in Type 1 Diabetes: A Randomized Within-Subject Trial. Diabetes Care. 2020 Jan;43(1):59-66. doi: 10.2337/dc19-0687. Epub 2019 Aug 27.
- Garcia A, Moscardo V, Ramos-Prol A, Diaz J, Boronat M, Bondia J, Rossetti P. Effect of meal composition and alcohol consumption on postprandial glucose concentration in subjects with type 1 diabetes: a randomized crossover trial. BMJ Open Diabetes Res Care. 2021 Oct;9(1):e002399. doi: 10.1136/bmjdrc-2021-002399.
- de Wit DF, Fuhri Snethlage CM, Rampanelli E, Maasen K, Walpot N, van Raalte DH, Nieuwdorp M, Soeters MR, Hanssen NMJ. Higher fibre and lower carbohydrate intake are associated with favourable CGM metrics in a cross-sectional cohort of 470 individuals with type 1 diabetes. Diabetologia. 2024 Oct;67(10):2199-2209. doi: 10.1007/s00125-024-06213-5. Epub 2024 Jul 5.
- Lupoli R, Pisano F, Capaldo B. Postprandial Glucose Control in Type 1 Diabetes: Importance of the Gastric Emptying Rate. Nutrients. 2019 Jul 10;11(7):1559. doi: 10.3390/nu11071559.
Study record dates
Study Major Dates
Study Start (Estimated)
Primary Completion (Estimated)
Study Completion (Estimated)
Study Registration Dates
First Submitted
First Submitted That Met QC Criteria
First Posted (Actual)
Study Record Updates
Last Update Posted (Actual)
Last Update Submitted That Met QC Criteria
Last Verified
More Information
Terms related to this study
Keywords
Additional Relevant MeSH Terms
Other Study ID Numbers
- 2025-0897-1
Plan for Individual participant data (IPD)
Plan to Share Individual Participant Data (IPD)?
Drug and device information, study documents
Studies a U.S. FDA-regulated drug product
Studies a U.S. FDA-regulated device product
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