» Articles » PMID: 38201991

Postprandial Glucose Variability Following Typical Meals in Youth Living with Type 1 Diabetes

Overview
Journal Nutrients
Date 2024 Jan 11
PMID 38201991
Authors
Affiliations
Soon will be listed here.
Abstract

We explored the association between macronutrient intake and postprandial glucose variability in a large sample of youth living with T1D and consuming free-living meals. In the Type 1 Diabetes Exercise Initiative Pediatric (T1DEXIP) Study, youth took photographs before and after their meals on 3 days during a 10 day observation period. We used the remote food photograph method to obtain the macronutrient content of youth's meals. We also collected physical activity, continuous glucose monitoring, and insulin use data. We measured glycemic variability using standard deviation (SD) and coefficient of variation (CV) of glucose for up to 3 h after meals. Our sample included 208 youth with T1D (mean age: 14 ± 2 years, mean HbA1c: 54 ± 14.2 mmol/mol [7.1 ± 1.3%]; 40% female). We observed greater postprandial glycemic variability (SD and CV) following meals with more carbohydrates. In contrast, we observed less postprandial variability following meals with more fat (SD and CV) and protein (SD only) after adjusting for carbohydrates. Insulin modality, exercise after meals, and exercise intensity did not influence associations between macronutrients and postprandial glycemic variability. To reduce postprandial glycemic variability in youth with T1D, clinicians should encourage diversified macronutrient meal content, with a goal to approximate dietary guidelines for suggested carbohydrate intake.

Citing Articles

Proposed Practical Guidelines to Improve Glycaemic Management by Reducing Glycaemic Variability in People with Type 1 Diabetes Mellitus.

de Torres-Sanchez A, Ampudia-Blasco F, Murillo S, Bellido V, Amor A, Mezquita-Raya P Diabetes Ther. 2025; .

PMID: 40019699 DOI: 10.1007/s13300-025-01703-0.


Clinical relevance of short-term glycemic variability in children and adolescents with type 1 diabetes: a narrative review.

Bombaci B, Passanisi S, Lombardo F, Salzano G Transl Pediatr. 2024; 13(7):1231-1241.

PMID: 39144438 PMC: 11320011. DOI: 10.21037/tp-24-114.

References
1.
Ma J, Stevens J, Cukier K, Maddox A, Wishart J, Jones K . Effects of a protein preload on gastric emptying, glycemia, and gut hormones after a carbohydrate meal in diet-controlled type 2 diabetes. Diabetes Care. 2009; 32(9):1600-2. PMC: 2732158. DOI: 10.2337/dc09-0723. View

2.
Spruijt-Metz D, Wen C, Bell B, Intille S, Huang J, Baranowski T . Advances and Controversies in Diet and Physical Activity Measurement in Youth. Am J Prev Med. 2018; 55(4):e81-e91. PMC: 6151143. DOI: 10.1016/j.amepre.2018.06.012. View

3.
Viguiliouk E, Stewart S, Jayalath V, Ng A, Mirrahimi A, de Souza R . Effect of Replacing Animal Protein with Plant Protein on Glycemic Control in Diabetes: A Systematic Review and Meta-Analysis of Randomized Controlled Trials. Nutrients. 2015; 7(12):9804-24. PMC: 4690061. DOI: 10.3390/nu7125509. View

4.
Monzon A, Smith L, Powers S, Dolan L, Patton S . The Association Between Glycemic Variability and Macronutrients in Young Children with T1D. J Pediatr Psychol. 2020; 45(7):749-758. PMC: 7381191. DOI: 10.1093/jpepsy/jsaa046. View

5.
Martin C, Correa J, Han H, Allen H, Rood J, Champagne C . Validity of the Remote Food Photography Method (RFPM) for estimating energy and nutrient intake in near real-time. Obesity (Silver Spring). 2011; 20(4):891-9. PMC: 3975169. DOI: 10.1038/oby.2011.344. View