Postprandial Glucose Variability Following Typical Meals in Youth Living with Type 1 Diabetes.
Susana R PattonSimon BergfordJennifer L SherrRobin L GalPeter CalhounMark A ClementsMichael C RiddellCorby K MartinPublished in: Nutrients (2024)
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.
Keyphrases
- physical activity
- type diabetes
- blood glucose
- glycemic control
- mental health
- young adults
- high intensity
- adipose tissue
- body mass index
- insulin resistance
- magnetic resonance imaging
- blood pressure
- cardiovascular disease
- deep learning
- clinical practice
- computed tomography
- risk assessment
- metabolic syndrome
- palliative care
- electronic health record
- small molecule
- resistance training
- fatty acid
- big data