Alexandra D Monzon1, Laura B Smith2, Scott W Powers2, Lawrence M Dolan3, Susana R Patton4. 1. Clinical Child Psychology Program, University of Kansas. 2. Division of Behavioral Medicine & Clinical Psychology, Cincinnati Children's Hospital Medical Center. 3. Division of Endocrinology, Cincinnati Children's Hospital Medical Center. 4. Nemours Center for Healthcare Delivery-Florida, Nemours Children's Health System.
Abstract
OBJECTIVE: There is limited information regarding the potential effect macronutrients have on postprandial glycemic variability in young children with type 1 diabetes (T1D). To date, studies examining nutrition and glycemic outcomes either assess these factors at a single timepoint, or aggregate large datasets for group level analyses. This study examined how inter- and intraindividual fluctuations in carbohydrate, fat, and protein intake impact glycemic variability in the postprandial period for young children with T1D. METHODS: Thirty-nine young children, aged 2-6 years, wore a continuous glucose monitor for 72 hr, while their parents completed detailed diet records of all food intake. The analyses tested three multilevel models to examine intra- and interindividual differences between food intake and postprandial glycemic variability. RESULTS: The results suggest carbohydrate intake, relates to greater postprandial glycemic variability. In contrast, the results reveal the inverse effect for protein, suggesting a tendency for young children who ate more protein at some meals to have lower postprandial glycemic variability, with the exception of lunch. There was no effect for fat on postprandial glycemic variability. CONCLUSION: These results suggest protein consumption may be an important consideration when aiming for optimal glycemic levels for some meals. When counseling parents of young children with T1D on common behaviors underlying glycemic excursion, pediatric psychologists may consider discussing the nutritional make up of children's meals. Further, the results demonstrate retaining longitudinal data at the person level, versus aggregating individual data for group level analyses, may offer new information regarding macronutrient intake and glycemic outcomes.
OBJECTIVE: There is limited information regarding the potential effect macronutrients have on postprandial glycemic variability in young children with type 1 diabetes (T1D). To date, studies examining nutrition and glycemic outcomes either assess these factors at a single timepoint, or aggregate large datasets for group level analyses. This study examined how inter- and intraindividual fluctuations in carbohydrate, fat, and protein intake impact glycemic variability in the postprandial period for young children with T1D. METHODS: Thirty-nine young children, aged 2-6 years, wore a continuous glucose monitor for 72 hr, while their parents completed detailed diet records of all food intake. The analyses tested three multilevel models to examine intra- and interindividual differences between food intake and postprandial glycemic variability. RESULTS: The results suggest carbohydrate intake, relates to greater postprandial glycemic variability. In contrast, the results reveal the inverse effect for protein, suggesting a tendency for young children who ate more protein at some meals to have lower postprandial glycemic variability, with the exception of lunch. There was no effect for fat on postprandial glycemic variability. CONCLUSION: These results suggest protein consumption may be an important consideration when aiming for optimal glycemic levels for some meals. When counseling parents of young children with T1D on common behaviors underlying glycemic excursion, pediatric psychologists may consider discussing the nutritional make up of children's meals. Further, the results demonstrate retaining longitudinal data at the person level, versus aggregating individual data for group level analyses, may offer new information regarding macronutrient intake and glycemic outcomes.
Authors: Janet Silverstein; Georgeanna Klingensmith; Kenneth Copeland; Leslie Plotnick; Francine Kaufman; Lori Laffel; Larry Deeb; Margaret Grey; Barbara Anderson; Lea Ann Holzmeister; Nathaniel Clark Journal: Diabetes Care Date: 2005-01 Impact factor: 19.112
Authors: Carmel E Smart; Francesca Annan; Laurie A Higgins; Elisabeth Jelleryd; Mercedes Lopez; Carlo L Acerini Journal: Pediatr Diabetes Date: 2018-10 Impact factor: 4.866
Authors: Laura M Gandrud; Dongyuan Xing; Craig Kollman; Jen M Block; Betsy Kunselman; Darrell M Wilson; Bruce A Buckingham Journal: Diabetes Technol Ther Date: 2007-08 Impact factor: 6.118
Authors: Carmel E M Smart; Megan Evans; Susan M O'Connell; Patrick McElduff; Prudence E Lopez; Timothy W Jones; Elizabeth A Davis; Bruce R King Journal: Diabetes Care Date: 2013-10-29 Impact factor: 19.112