958-P: Associations between Effect of Body-Mass Index (BMI) and HbA1c among Children and Young Adults with Type 1 Diabetes: A U.S. Based Multicenter Study

Background: The primary objective of this U.S. based multi-center study was to examine the association of overweight and obesity with A1c levels for children and adolescents with type 1 diabetes (T1D) . Methods: Electronic health record data spanning 2017-2021 for children and adolescents from the T1D Exchange Quality Improvement (T1DX-QI) Collaborative was analyzed. BMI percentiles were calculated using the Centers for Disease Control and Prevention growth curves, and children were categorized into normal weight, overweight, obese and severely obese groups. Normal weight was defined as a BMI < 85th percentile for age and sex. Overweight was defined as a BMI ≥ 85th to < 95th percentile. Obesity was defined as having a BMI <120% of the 95th percentile whereas severe obesity was defined as having BMI ≥120% of the 95th percentile. HbA1c levels and BMI were from last in-person encounter. Results: Of 14,484 T1D patients aged < 18 years, 2,063 (14%) were underweight, 9,320 (65%) normal weight, 1,769 (12%) overweight, 977 (7%) obese and 333 were severely obese (2%) . More people of Black (12%) and Hispanic (18%) race/ethnicity were in the obese group relative to the normal weight group (8% and 10% respectively; p<0.001) . HbA1c levels were higher in the obese/severely obese group compared to normal weight patients (HbA1c Mean (SD) : Obese (9.1 (2.3)) /severely obese (9.1 (2.2) vs. Normal weight: 8.7 (2.0) ; p<0.001) . Conclusion: In this extensive real-world study, we found obese children and adolescents with T1D were more likely of Black or Hispanic race/ethnicity and have higher HbA1c levels compared to those with healthy weight

Making Diabetes Electronic Medical Record Data Actionable: Promoting Benchmarking and Population Health Improvement Using the T1D Exchange Quality Improvement Portal

   This article describes how the T1D Exchange Quality Improvement Collaborative leverages an innovative web platform, the QI Portal, to gather and store electronic medical record (EMR) data to promote benchmarking and population health improvement in a type 1 diabetes learning health system. The authors explain the value of the QI Portal, the process for mapping center-level data from EMRs using standardized data specifications, and the QI Portal’s unique features for advancing population health.</p