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Updated: Jun 7, 2025

Concept Development and Use of an Automated Food Intake and Eating Behavior Assessment Method
Published on: February 19, 2021
The Cross-sectional Relationship Between Use of Automatic Insulin Delivery Systems and Eating Styles Among Older
Anna R Kahkoska1,2,3, Jessica Sprinkles1, Nikhita Gopisetty4
1Department of Nutrition, UNC Gillings School of Global Public Health, The University of North Carolina at Chapel Hill, Chapel Hill, NC, USA.
Background:
The number of older adults with type 1 diabetes (T1D) is increasing. Use of automated insulin delivery (AID) may influence nutrition and eating behaviors. We explored how three eating styles (restrained, external, emotional) differ between older adults with T1D who use and do not use AID.
Methods:
We administered a one-time electronic survey from September to November 2023 to adults ≥65 years with T1D receiving care through a university-affiliated hospital system. Clinical and demographic information was collected from medical records. Eating styles were characterized with the Dutch Eating Behavior Questionnaire.
Results:
Our sample (n = 77, 95% non-Hispanic white) had mean (SD) age: 71.8 (4.1) years, diabetes duration: 33 (18) years, hemoglobin A1c (HbA1c): 6.83 (1.12%), and body mass index (BMI): 27.3 (4.7) kg/m2. Respondents reported variable eating styles, with the highest median scores for external and restrained eating and lower scores for emotional eating. Older adults using AID systems had higher median scores for emotional and external eating, and more varied restrained eating scores compared to those not using AID systems. Weak correlations were found between eating styles and HbA1c (restrained: r = -0.14; external: r = 0.08; emotional: r = 0.15), as well as between restrained (r = 0.09) and external (r = 0.04) eating with BMI, with a small correlation between emotional eating and BMI (r = 0.27).
Conclusions:
Eating styles may vary between older adult AID users and non-users. To our knowledge, this is the first study to characterize eating styles in this population, though generalizability is limited by a non-diverse and small sample with high technology use overall (eg, continuous glucose monitoring, insulin pumps).
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