A Risk Profile for Disordered Eating Behaviors in Adolescents with Type 1 Diabetes: A Latent Class Analysis Study.
Giada BoccoliniMonica MarinoValentina TiberiAntonio IannilliGiulia LandiSilvana GrandiEliana Tossaninull Isped Study GroupValentino CherubiniPublished in: Nutrients (2023)
(1) Background: This multi-center study aimed to identify a risk profile for disordered eating behaviors (DEBs) in youth with type 1 diabetes (T1D) based on their dietary intake, lipid profile, body mass index (BMI-SDS), and glycometabolic control. (2) Methods: Adolescents aged 11 to 18 years from five centers across Italy were recruited. Lipid profile, HbA1c, BMI-SDS, and dietary intake data were collected. The risk for developing DEBs was assessed via the Diabetes Eating Problems Survey-R (DEPS-R) questionnaire. A latent class analysis (LCA) was performed using a person-centered approach. (3) Results: Overall, 148 participants aged 11-18 (12.1, ±3.34), 52% males with a mean diabetes duration of 7.2 (±3.4), were enrolled. Based on the results of the DEBS-R score, LCA allowed us to highlight two different classes of patients which were defined as "at-risk" and "not at-risk" for DEB. The risk profile for developing DEBs is characterized by higher BMI-SDS (23.9 vs. 18.6), higher HbA1c (7.9 vs. 7.1%), higher LDL cholesterol (99.9 vs. 88.8 mg/dL), lower HDL cholesterol (57.9 vs. 61.3 mg/dL), higher proteins (18.2 vs. 16.1%), and lower carbohydrates (43.9 vs. 45.3%). Adolescents included in the "at-risk" class were significantly older ( p = 0.000), and their parents' SES was significantly lower ( p = 0.041). (4) Conclusions: This study allowed us to characterize a risk profile for DEBs based on dietary behavior and clinical parameters. Early identification of the risk for DEBs allows timely intervention and prevention of behavior disorders.
Keyphrases
- body mass index
- physical activity
- young adults
- type diabetes
- randomized controlled trial
- mental health
- end stage renal disease
- chronic kidney disease
- machine learning
- weight loss
- metabolic syndrome
- newly diagnosed
- artificial intelligence
- skeletal muscle
- ejection fraction
- peritoneal dialysis
- community dwelling
- breast cancer risk