BACKGROUND: Type 1 diabetes management has evolved from meal plans towards flexible eating with carbohydrate counting. With this shift, youth with type 1 diabetes may consume excess fat and insufficient fiber, which may impact glycemic control. Few studies consider whether insulin regimen influences associations between dietary intake and hemoglobin A1c. PATIENTS AND METHODS: In this cross-sectional study, 252 youth (52% male; age, 13.2 ± 2.8 years; body mass index z-score [z-BMI], 0.7 ± 0.8) with type 1 diabetes completed 3-day food records. Dietary intake was compared with published guidelines. Logistic regression predicted the odds of suboptimal glycemic control (an A1c level of ≥ 8.5%) related to fat and protein intake or fiber intake according to insulin regimen (pump vs. injection) adjusting for age, sex, diabetes duration, z-BMI, insulin dose, glucose monitoring frequency, and total energy intake (TEI). RESULTS: Youth had a mean TEI of 40.9 ± 15.4 kcal/kg/day and excess fat and insufficient fiber intake compared against published guidelines. Pump-treated youth consuming the highest quartile of fat intake (as percentage TEI) had 3.6 (95% confidence interval, 1.3-9.7) times the odds of a suboptimal A1c than those in the lowest quartile. No such association was found in injection-treated youth. In the total sample, youth with the lowest quartile of fiber intake had 3.6 (95% confidence interval, 1.4-9.0) times the odds of a suboptimal A1c, but this association did not differ by insulin regimen. There was no association between protein intake and A1c. CONCLUSIONS: Higher fat intake in pump-treated youth and lower fiber intake in all youth were associated with an A1c level of ≥ 8.5%. Improving dietary quality may help improve A1c.
BACKGROUND: Type 1 diabetes management has evolved from meal plans towards flexible eating with carbohydrate counting. With this shift, youth with type 1 diabetes may consume excess fat and insufficient fiber, which may impact glycemic control. Few studies consider whether insulin regimen influences associations between dietary intake and hemoglobin A1c. PATIENTS AND METHODS: In this cross-sectional study, 252 youth (52% male; age, 13.2 ± 2.8 years; body mass index z-score [z-BMI], 0.7 ± 0.8) with type 1 diabetes completed 3-day food records. Dietary intake was compared with published guidelines. Logistic regression predicted the odds of suboptimal glycemic control (an A1c level of ≥ 8.5%) related to fat and protein intake or fiber intake according to insulin regimen (pump vs. injection) adjusting for age, sex, diabetes duration, z-BMI, insulin dose, glucose monitoring frequency, and total energy intake (TEI). RESULTS: Youth had a mean TEI of 40.9 ± 15.4 kcal/kg/day and excess fat and insufficient fiber intake compared against published guidelines. Pump-treated youth consuming the highest quartile of fat intake (as percentage TEI) had 3.6 (95% confidence interval, 1.3-9.7) times the odds of a suboptimal A1c than those in the lowest quartile. No such association was found in injection-treated youth. In the total sample, youth with the lowest quartile of fiber intake had 3.6 (95% confidence interval, 1.4-9.0) times the odds of a suboptimal A1c, but this association did not differ by insulin regimen. There was no association between protein intake and A1c. CONCLUSIONS: Higher fat intake in pump-treated youth and lower fiber intake in all youth were associated with an A1c level of ≥ 8.5%. Improving dietary quality may help improve A1c.
Authors: R Giacco; M Parillo; A A Rivellese; G Lasorella; A Giacco; L D'Episcopo; G Riccardi Journal: Diabetes Care Date: 2000-10 Impact factor: 19.112
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Authors: S N Balk; D A J M Schoenaker; G D Mishra; M Toeller; N Chaturvedi; J H Fuller; S S Soedamah-Muthu Journal: Eur J Clin Nutr Date: 2015-07-15 Impact factor: 4.016
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Authors: Amit Shapira; Kara R Harrington; Eveline R Goethals; Lisa K Volkening; Lori M Laffel Journal: Diabet Med Date: 2021-06-19 Impact factor: 4.213
Authors: Tonja R Nansel; Lori M B Laffel; Denise L Haynie; Sanjeev N Mehta; Leah M Lipsky; Lisa K Volkening; Deborah A Butler; Laurie A Higgins; Aiyi Liu Journal: Int J Behav Nutr Phys Act Date: 2015-05-08 Impact factor: 6.457