宏量营养素摄入和进餐次数对 1 型糖尿病青少年 1 年血糖结果的影响。

IF 5.7 2区 医学 Q1 ENDOCRINOLOGY & METABOLISM
Diabetes technology & therapeutics Pub Date : 2024-06-01 Epub Date: 2024-02-13 DOI:10.1089/dia.2023.0464
Rebecca Ortiz La Banca Barber, Lisa K Volkening, Sanjeev N Mehta, Eyal Dassau, Lori M Laffel
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引用次数: 0

摘要

目的:胰岛素栓剂量来自葡萄糖水平和计划碳水化合物摄入量,但脂肪和蛋白质会影响血糖偏移。我们研究了宏量营养素和每日正餐/零食数量对 1 型糖尿病青少年血糖结果的影响:患有 1 型糖尿病的青少年(136 人,8-17 岁)填写 3 天饮食记录,佩戴 3 天遮蔽式 CGM,每 3 个月测量一次 A1c,为期一年。饮食数据通过营养研究数据系统进行分析。纵向混合模型评估了宏量营养素摄入和正餐/零食数量对血糖结果的影响:基线时,青少年(48%为男性)的平均年龄为(12.8±2.5)岁,糖尿病病程为(5.9±3.1)年;73%使用胰岛素泵。基线 A1c 为 8.1±1.0%,70-180 毫克/分升范围内的时间百分比(%TIR)为 49±17%,180 毫克/分升范围内的时间百分比(%TAR)为 44±20%,血糖变异系数(CV)为 41±8%;宏量营养摄入包括 48±5%碳水化合物、36±5% 脂肪和 16±2% 蛋白质。大多数青少年(56%)表示每天吃 3-4 餐/零食(1-9 餐不等)。一年来,碳水化合物摄入量越高,A1c 越低(p=0.0003),TBR % 越高(p=0.0006),TAR % 越低(p=0.002),CV 越高(p=0.03)。脂肪摄入量越多,A1c 越高(p=0.006),TBR%越低(p=0.002),TAR%越高(p=0.005)。蛋白质摄入量增加与 A1c 升高有关(p=0.01)。每日进餐/零食越多,A1c 越低(p=0.001),%TIR 越高(p=0.0006),%TAR 越低(p=0.0001):结论:脂肪和蛋白质都会影响血糖结果。结论:脂肪和蛋白质都会影响血糖结果,未来的胰岛素自动给药系统应考虑所有宏量营养素,以便及时提供胰岛素。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Effects of Macronutrient Intake and Number of Meals on Glycemic Outcomes Over 1 Year in Youth with Type 1 Diabetes.

Objective: Insulin bolus doses derive from glucose levels and planned carbohydrate intake, although fat and protein impact glycemic excursions. We examined the impact of macronutrients and number of daily meals/snacks on glycemic outcomes in youth with type 1 diabetes. Methods: Youth (N = 136, ages 8-17) with type 1 diabetes completed 3-day food records, wore 3-day masked continuous glucose monitoring, and had A1c measurements every 3 months for 1 year. Diet data were analyzed using Nutrition Data System for Research. Longitudinal mixed models assessed effects of macronutrient intake and number of meals/snacks on glycemic outcomes. Results: At baseline, youth (48% male) had mean age of 12.8 ± 2.5 years and diabetes duration of 5.9 ± 3.1 years; 73% used insulin pumps. Baseline A1c was 8.1% ± 1.0%, percent time in range 70-180 mg/dL (%TIR) was 49% ± 17%, % time below range <70 mg/dL (%TBR) was 6% ± 8%, % time above range >180 mg/dL (%TAR) was 44% ± 20%, and glycemic variability as coefficient of variation (CV) was 41% ± 8%; macronutrient intake included 48% ± 5% carbohydrate, 36% ± 5% fat, and 16% ± 2% protein. Most youth (56%) reported 3-4 meals/snacks daily (range 1-9). Over 1 year, greater carbohydrate intake was associated with lower A1c (P = 0.0003), more %TBR (P = 0.0006), less %TAR (P = 0.002), and higher CV (P = 0.03). Greater fat intake was associated with higher A1c (P = 0.006), less %TBR (P = 0.002), and more %TAR (P = 0.005). Greater protein intake was associated with higher A1c (P = 0.01). More daily meals/snacks were associated with lower A1c (P = 0.001), higher %TIR (P = 0.0006), and less %TAR (P = 0.0001). Conclusions: Both fat and protein impact glycemic outcomes. Future automated insulin delivery systems should consider all macronutrients for timely insulin provision. The present research study derived from secondary analysis of the study registered under NCT00999375.

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来源期刊
Diabetes technology & therapeutics
Diabetes technology & therapeutics 医学-内分泌学与代谢
CiteScore
10.60
自引率
14.80%
发文量
145
审稿时长
3-8 weeks
期刊介绍: Diabetes Technology & Therapeutics is the only peer-reviewed journal providing healthcare professionals with information on new devices, drugs, drug delivery systems, and software for managing patients with diabetes. This leading international journal delivers practical information and comprehensive coverage of cutting-edge technologies and therapeutics in the field, and each issue highlights new pharmacological and device developments to optimize patient care.
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