Comparative efficacy of different eating patterns in the management of type 2 diabetes and prediabetes: An arm‐based Bayesian network meta‐analysis

Autor: Ben‐tuo Zeng, Hui‐qing Pan, Feng‐dan Li, Zhen‐yu Ye, Yang Liu, Ji‐wei Du
Rok vydání: 2022
Předmět:
Zdroj: Journal of Diabetes Investigation. 14:263-288
ISSN: 2040-1124
2040-1116
Popis: Aims/IntroductionDiet therapy is a vital approach to manage type 2 diabetes and prediabetes. However, the comparative efficacy of different eating patterns is not clear enough. We aimed to compare the efficacy of various eating patterns for glycemic control, anthropometrics, and serum lipid profiles in the management of type 2 diabetes and prediabetes.Materials and MethodsWe conducted a network meta-analysis using arm-based Bayesian methods and random effect models, and drew the conclusions using the partially contextualized framework. We searched twelve databases and yielded 9,534 related references, where 107 studies were eligible, comprising 8,909 participants.ResultsEleven diets were evaluated for fourteen outcomes. Caloric restriction was ranked as the best pattern for weight loss (SUCRA 86.8%) and waist circumference (82.2%), low-carbohydrate diets for body mass index (81.6%) and high-density lipoprotein (84.0%), and low-glycemic-index diets for total cholesterol (87.5%) and low-density lipoprotein (86.6%). Other interventions showed some superiorities, but were of imprecision due to insufficient participants and needed further investigation. The attrition rates of interventions were similar. Meta-regression suggested that macronutrients, energy intake, and weight may modify outcomes differently. The evidence was of moderate-to-low quality, and 38.2% of the evidence items met the minimal clinically important differences.ConclusionsThe selection and development of dietary strategies for diabetic/prediabetic patients should depend on their holistic conditions, i.e., serum lipids profiles, glucometabolic patterns, weight and blood pressures. It is recommended to identify the most critical and urgent metabolic indicator to control for one specific patient, and then choose the most appropriate eating pattern accordingly.
Databáze: OpenAIRE
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