Aims/Introduction Diet 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 Methods We 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. Results Eleven diets were evaluated for 14 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 imprecise 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. Conclusions The selection and development of dietary strategies for diabetic/prediabetic patients should depend on their holistic conditions, i.e., serum lipid profiles, glucometabolic patterns, weight, and blood pressure. 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.

The study aimed to compare and rank the efficacy of various eating patterns for glycemic control, anthropometrics, and serum lipid profiles in the management of type 2 diabetes and prediabetes, and provide evidence for personalized clinical decision-making. We conducted a network meta-analysis using arm-based Bayesian methods and random effect models following the Cochrane handbook. We drew the conclusions using the partially contextualized framework by the GRADE working group. Twelve English and Chinese databases and registers were retrieved, and we obtained 9,534 references, of which 107 independent studies were eligible, including 8,909 participants, ten experimental diets, and thirteen outcome variables. The meta-analysis denoted that: caloric restriction was ranked as the best pattern for weight loss (SUCRA 86.8%) and reducing waist circumference (82.2%), high-fiber diets for lowering fasting plasma glucose (82.1%) and insulin (79.4%), Dietary Approaches to Stop Hypertension for reducing glycated hemoglobin (90.5%) and systolic blood pressure (87.9%), simple high-protein diets for improving insulin resistance (86.3%) and diastolic blood pressure (74.6%), low-carbohydrate diets for improving body mass index (81.6%) and high-density lipoprotein (84.0%), low-glycemic-index diets for lowering total cholesterol (87.5%) and low-density lipoprotein (86.6%), and Paleolithic diets for reducing triacylglycerol (83.4%). However, the results were of moderate sensitivity, and publication bias of glycated hemoglobin, weight, and body mass index existed. Meta-regression suggested that macronutrients, energy intake, baseline, and weight may modify outcomes differently, while the duration did not show a significant association with results. Forty-nine (39.8%) out of 123 pieces of evidence was rated as moderate quality, and there was no high-quality evidence. Additionally, only 38.2% of the effect sizes of the evidence met the minimally important clinical difference threshold. Clinicians can use the evidence to provide personalized nutrition consultations to patients according to their baseline characteristics. However, the results should be carefully explained and applied because of the sensitivity and low quality.

Background: There is no existing research on hormone overdose and misuse (HODM) in Chinese transgender and gender non-conforming (TGNC) population, and little is known in this field. Objectives: We aim to determine the definition and criteria of HODM in Chinese TGNCs, address the rate of HODM in Chinese TGNC population, explore related factors and behavioral risks, identify the probable causes, and explore long-term effects. Methods: We propose: (1) a mixed-method study comprising expert panel meetings and stakeholder engagement to identify HODM criteria, types and grades; (2) a cross-sectional study to quantify HODM incidence rates, related factors and behavioral risks; (3) semi-structured interviews and focus groups to explore HODM motivations and reasons; and (4) a prospective cohort study to evaluate HODM long-term effects. Ethics: The study protocol was approved by the Medical Ethics Committee of Xiamen University (XDYX202210K27). Dissemination: Results will be published in international peer-reviewed journals, and a public-oriented version of the main findings will be prepared and disseminated through social media and online communities. The study will be completed before September 2023 except for the cohort study. Preliminary findings of the cohort study will be reported by March 2026. Key words: Transgender Persons; Gender Affirming Hormone Therapy; Stakeholder Participation; Mixed Methods Research; China