Meta-analysis of Low GI/GL Diets and Cardiometabolic Risk in Diabetes

Overview

Low glycemic index and low glycemic load diets have been shown to improve glycemic control and cardiometabolic risk factors in randomized controlled trials in people with diabetes and are associated with reduced incidence of diabetes and cardiovascular disease in prospective cohort studies inclusive of people with diabetes. These benefits have been recognized in the most recent updates of the clinical practice guidelines for the management of diabetes from the U.S., Canada, UK, and Australia. The European Association for the Study of Diabetes (EASD) also recommends low-GI/GL diets but has not updated their guidance in 15 years. To support the update of the EASD clinical practice guidelines for nutrition therapy, the investigators conducted a systematic review and meta-analysis of the totality of the available evidence from randomized controlled trials of the effect of low GI/GL dietary patterns on glycemic control and other established cardiometabolic risk factors in individuals with diabetes. The findings generated by this proposed knowledge synthesis will help improve the health of consumers through informing evidence-based guidelines and improving health outcomes by educating healthcare providers and patients, stimulating industry innovation, and guiding future research design.

Background: The prevalence of diabetes continues to rise globally and remains a major cause of cardiovascular disease and a leading cause of death. Diet and lifestyle remain the cornerstone of therapy for diabetes prevention and management. Approaches that target postprandial glycemic excursions may have particular advantages. Low glycemic index (GI) and low glycemic load (GL) diets have been shown to improve glycemic control and cardiometabolic risk factors in randomized controlled trials in people with diabetes and are associated with reduced incidence of diabetes and cardiovascular disease in prospective cohort studies inclusive of people with diabetes. These benefits have been recognized in the most recent updates of the clinical practice guidelines for diabetes from the U.S., Canada, UK, and Australia. The European Association for the Study of Diabetes (EASD) also recommends low-GI/GL diets but has not updated their guidance in 15 years. Need for proposed research: High quality systematic reviews and meta-analyses of randomized controlled trials represent the highest level of evidence to support dietary guidelines and public health policy development. As dietary guidelines and public health policy have shifted toward food and dietary-pattern based recommendations, there is a need for systematic reviews and meta-analyses comparing the role of low GI/GL diets in the management of diabetes. Objective: To support the update the European Association for the Study of Diabetes (EASD) clinical practice guidelines for nutrition therapy, the investigators conducted a systematic review and meta-analysis of randomized controlled trials using the GRADE approach of the effect of low GI/GL dietary patterns on glycemic control and other established cardiometabolic risk factors in individuals with diabetes. Design: The systematic review and meta-analysis will be conducted according to the Cochrane Handbook for Systematic Reviews of Interventions and reported according to the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA). Data sources: MEDLINE, EMBASE, and The Cochrane Central Register of Controlled Trials (Clinical Trials; CENTRAL) will be searched using appropriate search terms supplemented by manual searches of references of included studies. Study selection: Dietary randomized controlled trials conducted in humans with a follow-up duration ≥ 3 weeks investigating the effect of low GI/GL diets on measures of glycemic control, blood lipids, adiposity, blood pressure, or inflammation will be included. Studies that are not conducted in humans, not randomized, have an acute feeding design (\<3 weeks), lack a suitable control (non-isocaloric) and/or do not report viable endpoint data will not be included. Data extraction: Two or more investigators will independently extract relevant data and assess risk of bias using the Cochrane Risk of Bias Tool. All disagreements will be resolved by consensus. Standard computations and imputations will be used to derive missing variance data. Outcomes: The primary outcome will be HbA1c. Secondary outcomes will include other markers of glycemic control (fasting glucose, fasting insulin); blood lipids (LDL-C, non-HDL-C, apo B, HDL-C, triglycerides); adiposity (body weight, BMI, waist circumference), blood pressure (systolic and diastolic blood pressure), and inflammation (C-reactive protein \[CRP\]). Data synthesis: Separate pooled analyses will be conducted for each area of cardiometabolic control using the Generic Inverse Variance method. Random-effects models will be used even in the absence of statistically significant between-study heterogeneity, as they yield more conservative summary effect estimates in the presence of residual heterogeneity. Exceptions will be made for the use of fixed-effects models where there is \<5 included trials irrespective of heterogeneity or small trials are being pooled with larger more precise trials in the absence of statistically significant heterogeneity. Paired analyses will be applied to all crossover trials. Heterogeneity will be tested by the Cochran Q statistic and quantified by the I2 statistic. To explore sources of heterogeneity, the investigators will conduct sensitivity analyses, in which each study is systematically removed. If there are ≥10 studies, then the investigators will also explore sources of heterogeneity by a priori subgroup analyses by diabetes type (type 1 or type 2), study design (parallel or crossover), follow-up duration (\<12 weeks or ≥12 weeks), comparator diet, baseline measurements, risk of bias and diabetes duration. To further explore sources of heterogeneity, investigators will perform post hoc subgroup analyses by age (\<18y vs ≥18y), energy balance (neutral, negative or positive), feeding control (metabolic, supplemented, dietary advice, ad libitum), test GI (≤55 vs \>55 GI units), test GL (by median) and funding source. Meta-regression analyses will assess the significance of categorical and continuous subgroups analyses. Linear dietary GI and dietary GL dose-response analyses will be assessed using continuous meta-regression analyses. Non-linear dose-response association will be assessed using a two-stage multivariate random-effects method with restricted cubic splines with three knots. When ≥10 studies are available, publication bias will be investigated by inspection of funnel plots and formal testing using the Egger's and Begg's tests. If publication bias is suspected, then the investigators will attempt to adjust for funnel plot asymmetry by imputing the missing study data using the Duval and Tweedie trim and fill method. Evidence assessment: The certainty of the evidence for each outcome will be assessed using the Grading of Recommendations Assessment, Development and Evaluation (GRADE) approach. Knowledge translation plan: The results will be disseminated through interactive presentations at local, national, and international scientific meetings and publication in high impact factor journals. Target audiences will include the public health and scientific communities with interest in nutrition, diabetes, obesity, and cardiovascular disease. Feedback will be incorporated and used to improve the public health message and key areas for future research will be defined. Applicant/Co-applicant Decision Makers will network among opinion leaders to increase awareness and participate directly as committee members in the development of future guidelines. Significance: The proposed project will aid in knowledge translation related to the role of low GI/GL diets in the management of diabetes, strengthening the evidence-base for guidelines and improving health outcomes by educating healthcare providers and patients, stimulating industry innovation, and guiding future research design.