Effect of Liquid Meal Replacements on Cardiometabolic Risk Factors: A Series of Systematic Reviews and Meta-analyses of Randomized Controlled Trials
Effect of Liquid Meal Replacements on Cardiometabolic Risk Factors: A Series of Systematic Reviews and Meta-analyses of Randomized Controlled Trials
Obesity is a major risk factor for cardiovascular disease and diabetes. Weight loss is an important therapeutic goal for overweight and obese patients to reduce their risk of developing cardiovascular disease and diabetes. Liquid meal replacements (LMRs) are simple tools that may aid in weight loss and may improve weight-related risk cardiometabolic risk factors. There is a need to synthesize the evidence on LMRs and cardiometabolic risk to inform clinical practice guidelines. The authors propose to conduct a series of systematic review and meta-analysis of randomized controlled trials to evaluate the effect of LMRs on 4 areas of cardiometabolic risk: markers of adipsoity, glycemic control, established lipid targets, and blood pressure.
Background: Liquid meal replacements (LMRs) provide a mixture of carbohydrate, fat and protein, along with added vitamins and minerals in liquid ready-to-drink form or powder formulas that require mixing. They are designed to mimic a low-calorie meal and serve as a quick and easy source of calories to consume. Behavioral strategy tools are important to assist obese individuals in losing weight and maintaining weight loss. There is evidence that LMRs contribute to weight loss and may reduce related cardiometabolic risk factors.
Need for proposed research: An earlier meta-analysis demonstrated that partial meal replacement plans produced significant weight loss and improved weight-related cardiometabolic risk factors. Several controlled trials have since investigated the effect of liquid meal replacements on body weight and weight-related risk factors for disease. There is a need to update of the evidence of the effect of LMRs on cardiometabolic risk to inform dietary guidelines and public health policy development.
Objective: To synthesize the evidence of randomized controlled trials of the effect of LMRs on body weight, blood pressure, glycemic control and established lipid targets.
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.
Study selection: The investigators will include randomized controlled trials of >= 2-weeks duration that assess the effect of LMRs versus control diets on body weight, blood pressure, markers of glycemic control and lipid profile.
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: Four sets of outcomes will be assessed: (1) Markers of adiposity (body weight, BMI, body fat, waist circumference), (2) glycemic control (HbA1c, fasting glucose, and fasting insulin), (3) Established therapeutic lipid targets (LDL-cholesterol, non-HDL-cholesterol, apolipoprotein B, HDL-cholesterol, triglycerides), and (4) blood pressure (systolic blood pressure and diastolic blood pressure).
Data synthesis: Pooled analyses of the mean difference will be performed using the generic inverse variance method. Random-effects models will be used even in the absence of statistically significant between-study heterogeneity because they yield more conservative summary effect estimates in the presence of residual heterogeneity. Fixed-effects models will be used only if there are less than 5 included trials. Crossover trials will be assessed via paired analyses. Heterogeneity will be assessed 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 trials, the study investigators will conduct apriori subgroup analyses by liquid meal replacement type (diabetes-specific formula, soy-based formula and fiber-containing formula), age, health status (presence/absence of type 2 diabetes), comparator, dose, baseline measurements, study design (parallel, crossover), follow-up (<= 3 months, > 3 months) and risk of bias. Meta-regression analyses will assess the significance of categorical and continuous subgroup analyses. When >= 10 trials are available, publication bias will be investigated by funnel plots and formal testing using Egger and Begg 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 strength of the evidence for each outcome will be assessed using the Grading of Recommendations Assessment, Development and Evaluation (GRADE).
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 and obesity. 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 research will synthesize the highest quality evidence from randomized trials and aid in knowledge translation of the effect of LMRs on body weight and related cardiometabolic disease risk. It will strengthen the evidence-base for guidelines, improve health outcomes, by educating healthcare providers and patients, stimulating industry innovation, and guiding future research design.
Inclusion Criteria:
Exclusion Criteria: