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. Sensitivity and subgroup analyses will be conducted to identify sources of heterogeneity. Sensitivity analyses will involve an assessment of heterogeneity upon systematic removal of each trial. If there are >= 10 trials, the study investigators will conduct apriori subgroup analyses by age, health status, comparator, dose, baseline measurements, randomization, study design (parallel, crossover), energy balance (positive, neutral, negative), follow-up (<= 4 weeks, > 4 weeks) and risk of bias. Meta-regression analyses will assess the significance of categorical and continuous subgroup analyses. When more than 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.