Oral nutritional supplements (ONS) are used to promote catch-up growth in children with undernutrition. We conducted a systematic review and meta-analysis to summarize the evidence of ONS intervention effects on growth for 9-month- to 12-year-old children who were undernourished or at nutritional risk. Eleven randomized controlled trials met the inclusion criteria; trials compared changes in anthropometric measures in children using ONS or ONS + DC (dietary counselling) to measures for those following usual diet or placebo or DC alone. The RCTs included 2287 children without chronic diseases (mean age 5.87 years [SD, 1.35]; 56% boys). At follow-up time points up to 6 months, results showed that children in the ONS intervention group had greater gains in weight (0.423 kg, [95% confidence interval 0.234, 0.613], p < 0.001) and height (0.417 cm [0.059, 0.776], p = 0.022) versus control; greater gains in weight (0.089 kg [0.049, 0.130], p < 0.001) were evident as early as 7–10 days. Longitudinal analyses with repeated measures at 30, 60, and 90 days showed greater gains in weight parameters from 30 days onwards (p < 0.001), a trend towards greater height gains at 90 days (p = 0.056), and significantly greater gains in height-for-age percentiles and Z-scores at 30 and 90 days, respectively (p < 0.05). Similar results were found in subgroup analyses of studies comparing ONS + DC to DC alone. For children with undernutrition, particularly those who were mildly and moderately undernourished, usage of ONS in a nutritional intervention resulted in significantly better growth outcomes when compared to control treatments (usual diet, placebo or DC alone).

The dietary supplement industry has estimated sales of over $30 billion in the US and over $100 billion globally. Many consumers believe that dietary supplements are safer and possibly more effective than drugs to treat diabetes. The sheer volume of the literature in this space makes compiling them into one review challenging, so much so that primarily narrative reviews currently exist. By applying the interactive database supplied by the Office of Dietary Supplements at the National Institutes of Health, we identified the top 100 ingredients that appeared most often in dietary supplement products. One-hundred different keyword searches using the ingredient name and the word diabetes were performed using a program developed to automatically scrape PubMed. Each search was retained in a separate Excel spreadsheet, which was then reviewed for inclusion or exclusion. The studies that met the inclusion criteria were evaluated for effect of reducing and controlling diabetes. The PubMed scrape resulted in 6217 studies. For each keyword search only the most recent 100 were retained, which refined the total to 1823 studies. Of these 425 met the screening criteria. The ingredients, fiber, selenium and zinc had the most studies associated with improvement in diabetes. Several popular supplement ingredients (phosphorus, pantothenic acid, calcium, magnesium, glutamine, isoleucine, tyrosine, choline, and creatine monohydrate) did not result in any studies meeting our screening criteria. Our study demonstrates how to automate reviews to filter and collapse literature in content areas that have an enormous volume of studies. The aggregated set of studies suggest there is little clinical evidence for the use of dietary supplements to reduce or control diabetes.

Background: Obesity and dyslipidemia are frequently treated with dietary interventions before pharmacotherapy is given. Diets high in unsaturated fat have proven advantageous to disease treatment. Aims: The purpose of this systematic review and meta-analysis was to assess the evidence of the effect of saturated fatty acids (SFA) replacement with unsaturated fatty acids (UFA) in metabolically healthy adults with overweight and obesity on markers of dyslipidemia and body composition. Methods: Keyword search was performed in PubMed, CINAHL, and Cochrane Library for randomized controlled trials (RCTs) evaluating the effects of fatty acid substitution in adults with overweight and obesity. Meta-analysis was performed on interventions assessing lipoprotein levels and body composition. Publication bias was assessed by funnel plot inspection, Begg's, and Egger's test. Results: Eight RCTs enrolling 663 participants were included in the review, with intervention durations between 4 and 28 weeks. Although nonsignificant (p = 0.06), meta-analysis found UFA replacement to reduce total cholesterol concentrations by 10.68 mg/dL (95%CI -21.90 to 0.53). Reductions in low-density lipoprotein cholesterol and triglycerides were statistically nonsignificant. Conclusions: Due to null results and a small number of studies included, there is no strong evidence that replacement of SFA with UFA may benefit lipid profiles in this population.

Cardiovascular disease (CVD) remains the number one cause of death worldwide, and dyslipidemia is a major predictor of CVD mortality. Elevated lipid concentrations are the result of multiple genetic and environmental factors. Over 150 genetic loci have been associated with blood lipid levels. However, not all variants are present in pathways relevant to the pathophysiology of dyslipidemia. The study of these physiologically relevant variants can provide mechanistic understanding of dyslipidemia and identify potential novel therapeutic targets. Additionally, dietary fatty acids have been evidenced to exert both positive and negative effects on lipid profiles. The metabolism of both dietary and endogenously synthesized lipids can be affected by individual genetic variation to produce elevated lipid concentrations. This review will explore the genetic, dietary, and nutrigenetic contributions to dyslipidemia.

Regression to the mean (RTM) is a statistical phenomenon where initial measurements of a variable in a nonrandom sample at the extreme ends of a distribution tend to be closer to the mean upon a second measurement. Unfortunately, failing to account for the effects of RTM can lead to incorrect conclusions on the observed mean difference between the 2 repeated measurements in a nonrandom sample that is preferentially selected for deviating from the population mean of the measured variable in a particular direction. Study designs that are susceptible to misattributing RTM as intervention effects have been prevalent in nutrition and obesity research. This field often conducts secondary analyses of existing intervention data or evaluates intervention effects in those most at risk (i.e., those with observations at the extreme ends of a distribution). To provide best practices to avoid unsubstantiated conclusions as a result of ignoring RTM in nutrition and obesity research. We outlined best practices for identifying whether RTM is likely to be leading to biased inferences, using a flowchart that is available as a web-based app at https://dustyturner.shinyapps.io/DecisionTreeMeanRegression/. We also provided multiple methods to quantify the degree of RTM. Investigators can adjust analyses to include the RTM effect, thereby plausibly removing its biasing influence on estimating the true intervention effect. The identification of RTM and implementation of proper statistical practices will help advance the field by improving scientific rigor and the accuracy of conclusions. This trial was registered at clinicaltrials.gov as NCT00427193.