Background: Two previous studies tested the efficacy of Salacia oblonga extract in healthy adults. Objective: This study evaluated the effect of an herbal extract of Salacia oblonga on postprandial glycemia and insulinemia in patients with type 2 diabetes after ingestion of a high-carbohydrate meal. Design: Sixty-six patients with diabetes were studied in this randomized, double-blinded crossover study. In a fasted state, subjects consumed 1 of the following 3 meals: a standard liquid control meal, a control meal + 240 mg Salacia oblonga extract, and a control meal + 480 mg Salacia oblonga extract. Serum glucose and insulin samples were measured at baseline and at postprandial intervals up to 180 min. Results: Both doses of the Salacia extract significantly lowered the postprandial positive area under the glucose curve (14% for the 240 mg extract and 22% for the 480 mg extract) and the adjusted peak glucose response (19% for the lower dose and 27% for the higher dose of extract) to the control meal. In addition, both doses of the herbal extract significantly decreased the postprandial insulin response, lowering both the positive area under the insulin curve and the adjusted peak insulin response (14% and 9%, respectively, for the 240 mg extract; 19% and 12%, respectively, for the 480 mg extract) in comparison with the control meal. Conclusions: The extract of Salacia oblonga lowers acute glycemia and insulinemia in persons with type 2 diabetes after a high-carbohydrate meal. The results from this study suggest that Salacia may be beneficial to this population for postprandial glucose control.

Hypohydration can impair aerobic performance and deteriorate cognitive function during exercise. To minimize hypohydration, athletes are recommended to commence exercise at least euhydrated, ingest fluids containing sodium during long-duration and/or high-intensity exercise to prevent body mass loss over 2% and maintain elevated plasma osmolality, and rapidly restore and retain fluid and electrolyte homeostasis before a second exercise session. To achieve these goals, the compositions of the fluids consumed are key; however, it remains unclear what can be considered an optimal formulation for a hydration beverage in different settings. While carbohydrate–electrolyte solutions such as sports drinks have been extensively explored as a source of carbohydrates to meet fuel demands during intense and long-duration exercise, these formulas might not be ideal in situations where fluid and electrolyte balance is impaired, such as practicing exercise in the heat. Alternately, hypotonic compositions consisting of moderate to high levels of electrolytes (i.e., ≥45 mmol/L), mainly sodium, combined with low amounts of carbohydrates (i.e., <6%) might be useful to accelerate intestinal water absorption, maintain plasma volume and osmolality during exercise, and improve fluid retention during recovery. Future studies should compare hypotonic formulas and sports drinks in different exercise settings, evaluating different levels of sodium and/or other electrolytes, blends of carbohydrates, and novel ingredients for addressing hydration and rehydration before, during, and after exercise.

Food dislikes in children may result in avoiding particular food/s with major sources of essential nutrients leading to increased risk of impaired growth or cognitive development and compromised immune function. It is necessary to identify conditions contributing to feeding difficulty and associated complications. An instrument was designed to assist diagnosis and management of children with feeding difficulties. The study was conducted to test utility of the “Identification and Management of Feeding Difficulties (IMFeD)” tool in Indian children. A prospective, cross-sectional study was conducted in Indian children between 2 and 10 years identified to have picky eating behaviour. After completion of both pro forma sections (parent and physician) of the IMFeD tool, the child’s specific feeding difficulty was diagnosed and appropriate nutritional and/or behavioural counselling was provided. The subjects were followed at 30 and 60 days post-intervention. According to 66% of paediatricians the IMFeD tool was very easy to use. Approximately 85% of paediatricians required ≤20 min to administer the tool, diagnose the feeding difficulty(ies) and provide specific counselling or behavioural management. More than 70% of parents were satisfied and willing to accept the use of the IMFeD tool. After 60 days, 65% of the parents were either less worried or not worried at all about the feeding behaviour of the child using recommendations made on the basis of the IMFeD tool. The toolkit helped parents to know what to do if their child had a feeding problem. A total of 90% of the parents expressed that the tool is useful for assessing feeding difficulties in children. The IMFeD tool can be effectively used to identify feeding difficulties in Indian children. This toolkit also helps to offer nutritional and behavioural guidance as a part of the management.

The purpose of this study was to estimate the prevalence of pediatric undernutrition in the US general population using the Academy of Nutrition and Dietetics/American Society for Parenteral and Enteral Nutrition consensus statement on identification of pediatric malnutrition (undernutrition). National Health and Nutrition Examination Survey (NHANES) data for years 2005–2014 was analyzed for children ages 1–13 years (n = 13,950) with valid anthropometric data. The prevalence of undernutrition was assessed through z-scores for weight-for-height, body mass index (BMI)-for-age, height-for-age, and mid-upper-arm circumference-for-age generated from the 2000 Centers for Disease Control and Prevention growth charts. Children were stratified into: no undernutrition, mild undernutrition, and moderate or severe undernutrition. Descriptive statistics were used to identify the prevalence of undernutrition. Differences in Z-scores across growth chart metrics were compared across undernutrition categories using analysis of variance. The total prevalence of pediatric undernutrition in this sample was 0.4% (severe undernutrition), 2.0% (moderate undernutrition), and 10.9% (mild undernutrition) for all ages. Z-scores differed significantly across all levels of undernutrition for all anthropometrics, showing poorer mean growth metrics in those with undernutrition. Pediatric undernutrition is a prevalent condition that transcends the prior focus on <5th percentile of growth curves and impacts children across different demographic categories.