The effects of dairy and dairy-derived products on the human gut microbiota remains understudied. A systematic literature search was conducted using Medline, CINAHL, Embase, Scopus, and PubMed databases with the aim of collating evidence on the intakes of all types of dairy and their effects on the gut microbiota in adults. Risk of bias was assessed using the Cochrane risk-of-bias tool.The search resulted in 6,592 studies, of which eight randomized controlled trials (RCTs) met pre-determined eligibility criteria for inclusion, consisting of a total of 468 participants. Seven studies assessed the effect of type of dairy (milk, yogurt, and kefir) and dairy derivatives (whey and casein) on the gut microbiota, and one study assessed the effect of the quantity of dairy (high dairy vs low dairy). Three studies showed that dairy types consumed (milk, yogurt, and kefir) increased the abundance of beneficial genera Lactobacillus and Bifidobacterium. One study showed that yogurt reduced the abundance of Bacteroides fragilis, a pathogenic strain. Whey and casein isolates and the quantity of dairy consumed did not prompt changes to the gut microbiota composition. All but one study reported no changes to bacterial diversity in response to dairy interventions and one study reported reduction in bacterial diversity in response to milk intake.In conclusion, the results of this review suggest that dairy products such as milk, yogurt, and kefir may modulate the gut microbiota composition in favor to the host. However, the broader health implications of these findings remain unclear and warrant further studies.

Objective: Approximately 20% of people with Anorexia Nervosa (AN) and 10% with Bulimia Nervosa (BN) will eventually develop a long‐standing illness. Although there is no set definition for Severe and Enduring eating Disorder (SE‐ED), the common criteria relate to a long duration of the disorder and a number of unsuccessful treatment attempts. Research evidence for treatment of SE‐ED remains limited, thus the objective of this systematic review was to describe different treatment interventions and their effects on SE‐ED‐related outcomes.Method: A systematic search for quantitative treatment studies of adult participants with SE‐ED was conducted in June 2019 (PROSPERO, CRD42018115802) with no restriction on eating disorder type. Altogether, 2,938 studies were included for title and abstract screening.Results: After systematic searches and article screening, 23 studies (3 randomized controlled trials, 3 open‐label studies, 8 naturalistic follow‐up studies, 8 case series and case studies, and 1 partially blinded pilot study) were included in the analysis and data extraction. Methodological quality of the included studies was generally low. Inpatient treatment programs (n = 5) were effective in short‐term symptom reduction, but long‐term results were inconsistent. Outpatient and day‐hospital treatment programs (n = 5) seemed promising for symptom reduction. Drug interventions (n = 5) showed some benefits, especially as adjuvant therapies. Brain stimulation (n = 6) led to improvements in depressive symptoms. Other treatments (n = 2) produced mixed results.Discussion: This is the first systematic review to examine all of the different treatment interventions that have been studied in SE‐ED. The results will inform future interventions in research and clinical practice.

The use of artificial intelligence (AI) to assist with the prevention, identification, and management of eating disorders and body image concerns is exciting, but it is not without risk. Technology is advancing rapidly, and ensuring that responsible standards are in place to mitigate risk and protect users is vital to the success and safety of technologies and users.

Purpose: Urinary iodine concentration (UIC (μg/ml) from spot urine samples collected from school-aged children is used to determine the iodine status of populations. Some studies further extrapolate UIC to represent daily iodine intake, based on the assumption that children pass approximately 1 L urine over 24-h, but this has never been assessed in population studies. Therefore, the present review aimed to collate and produce an estimate of the average 24-h urine volume of children and adolescents (> 1 year and < 19 years) from published studies. Methods: EBSCOHOST and EMBASE databases were searched to identify studies which reported the mean 24-h urinary volume of healthy children (> 1 year and < 19 years). The overall mean (95% CI) estimate of 24-h urine volume was determined using a random effects model, broken down by age group. Results: Of the 44 studies identified, a meta-analysis of 27 studies, with at least one criterion for assessing the completeness of urine collections, indicated that the mean urine volume of 2–19 year olds was 773 (654, 893) (95% CI) mL/24-h. When broken down by age group, mean (95% CI) 24-h urine volume was 531 mL/day (454, 607) for 2–5 year olds, 771 mL/day (734, 808) for 6–12 year olds, and 1067 mL/day (855, 1279) for 13–19 year olds. Conclusions: These results demonstrate that the average urine volume of children aged 2–12 years is less than 1 L, therefore, misclassification of iodine intakes may occur when urine volumes fall below or above 1 L. Future studies utilizing spot urine samples to assess iodine status should consider this when extrapolating UIC to represent iodine intakes of a population.