BackgroundNutrition therapy is the cornerstone of treating diabetes mellitus. The inclusion of fish (particularly oily fish) at least two times per week is recommended by current international dietary guidelines for type 2 diabetes. In contrast to a large number of human studies examining the effects of oily fish on different cardiovascular risk factors, little research on this topic is available in patients with type 2 diabetes. The aims of this pilot study were to investigate the effects of a sardine-enriched diet on metabolic control, adiponectin, inflammatory markers, erythrocyte membrane fatty acid (EMFA) composition, and gut microbiota in drug-naïve patients with type 2 diabetes.Methods35 drug-naïve patients with type 2 diabetes were randomized to follow either a type 2 diabetes standard diet (control group: CG), or a standard diet enriched with 100 g of sardines 5 days a week (sardine group: SG) for 6 months. Anthropometric, dietary information, fasting glycated hemoglobin, glucose, insulin, adiponectin, inflammatory markers, EMFA and specific bacterial strains were determined before and after intervention.ResultsThere were no significant differences in glycemic control between groups at the end of the study. Both groups decreased plasma insulin (SG: −35.3 %, P = 0.01, CG: −22.6 %, P = 0.02) and homeostasis model of assessment - insulin resistance (HOMA-IR) (SG: −39.2 %, P = 0.007, CG: −21.8 %, P = 0.04) at 6-months from baseline. However only SG increased adiponectin in plasma compared to baseline level (+40.7 %, P = 0.04). The omega-3 index increased 2.6 % in the SG compared to 0.6 % in the CG (P = 0.001). Both dietary interventions decreased phylum Firmicutes (SG and CG: P = 0.04) and increased E. coli concentrations (SG: P = 0.01, CG: P = 0.03) at the end of the study from baseline, whereas SG decreased Firmicutes/Bacteroidetes ratio (P = 0.04) and increased Bacteroides-Prevotella (P = 0.004) compared to baseline.ConclusionsAlthough enriching diet with 100 g of sardines 5 days a week during 6 months to a type 2 diabetes standard diet seems to have neutral effects on glycemic control in drug-naïve patients with type 2 diabetes, this nutritional intervention could have beneficial effects on cardiovascular risk. Furthermore, both dietary interventions decreased HOMA-IR and altered gut microbiota composition of drug-naïve patients with type 2 diabetes.Trial registrationTrial number and name of the registry: NCT02294526, ClinicalTrials.govElectronic supplementary materialThe online version of this article (doi:10.1186/s12944-016-0245-0) contains supplementary material, which is available to authorized users.

Objective: Abdominal fat ultrasound (US) is a simple clinical tool that may allow measures of fat depots not visible using common dual-energy X-ray absorptiometry (DEXA) or computerized tomography (CT) imaging. The aim of this study was to validate the technique, give measures of superficial and profound subcutaneous, preperitoneal, omental and perirenal (retroperitoneal) fat and correlate them with MS markers. Methods: Sequential US measures of these five abdominal fat layers were done at 397 adults. Blood pressure (BP), body mass index (BMI), waist, body fat %, HOMA-IR index (homeostatic model assessment of insulin resistance), lipid profile and leptin were recorded. Metabolic syndrome (MS) was defined according to Cholesterol education programme adult treatment panel III (ATPIII) criteria. Results: Subcutaneous and omental fat were increased among people with obesity, whereas preperitoneal and perirenal fat did not show any difference according to BMI or waist. Women showed thicker subcutaneous fat (both superficial and profound), whereas men had bigger omental fat. Both postmenopausal and diabetic patients had changes in omental fat only, whereas patients with fatty liver showed thicker preperitoneal and perirenal fat, as well. MS patients showed both thicker perirenal and omental fat. A cutoff of 54 mm in male (M)/34 mm in female (F) of omental fat and 22.5 mm (M)/12.5 mm (F) of perirenal fat could be predictive of later MS onset. Conclusions: US is a valid method to measure all different abdominal fat depots. Omental and perirenal fat measures may classify patients at risk for MS. Preperitoneal fat depot may also correlate with fatty liver disease.

Background The use of apps for weight management has increased over recent years; however, there is a lack of evidence regarding the efficacy and safety of these apps. The EVALAPPS project will develop and validate an assessment instrument to specifically assess the safety and efficacy of weight management apps. Objective The aim of this study was to reach a consensus among stakeholders on a comprehensive set of criteria to guide development of the EVALAPPS assessment instrument. A modified Delphi process was used in order to verify the robustness of the criteria that had been identified through a literature review and to prioritize a set of the identified criteria. Methods Stakeholders (n=31) were invited to participate in a 2-round Delphi process with 114 initial criteria that had been identified from the literature. In round 1, participants rated criteria according to relevance on a scale from 0 (“I suggest this criterion is excluded”) to 5 (“This criterion is extremely relevant”). A criterion was accepted if the median rating was 4 or higher and if the relative intraquartile range was equal to 0.67 or lower. In round 2, participants were asked about criteria that had been discarded in round 1. A prioritization strategy was used to identify crucial criteria according to (1) the importance attributed by participants (criteria with a mean rating of 4.00 or higher), (2) the level of consensus (criteria with a score of 4 or 5 by at least 80% of the participants). Results The response rate was 83.9% (26/31) in round 1 and 90.3% (28/31) in round 2. A total of 107 out of 114 criteria (93.9%) were accepted by consensus—105 criteria in round 1 and 2 criteria in round 2. After prioritization, 53 criteria were deemed crucial. These related mainly to the dimensions of security and privacy (13/53, 24.5%) and usability (9/53, 17.0%), followed by activity data (5/53, 9.4%), clinical effectiveness (5/53, 9.4%), and reliability (5/53, 9.4%). Conclusions Results confirmed the robustness of the criteria that were identified, with those relating to security and privacy being deemed most relevant by stakeholders. Additionally, a specific set of criteria based on health indicators (activity data, physical state data, and personal data) was also prioritized.

Background The use of apps to tackle overweight and obesity by tracking physical and dietary patterns and providing recommendations and motivation strategies to achieve personalized goals has increased over recent years. However, evidence of the efficacy, effectiveness, and safety of these apps is severely lacking. Objective The aim of this study was to identify efficacy, safety, and effectiveness criteria used to assess weight control, overweight, and obesity management in mobile health (mHealth) interventions through a systematic review. Methods PubMed, PsycINFO, Scopus, UK Trial Database, ClinicalTrials.gov, and the Cochrane Library were surveyed up to May 2018. All types of clinical studies were considered. A total of 2 independent reviewers assessed quality using Scottish Intercollegiate Guidelines Network (SIGN) criteria. Ratings were used to provide an overall score for each study (low, moderate, or high). Data were synthesized in evidence tables. Results From 233 potentially relevant publications, only 28 studies were included. Of these, 13 (46%) were randomized control trials, 11 were single-arm studies (39%), 3 were nonrandomized controlled trials (11%), and 1 study was a cluster randomized trial (4%). The studies were classified as low (15), high (7), and moderate (6) quality according to SIGN criteria. All studies focused on efficacy, with only 1 trial mentioning safety and another 1 effectiveness. In 11 studies, the apps were used as stand-alone interventions, the others were multicomponent studies that included other tools for support such as sensors or websites. The main management tool included in the apps was feedback messaging (24), followed by goal-setting mechanisms (20) and self-monitoring (19). The majority of studies took weight or body mass index loss as the main outcome (22) followed by changes in physical activity (14) and diet (12). Regarding outputs, usability, adherence, and engagement (17) were the most reported, followed by satisfaction (7) and acceptability (4). Conclusions There is a remarkable heterogeneity among these studies and the majority have methodological limitations that leave considerable room for improvement. Further research is required to identify all relevant criteria for assessing the efficacy of mHealth interventions in the management of overweight and obesity. Trial Registration PROSPERO CRD42017056761; https://tinyurl.com/y2zhxtjx

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BACKGROUND The use of Mobile Applications (apps) for managing overweightness/obesity has increased over recent years. However, there is a lack of evidence on the efficacy, effectiveness and safety of these apps. The EVALAPPS project will develop and validate an assessment instrument to specifically assess these dimensions of overweightness/obesity management apps. OBJECTIVE To reach a consensus among stakeholders on a comprehensive set of criteria to guide development of the EVALAPPS assessment instrument. A modified Delphi process was used in order to: 1) verify the robustness of the criteria identified through a literature review; 2) prioritize a set of the identified criteria. METHODS 31 stakeholders were invited to participate in a 2 round Delphi process with an initial number of 114 criteria identified from the literature. In Round 1 participants rated criteria according to relevance (0 = “I suggest this criterion is excluded”, 5 = “This criterion is extremely relevant”). A criterion was accepted if a median value equal or greater than 4 and RIQR equal or less than 0.67 was reached. In Round 2 participants were asked about criteria discarded in round 1. The prioritization strategy was based on identifying those indicators categorized as Crucial in Round 1 according to: a) the importance attributed by participants (criteria with a mean value ≥ 4.00); and, b) the level of agreement (criteria scoring almost 4-5 by 80% of the participants). RESULTS The response rate was 84% in Round 1, 90% in Round 2. A total number of 107 criteria were accepted by consensus (94%), 105 in Round 1 and 2 in Round 2. After the prioritization strategy, 53 criteria were deemed Crucial. These related mainly to the Security and Privacy (24.5%) and Usability (17.0%) dimensions, followed by Health indicators: Activity data, Clinical Effectiveness and Reliability (9.4% each). CONCLUSIONS Results confirmed the robustness of the identified criteria, with those relating to Security and Privacy being deemed most relevant by stakeholders. Additionally, a specific set of criteria based on Health indicators was also prioritized (taken together, 20.7%). CLINICALTRIAL

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