Background: The high proportion of people with overweight and obesity has become a worldwide problem in recent decades, mainly due to health consequences, such as cardiovascular diseases, neoplasia, and type 2 diabetes mellitus. Regarding effective countermeasures, the digitization of health services offers numerous potentials, which, however, have not yet been sufficiently evaluated. Web-based health programs are becoming increasingly interactive and can provide individuals with effective long-term weight management support. Objective: The purpose of this randomized controlled clinical trial was to evaluate the effectiveness of an interactive web-based weight loss program on anthropometric, cardiometabolic, and behavioral variables and to compare it with a noninteractive web-based weight loss program. Methods: The randomized controlled trial included people who were aged between 18 and 65 years (mean 48.92, SD 11.17 years) and had a BMI of 27.5 to 34.9 kg/m2 (mean 30.71, SD 2.13 kg/m2). Participants (n=153) were assigned to either (1) an interactive and fully automated web-based health program (intervention) or (2) a noninteractive web-based health program (control). The intervention program focused on dietary energy density and allowed for dietary documentation with appropriate feedback on energy density and nutrients. The control group only received information on weight loss and energy density, but the website did not contain interactive content. Examinations were performed at baseline (t0), at the end of the 12-week intervention (t1), and at 6 months (t2) and 12 months (t3) thereafter. The primary outcome was body weight. The secondary outcomes were cardiometabolic variables as well as dietary and physical activity behaviors. Robust linear mixed models were used to evaluate the primary and secondary outcomes. Results: The intervention group showed significant improvements in anthropometric variables, such as body weight (P=.004), waist circumference (P=.002), and fat mass (P=.02), compared with the control group over the course of the study. The mean weight loss after the 12-month follow-up was 4.18 kg (4.7%) in the intervention group versus 1.29 kg (1.5%) in the control group compared with the initial weight. The results of the nutritional analysis showed that the energy density concept was significantly better implemented in the intervention group. Significant differences in cardiometabolic variables were not detected between the 2 groups. Conclusions: The interactive web-based health program was effective in reducing body weight and improving body composition in adults with overweight and obesity. However, these improvements were not associated with relevant changes in cardiometabolic variables, although it should be noted that the study population was predominantly metabolically healthy. Trial Registration: German Clinical Trials Register DRKS00020249; https://drks.de/search/en/trial/DRKS00020249 International Registered Report Identifier (IRRID): RR2-10.3390/ijerph19031393

Bioactive peptides are physiologically active peptides mostly derived from proteins following gastrointestinal digestion, fermentation or hydrolysis by proteolytic enzymes. It has been shown that bioactive peptides can be resorbed in their intact form and have repeatedly been shown to have a positive effect on health-related parameters such as hypertension, dyslipoproteinemia, inflammation and oxidative stress. In recent years, there has been increasing evidence that biologically active peptides could also play an important role in sports nutrition. Current studies have shown that bioactive peptides could have a positive impact on changes in body composition and muscular performance, reduce muscle damage following exercise and induce beneficial adaptions within the connective tissue. In the following overview, potential mechanisms as well as possible limitations regarding the sports-related effect of bioactive peptides and their potential mechanisms are presented and discussed. In addition, practical applications will be discussed on how bioactive peptides can be integrated into a nutritional approach in sports to enhance athletic performance as well as prevent injuries and improve the rehabilitation process.

Web-based lifestyle interventions have attracted considerable research interest. Available evidence on such interventions suggests health-promoting effects, but further research is needed. Therefore, this study aims to investigate short-, medium-, and long-term health effects of a web-based health program (“TK-HealthCoach”, TK-HC) offered by a national statutory health insurance fund (Techniker Krankenkasse, TK). The study comprises two randomized controlled clinical trials to evaluate the health goals “Increasing Fitness” (F_clin) and “Losing and Maintaining Weight” (W_clin). A total of n = 186 physically inactive (F_clin) and n = 150 overweight or obese (W_clin) adults will be randomly assigned to a 12-week interactive (TK-HC) or non-interactive web-based health program using permuted block randomization with a 1:1 allocation ratio. Primary outcomes include cardiorespiratory fitness (F_clin) and body weight (W_clin). Secondary outcomes comprise musculoskeletal fitness (F_clin), physical activity and dietary behavior, anthropometry, blood pressure, blood levels, and vascular health (F_clin, W_clin). All outcomes will be measured before and after the 12-week intervention and after a 6- and 12-month follow-up. Additionally, usage behavior data on the health programs will be assessed. Linear mixed models (LMMs) will be used for statistical analysis. Findings of this study will expand the available evidence on web-based lifestyle interventions.

Background: Diet quality indices can provide important information about relationships between diet and health independent of energy balance. The Healthy Eating Index-2015 (HEI-2015) is widely used and has been extensively evaluated. However, due to imperial units the HEI-2015 is difficult to apply in countries with metric systems. Our objective was to develop a metric version of the HEI-2015 and compare it to the original. The metric Healthy Eating Index-2015 (mHEI-2015) is intended to simplify the application of a dietary quality index in countries using the metric system.Methods: We developed a metric database logic following the methodology of the HEI-2015, which allows the application to metric databases and was applied to Food Patterns Equivalents Database (FPED). The HEI-2015 was calculated for the National Health and Nutrition Examination Survey (NHANES) 2017-2018 and the scoring standards for each component of the mHEI-2015 was calibrated against it. For the assessment of agreement between indices, HEI-2015 and mHEI-2015 were calculated for NHANES 2015-2016 and a Bland–Altman plot was created.Results: Healthy Eating Index-2015 and mHEI-2015 for the NHANES 2015-2016 averaged 52.5 ± 13.5 and 52.6 ± 13.2, respectively. The total scores as well as component scores of the indices were strongly correlated. The Bland–Altman plot revealed a high agreement of the total scores. An illustrated analysis of six different menu plans showed only minor differences between the HEI-2015 and mHEI-2015 component scores.Conclusion: The mHEI-2015 allows for superior analysis of metric dietary data to better examine the relationship between chronic diseases and diet. The streamlined metric methodology enables straightforward application to metric food databases and thus the development of country-specific indices.

Personal behavior patterns, such as unhealthy diet and lack of physical activity, lead to the development of overweight and obesity. These are associated with other comorbidities, reduced quality of life, premature frailty and increased mortality. Personalized web-based interventions are promising in inducing behavioral change leading to effective reductions in body weight at relatively low costs. However, the long-term effects have not been thoroughly investigated. This work evaluates the effectiveness of web-based interactive weight loss coaching and compares it to a non-interactive web-based health program. Therefore, a randomized controlled trial (RCT) was implemented, measuring primary and secondary outcomes at four time points (program start; end of the 12-week-program; 6 months after program end, 12 months after program end). The net sample covered 1499 subjects in the intervention group and 1492 in the control group. On average, the IG was 43 years old (±13.6), 80.1% male, and had 86.4 kg body weight (±16.1) at baseline. The CG was 42.7 years old (±13.9), 79.5% male and had a mean body weight of 86.1 (±15.7). Multilevel analyses with fixed effects were carried out both from the perspective of an intention-to-treat (ITT) and a complete cases approach (CCA). In sum, our adjusted models suggest a weight loss of 0.4 kg per time point. At the end of the program, significant differences in weight loss in % to baseline (delta M = 1.8 in the CCA) were observed in favor of the intervention group. From a long-term perspective, no superiority of the intervention group in comparison to the control group could be found. More intensive use of the program was not statistically associated with higher weight loss.

This randomized, controlled clinical trial examined the impact of a web-based weight loss intervention on diet quality. Furthermore, it was investigated whether corresponding changes in diet quality were associated with changes in measures of cardiovascular risk profile. Individuals with a body mass index (BMI) of 27.5 to 34.9 kg/m² and an age of 18 to 65 y were assigned to either an interactive and fully automated web-based weight loss program focusing on dietary energy density (intervention) or a non-interactive web-based weight loss program (control). Examinations were performed at baseline (t0), after the 12-week web-based intervention (t1), and after an additional 6 (t2) and 12 months (t3). Based on a dietary record, the Healthy Eating Index-NVS (HEI-NVS) was calculated and analyzed using a robust linear mixed model. In addition, bootstrapped correlations were performed independently of study group to examine associations between change in HEI-NVS and change in dietary, anthropometric, and cardiometabolic variables. A total of n = 153 participants with a mean BMI of 30.71 kg/m² (SD 2.13) and an average age of 48.92 y (SD 11.17) were included in the study. HEI-NVS improved significantly in the intervention group from baseline (t0) to t2 (p = 0.003) and to t3 (p = 0.037), whereby the course was significantly different up to t2 (p = 0.013) and not significantly different up to t3 (p = 0.054) compared to the control group. Independent of study group, there was a significant negative association between change in HEI-NVS and dietary energy density. A higher total score in HEI-NVS did not correlate with improvements in cardiovascular risk profile. The interactive and fully automated web-based weight loss program improved diet quality. Independent of study group, changes in HEI-NVS correlated with changes in energy density, but there was no association between improvements in HEI-NVS and improvements in cardiovascular risk profile.