Sonographically Assessed Intra-Abdominal Fat And Cardiometabolic Risk Factors in Adolescents with Extreme Obesity

Inflammatory markers in prepubertal children and their associations with abdominal fat

OBJECTIVE

To evaluate the association between inflammatory markers and abdominal fat assessed by ultrasound in prepubertal children with and without excess weight.

METHODS

A cross-sectional study involving 241 prepubertal children, 156 with obesity, 37 with overweight, and 48 with normal weight, aged five to ten years, who were followed at a research unit on Childhood Obesity from a teaching hospital belonging to a public health system. The concentration of interleukin-6, tumor necrosis factor-α and C-reactive protein were assessed and regression analyses, considering outcome variables such as abdominal wall and intra-abdominal fat thickness measured by ultrasound, were performed.

RESULTS

The findings highlighted an association between abdominal fat and inflammatory markers, even in children at this young age group. Subcutaneous fat showed a stronger association with inflammatory biomarkers compared to intra-abdominal fat when performing logistic regression, with a positive association between tumor necrosis factor-α and abdominal wall thickness equal to or greater than the 75th percentile in adjusted logistic regression (OR: 18.12; CI 95 %: 1.57: 209.55).

CONCLUSIONS

Abdominal wall fat, in contrast to what is often observed in adults, appears to have a greater impact on chronic inflammation related to excessive weight in very young children.

Twelve-Month Outcomes after Metabolic and Bariatric Surgery among Youths Participating in a Structured Preparation and Follow-Up Program: Results of the Youth with Extreme Obesity Study

INTRODUCTION

While invasive and associated with risks, metabolic and bariatric surgery (MBS) can promote sustained weight loss and substantial health benefits in youths with extreme obesity. The path toward informed decision making for or against MBS is poorly characterized and postoperative follow-up to assess risks and benefits is inconsistent. In youths with extreme obesity, we aimed to evaluate decision making toward MBS, as well as MBS outcomes and adherence with follow-up and recommendations in the setting of a structured pre- and post-MBS program.

METHODS

Participants were recruited in the setting of the multicenter "Youth with Extreme Obesity Study" (YES). YES is a cohort study in adolescents and young adults aged 14-24 years with obesity (BMI ≥30.0 kg/m2) who were recruited at four medical centers and one job center in Germany between 2012 and 2018. Participants at two medical centers with BMI ≥35 kg/m2, aged 14-24 years, and interested in pursuing MBS were included in the subproject 3 "Safety and effectiveness of weight loss surgery in adolescents with severe obesity within a structured pre- and post-surgery treatment program - an observational study" that comprised a 2-months pre- and 12-months post-MBS program.

RESULTS

Twenty-eight of 169 youths (17%) with BMI ≥35 kg/m2 were interested in MBS. Twenty-six fulfilled published eligibility criteria for MBS and participated in the structured pre-MBS preparation program. Of these, 9 participants (2 females) decided against, and 17 (n = 11 females) decided for MBS (sleeve gastrectomy). The 12-month follow-up rate was high (16/17 [94%]) and all participants achieved significant weight reduction (ΔBMI: -16.1 ± 5.6 kg/m2). Eleven of 16 participants (69%) reported taking the prescribed dietary supplements in the first year after MBS, but only five of them (31%) did so daily. In contrast to the high 12-month retention rate, follow-up after completion of the structured program was low at 24-months (9/16 [56%]) and at 36-months (5/15 [36%]), respectively.

CONCLUSION

Participants demonstrated active decision making for or against MBS and high adherence with the structured pre- and 12 months post-MBS program, but participation was low thereafter. These findings endorse the need for longer term structured post-MBS programs to capture long-term outcomes and provide adequate care in this vulnerable group at the transition to adulthood.

Flavor perception and health benefits of tea

As one of the most consumed non-alcoholic beverages in the world, tea is acclaimed for its pleasant flavor and various health benefits. Different types of tea present a distinctive flavor and bioactivity due to the changes in the composition and proportion of respective compounds. This article aimed to provide a more comprehensive understanding of tea flavor (including aroma and taste) and the character of tea in preventing and alleviating diseases. The recent advanced modern analytical techniques for revealing flavor components in tea, including enrichment, identification, quantitation, statistics, and sensory evaluation methodologies, were summarized in the following content. Besides, the role of tea in anti-cancer, preventing cardiovascular disease and metabolic syndrome, anti-aging and neuroprotection, and regulating gut microbiota was also listed in this article. Moreover, questions and outlooks were mentioned to objectify tea products' flavor quality and health benefits on a molecular level and significantly promote our understanding of the comprehensive value of tea as a satisfactory health beverage in the future.

Evaluating human basal metabolism: the erroneous and misleading use of so-called "prediction equations"

Prediction (regression) equations are widely used, but their reliability as predictive tools is questionable as they provide contradicting results. The key point is that values calculated by regression equations are not precisely defined numbers but lie within a range of possible values in the standard deviation interval, none of which can be considered as the most probable. Ignoring this point leads to illicit/improper calculations, generating wrong results, which may have adverse consequences for human health. To demonstrate this, we applied the equations of Harris and Benedict in a reverse method, i.e. calculating (predicting) the daily energy expenditure in the same subjects used to obtain the equations and comparing values with the original measured data. We used the Bland-Altman and frequency distribution analyses. We found large differences in both individual data and population characteristics, showing that prediction equations are not predictive tools.