Annals of Nutrition and Metabolism最新文献

Background: Breastmilk strengthens host defence mechanisms through innate and adaptive immune development and enhances the immature immunologic system of the neonate during a delicate and crucial period. As well as mammalian evolution, some of the mechanisms that explain active stimulation of the infant's immune system include three major phenomena: 1) human milk accelerates the maturation of gut barrier function in the otherwise immature neonatal mucosa; 2) a range of innate and adaptive immune factors in human milk protect the neonate and young infant from pathogenic damage; and 3) components in human milk actively modulate inflammatory reactions. Breastmilk feeding of newborns has been associated with reduced disease in early infancy and later life that may be attributed to many of the bioactive factors identified in milk such as extracellular vesicles, exosomes, micro RNA, stem cells, cytokines, hormones, growth factors, colony stimulating factors, and the nutrients, oligosaccharides, lipids and proteins that promote optimum development and protect against disease.

Summary: Our current knowledge of the mechanisms whereby human milk impacts on infant immunological development provides evidence that breastfeeding should be promoted.

Key message: All mothers should be encouraged and supported to exclusively breastfeed for at least the first six months of life. Breastfeeding and complementary foods beyond six months is recommended up to two years, to promote optimum health of the child.

Background: Abdominoperineal resection (APR) for low rectal cancer results in permanent stoma, psychosocial distress, and systemic inflammation, impairing quality of life and survival. This study evaluated whether app-based cognitive behavioral therapy (CBT) plus biomarker-guided nutrition could improve recovery and survival.

Methods: In this prospective, single-center, non-randomized controlled cohort, 186 patients with stage I-III low rectal adenocarcinoma undergoing curative abdominoperineal resection (APR) all received standard Enhanced Recovery After Surgery (ERAS) care. Patients were managed with ERAS alone or ERAS plus an integrative program combining digital cognitive behavioral therapy (CBT) and inflammation-guided precision nutrition, tailored according to prognostic nutritional index (PNI), C-reactive protein (CRP), and interleukin-6 (IL-6). Interventions began two weeks preoperatively and continued for six months. Primary outcomes were longitudinal changes in depression, sleep quality, sexual function, and health-related quality of life. Secondary outcomes included inflammatory markers, skeletal muscle index (SMI), and two-year disease-free and overall survival.

Results: By month 3, the intervention group showed greater improvements in all primary outcomes, sustained through 24 months (all p < 0.001). CRP and IL-6 were reduced by day 7 (both p < 0.001), with faster recovery and shorter hospitalization. SMI was better preserved at 24 months (p = 0.046). Two-year DFS (hazard ratio [HR] = 0.48, 95% confidence interval [CI] 0.26-0.89, p = 0.021) and OS (HR = 0.44, 95% CI 0.20-0.95, p = 0.036) were significantly improved. Findings remained robust in multivariable and sensitivity analyses.

Conclusions: Among patients undergoing APR managed within an ERAS pathway, the addition of digital CBT and inflammation-guided nutrition was associated with improved multidimensional recovery and favorable survival signals. Given the non-randomized design, these results should be regarded as hypothesis-generating and support further evaluation of ERAS-based integrative strategies in randomized multicenter trials.

Introduction: Sarcopenic obesity (SO) is defined as co-existence of obesity and sarcopenia. The co-occurrence of sarcopenia and obesity might act synergistically and SO might have a greater effect on adverse health outcomes than sarcopenia or obesity alone. The term osteosarcopenic obesity was introduced recently to describe the impairment of bone, muscle, and fat tissues. This study aimed to evaluate cardiometabolic and bone parameters in relation with the presence of sarcopenia and their association with components of sarcopenia (muscle strength, muscle mass, and physical performance) in children and adolescents with obesity.

Methods: A total of 95 children and adolescents with obesity (diagnosed with the use of International Obesity Task Force criteria) with a mean age of 12.7(±3) years participated in this study. Body composition was evaluated by bioelectrical impedance (BIA) and dual-energy X-ray absorptiometry (DXA). Grip strength and physical performance (six-minute walk test, timed up and go test) were evaluated. Blood pressure was measured and blood samples were taken. Sarcopenia was defined as co-occurrence of weak handgrip strength (≤10th centile) according to Dodds et al. [PLoS One. 2014;9(12):e113637] and low DXA-ASMM% (appendicular muscle mass/weight × 100%) (≤9nd centile) according to McCarthy et al. [Pediatr Obes. 2014;9(4):249-59].

Results: The overall prevalence of sarcopenia was 17.89%. In comparison with patients without sarcopenia, those with sarcopenia had significantly higher high-density lipoprotein cholesterol (HDL-C) and significantly lower total body less head bone mineral content (BMC-TBLH) and total body less head bone mineral density (BMD-TBLH). Partial correlation analyses controlling for age and sex were performed. BIA-ASMM% and DXA-ASMM% were negatively correlated with insulin 0', homeostasis model assessment of insulin resistance (HOMA-IR) and diastolic blood pressure. DXA-ASMM% correlated negatively with total cholesterol. Handgrip strength was negatively correlated with total cholesterol, low-density lipoprotein (LDL), and HDL cholesterol. Maximal handgrip was positively correlated with bone parameters (BMC-TBLH, BMC-lumbar spine (LS), BMD-TBLH, and BMD-LS). The highest diagnostic value for detecting sarcopenia in children and adolescents with obesity was achieved by HDL-C (cut-off value >44.8 mg/dL), area under ROC curve (AUC) = 0.73).

Conclusion: Muscle mass and muscle strength were significantly associated with cardiometabolic parameters in children and adolescents with obesity. The best independent predictive risk factor for diagnosing sarcopenia in obese children and adolescents is HDL-C (cut-off value >44.8 mg/dL). The results of our study regarding bone parameters suggest the presence of osteosarcopenic obesity.

Background: Arterial stiffness (AS) is a well-established independent predictor of cardiovascular events and all-cause mortality. However, few studies have examined the comparative predictive performance of traditional obesity indicators (BMI, WC) versus novel indices (WWI, ABSI, BRI, CI) for AS.

Methods: This study utilized baseline data from the Shaanxi cohort of the Regional Ethnic Cohort Study in Northwest China (RECS). Anthropometric measurements were collected to calculate obesity indicators, and estimated pulse wave velocity (ePWV) served as a surrogate for AS. Logistic regression and restricted cubic spline models assessed the associations and dose-response relationships between obesity indicators and ePWV. Receiver operating characteristic (ROC) curves were used to compare the predictive performance of these indicators.

Results: After adjusting for confounders, all obesity indices exhibited significant positive nonlinear associations with ePWV (P for nonlinearity < 0.001). Participants with overweight (OR = 1.63, 95% CI: 1.51-1.77) or obesity (OR = 2.13, 95% CI: 1.90-2.40) had a higher risk of elevated ePWV compared to those with normal BMI. Central adiposity (based on WC) was associated with a 70% increased risk (OR = 1.70, 95% CI: 1.58-1.83). Similarly, individuals in the highest quartile (Q4) of WWI, ABSI, BRI, and CI showed 1.40-, 1.14-, 2.24-, and 1.52-fold higher risks of elevated ePWV, respectively, compared to the lowest quartile (Q1). Novel obesity indices demonstrated superior predictive performance over traditional measures, with WWI exhibiting the strongest discriminative ability.

Conclusions: Obesity significantly increases AS risk in Chinese adults, and novel obesity indicators (particularly WWI) could outperform BMI and WC in predicting AS. Managing abdominal obesity and reducing visceral adiposity may mitigate AS risk, thereby lowering the likelihood of cardiovascular disease.

Introduction: Milk fat globule epidermal growth factor 8 (MFGE8) represents a recently characterized secreted integrin ligand involved in modulating systemic metabolic processes through impacts on nutrient absorption, gastrointestinal motility, and lipid homeostasis. Current literature supports its relevance in obesity pathogenesis. However, the exploration of MFGE8's function specifically within pediatric obesity contexts remains insufficient. This investigation aimed to delineate relationships between circulating MFGE8 concentrations and diverse obesity-associated parameters in children.

Methods: Our study included 104 participants (32 females, 72 males), consisting of 64 children diagnosed with obesity and 40 normal-weight controls. We measured serum MFGE8 levels employing enzyme-linked immunosorbent assay methodology. Multiple clinical and biochemical measures were evaluated, encompassing body mass index (BMI), waist and hip circumferences, blood pressure, hepatic enzyme patterns, cholesterol parameters, and fasting insulin (FINS).

Results: Obese participants exhibited substantially increased serum MFGE8 concentrations relative to non-obese controls (p < 0.05). MFGE8 levels correlated positively with numerous anthropometric measures: systolic blood pressure, heart rate (BPM), bone age, height, weight, BMI, waist circumference, hip circumference, waist-to-hip ratio, and waist-to-height ratio. Additionally, MFGE8 demonstrated significant positive relationships with multiple metabolic and inflammatory indicators: alanine aminotransferase, triglyceride, FINS, homeostatic model assessment of insulin resistance (HOMA-IR), basal metabolic rate, body fat percentage, uric acid, glutamyl transpeptidase, tumor necrosis factor-α, adiponectin, and leptin. Inverse correlations were identified with albumin and direct bilirubin. Multivariable linear regression modeling identified BMI, HOMA-IR, and male gender as independent positive predictors of MFGE8 concentrations.

Conclusion: Our results demonstrate that elevated MFGE8 levels are linked to pediatric obesity, implying its potential contribution to the development of this condition and associated metabolic complications.

Introduction: In intoxication-type inherited metabolic disorders (IMDs), strict protein restriction is vital; noncompliance may lead to coma or death. Meat and eggs are prohibited lifelong. This study developed personalized low-protein (LP) alternatives and chewable amino acid supplements to improve dietary adherence, palatability, and overall quality of life.

Methods: LP meat, egg, and amino acid-based candy prototypes were produced using a three-dimensional (3D) food printer. Proximate composition, color, texture, and pH measurements were performed. Sensory evaluation was conducted with 15 patients.

Results: Fifteen patients with IMDs participated in sensory testing of 3D-printed LP foods. Visual and overall acceptability scores were high, with 93.3% expressing willingness to include products in their diets. Isoleucine and valine soft candies (SCs) and LP meat analogs received the highest ratings for texture and appearance. Arginine SC scored lower in taste and texture, aligning with instrumental softness data. Open-ended feedback emphasized emotional and dietary impact. Texture profile analysis and proximate composition confirmed feasibility of protein restriction with preserved palatability.

Conclusion: 3D food printing provides visually and texturally acceptable LP options for patients with IMDs, enhancing dietary adherence and social participation. This pioneering study is the first to develop LP meat and egg analogs, offering significant contributions to the field.

The following document contains a total of 30 abstracts selected by the Board of Directors of the European Childhood Obesity Group (ECOG) for publication in the Annals of Nutrition and Metabolism in the context of the 34th ECOG annual congress.

Introduction: Malnutrition leads to negative health outcomes such as delayed recovery, increased hospital stays, and higher costs. The study aimed to develop a predictive tool to diagnose malnutrition using patient data, including anthropometric, phenotypic, and laboratory information.

Methods: A cohort of 252 adult patients was assessed at a tertiary hospital. Logistic regression and decision tree analysis were applied to evaluate the role of the data in predicting the risk of malnutrition. The performances of the models were tested with Akaike information criterion, null deviance, residual deviance, accuracy, and kappa metrics, and the statistical significance of the variables was evaluated with Wald-Z test. Attribute importance ranking was obtained by Bootstrap Optimized Random Univariate Tree Analysis algorithm.

Results: A total of 252 patients, 125 female (49.6%) and 127 male (50.4%), were included in the study. The mean age was 72.57 ± 13.6 years. Malnutrition was diagnosed in 174 patients (69%). According to the equations, the most important characteristics were determined as hand grip strength, weight loss, BMI, and gender. The model achieved high accuracy (89.8%) and a kappa value of 0.79, demonstrating its potential for clinical application.

Conclusion: Machine learning model offers a faster, more efficient alternative to traditional diagnostic tools. The study concludes that machine learning-based models provide superior prediction performance and could significantly enhance the efficiency and accuracy of malnutrition diagnosis in healthcare.