Sleep duration is associated with liver steatosis in children depending on body adiposity.

Sleep is a factor associated with overweight/obesity risk, wherein interactions with fatty liver should be ascertained. The aim of this cross-sectional study was to analyze the possible relationships of sleep with liver health and whether this interplay is related to body adiposity distribution in children and adolescents. Anthropometric, clinical, and biochemical measurements were performed in children and adolescents (2-18 years old) with overweight/obesity (n = 854). Body fat distribution was clinically assessed, and several hepatic markers, including hepatic steatosis index, were calculated. Sleep time mediation (hours/day) in the relationship between the hepatic steatosis index and body fat distribution was investigated. Differences among diverse fatty liver disease scores were found between children with overweight or obesity (p < 0.05). Linear regression models showed associations between hepatic steatosis index and lifestyle markers (p < 0.001). Hepatic steatosis index was higher (about + 15%) in children with obesity compared to overweight (p < 0.001). Pear-shaped body fat distribution may seemingly play a more detrimental role on liver fat deposition. The association between sleep time and hepatic steatosis index was dependent on body mass index z-score. Post hoc analyses showed that 39% of the relationship of body fat distribution on hepatic steatosis index may be explained by sleep time.  Conclusion: An association of sleep time in the relationship between body fat distribution and hepatic steatosis index was observed in children and adolescents with overweight/obesity, which can be relevant in the prevention and treatment of excessive adiposity between 2 and 18 years old. CLINICAL TRIAL: NCT04805762.    Import: As part of a healthy lifestyle, sleep duration might be a modifiable factor in the management of fatty liver disease in children. WHAT IS KNOWN: • Sleep is an influential factor of overweight and obesity in children. • Excessive adiposity is associated with liver status in children and adolescents. WHAT IS NEW: • Sleep time plays a role in the relationship between body fat distribution and liver disease. • Monitoring sleep pattern may be beneficial in the treatment of hepatic steatosis in children with excessive body weight.

Possible metabolic interplay between quality of life and fecal microbiota in a presenior population: Preliminary results.

OBJECTIVES: The number of people aged ≥60 y is increasing worldwide, so establishing a relationship between lifestyle and health-associated factors, such as gut microbiota in an older population, is important. This study aimed to characterize the gut microbiota of a presenior population, and analyze the association between some bacteria and quality of life with the Short Form (SF) 36 questionnaire. METHODS: Participants were adult men and women ages 50 to 80 y (n = 74). In addition to the SF-36 questionnaire, fecal samples were collected in cryotubes, and 16S RNA gene sequencing was performed to characterize microbial features. Participants were classified into two groups according to SF-36 punctuation. Linear and logistic regression models were performed to assess the possible association between any bacterial bowl and SF-36 score. Receiver operating characteristics curves were fitted to define the relative diagnostic strength of different bacterial taxa for the correct determination of quality of life. RESULTS: A positive relationship was established between SF-36 score and Actinobacteria (P = 0.0310; R = 0.2510) compared with Peptostreptococcaceae (P = 0.0259; R = -0.2589), which increased with decreasing quality of life. Logistic regressions models and receiver operating characteristics curves showed that the relative abundance of Actinobacteria and Peptostreptococcaceae may be useful to predict quality of life in a presenior population (area under the curve: 0.71). CONCLUSIONS: Quality of life may be associated with the relative abundance of certain bacteria, especially Actinobacteria and Peptostreptococcaceae, which may have a specific effect on certain markers and health care, which is important to improve quality of life in older populations.

Fecal microbiota relationships with childhood obesity: A scoping comprehensive review.

Childhood obesity is a costly burden in most regions with relevant and adverse long-term health consequences in adult life. Several studies have associated excessive body weight with a specific profile of gut microbiota. Different factors related to fecal microorganism abundance seem to contribute to childhood obesity, such as gestational weight gain, perinatal diet, antibiotic administration to the mother and/or child, birth delivery, and feeding patterns, among others. This review reports and discusses diverse factors that affect the infant intestinal microbiota with putative or possible implications on the increase of the obesity childhood rates as well as microbiota shifts associated with excessive body weight in children.

The hypertriglyceridemic-waist phenotype as a valuable and integrative mirror of metabolic syndrome traits.

Rates of non-communicable diseases (NCDs), such as obesity, diabetes, cardiovascular events and cancer, continue to rise worldwide, which require objective instruments for preventive and management actions. Diverse anthropometric and biochemical markers have been used to qualitatively evaluate degrees of disease, metabolic traits and evolution of nutritional status. The aim of this study was to integrate and assess the interactions between an anthropometric measurement, such as waist circumference (WC), and biochemical data, such as the triglyceride glucose index (TyG), in order to individually characterize metabolic syndrome (MetS) features considering the hypertriglyceridemic waist phenotype as a marker. An ancillary cross-sectional study was conducted using anthropometric measurements, such as weight, height, waist and hip circumferences, as well as fasting biochemical data of 314 participants. Different indices based on WC (WC, WC*TG and WC*TyG) were estimated to compute MetS components and accompanying comorbidities. ROC curves were fitted to define the strength of the analyses and the validity of the relationships. Associations were confirmed between anthropometric, biochemical and combined indices with some chronic disease manifestations, including hyperglycemia, hypertension and dyslipidemia. Both WC*TG and WC*TyG indices showed similar performance in diagnosing MetS (area under the ROC curve = 0.81). Interestingly, when participants were categorized according to a reference value of the WC*TyG index (842.7 cm*mg/dl), our results evidenced that subjects classified over this limit presented statistically higher prevalence of MetS and accompanying individual components with clinical relevance for interventions. These results revealed that WC*TyG mirrors the hypertriglyceridemic phenotype, which suggests may serve as a good indicator to define the metabolic syndrome phenotype and a suitable, sensitive, and simple proxy to complement others. A reference point was proposed with a good clinical performance and maximized sensitivity and specificity values.

Definition of nutritionally qualitative categorizing (proto)nutritypes and a pilot quantitative nutrimeter for mirroring nutritional well-being based on a quality of life health related questionnaire.

Introduction: Background: there are numerous approaches to assess nutritional status, which are putatively applied to nutritionally classify diseased people, but less information is available to study the role of environmental factors on nutritional well-being. A qualitative (nutritypes) and quantitative (nutrimeter) nutritional categorization based on dietary, lifestyle and disease criteria can be a useful nutritional approach to personalize health interventions and identify at risk individuals. Methods: cross-sectional study conducted on 102 patients (60 women), evaluating quality of life using the Short-Form 36 questionnaire (SF-36) and lifestyle factors with a general questionnaire, the Mediterranean Diet Adherence Screener (MEDAS) and the Global Physical Activity Questionnaire (GPAQ). A nutrimeter based on physical activity, fat mass, diet and diseases (hypertension, prediabetes, obesity and dyslipidemia) data was defined with an equation to quantitatively score the nutritive well-being of the participants, and classify them into two (proto)nutritypes. Results: participants were categorized into two groups (lower/higher global health) according to quality of life. Significant or marginal statistical differences in physical activity, fat mass, diet and disease were found (all p < 0.1). Two (proto)nutritypes were identified based on participant's age, sex, fat mass, physical activity, diet and diseases. Participants classified as high nutritional well-being nutritype showed higher values for physical, mental and global health dimensions. Age, fat mass, physical activity and diet, when categorized by the median, confirm that the designed nutritional well-being nutrimeter identified two (proto)nutritypes. Conclusions: the association between phenotypical (fat mass/diseases) and lifestyle factors (diet/physical activity) with quality of life allowed categorizing individuals with a nutritional quantitative score or nutrimeter according to their nutritional well-being and discriminate two qualitative (proto)nutritypes.

Introducción: Introducción: el estado nutricional puede clasificar metabólicamente a las personas enfermas, pero falta información sobre el papel de distintos factores ambientales relacionados con el bienestar nutricional. Una categorización nutricional cualitativa (nutritipo) y cuantitativa (nutrimetro) basada en la dieta, el estilo de vida y la enfermedad es una herramienta nutricional útil para personalizar las intervenciones de salud e identificar a aquellos individuos en riesgo. Métodos: estudio transversal en 102 pacientes, en el que se evalúa la calidad de vida mediante el cuestionario Short-Form 36 (SF-36) y los factores del estilo de vida con un cuestionario general, el Mediterranean Diet Adherence Screener (MEDAS) y el Global Physical Activity Questionnaire (GPAQ). Se diseñó una herramienta de evaluación (nutrimetro) de actividad física, masa grasa, dieta y enfermedades a través de una ecuación para calificar cuantitativamente el bienestar nutricional y clasificar a los participantes en (proto)nutritipos. Resultados: los participantes se clasificaron según la calidad de vida en dos grupos (menor/mayor salud global) y se encontraron diferencias estadísticas (p < 0,1) en la masa grasa, la actividad física, la dieta y las enfermedades. Se identificaron dos (proto)nutritipos en función de la edad, el sexo, la masa grasa, la actividad física, la dieta y las enfermedades. Los participantes clasificados en el nutritipo de alto bienestar nutricional mostraron valores significativamente más altos para las dimensiones físicas, mentales y de salud global. La edad, la masa grasa, la actividad física y la dieta confirman que el nutrimetro diseñado puede discriminar dos (proto)nutritipos. Conclusiones: factores fenotípicos (masa grasa/enfermedades) y del estilo de vida (dieta/actividad física) se han relacionado con la calidad de vida, permitiendo clasificar a individuos con una puntuación nutricional cuantitativa o nutrimetro según su bienestar nutricional y discriminar dos (proto)nutritipos.