Onealmcneil9952

Background Multicomponent family-based behavioral treatment (FBT) program for pediatric obesity includes nutrition and physical activity education, as well as behavior therapy techniques. Studies suggest that parent weight loss is the best predictor of child weight loss in FBT. However, given the important role that parents play in the implementation of FBT for their child, isolating the effects of specific FBT treatment component requires consideration of parent influences over time. Methods The following treatment components were assessed stimulus control (high/low-fat food items in home), nutrition knowledge, energy intake, physical activity, and parental monitoring, as well as weekly anthropometric measures. Adjusted models of interest using inverse probability weights were used to evaluate the effect of specific FBT components on time-varying child weight loss rate, adjusting for time-varying influence of parent weight loss. HDM201 MDM2 inhibitor Results One hundred thirty-seven parent-child dyads (CHILD mean BMI = 26.4 (3.7) and BMIz = 2.0 (0.3); mean age = 10.4 (1.3); 64.1% female; ADULT mean BMI = 31.9 (6.3); mean age = 42.9 (6.5); 30.1% Hispanic parents; 87.1% female) participated in an FBT program. In traditional model, adult BMI change (b = 0.08; p 0.1). In models that accounted for potential influences from parental weight loss and differential attendance during treatment period, lower availability of high-fat items (b = 1.10, p less then 0.02), higher availability of low-fat items (b = 3.73; p less then 0.01), and higher scores on parental monitoring practices (b = 1.10, p less then 0.01) were associated with greater rates of weight loss, respectively. Conclusion Results suggest that outside of parent weight change, changes in stimulus control strategies at home and improved parental-monitoring practices are important FBT components for child weight loss.Purpose The literature is inconsistent regarding milk intake and physical growth. This study aims to evaluate the association of milk intake with body height and weight in a nationally representative sample of Chinese children. Methods A total of 41,439 children ages 6-17 were recruited from 30 provinces in mainland China in 2013-2016 using a multistage stratified cluster sampling approach. Milk intake information was collected using a questionnaire aided with standard containers. Weight and height were measured using a standard physician beam scale with a height rod. Milk intake was categorized into no-, low-, and high-intake groups based on the intake rate, and weight status into normal, overweight, and obese groups based on the body-mass-index (BMI). Associations between height/weight status and milk intake were evaluated using multivariate weighted linear and logistic regression models. Results Chinese children had low milk intake 1/5 of children did not drink milk, and those drinking milk had a median intake of 100 ml/month. The low- and high-intake groups were 0.83 cm (95% confidence interval 0.00, 1.68 cm) and 1.26 cm (0.34, 2.19 cm) taller than the no-intake group for girls, respectively, after adjusting for confounding factors. Boys with high milk intake had lower BMI (-0.56, 95% CI -1.00, -0.12 kg/m2) and risk of obesity (OR = 0.67, 95% CI 0.46, 0.97) than those without milk intake. Conclusions This study revealed the association of increased milk intake with increased body height and lowered obesity risk among Chinese children. Given the cross-sectional nature of the study and the possibility of residual confounding, further research is warranted to uncover the role of milk intake in promoting children's growth.There are several different methods available for the determination of body fat composition. Two current methods requiring special instrumentation are magnetic resonance imaging (MRI) and dual energy x-ray absorptiometry (DXA). The use of these techniques is very limited despite desirable properties, due to their high costs. Dissection of all fat depots (DF) requires no special instrumentation and allows examination and evaluation of each fat depot in more detail. MRI, DXA, and DF each have their unique advantages and disadvantages when they are applied to animal models. Most studies have determined body fat in young animals, and few studies have been performed in aging models. The aim of this study was to compare MRI, DXA, and DF data in offspring (F1) of mothers fed with control and high-fat diet. We studied rats that varied by age, sex, and maternal diet. The relationships between the three methods were determined via linear regression methods (using log-transformed values to accommodate relativity in the relationships), incorporating when useful age, sex, or diet of the animal. We conclude that the three methods are comparable for measuring body fat, but that direct equivalence gets masked by age, sex, and sometimes dietary group. Depending on the equipment available, the budget of the laboratory, and the nature of the research questions, different approaches may often suggest themselves as the best one.Background/objectives Survivin is an oncogene associated with a decrease in apoptosis, an increase in tumor growth, and poor clinical outcome of diverse malignancies. A correlation between obesity, cancer, and survivin is reported in the literature. To date, the impact of weight loss on change in survivin levels is understudied. This study was aimed at (1) comparing survivin levels in adipose tissue (AT) from lean and obese animal models and evaluating changes after weight loss induced by energy restriction and/or exercise; (2) comparing survivin levels in normal weighted and obese humans and evaluating changes in survivin levels after weight loss induced by a very-low-calorie ketogenic diet (VLCKD) or bariatric surgery in AT and/or blood leukocytes (PBL/PBMCs). Subjects/methods Survivin expression was evaluated in subcutaneous (SAT) and visceral (VAT) AT derived from animal models of monogenic (Zucker rats) and diet-induced obesity (Sprague Dawley rats and C57BL/6J mice) and after a 4-week weight-loss protocol of energy restriction and/or exercise. Plasma was used to measure the inflammatory status. Survivin expression was also evaluated in PBMCs from patients with obesity and compared with normal weight, in PBLs after VLCKD, and in SAT and/or PBLs after bariatric surgery. Results Survivin expression was specifically higher in VAT from obese that lean animals, without differences in SAT. It decreased after weight loss induced by energy restriction and correlated with adiposity and inflammatory markers. In humans, the correlation between being obese and higher levels of survivin was confirmed. In obese subjects, survivin levels were reduced following weight loss after either VLCKD or bariatric surgery. Particularly, a decrease in PBMCs expression (not in SAT one) was found after surgery. Conclusions Weight loss is effective in decreasing survivin levels. Also, PBL/PBMC should be regarded as appropriate mirror of survivin levels in VAT for the identification of an obesity-related protumoral microenvironment.