METHODS: A total of 32 obese women were selected as subjects and administered the interventions of low-intensity combination exercise (Q2), moderate-intensity combination exercise (Q3), and high-intensity combination exercise (Q4). ELISA was used to measure irisin and IL-6 levels in all samples. Statistical analysis used one-way ANOVA and Turkey's-Honest Significant Difference (HSD) post hoc test.
RESULTS: The mean Δ IL-6 levels in the control groups (Q1), Q2, Q3, and Q4 were 0.27 ± 2.54, 2.07 ± 2.55, 5.99 ± 6.25, and 7.98 ± 2.82 pg/mL with (p=0.015). The mean Δ irisin levels were 0.06 ± 0.81 ng/mL in Q1, 0.59 ± 0.67 ng/mL in Q2, 1.99 ± 1.65 ng/mL in Q3, 4.63 ± 3.57 ng/mL in Q4 with (p=0.001).
CONCLUSIONS: This study proved that all three types of combined exercise intensity increased myokine levels, such as irisin and IL-6. However, high-intensity combination exercise provided the most optimal improvement in myokine levels in obese women. Future studies are needed to design long-term exercise programs specifically for obese adolescent women using the findings from this study.
METHODS: A systematic literature search was conducted using CINAHL, EMBASE, Ovid MEDLINE, PsycINFO and SPORTDiscus databases to retrieve articles published from 1st January 2000 to 31st December 2017. Randomised controlled trials (RCTs) and quasi-experimental studies comparing different strategies in managing overweight and obesity among schoolchildren (6 to 12 years of age) were included. The main outcomes of interest were reductions in weight related variables included anthropometry and body composition measurements. All variables were analysed using random effects meta-analyses.
RESULTS: Fourteen studies were reviewed, 13 were RCTs and one was a quasi-experimental study. The risk of bias for randomisation was low risk for all of RCTs except for one, which was unclear. The risk of bias for randomisation was high for the quasi-experimental study. Most interventions incorporated lifestyle changes and behavioural strategies such as coping and problem solving skills with family involvement. The meta-analyses did not show significant effects of the intervention in reducing weight related outcomes when compared with controls.
CONCLUSION: Meta-analyses of the selected studies did not show significant effects of the interventions on weight related outcomes among overweight and obese schoolchildren when compared with controls. The role of interdisciplinary team approaches with family involvement using behaviour and lifestyle strategies to curb obesity among schoolchildren is important.
METHODS: The social media analytics site SocialBlade.com was used to identify the most popular YouTube videos (n = 250) targeting children. Ads encountered while viewing these videos were recorded and analyzed for type of product promoted and ad format (video vs. overlay). Food and beverage ads were further coded based on food category and persuasive marketing techniques used.
RESULTS: In total 187 ads were encountered in sampled videos. Food and beverage ads were the most common at 38% (n=71), among which 56.3% (n = 40) promoted noncore foods. Ads for noncore foods were more commonly delivered as video rather than overlay ads. Among ads promoting noncore foods, the most commonly employed persuasive marketing techniques found were taste appeal (42.3%), uniqueness/novelty (32.4%), the use of animation (22.5%), fun appeal (22.5%), use of promotional characters (15.5%), price (12.7%), and health and nutrition benefits (8.5%).
CONCLUSIONS: Similar to television, unhealthy food ads predominate in content aimed toward children on YouTube. Policies regulating food marketing to children need to be extended to cover online content in line with a rapidly-evolving digital media environment. Service providers of social media can play a part in limiting unhealthy food advertising to children.
METHODS: Data were obtained from the 2012 Malaysia Global School-based Student Health Survey. Generalized ordered logit regression analysis was conducted on 24 339 adolescents by PA status.
RESULTS: Early- (ages 11-13) and middle-stage (ages 14-16) adolescents were associated with higher overweight and obesity risks than their older peers (ages 17-18). Male adolescents faced higher underweight and obesity likelihoods than females. Hunger due to food shortage at home was associated with higher likelihoods of underweight and normal weight BMI categories. Smokers were more likely to be underweight or normal weight than non-smokers. Segmented-sample analysis by PA status indicated that, while the direction of associations was parallel across PA status, the magnitudes of association between age, hunger and smoking status with BMI status were greater among active than inactive adolescents.
CONCLUSIONS: Male adolescents faced a dual burden of underweight and obesity. Other sociodemographic and dietary-lifestyle factors were associated with adolescent BMI categories. Segmented-sample analysis by PA status uncovered varying associations between factors that would otherwise be masked in pooled sample analysis. Public health authorities should take these factors into consideration when deliberating programs to ensure healthy adolescent body weight.
METHODOLOGY: We recruited 175 subjects, aged 7 to 18 years old, referred for obesity. We studied their demography (age, gender, ethnicity, family background), performed clinical/auxological examinations [weight, height, body mass index (BMI), waist circumference (WC), blood pressure (BP)], and analyzed their biochemical risks associated with metabolic syndrome [fasting plasma glucose (FPG), fasting lipid profile (FLP), fasting insulin, liver function tests (LFT)]. MetS was identified according to the criteria proposed by the International Diabetes Federation (IDF) for pediatric obesity. Multiple logistic regression models were used to examine the associations between risk variables and MetS.
RESULTS: The prevalence of metabolic syndrome among children with obesity was 56% (95% CI: 48.6 to 63.4%), with a mean age of 11.3 ± 2.73 years. Multiple logistic regression analysis showed age [adjusted odds ratio (OR) 1.27, 95% CI: 1.15 to 1.45] and sedentary lifestyle (adjusted OR 3.57, 95% CI: 1.48 to 8.59) were the significant factors associated with metabolic syndrome among obese children.
CONCLUSION: The prevalence of metabolic syndrome among obese children referred to our centers was 56%. Older age group, male gender, birth weight, sedentary lifestyle, puberty and maternal history of gestational diabetes mellitus (GDM) were found to be associated with MetS. However, older age group and sedentary lifestyle were the only significant predictors for metabolic syndrome.
METHODS: This is a cross-sectional comparison study whereby 225 overweight/obese children matched for age, sex, and ethnicity with 225 normal weight children participated in this study. Body image dissatisfaction, disordered eating, and depressive symptoms were assessed through a self-administered questionnaire. Blood pressure was measured, whereas blood was drawn to determine insulin, high-sensitivity C-reactive protein (hs-CRP), glucose, and lipid profiles. Homeostasis model assessment-estimated insulin resistance (HOMA-IR) was calculated using glucose and insulin levels. Wechsler's Intelligence Scale for Children-Fourth Edition (WISC-IV) was used to assess cognitive function in children. Ordinary least square regression analysis was conducted to determine the direct and indirect relationships between weight status and cognitive function.
RESULTS: A negative relationship was found between overweight/obesity with cognitive function. Overweight/obese children were on average 4.075 units lower in cognitive function scores compared to normal weight children. Such difference was found through mediators, such as body image dissatisfaction, disordered eating, depression, systolic blood pressure, triglycerides, HOMA-IR, and hs-CRP, contributing 22.2% of the variances in cognitive function in children.
CONCLUSION: Results highlight the important mediators of the relationship between overweight/obesity and cognitive function. Consequently, future interventions should target to improve psychological well-being and reduce cardiovascular disease risk for the prevention of poorer cognitive performance in overweight/obese children.
METHODS: Using a cross-sectional study design, body weight and height were measured, and BMI was calculated and classified using WHO BMI-for-age Z-score. Data was obtained using the National Fitness Standard (SEGAK) assessment, which was uploaded in a specific Health Monitoring System (HEMS).
RESULTS: From a total of 62,567 school adolescents, 50.7% were boys and 49.3% were girls. Girls had significantly higher BMI than boys in age groups of 13 to 15 and 16 to 17 years old. Among boys and girls, there were significant differences in mean BMI of school adolescents between rural and urban school locations in all age groups (p