Elise C. Brown

A Systematised Review of Primary School Whole Class Child Obesity Interventions: Effectiveness, Characteristics, and Strategies.

Background. A systematised review was conducted to examine the effectiveness of school-based interventions that focus on changing dietary intake and physical activity levels to reduce childhood obesity. Methods. Multiple databases were searched for randomised and nonrandomised interventions from 2007 to 2016 in full-time elementary schools, which were delivered to the whole class, included dietary and physical activity components, involved both sexes, were written in English, and used body mass index (BMI) as an outcome. Results. The database search produced 8,866 titles from which 78 were deemed relevant and assessed for inclusion resulting in 15 studies meeting all inclusion criteria. From these 15 studies, 9 yielded a reduction or stabilisation in BMI or BMI z-score in the entire intervention group and/or subgroups. Programmes lasting between 6 and 12 months that involve multiple environmental, educational, and physical strategies appear to be most likely to result in BMI or BMI z-score improvement. Moderators most likely influencing an improvement in BMI included increased physical activity, decreased sugar sweetened beverages intake, and increased fruit intake. Conclusions. School-based interventions may be an effective means for child obesity prevention. The identification of consistent elements used in school-based interventions that have demonstrated effectiveness may aid in preventing child obesity.

A criterion-referenced assessment is needed for measuring child obesity

ABSTRACT Body Mass Index (BMI), as an adiposity indicator, assumes that for any given height a change in weight is attributed to a change in fat. This seems problematic in growing youth as great divergence is evident in bone, muscle, and adipose tissue development. Secondly, use of reference populations in categorizing children based on BMI, frequently use arbitrary percentile cut-offs for obesity and do not meet all of the assumptions that cut-offs imply. Lastly, BMI does not control for maturation status. Criterion-referenced assessments of child obesity that account for abdominal adiposity and permit international comparisons, such as waist-to-height ratio (WtHR), must be considered. Better predictive utility has been demonstrated when using WtHR for abdominal adiposity and cardiovascular risk factors in youth compared with BMI. Although multiple methods for assessing waist circumference may be problematic for comparison purposes, its simplicity and international comparability aspects make it a promising alternative to BMI.

Fit for school: results of a 10-week school-based child healthy weight pilot intervention for primary school students

Background: The purpose of this pilot study was to report body mass index standard deviation score (BMI-SDS) changes following a Child Healthy Weight pilot intervention. Methods: Children (n = 3290) aged 4–12 years from southwest Scotland participated in a 10-week school-based pilot intervention comprised of parental engagement, behaviour change, and health literacy and physical activity modules. Children’s height and weight were measured during the first and last weeks of the intervention. A sub-group was followed up at 6 and 24 months after the interventions. Raw data were converted to BMI-SDS. Results: Significant reductions in BMI-SDS occurred in the total group [−0.03 ± 0.29 (95% CI −0.036 to −0.015), p < 0.001], non-overweight (p = 0.001) and combined overweight and obese children (p < 0.001). While BMI-SDS decreased in younger boys [−0.02 ± 0.30 (−0.037 to −0.002), p < 0.05] and girls [−0.04 ± 0.30 (−0.061 to −0.025), p < 0.001] as well as older boys [−0.03 ± 0.29 (−0.058 to −0.010), p < 0.01], no change was evident in older girls [−0.01 ± 0.29 (−0.031 to 0.017), p = 0.56]. Follow-up assessments confirmed that BMI-SDS significantly decreased from baseline to 6 months post-intervention but returned to pre-intervention levels 24 months post-intervention. Conclusions: Significant reductions in BMI-SDS were apparent in the short-term evaluation, but values regressed to the initial baseline levels after 24 months. Future work is needed to examine the long-term effects sustained intervention programmes.

Primary School Children's Health Behaviors, Attitudes, and Body Mass Index After a 10-Week Lifestyle Intervention With Follow-Up

Background: Given the current global child obesity epidemic, testing the effectiveness of interventions in reducing obesity and its influencers is paramount. The purpose of this study was to determine immediate and long-term changes in body mass index and psychosocial variables following a 10-week lifestyle intervention. Methods: Seven hundred and seventy participants (8.75 ± 0.98 years of age, 379 boys and 391 girls) took part in the study. Participants had height, weight, and psychosocial questionnaires assessed at pre- and post-control, pre- and post-intervention, and 6-months post-intervention. Participants completed a weekly 10-week intervention consisting of healthy eating and physical activity education, physical activity, parental involvement, and behavior change techniques. Regression models were fit with correlated errors where the correlation occurred only between time points, not between subjects, and the nesting effects of school and area deprivation were controlled. Results: Regression models revealed a significant decrease in body mass index from pre- to post-intervention of 0.8512 kg/m2 (P = 0.0182). No Changes in body mass index occurred from post-intervention to 6-month follow-up (P = 0.5446). The psychosocial variables did not significantly change. Conclusions: This lifestyle intervention may be an effective means for improving body mass index in primary school children in the short-term if the duration of the intervention is increased, but these changes may not be sustained without on-going support.

Utility of three anthropometric indices in assessing the cardiometabolic risk profile in children

To evaluate the ability of BMI, WC, and WHtR to identify increased cardiometabolic risk in pre‐adolescents.

A Meta-analysis Of Biomarkers Associated With The Overtraining Syndrome: 2418

Int J Exerc Sci 2(1): S2, 2009. Overtraining (OT) syndrome has been investigated extensively with little agreement as to reliable markers for detection. A meta-analytic review is a procedure designed to compile studies in an area with hopes of reaching a consensus view. PURPOSE: The purpose of this meta-analysis was to provide summary quantitative findings of biomarkers (i.e., blood) associated with the overtraining syndrome. METHODS: A meta-analytic research design was utilized to investigate selected studies allowing for a coding process to record data. Thirteen studies met inclusion/exclusion criteria. Biomarkers included samples taken with subjects in normal (N) condition and during OT. These biomarkers were the following: glutamine (um), glutamate (um), cortisol (nmo*l-1), IL-6 (nm), testosterone (mg*dL-1), total cholesterol (mg*dL-1), glucose (mg*dL-1), leptin (ng*mL-1), hematocrit (%), hemoglobin (g*L-1), norepinephrine (pg*mL-1), epinephrine (pg/ml), creatine kinase (u*L-1) To determine magnitude of difference between N and OT, the effect size calculation of M2M1/SD1 was used where M2 is the mean of the OT sample, M1 was the mean of the N sample and SD1 is the standard deviation of the N sample. RESULTS: Combined sample size (N) was 238 subjects with the mean time in OT of 6.6 (weeks). The following are mean (SD) of combined subject demographics: height (cm) 175.4 (2.4); weight (kg) 71.7 (2.6); body fat (%) 11.8 (0.9); age (y) 23.5 (2.03); VO2max (ml*kg -1*min -1) 55.4 (0.8). Mean (SD) biomarker changes from N to OT were the following: Glutamine -56.3 (-2); glutamate 49.7 (2); cortisol -89.7 (-12.2); IL 6 -0.52 (0.12); testosterone -88.9 (-30); cholesterol 4.6 (-1.6); glucose -13.3 (1.9); leptin 0.15 (-0.11); hematocrit -0.83 (-0.4); hemoglobin -20; norepinephrine 36 (-4.1); epinephrine -2.2 (-3.5); creatine kinase 29.2 (8.5). Effect size calculations for the above biomarkers were considered large for the following: glutamine (-4.02), glutamate (8), cortisol, (-1.4), IL 6 (-5.2), glucose (-1.1). CONCLUSION: From this analysis, the noted biomarker changes and direction of change (+, -) indicates considerable immune-suppression and increased stress with athletes experiencing the OT syndrome. TEXAS AMERICAN COLLEGE OF SPORTS MEDICINE 2009 CONFERENCE