Attending After-School Physical Activity Club 2 Days a Week Attenuated an Increase in Percentage Body Fat and a Decrease in Fitness Among Adolescent Girls at Risk for Obesity

Interventions to prevent obesity in children aged 12 to 18 years old

BACKGROUND

Prevention of obesity in adolescents is an international public health priority. The prevalence of overweight and obesity is over 25% in North and South America, Australia, most of Europe, and the Gulf region. Interventions that aim to prevent obesity involve strategies that promote healthy diets or 'activity' levels (physical activity, sedentary behaviour and/or sleep) or both, and work by reducing energy intake and/or increasing energy expenditure, respectively. There is uncertainty over which approaches are more effective, and numerous new studies have been published over the last five years since the previous version of this Cochrane Review.

OBJECTIVES

To assess the effects of interventions that aim to prevent obesity in adolescents by modifying dietary intake or 'activity' levels, or a combination of both, on changes in BMI, zBMI score and serious adverse events.

SEARCH METHODS

We used standard, extensive Cochrane search methods. The latest search date was February 2023.

SELECTION CRITERIA

Randomised controlled trials in adolescents (mean age 12 years and above but less than 19 years), comparing diet or 'activity' interventions (or both) to prevent obesity with no intervention, usual care, or with another eligible intervention, in any setting. Studies had to measure outcomes at a minimum of 12 weeks post baseline. We excluded interventions designed primarily to improve sporting performance.

DATA COLLECTION AND ANALYSIS

We used standard Cochrane methods. Our outcomes were BMI, zBMI score and serious adverse events, assessed at short- (12 weeks to < 9 months from baseline), medium- (9 months to < 15 months) and long-term (≥ 15 months) follow-up. We used GRADE to assess the certainty of the evidence for each outcome.

MAIN RESULTS

This review includes 74 studies (83,407 participants); 54 studies (46,358 participants) were included in meta-analyses. Sixty studies were based in high-income countries. The main setting for intervention delivery was schools (57 studies), followed by home (nine studies), the community (five studies) and a primary care setting (three studies). Fifty-one interventions were implemented for less than nine months; the shortest was conducted over one visit and the longest over 28 months. Sixty-two studies declared non-industry funding; five were funded in part by industry. Dietary interventions versus control The evidence is very uncertain about the effects of dietary interventions on body mass index (BMI) at short-term follow-up (mean difference (MD) -0.18, 95% confidence interval (CI) -0.41 to 0.06; 3 studies, 605 participants), medium-term follow-up (MD -0.65, 95% CI -1.18 to -0.11; 3 studies, 900 participants), and standardised BMI (zBMI) at long-term follow-up (MD -0.14, 95% CI -0.38 to 0.10; 2 studies, 1089 participants); all very low-certainty evidence. Compared with control, dietary interventions may have little to no effect on BMI at long-term follow-up (MD -0.30, 95% CI -1.67 to 1.07; 1 study, 44 participants); zBMI at short-term (MD -0.06, 95% CI -0.12 to 0.01; 5 studies, 3154 participants); and zBMI at medium-term (MD 0.02, 95% CI -0.17 to 0.21; 1 study, 112 participants) follow-up; all low-certainty evidence. Dietary interventions may have little to no effect on serious adverse events (two studies, 377 participants; low-certainty evidence). Activity interventions versus control Compared with control, activity interventions do not reduce BMI at short-term follow-up (MD -0.64, 95% CI -1.86 to 0.58; 6 studies, 1780 participants; low-certainty evidence) and probably do not reduce zBMI at medium- (MD 0, 95% CI -0.04 to 0.05; 6 studies, 5335 participants) or long-term (MD -0.05, 95% CI -0.12 to 0.02; 1 study, 985 participants) follow-up; both moderate-certainty evidence. Activity interventions do not reduce zBMI at short-term follow-up (MD 0.02, 95% CI -0.01 to 0.05; 7 studies, 4718 participants; high-certainty evidence), but may reduce BMI slightly at medium-term (MD -0.32, 95% CI -0.53 to -0.11; 3 studies, 2143 participants) and long-term (MD -0.28, 95% CI -0.51 to -0.05; 1 study, 985 participants) follow-up; both low-certainty evidence. Seven studies (5428 participants; low-certainty evidence) reported data on serious adverse events: two reported injuries relating to the exercise component of the intervention and five reported no effect of intervention on reported serious adverse events. Dietary and activity interventions versus control Dietary and activity interventions, compared with control, do not reduce BMI at short-term follow-up (MD 0.03, 95% CI -0.07 to 0.13; 11 studies, 3429 participants; high-certainty evidence), and probably do not reduce BMI at medium-term (MD 0.01, 95% CI -0.09 to 0.11; 8 studies, 5612 participants; moderate-certainty evidence) or long-term (MD 0.06, 95% CI -0.04 to 0.16; 6 studies, 8736 participants; moderate-certainty evidence) follow-up. They may have little to no effect on zBMI in the short term, but the evidence is very uncertain (MD -0.09, 95% CI -0.2 to 0.02; 3 studies, 515 participants; very low-certainty evidence), and they may not reduce zBMI at medium-term (MD -0.05, 95% CI -0.1 to 0.01; 6 studies, 3511 participants; low-certainty evidence) or long-term (MD -0.02, 95% CI -0.05 to 0.01; 7 studies, 8430 participants; low-certainty evidence) follow-up. Four studies (2394 participants) reported data on serious adverse events (very low-certainty evidence): one reported an increase in weight concern in a few adolescents and three reported no effect.

AUTHORS' CONCLUSIONS

The evidence demonstrates that dietary interventions may have little to no effect on obesity in adolescents. There is low-certainty evidence that activity interventions may have a small beneficial effect on BMI at medium- and long-term follow-up. Diet plus activity interventions may result in little to no difference. Importantly, this updated review also suggests that interventions to prevent obesity in this age group may result in little to no difference in serious adverse effects. Limitations of the evidence include inconsistent results across studies, lack of methodological rigour in some studies and small sample sizes. Further research is justified to investigate the effects of diet and activity interventions to prevent childhood obesity in community settings, and in young people with disabilities, since very few ongoing studies are likely to address these. Further randomised trials to address the remaining uncertainty about the effects of diet, activity interventions, or both, to prevent childhood obesity in schools (ideally with zBMI as the measured outcome) would need to have larger samples.

Response to school-based interventions for overweight and obesity: A systematic scoping review

Heterogeneity of response to paediatric obesity interventions is one of the greatest challenges to obesity care. While evaluating school-based interventions by mean changes compared to control is important, it does not provide an understanding of the individual variability in response to intervention. The objective of this study was to comprehensively review school-based interventions that reported study results in terms of response and identify definitions of response used. A scoping review was conducted using a systematic search of five scientific databases from 2009 to 2021. Inclusion criteria included randomized controlled trial design, school-based setting, weight-based outcomes (e.g., BMI, BMI z-score), weight-based outcomes analysed among youth with overweight/obesity, a study conducted in a developed country and publication in English. A total of 26 reports representing 25 unique studies were included. Overall, 19% (5/26) of articles reported response. Response was defined in three ways: maintenance/decrease in BMI z-score, decrease in BMI z-score ≥0.10, and decrease in BMI z-score ≥0.20. Few school-based interventions identified an a priori intervention goal or identified the proportion of participants who responded to the intervention. Without such evaluation participants who do not benefit are likely to be overlooked.

Trends in health behavior and weight outcomes following enhanced afterschool programming participation

BACKGROUND

The United States needs to increase access to effective obesity prevention and treatment programming for impoverished youth at risk for health disparities. Although recommended, schools have difficulty consistently implement evidence-based obesity programing. We report on the effectiveness of adding structured nutrition education and minimum physical activity (PA) requirements to standard middle school after-school programming.

METHODS

Using a longitudinal pre-post study design, we evaluated program effectiveness at one year on target behaviors on students recruited during three consecutive school years (2016-2018). We used generalized linear (or logistic) mixed-effects modeling to determine: 1) impact on healthy weight and target healthy behavior attainment, and 2) whether target behavior improvement and weight change were associated with after-school program attendance. The seven target behaviors relate to eating healthy, physical activity, and sleep.

RESULTS

Over the three years, a total of 76 students enrolled and completed one year of programming (62% Hispanic, 46% girls, 72% with BMI > 85th %ile, 49% with BMI > 95th %ile). Of students with BMI > 85th %ile, 44% maintained or decreased BMI Z-score. There were improvements (non-significant) in BMI Z-score and the adoption of four healthy eating behaviors: fruit, vegetables, sugar-free beverages, and unhealthy snack food. Students with higher after-school attendance (> 75%) had greater improvements (non-significant) in composite behavior scores, BMI Z-score, and in most target behaviors (5/7) than students with lower after-school attendance (< 75%). Sleep improvements were significantly associated with BMI Z-score decrease (Beta = - 0.05, 95% CI (- 0.1,-0.003), p = 0.038.) CONCLUSIONS: Enhancement of existing after-school programming with structured nutrition education and minimum physical activity requirements demonstrates positive improvements in several health behaviors and weight outcomes. Adopting enhanced after-school programming increases access to health activities and may bring us closer to solving obesity in at-risk youth in impoverished communities.

TRIAL REGISTRATION

ClinicalTrials.gov identifier (NCT number): NCT03565744 . Registered 21 June 2018 - Retrospectively registered.

A systematic review and meta-analysis of school-based interventions with health education to reduce body mass index in adolescents aged 10 to 19 years

BACKGROUND

Adolescents are increasingly susceptible to obesity, and thus at risk of later non-communicable diseases, due to changes in food choices, physical activity levels and exposure to an obesogenic environment. This review aimed to synthesize the literature investigating the effectiveness of health education interventions delivered in school settings to prevent overweight and obesity and/ or reduce BMI in adolescents, and to explore the key features of effectiveness.

METHODS

A systematic search of electronic databases including MEDLINE, CINAHL, PsychINFO and ERIC for papers published from Jan 2006 was carried out in 2020, following PRISMA guidelines. Studies that evaluated health education interventions in 10-19-year-olds delivered in schools in high-income countries, with a control group and reported BMI/BMI z-score were selected. Three researchers screened titles and abstracts, conducted data extraction and assessed quality of the full text publications. A third of the papers from each set were cross-checked by another reviewer. A meta-analysis of a sub-set of studies was conducted for BMI z-score.

RESULTS

Thirty-three interventions based on 39 publications were included in the review. Most studies evaluated multi-component interventions using health education to improve behaviours related to diet, physical activity and body composition measures. Fourteen interventions were associated with reduced BMI/BMI z-score. Most interventions (n = 22) were delivered by teachers in classroom settings, 19 of which trained teachers before the intervention. The multi-component interventions (n = 26) included strategies such as environment modifications (n = 10), digital interventions (n = 15) and parent involvement (n = 16). Fourteen studies had a low risk of bias, followed by 10 with medium and nine with a high risk of bias. Fourteen studies were included in a random-effects meta-analysis for BMI z-score. The pooled estimate of this meta-analysis showed a small difference between intervention and control in change in BMI z-score (- 0.06 [95% CI -0.10, - 0.03]). A funnel plot indicated that some degree of publication bias was operating, and hence the effect size might be inflated.

CONCLUSIONS

Findings from our review suggest that school-based health education interventions have the public health potential to lower BMI towards a healthier range in adolescents. Multi-component interventions involving key stakeholders such as teachers and parents and digital components are a promising strategy.

Concomitant exposure to area-level poverty, ambient air volatile organic compounds, and cardiometabolic dysfunction: a cross-sectional study of U.S. adolescents

PURPOSE

A key to better understanding the influence of the place of residence on cardiometabolic function is the effect of concomitant exposure to both air pollution and residence in economically marginalized areas. We hypothesized that, among adolescents, the association between air pollution and cardiometabolic function is exacerbated among residents of economically marginalized areas.

METHODS

In this cross-sectional study, individual-level data on cardiometabolic function collected from a representative sample of U.S. adolescents in the National Health and Nutrition Examination Survey (n = 10,415) were merged with data on area-level poverty (U.S. decennial survey and American Community Survey) and air pollution levels (National-Scale Air Toxics Assessment ) using contemporary census-tract identifiers. We excluded respondents who were pregnant, had hypertension or diabetes or using medication for hypertension or diabetes, or with missing data on outcome variables.

RESULTS

We observed a significant interaction between area-level poverty and air pollution. Among residents of high-poverty areas, exposure to high levels of air pollution predicted a 30% elevated odds of cardiometabolic dysfunction (OR = 1.30; 95% CI: 1.04, 1.61), whereas in low-poverty areas, exposure to high levels of air pollution was not associated with elevated odds of cardiometabolic dysfunction (OR = 1.04; 95% CI: 0.85, 1.28).

CONCLUSIONS

Our findings suggest that the cardiometabolic consequences of air pollution are more readily realized among residents of economically marginalized areas. Structural remedies are discussed.