Effect of multidimensional lifestyle interventions on metabolic risk reduction in children: a cluster randomised controlled trial

Interventions to prevent obesity in children aged 5 to 11 years old

BACKGROUND

Prevention of obesity in children is an international public health priority given the prevalence of the condition (and its significant impact on health, development and well-being). Interventions that aim to prevent obesity involve behavioural change strategies that promote healthy eating 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 children 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 children (mean age 5 years and above but less than 12 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 body mass index (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 172 studies (189,707 participants); 149 studies (160,267 participants) were included in meta-analyses. One hundred forty-six studies were based in high-income countries. The main setting for intervention delivery was schools (111 studies), followed by the community (15 studies), the home (eight studies) and a clinical setting (seven studies); one intervention was conducted by telehealth and 31 studies were conducted in more than one setting. Eighty-six interventions were implemented for less than nine months; the shortest was conducted over one visit and the longest over four years. Non-industry funding was declared by 132 studies; 24 studies were funded in part or wholly by industry. Dietary interventions versus control Dietary interventions, compared with control, may have little to no effect on BMI at short-term follow-up (mean difference (MD) 0, 95% confidence interval (CI) -0.10 to 0.10; 5 studies, 2107 participants; low-certainty evidence) and at medium-term follow-up (MD -0.01, 95% CI -0.15 to 0.12; 9 studies, 6815 participants; low-certainty evidence) or zBMI at long-term follow-up (MD -0.05, 95% CI -0.10 to 0.01; 7 studies, 5285 participants; low-certainty evidence). Dietary interventions, compared with control, probably have little to no effect on BMI at long-term follow-up (MD -0.17, 95% CI -0.48 to 0.13; 2 studies, 945 participants; moderate-certainty evidence) and zBMI at short- or medium-term follow-up (MD -0.06, 95% CI -0.13 to 0.01; 8 studies, 3695 participants; MD -0.04, 95% CI -0.10 to 0.02; 9 studies, 7048 participants; moderate-certainty evidence). Five studies (1913 participants; very low-certainty evidence) reported data on serious adverse events: one reported serious adverse events (e.g. allergy, behavioural problems and abdominal discomfort) that may have occurred as a result of the intervention; four reported no effect. Activity interventions versus control Activity interventions, compared with control, may have little to no effect on BMI and zBMI at short-term or long-term follow-up (BMI short-term: MD -0.02, 95% CI -0.17 to 0.13; 14 studies, 4069 participants; zBMI short-term: MD -0.02, 95% CI -0.07 to 0.02; 6 studies, 3580 participants; low-certainty evidence; BMI long-term: MD -0.07, 95% CI -0.24 to 0.10; 8 studies, 8302 participants; zBMI long-term: MD -0.02, 95% CI -0.09 to 0.04; 6 studies, 6940 participants; low-certainty evidence). Activity interventions likely result in a slight reduction of BMI and zBMI at medium-term follow-up (BMI: MD -0.11, 95% CI -0.18 to -0.05; 16 studies, 21,286 participants; zBMI: MD -0.05, 95% CI -0.09 to -0.02; 13 studies, 20,600 participants; moderate-certainty evidence). Eleven studies (21,278 participants; low-certainty evidence) reported data on serious adverse events; one study reported two minor ankle sprains and one study reported the incident rate of adverse events (e.g. musculoskeletal injuries) that may have occurred as a result of the intervention; nine studies reported no effect. Dietary and activity interventions versus control Dietary and activity interventions, compared with control, may result in a slight reduction in BMI and zBMI at short-term follow-up (BMI: MD -0.11, 95% CI -0.21 to -0.01; 27 studies, 16,066 participants; zBMI: MD -0.03, 95% CI -0.06 to 0.00; 26 studies, 12,784 participants; low-certainty evidence) and likely result in a reduction of BMI and zBMI at medium-term follow-up (BMI: MD -0.11, 95% CI -0.21 to 0.00; 21 studies, 17,547 participants; zBMI: MD -0.05, 95% CI -0.07 to -0.02; 24 studies, 20,998 participants; moderate-certainty evidence). Dietary and activity interventions compared with control may result in little to no difference in BMI and zBMI at long-term follow-up (BMI: MD 0.03, 95% CI -0.11 to 0.16; 16 studies, 22,098 participants; zBMI: MD -0.02, 95% CI -0.06 to 0.01; 22 studies, 23,594 participants; low-certainty evidence). Nineteen studies (27,882 participants; low-certainty evidence) reported data on serious adverse events: four studies reported occurrence of serious adverse events (e.g. injuries, low levels of extreme dieting behaviour); 15 studies reported no effect. Heterogeneity was apparent in the results for all outcomes at the three follow-up times, which could not be explained by the main setting of the interventions (school, home, school and home, other), country income status (high-income versus non-high-income), participants' socioeconomic status (low versus mixed) and duration of the intervention. Most studies excluded children with a mental or physical disability.

AUTHORS' CONCLUSIONS

The body of evidence in this review demonstrates that a range of school-based 'activity' interventions, alone or in combination with dietary interventions, may have a modest beneficial effect on obesity in childhood at short- and medium-term, but not at long-term follow-up. Dietary interventions alone may result in little to no difference. Limited evidence of low quality was identified on the effect of dietary and/or activity interventions on severe adverse events and health inequalities; exploratory analyses of these data suggest no meaningful impact. We identified a dearth of evidence for home and community-based settings (e.g. delivered through local youth groups), for children living with disabilities and indicators of health inequities.

Life Course Cardiovascular Health: Risk Factors, Outcomes, and Interventions

Since it was first defined by the American Heart Association in 2010, cardiovascular health (CVH) has been extensively studied across the life course. In this review, we present the current literature examining early life predictors of CVH, the later life outcomes of child CVH, and the relatively few interventions which have specifically addressed how to preserve and promote CVH across populations. We find that research on CVH has demonstrated that prenatal and childhood exposures are consistently associated with CVH trajectories from childhood through adulthood. CVH measured at any point in life is strongly predictive of future cardiovascular disease, dementia, cancer, and mortality as well as a variety of other health outcomes. This speaks to the importance of intervening early to prevent the loss of optimal CVH and the accumulation of cardiovascular risk. Interventions to improve CVH are not common but those that have been published most often address multiple modifiable risk factors among individuals within the community. Relatively few interventions have been focused on improving the construct of CVH in children. Future research is needed that will be both effective, scalable, and sustainable. Technology including digital platforms as well as implementation science will play key roles in achieving this vision. In addition, community engagement at all stages of this research is critical. Lastly, prevention strategies that are tailored to the individual and their context may help us achieve the promise of personalized prevention and help promote ideal CVH in childhood and across the life course.

Clusters of lifestyle behaviors associated with atherosclerosis risk factors in children and adolescents with congenital heart disease: Floripa CHild Study

Secondary cardiovascular disease is the main cause of mortality in congenital heart disease (CHD) patients. The cardiovascular risk could be widely prevented with adherence to a healthy lifestyle; however, clusters of lifestyle behaviors related to atherosclerosis risk factors in children and adolescents with CHD remain unclear. We aimed to describe the clusters of lifestyle behaviors of children and adolescents with CHD and to evaluate their association with atherosclerosis risk factors. We conducted a cross-sectional study on 227 children and adolescents with CHD (median age:10.02 [IQR:7.08-13.02] years). Dietary intake, physical activity (PA), and sedentary behavior (SB) were evaluated. Clusters of lifestyle behaviors were determined using a two-step cluster analysis. Atherosclerosis risk factors evaluated include body fat mass, central obesity, blood pressure, lipid parameters, glucose, C-reactive protein, and carotid intima-media thickness (cIMT). Multiple logistic regressions were used. The "unhealthy: high SB + low PA" cluster was associated with elevated body fat mass, central obesity, and elevated cIMT. Furthermore, the "unhealthy: low PA + unhealthy eating habits" cluster was associated with elevated body fat mass, central obesity, and elevated glucose. The unhealthier lifestyle behavior clusters were associated with atherosclerosis risk factors in children and adolescents with CHD. Multidisciplinary strategies to promote healthy behaviors are needed to prevent cardiovascular disease in later life.

School-based physical activity programs for promoting physical activity and fitness in children and adolescents aged 6 to 18

BACKGROUND

Physical activity among children and adolescents is associated with lower adiposity, improved cardio-metabolic health, and improved fitness. Worldwide, fewer than 30% of children and adolescents meet global physical activity recommendations of at least 60 minutes of moderate to vigorous physical activity per day. Schools may be ideal sites for interventions given that children and adolescents in most parts of the world spend a substantial amount of time in transit to and from school or attending school.

OBJECTIVES

The purpose of this review update is to summarise the evidence on effectiveness of school-based interventions in increasing moderate to vigorous physical activity and improving fitness among children and adolescents 6 to 18 years of age. Specific objectives are: • to evaluate the effects of school-based interventions on increasing physical activity and improving fitness among children and adolescents; • to evaluate the effects of school-based interventions on improving body composition; and • to determine whether certain combinations or components (or both) of school-based interventions are more effective than others in promoting physical activity and fitness in this target population.

SEARCH METHODS

We searched CENTRAL, MEDLINE, Embase, CINAHL, PsycINFO, BIOSIS, SPORTDiscus, and Sociological Abstracts to 1 June 2020, without language restrictions. We screened reference lists of included articles and relevant systematic reviews. We contacted primary authors of studies to ask for additional information.

SELECTION CRITERIA

Eligible interventions were relevant to public health practice (i.e. were not delivered by a clinician), were implemented in the school setting, and aimed to increase physical activity among all school-attending children and adolescents (aged 6 to 18) for at least 12 weeks. The review was limited to randomised controlled trials. For this update, we have added two new criteria: the primary aim of the study was to increase physical activity or fitness, and the study used an objective measure of physical activity or fitness. Primary outcomes included proportion of participants meeting physical activity guidelines and duration of moderate to vigorous physical activity and sedentary time (new to this update). Secondary outcomes included measured body mass index (BMI), physical fitness, health-related quality of life (new to this update), and adverse events (new to this update). Television viewing time, blood cholesterol, and blood pressure have been removed from this update.  DATA COLLECTION AND ANALYSIS: Two independent review authors used standardised forms to assess each study for relevance, to extract data, and to assess risk of bias. When discrepancies existed, discussion occurred until consensus was reached. Certainty of evidence was assessed according to GRADE. A random-effects meta-analysis based on the inverse variance method was conducted with participants stratified by age (children versus adolescents) when sufficient data were reported. Subgroup analyses explored effects by intervention type.

MAIN RESULTS

Based on the three new inclusion criteria, we excluded 16 of the 44 studies included in the previous version of this review. We screened an additional 9968 titles (search October 2011 to June 2020), of which 978 unique studies were potentially relevant and 61 met all criteria for this update. We included a total of 89 studies representing complete data for 66,752 study participants. Most studies included children only (n = 56), followed by adolescents only (n = 22), and both (n = 10); one study did not report student age. Multi-component interventions were most common (n = 40), followed by schooltime physical activity (n = 19), enhanced physical education (n = 15), and before and after school programmes (n = 14); one study explored both enhanced physical education and an after school programme. Lack of blinding of participants, personnel, and outcome assessors and loss to follow-up were the most common sources of bias.  Results show that school-based physical activity interventions probably result in little to no increase in time engaged in moderate to vigorous physical activity (mean difference (MD) 0.73 minutes/d, 95% confidence interval (CI) 0.16 to 1.30; 33 studies; moderate-certainty evidence) and may lead to little to no decrease in sedentary time (MD -3.78 minutes/d, 95% CI -7.80 to 0.24; 16 studies; low-certainty evidence). School-based physical activity interventions may improve physical fitness reported as maximal oxygen uptake (VO₂max) (MD 1.19 mL/kg/min, 95% CI 0.57 to 1.82; 13 studies; low-certainty evidence). School-based physical activity interventions may result in a very small decrease in BMI z-scores (MD -0.06, 95% CI -0.09 to -0.02; 21 studies; low-certainty evidence) and may not impact BMI expressed as kg/m² (MD -0.07, 95% CI -0.15 to 0.01; 50 studies; low-certainty evidence). We are very uncertain whether school-based physical activity interventions impact health-related quality of life or adverse events.

AUTHORS' CONCLUSIONS

Given the variability of results and the overall small effects, school staff and public health professionals must give the matter considerable thought before implementing school-based physical activity interventions. Given the heterogeneity of effects, the risk of bias, and findings that the magnitude of effect is generally small, results should be interpreted cautiously.

Speed of Movement, Fatness, and the Change in Cardiometabolic Risk Factors in Children

We aimed to examine speed of movement and its interactive association with fatness to changes in cardiometabolic risk factors over one year in children. The analysis included 8345 children aged 6-13 years. Cardiometabolic risk score was computed by summing Z-scores of waist circumference, the average of systolic and diastolic blood pressure, fasting glucose, high-density lipoprotein cholesterol (multiplied by -1), and triglycerides. Both high baseline and improvement in speed of movement were associated with favourable changes in percent body fat, lipids, and cardiometabolic risk score. Percentages of the association between baseline speed of movement and changes in cardiometabolic risk score, triglycerides, and high-density lipoprotein cholesterol explained by baseline BMI were 24.6% (19.6-29.1%), 26.2% (19.7-31.1%), and 12.5% (9.6-15.4%), respectively. The corresponding number for percent body fat was 47.0% (40.4-54.1%), 43.3% (36.7-51.7%), and 29.8% (25.0-34.6%), respectively. Speed of movement mediated the association between fatness and cardiometabolic risk factors. Improved speed of movement was associated with a lower increase in blood pressure in obese children only. Speed of movement is a strong predictor of changes in cardiometabolic risk factors. Fatness and speed of movement are interactively associated with cardiometabolic risk factors. Speed of movement may attenuate the positive association between fatness and blood pressure.