DE-PASS best evidence statement (BESt): determinants of adolescents' device-based physical activity and sedentary behaviour in settings: a systematic review and meta-analysis.

BACKGROUND: Although physical activity (PA) is associated with significant health benefits, only a small percentage of adolescents meet recommended PA levels. This systematic review with meta-analysis explored the modifiable determinants of adolescents' device-based PA and/or sedentary behaviour (SB), evaluated in previous interventions and examined the associations between PA/SB and these determinants in settings. METHODS: A search was conducted on five electronic databases, including papers published from January 2010 to July 2023. Randomized Controlled Trials (RCTs) or Controlled Trials (CTs) measuring adolescents' device-based PA/SB and their modifiable determinants at least at two time points: pre- and post-intervention were considered eligible. PA/SB and determinants were the main outcomes. Modifiable determinants were classified after data extraction adopting the social-ecological perspective. Robust Bayesian meta-analyses (RoBMA) were performed per each study setting. Outcomes identified in only one study were presented narratively. The risk of bias for each study and the certainty of the evidence for each meta-analysis were evaluated. The publication bias was also checked. PROSPERO ID: CRD42021282874. RESULTS: Fourteen RCTs (eight in school, three in school and family, and one in the family setting) and one CT (in the school setting) were included. Fifty-four modifiable determinants were identified and were combined into 33 broader determinants (21 individual-psychological, four individual-behavioural, seven interpersonal, and one institutional). RoBMAs revealed none or negligible pooled intervention effects on PA/SB or determinants in all settings. The certainty of the evidence of the impact of interventions on outcomes ranged from very low to low. Narratively, intervention effects in favour of the experimental group were detected in school setting for the determinants: knowledge of the environment for practicing PA, d = 1.84, 95%CI (1.48, 2.20), behaviour change techniques, d = 0.90, 95%CI (0.09, 1.70), choice provided, d = 0.70, 95%CI (0.36, 1.03), but no corresponding effects on PA or SB were found. CONCLUSIONS: Weak to minimal evidence regarding the associations between the identified modifiable determinants and adolescents' device-based PA/SB in settings were found, probably due to intervention ineffectiveness. Well-designed and well-implemented multicomponent interventions should further explore the variety of modifiable determinants of adolescents' PA/SB, including policy and environmental variables.

Ideal cardiovascular health at age 5-6 years and cardiometabolic outcomes in preadolescence.

BACKGROUND: The American Heart Association (AHA) developed a definition of ideal cardiovascular health (ICH) based on the presence of both ideal health behaviours (diet, physical activity, weight status and smoking) and ideal health factors (glucose, total cholesterol and blood pressure levels). However, research of ICH in the paediatric population is scarce. We aimed to study ICH at age 5-6 years by extending the original ICH score with the health behaviours: sleep duration, screen time and prenatal smoke exposure, and to evaluate its association with cardiometabolic outcomes at age 11-12. METHODS: A total of 1666 children aged 5-6 years were selected from the database of the ABCD-study, a prospective cohort study on the health and development of children born in Amsterdam, the Netherlands. Of these, 846 (50.8%) were boys and 1460 (87.6%) had a healthy weight. Data on self-reported health behaviours and health factors were used to calculate the ICH scores (original and extended) by adding the frequency of scoring 'healthy' on each indicator, based on international cut-offs. The children were followed up for 6 years and cardiometabolic outcomes (carotid intima-media thickness (CIMT), blood pressure, glucose and lipids) were measured. Associations between ICH (both original and extended) and cardiometabolic outcomes were examined using multivariable regression models. RESULTS: At age 5-6 years, 11% scored poor (score 1-5), 56% intermediate (score 6-7) and 33% good (score 8-9) on extended ICH. Healthy diet and normal total cholesterol concentrations were the least prevalent. Neither the original nor the extended ICH scores were associated with CIMT at age 11-12. A higher score on the extended ICH was associated with lower total cholesterol (p for trend < 0.001), lower systolic (p for trend = 0.012) and diastolic blood pressure (p for trend = 0.011), and lower body mass index (BMI) (p < 0.001) at age 11-12. The original ICH score was associated with lower total cholesterol (p < 0.001) and BMI (p < 0.001) only. CONCLUSION: Our findings suggest that extending the ICH score in young children with additional health behaviours improves prediction of some cardiometabolic outcomes, but not CIMT in preadolescence, compared to the original ICH score. We would recommend other researchers to incorporate objective measures of health behaviours and longer follow-up to find out whether associations persist into adulthood.

Effects of the Active Smarter Kids (ASK) physical activity intervention on cardiometabolic risk factors in children: A cluster-randomized controlled trial.

The onset of cardiometabolic diseases are recognized to occur in childhood. We aimed to investigate the effect of a school-based cluster-randomized controlled trial of physical activity (PA) on single and clustered cardiometabolic risk factors. We included 1129 fifth-grade children from 57 schools (≥seven children in each class) in Sogn and Fjordane County, Norway, randomized to 28 intervention schools and 29 control schools. The PA intervention was conducted between November 2014 and June 2015. Cardiometabolic risk factors were waist circumference (WC), systolic blood pressure (SBP), total cholesterol (TC):high-density lipoprotein (HDL)-ratio, triglycerides (TG), homeostatic model assessment (HOMA)-score, and cardiorespiratory fitness (CRF). PA was measured by accelerometry. No significant intervention effects were found for single or clustered cardiometabolic risk factors. However, in children with the less favorable baseline values, beneficial effects were found for SBP (p = 0.07 for group ∗ tertile interaction), TC:HDL ratio (p = 0.03 for group ∗ tertile interaction) and the clustered cardiometabolic risk score (p = 0.01 for group ∗ tertile interaction). Compared to boys, girls had a greater effect of the intervention on WC (p = 0.03 for group ∗ sex interaction) and CRF (p < 0.001 for group ∗ sex interaction). The majority of the children had high PA levels, thus limited potential for change, and we found no effects of the PA intervention on cardiometabolic risk in the total sample. However, the intervention had a significantly enhanced effect on fatness and fitness of girls compared to boys. Furthermore, the data suggest that children with the least favorable cardiometabolic risk profile and therefore most in need of change can benefit from school-based PA interventions. Trial registration number: Clinicaltrials.gov ID no.: NCT02132494.

Does cardiorespiratory fitness moderate the prospective association between physical activity and cardiometabolic risk factors in children?

BACKGROUND/OBJECTIVES: Physical activity (PA) and cardiorespiratory fitness (CRF) are independently associated with reduced cardiometabolic risk in children, and may affect risk through different pathways. This study aims to examine if CRF moderate the prospective association between PA, sedentary time, and cardiometabolic outcomes in 10-year-old children. SUBJECTS/METHODS: In total, 718 children of 1129 (drop out n = 7) had valid measures of PA (accelerometry), CRF (the Andersen running test), and a cardiometabolic risk profile measured at baseline and follow-up 7 months later. Cardiometabolic outcomes were systolic blood pressure, waist circumference (WC), total cholesterol, high-density lipoprotein, triglycerides, glucose, and insulin (HOMA-IR). The cardiometabolic risk factors were analysed individually, and as a clustered risk score (z score). A linear mixed model was used to examine the prospective associations between different PA exposures (overall PA, sedentary time, moderate-to-vigorous PA (MVPA), vigorous PA) and cardiometabolic outcomes, including the interaction term PA × CRF in the model to assess moderation by CRF. RESULTS: CRF modified the association for baseline overall PA (P < 0.039) and MVPA (min/day) with clustered cardiometabolic risk at follow-up (P < 0.023). Moreover, CRF modified the association between overall PA and MVPA with HOMA-IR independent of WC (P < 0.022). When stratified by CRF level (median split; high/low), MVPA predicted lower HOMA-IR [MVPA ß -0.133 (95% CI: -0.223, -0.043); P = 0.004] and clustered cardiometabolic risk [MVPA ß -0.094 (95% CI: -0.169, -0.019); P = 0.014] in children with low CRF, but not among their fitter peers (P > 0.232). There was neither direct association between sedentary time and cardiometabolic risk factors in any analyses, nor moderation by CRF. CONCLUSION: CRF significantly moderated the prospective association between PA and the clustered cardiometabolic risk, but not for time spent sedentary. The magnitude of association between MVPA and clustered cardiometabolic risk was stronger in children with low CRF, and no associations appeared present in their high-fit peers.

Effects of physical activity on schoolchildren's academic performance: The Active Smarter Kids (ASK) cluster-randomized controlled trial.

OBJECTIVE: To investigate the effect of a seven-month, school-based cluster-randomized controlled trial on academic performance in 10-year-old children. METHODS: In total, 1129 fifth-grade children from 57 elementary schools in Sogn og Fjordane County, Norway, were cluster-randomized by school either to the intervention group or to the control group. The children in the 28 intervention schools participated in a physical activity intervention between November 2014 and June 2015 consisting of three components: 1) 90min/week of physically active educational lessons mainly carried out in the school playground; 2) 5min/day of physical activity breaks during classroom lessons; 3) 10min/day physical activity homework. Academic performance in numeracy, reading and English was measured using standardized Norwegian national tests. Physical activity was measured objectively by accelerometry. RESULTS: We found no effect of the intervention on academic performance in primary analyses (standardized difference 0.01-0.06, p>0.358). Subgroup analyses, however, revealed a favorable intervention effect for those who performed the poorest at baseline (lowest tertile) for numeracy (p=0.005 for the subgroup∗group interaction), compared to controls (standardized difference 0.62, 95% CI 0.19-1.07). CONCLUSIONS: This large, rigorously conducted cluster RCT in 10-year-old children supports the notion that there is still inadequate evidence to conclude that increased physical activity in school enhances academic achievement in all children. Still, combining physical activity and learning seems a viable model to stimulate learning in those academically weakest schoolchildren.

Does an obesogenic family environment moderate the association between sports participation and body composition in children? The ENERGY project.

BACKGROUND: Previous research on the association between sports participation and body composition has shown mixed findings. The family home is considered one of the most influential environments on childhood obesity. Thus, the association between sports participation and body composition in children may be influenced by an obesogenic home environment. OBJECTIVES: To investigate if an obesogenic family environment moderates the association between sports participation and body composition in children. METHODS: A total of 3999 children (54% girls; 11.6 ± 0.7 years) and their parent(s) were included from the ENERGY project. A composite obesogenic family environment risk score was created from 10 questionnaire items. Height, weight (to calculate body mass index), and waist circumference were obtained by trained researchers and used as indicators of body composition. RESULTS: The composite risk score significantly moderated the association between sports participation and both waist circumference and body mass index. In children from families with moderate and high obesogenic risk, organized sports participation was significantly associated with smaller waist circumference (moderate risk: -0.29, 95% CI -0.45 to -0.14; high risk: -0.46, 95% CI -0.66 to -0.25) and lower body mass index (moderate risk: -0.10, 95% CI -0.16 to -0.04; high risk: -0.14, 95% CI -0.22 to -0.06), but not in children with a low obesogenic family risk score. CONCLUSIONS: Enrolling children in sports activities from an early age can be important for healthy weight maintenance, especially among children from obesogenic family environments.

Cardiometabolic risk factor levels in Norwegian children compared to international reference values: The ASK study.

OBJECTIVE: To investigate cardiometabolic risk factor levels in a group of Norwegian 10-year-old children compared to international values and examine the association between cardiorespiratory fitness (CRF) and the reference-standardized clustered risk score. METHODS: 913 children (49% girls) were included from the Active Smarter Kids (ASK) study. Body mass index (BMI), waist circumference (WC), systolic blood pressure (SBP), diastolic blood pressure (DBP), low-density lipoprotein cholesterol (LDL-C), high-density lipoprotein cholesterol (HDL-C), total cholesterol (TC) to HDL-C ratio, triglyceride (TG), glucose, insulin, homeostatic model assessment (HOMA) score and CRF, were standardized according to international age-and sex-specific reference values. RESULTS: The Norwegian children had significantly more favorable WC, DBP, glucose, HDL-C and CRF levels compared to the international reference values, but similar or less favorable levels of other cardiometabolic risk factors. CRF was the variable that differed the most from the international values (mean (95% CI) 1.20 (1.16 to 1.24) SD). The clustered risk score (excluding CRF) was higher in the Norwegian children, but decreased to below international levels when including CRF (mean (95% CI) - 0.08 (- 0.12 to -0.05) SD). CRF had a significant inverse association with the clustered risk score (excluding CRF) (ß - 0.37 SD, 95% CI -0.43 to -0.31). CONCLUSIONS: Norwegian children have substantially higher CRF levels than international standards, and including CRF in clustered risk scores reduces overall risk in Norwegian children below that of international levels. CRF is associated with improved cardiometabolic health in children.

Reference values for cardiometabolic risk scores in children and adolescents: Suggesting a common standard.

BACKGROUND AND AIMS: International reference values for cardiometabolic risk variables, to allow for standardization of continuous risk scores in children, are not currently available. The aim of this study was to provide international age- and gender-specific reference values for cardiometabolic risk factors in children and adolescents. METHODS: Cohorts of children sampled from different parts of Europe (North, South, Mid and Eastern) and from the United States were pooled. In total, 22,479 observations (48.7% European vs. 51.3% American), 11,234 from girls and 11,245 from boys, aged 6-18 years were included in the study. Linear mixed-model regression analysis was used to analyze the associations between age and each cardiometabolic risk factor. RESULTS: Reference values for 14 of the most commonly used cardiometabolic risk variables in clustered risk scores were calculated and presented by age and gender: systolic blood pressure (SBP), diastolic blood pressure (DBP), waist circumference (WC), body mass index (BMI), sum of 4 skinfolds (sum4skin), triglycerides (TG), total cholesterol (TC), high-density lipoprotein cholesterol (HDL-C), low-density lipoprotein cholesterol (LDL-C), TC:HDL-C ratio, glucose, insulin, homeostatic model assessment-score (HOMA-score), and cardiorespiratory fitness (CRF). CONCLUSIONS: This study suggests a common standard to define cardiometabolic risk in children. Adapting this approach makes single risk factors and clustered cardiometabolic disease risk scores comparable to the reference material itself and comparable to cardiometabolic risk values in studies using the same strategy. This unified approach therefore increases the prospect to estimate and compare prevalence and trends of cardiometabolic risk in children when using continuous cardiometabolic risk scores.

Moderate-to-vigorous physical activity, but not sedentary time, predicts changes in cardiometabolic risk factors in 10-y-old children: the Active Smarter Kids Study.

Background: Cross-sectional data have suggested an inverse relation between physical activity and cardiometabolic risk factors that is independent of sedentary time. However, little is known about which subcomponent of physical activity may predict cardiometabolic risk factors in youths.Objective: We examined the independent prospective associations between objectively measured sedentary time and subcomponents of physical activity with individual and clustered cardiometabolic risk factors in healthy children aged 10 y.Design: We included 700 children (49.1% males; 50.9% females) in which sedentary time and physical activity were measured with the use of accelerometry. Systolic blood pressure, waist circumference (WC), and fasting blood sample (total cholesterol, high-density lipoprotein cholesterol, triglycerides, glucose, fasting insulin) were measured with the use of standard clinical methods and analyzed individually and as a clustered cardiometabolic risk score standardized by age and sex (z score). Exposure and outcome variables were measured at baseline and at follow-up 7 mo later.Results: Sedentary time was not associated with any of the individual cardiometabolic risk factors or clustered cardiometabolic risk in prospective analyses. Moderate physical activity at baseline predicted lower concentrations of triglycerides (P = 0.021) and homeostatic model assessment for insulin resistance (P = 0.027) at follow-up independent of sex, socioeconomic status, Tanner stage, monitor wear time, or WC. Moderate-to-vigorous physical activity (P = 0.043) and vigorous physical activity (P = 0.028) predicted clustered cardiometabolic risk at follow-up, but these associations were attenuated after adjusting for WC.Conclusions: Physical activity, but not sedentary time, is prospectively associated with cardiometabolic risk in healthy children. Public health strategies aimed at improving children's cardiometabolic profile should strive for increasing physical activity of at least moderate intensity rather than reducing sedentary time. This trial was registered at clinicaltrials.gov as NCT02132494.