Physical activity attenuates metabolic risk of adolescents with overweight or obesity: the ICAD multi-country study

Social isolation is associated with higher leisure-time sedentary behavior and lower physical activity practice: A multi-country analysis of data from 79 countries from the Global School-Based Student Health Survey

AIM

To investigate the association of social isolation with physical activity and leisure-time sedentary behavior among adolescents.

METHODS

We used data from the Global School-based Health Survey, including a representative sample of 296,861 adolescents (11-18y) from 79 countries (48.9% girls, 14.5 ± 1.6 years). Social isolation was estimated by combining the self-reported number of friends and loneliness perception. Physical activity and leisure-time sedentary behavior were assessed through questionnaires. Multinomial logistic regression models were created to analyze the associations of social isolation with physical activity and leisure-time sedentary behavior.

RESULTS

Compared with those practicing ≥60 min of physical activity during 1-4 days/week, social isolation was associated with a higher prevalence of not practicing physical activity (Prevalence ratio [PR]:1.24; 95%CI:1.19-1.29), and a lower prevalence of practicing during ≥5d/wk. (PR:0.91; 95%CI:0.88-0.94). Compared with <4 h/d of leisure-time sedentary behavior, being socially isolated was also associated with a higher prevalence of 4-7 h/d (PR: 1.08; 95%CI:1.03-1.14) and ≥ 8 h/d (PR: 1.24; 95%CI:1.16-1.33) of leisure-time sedentary behavior. Compared with those participants without elevated leisure-time sedentary behavior and with those practicing adequate physical activity, social isolation was independently associated with a higher prevalence of physical inactivity (PR: 1.20; 95%CI: 1.15-1.26) and elevated leisure-time sedentary behavior (PR: 1.21; 95%CI: 1.14-1.30), as well as with both risk factors simultaneously (PR: 1.36; 95%CI: 1.28-1.45).

CONCLUSION

Reducing social isolation could be an important component of future interventions to reduce sedentary behavior and physical inactivity among adolescents.

Toward Systems Models for Obesity Prevention: A Big Role for Big Data

The relation among the various causal factors of obesity is not well understood, and there remains a lack of viable data to advance integrated, systems models of its etiology. The collection of big data has begun to allow the exploration of causal associations between behavior, built environment, and obesity-relevant health outcomes. Here, the traditional epidemiologic and emerging big data approaches used in obesity research are compared, describing the research questions, needs, and outcomes of 3 broad research domains: eating behavior, social food environments, and the built environment. Taking tangible steps at the intersection of these domains, the recent European Union project "BigO: Big data against childhood obesity" used a mobile health tool to link objective measurements of health, physical activity, and the built environment. BigO provided learning on the limitations of big data, such as privacy concerns, study sampling, and the balancing of epidemiologic domain expertise with the required technical expertise. Adopting big data approaches will facilitate the exploitation of data concerning obesity-relevant behaviors of a greater variety, which are also processed at speed, facilitated by mobile-based data collection and monitoring systems, citizen science, and artificial intelligence. These approaches will allow the field to expand from causal inference to more complex, systems-level predictive models, stimulating ambitious and effective policy interventions.

Impact of sports participation on components of metabolic syndrome in adolescents: ABCD growth study

OBJECTIVES

This study aimed to analyze the impact of sports participation (12 months of practice) on the components of metabolic syndrome (MetS) in both sexes.

METHODS

This is an observational longitudinal study, a part of which is entitled "Analysis of Behaviors of Children During Growth" (ABCD Growth Study), Presidente Prudente, São Paulo, Brazil. The sample was composed of 171 adolescents (112 boys and 59 girls), divided into non-sports and sports groups. High-density lipoprotein-cholesterol (HDL-c), triglycerides, and glucose were analyzed by the colorimetric method of dry chemistry and processed biochemically. Systolic blood pressure and diastolic blood pressure were measured using an automatic device. Body fat was estimated using a densitometry scanner.

RESULTS

Adolescents who practiced sports were younger (p-value=0.001) and had a lower peak height velocity (p-value=0.001) than the non-sports group. The differences (Δ) after 12 months were of greater magnitude for the sports group when compared to the non-sports group (p-value=0.013), glucose (moderate magnitude in favor of the sports group; p-value=0.001), HDL-c (small magnitude in favor of the sports group; p-value=0.0015), and MetS (moderate magnitude in favor of the sports group; p-value=0.001).

CONCLUSIONS

The practice of sports in adolescents had a protective effect on the metabolic components of MetS.

Association of change in the school travel mode with changes in different physical activity intensities and sedentary time: A International Children's Accelerometry Database Study

Our aim was to assess the association between changes in active travel to school and changes in different intensities of physical activity (i.e. moderate - MPA and vigorous - VPA) and time spent sedentary (SED) among adolescents and assess the moderating effect of children's sex, age and weight status. Data from six cohort studies in the International Children's Accelerometry Database were used (4108 adolescents aged 10-13y at baseline, with 1.9±0.7y of follow-up). Participants self-reported travel mode to school at baseline and follow-up. Mutually exclusive categories of change were created using passive (e.g. by car) or active (cycling or walking) forms of transport (active/active, passive/active, active/passive, passive/passive). Multilevel linear regression analyses assessed associations with change in accelerometer-assessed time spent MPA, VPA and SED, adjusting for potential confounders. The moderation of sex, age and weight status was tested though the inclusion of interaction terms in the regression models. Relative to those remaining in active travel (active/active), participants classified as passive/active increased VPA (B: 2.23 min/d; 95%CI: 0.97-3.48), while active/passive (MPA: -5.38min/d; -6.77 to -3.98; VPA: -2.92min/d; -4.06 to -1.78) and passive/passive (MPA: -4.53min/d; -5.55 to -3.50; VPA: -2.84min/d; -3.68 to -2.01) decreased MPA and VPA. There were no associations with SED. An interaction was observed, age group moderated the association with change in VPA: among 12-13y-olds a greater increase in VPA was observed for the passive/active group compared to active/active. Promoting active travel to school can be a strategy to attenuate the decline in physical activity through adolescence.

Structural equation model of the effect of biological maturation on metabolic syndrome risk and C-reactive protein: effect of trunk fat and sports participation

Our aim was to analyze the association between somatic maturation and alterations in metabolic syndrome (METs) risk and C-reactive protein (CRP), focusing on the effect of changes in trunk fat and sports practice. This was a longitudinal study with a one-year follow-up. The sample was composed of 139 adolescents (46 without sports participation and 93 young athletes), aged 10-17 years. As outcomes, we adopted CRP and METs risk (triglycerides, HDL-c, fasting glucose, and mean blood pressure). Somatic maturation was estimated using Mirwald's method. Structural equation models were used. Somatic maturation was not associated with sports practice, trunk fat, METs risk neither CRP. Sports practice was associated with a reduction in METs risk (β = -0.926; 95%CI:-1.773, -0.080) and reduction in trunk fat (-10.957; -19.630, -2.283), which was associated with increases in METs risk (0.020; 0.004, 0.036). In the CRP model, sports practice was associated with a reduction in trunk fat (-10.324; -18.637, -2.010), which in turn was associated with a reduction in CRP (0.007; 0.001, 0.013). Sports practice and lower trunk adiposity were associated with reductions in trunk fat, METs risk, and CRP through direct and indirect pathways. Our findings highlight the role of sports practice in attenuating the negative effect of trunk adiposity.

Associations of fitness, motor competence, and adiposity with the indicators of physical activity intensity during different physical activities in children

We investigated the associations of peak oxygen uptake (V̇O2peak), ventilatory threshold (VT), muscle strength, motor competence (MC), and adiposity with the indicators of PA intensity during different physical activities used to create absolute PA intensity cut-offs among 35 children 7-11-years-of-age. V̇O2peak was defined as the highest V̇O2 achieved in the maximal cardiopulmonary exercise test (CPET) on a cycle ergometer, self-paced running, or running on a treadmill at 8 km/h. VT was defined from the CPET data. Peak isometric knee extensor and flexor strength was assessed by a dynamometer, MC by the Körperkoordination test für Kinder tests, and body composition by the bioelectrical impedance analysis. PA intensity was assessed using V̇O2 as a % of V̇O2reserve or V̇O2 at VT, mean amplitude deviation (MAD) measured by accelerometry, metabolic equivalent of task (MET), and muscle activity measured by textile electromyography during walking or running on a treadmill at 4, 6, and 8 km/h, playing hopscotch, walking up and down the stairs, self-paced walking, and self-paced running. Children with lower V̇O2peak, V̇O2 at VT, and MC operated at higher intensity level during given physical task than their peers with higher fitness and MC when PA intensity was expressed using relative PA intensity using V̇O2 as a % of V̇O2reserve or V̇O2 at VT (p < 0.05). MAD and METs during different tasks were not able to discriminate PA intensity between children with varying levels of physical fitness or MC. Traditionally used absolute measures of PA intensity based on accelerometry or MET underestimated PA intensity in children with lower V̇O2peak, V̇O2 at VT, and MC.

Associations of age, body size, and maturation with physical activity intensity in different laboratory tasks in children

We investigated the associations of age, sex, body size, body composition, and maturity with measures of physical activity (PA) intensity in children. PA intensity was assessed using VO₂ as % of VO_2reserve or VO₂ at ventilatory threshold (VT), muscle activity measured by textile electromyography, mean amplitude deviation (MAD) measured by accelerometry, and metabolic equivalent of task (MET) during laboratory activities.Age, stature, and muscle mass were inversely associated with VO2 as % of VO_2reserve and % of VT, during walking or running on a treadmill for 4, 6, and 8 km/h (Spearman r = -0.645 to -0.358). Age was inversely associated with MAD during walking on treadmill for 4 km/h (r = -0.541) and positively associated with MAD during running on a treadmill for 8 km/h, playing hopscotch, and during self-paced running (r = 0.368 to 0.478). Fat mass was positively associated with VO2 as % of VO_2reserve and VO2 as % of VO2 at VT and waist circumference was positively associated with VO2 as a % of VO_2reserve and muscle activity during stair climbing (r = 0.416 to 0.519).Fixed accelerometry cut-offs used to define PA intensities should be adjusted for age, sex, body size, and body composition.

How do short-term associations between diet quality and metabolic risk vary with age?

PURPOSE

Poor diet quality is one of the key contributors to poor cardiovascular health and associated morbidity and mortality. This study aimed to assess how the short-term associations between diet quality and metabolic risk factors change with age.

METHODS

This longitudinal, observational study used data from the National Diet and Nutrition Survey (2008-2016) (n = 2024). Diet quality was measured using the Dietary Approaches to Stop Hypertension (DASH) index, fruit and vegetable (F&V) intake, and a F&V biomarker score. We assessed associations between measures of diet quality and a metabolic risk z score (generated from five metabolic risk factors) among those aged 11-60 years, and then tested effect modification by age group (adolescents 11-18 years, young adults 19-35 years, mid-aged adults 36-60 years).

RESULTS

Analysis across all age groups showed inverse associations between standardised DASH index and metabolic risk z score of - 0.19 (95% CI - 0.26, - 0.11). These associations were moderated by age group, with strong associations seen in mid-aged adults: - 0.27 (95% CI - 0.39, - 0.16), but associations were significantly attenuated in young adults [- 0.10 (95% CI - 0.22, 0.01)] and adolescents [0.03 (95% CI - 0.05, 0.11)]. Similar results were found for F&V intake and F&V biomarker score.

CONCLUSIONS

Short-term associations between diet quality and metabolic risk are not consistent across adolescent and young adult age groups, suggesting that mechanisms by which diet impacts on metabolic risk may be acting differently in younger age groups compared to adults. Further research is warranted using longitudinal study designs and replication in different populations to understand changes in determinants of cardiometabolic health with age.