Typologies of adolescent activity related health behaviours

Examination of Current Anxiety Problems with School Engagement and Volunteer and Paid Work among U.S. Adolescents

This study examined the relationships between current anxiety problems and school engagement, community service or volunteer work, and paid work among U.S. adolescents. The 2018-2019 National Survey of Children's Health (NSCH) dataset was analyzed and included 24,609 adolescents ages 12-17 years. We conducted unadjusted and adjusted logistic regression analyzes. A total of 12.6% of adolescents had healthcare provider-confirmed current anxiety problems. Adolescents with current anxiety were at decreased odds of engaging in school (aOR = 0.35, 95%CI = 0.29, 0.41) and participating in community service or volunteer work (aOR = 0.72, 95%CI = 0.59, 0.86) compared to adolescents without current anxiety. Adolescents with current anxiety were at increased odds of participating in paid work (OR = 1.18, 95%CI = 1.01, 1.38). This study reports that U.S. adolescents with anxiety were less likely to engage in school and participate in community service or volunteer work, but were more likely to participate in paid work compared to their peers without anxiety. Results should inform future interventions targeting adolescents.

Before-school physical activity patterns among adolescents using accelerometer and GPS data

Most adolescents do not meet physical activity (PA) guidelines. The before-school segment has been identified as one promising opportunity for intervention; however, there is a need for contextual understanding of PA in this segment. This study aimed to examine: a) adolescents' PA levels across various locations before school (6:00am - school start), b) contributions of before-school PA to daily PA and PA guidelines, and c) correlates of location-specific before-school PA. A cross-sectional analysis was conducted using adolescents' (n = 148, mean age 14.7) accelerometer and GPS data. Adolescents averaged 9.7 min in before-school moderate-to-vigorous PA (MVPA), representing substantial contributions to daily activity. Most MVPA occurred away from home and school. Significant correlates included segment duration, age, socio-economic status, and PA self-efficacy. Future work should consider these patterns and correlates to support adolescents' PA through targeted interventions.

A systematic scoping review of latent class analysis applied to accelerometry-assessed physical activity and sedentary behavior

BACKGROUND

Latent class analysis (LCA) identifies distinct groups within a heterogeneous population, but its application to accelerometry-assessed physical activity and sedentary behavior has not been systematically explored. We conducted a systematic scoping review to describe the application of LCA to accelerometry.

METHODS

Comprehensive searches in PubMed, Web of Science, CINHAL, SPORTDiscus, and Embase identified studies published through December 31, 2021. Using Covidence, two researchers independently evaluated inclusion criteria and discrepancies were resolved by consensus. Studies with LCA applied to accelerometry or combined accelerometry/self-reported measures were selected. Data extracted included study characteristics and both accelerometry and LCA methods.

RESULTS

Of 2555 papers found, 66 full-text papers were screened, and 12 papers (11 cross-sectional, 1 cohort) from 8 unique studies were included. Study sample sizes ranged from 217-7931 (mean 2249, standard deviation 2780). Across 8 unique studies, latent class variables included measures of physical activity (100%) and sedentary behavior (75%). About two-thirds (63%) of the studies used accelerometry only and 38% combined accelerometry and self-report to derive latent classes. The accelerometer-based variables in the LCA model included measures by day of the week (38%), weekday vs. weekend (13%), weekly average (13%), dichotomized minutes/day (13%), sex specific z-scores (13%), and hour-by-hour (13%). The criteria to guide the selection of the final number of classes and model fit varied across studies, including Bayesian Information Criterion (63%), substantive knowledge (63%), entropy (50%), Akaike information criterion (50%), sample size (50%), Bootstrap likelihood ratio test (38%), and visual inspection (38%). The studies explored up to 5 (25%), 6 (38%), or 7+ (38%) classes, ending with 3 (50%), 4 (13%), or 5 (38%) final classes.

CONCLUSIONS

This review explored the application of LCA to physical activity and sedentary behavior and identified areas of improvement for future studies leveraging LCA. LCA was used to identify unique groupings as a data reduction tool, to combine self-report and accelerometry, and to combine different physical activity intensities and sedentary behavior in one LCA model or separate models.

Combinations of Physical Activity, Sedentary Behavior, and Sleep Duration and Their Associations With Physical, Psychological, and Educational Outcomes in Children and Adolescents: A Systematic Review

We conducted a systematic review to evaluate combinations of physical activity, sedentary behavior, and sleep duration (defined as "movement behaviors") and their associations with physical, psychological, and educational outcomes in children and adolescents. MEDLINE, CINAHL, PsychInfo, SPORTDiscus, PubMed, EMBASE, and ERIC were searched in June 2020. Included studies needed to 1) quantitatively analyze the association of 2 or more movement behaviors with an outcome, 2) analyze a population between 5 and 17 years of age, and 3) include at least an English abstract. We included 141 studies. Most studies included the combination of physical activity and sedentary behavior in their analyses. Sleep was studied less frequently. In combination, a high level of physical activity and a low level of sedentary behavior were associated with the best physical health, psychological health, and education-related outcomes. Sleep was often included in the combination that was associated with the most favorable outcomes. Sedentary behavior had a stronger influence in adolescents than in children and tended to be associated more negatively with outcomes when it was defined as screen time than when defined as overall time spent being sedentary. More initiatives and guidelines combining all 3 movement behaviors will provide benefit with regard to adiposity, cardiometabolic risk factors, cardiorespiratory fitness, muscular physical fitness, well-being, health-related quality of life, mental health, academic performance, and cognitive/executive function.

Does light-intensity physical activity moderate the relationship between sitting time and adiposity markers in adolescents?

BACKGROUND

While the relationship between sedentary time and adiposity markers may be independent of moderate-to-vigorous intensity physical activity (MVPA) among adolescents, little is known about the role of light-intensity physical activity (LIPA) in this relationship. The aim of this cross-sectional study was to examine whether device-measured LIPA and MVPA moderate the associations between objectively measured sitting time and adiposity markers (body mass index (BMI)) and waist circumference (WC)) among adolescents.

METHODS

This study included accelerometer and inclinometer data obtained from 219 adolescents (age = 14.9 ± 1.6 years, mean ± SD), collected during 2014 and 2015 in Melbourne, Australia. ActiGraph GT3X accelerometers were used to determine time spent in total-LIPA (101 counts/min to 3.99 metabolic equivalents (METs)) was dichotomized into low-LIPA (101-799 counts/min) and high LIPA (800 counts/min to 3.99 METs), and MVPA (≥ 4 METs). The average time spent sitting was obtained from activPAL inclinometers. Anthropometric measures were assessed by trained staff. Interactions between sitting and total-LIPA, low-LIPA, high-LIPA, and MVPA on BMI z-score (zBMI) and WC z-score (zWC), respectively, were examined using linear regression, adjusting for age and sex; and moderation by total-LIPA, low-LIPA, high-LIPA, and MVPA were examined by adding interaction terms. Significant interaction effects were probed by comparing associations at the mean and at 1 SD below and above the mean.

RESULTS

Total-LIPA significantly moderated the association between sitting time and zBMI, and low-LIPA significantly moderated the association between sitting time and zBMI and zWC. No other associations were found for total-LIPA, high-LIPA, or MVPA. Specifically, at high levels of total-LIPA (+1 SD), there is a negative association between sitting time and zBMI. In addition, at high levels of low-LIPA (+1 SD), there is a negative association between sitting time and zBMI and zWC.

CONCLUSION

Associations between sitting and adiposity depended on time spent in total-LIPA and low-LIPA, but not high-LIPA or MVPA. Results suggest that increasing time spent in LIPA may provide protection from the deleterious effects of sitting on adiposity markers among adolescents. Experimental evidence is needed to support these conclusions.

A latent transition analysis of physical activity and screen-based sedentary behavior from adolescence to young adulthood

BACKGROUND

Distinct typologies of physical activity and screen-based sedentary behaviors are common during adolescence, but it is unknown how these change over time. This longitudinal study examined the stability of activity-related behavioral typologies over the transition out of secondary school.

METHODS

Year 11 students (penultimate school year) completed a self-report survey (baseline), which was repeated 2 years later (follow-up) (75% female, mean baseline age: 16.9 ± 0.4 years). Latent transition analysis identified typologies of physical activity and screen time behaviors and explored changes in typology membership between baseline and follow-up among those with complete data and who were not attending secondary school at follow-up (n = 803).

RESULTS

Three unique typologies were identified and labelled as: 1) Sedentary gamers (baseline: 17%; follow-up: 15%: high levels of screen behaviors, particularly video gaming); 2) Inactives (baseline: 46%; follow-up: 48%: low physical activities, average levels of screen behaviors); and 3) Actives (baseline: 37%; follow-up: 37%: high physical activities, low screen behaviors). Most participants remained in the same typology (83.2%), 8.5% transitioned to a typology with a more health-enhancing profile and 8.3% transitioned to a typology with a more detrimental behavioral profile.

CONCLUSIONS

The high proportion within the 'inactive' typology and the stability of typologies over the transition period suggests that public health interventions are required to improve activity-related behavior typologies before adolescents leave secondary school.

Outdoor public recreation spaces and social connectedness among adolescents

Background

Outdoor public recreation spaces are important settings for leisure and physical activity. Adolescents’ use of these spaces may contribute to social connectedness via social interaction with peers and the community in these settings. However, research on this topic is limited. This exploratory study examined associations of frequency of visitation and physical activity in outdoor public recreation spaces with social connectedness among adolescents in Melbourne, Australia.

Methods

Adolescents self-reported their frequency of visitation to parks, trails, beach/lake, and sports facilities; frequency of physical activity in a park, local street or path, and their street; and social connectedness. Separate analyses were conducted for visitation (n = 349, 15.4 ± 1.6 years, 58% female) and physical activity (n = 441, 15.4 ± 1.6 years, 59% female) using multilevel linear regression models.

Results

No significant associations were observed for frequency of visitation to a park (B = 0.86, 95% CI = − 0.26, 1.99), trails (B = 0.41, 95% CI = − 0.61, 1.44), beach/lake (B = − 0.44, 95% CI = − 1.46, 0.57), or sports facilities (B = 0.64, 95% CI = − 0.43, 1.70), nor for frequency of physical activity in their street (B = − 0.07, 95% CI = − 0.46, 0.31), local street/path (B = − 0.05, 95% CI = − 0.43, 0.33) or in a park (B = 0.23, 95% CI = − 0.14, 0.60) with adolescents’ social connectedness.

Conclusions

The findings did not support the hypothesis that visiting and being active in outdoor public recreation spaces are associated with adolescents’ social connectedness. Future research should consider the duration and context of outdoor public recreation space use (e.g., sports, socialising, relaxing alone) and whether different types and/or a combination of public spaces are more/less conducive to social connectedness.

Use of latent class analysis as a method of assessing the physical activity level, sedentary behavior and nutritional habit in the adolescents' lifestyle: A scoping review

BACKGROUND

Currently, adolescents' lifestyle is commonly characterized by physical inactivity, sedentary behavior, and inappropriate eating habits in general. A person-oriented approach as Latent Class Analysis (LCA) can offer more insight than a variable-centered approach when investigating lifestyle practices, habits, and behaviors of adolescent population.

OBJECTIVE

The aim of the present study was to assess which variables are mostly used to represent the physical activity level, sedentary behavior SB) and nutritional habit in the adolescents' lifestyle in studies that used the LCA.

DESIGN

Scoping review.

METHODS

The study was a performed in accordance with the proposed criteria for systematic reviews and meta-analyses-Preferred Reporting Items for Systematic Reviews and Meta-Analyses and registered in PROSPERO (CRD42018108444). The original articles were searched in MEDLINE/PubMed, Scopus, ScienceDirect, Web of Science, PsycINFO, and SPORTdiscus. The Quality Assessment Tool analyzed the risk of bias of the included studies.

RESULTS

30 original articles were selected. The physical activity level (28 studies), SB and nutritional habits (18 studies) were the most common variable used to evaluate the adolescent's lifestyle by LCA model. Specifically, physical inactivity and high SB were the manifest variables with higher frequency in the negative latent classes (LCs) in adolescent girls. On the other hand, physical exercises and sports were activities more commonly labeled as positive LCs.

CONCLUSIONS

The LCA models of the most of selected studies showed that physical inactivity, high SB were the most common in the LCs with negative characteristics of the adolescents' lifestyle. Better understanding the results of analyzes of clusters of multivariate behaviors such as the LCA can help to create more effective strategies that can make the lifestyle of adolescents healthier.

A comparison of children's diet and movement behaviour patterns derived from three unsupervised multivariate methods

Background

Behavioural patterns are typically derived using unsupervised multivariate methods such as principal component analysis (PCA), latent profile analysis (LPA) and cluster analysis (CA). Comparability and congruence between the patterns derived from these methods has not been previously investigated, thus it’s unclear whether patterns from studies using different methods are directly comparable. This study aimed to compare behavioural patterns derived across diet, physical activity, sedentary behaviour and sleep domains, using PCA, LPA and CA in a single dataset.

Methods

Parent-report and accelerometry data from the second wave (2011/12; child age 6-8y, n = 432) of the HAPPY cohort study (Melbourne, Australia) were used to derive behavioural patterns using PCA, LPA and CA. Standardized variables assessing diet (intake of fruit, vegetable, sweet, and savoury discretionary items), physical activity (moderate- to vigorous-intensity physical activity [MVPA] from accelerometry, organised sport duration and outdoor playtime from parent report), sedentary behaviour (sedentary time from accelerometry, screen time, videogames and quiet playtime from parent report) and sleep (daily sleep duration) were included in the analyses. For each method, commonly used criteria for pattern retention were applied.

Results

PCA produced four patterns whereas LPA and CA each generated three patterns. Despite the number and characterisation of the behavioural patterns derived being non-identical, each method identified a healthy, unhealthy and a mixed pattern. Three common underlying themes emerged across the methods for each type of pattern: (i) High fruit and vegetable intake and high outdoor play (“healthy”); (ii) poor diet (either low fruit and vegetable intake or high discretionary food intake) and high sedentary behaviour (“unhealthy”); and (iii) high MVPA, poor diet (as defined above) and low sedentary time (“mixed”).

Conclusion

Within this sample, despite differences in the number of patterns derived by each method, a good degree of concordance across pattern characteristics was seen between the methods. Differences between patterns could be attributable to the underpinning statistical technique of each method. Therefore, acknowledging the differences between the methods and ensuring thorough documentation of the pattern derivation analyses is essential to inform comparison of patterns derived through a range of approaches across studies.

Activity-related typologies and longitudinal change in physical activity and sedentary time in children and adolescents: The UP&DOWN Study

BACKGROUND

Children and adolescents can be distinguished by different typologies (clusters) of physical activity and sedentary behavior. How physical activity and sedentary behaviors change over time within different typologies is not known. This study examined longitudinal changes in physical activity and sedentary time among children and adolescents with different baseline typologies of activity-related behavior.

METHODS

In this longitudinal study (3 annual time points) of children (n = 600, age = 9.2 ± 0.4 years (mean ± SD), 50.3% girls) and adolescents (n = 1037, age = 13.6 ± 1.7 years, 48.4% girls), participants were recruited in Spain in 2011-2012. Latent class analyses identified typologies based on self-reported screen, educational, social and relaxing sedentary behaviors, active travel, muscle strengthening activity, and sport at baseline. Within each typology, linear mixed growth models explored longitudinal changes in accelerometer-derived moderate-to-vigorous physical activity and sedentary time, as well as time by class interactions.

RESULTS

Three typologies were identified among children ("social screenies", 12.8%; "exercisers", 61.5%; and "non-sporty active commuters", 25.7%) and among adolescents ("active screenies", 43.5%; "active academics", 35.0%; and "non-sporty active commuters", 21.5%) at baseline. Sedentary time increased within each typology among children and adolescents, with no significant differences between typologies. No changes in physical activity were found in any typology among children. In adolescents, physical activity declined within all typologies, with "non-sporty active commuters" declining significantly more than "active screenies" over 3 years.

CONCLUSION

These results support the need for intervention to promote physical activity and prevent increases in sedentary time during childhood and adolescence. Adolescents characterized as "non-sporty active commuters" may require specific interventions to maintain their physical activity over time.

Students' Physical Activity Profiles According to Children's Age and Parental Educational Level

The aim of this study was to identify different profiles of physical activity (PA) behaviors according to the school student’s age stage and their parents’ or guardians education level. Seven hundred twenty-seven students and parents of different educational stages were invited to take part in this study. The participants included, Preschool (1 to 5 years old), Primary School (6 to 11 years old), Secondary School (12 to 15 years old), and High School (16 to 18 years old). A questionnaire to assess the educational level of parents (low, intermediate, and high) and their child’s PA level and sedentary behaviors across various age stages was administered. The results showed a number of different physical activity profiles for preschool (4), primary (6), secondary (7) and high school (2) students. Primary and secondary school children’s behavioral profiles were reported to differ significantly between both physical activity levels and sedentary behaviors, while preschool students’ behavioral profiles only differed between sedentary behaviors. Higher parental education was most prevalent in clusters with significantly higher levels of PA in primary and secondary students, while there were equivocal trends for parental education level influencing behavioral profiles of high school students. These findings suggest there is some association between the behavioral profiles of student’s physical activity and sedentary behavior, and parental education level, most noticeably during the early to middle age stages.

Identifying typologies of diurnal patterns in desk-based workers' sedentary time

The purpose of this study was to identify typologies of diurnal sedentary behavior patterns and sociodemographic characteristics of desk-based workers. The sedentary time of 229 desk-based workers was measured using accelerometer devices. The within individual diurnal variations in sedentary time was calculated for both workdays and non-workdays. Diurnal variations in sedentary time during each time period (morning, afternoon, and evening) was calculated as the percentage of sedentary time during each time period divided by the percentage of the total sedentary time. A hierarchical cluster analysis (Ward’s method) was used to identify the optimal number of clusters. To refine the initial clusters, a non-hierarchical cluster analysis (k-means method) was performed. Four clusters were identified: stable sedentary cluster (46.7%), off-morning break cluster (26.6%), off-afternoon break cluster (8.3%), and evening sedentary cluster (18.3%). The stable sedentary cluster had the lowest variations in sedentary time throughout the day and the highest amount of total sedentary time. Participants in the off-morning and off-afternoon break clusters had nearly the same sedentary patterns but took short-term breaks during non-workday mornings or afternoons. The evening sedentary cluster had a completely different pattern, with a longer sedentary time during the evening both on workdays and non-workdays. Sociodemographic attributes such as sex, household income, educational attainment, employment status, sleep duration, and residential area, differed significantly between groups. Initiatives to address desk-based workers’ sedentary behavior need to focus not only on the workplace but also on the appropriate timing for reducing excessive sedentary time in non-work contexts depending on the characteristics and diurnal patterns of target subgroups.

Contemporaneous trajectories of physical activity and screen time in adolescents

Adolescents often report low moderate-to-vigorous physical activity (MVPA) and high screen time. We modeled sex-specific MVPA and screen time trajectories during adolescence and identified contemporaneous patterns of evolution. Data were drawn from 2 longitudinal investigations. The Nicotine Dependence in Teens (NDIT) study included 1294 adolescents recruited at age 12-13 years who completed questionnaires every 3 months for 5 years. The Monitoring Activities of Teenagers to Comprehend their Habits (MATCH) study included 937 participants recruited at age 9-12 years who completed questionnaires every 4 months for 7 years. MVPA was measured as the number of days per week of being active for at least 5 min (NDIT) or 60 min (MATCH). In both studies, screen time was measured as the number of hours spent weekly in screen activities. In each study, sex-specific group-based trajectories were modeled separately for MVPA and screen time from grade 7 to 11. Contemporaneous patterns of evolution were examined in mosaic plots. In both studies, 5 MVPA trajectories were identified in both sexes, and 4 and 5 screen time trajectories were identified in boys and girls, respectively. All combinations of MVPA and screen time trajectories were observed. However, the contemporaneous patterns of evolution were favourable in 14%-31% of participants (i.e., they were members of the stable high MVPA and the lower screen time trajectories). Novelty: MVPA and screen time trajectories during adolescence and their combinations showed wide variability in 2 Canadian studies. Up to 31% of participants showed favourable contemporaneous patterns of evolution in MVPA and screen time. Using uniform methods for trajectory modeling may increase the potential for replication across studies.

Exploration of Barriers to the Uptake of Nutritional Services Among Adolescent Girls from the Rural Communities of Tigray Region, Northern Ethiopia: A Qualitative Study

Background

Adolescence is a time of tremendous physical growth and mental development, with high nutrient requirements. Ethiopia is among the countries with a high prevalence of nutritional deficiencies among the women of reproductive age group, whilst adolescent girls from rural areas suffered disproportionately. However, there is a dearth of evidence regarding the barriers that hinder adolescent girls to utilize the available nutritional services.

Purpose

The current study aimed to qualitatively explore the range of barriers for the uptake of nutritional interventions among adolescent girls in rural communities of Tigray, Northern Ethiopia.

Methods and Participants

We employed an explorative qualitative study among purposively selected adolescent girls and school teachers from rural districts of Tigray region. We conducted 11 focused group discussions with adolescent girls, 17 in-depth interviews (seven with teachers, seven with in-school adolescent girls, and three with out-of-school adolescent girls) using a semi-structured guide. Data was audio-taped, transcribed verbatim in local language, translated into English, and imported into ATLAS.ti version 7.5 qualitative data analysis software for analysis.

Results

Adolescents perceived that stunting, anemia, and thinness are among the main nutritional problems in their community. Food insecurity, limited nutrition awareness in the community, limited access to a water source, high workload, service provider's little attention for adolescents' nutrition, and food taboo have emerged as barriers for the uptake of adolescent girls' nutritional interventions. Though limited in reach, available nutritional interventions include awareness creation, nutritional supplementation, and disease prevention.

Conclusion

Food insecurity poses a strong challenge to adolescent girls' nutrition. As access to safe drinking water continues to be a considerable bottleneck for nutritional interventions, a multi-sectoral response to integrate water, sanitation, and hygiene (WASH) services is required. Bounded by food taboo, high burden of workload among the adolescent girls, women empowerment and nutritional status seem to be the unfinished agenda in resource limited settings such as the rural areas of Tigray region.

Influence of the Parental Educational Level on Physical Activity in Schoolchildren

The factors influencing physical activity participation in children are varied, although there is evidence that the educational level of parents may be one important factor. The aim of this study is to analyze the influence of parental education on the level of physical activity and the sedentary behavior of their children. The parents of 727 students, separated based on school group (preschool: n = 179; primary: n = 284; secondary: n = 230; high: n = 34), were invited to complete a series of questionnaires assessing their educational level (low, intermediate, and high) and their child’s level of physical activity and sedentary behavior. Primary school students with high- and intermediate-educated parents were found to engage in significantly more physical activity per week and spent more time engaged in homework than children with lower-educated parents. Secondary school students with higher-educated parents were found to spend significantly less time engaged in sedentary behavior than children with lower- or intermediate-educated parents, and high schoolers with higher-educated parents engaged in less tablet time than children with lower-educated parents. Multiple linear regression demonstrated that greater physical activity was precipitated by certain sedentary behaviors in children with more educated parents, such as total time watching TV (primary school), doing homework (secondary school), and total time using a tablet/similar (high school), which increased total time engaged in physical activity. These findings suggest that more educated parents may implement structured time for their children to engage in a balance of physical activity and sedentary behaviors.

Ecological correlates of activity-related behavior typologies among adolescents

Background

Adolescents engage in various combinations (typologies) of physical activity and sedentary behaviors, which impact their health and wellbeing in different ways. As such, there is a need to understand the factors that may inhibit or facilitate engagement in combinations of activity-related behaviors to help inform effective intervention strategies targeting those most in need. The aim of this study was to identify ecological correlates of adolescent physical activity and sedentary behavior typologies.

Methods

Cross-sectional study of 473 adolescents (15.0 ± 1.6 years, 41.4% boys) from 18 secondary schools in Melbourne, Australia. Intrapersonal, interpersonal and neighborhood-physical environmental factors were assessed via self-report surveys and Geographic Information Systems. Multinomial logistic regression models determined the relative risk ratio of membership of three homogenous activity-related behavior typologies based on the potential correlates.

Results

Higher levels of self-efficacy for physical activity, parental screen-time restriction rules, parental support for physical activity, sibling screen-time co-participation and perceptions of neighborhood pedestrian/traffic safety were associated with greater likelihood of adolescents being in the typology defined as highly active and low sedentary compared to the physically inactive, highly sedentary typology. Higher frequency of co-participation in screen-time with friends was associated with greater likelihood of adolescents being in the typology defined as moderately active, high screen-time compared to physically inactive, highly sedentary.

Conclusions

A range of intrapersonal, interpersonal and environmental correlates appear to play a role in adolescent activity-related typology membership. The findings may inform public health interventions targeting unique adolescent subgroups most at risk of poor health outcomes based on their engagement in combinations of activity-related behaviors.

Electronic supplementary material

The online version of this article (10.1186/s12889-019-7386-9) contains supplementary material, which is available to authorized users.

Is sport enough? Contribution of sport to overall moderate- to vigorous-intensity physical activity among adolescents

OBJECTIVES

This study examined the contribution of sports participation to overall moderate-to-vigorous physical activity (MVPA) among adolescents, and explored potential moderators.

DESIGN

Cross-sectional observational study using survey and accelerometry data drawn from the NEighbourhood Activity in Youth (NEArbY) study.

METHODS

Adolescents (n=358) were recruited from secondary schools in Melbourne, Australia. Average min/day in MVPA was assessed using accelerometry. Participants self-reported sports participation (number of teams, type, frequency, and months of participation). Regression models determined the percent variance in MVPA explained by the sport variables, adjusted for wear time, age and sex, and accounting for clustering at the school level. Additional analyses tested if age, sex, body mass index (BMI), and socioeconomic status (SES) moderated relationships between sport variables and MVPA.

RESULTS

Participants (mean 15.3 years, 59% female) spent a mean (SD) of 68.6 (27.4) min/day in MVPA and 50% reported participating in any sport. Those who participated in sport did so 3.4 times/week on average and accumulated 7min/day of MVPA more than those who did no sport. For each additional sport participated in, on average, there were approximately 5 additional min/day of MVPA. The number and frequency of sports participation explained 3.2% and 3.8% of the variance in MVPA respectively. Participation in field hockey and gymnastics explained 2.2% and 3.6% of the variance in MVPA, respectively. There were no moderating effects.

CONCLUSIONS

Sport appears to make a very small contribution to adolescents' average daily physical activity. Effectiveness of approaches to increasing youth population levels of physical activity via sports participation needs to be tested.

The Relationship between Objectively Measured and Self-Reported Sedentary Behaviours and Social Connectedness among Adolescents

Adolescents spend significant amounts of time engaged in various types of sedentary behaviour (SB). This study examined associations between adolescents’ objectively measured sedentary time, sitting time, specific self-reported SBs and social connectedness. Adolescents (n = 429, 15.5 years, 41% male) completed an online survey reporting time in seven SBs (TV/videos/DVDs, computer/video games, internet, homework, reading, car and bus travel; examined individually and summed for screen time and total SB), and social connectedness using the eight-item Social Connectedness Scale. A subsample (n = 353) also wore an ActiGraph GT3X+ (model GT3X+, Pensacola, FL, USA) accelerometer to measure sedentary time (<100 cpm) and n = 237 wore an activPAL (PAL Technologies Ltd., Glasgow, Scotland) inclinometer to measure sitting time. Multiple linear mixed models determined associations between each SB variable and social connectedness, adjusting for confounders. Adolescents spent on average 7.8 h/day in self-reported total SB, 4.4 h/day in screen time, 9.1 h/day in ActiGraph-measured sedentary time, and 9.5 h/day in activPAL-measured sitting time. After adjusting for age, sex and area level socioeconomic status, total SB (−0.24, 95%CI: −0.37, −0.11), screen time (−0.23, 95%CI: −0.41, −0.05) and two individual SBs (computer/video games (−1.07, 95%CI: −1.53, −0.60), homework (−0.61, 95%CI: −1.04, −0.18) were negatively associated with social connectedness. There were no associations with the objective measures. The relationships may be bi-directional; therefore, future research should involve longitudinal designs and explore other potential contributing factors.

Longitudinal Changes in Sitting Patterns, Physical Activity, and Health Outcomes in Adolescents

This study examined two-year changes in patterns of activity and associations with body mass index (BMI) and waist circumference (WC) among adolescents. Inclinometers (activPAL) assessed sitting, sitting bouts, standing, stepping, and breaks from sitting. ActiGraph-accelerometers assessed sedentary time (SED), light-intensity physical activity (LIPA, stratified as low- and high-LIPA), and moderate-to-vigorous physical activity (MVPA). Anthropometric measures were objectively assessed at baseline and self-reported at follow-up. Data from 324 and 67 participants were obtained at baseline and follow-up, respectively. Multilevel mixed-effects linear regression models examined changes over time, and associations between baseline values and BMI and WC at follow-up. There were significant increases in BMI (0.6 kg/m²) and durations of prolonged sitting (26.4 min/day) and SED (52 min/day), and significant decreases in stepping (−19 min/day), LIPA (−33 min/day), low-LIPA (−26 min/day), high-LIPA (−6.3 min/day), MVPA (−19 min/day), and the number of breaks/day (−8). High baseline sitting time was associated (p = 0.086) with higher BMI at follow-up. There were no significant associations between baseline sitting, prolonged sitting, LIPA, or MVPA with WC. Although changes in daily activity patterns were not in a favourable direction, there were no clear associations with BMI or WC. Research with larger sample sizes and more time points is needed.