Profiles of children's physical activity and sedentary behaviour between age 6 and 9: a latent profile and transition analysis

Movement behaviour typologies and their associations with adiposity indicators in children and adolescents: a latent profile analysis of 24-h compositional data

OBJECTIVES

Growing evidence supports the important role of 24-hour movement behaviours (MB) in preventing childhood obesity. However, research to understand the heterogeneity and variability of MB among individuals and what kind of typologies of individuals are at risk of developing obesity is lacking. To bridge this gap, this study identified typologies of 24-hour MB in children and adolescents and investigated their associations with adiposity indicators.

METHODS

In this cross-sectional study, 374 children and 317 adolescents from the Czech Republic wore wrist-worn accelerometers for seven consecutive days. Time spent in moderate-to-vigorous physical activity (MVPA), light physical activity (LPA), sedentary behaviour (SB), and sleep was quantified using raw accelerometery data. Adiposity indicators included body mass index (BMI) z-score, fat mass percentage (FM%), fat mass index (FMI), and visceral adipose tissue (VAT). Bias-adjusted latent profile analysis was used on the 24-hour MB data to identify MB typologies and their associations with adiposity indicators. The models were adjusted for potential confounders. The identified typologies were labelled to reflect the behavioural profiles of bees to aid interpretability for the general public.

RESULTS

Two typologies were identified in children: highly active Workers characterised by high levels of MVPA and LPA, and inactive Queens characterised by low levels of MVPA and LPA, high levels of SB and longer sleep duration compared to Workers. In adolescents, an additional typology labelled as Drones was characterised by median levels of MVPA, LPA, SB and longest sleep duration. After controlling for covariates, we found that children labelled as Queens were associated with 1.38 times higher FM%, 1.43 times higher FMI, and 1.67 times higher VAT than Workers. In adolescents, Drones had 1.14 times higher FM% and Queens had 1.36 higher VAT in comparison with Workers, respectively.

CONCLUSION

Our study highlights the importance of promoting active lifestyles in children and adolescents to potentially reduce adiposity. These findings can provide insights for interventions aimed at promoting healthy MB and preventing childhood obesity.

Predicting Accelerometer-Assessed Estimates of Adolescents' Multidimensional Physical Activity: A Self-Determination Theory Approach

Based on the tenets in self-determination theory, a dual-process model of motivational processes was tested to predict accelerometer-assessed estimates of adolescents' light physical activity (LPA), moderate to vigorous physical activity (MVPA), and sedentary time. Here, we hypothesized that (a) perceptions of psychological need support for exercise would be positively associated with LPA and MVPA and negatively associated with sedentary time via exercise-related psychological need satisfaction and autonomous exercise motivation and (b) perceptions of psychological need thwarting for exercise would be negatively associated with LPA and MVPA and positively associated with sedentary time via exercise-related psychological need frustration and controlled exercise motivation. Adolescents (N = 338; 234 female) age 11-15 years (M = 12.75, SD = .90) wore an ActiGraph accelerometer for 8 days and completed questionnaires pertaining to the self-determination-theory variables. Results showed psychological need support to indirectly and positively predict LPA and MVPA via psychological need satisfaction and autonomous exercise motivation. Although directly predictive of need frustration and indirectly predictive of controlled motivation and amotivation, the hypothesized effects from psychological need thwarting to the behavioral outcomes were nonsignificant. The current findings highlight the important role that need-supportive environments play in facilitating autonomous exercise motivation and behavior by being conducive to exercise-related psychological need satisfaction.

Weekend physical activity profiles and their relationship with quality of life: The SOPHYA cohort of Swiss children and adolescents

INTRODUCTION

Quality of life (QoL) is an important health indicator among children and adolescents. Evidence on the effect of physical activity (PA)-related behaviors on QoL among youth remains inconsistent. Conventional accelerometer-derived PA metrics and guidelines with a focus on whole weeks may not adequately characterize QoL relevant PA behavior.

OBJECTIVE

This study aims to a) identify clusters of accelerometer-derived PA profiles during weekend days among children and adolescents living in Switzerland, b) assess their cross-sectional and predictive association with overall QoL and its dimensions, and c) investigate whether the associations of QoL with the newly identified clusters persist upon adjustment for the commonly used PA metrics moderate-to-vigorous physical activity (MVPA) and time spent in sedentary behavior (SB).

METHODS

The population-based Swiss children's Objectively measured PHYsical Activity (SOPHYA) cohort among children and adolescents aged 6 to 16 years was initiated at baseline in 2013. PA and QoL information was obtained twice over a five-year follow-up period. The primary endpoint is the overall QoL score and its six dimension scores obtained by KINDL® questionnaire. The primary predictor is the cluster membership of accelerometer-derived weekend PA profile. Clusters were obtained by applying the k-medoid algorithm to the distance matrix of profiles obtained by pairwise alignments of PA time series using the Dynamic Time Warping (DTW) algorithm. Secondary predictors are accelerometer-derived conventional PA metrics MVPA and SB from two combined weekend days. Linear regression models were applied to assess a) the cross-sectional association between PA cluster membership and QoL at baseline and b) the predictive association between PA cluster membership at baseline and QoL at follow-up, adjusting for baseline QoL.

RESULTS

The study sample for deriving PA profile clusters consisted of 51.4% girls and had an average age of 10.9 [SD 2.5] years). The elbow and silhouette methods indicated that weekend PA profiles are best classified in two or four clusters. The most differentiating characteristic for the two-clusters classification ("lower activity" and "high activity"), and the four-clusters classification ("inactive", "low activity", "medium activity", and "high activity"), respectively was the participant's mean counts per 15-seconds epoch. Participants assigned to high activity clusters were younger and more often male. Neither the clustered PA profiles nor MVPA or SB were cross-sectionally or predictively associated with overall QoL. The only association of a conventional PA metrics with QoL while adjusting for cluster membership was observed between MVPA during the weekend days and social well-being with a mean score difference of 2.4 (95%CI: 0.3 to 4.5; p = 0.025).

CONCLUSION

The absence of strong associations of PA metrics for the weekend with QoL, except for the positive association between MVPA during the weekend days and social well-being, is in line with results from two randomized studies not showing efficacy of PA interventions on youth QoL. But because PA decreases with age, its promotion and relevance to QoL remain important research topics. Larger longitudinal study samples with more than two follow-up time points of children and adolescents are needed to derive new novel accelerometer-derived PA profiles and to associate them with QoL dimensions.

Comparison of children's physical activity profiles before and after COVID-19 lockdowns: A latent profile analysis

Physical activity is important for children's health, but moderate to vigorous physical activity (MVPA) declines with age. COVID-19 lockdowns resulted in reduced MVPA and increased sedentary time among children. Characterising children's activity patterns may help identify groups who are most likely to be inactive post-lockdown. Data were combined from a pre-COVID-19 cohort study on children aged 5-6 years (Year1: n = 1299), 8-9 years (Year4: n = 1223) and 10-11 years (Year6: n = 1296) and cross-sectional post-lockdown data from a natural experiment on 10-11-year-olds in 2021 (Year6-W1: n = 393) and 2022 (Year6-W2: n = 436). The proportions of time spent in MVPA, light physical activity (LPA) and sedentary time on weekdays and weekends were derived from accelerometer data. Latent class analysis was used to identify activity profiles pre and post-lockdown, and estimate pre-COVID-19 transitions between Year4 and Year6. We identified six pre-COVID-19 activity profiles in Year6, including a new profile characterised by very low MVPA and high sedentary time (19% of children). There was substantial movement between profiles at Year4 and Year6, with 45% moving to a profile with lower MVPA. Likelihood ratio tests suggested differences in Year6 activity profiles pre and post-lockdown, with a new post-lockdown profile emerging characterised by higher LPA. The percentage of children in the least active profiles (where under 20% meet UK physical activity guidelines), rose post-lockdown, from 34% pre-COVID-19 to 50% in 2021 and 40% in 2022. We also saw gender and socioeconomic gaps widen, and increased separation between high and low physical activity levels. Children's physical activity has changed post-COVID-19, in terms of who is being active and how. The impact varies by activity profile, which is influenced by gender and socio-economic position. A greater understanding of these differences and targeting of low active groups is needed to increase both individual and population levels of physical activity.

Cross-sectional and prospective associations between behavioural patterns and adiposity in school-aged children

OBJECTIVE

Behavioural patterns are important in understanding the synergistic effect of multiple health behaviours on childhood adiposity. Most previous evidence assessing associations between patterns and adiposity were cross-sectional and investigated two or three behaviour domains within patterns. This study aimed to identify behavioural patterns comprising four behaviour domains and investigate associations with adiposity risk in children.

DESIGN

Parent-report and accelerometry data were used to capture daily dietary, physical activity, sedentary behaviour and sleep data. Variables were standardised and included in the latent profile analysis to derive behavioural patterns. Trained researchers measured children's height, weight and waist circumference using standardised protocols. Associations of patterns and adiposity measures were tested using multiple linear regression.

SETTING

Melbourne, Australia.

PARTICIPANTS

A total of 337 children followed up at 6-8 years (T2) and 9-11 years (T3).

RESULTS

Three patterns derived at 6-8 years were broadly identified to be healthy, unhealthy and mixed patterns. Patterns at 9-11 years were dissimilar except for the unhealthy pattern. Individual behaviours characterising the patterns varied over time. No significant cross-sectional or prospective associations were observed with adiposity at both time points; however, children displaying the unhealthy pattern had higher adiposity measures than other patterns.

CONCLUSION

Three non-identical patterns were identified at 6-8 and 9-11 years. The individual behaviours that characterised patterns (dominant behaviours) at both ages are possible drivers of the patterns obtained and could explain the lack of associations with adiposity. Identifying individual behaviour pattern drivers and strategic intervention are key to maintain and prevent the decline of healthy patterns.

Exploring effects of multi-level factors on transitions of risk-taking behaviors among middle-to-late adolescents

Adolescents experiment with risk behaviors, including delinquency, substance use, and sexual activity. Multi-level social factors, such as having high-risk peers, neighborhood risks, and parental monitoring, influence adolescents' behaviors. We modeled transition patterns in Bahamian adolescents' risk behaviors across three high school years and examined the effects of multi-level factors. We collected data from 2,564 Bahamian adolescents in Grade 10 and follow-ups through Grade 12. We used latent transition model to identify adolescents' risk statuses. Further analyses used multinomial logistic regression to explore the effects of multi-level factors on assignment to those latent statuses and transitions. We identified four distinct statuses: "low risk" (47.9% of the sample at baseline), "alcohol use" (36.8%), "alcohol use and sexual activity" (5.5%), and "high risk" (9.8%). Males were more likely to be in higher-risk statuses at baseline and to transition from a lower-risk status in Grade 10 to a higher-risk status in Grade 11. Social risk factors were significantly associated with higher-risk statuses at baseline. Neighborhood risk and peer risk involvement continued to affect transitions from lower to higher risk; parental monitoring did not have a significant effect in later years. Our findings have important implications for developing targeted and developmentally appropriate interventions to prevent and reduce risk behaviors among middle-to-late adolescents.

Analysis of the 24-h activity cycle: An illustration examining the association with cognitive function in the Adult Changes in Thought study

The 24-h activity cycle (24HAC) is a new paradigm for studying activity behaviors in relation to health outcomes. This approach inherently captures the interrelatedness of the daily time spent in physical activity (PA), sedentary behavior (SB), and sleep. We describe three popular approaches for modeling outcome associations with the 24HAC exposure. We apply these approaches to assess an association with a cognitive outcome in a cohort of older adults, discuss statistical challenges, and provide guidance on interpretation and selecting an appropriate approach. We compare the use of the isotemporal substitution model (ISM), compositional data analysis (CoDA), and latent profile analysis (LPA) to analyze 24HAC. We illustrate each method by exploring cross-sectional associations with cognition in 1,034 older adults (Mean age = 77; Age range = 65-100; 55.8% female; 90% White) who were part of the Adult Changes in Thought (ACT) Activity Monitoring (ACT-AM) sub-study. PA and SB were assessed with thigh-worn activPAL accelerometers for 7-days. For each method, we fit a multivariable regression model to examine the cross-sectional association between the 24HAC and Cognitive Abilities Screening Instrument item response theory (CASI-IRT) score, adjusting for baseline characteristics. We highlight differences in assumptions and the scientific questions addressable by each approach. ISM is easiest to apply and interpret; however, the typical ISM assumes a linear association. CoDA uses an isometric log-ratio transformation to directly model the compositional exposure but can be more challenging to apply and interpret. LPA can serve as an exploratory analysis tool to classify individuals into groups with similar time-use patterns. Inference on associations of latent profiles with health outcomes need to account for the uncertainty of the LPA classifications, which is often ignored. Analyses using the three methods did not suggest that less time spent on SB and more in PA was associated with better cognitive function. The three standard analytical approaches for 24HAC each have advantages and limitations, and selection of the most appropriate method should be guided by the scientific questions of interest and applicability of each model's assumptions. Further research is needed into the health implications of the distinct 24HAC patterns identified in this cohort.

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.

Associations of Device-Measured Physical Activity, Sedentary Behavior, and Executive Function in Preadolescents: A Latent Profile Approach

PURPOSE

This study investigated the associations between physical activity (PA), sedentary behavior, and executive function in preadolescents.

METHODS

One hundred and twenty preadolescents were recruited from 2 Hong Kong primary schools. PA and sedentary behavior were recorded for 7 consecutive days by accelerometer. Executive function performance, including inhibition (Stroop task and Flanker task) and working memory (Sternberg paradigm task), were measured. Body mass index and cardiorespiratory fitness (multistage fitness test) were tested. Latent profile analysis explored the profiles of PA and sedentary behavior in preadolescents.

RESULTS

Three distinct profiles were identified: low activity, average activity, and high activity. Participants in low activity performed worse in the accuracy of Stroop task (vs average activity, P = .03; vs high activity, P < .01), Flanker task (vs average activity, P = .02; vs high activity, P < .001), and Sternberg paradigm task (vs average activity, P < .01; vs high activity, P < .01). No significant difference was observed between participants with average and high activities. No significant association was observed for profiles on body mass index and cardiorespiratory fitness.

CONCLUSION

Supplementing the consensus of the literature that moderate to vigorous PA benefits cognition, the authors conclude that light PA may also enhance preadolescents' executive functioning.

Physical Activity, Body Mass Index (BMI) and Abdominal Obesity of Pre-Adolescent Children in the Region of Thrace, NE Greece, in Relation to Socio-Demographic Characteristics

This study aimed to explore the prevalence of overweight, obesity, and abdominal obesity, and define predictive factors of their occurrence among pre-adolescents in the region of Thrace, NE Greece. A secondary aim was to record physical activity at different times (schooldays, weekends, holidays) and explore associations with characteristics such as gender, overweight and obesity, and socio-demographic conditions. A cross-sectional study was conducted involving children aged 11–12 years. Participating children were measured for height, weight, and waist circumference, and their parents answered a questionnaire. In total, 1929 children were included. Prevalence of overweight was 31.5%, prevalence of obesity 17%, and only 1% of children were underweight. Abdominal obesity was detected in 20.3% of the sample. Overweight and obesity were more frequent in males, who also had higher mean values of Body Mass Index-for-age z-scores (BMIaz) and Waist-to-Height ratio (WtHR). Obesity rates were higher among those not participating in physical activities; however, no significant difference was observed between normal-weight, overweight and obese children in the time spent for organized athletic activities or free play. Logistic regression analysis showed that the probability for overweight/obesity was higher in boys (OR = 1.39, 95% CI = 1.16–1.66) and lower in children whose fathers had a higher educational level (OR = 0.75, 95% CI = 0.60–0.93). The probability for abdominal obesity was also higher in boys (OR = 1.37, 95% CI = 1.10–1.72) and lower in children participating at least one hour/day in an organized physical activity (compared to those with no physical activity (OR = 0.66, 95% CI = 0.51–0.85), and whose father was exercising at least 1–2 times/week (OR = 0.76, 95% CI = 0.591–0.98). In conclusion, the prevalence of overweight and obesity among pre-adolescents in NE Greece was estimated at 48.5%. This is associated with the male gender and not participating in physical activities. The educational level and exercise habits of the father (but not of the mother) affect the probability of obesity and abdominal obesity, respectively.

Teachers' Perspectives on the Acceptability and Feasibility of Wearable Technology to Inform School-Based Physical Activity Practices

Background: Many children are not engaging in sufficient physical activity and there are substantial between-children physical activity inequalities. In addition to their primary role as educators, teachers are often regarded as being well-placed to make vital contributions to inclusive visions of physical activity promotion. With the dramatic increase in popularity of wearable technologies for physical activity promotion in recent years, there is a need to better understand teachers' perspectives about using such devices, and the data they produce, to support physical activity promotion in schools. Method: Semi-structured interviews were conducted with 26 UK-based primary school teachers, exploring their responses to children's physical activity data and their views about using wearable technologies during the school day. Interview discussions were facilitated by an elicitation technique whereby participants were presented with graphs illustrating children's in-school physical activity obtained from secondary wearable technology data. Interview transcripts were thematically analyzed. Results: Most teachers spoke positively about the use of wearable technologies specifically designed for school use, highlighting potential benefits and considerations. Many teachers were able to understand and critically interpret data showing unequal physical activity patterns both within-and between-schools. Being presented with the data prompted teachers to provide explanations about observable patterns, emotional reactions-particularly about inequalities-and express motivations to change the current situations in schools. Conclusion: These findings suggest that primary school teachers in the UK are open to integrating wearable technology for measuring children's physical activity into their practices and can interpret the data produced by such devices. Visual representations of physical activity elicited strong responses and thus could be used when working with teachers as an effective trigger to inform school practices and policies seeking to address in-school physical inactivity and inequalities.

Associations between Child and Family Level Correlates and Behavioural Patterns in School-Aged Children

Identifying correlates of behavioural patterns are important to target population sub-groups at increased health risk. The aim was to investigate correlates of behavioural patterns comprising four behavioural domains in children. Data were from the HAPPY study when children were 6–8 years (n = 335) and 9–11 years (n = 339). Parents reported correlate and behavioural data (dietary intake, physical activity, sedentary behaviour, and sleep). Behavioural data were additionally captured using accelerometers. Latent profile analysis was used to derive patterns. Patterns were identified as healthy, unhealthy, and mixed at both time points. Multinomial logistic regression tested for associations. Girls were more likely to display healthy patterns at 6–8 years and display unhealthy and mixed patterns at 9–11 years than boys, compared to other patterns at the corresponding ages. Increased risk of displaying the unhealthy pattern with higher age was observed at both timepoints. At 9–11 years, higher parental working hours were associated with lower risk of displaying mixed patterns compared to the healthy pattern. Associations observed revealed girls and older children to be at risk for unhealthy patterns, warranting customisation of health efforts to these groups. The number of behaviours included when deriving patterns and the individual behaviours that dominate each pattern appear to be drivers of the associations for child level, but not for family level, correlates.

24-hour movement behaviour profiles and their transition in children aged 5.5 and 8 years - findings from a prospective cohort study

BACKGROUND

Time spent in movement behaviours, including physical activity (PA), sedentary behaviour (SB) and sleep, across the 24-h day may have distinct health consequences. We aimed to describe 24-h movement behaviour (24 h-MB) profiles in children and how profile membership changed from age 5.5 to 8 years.

METHODS

Children in the Growing Up in Singapore Towards healthy Outcomes (GUSTO) cohort were asked to wear an accelerometer (ActiGraph-GT3X+) on their wrist for seven consecutive days at ages 5.5 and 8 years to measure 24 h-MB patterns. Time spent in night sleep, inactivity (proxy for SB), light PA, moderate PA (MPA), and vigorous PA (VPA) per day were calculated using the R-package GGIR 2.0. Using latent profile analyses (n = 442) we identified 24 h-MB profiles, which were given animal names to convey key characteristics. Latent transition analyses were used to describe the profile membership transition from ages 5.5 to 8 years. Associations with sex and ethnicity were examined.

RESULTS

We identified four profiles, "Rabbits" (very high-MPA/VPA, low-inactivity and average-night-sleep), "Chimpanzees" (high-MPA, low-inactivity and average-night-sleep), "Pandas" (low-PA, high-inactivity and high-night-sleep) and "Owls" (low-PA, high-inactivity and low-night-sleep), among children at both time points. At ages 5.5 and 8 years, the majority of children were classified into profiles of "Chimpanzees" (51 and 39%, respectively) and "Pandas" (24 and 37%). Half of the sample (49%), particularly "Rabbits", remained in the same profile at ages 5.5 and 8 years: among children who changed profile the predominant transitions occurred from "Chimpanzees" (27%) and "Owls" (56%) profiles to "Pandas". Sex, but not ethnicity, was associated with profile membership: compared to girls, boys were more likely to be in the "Rabbits" profile (adjusted OR [95% CI]: 3.6 [1.4, 9.7] and 4.5 [1.8, 10.9] at ages 5.5 and 8 years, respectively) and less likely to be in the "Pandas" profile (0.5 [0.3, 0.9] and 0.4 [0.2, 0.6]) at both ages.

CONCLUSIONS

With increasing age about half the children stayed in the same of four 24 h-MB profiles, while the predominant transition for the remaining children was towards lower PA, higher inactivity and longer sleep duration. These findings can aid development and implementation of public health strategies to promote better health.

STUDY REGISTRATION

This study was registered on 4th August 2010 and is available online at ClinicalTrials.gov: NCT01174875 .

Longitudinal patterns of lifestyle behaviours in adolescence: a latent transition analysis

The interdependence among eating behaviour (EB), physical activity (PA) and sedentary time (ST) suggests simultaneously identifying homogeneous profiles and describing their changes. This study aimed to (1) identify cross-sectional lifestyle behaviour profiles and their 2-year changes among French school-age adolescents and (2) identify factors associated with these profiles and changes. Longitudinal data from adolescents who participated in the PRomotion de l'ALIMentation et de l'Activité Physique trial were used. PA and ST were assessed with the International Physical Activity Questionnaire and EB with a FFQ. Profiles at baseline and their changes were identified by latent transition analysis. Multinomial logistic regression models were used to identify factors associated with profiles and their changes. Among 2390 adolescents included (14-18 years), five baseline profiles that differed mainly in EB were identified: 'healthy diet and high PA (7·9 %)', 'big eater and moderate to high PA (23·8 %)', 'healthy diet and low PA (31·2 %)', 'restrictive diet and moderate PA (20·6 %)' and 'sugar products, nibbling and moderate PA (16·5 %)'. Young adolescents, those who were overweight or obese and socially advantaged, were more in the 'healthy diet and low PA' than others. Boys, older and socially less advantaged adolescents exhibited more 'unfavourable' than 'mixed' changes, while adolescents with overweight or obesity had less 'unfavourable' than 'mixed' changes. In conclusion, adolescents were twice the number in the least than the most favourable profile. Findings highlighted the importance of EB among adolescents and suggest taking adolescents' sociodemographic and weight characteristics into account in interventions aimed at acting on adolescents' behaviours.

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.

Obesity and decrease of daily physical activity among children and adolescents: a follow-up study

ABSTRACT We analyzed the effect of obesity on daily physical activity (DPA), light-intensity physical activity (LPA), moderate-intensity physical activity (MPA) and vigorous- intensity physical activity (VPA) in children and adolescents. Overall, 462 students from a public school (53.6% boys; aged 7-12 years) were involved in this one-year longitudinal study. Physical activities and sedentary behaviors (SB) were reported in the questionnaire Food Intake and Physical Activity of Students (Web-CAAFE). Obesity was evaluated through Body Mass Index (BMI z score ≥ 2). Obesity was observed in 16.5% of participants, but it did not influence LPA, MPA or DPA. However, VPA were 20% less frequent among obese students (β2=0.80; CI 95%: 0.66-0.98). Obese girls showed less frequency of VPA than non-obese boys (Mean Difference = -0.97; CI 95%: -1.36 to -0.57). Non-obese girls showed less VPA than non-obese boys (Mean Difference = -1.18; CI 95%: -1.40 to -0.95) and obese ones (Mean Difference = -0.57; CI 95%: -0.90 to -0.24). Obese boys showed fewer VPA, if compared to non-obese ones (Mean Difference = -0.61; CI 95%: -0.96 to -0.26). The analysis of the obesity-sex-age interaction showed a greater reduction in VPA among obese girls aged 10 years or more when compared to obese girls aged 7-9 years, and among boys obese and non-obese regardless of age. Amounts of VPA and SB increased simultaneously among non-obese boys and non-obese children aged 7-9 years. Obesity reduced VPA in the sample during the follow up of one year, independently of age and SB.

“I feel proper self-conscious all the time”: A qualitative study of adolescent girls’ views of menstruation and physical activity

Background: Many children and adolescents do not engage in sufficient physical activity. Girls are less active than boys, and their activity levels decline more steeply with age. Menstruation may be associated with the decline in girls’ activity but there are few person-centred studies examining adolescent girl’s experiences of menstruation and physical activity. These are needed to understand the influence that menstruation has on the physical activity experiences of girls to inform effective interventions. Methods: Focus groups were conducted with 46 girls aged 13-15 years across three schools. The discussions explored; experiences of, barriers to and facilitators of being active during menstruation; experiences in physical education/sports teams; and talking with others about periods and being active. Data were analysed using thematic analysis. Results: Four themes were identified: 1) balancing perceived barriers and benefits 2) motivation and enjoyment, 3) social influences and 4) coping strategies. Participants reported using diverse strategies to overcome barriers to being active posed by menstruation and the importance of peer-support and enjoyable forms of activity. Conclusions: Menstruation has a strong influence on girls’ physical activity experiences through intra- and inter-personal factors. The implications for how these can be addressed in efforts to increase girls’ physical activity are discussed.

Compliance of the 24-Hour Movement Guidelines in 9- to 11-Year-Old Children From a Low-Income Town in Chile

BACKGROUND

The purpose was to determine the proportion of 9- to 11-year-old children meeting the 24-hour movement guidelines (24-HMG) in a low-income town from Chile.

METHODS

Physical activity, sedentary behavior (recreational screen), and sleep times were measured with both questionnaire and accelerometer in 258 children from third to sixth grade. Meeting the 24-HMG was defined as having ≥60 minutes per day of moderate to vigorous physical activity, ≤2 hour day of screen time, and 9 to 11 hours of sleep per night. Compliance rates were calculated as self-reported 24-HMG, with all estimations based on questionnaires, and mixed 24-HMG, in which physical activity and sleep were determined with an accelerometer and sedentary behavior was determined with a questionnaire.

RESULTS

About 198 children (10.1 [0.8] y, range 9-11 y) provided valid data for estimating self-reported 24-HMG, and 141 for mixed 24-HMG. Only 3.2% and 0.7% met the 24-HMG when using the self-reported and mixed methods, respectively. When assessing individual recommendations, 13.1% and 3.7% of the sample were physically active based on the self-report and accelerometer, respectively. About a quarter met the sedentary behavior recommendations, while around 50% met the sleep recommendations with both self-reported and mixed methods.

CONCLUSIONS

An extremely low percentage of the participants met the 24-HMG. Multicomponent initiatives must be implemented to promote healthy movement behaviors in Chilean children.

A systematic review of lifestyle patterns and their association with adiposity in children aged 5-12 years

Diet, physical activity, sedentary behaviour and sleep are typically examined independently with childhood adiposity; however, their combined influence remains uncertain. This review aims to systematically summarize evidence on the clustering of these behaviours through lifestyle patterns and evaluate associations with adiposity in children aged 5-12 years. Search strategies were run in six databases. Twenty-eight papers met the inclusion criteria, six of which included all four behaviours. A range of lifestyle patterns were identified (healthy, unhealthy and mixed). Mixed patterns were most frequently reported. Unhealthy patterns comprising low physical activity and high sedentary behaviour were also frequently observed. Mixed patterns comprising healthy diets, low physical activity and high sedentary behaviour were more commonly seen in girls, whereas boys were more physically active, similarly sedentary and had unhealthier diets. Children from lower socio-economic backgrounds tended to more frequently display unhealthy patterns. Unhealthy lifestyle patterns were more often associated with adiposity risk than healthy and mixed patterns. With few studies including all four behaviours, it is difficult to establish a clear picture of their interplay and associations with adiposity. Nonetheless, reliance on lifestyle patterns is likely more beneficial than individual behaviours in targeting adiposity and improving understanding of how these behaviours influence health.

Associations between meeting sleep, physical activity or screen time behaviour guidelines and academic performance in Australian school children

BACKGROUND

Current guidelines suggest too little sleep, too little physical activity, and too much sedentary time are associated with poor health outcomes. These behaviours may also influence academic performance in school children. The primary purpose of this study was to examine the relationships between sleep, physical activity, or sedentary behaviours and academic performance in a school with a well-developed and integrated technology use and well-being program.

METHODS

This was a cross-sectional survey of students (n = 934, Grades 5-12) in an Australian school with a bring-your-own device (tablet or laptop computer) policy. Students reported sleep, physical activity, and sedentary (screen and non-screen) behaviours. Academic performance was obtained from school records. Linear regressions were used to test the association between behaviours and academic performance outcomes.

RESULTS

Seventy-four percent of students met sleep guidelines (9 to 11 h for children 5-13 years and 8 to 10 h for 14-17 year olds), 21% met physical activity guidelines (60 min of moderate-to-vigorous physical activity every day), and 15% met screen time guidelines (no more than 2 h recreational screen time per day); only 2% met all three. There were no associations between meeting sleep guidelines and academic performance; however later weekend bedtimes were associated with poorer academic performance (- 3.4 points on the Average Academic Index, 95%CI: - 5.0, - 1.7, p < .001). There were no associations between meeting physical activity guidelines and academic performance. Meeting screen guidelines was associated with higher Average Academic Index (5.8, 95%CI: 3.6, 8.0, p < .001), Maths 7.9, 95%CI: 4.1, 11.6, p < .001) and English scores (3.8, 95%CI: 1.8, 5.8, p < .001) and higher time in sedentary behaviours was associated with poorer academic performance, including total sedentary behaviours in hrs/day (5.8 points on Average Academic Index, 95%CI: 3.6, 8.0, p < .001. Meeting at least two of the three behaviour guidelines was associated with better academic performance.

CONCLUSIONS

Sleep and sedentary behaviours were linked to academic performance. School communities should emphasize comprehensive wellness strategies to address multiple behaviours to maximize student health and academic success.

Multidimensional motivation for exercise: A latent profile and transition analysis

OBJECTIVES

To: a) identify motivational profiles for exercise, using Self-Determination Theory as a theoretical framework, among a sample of parents of UK primary school children; b) explore the movement between motivational profiles over a five year period; and c) examine differences across these profiles in terms of gender, physical activity and BMI.

DESIGN

Data were from the B-Proact1v cohort.

METHODS

2555 parents of British primary school children participated across three phases when the child was aged 5-6, 8-9, and 10-11. Parents completed a multidimensional measure of motivation for exercise and wore an ActiGraph GT3X + accelerometer for five days in each phase. Latent profile and transition analyses were conducted using a three-step approach in MPlus.

RESULTS

Six profiles were identified, comprising different combinations of motivation types. Between each timepoint, moving between profiles was more likely than remaining in the same one. People with a more autonomous profile at a previous timepoint were unlikely to move to more controlled or amotivated profiles. At all three timepoints, more autonomous profiles were associated with higher levels of MVPA and lower BMI.

CONCLUSIONS

The results show that people's motivation for exercise can be described in coherent and consistent profiles which are made up of multiple and simultaneous types of motivation. More autonomous motivation profiles were more enduring over time, indicating that promoting more autonomous motivational profiles may be central to facilitating longer-term physical activity engagement.

A Multilevel Analysis of Neighbourhood, School, Friend and Individual-Level Variation in Primary School Children's Physical Activity

Physical activity is influenced by individual, inter-personal and environmental factors. In this paper, we explore the variability in children's moderate-to-vigorous physical activity (MVPA) at different individual, parent, friend, school and neighbourhood levels. Valid accelerometer data were collected for 1077 children aged 9, and 1129 at age 11, and the average minutes of MVPA were derived for weekdays and weekends. We used a multiple-membership, multiple-classification model (MMMC) multilevel model to compare the variation in physical activity outcomes at each of the different levels. There were differences in the proportion of variance attributable to the different levels between genders, for weekdays and weekends, at ages 9 and 11. The largest proportion of variability in MVPA was attributable to individual variation, accounting for half of the total residual variability for boys, and two thirds of the variability for girls. MVPA clustered within friendship groups, with friends influencing peer MVPA. Including covariates at the different levels explained only small amounts (3%-13%) of variability. There is a need to enhance our understanding of individual level influences on children's physical activity.

Association of BMI category with change in children's physical activity between ages 6 and 11 years: a longitudinal study

BACKGROUND/OBJECTIVES

To examine the association of body mass index (BMI) with change in children's physical activity and sedentary time between ages 6 and 11.

PARTICIPANTS

A total of 2132 children participated from 57 schools in Southwest England, from the B-PROACT1V study.

METHODS

Mean minutes of MVPA and sedentary time per day were derived from accelerometer-based measurements at ages 6, 9 and 11. Linear multilevel models examined the association of BMI categories with MVPA and sedentary time between 6 and 11, adjusting for seasonality, wear time, gender and household education. Differences in change over time were examined using interaction terms.

RESULTS

Average weekday MVPA decreased between ages 6 and 11 by 2.2 min/day/year (95% CI: 1.9 to 2.5), with a steeper decline at weekends. Average sedentary time increased at a rate of 12.9 min/day/year (95% CI: 12.2 to 13.6). There were no differences in mean levels of MVPA by BMI categories at age 6, but differences emerged as children aged, with the gap between children who were healthy weight and overweight increasing by 1.7 min/day (95% CI: 0.8-2.6) every year, and between healthy and obese by 2.0 min/day (95% CI: 0.9-3.1) each year. Children who were overweight/obese engaged in less average weekday sedentary time at age 6 than those of healthy weight, but the gap closed by age 11.

CONCLUSION

MVPA declines and sedentary time increases on average for all children between ages 6 and 11. While there are no differences in activity levels by BMI category at age 6, differences in MVPA emerge over time for those who are overweight and obese. Developing interventions that support children to retain activity levels as they approach older childhood, particularly those who are overweight/obese could improve public health.

A Longitudinal Study of the Associations of Family Structure with Physical Activity across the Week in Boys and Girls

The aim of this study was to examine how family structure is associated with moderate-to-vigorous-intensity physical activity (MVPA) for children aged between 6 and 11. At 6, 9 and 11 years, children wore an accelerometer and parents/carers completed questionnaires on demographics and family structure. Linear regression models examined cross-sectional associations between family structure and MVPA at age 9 and 11. Linear multilevel models examined longitudinal associations between age 6 and 11, differences in change over time were examined using interaction terms. No associations between exposures and MVPA were evident at age 9. Compared to boys living in one home, eleven-year-old boys who lived in multiple homes performed 15.99 (2.46-29.52) fewer minutes of MVPA on weekend days. In longitudinal analyses, the evidence was unclear whether the association with family structure changed over time. Models that assumed associations with family structure remained constant over time, found that boys who lived in multiple homes performed 11.02 (0.76-21.28) fewer minutes of MVPA per weekend day, while for each additional sibling, girls performed an extra 1.89 (0.25-3.53) minutes of MVPA per weekend day. Findings indicate a small number of associations, varying in magnitude, between family structure and children's MVPA. Therefore, families of all structures should be supported to help their children meet MVPA recommendations.

The association of school-related active travel and active after-school clubs with children's physical activity: a cross-sectional study in 11-year-old UK children

BACKGROUND

Physical activity is associated with improved physical and mental health among children, but many children do not meet the recommended hour per day of moderate-to-vigorous-intensity physical activity (MVPA). The aim of this paper is to investigate participation in active after-school clubs and active travel to and from school at age 11 and estimate the average daily minutes of MVPA associated with active club attendance and active travel.

METHODS

Accelerometer data were collected on three weekdays for 1296 11-year-old children in a cross-sectional study. Children reported attendance at active after-school clubs and how they travelled to and from school for each day of the week. To account for repeat days within child and clustering within schools we used multilevel models with random effects at the school and child level, and fixed effects for all covariates. We calculated odds ratios for participation in active after-school clubs and active travel for gender, measures of socio-economic position and BMI category. We also explored the association between active club attendance, active travel and daily average MVPA.

RESULTS

Boys and girls were equally likely to attend active after-school clubs. Boys were more likely to travel to school using active modes. Attendance at active after-school clubs and active travel home were not associated with each other. Attending an active after-school club was associated with an additional 7.6 min (95% CI: 5.0 to 10.3) average MVPA on that day among both boys and girls. Active travel was associated with an additional 4.7 min (95% CI: 2.9 to 6.5) average MVPA per journey for boys and 2.4 min (95% CI: 1.0 to 3.7) for girls.

CONCLUSIONS

Both active after-school clubs and active travel are associated with greater physical activity on the day that children participate in these, and we saw no evidence that those attending active clubs do so at the expense of active travel home afterwards. While the increased daily MVPA is small to moderate, active after-school clubs and active travel on multiple days of the week could make important contributions as part of complex interventions aimed at increasing population levels of physical activity in children.

Visualising Combined Time Use Patterns of Children's Activities and Their Association with Weight Status and Neighbourhood Context

Compositional data techniques are an emerging method in physical activity research. These techniques account for the complexities of, and interrelationships between, behaviours that occur throughout a day (e.g., physical activity, sitting, and sleep). The field of health geography research is also developing rapidly. Novel spatial techniques and data visualisation approaches are increasingly being recognised for their utility in understanding health from a socio-ecological perspective. Linking compositional data approaches with geospatial datasets can yield insights into the role of environments in promoting or hindering the health implications of the daily time-use composition of behaviours. The 7-day behaviour data used in this study were derived from accelerometer data for 882 Auckland school children and linked to weight status and neighbourhood deprivation. We developed novel geospatial visualisation techniques to explore activity composition over a day and generated new insights into links between environments and child health behaviours and outcomes. Visualisation strategies that integrate compositional activities, time of day, weight status, and neighbourhood deprivation information were devised. They include a ringmap overview, small-multiple ringmaps, and individual and aggregated time–activity diagrams. Simultaneous visualisation of geospatial and compositional behaviour data can be useful for triangulating data from diverse disciplines, making sense of complex issues, and for effective knowledge translation.