Patterns of movement behaviors and their association with overweight and obesity in youth

Combined effects of sugar-sweetened beverage consumption, screen-based sedentary behavior, and sleep duration on South Korean adolescent obesity: a cross-sectional study

PURPOSE

This study examined the combined effects of sugar-sweetened beverage (SSB) consumption, screen-based sedentary behaviors, and sleep duration on adolescent obesity.

METHODS

It followed a cross-sectional study design and conducted secondary analysis on data from 20,497 high school students who participated in the 17th (2021) Korea Youth Risk Behavior Web-based Survey. This study underwent logistic regression analysis in complex sampling analysis.

RESULTS

The combinations of low and medium consumption of SSBs, excessive screen-based sedentary behaviors, and short sleep durations were associated with a 1.18 and 1.12 fold increased likelihood of obesity (95% confidence interval [CI]=1.03-1.35) and (95% CI=1.02-1.22), respectively. The combination of high SSB consumption, appropriate screen-based sedentary behaviors, and short sleep duration (adjusted odds ratio [aOR]=1.15, 95% CI=1.01-1.31) and high SSB consumption, excessive screen-based sedentary behaviors, and short sleep duration (aOR=1.40, 95% CI=1.16-1.69) were associated with obesity.

CONCLUSION

Integrated and tailored programs considering combination patterns of SSB consumption, screen-based sedentary behaviors, and short sleep duration need to be developed for preventing adolescent obesity.

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.

Factors Related to High-School Students’ Odds of Having Overweight or Obesity

This study used data the Youth Risk Behavior Surveillance System ( N = 7,088) to examine factors associated with the odds of overweight/obesity. Overweight/obese was defined as a body mass index ≥85th percentile, based on age- and sex-specific growth charts. Participants were categorized into meeting/not meeting guidelines for: sleep, moderate-to-vigorous PA (MVPA), muscle strengthening PA, screen time, breakfast eating, fruit and vegetable consumption, and soda and milk consumption. Logistic regression analyses determined whether meeting guidelines for each health behavior was associated with the odds of students having overweight/obesity in the total group and stratified by sex. Meeting MVPA guidelines was the only behavior associated with having a lower odds of overweight/obesity in both sexes. For females, meeting recommendations for breakfast eating and strength training were also associated with lower odds of having overweight/obesity, whereas for boys, getting the recommended amount of sleep was associated with having lower odds of overweight/obesity. Interventions to reduce the prevalence of overweight/obesity in youth should be implemented inside and outside of the school environment and should include components addressing physical activity, diet, and sleep. Such interventions should address barriers to healthy behaviors that are unique to adolescents already affected by overweight/obesity.

Correlation between lifestyle patterns and overweight and obesity among Chinese adolescents

Lifestyles such as physical exercise, sedentary behavior, eating habits, and sleep duration are all associated with adolescent overweight and obesity. The purpose of this study was to investigate how Chinese adolescents' lifestyles clustered into different lifestyle patterns, and to analyze the correlation between these patterns and adolescent overweight and obesity. The investigated respondents included 13,670 adolescents aged 13-18 from various administrative regions in China. Latent class analysis was employed to cluster the lifestyles of adolescents, χ2 test and Logistic regression were used to explore the relationship between lifestyle patterns and overweight and obesity in adolescents. The results identified 6 types of Chinese adolescents' lifestyle patterns, as well as the significant differences in gender and age. The adolescents with high exercise-high calorie diet had the lowest risk of overweight and obesity, and the adolescents with low consciousness-low physical activity and low consciousness-unhealthy had the highest risk of overweight and obesity, which were 1.432 times and 1.346 times higher than those with high exercise-high calorie diet, respectively. The studied demonstrated that there was a coexistence of healthy behaviors and health-risk behaviors in the lifestyle clustering of Chinese adolescents. Low physical exercise and high intake of snacks and carbonated beverages were the most common. Physical exercise and health consciousness were the protective factors of overweight and obesity in adolescents.

Obesity researches in youth: A scientometrics study in Middle East countries

BACKGROUND

The alarming trends of obesity/overweight in youth have been interested policy makers and other stakeholders to exact follow and analysis of related scientific evidence. The present paper quantify the trends of outputs of youth obesity/overweight researches in Middle East countries.

MATERIALS AND METHODS

The Scopus database systematically searched as the most comprehensive multidisciplinary database, for all related obesity/overweight that focused on youth age groups concerns, from 2000 to 2017. These scientometrics analysis included the trends of scientific products, citations, and other scientometric index in Middle East countries.

RESULTS

During 2000-2017, in the field of youth obesity, 2350 papers published (0.40% of total 591,105 indexed paper of this region) by Middle East countries. In this regard, Iran with 574 publication (24.43%) had the first rank. After that Turkey and Saudi Arabia, respectively, with 489 (20.81%) and 313 (13.32%) papers, had the next ranks. Over 18-year period, based on the findings all of Eastern Mediterranean countries follow the progressive plans for topics related to youth obesity. Between them, Iran and Turkey have significant growth rates (0.77% and 0.40%, respectively). Scientometric indicators such as "number of published papers," "number of citations" confirmed that during the 2000-2017 the P-trends of total number of related published papers and the correspond citations, in region countries, were significant (2168 papers and 34,132 citations, P < 0.001).

CONCLUSION

Most of countries at global and regional levels follow ascending trends in publications and citations in obesity/overweight fields. Iran's position has grown significantly among them. Maintaining and promoting this position requires careful planning and special attention. The findings also could be used for better health policy and complementary researches.

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.

Identifying patterns of movement behaviours in relation to depressive symptoms during adolescence: A latent profile analysis approach

Movement behaviour guideline adherence has been associated with lower depressive symptoms during adolescence, yet no studies have used person-centered approaches to examine this relationship. The purpose of the present study was to identify whether unique adolescent movement behaviour profiles exist, evaluate predictors of profile membership, and determine whether profile membership was associated with differences in depressive symptoms cross sectionally and longitudinally. This study involved secondary analysis of the public-use data from Wave 1 and Wave 2 of the National Study of Adolescent Health. Adolescents (N = 6436; 48% male) in grades 7 to 12 (M_age = 16.03 ± 1.75) completed measures to assess moderate-to-vigorous physical activity (MVPA), recreational screen time (ST), and sleep - collectively known as movement behaviours - and depressive symptoms. Latent profile analysis identified four profiles that had similar sleep patterns and were thus characterized by different levels of MVPA and ST: high MVPA/low ST (29%), high MVPA/high ST (4%), low MVPA/low ST (53%), and low MVPA/high ST (14%). Several socio-demographic variables were found to influence profile membership. After adjusting for covariates, findings revealed depressive symptoms were lowest among the high MVPA/low ST profile and this trend was evident one year later. Engaging in high levels of either MVPA or ST alone did not provide additive benefits for depressive symptoms compared to those who engaged in low levels of both MVPA and ST. These findings suggest intervention efforts should take an integrative approach to improve mental health outcomes among adolescents by considering each of the movement behaviours concurrently.

Gender differences in the longitudinal association between multilevel latent classes of chronic disease risk behaviours and body mass index in adolescents

INTRODUCTION

Few studies have assessed the relationship between chronic disease risk behaviours and body mass index (BMI) in a longitudinal, sex/gender-specific context. This study used gender-specific analyses to assess the extent to which chronic disease risk behaviour latent classes are associated with BMI and weight status at follow-up.

METHODS

Longitudinal data from 4510 students in Grades 9 to 12, tracked from 2013- 2015, who participated in the COMPASS study were used to assess gender differences in the lagged association between previously determined latent classes (of physical activity and substance use) with BMI using multilevel mixed-effects models. Our multilevel regression models assessed the association between two latent classes, active experimenters and inactive non-using youth, with BMI when stratified by gender.

RESULTS

Male inactive non-substance-using youth were associated with a 0.29 higher continuous BMI (95% CI: 0.057, 0.53) and odds of overweight/obesity increased by 72% (OR = 1.72, 95% CI: 1.2, 2.4) for binary BMI at follow-up relative to active youth who experiment with substance use. No significant associations were detected in females.

CONCLUSION

Over time, physical activity has a protective role on BMI in male youth. Both substance use and physical inactivity should be addressed in obesity prevention efforts. Gender stratification in analyses is also important since females and males have different contributing factors to increases in BMI.

Healthy or Unhealthy? The Cocktail of Health-Related Behavior Profiles in Spanish Adolescents

The aim of this study was to identify the prevalence and clustering of health-related behaviors in Spanish adolescents and to examine their association with sex, body mass index (BMI), different types of sedentary screen time, and adherence to 24-hour movement guidelines. A final sample of 173 students (M = 12.99 ± 0.51) participated in this study. Cluster analysis was conducted based on five health-related behaviors: PA and sedentary time derived from accelerometers, as well as healthy diet, sedentary screen time, and sleep duration derived from self-reported scales. Recommendations for 24-hour movement guidelines (i.e., physical activity (PA), screen time, and sleep duration) were analyzed both independently and combined. A total of 8.9% of the sample did not meet any of the guidelines, whereas 72.3%, 17.3%, and 1.7% of the sample met 1, 2, or all 3 guidelines, respectively. Six distinct profiles were identified, most of them showing the co-occurrence of healthy- and unhealthy-related behaviors. Given that most of the adolescents failed to meet the combination of PA, screen time, and sleep duration guidelines, these findings suggest the necessity to implement school-based interventions that target multiple health behaviors, especially because (un)healthy behaviors do not always cluster in the same direction.

Activity-related behavior typologies in youth: a systematic review

BACKGROUND

Clusters of adolescents differentiated by patterns of physical activity and sedentary behavior (activity-related typologies) are common. Understanding both the characteristics of adolescents and modifiable correlates of these typologies, can help to develop interventions for those most at risk. This systematic review aimed to synthesize the socio-demographic characteristics and modifiable correlates of activity-related behavioral typologies among adolescents.

METHODS

A systematic search of seven electronic databases was conducted to identify quantitative studies using person-oriented statistical approaches to identify activity-related behavioral typologies among 12-18 year-olds. This systematic review was registered in Prospero (registration number: CRD42016046879).

RESULTS

Thirty-six studies met the inclusion criteria and were classified according to three sub-themes based on behaviors included in the typologies (1. physical activity and sedentary behavior only; 2. physical activity, sedentary behavior and risk-related behaviors; 3. physical activity, sedentary behavior and diet). Studies were mostly cross-sectional and relied on self-report measures. Methods were considerably heterogeneous, however results revealed some consistency in typologies within specific groups. For example, typologies characterized by unhealthy behavior patterns (e.g., characterized by physical inactivity, high sedentary behavior and poor diet or high risk-related behaviors) comprised more older adolescents. With the exception of socio-demographics (age, sex, body mass index and socio-economic status), very few correlates have been studied to date (mostly school-related behavioral factors and intrapersonal influences), with evidence largely from typologies comprised of physical activity, sedentary behavior and diet.

CONCLUSIONS

More research is needed to assess a range of modifiable correlates associated with activity-related behavior typologies among adolescents. This will allow for more targeted interventions, to achieve long-lasting, positive behavior change in adolescent populations.

Physical Activity, Screen Time, and Dietary Intake in Families: A Cluster-Analysis With Mother-Father-Child Triads

Background: The co-occurrence of multiple health behaviors such as physical activity, diet, and sedentary behavior affects individuals' health. Co-occurence of different health behaviors has been shown in a large number of studies. This study extended this perspective by addressing the co-occurrence of multiple health behaviors in multiple persons. The objective was to examine familial health behavioral patterns by (1) identifying clusters of families with similar behavior patterns and (2) characterizing the clusters by analyzing their correlates.

Methods: Cross-sectional data were collected from 198 families (mother, father, and child). Mothers, fathers, and children completed questionnaires assessing health related behaviors (physical activity, consumption of “healthy” and “unhealthy” foods, and screen time), the perception of Family Health Climate (regarding physical activity and nutrition) and demographics. Twelve variables (four health behaviors of three family members) were included in a cluster analysis conducted with Ward's Method and K-means analysis. Chi-square tests and analyses of variance were performed to characterize the family clusters regarding their demographics and their perception of Family Health Climate.

Results: Three clusters of families with specific behavioral patterns were identified: “healthy behavior families” with levels of physical activity and consumption of healthful foods above average and levels of media use and consumption of sweets below average; “unhealthy behavior families” with low levels of consumption of healthful foods and high levels of screen time; “divergent behavior families” with unhealthier behavioral patterns in parents and healthier screen time and eating behaviors combined with low physical activity levels in children. Family Health Climate differed between family clusters with most positive ratings in “healthy behavior families” and least positive ratings in “unhealthy behavior families.” “Divergent behavior families” rated the nutrition climate nearly as high as “healthy behavior families” while they rated the physical activity climate nearly as low as the “unhealthy behavior families.”

Conclusions: The study shows that co-occurrence of multiple health behaviors occurs on the family level. Therefore, focusing the family as a whole instead of individuals and targeting aspects related to the Family Health Climate in interventions could result in benefits for both children and adults and enhance effectivity of intervention programs.

Profiles of Physical Fitness Risk Behaviours in School Adolescents from the ASSO Project: A Latent Class Analysis

The aim of the present investigation was to describe profiles of adolescents’ fitness level, identify latent classes of fitness-related risk behaviours, and describe their sociodemographic and environmental predictors. In total, 883 adolescents (16.4 ± 1.4 years; 167.3 ± 10.4 cm; 62.8 ± 13.5 kg; 62.2% males) were assessed for personal and lifestyle information and for physical fitness components. Eleven possible fitness determinants and seven predictors were included. Latent class analysis (LCA) was used to determine fitness-related risk behaviours. Logistic regressions predicted class membership and assessed associations with fitness levels and fitness components. Five latent classes were recognised: 1—virtuous, 30.7% of respondents; 2—low physical activity/sport, 18.8%; 3—incorrect alcohol/food habits, 25.8%; 4—health risk/overweight, 15.9%; 5—malaise/diseases, 8.8%. Sex, age, parents’ overweightness/obesity and education, and school type predicted most classes significantly. Compared to class 1, class 2 had higher odds of having all poor fitness components except upper body maximal strength; class 4 had higher risk of low muscular endurance; and class 5 was likely to have lower maximal strength, muscular endurance, and speed/agility. Educating adolescents to reach a sufficient practice of PA/sport could help decreasing the risk of low health-related fitness more than discouraging them from using alcohol, addressing proper food behaviours and habits, and helping them understand their psychophysical malaise symptoms.

Behavioural patterns only predict concurrent BMI status and not BMI trajectories in a sample of youth in Ontario, Canada

Background

Youth are engaging in multiple risky behaviours, increasing their risk of overweight, obesity, and related chronic diseases. The objective of this study was to examine the effect of engaging in unique clusters of unhealthy behaviours on youths’ body mass index (BMI) trajectories.

Methods

This study used a linked-longitudinal sample of Grades 9 and 10 students (13 to 17 years of age) participating in the COMPASS host study. Students reported obesity-related and other risky behaviours at baseline and height and weight (to derive BMI) at baseline (2012/2013) and annually for 2 years post-baseline (2013/14 and 2014/15). Students were grouped into behavioural clusters based on response probabilities. Linear mixed effects models, using BMI as a continuous outcome measure, were used to examine the effect of engaging in clusters of risky behaviours on BMI trajectories.

Results

There were significant differences in BMI of the four behavioural clusters at baseline that remained consistent over time. Higher BMI values were found among youth classified at baseline to be Typical High School Athletes (β = 0.232 kg/m², [confidence interval (CI): 0.03–0.50]), Inactive High Screen-User (β = 0.348 kg/m², CI: 0.11–0.59) and Moderately Active Substance Users (β = 0.759 kg/m², CI: 0.36–1.15) compared to students classified as Health Conscious. Despite these baseline differences, BMI appeared to increase across all behavioural clusters annually by the same amount (β = 0.6097 kg/m², (CI) = 0.57–0.64).

Conclusions

Although annual increases in BMI did not differ by behavioural clusters, membership in a particular behavioural cluster was associated with baseline BMI, and these differences remained consistent over time. Results indicate that intervening and modifying unhealthy behaviours earlier might have a greater impact than during adolescence. Health promotion strategies targeting the highest risk youth as they enter secondary school might be promising means to prevent or delay the onset of obesity.

Meeting new Canadian 24-Hour Movement Guidelines for the Early Years and associations with adiposity among toddlers living in Edmonton, Canada

BACKGROUND

Canada has recently released guidelines that include toddler-specific recommendations for physical activity, screen-based sedentary behaviour, and sleep. This study examined the proportions of toddlers meeting the new Canadian 24-Hour Movement Guidelines for the Early Years (0-4 years) and associations with body mass index (BMI) z-scores in a sample from Edmonton, Canada.

METHODS

Participants included 151 toddlers (aged 19.0 ± 1.9 months) for whom there was complete objectively measured physical activity data from the Parents' Role in Establishing healthy Physical activity and Sedentary behaviour habits (PREPS) project. Toddlers' physical activity was measured using ActiGraph wGT3X-BT monitors. Toddlers' screen time and sleep were measured using the PREPS questionnaire. Toddlers' height and weight were objectively measured by public health nurses and BMI z-scores were calculated using World Health Organization growth standards. Meeting the overall 24-Hour Movement Guidelines was defined as: ≥180 min/day of total physical activity, including ≥1 min/day of moderate- to vigorous-intensity physical activity; no screen time per day (for those aged 12-23 months) or ≤1 h/day of screen time per day (ages 24-35 months); and 11-14 h of sleep per 24-h period. Frequency analyses and linear regression models were conducted.

RESULTS

Only 11.9% of toddlers met the overall 24-Hour Movement Guidelines, but this finding was largely driven by screen time. The majority of toddlers met the individual physical activity (99.3%) and sleep (82.1%) recommendations, while only 15.2% of toddlers met the screen time recommendation. No associations were observed between meeting specific and general combinations of recommendations within the guidelines and BMI z-scores.

CONCLUSIONS

Most toddlers in this sample were meeting physical activity and sleep recommendations but were engaging in more screen time than recommended. Consequently, only a small proportion of toddlers met the overall guidelines. Based on the findings of this study, identifying modifiable correlates of screen time to inform appropriate strategies to reduce screen time appears key for increasing the proportion of toddlers meeting the 24-Hour Movement Guidelines for the Early Years. Future research should examine the associations between meeting the new guidelines and other health indicators. Furthermore, future high-quality studies examining dose-response relationships between movement behaviours and health indicators are needed to inform guideline updates.

Systematic review of the relationships between combinations of movement behaviours and health indicators in the early years (0-4 years)

BACKGROUND

A recent review highlighted important relationships between combinations of movement behaviours (i.e., sleep, sedentary behaviour, and physical activity) and health indicators among school-aged children and youth (aged 5-17 years). It is unclear whether similar relationships exist in younger children. Therefore, this review sought to examine the relationships between combinations of movement behaviours and health indicators in the early years (1.00 month to 4.99 years).

METHODS

Medline, EMBASE, PsycINFO, and SportDiscus were searched for relevant studies up to November 2016, with no date or study design limits. Included studies met the a priori-determined population (apparently healthy children aged 1.00 month to 4.99 years), intervention (combination of ≥2 movement behaviours [i.e., sleep and sedentary behaviour; sleep and physical activity; sedentary behaviour and physical activity; and sleep, sedentary behaviour, and physical activity]), comparator (various levels and combinations of movement behaviours), and health outcome/indicator (Critical: adiposity, motor development, psychosocial health/emotional regulation, cognitive development, fitness, and growth; Important: bone and skeletal health, cardiometabolic health, and risks). For each health indicator, quality of evidence was assessed by study design using the Grading of Recommendations Assessment, Development, and Evaluation (GRADE) framework.

RESULTS

Ten articles (n = 7436 participants; n = 5 countries) were included. Across observational and experimental study designs, the most ideal combinations of sedentary behaviour and physical activity were: favourably associated with motor development and fitness among preschool-aged children (3.00 to 4.99 years); both favourably and not associated with adiposity among toddlers (1.10 to 2.99 years) and preschool-aged children; and not associated with growth among toddlers and preschool-aged children. The most ideal combinations of sleep and sedentary behaviour were favourably associated with adiposity among infants (1.00 month to 1.00 years) and toddlers. Quality of evidence ranged from "very low" to "moderate".

CONCLUSIONS

The most ideal combinations of movement behaviours (e.g., high sleep, low sedentary behaviour, high physical activity) may be important for optimal health in the early years. Findings can help inform movement behaviour guidelines for the early years. Given the limited evidence, future research is needed to determine the ideal distribution of daily movement behaviours for optimal health throughout the early years.

Unequal Distribution of Overweight Adolescents in Immigrant-Rich Areas: Analysis of Disparities among Public and Private School Students in Shanghai, China

Accelerated urbanization and rising immigration to the big cities in China has resulted in education policies that produce disparate treatment of immigrant and non-immigrant students. The two types of students frequently wind up in different types of junior high schools. However, there is little research on whether disparities exist between students in public and private schools with regard to overweight. This study aims to address this gap through a comparison of the overweight status of junior high school students in public and private schools in Shanghai and explore the possible reasons for the observed differences. Students from two public and two private junior high schools were measured. In order to determine what factors might shape overweight among adolescents. Logistic regression analysis was used to assess associations between overweight and personal characteristics, birth-related factors, levels of physical activity, diet, family socioeconomic status and school environment. Students in private schools proved more likely to be overweight (15.20%, p < 0.05) than public school students (10.18%). Similarly, gender, breastfeeding, parental care and number of classes excluding physical education per day were found to be significant factors. However, private school students were also influenced by gestational age (yes/no: OR = 4.50, p < 0.001), frequency of snacks (sometimes/often: OR = 0.53, p < 0.01) and family income (¥6001-12,000/below ¥6000: OR = 3.27, p < 0.05). Time for lunch was the sole risk factor for public school students in the study (p < 0.05). To reduce the unequal distribution of overweight students between the two types of schools, interventions that consider different multiple risk factors should be implemented.

Health associations with meeting new 24-hour movement guidelines for Canadian children and youth

The study objective was to examine whether meeting the new Canadian 24-hour movement guidelines was associated with health indicators in a representative sample of Canadian children and youth. Cross-sectional findings are based on 4157 (1239 fasting subsample) children and youth aged 6-17years from cycles 1-3 of the Canadian Health Measures Survey (CHMS). Sleep and screen time were subjectively measured while moderate- to vigorous-intensity physical activity (MVPA) was accelerometer-determined. Health indicators in the full sample (body mass index (BMI) z-scores, waist circumference, blood pressure, behavioral strengths and difficulties score (lower=better), and aerobic fitness) and fasting subsample (triglycerides, high-density lipoprotein (HDL)-cholesterol, C-reactive protein, and insulin) were measured. Meeting the overall guidelines was defined as: 9-11 hour/night (5-13years) or 8-10 hour/day (14-17years) of sleep, ≤2 hour/day of screen time, and ≥60 minute/day of MVPA. Compared to meeting all three recommendations, meeting none, one, and two recommendations were associated with a higher BMI z-score, waist circumference, and behavioral strengths and difficulties score and lower aerobic fitness in a gradient pattern (P_trend<0.05). Additionally, compared to meeting all three recommendations, meeting none and one recommendation were associated with higher systolic blood pressure and insulin (P_trend<0.05). Finally, compared to meeting all three recommendations, meeting no recommendations was associated with higher triglycerides and lower HDL-cholesterol (P_trend<0.05). Collectively, meeting more recommendations within the 24-hour movement guidelines was associated with better overall health. Since a small proportion (17%) of this representative sample was meeting the overall guidelines, efforts to promote adoption are needed.

Interactions between sleep, movement and other non-movement behaviours in the pathogenesis of childhood obesity

Research examining the health effects of physical activity, sedentary behaviour and sleep on different health outcomes has largely been conducted independently or in isolation of the other behaviours. However, the fact that time is finite (i.e. 24 h) suggests that the debate on whether or not the influence of a single behaviour is independent of another one is conceptually incorrect. Time spent in one behaviour should naturally depend on the composition of the rest of the day. Recent evidence using more appropriate analytical approaches to deal with this methodological issue shows that the combination of sleep, movement and non-movement behaviours matters and all components of the 24-h movement continuum should be targeted to enhance health and prevent childhood obesity. The objective of this review is to discuss research investigating how combinations of physical activity, sedentary behaviour and sleep are related to childhood obesity. Emerging statistical approaches (e.g. compositional data analysis) that can provide a good understanding of the best 'cocktail' of behaviours associated with lower adiposity and improved health are also discussed. Finally, future research directions are provided. Collectively, it becomes clearer that guidelines and public health interventions should target all movement behaviours synergistically to optimize health of children and youth around the world.

Clustering of risk-related modifiable behaviours and their association with overweight and obesity among a large sample of youth in the COMPASS study

BACKGROUND

Canadian youth exhibit a number of risky behaviours, some of which are associated with overweight and obesity. The purpose of this study was to examine the prevalence of 15 modifiable risk behaviours in a large sample of Canadian youth, to identify underlying subgroups based on patterns of health behaviours, and to examine the association between identified subgroups and overweight/obesity.

METHODS

Data from 18,587 grades 9-12 students in Year 1 (2012-13) of the COMPASS study and latent class analysis were used to identify patterns and clustering among 15 health behaviours (e.g., physical inactivity, sedentary behaviour, unhealthy eating, substance use). A logistic regression model examined the associations between these clusters and overweight/obesity status.

RESULTS

Four distinct classes were identified: traditional school athletes, inactive screenagers, health conscious, and moderately active substance users. Each behavioural cluster demonstrated a distinct pattern of behaviours, some with a greater number of risk factors than others. Traditional school athletes (odds ratio (OR) 1.15, 95% CI 1.03-1.29), inactive screenagers (OR 1.33; 1.19-1.48), and moderately active substance users (OR 1.27; 1.14-1.43) were all significantly more likely to be overweight/obese compared to the health conscious group.

CONCLUSIONS

Four distinct subpopulations of youth were identified based on their patterns of health and risk behaviours. The three clusters demonstrating poorer health behaviour were all at an increased risk of being overweight/obese compared to their somewhat healthier peers. Obesity-related public health interventions and health promotion efforts might be more effective if consideration is given to population segments with certain behavioural patterns, targeting subgroups at greatest risk of overweight or obesity.

Television food advertising to children in Slovenia: analyses using a large 12-month advertising dataset

OBJECTIVES

The marketing of energy-dense foods is recognised as a probable causal factor in children's overweight and obesity. To stimulate policymakers to start using nutrient profiling to restrict food marketing, a harmonised model was recently proposed by the WHO. Our objective is to evaluate the television advertising of foods in Slovenia using the above-mentioned model.

METHODS

An analysis is performed using a representative dataset of 93,902 food-related advertisements broadcast in Slovenia in year 2013. The advertisements are linked to specific foods, which are then subject to categorisation according to the WHO and UK nutrient profile model.

RESULTS

Advertising of chocolate and confectionery represented 37 % of food-related advertising in all viewing times, and 77 % in children's (4-9 years) viewing hours. During these hours, 96 % of the food advertisements did not pass the criteria for permitted advertising according to the WHO profile model.

CONCLUSIONS

Evidence from Slovenia shows that, in the absence of efficient regulatory marketing restrictions, television advertising of food to children is almost exclusively linked to energy-dense foods. Minor modifications of the proposed WHO nutrient profile model are suggested.

A quasi-experimental examination of how school-based physical activity changes impact secondary school student moderate- to vigorous- intensity physical activity over time in the COMPASS study

Background

Adolescence is characterized by low moderate- to vigorous- intensity physical activity (MVPA) levels. Targeting the school setting can increase MVPA among a large proportion of adolescents. However, school-based physical activity interventions for adolescents remain largely ineffective. Therefore, the purpose of this study was to examine how naturally-occurring changes to school physical activity policy, recreational programming, public health resources, and the physical environment, impact adolescent MVPA over a 1-year period.

Methods

Quasi-experimental longitudinal data from 18,777 grade 9–12 students (mean age = 15.1 ± 0.02 years), and 86 principals from 86 schools, participating in year 2 (2013–2014) and year 3 (2014–2015) of the COMPASS study (Ontario and Alberta, Canada) was used. Total MVPA over the previous week was self-reported at both time points using the COMPASS Student Questionnaire and average daily MVPA was calculated. Changes to physical activity policies, recreational programming, public health resources, and the physical environment were self-reported by school principals. Changes to the number and condition of physical activity facilities were objectively measured during school audits using the COMPASS School Environment Application. Multi-level modeling was used to examine change in student MVPA between schools that made changes and schools that did not. Models were adjusted for several student and school level confounders.

Results

Over the 1-year period, 61 of 86 schools made physical activity related changes. Of these, 9 significantly changed student MVPA. However, only 4 of 9 schools’ changes increased student MVPA, including opening the fitness centre at lunch (β = 17.2, 95 % CI: 2.6–31.7), starting an outdoor club (β = 17.8, 95 % CI:7.4–28.1), adding a bike rack (β–14.9, 95 % CI:0.7–29.1), and adding weightlifting and run/walk clubs, archery, figure skating, increased access to the sports field, and improved condition of the outdoor basketball court (β = 15.5, 95 % CI: 5.2–25.7).

Conclusions

Changes such as adding or increasing access to facilities, and adding multiple recreational programs, seemed to be effective for increasing student MVPA over the 1-year period. However, given the specificity of results, a one-size fits all approach may not be effective for increasing MVPA. Instead, school principals need to consider the resources within and surrounding their school, and the interests of the students.

National youth sedentary behavior and physical activity daily patterns using latent class analysis applied to accelerometry

Background

Applying latent class analysis (LCA) to accelerometry can help elucidated underlying patterns. This study described the patterns of accelerometer-determined sedentary behavior and physical activity among youth by applying LCA to a nationally representative United States (US) sample.

Methods

Using 2003–2006 National Health and Nutrition Examination Survey data, 3998 youths 6–17 years wore an ActiGraph 7164 accelerometer for one week, providing > =3 days of wear for > =8 h/day from 6:00 am-midnight. Cutpoints defined sedentary behavior (<100 counts/minute), light activity (100–2295 counts/minute), moderate to vigorous physical activity (MVPA; > = 2296 counts/minute), and vigorous activity (> = 4012 counts/minute). To account for wear time differences, outcomes were expressed as percent of day in a given intensity. LCA was used to classify daily (Monday through Sunday) patterns of average counts/minute, sedentary behavior, light activity, MVPA, and vigorous activity separately. The latent classes were explored overall and by age (6–11, 12–14, 15–17 years), gender, and whether or not youth attended school during measurement. Estimates were weighted to account for the sampling frame.

Results

For average counts/minute/day, four classes emerged from least to most active: 40.9 % of population (mean 323.5 counts/minute/day), 40.3 % (559.6 counts/minute/day), 16.5 % (810.0 counts/minute/day), and 2.3 % (1132.9 counts/minute/day). For percent of sedentary behavior, four classes emerged: 13.5 % of population (mean 544.6 min/day), 30.1 % (455.1 min/day), 38.5 % (357.7 min/day), and 18.0 % (259.2 min/day). For percent of light activity, four classes emerged: 12.3 % of population (mean 222.6 min/day), 29.3 % (301.7 min/day), 41.8 % (384.0 min/day), and 16.6 % (455.5 min/day). For percent of MVPA, four classes emerged: 59.9 % of population (mean 25.0 min/day), 33.3 % (60.9 min/day), 3.1 % (89.0 min/day), and 3.6 % (109.3 min/day). For percent of vigorous activity, three classes emerged: 76.8 % of population (mean 7.1 min/day), 18.5 % (23.9 min/day), and 4.7 % (47.4 min/day). Classes were developed by age, gender, and school attendance since some patterns differed when stratifying by these factors.

Conclusion

The models supported patterns for average intensity, sedentary behavior, light activity, MVPA, and vigorous activity. These latent class derived patterns can be used in other youth studies to explore correlates or outcomes and to target sedentary behavior or physical activity interventions.

Electronic supplementary material

The online version of this article (doi:10.1186/s12966-016-0382-x) contains supplementary material, which is available to authorized users.