Kt Prkr ,Ann Timprio ,Jo Slmon ,Krn Villnuv ,Hln Brown ,Irn Estn-Cornjo ,Vronic Cns-Sˊnchz ,Josˊ Cstro-Pi～nro ,Dvid Sˊnchz-Oliv,Oscr L.Vi

a School of Exercise and Nutrition Sciences,Institute for Physical Activity and Nutrition(IPAN),Deakin University,Geelong,VIC 3220,Australia

b Centre for Urban Research,School of Global Urban and Social Studies,RMIT University,Melbourne,VIC 3000,Australia

c Center for Cognitive and Brain Health,Department of Psychology,Northeastern University,Boston,MA 02115,USA

d PROmoting FITness and Health through physical activity(PROFITH)research group,Department of Physical Education and Sports,Faculty of Sport Sciences,University of Granada,Granada 18010,Spain

e Department of Physical Education,Sports and Human Movement,Autonomous University of Madrid,Madrid 28049,Spain

f Research Centre in Physical Activity,Health and Leisure(CIAFEL),Faculty of Sport,University of Porto,Porto 4099-002,Portugal

g Department of Physical Education,Faculty of Education Sciences,University of Cˊadiz,Puerto Real 11003,Spain

h Biomedical Research and Innovation Institute of Cˊadiz(INiBICA),Cˊadiz 11003,Spain

Abstract Background:Children and adolescents can be distinguished by different typologies(clusters)of physical activity and sedentary behavior.How physical activity and sedentary behaviors change over time within different typologies is not known.This study examined longitudinal changes in physical activity and sedentary time among children and adolescents with different baseline typologies of activity-related behavior.Methods:In this longitudinal study(3 annual time points)of children(n=600,age=9.2±0.4 years(mean±SD),50.3%girls)and adolescents(n=1037,age=13.6 ± 1.7 years,48.4% girls),participants were recruited in Spain in 2011－2012.Latent class analyses identif ied typologies based on self-reported screen,educational,social and relaxing sedentary behaviors,active travel,muscle strengthening activity,and sport at baseline.Within each typology,linear mixed growth models explored longitudinal changes in accelerometer-derived moderate-to-vigorous physical activity and sedentary time,as well as time by class interactions.Results:Three typologies were identif ied among children(“social screenies”,12.8%;“exercisers”,61.5%;and“non-sporty active commuters”,25.7%)and among adolescents(“active screenies”,43.5%;“active academics”,35.0%;and“non-sporty active commuters”,21.5%)at baseline.Sedentary time increased within each typology among children and adolescents,with no signif icant differences between typologies.No changes in physical activity were found in any typology among children.In adolescents,physical activity declined within all typologies,with“non-sporty active commuters”declining signif icantly more than“active screenies”over 3 years.Conclusion:These results support the need for intervention to promote physical activity and prevent increases in sedentary time during childhood and adolescence.Adolescents characterized as“non-sporty active commuters”may require specif ic interventions to maintain their physical activity over time.

Keywords:Behavior change;Physical activity;Sedentary behavior;Typologies;Youth

1.Introduction

Lifestyle-related chronic health conditions(e.g.,overweight and obesity and cardiovascular disease markers) are becoming more prevalent in children and adolescents,attributable in part to a lack of regular physical activity and excessive sedentary time.1Like other youth around the world,2national data suggest that youth in Spain have low levels of adherence to physical activity(21%－40%) and sedentary behavior guidelines (21%－40%),3which recommend that children and adolescents accumulate at least 60 min of moderate-to-vigorous physical activity (MVPA)daily and spend no more than 2 h/day in screen time.4Spanish data from 2016 show that physical activity participation rates among females are particularly low,with as little as 9%of female adolescents meeting both the physical activity and sedentary behavior guidelines.3Furthermore,there is consistent evidence for age-related declines in the proportion of youth in Spain achieving both the physical activity and sedentary behavior guidelines.3However,these results are based on overall averages and fail to consider potential differences between subgroups.

As identif ied within a recent systematic review,a growing body of research has focused on identifying distinct groups of individuals based on engagement in different types of physical activity and sedentary behavior.5Thirteen studies have identif ied typologies based purely on physical activities and sedentary behaviors,with results suggesting that individuals who undertake more physical activities tend to be younger in age.5To date,studies assessing different combinations(typologies)of physical activity and sedentary behavior have primarily done so cross-sectionally.5Results from these studies can be used to tailor and target interventions to different groups.However,while it has been shown repeatedly that physical activity generally tends to decline and sedentary time tends to increase during childhood and adolescence,6it is unknown how these behaviors change among children and adolescents with diverse baseline activity-related typologies.Because both physical activity and sedentary time could have unique inf luences on health,7－11it is important to look at how these behaviors change concurrently over time.Identifying whether and how these behaviors change over time based on baseline activity typologies may help effectively target interventions to prevent declines in physical activity and increases in sedentary time.To date,no studies have examined the associations between different activity-related behavioral typologies and later behavioral outcomes,such as physical activity and sedentary time.The aim of the current study was to explore changes in physical activity and sedentary time over 3 years according to baseline activity-related typologies.

2.Methods

This study used data from the UP&DOWN study,12a longitudinal study of healthy children(6－11 years of age)and adolescents (11－18 years of age) in Spain.Baseline data collection occurred between September 2011 and June 2012.Children＜8 years old were excluded because they did not complete selfreported questionnaires due to their age (limited ability to provide reliable and valid information).The study involved 2 annual follow-ups (3 time points,including baseline).Ethical approval for the UP&DOWN study was obtained from the Bioethics Committee of the National Research Council (Madrid,Spain),the Ethics Committee of the Hospital Puerta de Hierro(Madrid,Spain),and the Committee for Research Involving Human Subjects at the University of Cˊadiz(Cˊadiz,Spain).Clustering of lifestyle behaviors have previously been identif ied in this dataset,with cross-sectional associations with physical fitness10and prospective associations with fatness.11The present study examined activity-related typologies(excluding diet and sleep).

2.1.Sample

Participants were recruited from primary and secondary schools within the Cˊadiz and Madrid regions of Spain,respectively.Information about the study and an invitation to participate were sent to headmasters or physical education teachers at each school,of which 23 primary schools (24 invited,96% response rate) and 22 secondary schools (46 invited,48%response rate)provided consent to participate.A flyer describing the study was provided to all parents of students in the 1st and 4th grades(primary school)and in the 7th and 10th grades (secondary school).The flyer provided inclusion criteria (no physical disability or health problems that might limit levels of physical activity) and an invitation to parents to attend an information evening at their child’s school.Following the information evening,written parental informed consent and child written assent was obtained for 1188 children and 1038 adolescents.Response rates for this component of the study were not calculated because the number of parents present at the information evenings was not recorded.Further details regarding recruitment have been published elsewhere.12

2.2.Measures

2.2.1.Self-reported physical activity and sedentary behaviors at baseline

Children aged 8－11 years and adolescents aged 11－18 years completed self-report questionnaires,indicating their age,sex,and participation in a range of activity-related behaviors.Participants were asked to record how many days during the last 7 days they exercised to strengthen their muscles.This was re-coded as 1 (≥2 times/week) vs.0(＜2 times/week) to provide an indication of whether participants regularly engaged in muscle-strengthening activities suff icient for strength benef its.13,14Participation in organized sport was determined from the Finnish Physical Activity Index.15Participants were asked to indicate whether they were currently involved in sport at the local,regional,national,or international level (coded as 1) or not currently participating in any sport(coded as 0).Active travel to and from school was determined based on a question asking participants to choose their usual mode of transport to and from school from a list of options.16This item was dichotomized based on reported walking or cycling to and from school as the usual mode(coded as 1)vs.other modes(coded as 0).

The Youth Leisure-time Sedentary Behaviour Questionnaire was used to indicate time spent in 12 different sedentary behaviors across both weekdays and weekend days in the week prior to completing the survey.16Participants were asked to recall the average time spent in each behavior during the previous week,reporting weekdays,and weekend days,separately.Response options were 0 min,30 min,1 h,2 h,3 h,4 h,and ≥5 h.The average time per day spent on each behavior was calculated using the following method:((weekday-time × 5)+(weekend-time × 2))/7.These values were adjusted to account for the participants’ sleep and school time to give an indication of their leisure-time sedentary behaviors.The adjustments followed a protocol that has been detailed previously.16Overall screen time was categorized as ≥2 h/day (coded as 1) vs.＜2 h/day(coded as 0),which was consistent with the guidelines.4Time spent in “educational sedentary behaviors” (homework/study with a computer and homework/study without a computer),“social sedentary behaviors” (sitting and talking with family or friends,listening to music,talking on the telephone,and sending messages),and “relaxation sedentary behaviors” (reading for fun,sitting to rest,and cognitive hobbies) were each dichotomized as ≥1 h/day (coded as 1) and ＜1 h/day (coded as 0),based on previous research protocols.17,18

2.2.2.Objectively assessed physical activity and sedentary time at baseline,Year 2,and Year 3

Physical activity and sedentary time were also assessed objectively using reliable ActiGraph accelerometer models GT1M,GT3X,and GT3X+(Actigraph TM LLC.,Fort Walton Beach,FL,USA) at each time point.The GT1M accelerometers collected data at 2-s epochs,and the GT3X and GT3X+collected data at 30 Hz.However,all data were subsequently transformed into a 10-s epoch prior to analysis to increase sensitivity to sporadic movement behaviors typical of children and adolescents.19Furthermore,the use of 3 models did not imply any methodological problems because estimates across the 3 models show strong agreement among children and adolescents.20,21Participants were asked to wear the device on their hip during all waking hours(with the exception of water-based activities)for 7 consecutive days,which is consistent with established procedures.22Non-wear time was def ined as 60 min of consecutive 0 count,allowing for up to 2 min of ＜100 counts per minute(cpm),with a small window of 30 min of consecutive 0 count for detection of artifactual movements based on the algorithm proposed by Choi et al.23Inclusion criterion was based on a minimum 3 days of recording with at least 10 h/day.19Average duration per day of sedentary time and MVPA were determined using the cutpoint values of ＜100 cpm19and ≥2000 cpm,24respectively.The data-processing procedures used to estimate sedentary time and physical activity are consistent with previous studies among children and adolescents.25,26

2.3.Data analyses

Analyses were stratif ied by age (children and adolescents).Latent class analysis(LCA)was conducted in MPlus(Version 8.0;Mˊuthen&Mˊuthen,Los Angeles,CA,USA)27to generate baseline activity prof iles (typologies) based on 7 self-reported activity-related behaviors described above(screen time,educational sedentary behaviors,social sedentary behaviors,relaxing sedentary behaviors,active travel to and from school,muscle strengthening activities,and sport).Although valid data were not obtained from all participants for each of these self-report variables(n=10－24 missing on muscle strengthening and sport variables),LCA conducted in MPlus handles missing data using maximum likelihood estimation.Therefore,the LCA was based on the full sample.After excluding children aged between 6 and 8 years,the final baseline analytical sample included 600 children and 1037 adolescents.Five LCA models were conducted with class sizes of 1－5,and the statistical indicators used to identify the optimal class solution were Akaike information criterion (lower=better model fit),28Bayesian information criterion (lower=better model fit),29entropy (higher=greater precision of model fit),30and Lo-Mendel Rubin(p ＜0.05 indicates n－1 class is better than n class model).31Class sizes within each solution were also compared to ensure they were suff icient for further analyses.Once the optimal class solution was determined,linear mixed growth models for continuous repeated measures with random intercept were performed using STATA (Version 15.1;Stata Corp.,College Station,TX,USA) to determine change in MVPA and sedentary time over 3 years within each baseline typology,as well as time by class interactions.The statistical approach used to identify longitudinal change in MVPA and sedentary time was chosen because it has the ability to(a)adjust for missing data points,(b) model nonlinear,individual characteristics between participants,and (c) account for non-independence of each participant’s residuals.32Signif icance was set as p ＜0.05(two-tailed)for all tests.

3.Results

3.1.Participants

The mean age of child participants was 9.2 ± 0.4 years(mean±SD),and 50.3%were girls.The mean age of adolescent participants was 13.6±1.7 years,with 48.4%girls.

3.2.Baseline typologies of activity-related behaviors

Three typologies of activity-related behaviors were identif ied for children and for adolescents.This was based on the best model fit indices across each of the LCA models explored(Supplementary Table 1).The item－response probability plots for these 3-class solutions are shown in Fig.1,and the distribution of activity-related behaviors within each typology are shown in Table 1.

Among children,the 3 typologies can be described as “social screenies” (Class 1;n=77,12.8%),“exercisers” (Class 2;n=369,61.5%),and “non-sporty active commuters” (Class 3;n=154,25.7%).Children in the“social screenies”typology selfreported the highest amount of all sedentary behaviors,with all participants reporting ≥2 h/day of screen time and ＞1 h/day of educational,social,and relaxing sedentary time.Compared to the other 2 typologies,the smallest proportion of these children reported participation in sport and regular active travel to and from school.Children classif ied within the “exercisers” typology all self-reported meeting the muscle strengthening guidelines of≥2 sessions/week,and the highest proportion of these children engaged in organized sport.Sedentary time and active travel were similar to the“non-sporty active commuters” typology(Class 3).Children classif ied within the “non-sporty active commuters”typology were similar to“exercisers”on all activity-related behaviors,with the exception of muscle strengthening exercise and organized sport.None of these children achieved muscle strengthening exercise guidelines,and less than one-quarter reported any participation in sport.Overall,objectively measured MVPA and sedentary time did not differentiate the 3 typologies(Fig.1 and Table 1).

Fig.1.Typologies item-response probability plot for(A)children and(B)adolescents.

The 3 adolescent typologies can be described as “active screenies” (Class 1;n=451,43.5%),“active academics” (Class 2;n=363,35.0%),and“non-sporty active commuters”(Class 3;n=223,21.5%).The male-dominated “active screenies”typology had the highest proportion of adolescents who selfreported ≥2 h/day of screen time,regular active transport to and from school and muscle-strengthening activities,and the lowest proportion engaging in ≥1 h/day of sedentary time for relaxation.They also had the highest MVPA across the 3 typologies.The “active academics” typology comprised the youngest adolescents with almost all reported spending ≥1 h/day in educational sedentary time and the lowest proportion reported engaging in ≥2 h/day in screen time and ≥1 h/day in social sedentary time compared to the other 2 typologies.The“non-sporty active commuters” typology was composed mostly of females,less than 20% of those classif ied in this typology reported≥2 sessions/week of muscle strengthening exercise,and none reported engaging in sport.The majority of adolescents in this typology also reported excessive screen time and ≥1 h/day of educational and social sedentary.This typology had the highest proportion of adolescents engaging in ≥1 h/day of relaxing sedentary time compared to the other 2 typologies,and overall engaged in signif icantly higher sedentary time compared to the“active academics”(Fig.1 and Table 1).

Table 1Characteristics and activity-related behavior participation of children’s and adolescents’typologies at baseline.

3.3.Change in physical activity and sedentary behavior

Results of the linear mixed growth models(Fig.2)revealed no signif icant differences in average minutes per day of MVPA over the 3 time points among children(p=0.13);however,each year was associated with an increase of 19.71 min/day of sedentary time (95% conf idence interval(95%CI):7.70－31.72,p=0.001).There were no signif icant differences in change in MVPA over time between the“exercisers” (p=0.23) or “non-sporty active commuters”(p=0.89) compared to the “social screenies” typology,nor were there any signif icant differences for sedentary time(“exercisers”,p=0.80;“non-sporty active commuters”,p=0.46) compared to the “social screenies” typology.There was no evidence of an interaction between class membershipand time for physical activity (p=0.20) or sedentary time(p=0.66),with a similar minimal magnitude of change in the same direction across each of the 3 typologies.

Fig.2.Activity-related typologies and changes (mean ± SD) in children’s (A) MVPA and (B) sedentary behavior.MVPA=moderate-to-vigorous physical activity;SED=sedentary time.

There was a signif icant change in MVPA for adolescents(Fig.3),with a 2.26-min (95%CI:－3.52 to－0.99,p ＜0.001)decrease per year.This trajectory differed between classes,with MVPA among the “non-sporty active commuters” typology declining signif icantly more than the “active screenies” (coeff icient=－12.94,95%CI:－18.18 to－7.71,p ＜0.001).No significant differences were evident between the “active academics”and“active screenies”(p=0.07).Additionally,as can be seen in Fig.3,there were no class by time interaction effects seen for MVPA among adolescents (p=0.56) across the 3 time points.Sedentary time signif icantly increased by 11.73 min with each year of the study(95%CI:5.47－17.99,p ＜0.001).However,no signif icant differences were seen between “active academics”(p=0.74) or “non-sporty active commuters” (p=0.43) compared to“active screenies”.There were also no signif icant interaction effects between class membership and time(p=0.69)for sedentary time among adolescents.

4.Discussion

Our study explored changes in physical activity and sedentary time of children and adolescents over 3 years dependent on baseline typologies of activity-related behaviors.Because the study is the first of its kind,it is diff icult to draw comparisons with other studies.Results revealed 3 independent,homogeneous typologies of children (“social screenies”,“exercisers”,and“non-sporty active commuters”)and adolescents(“active screenies”,“active academics”,and“non-sporty active commuters”)at baseline.Overall,for each age group and regardless of typology,sedentary time followed a similar increase across the 3 years.Sedentary time in this sample of youth tended to increase by 11－20 min/day with each consecutive year of the study.This sedentary time is less than the sedentary time found in a systematic review of 10 longitudinal studies,which reported that accelerometer-derived sedentary time tends to increase by approximately 30 min/day with each consecutive year in school-age children and adolescents from Western countries.33These differences may be due to variation in the follow-up period (1－10 years),baseline age (3.8－13.2 years),population group(no previous studies focused on youth from Spain),or differences in accelerometer data processing methods.33

Fig.3.Activity-related typologies and changes (mean ± SD) in adolescent’s (A) MVPA and (B) sedentary behavior.MVPA=moderate-to-vigorous physical activity;SED=sedentary time.

Among children,typologies were def ined by unique combinations of self-reported individual activity-related behaviors;however,there were no differences in overall MVPA or sedentary time between these groups at baseline.Furthermore,the magnitude of change in MVPA and in sedentary time was similar between the groups over the 3 years.In adolescents,however,declines in physical activity were signif icant among all typologies,with “non-sporty active commuters” declining signif icantly more than “active screenies” over the 3 years.Although not a direct comparison of methods used,these findings differ from those of Farooq et al.,34who identif ied 4 negative trajectories of MVPA over 8 years(baseline age=7 years)with no indication that the declines were greater during adolescence than childhood.In the current study sample,the differences in physical activity change seen between children (no change over time)and adolescents(signif icant decline)may be due to youth facing other additional pressures during adolescence,such as school examinations,employment,and increasing social interactions outside of school time compared to during childhood.35Further research is needed to identify these predictors of change.

The findings that the adolescent“non-sporty active commuters”typology were majority female suggests that female adolescents may be most in need of physical activity interventions.Specif ically,the consistency of the current results with previous literature5highlights the need for intervention targeting female adolescents engaging in high levels of sedentary behaviors and low physical activity participation.More research is needed to identify potential intervention strategies for this target group.Additionally,while no signif icant changes in overall MVPA were seen with time,we found that children identif ied as “social screenies” were the least likely to report regular active travel to and from school and sport engagement at baseline.Active travel to school has long been suggested as a way to increase daily physical activity in all youth.36This finding suggests that existing successful school initiatives aimed at increasing active travel (e.g.,Safe Routes to School,Walking School Bus,TravelSmart initiatives)37could be potential ways to help these children increase their physical activity.

Almost all children and adolescents in the “non-sporty active commuters” typologies self-reported no muscle strengthening exercise or sport engagement,combined with one-half to three-quarters indicating high levels of all sedentary behaviors (except social sedentary behaviors).This combination of unhealthy baseline behaviors and the changes in their physical activity and sedentary time over the 3 years suggests that these youth in particular should be of high priority to target in health promotion initiatives.More specif ically,given their lack of participation in organized sport and muscle strengthening activities,interventions could be tailored to include sport and muscle strengthening exercises.Future research should explore the individual,social,and environmental factors that predict the likelihood of youth engaging in such combinations of behavior combinations and changes over time to determine strategies that may be most appropriate for intervention.Given the difference in activity-related behavior typologies and physical activity changes over time between children and adolescents,it is possible that inf luencing factors may also differ between children and adolescents.

Few studies examining typologies of activity-related behaviors have used longitudinal study designs.While this study was unique in examining changes in physical activity and sedentary time among children and adolescents according to activity typologies,future studies should examine changes in behavioral typologies over time.Little is known about whether these typologies (patterns of sedentary behaviors and physical activities) remain stable over time or whether they are disrupted.In addition,the current study examined changes in physical activity and sedentary time separately using group means.However,it is possible that other trajectories of change were masked using this approach.Future research should consider using group-based trajectory analysis to identify different groups of individuals based on patterns of behavior change.

The strengths of this study include the use of a large cohort of children and adolescents,including a relatively even distribution of boys and girls,and the longitudinal study design.The subjective nature of the activity-related behavior variables used to determine the baseline typologies means that these variables were open to social-desirability and recall biases.However,objective measures of MVPA and sedentary time were used to examine changes in behavior over time.

5.Conclusion

This study was the first to examine longitudinal change in physical activity and sedentary time among children and adolescents with different baseline typologies of activity-related behavior.Findings revealed relatively similar baseline typologies between both children and adolescents.Sedentary time increased over time,irrespective of baseline typology,indicating the constant need to target a reduction in sedentary behaviors during childhood and adolescence.Physical activity declined among adolescents(but not children),with the majority female “non-sporty active commuters” declining signif icantly more than “active screenies” over the 2 years.These findings suggest that different physical activity interventions are needed targeting adolescents compared to children,as well as targeting adolescent females and sport engagement or muscle strengthening exercise specif ically.However,for tailored interventions to be developed,more research is needed to determine group-based trajectories of change in physical activity and sedentary time,as well as the individual,social,and environmental determinants associated with potential changes.

Acknowledgments

This work was supported by the National Plan for Research,Development and Innovation (RDi) Ministry of Science and Innovation (DEP 2010-21662-C04-00).DSO was awarded a“Juan de la Cierva” postdoctoral fellowship (FJCI-2015-25867)from the Spanish Ministry of Economy,Industry,and Competitiveness.IEC is supported by the Spanish Ministry of Economy and Competitiveness (RTI2018-095284-J-100) and the Spanish Ministry of Science and Innovation(RYC2019-027287-I).

Authors’contributions

KP contributed to the conceptualization of the focus of this paper,conducted all statistical analyses,drafted the manuscript,and prepared the manuscript for publication;AT,JS,KV,and HB contributed to the conceptualization of the focus of this paper,provided critical feedback on draft versions of the manuscript;IEC,VCS,JCP,DSO,and OLV contributed to the initiation of the UP&DOWN study,the conceptualization of the focus of this paper,provided critical feedback on draft versions of the manuscript.All authors have read and approved the final version of the manuscript,and agree with the order of presentation of the authors.

Competing interests

The authors declare that they have no competing interests.

Supplementary materials

Supplementary material associated with this article can be found in the online version at doi:10.1016/j.jshs.2020.02.004.