OBJECTIVES: The objective of this study was to identify typologies of activity-related behaviours during adolescence and to explore transitions between the identified typologies. Additionally, we aimed to identify demographic indicators associated with the transitions and typology membership. DESIGN: Prospective cohort study. SETTING: Czech Republic. PARTICIPANTS: Individuals involved in the Czech part of the European Longitudinal Study of Pregnancy and Childhood study, aged 11 to 18 years. The study involved over 563 individuals, of whom 380 provided complete data for the analysis. PRIMARY OUTCOME MEASURES: Time spent outdoors, participation in organised physical activity (PA) and sport activities, time spent watching television and using a personal computer, and total sleep duration at ages 11, 15 and 18 years. Typologies were identified using Latent Transition Analysis. RESULTS: Four typologies of activity-related behaviours were identified and labelled to reflect their behavioural profiles: (1) Actives (high outdoor time and organised PA and sport participation, low screen time and optimal sleep duration); (2) Active screeners (median outdoor time, high organised PA and sport participation, high screen time, and optimal sleep duration); (3) Poor sleepers (average outdoor time and organised PA and sport participation, low screen time and not meeting sleep guidelines) and (4) Averages (average duration of all behaviours and optimal sleep duration). A major shift in typology membership from 11 to 18 years was observed, with a decreasing proportion of individuals in typologies characterised by a high proportion of outdoor time and participation in organised PA and sport activities (ie, Actives; Active screeners). A high proportion of individuals also transitioned to the typology with poor sleeping habits (ie, Poor sleepers). Sex and maternal education were associated with the typology membership and transition probabilities (p<0.05). CONCLUSIONS: Targeting lifestyle interventions to those with specific lifestyle patterns in early adolescence may be beneficial for reducing the risk of poor sleep and promoting healthy lifestyle patterns later in life.

Deakin University School of Exercise and Nutrition Sciences Burwood Victoria Australia

Palacky University Olomouc Olomouc Czech Republic

RECETOX Masaryk University Brno Czech Republic

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Best O, Ban S. Adolescence: physical changes and neurological development. Br J Nurs. 2021;30:272–5. doi: 10.12968/bjon.2021.30.5.272. PubMed DOI

van Sluijs EMF, Ekelund U, Crochemore-Silva I, et al. Physical activity behaviours in adolescence: current evidence and opportunities for intervention. The Lancet. 2021;398:429–42. doi: 10.1016/S0140-6736(21)01259-9. PubMed DOI PMC

Leidy HJ, Gwin JA. Growing up strong: The importance of physical, mental, and emotional strength during childhood and adolescence with focus on dietary factors. Appl Physiol Nutr Metab. 2020;45:1071–80. doi: 10.1139/apnm-2020-0058. PubMed DOI

Voss M-L, Claeson M, Bremberg S, et al. The missing middle of childhood. Glob Health Action. 2023;16:2242196. doi: 10.1080/16549716.2023.2242196. PubMed DOI PMC

Telama R, Yang X, Viikari J, et al. Physical activity from childhood to adulthood: a 21-year tracking study. Am J Prev Med. 2005;28:267–73. doi: 10.1016/j.amepre.2004.12.003. PubMed DOI

Janssen X, Mann KD, Basterfield L, et al. Development of sedentary behavior across childhood and adolescence: longitudinal analysis of the Gateshead Millennium Study. Int J Behav Nutr Phys Act. 2016;13:88. doi: 10.1186/s12966-016-0413-7. PubMed DOI PMC

Matricciani L, Paquet C, Galland B, et al. Children’s sleep and health: A meta-review. Sleep Med Rev. 2019;46:136–50. doi: 10.1016/j.smrv.2019.04.011. PubMed DOI

Harding SK, Page AS, Falconer C, et al. Longitudinal changes in sedentary time and physical activity during adolescence. Int J Behav Nutr Phys Act. 2015;12:44. doi: 10.1186/s12966-015-0204-6. PubMed DOI PMC

Aira T, Vasankari T, Heinonen OJ, et al. Physical activity from adolescence to young adulthood: patterns of change, and their associations with activity domains and sedentary time. Int J Behav Nutr Phys Act. 2021;18:85. doi: 10.1186/s12966-021-01130-x. PubMed DOI PMC

Rubín L, Gába A, Pelclová J, et al. Changes in sedentary behavior patterns during the transition from childhood to adolescence and their association with adiposity: a prospective study based on compositional data analysis. Arch Public Health . 2022;80:1. doi: 10.1186/s13690-021-00755-5. PubMed DOI PMC

Rollo S, Antsygina O, Tremblay MS. The whole day matters: Understanding 24-hour movement guideline adherence and relationships with health indicators across the lifespan. J Sport Health Sci. 2020;9:493–510. doi: 10.1016/j.jshs.2020.07.004. PubMed DOI PMC

Twohig-Bennett C, Jones A. The health benefits of the great outdoors: A systematic review and meta-analysis of greenspace exposure and health outcomes. Environ Res. 2018;166:628–37. doi: 10.1016/j.envres.2018.06.030. PubMed DOI PMC

Stiglic N, Viner RM. Effects of screentime on the health and well-being of children and adolescents: a systematic review of reviews. BMJ Open. 2019;9:e023191. doi: 10.1136/bmjopen-2018-023191. PubMed DOI PMC

Parker KE, Salmon J, Costigan SA, et al. Activity-related behavior typologies in youth: a systematic review. Int J Behav Nutr Phys Act. 2019;16:44. doi: 10.1186/s12966-019-0804-7. PubMed DOI PMC

Dakin M, Manneville F, Langlois J, et al. Longitudinal patterns of lifestyle behaviours in adolescence: a latent transition analysis. Br J Nutr. 2021;126:621–31. doi: 10.1017/S0007114520004316. PubMed DOI

Parker K, Cleland V, Dollman J, et al. A latent transition analysis of physical activity and screen-based sedentary behavior from adolescence to young adulthood. Int J Behav Nutr Phys Act. 2022;19:98. doi: 10.1186/s12966-022-01339-4. PubMed DOI PMC

Parker KE, Salmon J, Villanueva K, et al. Ecological correlates of activity-related behavior typologies among adolescents. BMC Public Health. 2019;19:1041. doi: 10.1186/s12889-019-7386-9. PubMed DOI PMC

Caetano IT, Miranda VPN, Dos Santos FK, et al. Ecological correlates related to adolescent movement behaviors: A latent class analysis. PLoS One. 2022;17:e0271111. doi: 10.1371/journal.pone.0271111. PubMed DOI PMC

Piler P, Kandrnal V, Kukla L, et al. Cohort Profile: The European Longitudinal Study of Pregnancy and Childhood (ELSPAC) in the Czech Republic. Int J Epidemiol. 2016;46:dyw091. doi: 10.1093/ije/dyw091. PubMed DOI PMC

Paruthi S, Brooks LJ, D’Ambrosio C, et al. Recommended Amount of Sleep for Pediatric Populations: A Consensus Statement of the American Academy of Sleep Medicine. J Clin Sleep Med. 2016;12:785–6. doi: 10.5664/jcsm.5866. PubMed DOI PMC

Team, R.C . Vienna, Austria: R Foundation for Statistical Computing; 2021. R: a language and environment for statistical computing.

Everitt BS. The Cambridge dictionary of statistics. Cambridge University Press; 2006.

Collins LM, Lanza ST. Latent Class and Latent Transition Analysis. 2009. DOI

Lubke G, Neale MC. Distinguishing Between Latent Classes and Continuous Factors: Resolution by Maximum Likelihood? Multivariate Behav Res. 2006;41:499–532. doi: 10.1207/s15327906mbr4104_4. PubMed DOI

Weller BE, Bowen NK, Faubert SJ. Latent Class Analysis: A Guide to Best Practice. Journal of Black Psychology. 2020;46:287–311. doi: 10.1177/0095798420930932. DOI

Nylund-Gibson K, Choi AY. Ten frequently asked questions about latent class analysis. Transl Issues Psychol Sci. 2018;4:440–61. doi: 10.1037/tps0000176. DOI

Oberski DL, van Kollenburg GH, Vermunt JK. A Monte Carlo evaluation of three methods to detect local dependence in binary data latent class models. Adv Data Anal Classif. 2013;7:267–79. doi: 10.1007/s11634-013-0146-2. DOI

Di Mari R, Oberski DL, Vermunt JK. Bias-Adjusted Three-Step Latent Markov Modeling With Covariates. Struct Equ Modeling. 2016;23:649–60. doi: 10.1080/10705511.2016.1191015. DOI

Delfmann LR, Verloigne M, Deforche B, et al. Psychosocial Determinants of Sleep Behavior and Healthy Sleep Among Adolescents: A Two-Wave Panel Study. J Youth Adolesc. 2024;53:360–73. doi: 10.1007/s10964-023-01866-8. PubMed DOI PMC

Ferrar K, Chang C, Li M, et al. Adolescent time use clusters: a systematic review. J Adolesc Health. 2013;52:259–70. doi: 10.1016/j.jadohealth.2012.06.015. PubMed DOI

Hadiwijaya H, Klimstra TA, Vermunt JK, et al. On the Development of Harmony, Turbulence, and Independence in Parent-Adolescent Relationships: A Five-Wave Longitudinal Study. J Youth Adolesc. 2017;46:1772–88. doi: 10.1007/s10964-016-0627-7. PubMed DOI PMC

Kemp BJ, Cliff DP, Chong KH, et al. Longitudinal changes in domains of physical activity during childhood and adolescence: A systematic review. J Sci Med Sport. 2019;22:695–701. doi: 10.1016/j.jsams.2018.12.012. PubMed DOI

Hicks BM, Clark DA, Durbin CE. Person-centered approaches in the study of personality disorders. Personal Disord. 2017;8:288–97. doi: 10.1037/per0000212. PubMed DOI PMC

Jago R, Salway R, Lawlor DA, et al. Profiles of children’s physical activity and sedentary behaviour between age 6 and 9: a latent profile and transition analysis. Int J Behav Nutr Phys Act. 2018;15:103. doi: 10.1186/s12966-018-0735-8. PubMed DOI PMC

Totland TH, Bjelland M, Lien N, et al. Adolescents’ prospective screen time by gender and parental education, the mediation of parental influences. Int J Behav Nutr Phys Act. 2013;10:89. doi: 10.1186/1479-5868-10-89. PubMed DOI PMC

Radó SI, Molnár M, Széll R, et al. Association between Screen Time and Sociodemographic Factors, Physical Activity, and BMI among Children in Six European Countries (Feel4Diabetes): A Cross-Sectional Study. Children (Basel) 2024;11:458. doi: 10.3390/children11040458. PubMed DOI PMC

Rodrigues D, Gama A, Machado-Rodrigues AM, et al. Home vs. bedroom media devices: socioeconomic disparities and association with childhood screen- and sleep-time. Sleep Med. 2021;83:230–4. doi: 10.1016/j.sleep.2021.04.012. PubMed DOI

Mielke GI, Brown WJ, Nunes BP, et al. Socioeconomic Correlates of Sedentary Behavior in Adolescents: Systematic Review and Meta-Analysis. Sports Med. 2017;47:61–75. doi: 10.1007/s40279-016-0555-4. PubMed DOI PMC

Janda D, Gába A, Vencálek O, et al. A 24-h activity profile and adiposity among children and adolescents: Does the difference between school and weekend days matter? PLoS One. 2023;18:e0285952. doi: 10.1371/journal.pone.0285952. PubMed DOI PMC

Zosel K, Monroe C, Hunt E, et al. Examining adolescents’ obesogenic behaviors on structured days: a systematic review and meta-analysis. Int J Obes. 2022;46:466–75. doi: 10.1038/s41366-021-01040-9. PubMed DOI