Cargando…

Multilevel predictors of adolescent physical activity: a longitudinal analysis

BACKGROUND: To examine how factors from a social ecologic model predict physical activity (PA) among adolescents using a longitudinal analysis. METHODS: Participants in this longitudinal study were adolescents (ages 10-16 at baseline) and one parent enrolled in the Transdisciplinary Research on Ener...

Descripción completa

Detalles Bibliográficos
Autores principales: Hearst, Mary O, Patnode, Carrie D, Sirard, John R, Farbakhsh, Kian, Lytle, Leslie A
Formato: Online Artículo Texto
Lenguaje:English
Publicado: BioMed Central 2012
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3305547/
https://www.ncbi.nlm.nih.gov/pubmed/22309949
http://dx.doi.org/10.1186/1479-5868-9-8
_version_ 1782227093737701376
author Hearst, Mary O
Patnode, Carrie D
Sirard, John R
Farbakhsh, Kian
Lytle, Leslie A
author_facet Hearst, Mary O
Patnode, Carrie D
Sirard, John R
Farbakhsh, Kian
Lytle, Leslie A
author_sort Hearst, Mary O
collection PubMed
description BACKGROUND: To examine how factors from a social ecologic model predict physical activity (PA) among adolescents using a longitudinal analysis. METHODS: Participants in this longitudinal study were adolescents (ages 10-16 at baseline) and one parent enrolled in the Transdisciplinary Research on Energetics and Cancer-Identifying Determinants of Eating and Activity (TREC-IDEA) and the Etiology of Childhood Obesity (ECHO). Both studies were designed to assess a socio-ecologic model of adolescent obesity risk. PA was collected using ActiGraph activity monitors at two time points 24 months apart. Other measures included objective height and weight, adolescent and parent questionnaires on multilevel psychological, behavioral and social determinants of PA, and a home PA equipment inventory. Analysis was conducted using SAS, including descriptive characteristics, bivariate and stepped multivariate mixed models, using baseline adjustment. Models were stratified by gender. RESULTS: There were 578 adolescents with complete data. Results suggest few statistically significant longitudinal associations with physical activity measured as minutes of MVPA or total counts from accelerometers. For boys, greater self-efficacy (B = 0.75, p = 0.01) and baseline MVPA (B = 0.55, p < 0.01) remained significantly associated with MVPA at follow-up. A similar pattern was observed for total counts. For girls, baseline MVPA (B = 0.58, p = 0.01) and barriers (B = -0.32, p = 0.05) significantly predicted MVPA at follow-up in the full model. The full multilevel model explained 30% of the variance in PA among boys and 24% among girls. CONCLUSIONS: PA change in adolescents is a complex issue that is not easily understood. Our findings suggest early PA habits are the most important predictor of PA levels in adolescence. Intervention may be necessary prior to middle school to maintain PA through adolescence.
format Online
Article
Text
id pubmed-3305547
institution National Center for Biotechnology Information
language English
publishDate 2012
publisher BioMed Central
record_format MEDLINE/PubMed
spelling pubmed-33055472012-03-16 Multilevel predictors of adolescent physical activity: a longitudinal analysis Hearst, Mary O Patnode, Carrie D Sirard, John R Farbakhsh, Kian Lytle, Leslie A Int J Behav Nutr Phys Act Research BACKGROUND: To examine how factors from a social ecologic model predict physical activity (PA) among adolescents using a longitudinal analysis. METHODS: Participants in this longitudinal study were adolescents (ages 10-16 at baseline) and one parent enrolled in the Transdisciplinary Research on Energetics and Cancer-Identifying Determinants of Eating and Activity (TREC-IDEA) and the Etiology of Childhood Obesity (ECHO). Both studies were designed to assess a socio-ecologic model of adolescent obesity risk. PA was collected using ActiGraph activity monitors at two time points 24 months apart. Other measures included objective height and weight, adolescent and parent questionnaires on multilevel psychological, behavioral and social determinants of PA, and a home PA equipment inventory. Analysis was conducted using SAS, including descriptive characteristics, bivariate and stepped multivariate mixed models, using baseline adjustment. Models were stratified by gender. RESULTS: There were 578 adolescents with complete data. Results suggest few statistically significant longitudinal associations with physical activity measured as minutes of MVPA or total counts from accelerometers. For boys, greater self-efficacy (B = 0.75, p = 0.01) and baseline MVPA (B = 0.55, p < 0.01) remained significantly associated with MVPA at follow-up. A similar pattern was observed for total counts. For girls, baseline MVPA (B = 0.58, p = 0.01) and barriers (B = -0.32, p = 0.05) significantly predicted MVPA at follow-up in the full model. The full multilevel model explained 30% of the variance in PA among boys and 24% among girls. CONCLUSIONS: PA change in adolescents is a complex issue that is not easily understood. Our findings suggest early PA habits are the most important predictor of PA levels in adolescence. Intervention may be necessary prior to middle school to maintain PA through adolescence. BioMed Central 2012-02-06 /pmc/articles/PMC3305547/ /pubmed/22309949 http://dx.doi.org/10.1186/1479-5868-9-8 Text en Copyright ©2012 Hearst et al; licensee BioMed Central Ltd. http://creativecommons.org/licenses/by/2.0 This is an Open Access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/2.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
spellingShingle Research
Hearst, Mary O
Patnode, Carrie D
Sirard, John R
Farbakhsh, Kian
Lytle, Leslie A
Multilevel predictors of adolescent physical activity: a longitudinal analysis
title Multilevel predictors of adolescent physical activity: a longitudinal analysis
title_full Multilevel predictors of adolescent physical activity: a longitudinal analysis
title_fullStr Multilevel predictors of adolescent physical activity: a longitudinal analysis
title_full_unstemmed Multilevel predictors of adolescent physical activity: a longitudinal analysis
title_short Multilevel predictors of adolescent physical activity: a longitudinal analysis
title_sort multilevel predictors of adolescent physical activity: a longitudinal analysis
topic Research
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3305547/
https://www.ncbi.nlm.nih.gov/pubmed/22309949
http://dx.doi.org/10.1186/1479-5868-9-8
work_keys_str_mv AT hearstmaryo multilevelpredictorsofadolescentphysicalactivityalongitudinalanalysis
AT patnodecarried multilevelpredictorsofadolescentphysicalactivityalongitudinalanalysis
AT sirardjohnr multilevelpredictorsofadolescentphysicalactivityalongitudinalanalysis
AT farbakhshkian multilevelpredictorsofadolescentphysicalactivityalongitudinalanalysis
AT lytlelesliea multilevelpredictorsofadolescentphysicalactivityalongitudinalanalysis