Developmental trajectories of physical activity and television viewing during adolescence among girls: National Growth and Health Cohort Study
BMC Public Health, ISSN: 1471-2458, Vol: 15, Issue: 1, Page: 667
2015
- 22Citations
- 171Captures
Metric Options: CountsSelecting the 1-year or 3-year option will change the metrics count to percentiles, illustrating how an article or review compares to other articles or reviews within the selected time period in the same journal. Selecting the 1-year option compares the metrics against other articles/reviews that were also published in the same calendar year. Selecting the 3-year option compares the metrics against other articles/reviews that were also published in the same calendar year plus the two years prior.
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Example: if you select the 1-year option for an article published in 2019 and a metric category shows 90%, that means that the article or review is performing better than 90% of the other articles/reviews published in that journal in 2019. If you select the 3-year option for the same article published in 2019 and the metric category shows 90%, that means that the article or review is performing better than 90% of the other articles/reviews published in that journal in 2019, 2018 and 2017.
Citation Benchmarking is provided by Scopus and SciVal and is different from the metrics context provided by PlumX Metrics.
Metrics Details
- Citations22
- Citation Indexes22
- 22
- CrossRef19
- Captures171
- Readers171
- 97
- 69
Article Description
Background: Analytic methodology for investigating physical activity patterns over time has been limited. The aim of this study was to demonstrate the group-based trajectory analysis process for identifying developmental physical activity (PA) and television (TV) viewing trajectories and the risk factor of PA trajectories, and for examining a relationship between PA and TV viewing trajectories among adolescent girls. Methods: Secondary analysis was conducted using the National Growth and Health Study (NGHS) dataset. The NGHS administered the Habitual Activity Questionnaire and TV viewing questionnaire to White and Black girls at age 10, 12, 14, 16, 17, 18, and 19 years. Group-based trajectory analyses were conducted to identify distinct PA trajectories. Race was chosen to present an example of the risk factor analysis and was added as a predictor in the trajectory model. Dual-trajectory analysis was conducted to estimate probabilities of TV viewing trajectory groups conditional on the PA trajectory groups. Results: A total of 2,155 girls (52 % Black) were included in the data analysis. We identified four PA trajectories: substantially decreasing from high PA (PA group 1, 9.4 %), maintaining moderate PA (PA group 2, 31.6 %), maintaining high PA (PA group 3, 5.8 %), and decreasing from moderate PA (PA group 4, 53.2 %). A significantly lower proportion of Black girls had high PA levels at baseline and maintained their baseline PA than White girls. Most girls who were classified as maintaining high PA (88 %) were also classified as decreasing TV viewing. Conclusions: A group-based trajectory approach provides new insights about the patterns of maintaining moderate or high levels of PA that exist among adolescent girls. However, a lower proportion of Black girls followed the maintenance patterns than White girls. The behavioral development of PA and TV viewing may be intertwined among adolescent girls.
Bibliographic Details
http://www.scopus.com/inward/record.url?partnerID=HzOxMe3b&scp=84937198396&origin=inward; http://dx.doi.org/10.1186/s12889-015-2043-4; http://www.ncbi.nlm.nih.gov/pubmed/26174016; http://bmcpublichealth.biomedcentral.com/articles/10.1186/s12889-015-2043-4; https://dx.doi.org/10.1186/s12889-015-2043-4; https://bmcpublichealth.biomedcentral.com/articles/10.1186/s12889-015-2043-4; http://www.biomedcentral.com/1471-2458/15/667; https://bmcpublichealth.biomedcentral.com/counter/pdf/10.1186/s12889-015-2043-4
Springer Science and Business Media LLC
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