Evidence map›Paper›PMID 30190099›Full record

ArticleJournal of science and medicine in sport2019

Typologies of adolescent activity related health behaviours.

Kate E Parker, Jo Salmon, Helen L Brown, Karen Villanueva, Anna Timperio

Abstract read
In one paragraph

Article in Journal of science and medicine in sport, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 19 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
19citing papers in PubMed, 1 pooled it
4.8field-weighted citation impact, top 5% of its field
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

19 citing papers in PubMed, 1 synthesis or guideline pooled it, 38 citations in OpenAlex.

  1. Pooled it
  2. Article
  3. Article
  4. Article
  5. Article
  6. Article
  7. Article
  8. Article
  9. Article
  10. Article
  11. Article
  12. Article
  13. Article
  14. Article
  15. Article
  16. Observational
  17. Article
  18. Article
  19. Article
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

5 authors at 2 institutions in 1 country.

Kate E ParkerDeakin University, GEELONG, Australia, Institute for Physical Activity and Nutrition (IPAN), School of Exercise and Nutrition Sciences. Electronic address: k.parker@deakin.edu.au.
Jo SalmonDeakin University, GEELONG, Australia, Institute for Physical Activity and Nutrition (IPAN), School of Exercise and Nutrition Sciences.
Helen L BrownDeakin University, GEELONG, Australia, Institute for Physical Activity and Nutrition (IPAN), School of Exercise and Nutrition Sciences.
Karen VillanuevaCentre for Urban Research, School of Global Urban and Social Studies, RMIT University, Australia.
Anna TimperioDeakin University, GEELONG, Australia, Institute for Physical Activity and Nutrition (IPAN), School of Exercise and Nutrition Sciences.
Deakin University · AURMIT University · AU

Funding

IPEN Adolescent: International Study of Built Environments and Physical ActivityR01HL111378 · NHLBI · UNIVERSITY OF CALIFORNIA, SAN DIEGO · PI SALLIS, JAMES F. · 2012 to 2015
$2.8M
Ecological Analysis of Activity, Eating, & Weight in AdolescentsR01HL083454 · NHLBI · UNIVERSITY OF CALIFORNIA, SAN DIEGO · PI SALLIS, JAMES F. · 2007 to 2010
$2.7M
NHLBI NIH HHS R01 HL083454NHLBI NIH HHS R01 HL111378
6 · The paper itself

Abstract

objectivesTo identify typologies of activity-related behaviours and demographic characteristics of these typologies among Australian adolescents.

designCross-sectional study of 473 Secondary School students (41.4% boys, mean age 14.95±1.61 years) conducted in 2014-15.

methodsActive travel to school, sport participation, leisure-time sedentary and demographic variables were self-reported in a survey. Duration of sedentary time and moderate-to-vigorous physical activity (mins/day) were accelerometer-derived. Latent class analysis (LCA) was conducted to identify typologies of activity-related health behaviours. One-way ANOVAs and chi-square tests were used to explore differences by demographic characteristics.

resultsThree typologies were identified: (1) "Physically inactive, highly sedentary" (44%); (2) "Moderately active, high screen-time" (42%); and (3) "Highly active, low sedentary" (14%). Differences between typologies were evident for age, sex, body mass index (BMI), cultural identity, employment status and socioeconomic position (SEP). Those in typology 3 (optimal behaviour pattern) tended to be younger, of higher SEP and lower BMI.

conclusionsThis study found that older adolescents have less active, more sedentary profiles than younger adolescents. The findings support the need for targeted interventions to improve adolescent activity-related behaviour engagement.

Indexed as

Adolescent BehaviorHealth BehaviorAdolescentAge FactorsAustraliaBody Mass IndexCross-Sectional StudiesExerciseFemaleHumansLeisure ActivitiesMaleSedentary BehaviorSelf ReportSocial ClassAdolescentsClusteringDemographicsLatent class analysisPhysical activitySedentary behaviour

Identifiers

PMID30190099
PMCPMC6703174
OpenAlexW2889062383

What OpenQuestion holds

Textmetadata
LicenceTDM
Read underepoch 390

Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.