Evidence map›Paper›PMID 30189647›Full record

ArticleInternational journal of environmental research and public health2018

Profiles of Physical Fitness Risk Behaviours in School Adolescents from the ASSO Project: A Latent Class Analysis.

Garden Tabacchi, Avery Faigenbaum, Monèm Jemni, Ewan Thomas, Laura Capranica, Antonio Palma, Joao Breda, Antonino Bianco

Abstract read
In one paragraph

Article in International journal of environmental research and public health, 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 18 papers.

0numbers the graph read from it
0cells of the map it votes in
18citing papers in PubMed
–field-weighted citation impact
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

18 citing papers in PubMed.

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  16. What to Do about Childhood Obesity?International journal of environmental research and public health · 2019
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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

8 authors.

Garden TabacchiSport and Exercise Sciences Unit, SPPF Department, University of Palermo, Via Giovanni Pascoli 6, 90144 Palermo, Italy. tabacchi.garden@libero.it.
Avery FaigenbaumDepartment of Health and Exercise Science, The College of New Jersey, 2000 Pennington Rd Ewing, NJ 08628, USA. faigenba@tcnj.edu.
Monèm JemniISAFA-International Science and Football Association, 13 Musker Pl, Papworth Everard, Cambridge CB23 3LE, UK. monemj@hotmail.com.
Ewan ThomasSport and Exercise Sciences Unit, SPPF Department, University of Palermo, Via Giovanni Pascoli 6, 90144 Palermo, Italy. ewan.thomas@unipa.it.ORCID 0000-0001-5991-8316
Laura CapranicaDepartment of Movement, Human and Health Sciences, University of Rome Foro Italico, P.za Lauro de Bosis 15, 00135 Rome, Italy. laura.capranica@uniroma4.it.
Antonio PalmaSport and Exercise Sciences Unit, SPPF Department, University of Palermo, Via Giovanni Pascoli 6, 90144 Palermo, Italy. antonio.palma@unipa.it.
Joao BredaDivision of Non-communicable Diseases and Life-Course, World Health Organization Regional Office for Europe, UN City, Marmorvej 51, DK, 2100 Copenhagen, Denmark. rodriguesdasilvabred@who.int.ORCID 0000-0002-8177-4926
Antonino BiancoSport and Exercise Sciences Unit, SPPF Department, University of Palermo, Via Giovanni Pascoli 6, 90144 Palermo, Italy. antonino.bianco@unipa.it.ORCID 0000-0001-8334-6581

Funding

World Health Organization 001
6 · The paper itself

Abstract

The aim of the present investigation was to describe profiles of adolescents' fitness level, identify latent classes of fitness-related risk behaviours, and describe their sociodemographic and environmental predictors. In total, 883 adolescents (16.4 ± 1.4 years; 167.3 ± 10.4 cm; 62.8 ± 13.5 kg; 62.2% males) were assessed for personal and lifestyle information and for physical fitness components. Eleven possible fitness determinants and seven predictors were included. Latent class analysis (LCA) was used to determine fitness-related risk behaviours. Logistic regressions predicted class membership and assessed associations with fitness levels and fitness components. Five latent classes were recognised: 1-virtuous, 30.7% of respondents; 2-low physical activity/sport, 18.8%; 3-incorrect alcohol/food habits, 25.8%; 4-health risk/overweight, 15.9%; 5-malaise/diseases, 8.8%. Sex, age, parents' overweightness/obesity and education, and school type predicted most classes significantly. Compared to class 1, class 2 had higher odds of having all poor fitness components except upper body maximal strength; class 4 had higher risk of low muscular endurance; and class 5 was likely to have lower maximal strength, muscular endurance, and speed/agility. Educating adolescents to reach a sufficient practice of PA/sport could help decreasing the risk of low health-related fitness more than discouraging them from using alcohol, addressing proper food behaviours and habits, and helping them understand their psychophysical malaise symptoms.

Indexed as

Health BehaviorHealth StatusPhysical FitnessAdolescentAge FactorsAlcohol DrinkingDietExerciseFeeding BehaviorFemaleHumansLatent Class AnalysisLife StyleMaleOverweightParentsadolescentshealthlatent class analysisphysical fitness

Identifiers

PMID30189647
PMCPMC6163564

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Registered trials

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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.