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

Author

Listed:
  • Garden Tabacchi

    (Sport and Exercise Sciences Unit, SPPF Department, University of Palermo, Via Giovanni Pascoli 6, 90144 Palermo, Italy)

  • Avery Faigenbaum

    (Department of Health and Exercise Science, The College of New Jersey, 2000 Pennington Rd Ewing, NJ 08628, USA)

  • Monèm Jemni

    (ISAFA—International Science and Football Association, 13 Musker Pl, Papworth Everard, Cambridge CB23 3LE, UK)

  • Ewan Thomas

    (Sport and Exercise Sciences Unit, SPPF Department, University of Palermo, Via Giovanni Pascoli 6, 90144 Palermo, Italy)

  • Laura Capranica

    (Department of Movement, Human and Health Sciences, University of Rome Foro Italico, P.za Lauro de Bosis 15, 00135 Rome, Italy)

  • Antonio Palma

    (Sport and Exercise Sciences Unit, SPPF Department, University of Palermo, Via Giovanni Pascoli 6, 90144 Palermo, Italy)

  • Joao Breda

    (Division of Non-communicable Diseases and Life-Course, World Health Organization Regional Office for Europe, UN City, Marmorvej 51, DK, 2100 Copenhagen, Denmark)

  • Antonino Bianco

    (Sport and Exercise Sciences Unit, SPPF Department, University of Palermo, Via Giovanni Pascoli 6, 90144 Palermo, Italy)

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.

Suggested Citation

  • Garden Tabacchi & Avery Faigenbaum & Monèm Jemni & Ewan Thomas & Laura Capranica & Antonio Palma & Joao Breda & Antonino Bianco, 2018. "Profiles of Physical Fitness Risk Behaviours in School Adolescents from the ASSO Project: A Latent Class Analysis," IJERPH, MDPI, vol. 15(9), pages 1-17, September.
    • Handle: RePEc:gam:jijerp:v:15:y:2018:i:9:p:1933-:d:167937
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    References listed on IDEAS

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    1. Valerie Carson & Guy Faulkner & Catherine Sabiston & Mark Tremblay & Scott Leatherdale, 2015. "Patterns of movement behaviors and their association with overweight and obesity in youth," International Journal of Public Health, Springer;Swiss School of Public Health (SSPH+), vol. 60(5), pages 551-559, July.
    2. Ronald Iannotti & Ian Janssen & Ellen Haug & Hanna Kololo & Beatrice Annaheim & Alberto Borraccino, 2009. "Interrelationships of adolescent physical activity, screen-based sedentary behaviour, and social and psychological health," International Journal of Public Health, Springer;Swiss School of Public Health (SSPH+), vol. 54(2), pages 191-198, September.
    3. Yang, Chih-Chien, 2006. "Evaluating latent class analysis models in qualitative phenotype identification," Computational Statistics & Data Analysis, Elsevier, vol. 50(4), pages 1090-1104, February.
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    3. Carlos Bou-Sospedra & Mireia Adelantado-Renau & Maria Reyes Beltran-Valls & Diego Moliner-Urdiales, 2020. "Association between Health-Related Physical Fitness and Self-Rated Risk of Depression in Adolescents: Dados Study," IJERPH, MDPI, vol. 17(12), pages 1-9, June.
    4. Sara Pereira & Peter T. Katzmarzyk & Donald Hedeker & José Maia, 2018. "Profile Resemblance in Health-Related Markers: The Portuguese Sibling Study on Growth, Fitness, Lifestyle, and Health," IJERPH, MDPI, vol. 15(12), pages 1-14, December.
    5. Haein Lee & In-Seo La, 2021. "Latent Class Analysis of Obesogenic Behaviors among Korean Adolescents: Associations with Weight-Related Outcomes," IJERPH, MDPI, vol. 18(21), pages 1-14, October.

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