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Physical activity barriers according to social stratification in Europe

Author

Listed:
  • Antonio Moreno-Llamas

    (University of Murcia)

  • Jesús García-Mayor

    (University of Murcia)

  • Ernesto De la Cruz-Sánchez

    (University of Murcia)

Abstract

Objectives To analyse relationships of social stratification on physical activity (PA) prevalence and barriers in the European population. Methods Data were retrieved from Eurobarometer 88.4, a cross-sectional survey conducted in 2017 with 28,031 over 15-year-old inhabitants of the European Union. PA prevalence was calculated along with the probability to be physically inactive by social stratification. Logistic regressions were run in the inactive population to show the social class effect on each barrier adjusted by sociodemographic factors employing a propensity score matched method. Results Low social class presented higher inactivity prevalence (43.11%), whilst the high social class reported the lowest prevalence (23.30%). Also, the low (OR 0.52; 95% CI 0.47–0.58) and middle (OR 0.71; 95% CI 0.64–0.79) social classes were less likely to be active compared to high social class. In the inactive population, the low social class had mostly higher odds to report each barrier. Conclusions Social class is a relevant factor for low PA, with more barriers in the lower social classes. Public health institutions should implement strategies on more influential PA barriers and disadvantaged social groups.

Suggested Citation

  • Antonio Moreno-Llamas & Jesús García-Mayor & Ernesto De la Cruz-Sánchez, 2020. "Physical activity barriers according to social stratification in Europe," International Journal of Public Health, Springer;Swiss School of Public Health (SSPH+), vol. 65(8), pages 1477-1484, November.
  • Handle: RePEc:spr:ijphth:v:65:y:2020:i:8:d:10.1007_s00038-020-01488-y
    DOI: 10.1007/s00038-020-01488-y
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    References listed on IDEAS

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    1. Sarah Kelly & Steven Martin & Isla Kuhn & Andy Cowan & Carol Brayne & Louise Lafortune, 2016. "Barriers and Facilitators to the Uptake and Maintenance of Healthy Behaviours by People at Mid-Life: A Rapid Systematic Review," PLOS ONE, Public Library of Science, vol. 11(1), pages 1-26, January.
    2. Kosuke Imai & Marc Ratkovic, 2014. "Covariate balancing propensity score," Journal of the Royal Statistical Society Series B, Royal Statistical Society, vol. 76(1), pages 243-263, January.
    3. Reichert, F.F. & Barros, A.J.D. & Domingues, M.R. & Hallal, P.C., 2007. "The role of perceived personal barriers to engagement in leisure-time physical activity," American Journal of Public Health, American Public Health Association, vol. 97(3), pages 515-519.
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    Cited by:

    1. Jesús García-Mayor & Élvio Rúbio Gouveia & Adilson Marques & Ernesto De la Cruz-Sánchez & Antonio Moreno-Llamas & Cíntia França & Bruna R. Gouveia & Andreas Ihle, 2022. "Exploring the Role of Physical Activity in Mediating the Association between Educational Level and Health-Related Quality of Life in an Adult Lifespan Sample from Madeira Island," IJERPH, MDPI, vol. 19(13), pages 1-13, June.
    2. Celia Marcen & Eduardo Piedrafita & Rubén Oliván & Irela Arbones, 2022. "Physical Activity Participation in Rural Areas: A Case Study," IJERPH, MDPI, vol. 19(3), pages 1-21, January.
    3. Rafał Rowiński & Grażyna Kowalska & Mariusz Kozakiewicz & Kornelia Kędziora-Kornatowska & Maciej Kornatowski & Joanna Hawlena & Karolina Rowińska, 2021. "Physical Activity and Its Determinants among Senior Residents of Podlasie, a Green Region of Poland, Based on the National PolSenior Study," IJERPH, MDPI, vol. 18(20), pages 1-12, October.
    4. Elżbieta Antczak & Katarzyna M. Miszczyńska, 2021. "Causes of Sickness Absenteeism in Europe—Analysis from an Intercountry and Gender Perspective," IJERPH, MDPI, vol. 18(22), pages 1-22, November.

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