What explains the socioeconomic status gap in activity? Educational differences in determinants of physical activity and screentime

BMC Public Health

Research Article

Matti T. J. Heino¹  Emilia Kujala¹  Sini-Tuuli Hynynen¹  Ari Haukkala¹  Nelli Hankonen²  Vera Araújo-Soares³  Katja Borodulin⁴  Pilvikki Absetz⁵ 

[1] Department of Social Research, University of Helsinki, Helsinki, Finland;Department of Social Research, University of Helsinki, Helsinki, Finland;School of Social Sciences and Humanities, University of Tampere, Tampere, Finland;Institute of Health and Society, Faculty of Medical Sciences, Newcastle University, Newcastle, UK;National Institute for Health and Welfare, Helsinki, Finland;School of Health Sciences, University of Tampere, Tampere, Finland;

关键词: Socioeconomic status;    Adolescents;    Physical activity;    Screen time;    Sedentary behaviour;    Theoretical determinants;    Theoretical domains framework;   

DOI  :  10.1186/s12889-016-3880-5

 received in 2016-05-17, accepted in 2016-11-25,  发布年份 2017

来源: Springer

【 摘 要 】

BackgroundDesigning evidence-based interventions to address socioeconomic disparities in health and health behaviours requires a better understanding of the specific explanatory mechanisms. We aimed to investigate a comprehensive range of potential theoretical mediators of physical activity (PA) and screen time in different socioeconomic status (SES) groups: a high SES group of high school students, and a low SES group of vocational school students. The COM-B system, including the Theoretical Domains Framework (TDF), was used as a heuristic framework to synthesise different theoretical determinants in this exploratory study.MethodsFinnish vocational and high school students (N = 659) aged 16–19, responded to a survey assessing psychological, social and environmental determinants of activity (PA and screen time). These determinants are mappable into the COM-B domains: capability, opportunity and motivation. The outcome measures were validated self-report measures for PA and screen time. The statistical analyses included a bootstrapping-based mediation procedure.ResultsRegarding PA, there were SES differences in all of the COM-B domains. For example, vocational school students reported using less self-monitoring of PA, weaker injunctive norms to engage in regular PA, and fewer intentions than high school students. Mediation analyses identified potential mediators of the SES-PA relationship in all of three domains: The most important candidates included self-monitoring (CI95 for b: 0.19–0.47), identity (0.04–0.25) and material resources available (0.01–0.16). However, SES was not related to most determinants of screentime, where there were mainly gender differences. Most determinants were similarly related with both behaviours in both SES groups, indicating no major moderation effect of SES on these relationships.ConclusionsThis study revealed that already in the first years of educational differentiation, levels of key PA determinants differ, contributing to socioeconomic differences in PA. The analyses identified the strongest mediators of the SES-PA association, but additional investigation utilising longitudinal and experimental designs are needed. This study demonstrates the usefulness of combining constructs from various theoretical approaches to better understand the role of distinct mechanisms that underpin socioeconomic health behaviour disparities.

【 授权许可】

CC BY   
© The Author(s). 2016