Socio-economic determinants of physical activity across the life course: A "DEterminants of DIet and Physical ACtivity" (DEDIPAC) umbrella literature review

Abstract

BackgroundTo date, the scientific literature on socioeconomic correlates and determinants of physical activity behaviours has been dispersed throughout a number of systematic reviews, often focusing on one factor (e.g. education or parental income) in one specific age group (e.g. pre-school children or adults). The aim of this umbrella review is to provide a comprehensive and systematic overview of the scientific literature from previously conducted research by summarising and synthesising the importance and strength of the evidence related to socioeconomic correlates and determinants of PA behaviours across the life course.MethodsMedline, Embase, ISI Web of Science, Scopus and SPORTDiscus were searched for systematic literature reviews and meta-analyses of observational studies investigating the association between socioeconomic determinants of PA and PA itself (from January 2004 to September 2017). Data extraction evaluated the importance of determinants, strength of evidence, and methodological quality of the selected papers. The full protocol is available from PROSPERO (PROSPERO2014:CRD42015010616).ResultsNineteen reviews were included. Moderate methodological quality emerged. For adults, convincing evidence supports a relationship between PA and socioeconomic status (SES), especially in relation to leisure time (positive relationship) and occupational PA (negative relationship). Conversely, no association between PA and SES or parental SES was found for pre-school, school-aged children and adolescents.ConclusionsAvailable evidence on the socioeconomic determinants of PA behaviour across the life course is probable (shows fairly consistent associations) at best. While some evidence is available for adults, less was available for youth. This is mainly due to a limited quantity of primary studies, weak research designs and lack of accuracy in the PA and SES assessment methods employed. Further PA domain specific studies using longitudinal design and clear measures of SES and PA assessment are required.

Daily physical activity patterns among aging workers: the Finnish Retirement and Aging Study (FIREA)

“…We found no differences in leisure-time physical activity between the occupational categories, which is contrary to some previous studies which have used self-reported physical activity as an outcome 2. Nevertheless, our results are similar to several studies using objective measures for physical activity which have not observed differences in leisure-time physical activity between manual and non-manual occupations 5–8.…”

“…Generally, non-manual occupational status has been found to associate with more total or leisure time physical activity, but with less occupational physical activity 2. However, the research on physical activity across different occupations has mostly relied on self-reported measures of physical activity,1 which usually capture only moderate-to-vigorous physical activity (MVPA) and are prone to reporting bias 3.…”

Impact of school and work status on diet and physical activity in rural Guatemalan adolescent girls: a qualitative study

“…Recent literature from LMICs has begun to explore how the school environment is an important modifier of food and physical activity choices for adolescent girls, similar to well-established findings from HICs. 5,6,15,16 However, most of this work has been conducted in large metropolitan settings (including in Guatemala) and much less is known about the choices of adolescent girls from outside these areas. 18,20 In addition, comparative work on the choices of out-of-school girls has not been conducted, despite the importance of this issue in LMICs, where many adolescents are not enrolled in school due to multiple reasons, including work and pregnancy.…”

“…There is an extensive literature on the social and environmental factors that impact adolescents' decision making around diet and activity. [2][3][4][5][6][7][8][9] In particular, the school environment has been well studied, both as a formative environment shaping diet and activity behaviors and, consequently, a potential site for interventions a These authors contributed equally. designed to promote healthy behaviors.…”

Active 10

“…Apple Watch or Garmin's) can potentially provide such information if the data is further processed [8]. However, access to such devices is challenging at a population level, particularly amongst the least active who also tend to be amongst the least affluent parts of society [18]. Therefore, the Active 10 intervention started with the development of a custom selfmonitoring app, especially designed to track the achievement of daily bouts of 10 minutes of brisk walking via mobile phone.…”