Explaining educational differences in leisure‐time physical activity in Europe: the contribution of work‐related factors

Abstract

Although educational differences in leisure-time physical activity (LTPA) exist across Europe, the independent effect of educational level on leisure-time physical activity has rarely been explored. This study examines the relative contribution of occupational class, employment status, and educational level to LTPA across 12 European countries. The data were obtained from 12 European health surveys conducted at the turn of the century and identified in the EUROTHINE project. All information was self-reported. Logistic regression was applied and relative inequality index (RII) was calculated. Analyses were limited to those in the prime working-age (age 30-59; total N=137,646) men and women. In all 12 European countries, LTPA was more common in the high-educated than in the low-educated. The association between education and LTPA remained mostly unchanged after adjusting for marital status, urbanization, and self-rated health. After further adjusting for occupational class and employment status, the educational differences in LTPA were only slightly attenuated. An inverse association was found between educational level and LTPA across almost all 12 European countries. Occupational class and employment status had only a modest effect on educational differences in LTPA in most of the examined countries, suggesting that education remains an important predictor of LTPA.

Macroenvironmental Factors Including GDP per Capita and Physical Activity in Europe

“…At the level of the individual. Mäkinen et al (12) previously found educational attainment to be the strongest determinant of leisure-time physical activity across 12 European countries. At the macrolevel, we show here that educational attainment (the percentage completing tertiary education) was also related to between-country differences in leisure-time physical activity.…”

“…The mean age of included participants by country was not reported for any study, but in most cases, the uniform study design aimed to generate a sample of similar age profile in each countiy (1,4,10,13,19,20,29). In the study of Mäkinen et al (12), which involved data from 12 national health surveys, only adults age 30 to 59 yr were included. All analyses were conducted using Stata 11.1 (21).…”

“…With the exception of education, all macroenvironmental variables were selected based on their associations with leisure-time physical activity in the previous pan-European analysis of Van Tuyckom (29). Educational attainment was included based on the finding that at the level of the individual, it was the strongest determinant of leisure-time physical activity across 12 European countries (12). Van Tuyckom (29) also found associations between nutritionrelated variables and physical activity levels.…”

An evaluation of equity and equality in physical activity policies in four European countries

“…Health related behavior can be positively influenced only by addressing health-related behaviors and socioeconomic and environmental factors in PA policies. In various studies that present data from the European countries, it has been shown that smoking [5, 6], excessive alcohol consumption [7], lack of physical exercise [8, 9] and obesity [10] are all more common in lower socioeconomic groups. However, the extent of the impact of behavioral risk factors on health differs between countries.…”

Atividade física após hospitalização por doenças do aparelho circulatório

“…Outra associação esperada na presente pesquisa era a maior prevalência de atividade física em sujeitos com maior escolaridade. Pesquisa realizada em doze países europeus mostrou que a atividade física no lazer foi diretamente associada com o alto nível de escolaridade dos sujeitos 29 . Outros achados também associaram positivamente maior nível de escolaridade com a prática de atividade física 21,24,30 .…”