How socio-economic status contributes to participation in leisure-time physical activity

Abstract

The aim of this cross-sectional study was to identify individual, social, and environmental contributors (mediators) to individual- and area-level differences in leisure-time physical activity across socio-economic groups. A two-stage stratified sampling design was used to recruit 20–65 year old adults (N = 2194) living in 154 census collection districts of Adelaide, Australia (overall response rate: 12%). Participants completed two surveys six months apart (response rate on the second survey: 83%). Individual-level socio-economic status (SES) was assessed using self-report measures on educational attainment, household income, and household size. Area-level SES was assessed using census data on median household income and household size for each selected census district. Bootstrap generalized linear models were used to examine associations between SES, potential mediators, and leisure-time physical activity. The product-of-coefficient test was used to estimate mediating effects. All SES measures were independently associated with potential individual and social mediators of the SES-activity relationships. Individual- and area-level income was also associated with perceived neighborhood attributes. Self-efficacy and social support for physical activity explained virtually all of the differences in physical activity across educational attainment groups. Physical barriers to walking and access to public open space contributed in part to the explanation of differences in recreational walking across income groups. Yet, self-efficacy and social support were the key mediators of the observed relationships between individual- and area-level income and physical activity. This study suggests that in order to increase physical activity participation in the more disadvantaged segments of the population, comprehensive, multilevel interventions targeting activity-related attitudes and skills as well as social and physical environments are needed.

Introduction

Socio-economic status (SES), commonly measured by household income, educational attainment, or occupation, is a major source of health inequalities (National Research Council, 1999). Lower SES has been associated with increased prevalence of overweight and obesity, and related co-morbidities in both developed and developing countries (Kavanagh et al., 2005, Taylor et al., 2006). A recent study has identified leisure-time physical activity (also referred to as physical activity or activity) as the key health behavior protecting against obesity with the largest educational disparities in the United States (Harper & Lynch, 2007). Also, there is evidence that the higher prevalence of leisure-time physical inactivity observed in racial/ethnic minority groups might, in the main, be due to differences in SES (Marshall et al., 2007).

To devise interventions aimed at reducing health inequalities in disadvantaged populations, there is a pressing need for a better understanding of the mechanisms underlying differences in health behaviors. Current social ecological models attribute variations in health behavior to the interactive play of individual psychological, social, and physical environmental factors (McLeroy, Bibeau, Steckler, & Glanz, 1988). According to these models, social inequalities (e.g., socio-economic status) can influence health behavior directly or indirectly through mediating mechanisms that differ for distinct outcomes. In the case of physical activity, inequalities across educational attainment groups, independent of individual income, could be due to differences in problem-solving and coping capacity arising from educational experience, which in turn are likely to impact on self-efficacy for physical activity (Mirowsky & Ross, 2003). Educational attainment may be also associated with greater exposure to health messages instilling higher levels of perceived benefits of physical activity, and a greater capacity to seek, understand, internalize, and act upon these messages (self-efficacy for physical activity) (Winkleby, Jatulis, Frank, & Fortmann, 1992). Further, highly educated individuals, with a better understanding of the health benefits of an active lifestyle, may seek to live in activity-friendly environments. They are also likely to get more support for being physically active from their social network, sharing a similar hierarchy of values and set of social norms (Heaney & Israel, 1997). Finally, higher educational attainment is related to better general health, which may increase the likelihood of being more physically active (McNeill, Kreuter, & Subramanian, 2006). These factors are thought to be interconnected and mutually dependent (reciprocal causality).

The independent effect of individual income on engagement in physical activity can be theoretically explained through pathways similar to those of educational attainment. The main difference between these two factors pertains to the fact that the individual income is bound to exert its main effect through access to health care resources and recreational facilities and opportunities (McNeill et al., 2006). Individuals with higher discretionary income can choose to live in environments that are more conducive to an active lifestyle as well as more readily obtain social and material resources that help to maintain an active lifestyle even in adverse conditions (e.g., lack of family support; lack of facilities in the neighborhood). In contrast, the effects of educational attainment on physical activity are likely to be, by and large, channeled through psychological and social pathways (Winkleby et al., 1992).

Neighborhood SES, usually measured using area-level variables (e.g., percent unemployed, median household income by census tract), may also independently affect residents' leisure-time physical activity over and above individual SES (McNeill et al., 2006, Taylor et al., 2006). For instance, a recent Australian study reported that, after adjusting for individual-level household income and education, area SES was positively associated with the likelihood of jogging and of engaging in health-enhancing levels of physical activity (Kavanagh et al., 2005). Similar independent positive association between area SES and physical activity have been observed in other developed countries (e.g., van Lenthe, Brug, & Mackenbach, 2005).

Several potential mechanisms have been proposed to explain the effect of area SES on residents' physical activity. These include physical characteristics of the neighborhood environment, access to recreational facilities, and social capital defined by neighborhood social and cultural norms, perceived safety, trust, connections and reciprocity (Lindström et al., 2001, Macintyre et al., 2002). Although not definitive, a number of published reports indicate that lower SES areas have limited access to environments supportive of an active lifestyle (Taylor et al., 2006). Thus, higher SES areas were found to have better access to sporting and recreational spaces (Powell, Slater, & Chaloupka, 2004), higher levels of safety and aesthetics (Wilson, Kirkland, Ainsworth, & Addy, 2004), and even a greater number of free-for-use physical activity resources (Estabrooks, Lee, & Gyurcsik, 2003). To date, no studies have explicitly examined the potential effects of area-level social-capital related characteristics, such as neighborhood-level norms and attitudes, connectivity and social support for physical activity on leisure-time physical activity.

While previous studies, adopting a social ecological perspective, have examined the independent contributions of psychological, social and environmental factors to physical activity behavior (Giles-Corti & Donovan, 2002), it remains unclear the extent to which these factors can explain individual- and area-level SES inequalities in leisure-time physical activity. Empirical reports on potential mediators of the relationships between SES and leisure-time physical activity have been rather limited in scope, focusing on either individual-level or area-level SES indicators, environmental or psychosocial mediating variables (Droomers et al., 1998, van Lenthe et al., 2005). Hence, the main aim of this study was to establish the independent contributions of potential individual (self-efficacy for physical activity; perceived benefits of physical activity; and self-reported health), social (social support for physical activity), and environmental mediators (perceived access to recreational facilities; aesthetics; traffic; crime; and infrastructure for walking) to the explanation of individual-level (educational attainment and household income) and area-level SES (median census tract household income) differences in leisure-time physical activity. As self-efficacy has been identified as one of the strongest predictors of, and most proximal links in the causal chain leading to specific health behaviors (Bandura, 1986, Rimal, 2000), it was hypothesized that the differential effects of social, environmental and individual factors on leisure-time physical activity would be partly mediated by self-efficacy (see Fig. 1).