US state- and county-level social capital in relation to obesity and physical inactivity: A multilevel, multivariable analysis

Abstract

Although social capital has been linked to a variety of health outcomes, its association with obesity has yet to be elucidated. This study explored the relations between social capital measured at the US state and county levels and individual obesity and leisure-time physical inactivity. Individual-level data were drawn from the 2001 Behavioral Risk Factor Surveillance System survey, while data from other surveys and administrative sources were used to construct contextual measures. Two state-level social capital scales were derived from 10 indicators and two county-level scales from five indicators. In 2-level analyses of over 167,000 adults nested within 48 states plus the District of Columbia, residence in a state above the median on one or both state social capital scales (vs. neither scale) was associated with lower relative odds of obesity and physical inactivity, controlling for individual-level covariables and state-level estimates of mean household income, the Gini coefficient, and the percentage of Black residents. In 3-level analyses, the adjusted odds ratio (OR) for physical inactivity associated with residence in a county above the median on one or both county social capital scales was significantly below 1, while the association with obesity was not significant. Significantly weaker inverse ORs for the relations between state- and county-level social capital and obesity were observed among American Indians/Alaska Natives compared to Whites. Meanwhile, little support was found for mediation by social capital of the associations of urban sprawl and income inequality with obesity or physical inactivity. Overall, this study provides some evidence for the promotion of social capital as a potential strategy for addressing the burgeoning obesity epidemic.

Introduction

In the 2001 report ‘A Call to Action to Prevent and Decrease Overweight and Obesity’, the US Surgeon General declared obesity to have reached epidemic proportions in America (U.S. Department of Health and Human Services, 2001). Obesity results from a positive energy balance over time, when total energy intake (through food and/or drink) exceeds total energy expenditure (during work and/or leisure time). Several individual-level behavioral factors have been shown in prospective studies to predict weight gain or obesity, including the consumption of fast foods (Pereira et al., 2005) and sugar-sweetened beverages (Ludwig, Peterson, & Gortmaker, 2001; Schulze et al., 2004), television viewing, and low levels of leisure- or work-time physical activity (Hu, Li, Colditz, Willett, & Manson, 2003; Koh-Banerjee et al., 2003).

To explain the obesity epidemic, increasing attention has been focused on identifying contextual determinants (French, Story, & Jeffery, 2001; Hill & Peters, 1998; Nestle, 2003), with some recent evidence implicating the factors of urban sprawl and income inequality. In a multilevel analysis, Ewing, Schmid, Killingsworth, Zlot, and Raudenbush (2003) found modest yet significant associations between US county-level urban sprawl and diminished time spent walking and between urban sprawl and an increased risk of obesity in individuals. Chang and Christakis (2005) reported an inverse relation between higher metropolitan area-level income inequality and individual obesity risk, in contrast to prior studies which observed positive associations between higher state-level income inequality and overweight status (Kahn, Tatham, Pamuk, & Heath, 1998; Subramanian, Blakely, & Kawachi, 2003).

An unexplored but plausible contextual determinant of obesity is social capital. Social capital has been defined as the resources embedded in social structures which are accessed and/or mobilized in purposive actions (Lin, 2001). This and alternative definitions (e.g., Bourdieu, 1983; Coleman, 1988; Portes, 1998; Putnam, 2000) possess distinctions such as the extent to which social capital is viewed as an individual vs. collective attribute (Kawachi, Kim, Coutts, & Subramanian, 2004). Nevertheless, most versions encompass attitudinal/cognitive domains (e.g., perceived interpersonal trust, reciprocity), as well as behavioral/relational/structural components (e.g., civic participation, informal socializing, volunteering) (Subramanian, Kim, & Kawachi, 2002).

A growing number of studies have attempted to empirically link social capital to favorable health outcomes, both at the collective and individual levels (Kawachi et al., 2004). Proposed mechanisms by which social capital may contribute to better health include the diffusion of knowledge about health promotion, maintenance of healthy behavioral norms through informal social control, promotion of access to local services and amenities, and psychosocial processes which provide affective support and mutual respect (Kawachi & Berkman, 2000). For instance, drawing on the diffusion of innovations theory (Rogers, 2003), residents of high social capital neighborhoods in which exercise and healthy eating (e.g., the avoidance of sugar-sweetened beverages) are practiced among some residents may be more likely to adopt these beneficial behaviors through diffusion of knowledge about the behaviors within facilitative social structures. In one study, low individual social participation in one's community was strongly and significantly associated with leisure-time physical inactivity (Lindstrom, Moghaddassi, & Merlo, 2003). Furthermore, in a recent cross-sectional analysis among 807 adolescents living in the US Los Angeles County, neighborhood collective efficacy (i.e., the willingness to intervene for the common good, the measure of which included several items tapping into attitudinal/cognitive dimensions of social capital) was significantly inversely related to overweight status (Cohen, Finch, Bower, & Sastry, 2006).

While the proposed mechanisms for social capital operate primarily at the local/neighborhood level, it is conceivable that social capital at larger geographical scales (e.g., the county or state level) could also be relevant to population health outcomes. For example, US states higher on average in social capital may be better able to undertake collective action to combat population health threats, and to provide health-promoting public goods for its residents, such as health care. Statewide taxes on soft drinks and snack foods (Jacobson & Brownell, 2000) and policies involving the subsidization of municipal associations and clubs to provide opportunities for physical activity might plausibly be sequelae of social capital acting at the state level. The absence of effective public opposition to such policies could arguably be the result of low state-level social capital, in particular active political mobilization.

Social capital at larger scales might further directly influence local levels of social capital through policy-related mechanisms, including collective efforts to subsidize neighborhood associations to promote civic and social participation. It might also have contextual effects on individual levels of social capital through attitudinal/cognitive mechanisms. For instance, high-trusting and democratic state governmental institutions could conceivably increase public confidence in governmental institutions, which in turn may boost levels of interpersonal trust (Brehm & Rahn, 1997; Levi, 1996).

Urban sprawl may contribute to lower levels of social capital through reductions in time engaged in informal and formal social interactions (due to increased time spent in transit); rises in social segregation and social homogeneity; and disruptions in community boundedness, which may lead to lower levels of community investment by residents (Putnam, 2000). Meanwhile, income inequality has been hypothesized to affect health in part by eroding social cohesion through a widening of the gap between the rich and poor (Kawachi, 2000).

Importantly, the effects of social capital may not necessarily apply uniformly across population sub-groups. Norms of ideal body weight are known to vary across racial/ethnic groups (Caldwell, Brownell, & Wilfley, 1997; Chang & Christakis, 2005; Wilfley et al., 1996), such that some groups may be more resistant to contextual influences of social capital. Furthermore, several studies have found the associations of weight status with educational and occupational attainment to be stronger among women than men (Averett & Korenman, 1996; Gortmaker, Must, Perrin, Sobal, & Dietz, 1993; Sargent & Blanchflower, 1994). Women may face a higher social penalty for being overweight compared to men (Chang & Christakis, 2005), and may be more responsive to factors such as social capital contributing to bodily appearance and obesity.

In the present study, social capital at both the US state and county levels were explored as having possible contextual effects on individual obesity and leisure-time physical inactivity. Two-level analyses (with individuals nested within states) were conducted on the associations between state-level social capital and the risks of obesity and leisure-time physical inactivity among individuals. Three-level analyses (with individuals nested within counties, in turn nested within states) were also performed on the associations of county-level social capital with the same outcomes. Each analysis utilized individual-level data from the US Behavioral Risk Factor Surveillance System (BRFSS) survey, along with data from other surveys and administrative sources to construct contextual measures. In addition, the potential mediating role of social capital in the relations between urban sprawl and income inequality and obesity and physical inactivity, and the possible presence of differential social capital associations by gender and race/ethnicity, were examined.