Elsevier

Social Science & Medicine

Volume 62, Issue 3, February 2006, Pages 769-778
Social Science & Medicine

Collective efficacy and obesity: The potential influence of social factors on health

https://doi.org/10.1016/j.socscimed.2005.06.033Get rights and content

Abstract

Social determinants have been identified as a fundamental cause of health and disease in most industrialized countries. However, much less is known about which characteristics of communities may lead to disparities in health outcomes. Collective efficacy—the willingness of community members to look out for each other and intervene when trouble arises—is a social factor shown to be associated with outcomes related to obesity, including premature mortality and cardiovascular disease. The objective of this study is to determine whether neighborhood collective efficacy is associated with individual measures of body mass index (BMI) in adolescents.

We use a multi-level, cross-sectional survey in Los Angeles County, involving 807 adolescents in 684 households in 65 neighborhoods in addition to a sample of 3000 adult respondents. The main outcomes measures are BMI, at risk of overweight, and overweight status. Using a two-level model, we find significant relationships between collective efficacy and all three outcomes, net of levels of neighborhood disadvantage.

The associations between BMI and collective efficacy could potentially be explained by several factors, including a metabolic pathway, neighborhood differences in the physical and social environments, or a combination of these two. If group-level collective efficacy is indeed important in the regulation of individual-level net energy balance, it suggests that future interventions to control weight by addressing the social environment at the community level may be promising.

Introduction

Obesity is recognized as the most important health problem in US today, given its contribution to a wide variety of negative health outcomes, including premature mortality, morbidity, and the astronomical costs it exacts from both health care plans and employers, in excess of $75 billion/year (Finkelstein, Fiebelkorn, & Wang, 2004). More recent evidence indicates that this problem is not constrained to the US, but is also affecting several industrialized countries around the globe (Seidell, 1995; Silventoinen et al., 2004). However, the precise cause and a feasible solution to the epidemic continue to elude us. A consensus has developed that the primary etiology is neither genetic nor physiological, given that no significant mutations or changes in human anatomy have occurred in the past two decades. In short, while there may be a large genetic component to obesity (Sorensen, 2001), this does not explain the recent increase in obesity. As a result, the most recent thinking points to environmental factors, which make it easy to consume excessive calories and more difficult to expend them in routine physical activity (Giles-Corti & Donovan, 2003; Hill, Wyatt, Reed, & Peters, 2003). However, while obesity is found in all income and ethnic groups, low-income groups and ethnic and racial minorities are disproportionately affected (United States Department of Health and Human Services (USDHHS, 2001))—suggesting that changes in the physical environment cannot fully explain this phenomenon. This health disparity points to social factors as likely contributors to the obesity epidemic.

New research methods allow one to distinguish individual-level factors from those that influence or originate from groups or populations. Study designs that can examine individuals nested within families and families nested within communities are able to pinpoint at what level the sources of influence arise (Snijders & Bosker, 1999). While many have theorized that neighborhoods are potentially strong determinants of individual-level health and health behaviors, most studies have found only modest neighborhood-level effects, if any (House & Williams, 2000). Most neighborhood effects have been identified using administrative (e.g. census) data and these studies often show significant relationships between neighborhood socio-economic status (SES) and health (Morenoff & Lynch, 2002). While neighborhood SES might profoundly affect the level of social resources and social interaction in a given neighborhood, these constructs are not entirely the same. That is, one can imagine two poor communities, one with a high level of social cohesion and positive social interactions and another that is riddled with social problems due to a lack of cohesion and generally negative social interactions. The quality and quantity of social resources in a community are generally referred to as social capital (Kawachi, 1999). Collective efficacy is a concept closely associated with social capital (Coleman, 1988; Kawachi, 1999; Kennedy et al., 1998; Veenstra, 2000), defined as the norms and networks that enable collective action.

Both collective efficacy and social capital may measure otherwise intangible factors related to quality of life and social relationships, such as feelings of security or safety, since a person living in a neighborhood with high levels might have fewer worries if neighbors can be relied upon for help. Collective efficacy, the willingness of people to intervene for the good of the community, and the linkage of mutual trust within a community has been found to strongly predict neighborhood crime (Sampson, Raudenbush, & Earls, 1997). The level of collective efficacy within a community is not reducible to the characteristics of individual members of their respective communities. Collective efficacy has been described as a combination of both informal social control and social cohesion, and reflects the willingness of community members to look out for each other and intervene when trouble arises, especially on behalf of the community's youth. This group-oriented behavior is believed to constrain deviant behaviors and to reflect a community's ability to extract resources from the larger set of infrastructure and social services within a community (Sampson et al., 1997).

Recent studies have documented that collective efficacy is also associated with a variety of health outcomes that cluster at the neighborhood level, including premature mortality and cardiovascular disease mortality (Cohen, Farley, & Mason, 2003; Lochner, Kawachi, Brennan, & Buka, 2003), suggesting that the concept of collective efficacy does more than just control deviant or criminal behavior. Collective efficacy might also reflect social interactions that result in greater conformity. Deviance from the norm might be less tolerated in high efficacy neighborhoods compared with low efficacy neighborhoods. Collective efficacy could also be a measure of political power; for example, residents of neighborhoods with high levels of collective efficacy might band together to maintain or improve their local environment.

Population health distributions of overweight and obesity may be dependent upon both individual-level characteristics and community-level characteristics. While the measures of collective efficacy do not capture anything directly related to diet and exercise, there may be indirect effects on obesity-related factors related to social influences and social control, for example.

One such pathway may be related to allostatic load, which represents the wear and tear the body experienced from stress (McEwen, 2003). Stress is associated with higher levels of cortisol excretion and over time, with excess weight gain, particularly truncal obesity (McEwen (1998a), McEwen (1998b)). People in low collective efficacy neighborhoods likely experience greater daily stress, since they would find lower levels of social support from their neighbors and would be forced to tackle any local problems on their own. In the Alameda County study, persons with fewer social ties were more likely to be obese as well as have higher rates of premature mortality (Berkman & Syme, 1979).

Another pathway through which neighborhoods might affect body mass index (BMI) is through physical activity. Neighborhood “walkability,” including the condition of its sidewalks, street design, and, in particular, land use in which there is a set of thriving businesses that people can walk to for routine errands, has been shown to be associated with both physical activity and BMI (Ewing, Schmid, Killingsworth, Zlot, & Raudenbush, 2003). The political resources of a neighborhood may be responsible for making neighborhoods walkable, for insuring access to recreational facilities, safety from traffic and crime, and might be able to prevent other obesogenic influences such as fast-food outlets or advertisements promoting energy-dense foods from being placed in their area. Neighborhoods with high collective efficacy are more likely to take political action to foster a healthy local environment.

Another possibility is that in neighborhoods with high collective efficacy adults may be willing to express approval and disapproval about an entire range of behaviors beyond delinquency, including diet and exercise, to discourage children from eating energy-dense foods and from being sedentary, and to encourage healthy food consumption and vigorous physical activity. The mechanism could include not just verbal interactions, but actual efforts by adults to serve more healthy foods, to create opportunities for physical activity (e.g., setting up sports leagues), and to prohibit children from spending too much time watching television or playing video and computer games. In low collective efficacy neighborhoods, adults might not care, or they might think it is not their place to interfere with how other people's children behave. In such neighborhoods people may interact less or avoid each other, children may be less likely to engage in physical activity outside, for either leisure or routine activities, and may spend more time indoors being sedentary and eating to excess. On the other hand, it is plausible that a high collective efficacy neighborhood could potentially provide support for being overweight, especially if that happens to be the norm among adults.

As such, the purpose of our study was to further investigate neighborhood level measures of collective efficacy and their association with BMI and overweight in youth. Selecting an analysis of adolescents is purposive and important for several non-trivial reasons. First, the behaviors of adolescents are generally more malleable and not rooted in years of habits and patterns as they often are among adults. Second, adolescents are reliant on their social environments and thus may be more subject to effects of varying conditions in their neighborhoods. Third, selection issues are minimized as it is less plausible that adolescents chose the neighborhoods they lived in and therefore, a third (omitted) factor is probably not driving relationships between community level factors and health.

Section snippets

Study population and design

The first wave of the Los Angeles Family and Neighborhood Survey (LAFANS) survey was carried out between the Spring of 2000 and the end of 2001 among 65 neighborhoods (census tracts) in Los Angeles County. Although the sample contains neighborhoods across the income range, the sample-design purposively over-sampled poor (between the 60th–89th percentile of the poverty distribution) and very poor (top decile) neighborhoods. LAFANS was designed specifically as a multi-level survey, sampling

Descriptive analysis

Descriptive statistics for each of the variables used in our multivariate regression models are presented in Table 1. Further, empty models (i.e., no predictor variables included) are estimated to get an idea of the amount of variation that is due to neighborhood-level characteristics. These models indicate that about 7.2% of the variation in BMI and 5.7% and 3.3% of variation in risk of overweight and overweight, respectively, is due to neighborhood-level characteristics. In other words, the

Discussion/conclusions

Our study shows a significant relationship between collective efficacy and each of our outcomes: BMI, at-risk for overweight, and overweight status, suggesting that group-level social factors among adults are substantially associated with the net energy balance of neighborhood children. Although the cross-sectional design of our study precludes any causal inferences, and because the collective efficacy measures do not cover any items directly related to diet and exercise, we can only speculate

References (33)

  • R. Ewing et al.

    Relationship between urban sprawl and physical activity, obesity, and morbidity

    American Journal of Health Promotion

    (2003)
  • E. Finkelstein et al.

    State-level estimates of annual medical expenditures attributable to obesity

    Obesity Research

    (2004)
  • B. Giles-Corti et al.

    Relative influences of individual, social environmental, and physical environmental correlates of walking

    American Journal of Public Health

    (2003)
  • S.L. Gortmaker et al.

    Television viewing as a cause of increasing obesity among children in the United States, 1986–1990

    Archives of Pediatrics & Adolescent Medicine

    (1996)
  • J.O. Hill et al.

    Obesity and the environment: Where do we go from here?

    Science

    (2003)
  • J. House et al.

    Understanding and reducing socioeconomic and racial/ethnic disparities in health

  • Cited by (0)

    This manuscript was supported in part by a grant from HRSA-MCH Grant # R40MC00303.

    View full text