Building on previous research that points to physical and structural characteristics of disadvantaged neighborhoods as sources of stress (Boardman et al. 2001
; Robert 1999
), we found evidence that one neighborhood stressor (high violent crime) is associated with worse mental health outcomes, above and beyond effects of neighborhood economic context. In contrast to studies suggesting that signs of public drinking and alcohol-related problems are sources of stress, alcohol availability was not associated with our outcomes. We believe that neighborhood crime operates to influence perceptions of neighborhoods as dangerous, threatening, or stressful and by increasing residents' risk of being a victim of crime. In turn, these increased risks and negative perceptions are associated with ADM disorders.
Studies of stress suggest that social support and personal resources have positive effects on health and mental health (Kawachi & Berkman 2001
). Our results expand on this finding to demonstrate that neighborhood stress-buffering mechanisms, particularly neighborhood housing distribution characteristics and organizational resources such as churches, are associated with a lower likelihood of any ADM disorders. Moreover, these effects remain significant when neighborhood economic context and stressors are included, and may reduce effects of neighborhood stressors, as indicated by the non-significant group test of neighborhood stressors in Model 4. We believe that these factors operate by affecting network development among neighbors, perceptions of social support in the neighborhood, and by providing resources to alleviate psychological distress.
We also explored whether neighborhood characteristics interact with individual-level characteristics to compound or buffer their effects. Our results demonstrate that high neighborhood violent crime amplifies the negative effect of violence exposure. Our results expand on the literature (Kawachi & Berkman 2001
) by demonstrating that neighborhood stress-buffering mechanisms may also interact with individual-level functional social support to protect against social isolation. However, we did not find that neighborhood stress-buffering mechanisms protect against effects of individual trauma (i.e., violence exposure). Based on these findings and results of previous research, we believe that higher household occupancy rates may contribute to better ADM outcomes by creating more opportunities for social interaction, particularly for those who lack social support, and encouraging the development of social ties among neighbors. However, our results suggest that neighborhood stability (median years lived in unit) may not be as important for social interaction and development of networks as has been suggested by social disorganization theory.
Even after controlling for neighborhood stressors, a significant effect remained for some neighborhood economic context variables on two outcomes. The result for depressive/anxiety disorders confirms results of previous studies that demonstrated no or a negative effect on likelihood. Likewise, although counter to what social disorganization theory suggests, the positive association between neighborhood income and likelihood of alcohol/substance abuse disorders has also been found by Ennett, et al. (1997)
. Compared with lower income areas, individuals in higher income neighborhoods may have more discretionary income with which to purchase “luxury” items such as alcohol and other illicit substances. Alternatively, although the model did include design variables that should account for non-response, these results could reflect either response or reporting bias (for example, people living in low income neighborhoods may be less likely to report substance abuse problems, or low income people with substance abuse problems may be more difficult to contact by telephone).
Finally, we caution readers to consider the following methodological issues. First, the response rate for HCC is relatively low. Although our models include design variables to account for oversampling and higher likelihood of attrition, and we adjust for individual-level characteristics that may be related to attrition, our results should not be considered conclusive. These analyses should be replicated using other nationally representative samples of adults before firm conclusions are drawn about the relationship between neighborhood characteristics and ADM disorders.
The second, and potentially most serious issue, is the possibility of selection effects. Others have cautioned that people with ADM disorders may choose or be forced as a result of circumstances to live in disadvantaged neighborhoods that not only lack stress-buffering mechanisms, but also have more environmental stressors. Less plausible but still a consideration is the possibility that migration of people with ADM disorders to certain neighborhoods actually causes neighborhood deterioration. Adjusting for individual socioeconomic characteristics, as our analyses do, should at least partially offset the effect of selection processes. In sensitivity analysis (not reported; contact first author for full results), we used the longitudinal component of HCC to investigate the possibility of selection effects.1
We explored whether people with ADM disorders were more likely to move, and whether movers with ADM disorders were more likely to move to worse neighborhoods. Our exploration found no evidence in support of selection effects due to ADM disorders. Other potential mechanisms, such as individual socioeconomic characteristics, should be explored in future research.
Another issue common to neighborhood effects research is how contextual effects may vary as a result of geographic conceptualization (Sampson, et al. 2002
; Pickett & Pearl 2001
; Robert 1999
). Neighborhood effects research is limited to the extent that the geographic “neighborhood” is defined by the entity that collects data on neighborhood characteristics. Thus, the neighborhood as operationalized may not correspond closely with the geographic area considered “the neighborhood” by its residents, making it more difficult to find neighborhood effects. One study that explored the differences due to size of geographic areas found almost no difference in the size of health differences by area characteristics when using larger versus smaller area definitions (Reijneveld, et al. 2000
). Nevertheless, because where boundaries are drawn is just as important as size of the geographic area considered “neighborhood”, we used data for the smallest geographic unit available, i.e., the Census tract, whenever possible. However, data on crime, churches per capita, and some of our neighborhood variables were not available at the Census tract level. We thus used data that was measured at the zip code and the county levels. Both ZIP codes and counties cover diverse areas, especially urban ones, that vary widely within each unit in terms of their size and the geographic level variables used here, since their boundaries are not drawn to create sociodemographically homogenous areas as are census tracts. This may have resulted in weaker effects than would have otherwise been found if boundaries were drawn to reflect “neighborhoods”. Future research on neighborhood effects should consider employing spatial techniques, such as hierarchical geostatistical modeling (Chaix et al. 2006
) that rely less on artificially imposed neighborhood boundaries and take into account characteristics of proximate neighborhoods.
A few other limitations should also be considered. First, crime rates may be biased towards underreporting because reporting jurisdictions don't provide complete reports and individuals don't report crimes. We addressed the first of these by eliminating jurisdictions that did not report crimes; however our results are vulnerable to underreporting by individuals. As a consequence, the relationship between crime rate and ADM disorders may be weaker than what would be expected with complete reporting. In addition, since we do not have a measure of congregation size or church attendance, number of churches per capita can only be considered a proxy variable for stress-buffering supports from religious institutions, and a stronger relationship may have been discovered if we had a more direct measure of contact with communities of faith. The number of ADM facilities in neighborhoods may be a poor approximation of access to care, given that health care coverage is not universal in the US. Finally, individuals with ADM disorders may be more likely to have negative perceptions of their neighborhoods, may be more sensitive to variations in neighborhood characteristics, and/or more vulnerable to neighborhood stressors. For example, some research has found that individuals with SMI are more likely to be victimized (Teplin et al. 2005
), which may account for the association between neighborhood characteristics and mental health. We used crime rates rather than fear of crime, which minimizes the risk of reverse causation.
Until our results are replicated with longitudinal data for neighborhood characteristics, they should be considered suggestive, rather than conclusive, evidence of a causal relationship. If replicated by future studies using longitudinal data, our results have implications for policies and programs targeting neighborhoods. First, our findings suggest that interventions targeting violence-exposed persons in high crime neighborhoods may reduce depressive/anxiety disorders. In fact, one program in Los Angeles, CA to address the consequences of violence exposure among school-aged children is showing promising preliminary results (Stein et al. 2003
; Kataoka et al. 2003
). In addition, our findings suggest that neighborhoods and housing can be designed to increase opportunities for social interaction and network development among neighbors, and this may be particularly important for people who lack social support. Some researchers examining the link between housing and health have suggested that housing guidelines and codes that encourage more social interaction should be developed and implemented (Kreiger & Higgins 2002; Ahrentzen 2003