Urban neighborhoods, chronic stress, gender and depression☆
Introduction
The idea that features of the social environment in which we live are important determinants of healthy lives is not new. In one of the earliest studies on environment and mental health, Faris and Dunham (1939) showed that psychiatric admissions in Chicago varied by location within the city with higher rates for those living in the inner-city core than in outlying areas. The ecological approach to the study of health was largely supplanted by individualistic approaches, but more recently the hybrid approach of multilevel modeling has become more popular. Historical and modern writings advocate for population-level studies of health, reasoning that while risk factors originate in individuals (compostional effects), many of these risks propagate and become reinforced within social contexts (contextual effects), especially risks associated with health and health-related behavior. Durkheim (1951) studied the social causes of suicide and found regularities in suicide rates among specific population groups. He argued that social integration and regulation, characteristics of the social environment rather than the individual, contributed to the suicide rate in a particular group thus producing differences from the rate in other groups. According to Dunn, Frohlich, Ross, Curtis, and Sanmartin (2005) social facts may provide details on the uniqueness of specific places and particularly those stressors that influence, enhance and undermine the health of the population. They argue that it is imperative to examine these underlying phenomena to inform a global discussion of population health. Geoffrey Rose (1985) argued that groups of individuals function as a collectivity and these groups are affected by the average functioning of the group. Multilevel modeling allows researchers to simultaneously study individual and contextual effects and to ask questions about the relationship between neighborhood and personal health.
Section snippets
The nature of chronic stress in context
So what is it about the social environment that might lead to deterioration in the health of individuals? One issue, often identified, is chronic stressors in the local residential environment. In the social science literature contextual features such as crowding (Gillis, 1979a; Gillis, Richard, & Hagan, 1986), density, (Gillis (1974), Gillis (1979b); Gillis & Hagan, 1982; Regoeczi, 2002; Sampson, 1983) and housing (Dunn, 2002; Dunn & Hayes, 2000; Gillis, 1977) have been examined as sources of
Gender and neighborhood chronic stress
The stress process model posits that social status determines one's position in the social structure, and thus the types and intensity of stressors to which one is exposed. Gender is recognized as a status position that organizes our lives and frames our access to personal and social resources primarily because gender encompasses both biological/genetic and social learning differences. Explanations of gender differences in depression, with women at greater risk, reflect both sex-related
Research questions
This paper addresses the four following research questions:
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Is neighborhood stress correlated with higher risk of depression?
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To what extent does chronic stress account for neighborhood variation in depression?
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Does the association of neighborhood chronic stress remain after controlling for individual characteristics, neighborhood ethnic diversity and dependency?
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Is neighborhood chronic stress associated with gender differences in depression?
Data sources
Two data sources were used to investigate the association between neighborhood context and depression—the Canadian Community Health Survey (CCHS) and the 2001 census of Canada, both collected by Statistics Canada. The CCHS is a cross-sectional nationally representative survey that provides detailed information on health determinants and health outcomes (see Beland, 2002 for detailed methodology). Two cycles of the CCHS (cycle 1.1 and cycle 2.1 collected in 2000–2001 and 2003–2004, respectively)
Descriptive statistics
Correlations among the factors and their components are presented in the third column of Table 1. Correlations among residential instability and its component measures range from 0.67 to 0.95; those for the components of material deprivation range from 0.52 to 0.88; those for the components of dependency range from 0.82 to 0.91; and those between ethnic diversity and its components range from 0.92 to 0.94.
As shown in Table 2 the prevalence of depression in the sample was 9% ().
Discussion
Rose (1985) argues that we should shift some of our focus from treatment and prevention at the individual level to prevention for “sick populations”. In this study we asked: “Why do some neighborhoods have more depression than others”? We argued that at least part of the answer might lie in the existence of chronic stressors in the local residential environment. Identification of chronic stressors that may be uncontrollable at the individual-level, but which are embedded in the social and
Limitations
Census variables are commonly used to characterize neighborhoods, but they tend to be relatively non-specific. Better measures are required to elucidate pathways and provide opportunities for intervention. A shortcoming of this research is that our exploration of neighborhood chronic stressors and their impact on depression was restricted to urban centers. Much of rural Canada is not tracted so census characteristics cannot be ascribed to these areas at the same geographic level. Census
Conclusions
Rose (1985) and Weich (1997) emphasize that approaches to prevention and treatment need to go beyond the individual to the level of the population and have suggested that prevention and treatment within the community or neighborhood should be considered, not as an alternative to clinical practice, but as an approach to improve the general health of a large network of people. Studies that employ multilevel methods will assist in this endeavor through identification of communities and
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This research was made possible through the assistance of the Social Sciences and Humanities Research Council of Canada, Standard Research Grant 410-2005-2306.