Concentrated disadvantage and mortality rates in chicago's 77 community areas

Concentrated disadvantage has emerged in the field of public health as a measure of neighborhood effects, capturing the notions that: social inequality exists between neighborhoods, especially in terms of race and SES; health problems tend to cluster in geographically defined units and are predicted by neighborhood characteristics; the relationship between community context and health outcomes persists even when individual-level risk factors are controlled. In order to examine the relationship between concentrated disadvantage and cause-specific mortality, we calculated 3-year average (2005-2007) age-adjusted mortality rates for Chicago and by Chicago community area (CA, n=77). Mortality rates per 100,000 population were calculated for several causes of death, revealing extensive variation across the city's CAs: heart disease (range: 141-372), cancer (110-295), stroke (23-104), and diabetes (7-68). We also performed a principal component analysis on six variables often used to create a measure of concentrated disadvantage: welfare receipt, poverty, unemployment, female-headed households, racial composition, and density of children. These indicators all loaded on a single principal component, concentrated disadvantage, which explains 76% of the variance across these items (Eigenvalue=4.6; next largest<0.75). The variables were thus summed to produce the concentrated disadvantage scores for each CA. The mortality rate for each cause of death was positively and statistically significantly correlated (r<0.64, p<0.0001) with the concentrated disadvantage scores. Data for each cause of death will be presented by CA in map form. We will also present the correlations between the concentrated disadvantage scores and the cause-specific mortality rates.