Neighbourhood characteristics and health outcomes: evaluating the association between socioeconomic status, tobacco store density and health outcomes in Baltimore City.

INTRODUCTION: Several studies suggest that the health of an individual is influenced by the socioeconomic status (SES) of the community in which he or she lives. This analysis seeks to understand the relationship between SES, tobacco store density and health outcomes at the neighbourhood level in a large urban community. METHODS: Data from the 55 neighbourhoods of Baltimore City were reviewed and parametric tests compared demographics and health outcomes for low-income and high-income neighbourhoods, defined by the 50th percentile in median household income. Summary statistics are expressed as median. Tobacco store density was evaluated as both an outcome and a predictor. Association between tobacco store densities and health outcomes was determined using Moran's I and spatial regression analyses to account for autocorrelation. RESULTS: Compared with higher-income neighbourhoods, lower-income neighbourhoods had higher tobacco store densities (30.5 vs 16.5 stores per 10 000 persons, P=0.01), lower life expectancy (68.5 vs 74.9 years, P<0.001) and higher age-adjusted mortality (130.8 vs 102.1 deaths per 10 000 persons, P<0.001), even when controlling for other store densities, median household income, race, education status and age of residents. CONCLUSION: In Baltimore City, median household income is inversely associated with tobacco store density, indicating poorer neighbourhoods in Baltimore City have greater accessibility to tobacco. Additionally, tobacco store density was linked to lower life expectancy, which underscores the necessity for interventions to reduce tobacco store densities.

The effect of community socioeconomic status on sepsis-attributable mortality.

PURPOSE: Community factors may play a role in determining individual risk for sepsis, as well as sepsis-related morbidity and mortality. We sought to define the relationship between community socioeconomic status and mortality due to sepsis in an urban locale. METHODS: Using community statistical areas of Baltimore City, we dichotomized neighborhoods at median household income, and compared distribution of outcomes of interest within the two income categories. We performed multivariable regression analyses to determine the relationship between socioeconomic variables and sepsis-attributable mortality. RESULTS: The collective median household income was $38,660 (IQR $32,530, 54,480), family poverty rate was 28.4% (IQR 13.5, 38.8%), and rate of death from sepsis was 3.1 per 10,000 persons (IQR 2.60, 4.10). Lower household income communities demonstrated higher rates of death from sepsis (3.65 (IQR 2.78, 4.40)) than higher household income communities (2.80 (IQR 2.05, 3.55)) (p = .02). In regression models, household income (ß = -8.42, p = .006) and percentage of poverty in communities (ß = 2.71, p = .01) demonstrated associations with sepsis-attributable mortality. DISCUSSION: Our findings suggest that socioeconomic variables play significant role in sepsis-attributable mortality. Such confirmation of regional disparities in mortality due to sepsis warrants further consideration, as well as integration, for future national sepsis policies.