Neighbourhood characteristics and health outcomes: evaluating the association between socioeconomic status, tobacco store density and health outcomes in Baltimore City. Issue Volume 27:Issue e1(2018) (23rd November 2017)

• Record Type: Journal Article
• Authors: Galiatsatos, Panagis; Kineza, Cynthia; Hwang, Seungyoun; Pietri, Juliana; Brigham, Emily; Putcha, Nirupama; Rand, Cynthia S; McCormack, Meredith; Hansel, Nadia N
• Is Part Of: Tobacco control. Volume 27:Issue e1(2018)
• Page Start: e19
• Page End: e24
• Publication Date: 2017-11-23
• Subjects: advocacy -- disparities -- priority/special populations -- socioeconomic status; Tobacco use -- Prevention -- Periodicals; Tobacco use -- Periodicals; Smoking -- Law and legislation -- Periodicals; Smoking -- prevention & control -- Periodicals; Tobacco Use Disorder -- prevention & control -- Periodicals; Tobacco -- Periodicals; Electronic journals; 613.85
• DOI: 10.1136/tobaccocontrol-2017-053945
• Languages: English
• ISSNs: 0964-4563

Abstract

Abstract : 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.