Shannon M Farley1, Andrew R Maroko2, Shakira F Suglia3, Lorna E Thorpe4. 1. 1 Bureau of Chronic Disease Prevention and Tobacco Control, New York City Department of Health and Mental Hygiene, Long Island City, NY, USA. 2. 2 Urban GISc Laboratory, Lehman College, Bronx, NY, USA. 3. 3 Rollins School of Public Health, Emory University, Atlanta, GA, USA. 4. 4 Department of Population Health, New York University, New York, NY, USA.
Abstract
OBJECTIVES: Researchers have identified associations between neighborhood-level factors (eg, income level, tobacco retailer density) and smoking behavior, but few studies have assessed these factors in urban environments. We explored the effect of tobacco retailer density, neighborhood poverty, and housing type (multiunit and public) on smoking in a large urban environment (New York City). METHODS: We used data on smoking prevalence and individual sociodemographic characteristics from the 2011-2013 New York City Community Health Survey, data on tobacco retailers from the 2012 New York City Department of Consumer Affairs, data on neighborhood sociodemographic characteristics and population density from the 2009-2013 American Community Survey, and data on multiunit and public housing from the 2012 New York City Primary Land Use Tax Lot Output data set. We used aggregate neighborhood-level variables and ordinary least squares regression, geographic weighted regression, and multilevel models to assess the effects of tobacco retailer density and neighborhood poverty on smoking prevalence, adjusting for sociodemographic characteristics (age, sex, race/ethnicity, and education) and neighborhood population density. We also assessed interactions between tobacco retailer density and poverty and each housing type on smoking. RESULTS: Neighborhood poverty positively and significantly modified the association between tobacco retailer density and prevalence of neighborhood smoking ( β = 0.003, P = .01) when we controlled for population density, sociodemographic characteristics, and types of housing. Neighborhood poverty was positively associated with the prevalence of individual smoking ( β = 0.0099, P < .001) when we adjusted for population density, sociodemographic characteristics, and type of housing. CONCLUSION: More research is needed to determine all the environmental factors associated with smoking prevalence in a densely populated urban environment.
OBJECTIVES: Researchers have identified associations between neighborhood-level factors (eg, income level, tobacco retailer density) and smoking behavior, but few studies have assessed these factors in urban environments. We explored the effect of tobacco retailer density, neighborhood poverty, and housing type (multiunit and public) on smoking in a large urban environment (New York City). METHODS: We used data on smoking prevalence and individual sociodemographic characteristics from the 2011-2013 New York City Community Health Survey, data on tobacco retailers from the 2012 New York City Department of Consumer Affairs, data on neighborhood sociodemographic characteristics and population density from the 2009-2013 American Community Survey, and data on multiunit and public housing from the 2012 New York City Primary Land Use Tax Lot Output data set. We used aggregate neighborhood-level variables and ordinary least squares regression, geographic weighted regression, and multilevel models to assess the effects of tobacco retailer density and neighborhood poverty on smoking prevalence, adjusting for sociodemographic characteristics (age, sex, race/ethnicity, and education) and neighborhood population density. We also assessed interactions between tobacco retailer density and poverty and each housing type on smoking. RESULTS: Neighborhood poverty positively and significantly modified the association between tobacco retailer density and prevalence of neighborhood smoking ( β = 0.003, P = .01) when we controlled for population density, sociodemographic characteristics, and types of housing. Neighborhood poverty was positively associated with the prevalence of individual smoking ( β = 0.0099, P < .001) when we adjusted for population density, sociodemographic characteristics, and type of housing. CONCLUSION: More research is needed to determine all the environmental factors associated with smoking prevalence in a densely populated urban environment.
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