1. 1 The Inequitable Distribution of Tobacco Outlets in Maryland: Race or Income? David O. Fakunle, BA Doctoral Student Johns Hopkins Bloomberg School of Public Health, Baltimore, MD

2. What is Tobacco Outlet Density? The physical availability of tobacco products in a given area – derived from alcohol outlet density Can be defined/measured in different ways based on geographical units – census tracts, miles/kilometers of roadway, neighborhood buffers, etc. Relatively new area of study in drug epidemiology research Predominantly investigated in relation to youth tobacco use Little research done to investigate relationships with demographic variables – Blacks, Latinos, and low-income individuals 2

3. Literature Review Previous Studies – Laws et. al (2002); Hyland et. al (2003); Peterson et. al (2005); Schneider et. al (2005) –Positive associations between underrepresented racial/ethnic concentrations and tobacco outlet density –Suggestion is that tobacco outlet density is highest among underrepresented racial/ethnic individuals Fakunle, Morton, & Peterson (2010) –Socioeconomic status (median household income) had the strongest relationship with tobacco outlet density, inclusive of race –Suggestion is that tobacco outlet density is highest among lower- income individuals, which tend to be from underrepresented racial/ethnic groups 3

4. Objective & Design Further investigate socioeconomic status – tobacco outlet density relationship by “isolating” race/ethnicity (natural stratification) Hypothesis: geopolitical area with the higher median household income will have a lower tobacco outlet density than the geopolitical area with the lower median household income, regardless of race Cross-sectional design Tobacco outlets: 2013 MD Judiciary Business License Population data: 2010 Decennial Census and 2007-2011 American Community Survey Geocoding: ArcMap Analyses: SPSS & Stata –Two-sample t-test –Spatial lag model Units of tobacco outlet density: –# tobacco outlets per inhabited census tract (raw) –# tobacco outlets per 1,000 persons per census tract (standardized) 4

5. Areas of Study CharacteristicBaltimore CityPrince George’s County Total Population620,644865,443 Median Household Income$43,571.20$77,190.01 Percentage of Incomes below Poverty Level 19.57%6.28% Black Population Percentage65.25%67.49% Number of Inhabited Census Tracts 199218 Mean Tobacco Outlets per 1,000 Persons per Census Tract 2.961.06 Tobacco Outlet Range per Residential Census Tract 0 – 740 – 20 5

6. Areas of Study CharacteristicBaltimore CountyMontgomery County Total Population807,318974,824 Median Household Income$71,021.06$106,485.56 Percentage of Incomes below Poverty Level 5.67%4.41% White Population Percentage69.41%62.45% Number of Inhabited Census Tracts 211215 Mean Tobacco Outlets per 1,000 Persons per Census Tract 1.300.82 Tobacco Outlet Range per Residential Census Tract 0 – 160 – 28 6

7. Areas of Study Social Classes Baltimore City: Working Class Baltimore County: Satisfied Middle Class Prince George’s County: Satisfied Middle Class Montgomery County: Upper Middle Class Morin, R. (2008, July 28). America’s Four Middle Classes. Retrieved from http://www.pewsocialtrends.org/2008/07/29/americas-four-middle- classes/ 7

8. T-Test Results Geopolitical Area Baltimore City Prince George’s County tdf Black Population Percentage (SD) 65.25% (34.62%)67.49% (24.79%)-0.76415 Median Household Income (SD) $43,571.20 ($23,286.28) $77,190.01 ($27,061.19) -13.52***414 Percentage of Incomes below Poverty Level (SD) 19.57% (14.47%)6.28% (5.80%)12.50***414 Mean Tobacco Outlets per 1,000 Persons per Census Tract (SD) 2.96 (2.75)1.06 (1.02)9.51***415 * p <.05. ** p <.01. *** p <.001 8

9. T-Test Results Geopolitical Area Baltimore CountyMontgomery Countytdf White Population Percentage (SD) 69.41% (27.48%)62.45% (20.45%)2.97***424 Median Household Income (SD) $71,021.06 ($25,828.83) $106,485.56 ($42,895.92) -10.29***421 Percentage of Incomes below Poverty Level (SD) 5.67% (5.49%)4.41% (4.71%)2.54*423 Mean Tobacco Outlets per 1,000 Persons per Census Tract (SD) 1.30 (1.51)0.82 (1.22)3.60***424 * p <.05. ** p <.01. *** p <.001 9

10. Why Spatial Lag Models? 10

11. Adjusted Spatial Lag Model Baltimore City Prince George's County Baltimore CountyMontgomery County βpβpβpβp Median Household Income -0.0360.001***-0.0090.001***-0.0130.004**-0.0080.001*** Area x Incomep = 0.005**p = 0.22 % Black-0.0180.019*0.0020.625-0.0060.1400.0000.966 % Latino0.0070.8080.0000.959-0.0300.239-0.0120.101 % with less than HS Diploma 0.0600.2170.0100.6950.0260.535-0.0380.348 * p <.05. ** p <.01. *** p <.001 11

12. Results of the analyses are consistent with our hypothesis: geopolitical areas with higher income level, despite similar racial concentration, had lower tobacco outlet density White geopolitical areas, when compared to economically relative Black geopolitical areas (i.e., higher vs. higher, lower vs. lower), consistently had significantly higher socioeconomic status (higher median household income, lower percentage of incomes below poverty level) and significantly lower tobacco outlet density Interpretations 12

13. Weaknesses & Strengths Weaknesses –Cross-sectional study: causation cannot be established Strengths –Suggests the link between socioeconomic status and tobacco outlet density is substantiated –Further clarifies the association between race and tobacco outlet density Contribution –Shows that a severely detrimental environmental substance is most available among the more economically and likely health- disadvantaged populations – may exacerbate health and economic disparities 13

14. Socioeconomic status matters in regards to the physical availability of tobacco products, but socioeconomic status is still defined within long- existing racial disparities –Rich and poor for Whites ≠ rich and poor for Blacks What are the mechanisms by which income inequality affects tobacco outlet density, as well as the physical availability of other potentially detrimental substances (alcohol, fast food)? How can income inequality be addressed? Discussion 14

15. Additional studies of similar design in other geographical areas –Geopolitical areas with similar Latino populations and differing income levels – but where? Investigate possible relationship with maladaptive behaviors of a criminal element (e.g. violence) – Reid et. al (2003) Presence of “underground” tobacco outlets in response to reduced density (e.g., CVS) – Stillman et. al (2014) Rise of electronic cigarettes and its presence within outlet- dense areas – Rose et. al, 2014; Wagoner et. al, 2014 Future Research 15

16. Acknowledgements Institutional National Research Service Award from the National Institute on Drug Abuse (NIDA), T32DA007292 Adam J. Milam, Ph.D., M.H.S. –Department of Mental Health – Johns Hopkins Bloomberg School of Public Health, Baltimore, MD –School of Medicine – Wayne State University, Detroit, MI C. Debra Furr-Holden, Ph.D. –Department of Mental Health – Johns Hopkins Bloomberg School of Public Health, Baltimore, MD James Butler III, DrPH, MEd –Department of Behavioral and Community Health – University of Maryland School of Public Health, College Park, MD Thomas A. LaVeist, Ph.D. –Department of Health Policy & Management – Johns Hopkins Bloomberg School of Public Health, Baltimore, MD 16

17. References Fakunle, D., Morton, C. M., & Peterson, N. A. (2010). The importance of income in the link between tobacco outlet density and demographics at the tract level of analysis in New Jersey. Journal of ethnicity in substance abuse, 9(4), 249-259. Hyland, A., Travers, M.J., Cummings, K.M., Bauer, J., Alford, T., & Wieczorek, W.F. (2003). Tobacco outlet density and demographics in Erie County, New York. American Journal of Public Health, 93(7), 1075-1076. LaVeist, T. A., & Wallace Jr, J. M. (2000). Health risk and inequitable distribution of liquor stores in African American neighborhood. Social science & medicine, 51(4), 613-617. Laws, M.B., Whitman, J., Bowser, D.M., & Krech, L. (2002). Tobacco availability and point of sale marketing demographically contrasting districts of Massachusetts. Tobacco Control, 2(11), 71-73. Peterson, N.A., Lowe, J.B., & Reid, R.J. (2005). Tobacco outlet density, cigarette smoking prevalence, and demographics at the county level of analysis. Substance Use and Misuse, 40(11), 1627-1635. Reid, R. J., Hughey, J., & Andrew Peterson, N. (2003). Generalizing the alcohol outlet-assaultive violence link: evidence from a US Midwestern city. Substance use & misuse, 38(14), 1971-1982. Rose, S. W., Barker, D. C., D'Angelo, H., Khan, T., Huang, J., Chaloupka, F. J., & Ribisl, K. M. (2014). The availability of electronic cigarettes in US retail outlets, 2012: results of two national studies. Tobacco Control, 23( 3), iii10-iii16. Schneider, J.E., Reid, R.J., Peterson, N.A., Lowe, J.B., & Hughey, J. (2005). Tobacco Outlet Density and demographics at the tract level of analysis in Iowa: Implications for environmentally based prevention initiatives. Prevention Science, 6(4), 319-325. Stillman, F. A., Bone, L. R., Milam, A. J., Ma, J., & Hoke, K. (2014). Out of View but in Plain Sight: The Illegal Sale of Single Cigarettes. Journal of Urban Health,91(2), 355-365. Wagoner, K. G., Song, E. Y., Egan, K. L., Sutfin, E. L., Reboussin, B. A., Spangler, J., & Wolfson, M. (2014). E-cigarette Availability and Promotion Among Retail Outlets Near College Campuses in Two Southeastern States. Nicotine & Tobacco Research, 1150-1155. 17