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Paul L. Robinson, Norma Guzman-Becerra, Richard S. Baker Charles R. Drew University of Medicine and Science Didra Brown-Taylor, Integrated Substance Abuse.

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Presentation on theme: "Paul L. Robinson, Norma Guzman-Becerra, Richard S. Baker Charles R. Drew University of Medicine and Science Didra Brown-Taylor, Integrated Substance Abuse."— Presentation transcript:

1 Paul L. Robinson, Norma Guzman-Becerra, Richard S. Baker Charles R. Drew University of Medicine and Science Didra Brown-Taylor, Integrated Substance Abuse Programs, UCLA Ricky N. Bluthenthal, Charles Drew University RAND Alcohol Outlet Density vs. Distance to Preferred Outlet: Relationships with Overall Consumption in an Inner City Setting

2 Background Racial ethnic differences in drinking trends and alcohol problems. Significant differences in drinking patterns and problems. Whites in their 20’s African Americans in their 30’s and 50’s Hispanics in their 50’s Measures and observed effects of community exposure to alcohol outlets vary in significance and intensity. Given the importance of drinking cultures and drinking context, how is distance to preferred place of purchase associated with drinking quantity and frequency.

3 MLB Survey 329 respondent surveyed at 16 off-site liquor outlets in inner city Los Angeles 88% African American 72% Male 35% Unemployed 49% 39 or older 60% Earned less than $10,001 a year 57% Low employment rates 6% Homeless 39% On public assistance 56% Daily or near-daily drinkers 26% Alcohol treatment at least once 307 were geo-coded to nearest cross street from home address. Census tract of residence used to link neighborhood attributes of residence, including common alcohol accessibility measures Quantity and frequency of alcohol consumption index (90 days)

4 Methods Measures of accessibility Community characteristics OLS model

5 Geographic Measures of Alcohol Accessibility Accessibility to Alcohol Liquor Stores per sq. mile Liquor Stores roadway mile Liquor stores / 1000 persons Gravity based Accessibility model Distance from residence to outlet Straight line distances from nearest cross street to the respondents outlet

6 OLS model SAS PROC REG SAS PROC MIXED used for spatial adjustment Repeated measures of coordinate values Spherical covariance structure Lag distance 2.5-5 miles Type 3 test for fixed effects

7 Results Respondents represent a highly neighborhood based population living in a dense offsite outlet environment. (Mean distance to survey outlet = 1.4 miles, Mean outlet per square mile = 8.4) Distance to survey outlet was the sole predictor of 90 day reported quantity and frequency. Community characteristics don’t predict Common alcohol measures don’t predict

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9 Results Continued Variables with absolutely no significance: Gravity based accessibility model, Alcohol outlets per roadway mile, Alcohol outlets per square mile, Outlets per 1000 people, Percent White, Per capita income, Percent unemployed, Percent males unemployed, Percent Hispanic, Percent of Minorities, Percent of people living in poverty, Percent of people who own their home, Percent of vacant homes, Percent of people who are Spanish speaking, Spanish linguistic isolation, Foreign born, Residential stability, Average household size, Population density. Variable Significance and Beta Effect Direction Overall Model ANOVA.0002

10 Conclusion Within a sample of working class mostly middle-aged African American males, distance to preferred outlet is the single predictor of heavier drinking. This occurs independently of other commonly used alcohol availability measures such as density of outlets, outlets per person, outlets per roadway mile, and gravity model based accessibility surfaces as well as community racial, ethnic, and socio-economic characteristics.

11 Implications Alcohol consumption is linked to a variety of individual and environmental processes. A community systems perspective, which addresses the social, political, cultural, and economic influences upon individual drinking behaviors is required. This approach is particularly relevant in explaining and understanding drinking behaviors and trends found in isolated sub- populations such as the MLB survey respondents.


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