A Multilevel Decomposition Approach to Estimate the Role of Program Location and Neighborhood Disadvantage in Racial Disparities in Alcohol Treatment Completion
Published In: Social Science and Medicine, v. 64, no. 2, Jan. 2007, p. 462-476
Posted on RAND.org on January 01, 2007
Large racial disparities in completion rates from substance abuse treatment programs in urban settings remain largely unexplained, although evidence is accumulating that neighborhood conditions may influence individual substance abuse patterns and consequences. Understanding racial disparities in alcohol treatment completion, in particular, is crucial to resolving health disparities because racial/ethnic minorities bear a disproportionate burden of alcohol-related health consequences. Patient records for all non-homeless African American (N=1677), Hispanic (N=1635), and white (N=1216) alcohol outpatients, ages 18 or older, discharged during 1998-2000 from publicly funded treatment programs in Los Angeles County, the second largest system of publicly funded substance abuse treatment in the United States, were combined with census data. The authors tested the hypothesis that racial differences in treatment completion are related to differences in neighborhood context, particularly neighborhood-level disadvantage. Estimates from multilevel statistical models indicate that treatment neighborhood disadvantage is independently associated with treatment completion after controlling for patient characteristics and facility- and zip code-level random effects. Results of a Oaxaca decomposition of the regression estimates indicate that racial differences in treatment neighborhood disadvantage account for 32.3% of African American-white differences in treatment completion. Hispanic-white differences in completion, and the effect of home neighborhood disadvantage on completion, were non-significant. We conclude that the location of publicly funded alcohol treatment programs is related to racial disparities in treatment completion, but additional research is necessary to understand the mechanism behind this association.