Local spatial clustering in youths' use of tobacco, alcohol, and marijuana in Boston. (3rd July 2016)

• Record Type: Journal Article
• Authors: Duncan, Dustin T.; Rienti, Michael; Kulldorff, Martin; Aldstadt, Jared; Castro, Marcia C.; Frounfelker, Rochelle; Williams, James H.; Sorensen, Glorian; Johnson, Renee M.; Hemenway, David; Williams, David R.
• Is Part Of: American journal of drug and alcohol abuse. Volume 42:Number 4(2016:Jul.)
• Page Start: 412
• Page End: 421
• Publication Date: 2016-07-03
• Subjects: Spatial clustering -- drug use -- tobacco use -- alcohol use -- marijuana use -- youth; Drug abuse -- Treatment -- Periodicals; Alcoholism -- Treatment -- Periodicals; Substance-abuse -- Treatment -- Periodicals; Alcoholism -- Periodicals; Substance-Related Disorders -- Periodicals; 616.86
• DOI: 10.3109/00952990.2016.1151522
• Languages: English
• ISSNs: 0095-2990

Abstract

ABSTRACT: Background : Understanding geographic variation in youth drug use is important for both identifying etiologic factors and planning prevention interventions. However, little research has examined spatial clustering of drug use among youths by using rigorous statistical methods. Objectives : The purpose of this study was to examine spatial clustering of youth use of tobacco, alcohol, and marijuana. Methods : Responses on tobacco, alcohol, and marijuana use from 1, 292 high school students ages 13–19 who provided complete residential addresses were drawn from the 2008 Boston Youth Survey Geospatial Dataset. Response options on past month use included "none, " "1–2, " "3–9, " and "10 or more." The response rate for each substance was approximately 94%. Spatial clustering of youth drug use was assessed using the spatial Bernoulli model in the SatScan™ software package. Results : Approximately 12%, 36%, and 18% of youth reported any past-month use of tobacco, alcohol, and/or marijuana, respectively. Two clusters of elevated past tobacco use among Boston youths were generated, one of which was statistically significant. This cluster, located in the South Boston neighborhood, had a relative risk of 5.37 with a p -value of 0.00014. There was no significant localized spatial clustering in youth past alcohol or marijuana use in either the unadjusted or adjusted models. Conclusion : Significant spatial clustering in youth tobacco use was found. Finding a significant cluster in the South Boston neighborhood provides reason for further investigation into neighborhood characteristics that may shape adolescents' substance use behaviors. This type of research can be used to evaluate the underlying reasons behind spatial clustering of youth substance and to target local drug abuse prevention interventions and use.