Christina Mair1, Bridget Freisthler2, William R Ponicki3, Andrew Gaidus4. 1. University of Pittsburgh Graduate School of Public Health, Department of Behavioral and Community Health Sciences, 219 Parran Hall, 130 DeSoto Street, Pittsburgh, PA, 15261, USA; Prevention Research Center, 180 Grand Ave., Ste. 1200, Oakland, CA, 94612, USA. Electronic address: cmair@pitt.edu. 2. Prevention Research Center, 180 Grand Ave., Ste. 1200, Oakland, CA, 94612, USA; UCLA Luskin School of Public Affairs, Department of Social Welfare, 3250 Public Affairs Building, Box 951656, Los Angeles, CA, 90095, USA. Electronic address: freisthler@luskin.ucla.edu. 3. Prevention Research Center, 180 Grand Ave., Ste. 1200, Oakland, CA, 94612, USA. Electronic address: bponicki@prev.org. 4. Prevention Research Center, 180 Grand Ave., Ste. 1200, Oakland, CA, 94612, USA. Electronic address: agaidus@prev.org.
Abstract
BACKGROUND: As an increasing number of states liberalize cannabis use and develop laws and local policies, it is essential to better understand the impacts of neighborhood ecology and marijuana dispensary density on marijuana use, abuse, and dependence. We investigated associations between marijuana abuse/dependence hospitalizations and community demographic and environmental conditions from 2001 to 2012 in California, as well as cross-sectional associations between local and adjacent marijuana dispensary densities and marijuana hospitalizations. METHODS: We analyzed panel population data relating hospitalizations coded for marijuana abuse or dependence and assigned to residential ZIP codes in California from 2001 through 2012 (20,219 space-time units) to ZIP code demographic and ecological characteristics. Bayesian space-time misalignment models were used to account for spatial variations in geographic unit definitions over time, while also accounting for spatial autocorrelation using conditional autoregressive priors. We also analyzed cross-sectional associations between marijuana abuse/dependence and the density of dispensaries in local and spatially adjacent ZIP codes in 2012. RESULTS: An additional one dispensary per square mile in a ZIP code was cross-sectionally associated with a 6.8% increase in the number of marijuana hospitalizations (95% credible interval 1.033, 1.105) with a marijuana abuse/dependence code. Other local characteristics, such as the median household income and age and racial/ethnic distributions, were associated with marijuana hospitalizations in cross-sectional and panel analyses. CONCLUSIONS: Prevention and intervention programs for marijuana abuse and dependence may be particularly essential in areas of concentrated disadvantage. Policy makers may want to consider regulations that limit the density of dispensaries.
BACKGROUND: As an increasing number of states liberalize cannabis use and develop laws and local policies, it is essential to better understand the impacts of neighborhood ecology and marijuana dispensary density on marijuana use, abuse, and dependence. We investigated associations between marijuana abuse/dependence hospitalizations and community demographic and environmental conditions from 2001 to 2012 in California, as well as cross-sectional associations between local and adjacent marijuana dispensary densities and marijuana hospitalizations. METHODS: We analyzed panel population data relating hospitalizations coded for marijuana abuse or dependence and assigned to residential ZIP codes in California from 2001 through 2012 (20,219 space-time units) to ZIP code demographic and ecological characteristics. Bayesian space-time misalignment models were used to account for spatial variations in geographic unit definitions over time, while also accounting for spatial autocorrelation using conditional autoregressive priors. We also analyzed cross-sectional associations between marijuana abuse/dependence and the density of dispensaries in local and spatially adjacent ZIP codes in 2012. RESULTS: An additional one dispensary per square mile in a ZIP code was cross-sectionally associated with a 6.8% increase in the number of marijuana hospitalizations (95% credible interval 1.033, 1.105) with a marijuana abuse/dependence code. Other local characteristics, such as the median household income and age and racial/ethnic distributions, were associated with marijuana hospitalizations in cross-sectional and panel analyses. CONCLUSIONS: Prevention and intervention programs for marijuana abuse and dependence may be particularly essential in areas of concentrated disadvantage. Policy makers may want to consider regulations that limit the density of dispensaries.
Authors: Carla Alexia Campbell; Robert A Hahn; Randy Elder; Robert Brewer; Sajal Chattopadhyay; Jonathan Fielding; Timothy S Naimi; Traci Toomey; Briana Lawrence; Jennifer Cook Middleton Journal: Am J Prev Med Date: 2009-12 Impact factor: 5.043
Authors: Stephen E Lankenau; Loni Philip Tabb; Avat Kioumarsi; Janna Ataiants; Ellen Iverson; Carolyn F Wong Journal: Subst Use Misuse Date: 2019-06-03 Impact factor: 2.164