TY - JOUR
PY - 2020//
TI - Multivariate spatiotemporal modeling of drug- and alcohol-poisoning deaths in New York City, 2009-2014
JO - Spatial and spatio-temporal epidemiology
A1 - Ransome, Yusuf
A1 - Subramanian, S. V.
A1 - Duncan, Dustin T.
A1 - Vlahov, Daivid
A1 - Warren, Joshua
SP - e100306
EP - e100306
VL - 32
IS -
N2 - Drug- and alcohol-poisoning deaths remain current public health problems. Studies to date have typically focused on individual-level predictors of drug overdose deaths, and there remains a limited understanding of the spatiotemporal patterns and predictors of the joint outcomes. We use a hierarchical Bayesian spatiotemporal multivariate Poisson regression model on data from (N = 167) ZIP-codes between 2009 and 2014 in New York City to examine the spatiotemporal patterns of the joint occurrence of drug (opioids) and alcohol-poisoning deaths, and the covariates associated with each outcome.
RESULTS indicate that rates of both outcomes were highly positively correlated across ZIP-codes (cross-correlation: 0.57, 95% credible interval (CrI): 0.29, 0.77). ZIP-codes with a higher prevalence of heavy drinking had higher alcohol-poisoning deaths (relative risk (RR):1.63, 95% CrI: 1.26, 2.05) and drug-poisoning deaths (RR: 1.29, 95% CrI: 1.03, 1.59). These spatial patterns may guide public health planners to target specific areas to address these co-occurring epidemics.
Copyright © 2019 Elsevier Ltd. All rights reserved.
Language: en
LA - en SN - 1877-5845 UR - http://dx.doi.org/10.1016/j.sste.2019.100306 ID - ref1 ER -