TY - JOUR
T1 - Polysubstance Overdose Deaths in the Fentanyl Era
T2 - A Latent Class Analysis
AU - Park, Ju Nyeong
AU - Schneider, Kristin E.
AU - Fowler, David
AU - Sherman, Susan G.
AU - Mojtabai, Ramin
AU - Nestadt, Paul S.
N1 - Funding Information:
Drs. Park and Sherman are partially supported by the Johns Hopkins University Center for AIDS Research (1P30AI094189). Dr. Schneider was supported by a NIDA training grant (5T32DA007292). Dr. Nestadt is supported by the James Wah Foundation for Mood Disorders and the American Foundation for Suicide Prevention (YIG-0-093-18).
Publisher Copyright:
Copyright © 2022 American Society of Addiction Medicine.
PY - 2022/1/1
Y1 - 2022/1/1
N2 - Objectives:To elucidate the main latent classes of substances detected among overdose decedents, and latent class associations with age, sex, race, and jurisdiction of death in Maryland.Methods:We used toxicology data from the Office of the Chief Medical Examiner of Maryland for all decedents. We analyzed all cases of drug overdose deaths that occurred from 2016 to 2018 (N = 6566) using latent class analysis and regression.Results:Drug overdose deaths were concentrated in 2 of 24 counties in Maryland (Baltimore City and County). Fentanyl was involved in 71% of all drug overdose deaths, and the majority (76%) of these deaths included multiple substances. Three latent classes emerged: (1) fentanyl/heroin/cocaine (64%); (2) fentanyl/alcohol (18%); and (3) prescription drugs including opioids, benzodiazepines and antidepressants (18.0%). The fentanyl/heroin/cocaine class members were significantly younger (<30 years), female and White compared to the fentanyl/alcohol class, but more male and non-White than the prescription drugs class (all P < 0.05). Deaths in Baltimore City/County were more likely than in other locations to involve fentanyl/alcohol (P < 0.05).Conclusions:The majority of fentanyl-involved overdose deaths in Maryland involved multiple substances, and several demographic and geographic differences in these patterns emerged. Geographically-targeted interventions that are tailored to reduce the harms associated with polysubstance use (including cocaine, alcohol, and prescription drugs) for different demographic groups are warranted.
AB - Objectives:To elucidate the main latent classes of substances detected among overdose decedents, and latent class associations with age, sex, race, and jurisdiction of death in Maryland.Methods:We used toxicology data from the Office of the Chief Medical Examiner of Maryland for all decedents. We analyzed all cases of drug overdose deaths that occurred from 2016 to 2018 (N = 6566) using latent class analysis and regression.Results:Drug overdose deaths were concentrated in 2 of 24 counties in Maryland (Baltimore City and County). Fentanyl was involved in 71% of all drug overdose deaths, and the majority (76%) of these deaths included multiple substances. Three latent classes emerged: (1) fentanyl/heroin/cocaine (64%); (2) fentanyl/alcohol (18%); and (3) prescription drugs including opioids, benzodiazepines and antidepressants (18.0%). The fentanyl/heroin/cocaine class members were significantly younger (<30 years), female and White compared to the fentanyl/alcohol class, but more male and non-White than the prescription drugs class (all P < 0.05). Deaths in Baltimore City/County were more likely than in other locations to involve fentanyl/alcohol (P < 0.05).Conclusions:The majority of fentanyl-involved overdose deaths in Maryland involved multiple substances, and several demographic and geographic differences in these patterns emerged. Geographically-targeted interventions that are tailored to reduce the harms associated with polysubstance use (including cocaine, alcohol, and prescription drugs) for different demographic groups are warranted.
KW - drug use
KW - opioids
KW - substance use
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U2 - 10.1097/ADM.0000000000000823
DO - 10.1097/ADM.0000000000000823
M3 - Article
C2 - 33675604
AN - SCOPUS:85118506328
SN - 1932-0620
VL - 16
SP - 49
EP - 55
JO - Journal of Addiction Medicine
JF - Journal of Addiction Medicine
IS - 1
ER -