BACKGROUND: Drug overdose deaths have risen to epidemic levels in the U.S. In 2015, the drug overdose mortality rate in Minnesota was 10.6 per 100,000 population: the sixth lowest rate in the U.S. However, in Minnesota, there are significant disparities in drug overdose mortality rates, particularly among American Indians (AI). To provide more detailed information regarding the risk factors and circumstances of drug overdose deaths in AI, the decision was made to include 2015 AI drug overdose deaths within the Minnesota Violent Death Reporting System (MNVDRS).
METHODS: Death certificates were used to identify unintentional AI drug overdose deaths with an ICD-10 underlying cause of death of X40-X44. These death certificates were then imported into MNVDRS. Data were abstracted from medical examiner records, law enforcement reports, and medical records to provide information regarding the risk factors, circumstances, and precipitating events that occurred before an unintentional drug overdose. These data were then analyzed and summarized.
RESULTS: In 2015, 41 drug overdose deaths in AI were identified; 39 were classified as unintentional; all were abstracted into the MNVDRS. Among AI, heroin was the most frequent drug cited in overdose deaths (44% among AI vs. 20% of all drug overdose deaths statewide). Toxicology results provided detailed descriptions of substances found, with a majority of decedents of all populations having more than one positive drug test. The median age of death among AI was 34.5 years, and younger than the overall median age of 44 years (p=0.0002). A number of the AI unintentional poisoning deaths were notable with regards to the manner of death, as the risk factors and circumstances resembled suicides.
CONCLUSIONS: Drug overdose deaths among AI occur at more than four times the rate of the overall population in Minnesota; decedents are younger, and have a higher prevalence of heroin, as well as other substances. Because of the findings and community concerns of an underreporting of suicide in AI, we created a suicide probability index based on the presence of the suicide risk factors of prior suicide ideation, attempt(s), and evidence of undiagnosed depression. This index will be used to enable a better understanding of these deaths and inform prevention measures.