Identifying the changing age distribution of opioid-related mortality with high-frequency data

|| Lauren A. Paul, Ye Li, Pamela Leece, Tara Gomes, Ahmed M. Bayoumi, Jeremy Herring, Regan Murray, Patrick Brown ||


Opioid-related mortality continues to rise across North America, and mortality rates have been further exacerbated by the COVID-19 pandemic. This study sought to provide an updated picture of trends of opioid-related mortality for Ontario, Canada between January 2003 and December 2020, in relation to age and sex.


Using mortality data from the Office of the Chief Coroner for Ontario, we applied Bayesian Poisson regression to model age/sex mortality per 100,000 person-years, including random walks to flexibly capture age and time effects. Models were also used to explore how trends might continue into 2022, considering both pre- and post-COVID-19 courses.


From 2003 to 2020, there were 11,633 opioid-related deaths in Ontario. A shift in the age distribution of mortality was observed, with the greatest mortality rates now among younger individuals. In 2003, mortality rates reached maximums at 5.5 deaths per 100,000 person-years (95% credible interval: 4.0–7.6) for males around age 44 and 2.2 deaths per 100,000 person-years (95% CI: 1.5–3.2) for females around age 51. As of 2020, rates have reached maximums at 67.2 deaths per 100,000 person-years (95% CI: 55.3–81.5) for males around age 35 and 16.8 deaths per 100,000 person-years (95% CI: 12.8–22.0) for females around age 37. Our models estimate that opioid-related mortality among the younger population will continue to grow, and that current conditions could lead to male mortality rates that are more than quadruple those of pre-pandemic estimations.


This analysis may inform a refocusing of public health strategy for reducing rising rates of opioid-related mortality, including effectively reaching both older and younger males, as well as young females, with health and social supports such as treatment and harm reduction measures.

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