Your browser doesn't support javascript.
Identifying the changing age distribution of opioid-related mortality with high-frequency data.
Paul, Lauren A; Li, Ye; Leece, Pamela; Gomes, Tara; Bayoumi, Ahmed M; Herring, Jeremy; Murray, Regan; Brown, Patrick.
  • Paul LA; Health Protection, Public Health Ontario, Toronto, Ontario, Canada.
  • Li Y; Dalla Lana School of Public Health, University of Toronto, Toronto, Ontario, Canada.
  • Leece P; Knowledge Services, Public Health Ontario, Toronto, Ontario, Canada.
  • Gomes T; Dalla Lana School of Public Health, University of Toronto, Toronto, Ontario, Canada.
  • Bayoumi AM; Health Promotion, Chronic Disease and Injury Prevention, Public Health Ontario, Toronto, Ontario, Canada.
  • Herring J; Substance Use Service, Women's College Hospital, Toronto, Ontario, Canada.
  • Murray R; Department of Family and Community Medicine, University of Toronto, Toronto, Ontario, Canada.
  • Brown P; Li Ka Shing Knowledge Institute, St. Michael's Hospital, Toronto, Ontario, Canada.
PLoS One ; 17(4): e0265509, 2022.
Article in English | MEDLINE | ID: covidwho-1968853
ABSTRACT

BACKGROUND:

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.

METHODS:

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.

RESULTS:

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.

CONCLUSIONS:

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.
Subject(s)

Full text: Available Collection: International databases Database: MEDLINE Main subject: COVID-19 / Analgesics, Opioid Type of study: Experimental Studies / Observational study / Prognostic study / Randomized controlled trials Topics: Long Covid Limits: Adult / Female / Humans / Male / Middle aged Country/Region as subject: North America Language: English Journal: PLoS One Journal subject: Science / Medicine Year: 2022 Document Type: Article Affiliation country: Journal.pone.0265509

Similar

MEDLINE

...
LILACS

LIS


Full text: Available Collection: International databases Database: MEDLINE Main subject: COVID-19 / Analgesics, Opioid Type of study: Experimental Studies / Observational study / Prognostic study / Randomized controlled trials Topics: Long Covid Limits: Adult / Female / Humans / Male / Middle aged Country/Region as subject: North America Language: English Journal: PLoS One Journal subject: Science / Medicine Year: 2022 Document Type: Article Affiliation country: Journal.pone.0265509