Evidence map›Paper›PMID 35442953›Full record

ArticlePloS one2022

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

Abstract read
In one paragraph

Article in PloS one, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.

0numbers the graph read from it
0cells of the map it votes in
2citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

2 citing papers in PubMed.

  1. Article
  2. Opioid-related deaths between 2019 and 2021 across 9 Canadian provinces and territories.CMAJ : Canadian Medical Association journal = journal de l'Association medicale canadienne · 2024
    Article
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

8 authors.

Lauren A PaulHealth Protection, Public Health Ontario, Toronto, Ontario, Canada.
Ye LiDalla Lana School of Public Health, University of Toronto, Toronto, Ontario, Canada.ORCID 0000-0001-6338-7474
Pamela LeeceDalla Lana School of Public Health, University of Toronto, Toronto, Ontario, Canada.ORCID 0000-0001-8374-6518
Tara GomesLi Ka Shing Knowledge Institute, St. Michael's Hospital, Toronto, Ontario, Canada.ORCID 0000-0002-1468-1965
Ahmed M BayoumiLi Ka Shing Knowledge Institute, St. Michael's Hospital, Toronto, Ontario, Canada.
Jeremy HerringKnowledge Services, Public Health Ontario, Toronto, Ontario, Canada.
Regan MurrayOffice of the Chief Coroner for Ontario, Toronto, Ontario, Canada.
Patrick BrownLi Ka Shing Knowledge Institute, St. Michael's Hospital, Toronto, Ontario, Canada.ORCID 0000-0003-2541-3744

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundOpioid-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.

methodsUsing 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.

resultsFrom 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.

conclusionsThis 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.

Indexed as

Analgesics, OpioidCOVID-19AdultAge DistributionBayes TheoremFemaleHumansMaleMiddle AgedMortalityOntarioPandemicsAnalgesics, Opioid

Identifiers

PMID35442953
PMCPMC9020746

What OpenQuestion holds

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LicenceCC BY
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Registered trials

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.