Evidence map›Paper›PMID 39014350›Full record

ArticleBMC public health2024

Effect of wildfire on the prevalence of opioid misuse through anxiety among young adults in the United States: a modeling study.

Sigal Maya, Ali Mirzazadeh, James G Kahn

Abstract read
In one paragraph

Article in BMC public health, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
2citing papers in PubMed, 1 pooled it
–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

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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 synthesis or guideline pooled it.

  1. Pooled it
  2. Article
4 · The record

Corrections and comments

5 · Who and what money

Authors and funding

3 authors.

Sigal MayaPhilip R. Lee Institute for Health Policy Studies, University of California San Francisco, San Francisco, CA, USA. Sigal.Maya@ucsf.edu.
Ali MirzazadehDepartment of Epidemiology and Biostatistics, University of California San Francisco, San Francisco, CA, USA.
James G KahnPhilip R. Lee Institute for Health Policy Studies, University of California San Francisco, San Francisco, CA, USA.

Funding

Making Better Decisions: Policy Modeling for AIDS and Drug AbuseR37DA015612 · NIDA · STANFORD UNIVERSITY · PI DOUGLAS K OWENS · 2019 to 2026
$6.3M
NIDA NIH HHS R37 DA015612
6 · The paper itself

Abstract

backgroundExposure to climate change events like wildfires can lead to health and mental health problems. While conceptual frameworks have been hypothesized describing the potential relationship between disaster exposure and substance use, the association remains under-researched and unquantified.

methodsWe constructed a quantitative portrayal of one proposed conceptual framework that focuses on the intermediary role of anxiety. We used the Monte Carlo simulation to estimate the impact of wildfire exposure on opioid misuse outcomes through increased anxiety. We searched for and extracted prior empirical evidence on the associations between wildfire anxiety and anxiety-opioid misuse. Three scenarios were devised: in S1 the impact of wildfire on opioid misuse was limited to increasing anxiety incidence; in S2 we also considered the additive role of altered anxiety phenotype; and in S3 we further considered the role of increased opioid-related consequences of pre-existing anxiety due to wildfire exposure.

resultsModels show that the prevalence of opioid misuse post-wildfire may rise to 6.0%-7.2% from a baseline of 5.3%. In S1, the opioid misuse prevalence ratio was 1.12 (95% uncertainty interval [UI]: 1.00 - 1.27). The two exploratory scenarios, with less stringent assumptions, yielded prevalence ratios of 1.23 (95% UI: 1.00 - 1.51) and 1.34 (95% UI: 1.11 - 1.63).

conclusionsOur modeling study suggests that exposure to wildfires may elevate opioid misuse through increasing anxiety incidence and severity. This can lead to substantial health burdens, possibly beyond the duration of the wildfire event, which may offset recent gains in opioid misuse prevention.

Indexed as

AnxietyOpioid-Related DisordersWildfiresAdolescentAdultFemaleHumansMaleMonte Carlo MethodPrevalenceUnited StatesYoung AdultAnxietyOpioid useSubstance useWildfire

Identifiers

PMID39014350
PMCPMC11253393

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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.