Evidence map›Paper›PMID 40242321›Full record

ArticleLancet regional health. Americas2025

Spatiotemporal analysis of substance use disorder mortality in the United States: an observational study of emerging hotspots and vulnerable populations (2005-2020).

Santiago Escobar, Neil J MacKinnon, Preshit Ambade, Zach Hoffman, Diego F Cuadros

Abstract read
In one paragraph

Article in Lancet regional health. Americas, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.

0numbers the graph read from it
0cells of the map it votes in
3citing 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

3 citing papers in PubMed.

  1. Article
  2. Article
  3. 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

5 authors.

Santiago EscobarDigital Epidemiology Laboratory, Digital Futures, University of Cincinnati, Cincinnati, OH, USA.
Neil J MacKinnonCollege of Medicine, Central Michigan University, Mount Pleasant, MI, USA.
Preshit AmbadeCollege of Medicine, Central Michigan University, Mount Pleasant, MI, USA.
Zach HoffmanCollege of Medicine, Central Michigan University, Mount Pleasant, MI, USA.
Diego F CuadrosDigital Epidemiology Laboratory, Digital Futures, University of Cincinnati, Cincinnati, OH, USA.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Background: The escalating substance use disorder (SUD) crisis in the contiguous United States (US), with rising mortality since 1999, necessitates a spatiotemporal analysis to identify high-risk areas and vulnerable populations. This study examines the geospatial distribution and clustering patterns of SUD mortality, assessing disparities by race and urban-rural status. Methods: We analyzed county-level ecological data on SUD-related deaths from the Centers for Disease Control and Prevention (CDC) from 2005 to 2020. Using spatial scan statistics, we identified significant clusters of elevated SUD mortality and assessed shifts over time. The analysis stratified results by race (White and Black subpopulations) and urban-rural classification to explore disparities. Findings: Among 3142 U.S. counties, we identified 27 significant spatiotemporal clusters of elevated SUD mortality, primarily emerging post-2013 and persisting until 2020. The epidemic's epicenter shifted from the western to the eastern U.S. around 2016. Clusters in the White population (n = 26) had an estimated mortality rate of 28.42 per 100,000 person-years (95% confidence interval [CI]: 28.30-28.54), compared to 14.83 per 100,000 person-years (95% CI: 14.74-14.92) outside clusters. For the Black population (n = 17), the mortality rate was 33.16 per 100,000 person-years (95% CI: 32.80-33.51) within clusters, versus 13.36 per 100,000 person-years (95% CI: 13.14-13.59) outside. Clusters in the Black population emerged later, mostly after 2013, while White clusters followed a pattern similar to the general population. The urban SUD mortality rate was 1.30 per 10,000 per year, while the rural mortality rate was 1.03 per 10,000 per year. Within clusters, urban counties had a mortality rate of 1.61 per 10,000, compared to 0.97 per 10,000 outside. Rural counties had 1.43 per 10,000 in clusters, while non-clustered rural areas had 0.81 per 10,000. Interpretation: The shifting geographic and racial patterns of SUD mortality underscore the need for targeted, region-specific interventions. The increasing impact on Black populations and urban centers in the East highlights the importance of equitable access to treatment and harm reduction services. Real-time surveillance and tailored urban-rural strategies are essential to mitigate the evolving crisis. Funding: None.

Indexed as

AddictionLongitudinal studiesOverdoseScan statisticsSpatial epidemiologySpatiotemporal clusteringSubstance use disorder mortality

Identifiers

PMID40242321
PMCPMC12003021

What OpenQuestion holds

Textmetadata
LicenceCC BY
Read underepoch 390

Registered trials

None linked

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.