Evidence map›Paper›PMID 35752791›Full record

ArticleBMC public health2022

Spatial clustering of heroin-related overdose incidents: a case study in Cincinnati, Ohio.

Jung Im Choi, Jinha Lee, Arthur B Yeh, Qizhen Lan, Hyojung Kang

Open access · goldAbstract read
PubMed Full text at PMC Publisher
In one paragraph

Article in BMC public health, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers.

0numbers the graph read from it
0cells of the map it votes in
4citing papers in PubMed
1.6field-weighted citation impact, top 17% of its field
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

4 citing papers in PubMed, 12 citations in OpenAlex.

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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 at 2 institutions in 1 country.

Jung Im ChoiData Science, Bowling Green State University, 221 Hayes Hall, Bowling Green, OH, 43403, USA.
Jinha LeeFaculty of Public and Allied Health, Bowling Green State University, 111 Health and Human Services Building, Bowling Green, OH, 43403, USA. jinhal@bgsu.edu.
Arthur B YehFaculty of Applied Statistics and Operations Research, Bowling Green State University, 1001 E Wooster Street, Maurer Center 241J, Bowling Green, OH, 43403, USA.
Qizhen LanData Science, Bowling Green State University, 221 Hayes Hall, Bowling Green, OH, 43403, USA.
Hyojung KangFaculty of Kinesiology and Community Health, University of Illinois at Urbana-Champaign, 1206 Fourth Street, IL, 61820, Champaign, USA. hyokang@illinois.edu.
Bowling Green State University · USUniversity of Illinois Urbana-Champaign · US

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundDrug overdose is one of the top leading causes of accidental death in the U.S., largely due to the opioid epidemic. Although the opioid epidemic is a nationwide issue, it has not affected the nation uniformly.

methodsWe combined multiple data sources, including emergency medical service response, American Community Survey data, and health facilities datasets to analyze distributions of heroin-related overdose incidents in Cincinnati, Ohio at the census block group level. The Ripley's K function and the local Moran's I statistics were performed to examine geographic variation patterns in heroin-related overdose incidents within the study area. Then, conditional cluster maps were plotted to examine a relationship between heroin-related incident rates and sociodemographic characteristics of areas as well as the resources for opioid use disorder treatment.

resultsThe global spatial analysis indicated that there was a clustered pattern of heroin-related overdose incident rates at every distance across the study area. The univariate local spatial analysis identified 7 hot spot clusters, 27 cold spot clusters, and 1 outlier cluster. Conditional cluster maps showed characteristics of neighborhoods with high heroin overdose rates, such as a higher crime rate, a high percentage of the male, a high poverty level, a lower education level, and a lower income level. The hot spots in the Southwest areas of Cincinnati had longer distances to opioid treatment programs and buprenorphine prescribing physicians than the median, while the hot spots in the South-Central areas of the city had shorter distances to those health resources.

conclusionsOur study showed that the opioid epidemic disproportionately affected Cincinnati. Multi-phased spatial clustering models based on various data sources can be useful to identify areas that require more policy attention and targeted interventions to alleviate high heroin-related overdose rates.

Indexed as

Drug OverdoseHeroinAnalgesics, OpioidAnti-Inflammatory Agents, Non-SteroidalCluster AnalysisHumansMaleOhioSpatial AnalysisAnalgesics, OpioidAnti-Inflammatory Agents, Non-SteroidalHeroinClusteringDrug overdoseEmergency medical service response (EMS)Geospatial analysisHeroin-related incidentSocioeconomic factors

Identifiers

PMID35752791
PMCPMC9233379
OpenAlexW4283527507

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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.