Evidence map›Paper›PMID 40214702›Full record

ArticleSocial psychiatry and psychiatric epidemiology2025

Associations of community socioeconomic factors and opioid use disorder across an urban-to-rural spectrum in Pennsylvania: an electronic health record-based case-control study.

Melissa N Poulsen, Cara M Nordberg, Joseph DeWalle, Meghann Reeder, Wade Berrettini, Brian S Schwartz

Abstract read
In one paragraph

Article in Social psychiatry and psychiatric epidemiology, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing 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

1 citing paper in PubMed.

  1. Article
4 · The record

Corrections and comments

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5 · Who and what money

Authors and funding

6 authors.

Melissa N PoulsenDepartment of Population Health Sciences, Geisinger College of Health Sciences, Danville, PA, USA. mpoulsen@geisinger.edu.ORCID http://orcid.org/0000-0002-5915-371X
Cara M NordbergDepartment of Population Health Sciences, Geisinger College of Health Sciences, Danville, PA, USA.ORCID http://orcid.org/0000-0003-2317-5332
Joseph DeWalleDepartment of Population Health Sciences, Geisinger College of Health Sciences, Danville, PA, USA.ORCID http://orcid.org/0000-0002-2053-737X
Meghann ReederDepartment of Population Health Sciences, Geisinger College of Health Sciences, Danville, PA, USA.ORCID http://orcid.org/0009-0005-1142-9480
Wade BerrettiniDepartment of Psychiatry, University of Pennsylvania Perelman School of Medicine, Philadelphia, PA, USA.ORCID http://orcid.org/0000-0001-8445-5165
Brian S SchwartzDepartment of Population Health Sciences, Geisinger College of Health Sciences, Danville, PA, USA.ORCID http://orcid.org/0000-0002-0739-9865

Funding

Understanding the role of community determinants in opioid use disorder and program implementation factors influencing patient adherence to opioid agonist therapyK01DA049903 · NIDA · GEISINGER CLINIC · PI POULSEN, MELISSA · 2020 to 2024
$810k
NIDA NIH HHS K01 DA049903NIDA NIH HHS K01DA049903
6 · The paper itself

Abstract

purposeTo elucidate the role of community socioeconomic conditions in creating opioid-related risk environments, we assessed community-level socioeconomic measures in association with opioid use disorder (OUD) across a diverse geography.

methodsWe conducted a case-control study using medical records (2012-2020) from a Pennsylvania health system to identify cases of OUD (n = 14,674) and controls (n = 58,696; frequency-matched on age, sex, year, medical record duration). Residential addresses were used to assign community-level measures: community socioeconomic deprivation (CSD), high proportional housing costs (HPHC), population in service occupations (PSO), and community credit score (CCS). Logistic regression analyzed associations of community type (city census tracts [CCT], boroughs, townships) and community socioeconomic features (stratified by community type) with OUD, adjusting for demographics and individual-level socioeconomic status.

resultsCCT or borough (versus township) residence was associated with higher OUD odds. CSD, HPHC, and CCS were associated with OUD across community types; PSO was only associated in CCTs. The highest (versus lowest) level of CSD was associated (odds ratio, 95% CI) with higher OUD odds among individuals in townships (1.18 [1.03, 1.36]), boroughs (1.34 [1.09, 1.63]), and CCTs (1.46 [1.13, 1.88]). "Good" (versus "high fair") CCS was associated with lower odds in townships (0.78 [0.71, 0.86]), boroughs (0.56 [0.41, 0.77]), and CCTs (0.73 [0.44, 1.22]).

conclusionFindings indicate poor community socioeconomic conditions are related to higher OUD risk, highlight the value of research regarding opioid-related risk environments, and suggest structural and policy interventions, such as vocational training and rent subsidies, as important for addressing the root causes of OUD.

Indexed as

Neighborhood CharacteristicsOpioid-Related DisordersResidence CharacteristicsRural PopulationSocioeconomic FactorsUrban PopulationAdultCase-Control StudiesElectronic Health RecordsFemaleHumansMaleMiddle AgedPennsylvaniaRisk FactorsCredit scoresElectronic health recordsEmploymentHousingOpioid-related disordersSocioeconomic factors

Identifiers

PMID40214702
PMCPMC12284836

What Socratic holds

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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 Socratic graph.