Evidence map›Paper›PMID 41723457›Full record

ArticleHarm reduction journal2026

The geography of risk: understanding disparities in nonmedical opioid mortality and the role of socio-built environments in New Jersey.

Barbara Tempalski, Chunki Fong, Sean T Doyle, Danielle C Ompad

Abstract read
In one paragraph

Article in Harm reduction journal, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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

0 citing papers in PubMed.

No citing paper in PubMed yet.

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

4 authors.

Barbara TempalskiCenter for Community-Based Population Health Research, National Development & Research Institutes - USA (NDRI-USA), Inc., 31 West 34th Street, New York, NY, 10001, USA. tempalski@ndri-usa.org.
Chunki FongNDRI-USA. Inc., Institute for Implementation Science in Population Health, CUNY Graduate School of Public Health & Health Policy, New York, NY, 10027, USA.
Sean T DoyleNDRI-USA, Inc., Social Sciences Innovations Corporation, Colorado Springs, CO, 80927, USA.
Danielle C OmpadCenter for Drug Use and HIV, HCV Research, New York University School of Global Public Health, 708 Broadway, New York, NY, 10003, USA.

Funding

Transdisciplinary Theoretical Svnthesis and Development CoreP30DA011041 · NIDA · NEW YORK UNIVERSITY · PI Holly Hagan · 1998 to 2026
$38.9M
Developing a public health measure of built environment to assess risk of nonmedical opioid use and related mortality in urban and non-urban areas in New JerseyR21DA046739 · NIDA · NDRI-USA, INC. · PI TEMPALSKI, BARBARA · 2020 to 2021
$393k
Center for Drug Use and HIV Research P30DA011041NIDA NIH HHS P30 DA011041NIDA NIH HHS R21 DA046739NIDA NIH HHS R21DA046739
6 · The paper itself

Abstract

backgroundDisparities in nonmedical opioid (NMO) mortality reflect a shifting geography of risk that presents urgent public health challenges. This study uses a socio-built environment (SBE) framework to investigate how place-based conditions shape NMO-related risks across urban, suburban, and rural municipalities in New Jersey.

methodsSix SBE domains with multiple indicators were analyzed. Generalized linear models with a negative binomial distribution examined associations with NMO mortality, estimating incidence rate ratios with 95% confidence intervals. Domain-level contributions were assessed using log-likelihood ratio chi-square tests, with models stratified by geographies.

resultsThe quality of residential, commercial, and community economic engagement domains contributed significantly to NMO mortality across all municipalities. The physical environment, community participation, and spatial access to opioid health programs domains were more influential in urban settings, with weaker or inconsistent effects in suburban and rural areas. Foreclosure rates, vacant storefronts, liquor license density, and greater economic distress were positively associated with mortality risk, while housing stability, business density, and higher per capita income were protective. Suburban and rural municipalities showed the largest disparities in mortality risk, with distances to naloxone sites nearly eight times greater than in urban areas (IRR = 7.88, p = 0.003). Urban municipalities benefited from closer proximity to syringe access programs, which was associated with reduced mortality risk (IRR = 0.92, p = 0.011).

conclusionDisparities in NMO mortality are shaped by SBEs that vary across urban, suburban, and rural municipalities. Housing instability, economic distress, and spatial access gaps in opioid health programs consistently contributed to elevated mortality, while stronger local economies and more stable housing were protective. These findings underscore that the risk of overdose mortality emerges through place-based conditions and call for strategies responsive to local SBEs, expanding affordable housing, strengthening community economies, and improving spatial access to harm reduction and treatment services across diverse geographic settings, as demonstrated in New Jersey.

Indexed as

Drug OverdoseOpiate OverdoseOpioid-Related DisordersHumansNew JerseyResidence CharacteristicsRural PopulationSocioeconomic Disparities in HealthSocioeconomic FactorsUrban PopulationHousing instabilityNonmedical opioid mortalityOpioid use–related health servicesSocial and built environmentsUrban–suburban–rural disparities

Identifiers

PMID41723457
PMCPMC13393885

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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.