The DOI matches its Crossref record; 47 of the 47 references it cites were found in a registry or an index.
Intertwined Epidemics: National Demographic Trends in Hospitalizations for Heroin- and Opioid-Related Overdoses, 1993–2009
Open accessAbstract
The historical patterns of opiate use show that sources and methods of access greatly influence who is at risk. Today, there is evidence that an enormous increase in the availability of prescription opiates is fuelling a rise in addiction nationally, drawing in new initiates to these drugs and changing the geography of opiate overdoses. Recent efforts at supply-based reductions in prescription opiates may reduce harm, but addicted individuals may switch to other opiates such as heroin. In this analysis, we test the hypothesis that changes in the rates of Prescription Opiate Overdoses (POD) are correlated with changes in the rate of heroin overdoses (HOD). ICD9 codes from the Nationwide Inpatient Sample and population data from the Census were used to estimate overall and demographic specific rates of POD and HOD hospital admissions between 1993 and 2009. Regression models were used to test for linear trends and lagged negative binomial regression models were used to model the interrelationship between POD and HOD hospital admissions. Findings show that whites, women, and middle-aged individuals had the largest increase in POD and HOD rates over the study period and that HOD rates have increased in since 2007. The lagged models show that increases in a hospitals POD predict an increase in the subsequent years HOD admissions by a factor of 1.26 (p<0.001) and that each increase in HOD admissions increase the subsequent years POD by a factor of 1.57 (p<0.001). Our hypothesis of fungibility between prescription opiates and heroin was supported by these analyses. These findings suggest that focusing on supply-based interventions may simply lead to a shift in use to heroin rather minimizing the reduction in harm. The alternative approach of using drug abuse prevention resources on treatment and demand-side reduction is likely to be more productive at reducing opiate abuse related harm.
Overview
The claims and statistics of this paper haven’t been checked yet.
Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.
Integrity signals
Registry
Cites
Statistics
Verification
Claims the paper makes
The claims and statistics of this paper haven’t been checked yet.
Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.
Self-check
Percentages, sums and reported differences re-computed from the paper’s own numbers.
The self-check needs the paper’s full text.
Citations
Cites
National Center for Health Statistics ( NCHS )
Feinleib, M. (2005) · Encyclopedia of Biostatistics · doi:10.1002/0470011815.b2a16042 · Cited by 1,574
Vital signs: overdoses of prescription opioid pain relievers---United States, 1999--2008.
Paulozzi, L. J., Jones, C. M., Mack, K. A., & Rudd, R. A. (2011) · PubMed · Cited by 1,364
The Agency for Healthcare Research and Quality
Baine, W. B. (2006) · Italian Journal of Public Health · doi:10.2427/5924 · Cited by 1,191
A Flood of Opioids, a Rising Tide of Deaths
Okie, S. (2010) · New England Journal of Medicine · doi:10.1056/nejmp1011512 · Cited by 830
Trends in Opioid Prescribing by Race/Ethnicity for Patients Seeking Care in US Emergency Departments
Pletcher, M. J., Kertesz, S. G., Kohn, M. A., & Gonzales, R. (2008) · JAMA · doi:10.1001/jama.2007.64 · Cited by 827
Vital signs: overdoses of prescription opioid pain relievers---United States, 1999--2008.
(2011) · PubMed · Cited by 640
IMS Institute for Healthcare Informatics
Evans, R. (2014) · Nursing Standard · doi:10.7748/ns2014.04.28.32.30.s36 · Cited by 594
Initiation into prescription opioid misuse amongst young injection drug users
Lankenau, S. E., Teti, M., Silva, K., Bloom, J. J., Harocopos, A., & Treese, M. (2012) · International Journal of Drug Policy · doi:10.1016/j.drugpo.2011.05.014 · Cited by 440 · cited 1×
“Heroin use has some fluidity among certain populations and injectors may switch between opiates [41].”
BackgroundWarner, M., Chen, L. H., & Makuc, D. M. (2009) · PsycEXTRA Dataset · doi:10.1037/e665272010-001 · Cited by 344
Effect of Abuse-Deterrent Formulation of OxyContin
Cicero, T. J., Ellis, M. S., & Surratt, H. L. (2012) · New England Journal of Medicine · doi:10.1056/nejmc1204141 · Cited by 336
Cited by
Relationship between Nonmedical Prescription-Opioid Use and Heroin Use
Compton, W. M., Jones, C. M., & Baldwin, G. T. (2016) · New England Journal of Medicine · doi:10.1056/nejmra1508490 · Cited by 1,044
The rise of illicit fentanyls, stimulants and the fourth wave of the opioid overdose crisis
Ciccarone, D. (2021) · Current Opinion in Psychiatry · doi:10.1097/yco.0000000000000717 · Cited by 987
Self-citationOpioid crisis: no easy fix to its social and economic determinants
Dasgupta, N., Beletsky, L., & Ciccarone, D. (2018) · American Journal of Public Health · doi:10.2105/ajph.2017.304187 · Cited by 923
Self-citationThe triple wave epidemic: Supply and demand drivers of the US opioid overdose crisis
Ciccarone, D. (2019) · International Journal of Drug Policy · doi:10.1016/j.drugpo.2019.01.010 · Cited by 677
Self-citationMowry, J. B., Spyker, D. A., Brooks, D. E., McMillan, N., & Schauben, J. L. (2015) · Clinical Toxicology · doi:10.3109/15563650.2015.1102927 · Cited by 507
Metadata
- Authors
- Unick, G. J., Rosenblum, D., Mars, S., & Ciccarone, D.
- Venue
- PLoS ONE
- Publisher
- Public Library of Science (PLoS)
- Published
- 2013-02-06
- Volume
- 8
- Issue
- 2
- Pages
- e54496
- ISSN
- 1932-6203 (ISSN-L)
- OpenAlex
- W2054245407
- Cited by
- 255
- References
- 47
- FWCI
- 23.63
- Type
- journal article
- Language
- en
- Open access
- gold
About these checks
Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.
Statistics and arithmetic are recomputed, not judged.
Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.
What counts as a claim ›How we measure confidence ›How we check this ›
Are you an author, or do you see a problem with this page? Request a review
How to cite
Cite CoChat for the checks on this page, and the paper for its own findings.
- This page
- CoChat. (2026). Citation check: Intertwined Epidemics: National Demographic Trends in Hospitalizations for Heroin- and Opioid-Related Overdoses, 1993–2009. https://app.cochat.ai/papers/10.1371/journal.pone.0054496
- The paper
- Unick, G. J., Rosenblum, D., Mars, S., & Ciccarone, D. (2013). Intertwined Epidemics: National Demographic Trends in Hospitalizations for Heroin- and Opioid-Related Overdoses, 1993–2009. PLoS ONE. https://doi.org/10.1371/journal.pone.0054496
Data sources
Bibliographic data: Semantic Scholar, OpenAlex, Crossref.
Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).
Semantic Scholar’s data is described in: Kinney, R., et al. (2023). The Semantic Scholar Open Data Platform. arXiv:2301.10140.