Cited by 39Opioid Use Disorder TreatmentSubstance Abuse Treatment and OutcomesPain Management and Opioid Use

Days With Pain and Substance Use Disorders: Is There an Association?

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Edlund, Mark J., Sullivan, Mark D., Han, Xiaotong, Booth, Brenda M.·2013·The Clinical Journal of Pain

Abstract

OBJECTIVES: We investigated possible associations between pain frequency and the 5 most common substance use disorders: alcohol abuse/dependence, cocaine abuse/dependence, methamphetamine abuse/dependence, opioid abuse/dependence, and marijuana abuse/dependence. METHODS: We used data from the Rural Stimulant Study, a longitudinal (7 waves), observational study of at-risk stimulant users (cocaine and methamphetamine) in Arkansas and Kentucky (n=462). In fixed-effects logistic regression models, we regressed our measures of substance use disorders on the number of days with pain in the past 30 days and depression severity. RESULTS: Time periods when individuals had 1 to 15 days [odds ratio (OR)=1.85, P<0.001] or 16+ days (OR=2.18, P<0.001) with pain in the past 30 days were more likely to have a diagnosis of alcohol abuse/dependence, compared with time periods when individuals had no days with pain. Compared with time periods when individuals had no pain days in the past 30 days, time periods when individuals had 16+ pain days were more likely to have a diagnosis of opioid abuse/dependence (OR=3.32, P=0.02). Number of days with pain was not significantly associated with other substance use disorders. DISCUSSION: Pain frequency seems to be associated with an increased risk for alcohol abuse/dependence and opioid abuse/dependence in this population, and the magnitude of the association is medium to large. Further research is needed to investigate this in more representative populations and to determine causal relationships.

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  • Pain severity is positively associated with higher risk for AUD.

    “Indeed, there is a positive association between pain severity and a higher risk for AUD (Lawton and Simpson, 2009;Edlund et al., 2013).”

    From Drug Addiction: Hyperkatifeia/Negative Reinforcement as a Framework for Medications Development (2021) · cites this paper as Edlund et al., 2013

    The Methods (2.2 Measures; page unavailable) say that pain severity was tested but was not statistically significant after controlling for days with pain and depression. The Discussion (section 4; page unavailable) reports a positive association for pain frequency—not severity—with alcohol abuse/dependence. (LLM, conf=0.90)

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  1. [3]Joy JE Watson SJ Benson JA Marijuana and medicine: assessing the science base Washington, DC National Academy Press 1999 25101425

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Authors
Edlund, M. J., Sullivan, M. D., Han, X., & Booth, B. M.
Affiliations
  • RTI International (US)
  • University of Washington (US)
  • University of Arkansas for Medical Sciences (US)
  • Central Arkansas Veterans Healthcare System (US)
Corresponding author
Edlund, Mark J.
Venue
The Clinical Journal of Pain
Published
2013-08
Volume
29
Issue
8
Pages
689-695
ISSN
0749-8047 (ISSN-L)
OpenAlex
W1995278421
Cited by
39
References
64
Citations by year
2026: 2 · 2025: 4 · 2024: 3 · 2023: 4 · 2022: 2 · 2021: 7 · 2020: 5 · 2019: 5 · 2018: 2 · 2017: 4 · 2015: 1
FWCI
0.34
Type
journal article
Language
en
Open access
Locations
  • Clinical Journal of Pain (publishedVersion)
  • PubMed (publishedVersion)
  • PubMed Central (acceptedVersion)
Funders
National Institute on Drug Abuse (R01DA015363)
Topics
  • Health Sciences › Medicine › Public Health, Environmental and Occupational Health › Opioid Use Disorder Treatment
  • Health Sciences › Medicine › Epidemiology › Substance Abuse Treatment and Outcomes
  • Health Sciences › Medicine › Anesthesiology and Pain Medicine › Pain Management and Opioid Use
Keywords
pain frequency, substance use disorders, alcohol abuse, alcoholism, opioid abuse, opioid use disorder, cocaine abuse, methamphetamine abuse, cannabis use disorder, depression severity
MeSH terms
Adolescent, Adult, Arkansas, Female, Humans, Kentucky, Longitudinal Studies, Male, Middle Aged, Pain, Risk Factors, Rural Population, Time Factors, Logistic Models, Observation, Substance-Related Disorders, Young Adult

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