Urban-rural variation in the socioeconomic determinants of opioid overdose

Veronica A. Pear, William R. Ponicki, Andrew Gaidus, Katherine M. Keyes, Silvia S. Martins, David S. Fink, Ariadne Rivera-Aguirre, Paul J. Gruenewald, Magdalena Cerda

Research output: Contribution to journalArticle

4 Citations (Scopus)

Abstract

Background: Prescription opioid overdose (POD) and heroin overdose (HOD) rates have quadrupled since 1999. Community-level socioeconomic characteristics are associated with opioid overdoses, but whether this varies by urbanicity is unknown. Methods: In this serial cross-sectional study of zip codes in 17 states, 2002–2014 (n = 145,241 space-time units), we used hierarchical Bayesian Poisson space-time models to analyze the association between zip code-level socioeconomic features (poverty, unemployment, educational attainment, and income) and counts of POD or HOD hospital discharges. We tested multiplicative interactions between each socioeconomic feature and zip code urbanicity measured with Rural-Urban Commuting Area codes. Results: Percent in poverty and of adults with ≤ high school education were associated with higher POD rates (Rate Ratio [RR], 5% poverty: 1.07 [95% credible interval: 1.06–1.07]; 5% low education: 1.02 [1.02–1.03]), while median household income was associated with lower rates (RR, $10,000: 0.88 [0.87–0.89]). Urbanicity modified the association between socioeconomic features and HOD. Poverty and unemployment were associated with increased HOD in metropolitan areas (RR, 5% poverty: 1.12 [1.11–1.13]; 5% unemployment: 1.04 [1.02–1.05]), and median household income was associated with decreased HOD (RR, $10,000: 0.88 [0.87–0.90]). In rural areas, low educational attainment alone was associated with HOD (RR, 5%: 1.09 [1.02–1.16]). Conclusions: Regardless of urbanicity, elevated rates of POD were found in more economically disadvantaged zip codes. Economic disadvantage played a larger role in HOD in urban than rural areas, suggesting rural HOD rates may have alternative drivers. Identifying social determinants of opioid overdoses is particularly important for creating effective population-level interventions.

Original languageEnglish (US)
Pages (from-to)66-73
Number of pages8
JournalDrug and Alcohol Dependence
Volume195
DOIs
StatePublished - Feb 1 2019

Fingerprint

Heroin
Opioid Analgesics
Poverty
Prescriptions
Unemployment
Education
Space Simulation
Vulnerable Populations
Cross-Sectional Studies
Economics
Population

Keywords

  • Heroin
  • Opioid-related disorders
  • Prescription drug misuse
  • Rural health
  • Socioeconomic factors
  • Urban health

ASJC Scopus subject areas

  • Toxicology
  • Pharmacology
  • Psychiatry and Mental health
  • Pharmacology (medical)

Cite this

Urban-rural variation in the socioeconomic determinants of opioid overdose. / Pear, Veronica A.; Ponicki, William R.; Gaidus, Andrew; Keyes, Katherine M.; Martins, Silvia S.; Fink, David S.; Rivera-Aguirre, Ariadne; Gruenewald, Paul J.; Cerda, Magdalena.

In: Drug and Alcohol Dependence, Vol. 195, 01.02.2019, p. 66-73.

Research output: Contribution to journalArticle

Pear, VA, Ponicki, WR, Gaidus, A, Keyes, KM, Martins, SS, Fink, DS, Rivera-Aguirre, A, Gruenewald, PJ & Cerda, M 2019, 'Urban-rural variation in the socioeconomic determinants of opioid overdose', Drug and Alcohol Dependence, vol. 195, pp. 66-73. https://doi.org/10.1016/j.drugalcdep.2018.11.024
Pear, Veronica A. ; Ponicki, William R. ; Gaidus, Andrew ; Keyes, Katherine M. ; Martins, Silvia S. ; Fink, David S. ; Rivera-Aguirre, Ariadne ; Gruenewald, Paul J. ; Cerda, Magdalena. / Urban-rural variation in the socioeconomic determinants of opioid overdose. In: Drug and Alcohol Dependence. 2019 ; Vol. 195. pp. 66-73.
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abstract = "Background: Prescription opioid overdose (POD) and heroin overdose (HOD) rates have quadrupled since 1999. Community-level socioeconomic characteristics are associated with opioid overdoses, but whether this varies by urbanicity is unknown. Methods: In this serial cross-sectional study of zip codes in 17 states, 2002–2014 (n = 145,241 space-time units), we used hierarchical Bayesian Poisson space-time models to analyze the association between zip code-level socioeconomic features (poverty, unemployment, educational attainment, and income) and counts of POD or HOD hospital discharges. We tested multiplicative interactions between each socioeconomic feature and zip code urbanicity measured with Rural-Urban Commuting Area codes. Results: Percent in poverty and of adults with ≤ high school education were associated with higher POD rates (Rate Ratio [RR], 5{\%} poverty: 1.07 [95{\%} credible interval: 1.06–1.07]; 5{\%} low education: 1.02 [1.02–1.03]), while median household income was associated with lower rates (RR, $10,000: 0.88 [0.87–0.89]). Urbanicity modified the association between socioeconomic features and HOD. Poverty and unemployment were associated with increased HOD in metropolitan areas (RR, 5{\%} poverty: 1.12 [1.11–1.13]; 5{\%} unemployment: 1.04 [1.02–1.05]), and median household income was associated with decreased HOD (RR, $10,000: 0.88 [0.87–0.90]). In rural areas, low educational attainment alone was associated with HOD (RR, 5{\%}: 1.09 [1.02–1.16]). Conclusions: Regardless of urbanicity, elevated rates of POD were found in more economically disadvantaged zip codes. Economic disadvantage played a larger role in HOD in urban than rural areas, suggesting rural HOD rates may have alternative drivers. Identifying social determinants of opioid overdoses is particularly important for creating effective population-level interventions.",
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T1 - Urban-rural variation in the socioeconomic determinants of opioid overdose

AU - Pear, Veronica A.

AU - Ponicki, William R.

AU - Gaidus, Andrew

AU - Keyes, Katherine M.

AU - Martins, Silvia S.

AU - Fink, David S.

AU - Rivera-Aguirre, Ariadne

AU - Gruenewald, Paul J.

AU - Cerda, Magdalena

PY - 2019/2/1

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N2 - Background: Prescription opioid overdose (POD) and heroin overdose (HOD) rates have quadrupled since 1999. Community-level socioeconomic characteristics are associated with opioid overdoses, but whether this varies by urbanicity is unknown. Methods: In this serial cross-sectional study of zip codes in 17 states, 2002–2014 (n = 145,241 space-time units), we used hierarchical Bayesian Poisson space-time models to analyze the association between zip code-level socioeconomic features (poverty, unemployment, educational attainment, and income) and counts of POD or HOD hospital discharges. We tested multiplicative interactions between each socioeconomic feature and zip code urbanicity measured with Rural-Urban Commuting Area codes. Results: Percent in poverty and of adults with ≤ high school education were associated with higher POD rates (Rate Ratio [RR], 5% poverty: 1.07 [95% credible interval: 1.06–1.07]; 5% low education: 1.02 [1.02–1.03]), while median household income was associated with lower rates (RR, $10,000: 0.88 [0.87–0.89]). Urbanicity modified the association between socioeconomic features and HOD. Poverty and unemployment were associated with increased HOD in metropolitan areas (RR, 5% poverty: 1.12 [1.11–1.13]; 5% unemployment: 1.04 [1.02–1.05]), and median household income was associated with decreased HOD (RR, $10,000: 0.88 [0.87–0.90]). In rural areas, low educational attainment alone was associated with HOD (RR, 5%: 1.09 [1.02–1.16]). Conclusions: Regardless of urbanicity, elevated rates of POD were found in more economically disadvantaged zip codes. Economic disadvantage played a larger role in HOD in urban than rural areas, suggesting rural HOD rates may have alternative drivers. Identifying social determinants of opioid overdoses is particularly important for creating effective population-level interventions.

AB - Background: Prescription opioid overdose (POD) and heroin overdose (HOD) rates have quadrupled since 1999. Community-level socioeconomic characteristics are associated with opioid overdoses, but whether this varies by urbanicity is unknown. Methods: In this serial cross-sectional study of zip codes in 17 states, 2002–2014 (n = 145,241 space-time units), we used hierarchical Bayesian Poisson space-time models to analyze the association between zip code-level socioeconomic features (poverty, unemployment, educational attainment, and income) and counts of POD or HOD hospital discharges. We tested multiplicative interactions between each socioeconomic feature and zip code urbanicity measured with Rural-Urban Commuting Area codes. Results: Percent in poverty and of adults with ≤ high school education were associated with higher POD rates (Rate Ratio [RR], 5% poverty: 1.07 [95% credible interval: 1.06–1.07]; 5% low education: 1.02 [1.02–1.03]), while median household income was associated with lower rates (RR, $10,000: 0.88 [0.87–0.89]). Urbanicity modified the association between socioeconomic features and HOD. Poverty and unemployment were associated with increased HOD in metropolitan areas (RR, 5% poverty: 1.12 [1.11–1.13]; 5% unemployment: 1.04 [1.02–1.05]), and median household income was associated with decreased HOD (RR, $10,000: 0.88 [0.87–0.90]). In rural areas, low educational attainment alone was associated with HOD (RR, 5%: 1.09 [1.02–1.16]). Conclusions: Regardless of urbanicity, elevated rates of POD were found in more economically disadvantaged zip codes. Economic disadvantage played a larger role in HOD in urban than rural areas, suggesting rural HOD rates may have alternative drivers. Identifying social determinants of opioid overdoses is particularly important for creating effective population-level interventions.

KW - Heroin

KW - Opioid-related disorders

KW - Prescription drug misuse

KW - Rural health

KW - Socioeconomic factors

KW - Urban health

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