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Estimating the impact of drug use on US mortality, 1999-2016

Open access
Glei, Dana A., Preston, Samuel H.·2020·PLOS ONE
DOI 10.1371/journal.pone.0226732PMC PMC6961845
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Abstract

The impact of rising drug use on US mortality may extend beyond deaths coded as drug-related to include excess mortality from other causes affected by drug use. Here, we estimate the full extent of drug-associated mortality. We use annual death rates for 1999-2016 by state, sex, five-year age group, and cause of death to model the relationship between drug-coded mortality-which serves as an indicator of the population-level prevalence of drug use-and mortality from other causes. Among residents aged 15-64 living in the 50 US states, the estimated number of drug-associated deaths in 2016 (141,695) was 2.2 times the number of drug-coded deaths (63,000). Adverse trends since 2010 in midlife mortality are largely attributable to drug-associated mortality. In the absence of drug use, we estimate that the probability of dying between ages 15 and 65 would have continued to decline after 2010 among men (to 15% in 2016) and would have remained at a low level (10%) among women. Our results suggest that an additional 3.9% of men and 1.8% of women died between ages 15 and 65 in 2016 because of drug use. In terms of life expectancy beyond age 15, we estimate that drug use cost men 1.4 years and women 0.7 years, on average. In the hardest-hit state (West Virginia), drug use cost men 3.6 and women 1.9 life years. Recent declines in US life expectancy have been blamed largely on the drug epidemic. Consistent with that inference, our results imply that, in the absence of drug use, life expectancy at age 15 would have increased slightly between 2014 and 2016. Drug-associated mortality in the US is roughly double that implied by drug-coded deaths alone. The drug epidemic is exacting a heavy cost to American lives, not only from overdoses but from a variety of causes.

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Crossref · 10.1371/journal.pone.0226732

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Figures

Fig 1 Box plot of drug-coded mortality rate (per 1,000) among 50 US states, by five-year age group in 1999 and 2016 among A) males and B) females. Note: In these plots, the box represents the 25th (p25), 50th (p50), and 75th (p75) percentiles of the distribution; the whiskers represent the lower and upper adjacent values. The lower adjacent value is defined as p25−1.5×IQR, where IQR = p75−p25. Similarly, the upper adjacent value is defined as p75+1.5×IQR. Values outside of the whiskers are not shown.
Fig 1 Box plot of drug-coded mortality rate (per 1,000) among 50 US states, by five-year age group in 1999 and 2016 among A) males and B) females. Note: In these plots, the box represents the 25th (p25), 50th (p50), and 75th (p75) percentiles of the distribution; the whiskers represent the lower and upper adjacent values. The lower adjacent value is defined as p25−1.5×IQR, where IQR = p75−p25. Similarly, the upper adjacent value is defined as p75+1.5×IQR. Values outside of the whiskers are not shown.CC BY · PubMed Central
Fig 2 Estimated number of drug-associated deaths at ages 15–64 across groups of causes, by sex, US, 2016. Note: See S5 Appendix for ICD-10 codes that define each cause group. Negative values result when the model indicates an inverse association between drug-coded mortality and mortality from the specified cause group.
Fig 2 Estimated number of drug-associated deaths at ages 15–64 across groups of causes, by sex, US, 2016. Note: See S5 Appendix for ICD-10 codes that define each cause group. Negative values result when the model indicates an inverse association between drug-coded mortality and mortality from the specified cause group.CC BY · PubMed Central
Fig 3 Life expectancy at age 15 (e15) with and without drug use, US, 1999–2016, by sex. Note: Estimates are based on the model that includes smoking.
Fig 3 Life expectancy at age 15 (e15) with and without drug use, US, 1999–2016, by sex. Note: Estimates are based on the model that includes smoking.CC BY · PubMed Central
Fig 4 Percentage dying between age 15 and 65 (q[15,65]) with and without drug use, US, 1999–2016, by sex. Note: Estimates are based on the model that includes smoking.
Fig 4 Percentage dying between age 15 and 65 (q[15,65]) with and without drug use, US, 1999–2016, by sex. Note: Estimates are based on the model that includes smoking.CC BY · PubMed Central

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Citations

Cites

Research works printed but not linked: 5

  1. U.S. Department of Health and Human Services (HHS), Office of the Surgeon General, 2016, Facing addiction in American: the Surgeon General's report on alcohol, drugs, and health
  2. SH Preston, 2010, International differences in mortality at older ages: dimensions and sources. Panel on Understanding Divergent Trends in Longevity in High-Income Countries. Committee on Population, Division of Behavioral and Social Sciences and Education, 105
  3. StataCorp, 2015, Stata: Release 14. Statistical Software
  4. AJ Cherlin, 2016, Why are white death rates rising?
  5. L Bernstein, 2018, U.S. life expectancy declines again, a dismal trend not seen since World War I, Washington Post 2018 November 29

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Metadata

Authors
Glei, D. A., & Preston, S. H.
Affiliations
  • Georgetown University (US)
  • University of Pennsylvania (US)
Corresponding author
Glei, Dana A.
ORCID
Venue
PLOS ONE
Publisher
Public Library of Science (PLoS)
Published
2020-01-15
Volume
15
Issue
1
Pages
e0226732
ISSN
1932-6203 (ISSN-L)
DOI
10.1371/journal.pone.0226732
PMC
PMC6961845
OpenAlex
W2999505629
Cited by
123
References
38
Citations by year
2026: 7 · 2025: 8 · 2024: 18 · 2023: 54 · 2022: 12 · 2021: 14 · 2020: 10
FWCI
16.85
Type
journal article
Language
en
Open access
Licence
Locations
  • PLoS ONE (publishedVersion, cc-by)
  • Europe PMC (PubMed Central) (publishedVersion, cc-by)
  • PubMed Central (publishedVersion, cc-by)
  • PubMed (publishedVersion)
  • DOAJ (DOAJ: Directory of Open Access Journals) (submittedVersion, cc-by-sa)
  • Figshare (submittedVersion, cc-by)
Funders
  • National Institute on Aging (1R01AG060115)
  • Georgetown University
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 › Epidemiology › HIV, Drug Use, Sexual Risk
Keywords
drug use, excess mortality, opioid epidemic, life expectancy, midlife mortality, mortality trends, sex differences in mortality, United States
MeSH terms
Adolescent, Adult, Female, Humans, Male, Middle Aged, United States, Models, Statistical, Substance-Related Disorders, Young Adult, Drug Overdose

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