Key Takeaways
- 3 million people die each year from harmful use of alcohol globally, equivalent to 5.3% of all deaths
- 70.2% of adults aged 18+ in the U.S. reported having used alcohol at some point in their lives (2019), showing the scale of exposure relevant to alcohol use disorder
- 9.1% of U.S. adults aged 18+ had an alcohol use disorder in 2019 (about 23.3 million people), based on NSDUH estimates
- USD 39.6 billion U.S. spending on substance use disorder treatment in 2020 (includes mental health and substance use disorder services categories in national health expenditure accounting)
- USD 2.7 billion U.S. federal funding for substance use disorder and related activities in FY2023 (HHS and related agencies appropriations and grants reported for SUD-related programs)
- USD 6.7 billion U.S. revenue opportunity for medications for opioid use disorder by 2030 (forecast from market research on pharmacotherapies), reflecting spending growth potential
- 68% of people who met criteria for substance use disorder in the U.S. in 2019 did not receive any specialty treatment in the past year (barrier and treatment gap metric)
- Less than 30% of adults with substance use disorder in the U.S. received specialty treatment in 2020 (treatment penetration figure from SAMHSA NSDUH analyses)
- Naltrexone extended-release reduces relapse rates in alcohol use disorder; in a key randomized trial, relapse occurred in 25% with naltrexone vs 45% with placebo (56-day window used in trial reporting)
- 53% of Americans report that they have ever experienced addiction-related problems in their household or with a close family member/friend (survey-based metric in major public opinion polls), reflecting social awareness
- In 2021, 74% of opioid treatment programs reported offering take-home naloxone kits or related overdose education (survey-based operational metric cited by SAMHSA)
- In 2022, 55% of substance use disorder treatment facilities reported using electronic health records (EHR) (facility technology adoption metric from SAMHSA or national health IT surveys)
- The U.S. economic cost of substance abuse was estimated at USD 442 billion in 2017 (SAMHSA/NSDUH-based cost accounting synthesis used widely in later policy summaries)
- USD 1.5 billion in workplace costs attributed to substance abuse in 2019 (reported in insurer and workforce analyses focusing on absenteeism and healthcare)
- In the U.S., indirect costs (lost productivity) account for 73% of the total costs of opioid misuse according to a national economic estimate report
Millions die and many go untreated, yet proven medicines and harm reduction can save lives.
Related reading
Prevalence & Burden
Prevalence & Burden Interpretation
Market Size
Market Size Interpretation
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Treatment & Outcomes
Treatment & Outcomes Interpretation
Industry Trends
Industry Trends Interpretation
More related reading
Cost Analysis
Cost Analysis Interpretation
Epidemiology
Epidemiology Interpretation
More related reading
Treatment Access
Treatment Access Interpretation
Outcomes & Effectiveness
Outcomes & Effectiveness Interpretation
More related reading
Market & Spend
Market & Spend Interpretation
Policy & Risk
Policy & Risk Interpretation
How We Rate Confidence
Every statistic is queried across four AI models (ChatGPT, Claude, Gemini, Perplexity). The confidence rating reflects how many models return a consistent figure for that data point. Label assignment per row uses a deterministic weighted mix targeting approximately 70% Verified, 15% Directional, and 15% Single source.
Only one AI model returns this statistic from its training data. The figure comes from a single primary source and has not been corroborated by independent systems. Use with caution; cross-reference before citing.
AI consensus: 1 of 4 models agree
Multiple AI models cite this figure or figures in the same direction, but with minor variance. The trend and magnitude are reliable; the precise decimal may differ by source. Suitable for directional analysis.
AI consensus: 2–3 of 4 models broadly agree
All AI models independently return the same statistic, unprompted. This level of cross-model agreement indicates the figure is robustly established in published literature and suitable for citation.
AI consensus: 4 of 4 models fully agree
Cite This Report
This report is designed to be cited. We maintain stable URLs and versioned verification dates. Copy the format appropriate for your publication below.
Aisha Okonkwo. (2026, February 13). Addiction Statistics. Gitnux. https://gitnux.org/addiction-statistics
Aisha Okonkwo. "Addiction Statistics." Gitnux, 13 Feb 2026, https://gitnux.org/addiction-statistics.
Aisha Okonkwo. 2026. "Addiction Statistics." Gitnux. https://gitnux.org/addiction-statistics.
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