Abstract
Introduction:
Cannabis use for medical purposes is legalized across 39 states and the District of Columbia in the US. The objective of this study was to evaluate temporal trends and correlates of cannabis use for medical purposes in the US.
Methods:
Data from 2013–2020 National Survey on Drug Use and Health (NSDUH) were used. Since 2013, medical cannabis use has been assessed using a dichotomous question asking whether any medical cannabis use was recommended by a doctor among those who used cannabis in the past 12 months. A modified Poisson model was used to estimate the average annual percent change (AAPC) of medical cannabis use from 2013 to 2020. The analyses were repeated for key socio-demographic and clinical subgroups. Data were analyzed from September to November, 2022.
Results:
The prevalence of US residents using cannabis for medical purposes increased significantly from 1.2% in 2013–2014 to 2.5% in 2019–2020, with an AAPC of 12.9% (95% confidence interval [CI], 10.4–15.5%), and many of socio-demographic and clinical subgroups showed similar significant increases in cannabis use for medical purposes. In the multivariable-adjusted model, living in a state that legalized medical cannabis remained significantly associated with medical cannabis use (adjusted odds ratio, 4.10; 95% CI, 3.68–4.56).
Conclusions:
The study documents a continued nationwide increase in use of cannabis for diverse medical purposes between 2013 and 2020, two decades after the first state passed legalizing legislation.
Introduction
As of February 2023, medical cannabis has been legalized in 37 states and the District of Columbia.1,2 While the Controlled Substances Act of 1971 designates cannabis as a Schedule I substance, indicating that it has no accepted medical use and is illegal,1,3 state-level legalization—which began in California in 1996—has increased the accessibility of cannabis for medical purposes and generated more permissive public attitudes throughout the US.1 This study extends earlier studies,4,5 and evaluates temporal trends and correlates of cannabis use for medical purposes.
Methods
Data were from US civilian, non-institutionalized residents aged ≥12 who participated in the 2013–2020 National Survey on Drug Use and Health (NSDUH).6 The annual survey response rates ranged from 60.4% to 75.6%.6 Since 2013, medical cannabis use has been assessed using a dichotomous question asking whether any medical cannabis use was recommended by a doctor among those who used cannabis in the past 12 months. A modified Poisson model7,8 was used to estimate the average annual percent change (AAPC) of medical cannabis use. The same analyses were repeated for key socio-demographic and clinical subgroups.
Second, correlates of cannabis use for medical purposes were assessed using a multivariable-adjusted logistic regression model. Both bivariate and multivariable-adjusted interaction effects of survey year and residing in a state that had legalized medical cannabis use (yes/no; self-report) as well as other sociodemographic and clinical characteristics4,5 on medical cannabis use were tested to determine respondent characteristics associated with changes over time in medical cannabis use. Details of the survey including questionnaires and methodology are available on the NSDUH website.6
Stata version 17.1 MP/4-Core was used for all analyses. The complex survey design (i.e., unequal probability of selection, clustering, and stratification) used in the data collection was taken into account.9–11 A two-sided p-value<0.05 was set as the test of statistical significance. This study was deemed exempt by the Institutional Review Board at Yale School of Medicine since publicly available, de-identified data were used. Study procedures followed the Strengthening the Reporting of Observational Studies in Epidemiology (STROBE) reporting guideline. Data were analyzed from September to November, 2022.
Results
The prevalence of US residents using cannabis for medical purposes increased significantly from 1.2% in 2013–2014 to 2.5% in 2019–2020, with an AAPC of 12.9% (95% confidence interval [CI], 10.4–15.5%), and many socio-demographic and clinical subgroups showed similar significant increases in cannabis use for medical purposes (Table 1). Most notably, respondents living in states that had legalized medical cannabis had greater odds of using medical cannabis (odds ratio [OR], 4.54; 95% CI, 4.15–4.96). Overall, six variables showed significant interaction effects with survey year in association with medical cannabis use, including: living in a state that had legalized medical cannabis, ages 18–25, male sex, never having married, completing some college education, and being uninsured (Table 1, indicated by § in the extreme right-hand column).
Table 1.
National trends of past-year any medical cannabis use by socio-demographic and clinical characteristics in 426,092 US residents, 2013–2020
| Variable | Sample size | 2013–2014 | 2015–2016 | 2017–2018 | 2019–2020 | Average annual percent changea) (95% CI) | Bivariate association with medical cannabis use, odds ratio (95% CI)§ |
|---|---|---|---|---|---|---|---|
| Overall | 426,092 | 1.2% | 1.6% | 1.8% | 2.5% | 12.94% (10.41 to 15.53%) | |
| Residing in a state that legalized medical cannabis | 239,777 | 2.4% | 2.5% | 2.4% | 3.2% | 5.77% (3.17 to 8.43%) | 4.54 (4.15–4.96)§ |
| Age, y | |||||||
| 12–17 | 105,322 | 0.3% | 0.4% | 0.4% | 0.4% | 6.67% (−3.63 to 18.06%) | 0.20 (0.17–0.23) |
| 18–25 | 109,073 | 1.9% | 2.7% | 2.8% | 3.1% | 7.22% (4.35 to 10.17%) | 1.62 (1.49–1.76)§ |
| 26–34 | 63,563 | 2.0% | 2.6% | 3.2% | 3.5% | 10.29% (6.74 to 13.96%) | 1.82 (1.67–1.98) |
| 35–49 | 82,730 | 1.3% | 1.6% | 2.1% | 2.9% | 15.08% (11.53 to 18.74%) | 1.16 (1.07–1.26) |
| ≥50 | 65,404 | 0.9% | 1.1% | 1.2% | 2.2% | 17.94% (11.16 to 25.14%) | 0.63 (0.55–0.71) |
| Sex | |||||||
| Male | 202,440 | 1.5% | 1.9% | 2.1% | 2.7% | 9.99% (6.80 to 13.27%) | 1.42 (1.30–1.54)§ |
| Female | 223,652 | 0.9% | 1.2% | 1.5% | 2.3% | 17.06% (13.31 to 20.93%) | Reference |
| Race/ethnicity | |||||||
| Non-Hispanic white | 252,560 | 1.3% | 1.5% | 1.8% | 2.8% | 13.96% (10.81 to 17.20%) | 1.16 (1.06–1.27) |
| Non-Hispanic black | 53,083 | 0.8% | 1.6% | 1.8% | 2.2% | 14.93% (9.88 to 20.20%) | 0.89 (0.79–1.00) |
| Hispanic | 76,526 | 1.0% | 1.6% | 1.8% | 1.9% | 8.80% (4.50 to 13.27%) | 0.89 (0.80–1.00)§ |
| Non-Hispanic other | 43,923 | 1.2% | 1.6% | 1.6% | 2.0% | 10.62% (3.06 to 18.74%) | 0.91 (0.79–1.04) |
| Marital status | |||||||
| Married | 130,919 | 0.7% | 1.1% | 1.1% | 1.9% | 16.39% (11.78 to 21.19%) | 0.45 (0.41–0.49) |
| Widowed | 9,677 | 0.7% | 1.2% | 1.0% | 1.1% | 6.07% (−7.52 to 21.67%) | 0.51 (0.38–0.68) |
| Divorced/separated | 34,041 | 1.9% | 2.1% | 2.4% | 4.1% | 14.80% (7.06 to 23.09%) | 1.48 (1.29–1.70) |
| Never married | 199,687 | 1.9% | 2.4% | 3.0% | 3.2% | 9.78% (6.67 to 12.98%) | 2.07 (1.89–2.27)§ |
| Education | |||||||
| < High school | 41,431 | 1.5% | 1.3% | 1.9% | 2.4% | 10.17% (3.12 to 17.71%) | 0.90 (0.80–1.02) |
| High school or equivalent | 87,147 | 1.3% | 1.7% | 1.9% | 3.1% | 16.08% (11.10 to 21.29%) | 1.06 (0.95–1.18) |
| Some college | 103,697 | 1.7% | 2.3% | 2.5% | 2.9% | 8.75% (6.05 to11.51%) | 1.37 (1.26–1.49)§ |
| ≥ Bachelor’s degree | 88,495 | 0.8% | 1.3% | 1.5% | 2.3% | 17.24% (11.37 to 23.42%) | 0.71 (0.63–0.79) |
| Employment | |||||||
| Full-time | 167,752 | 1.0% | 1.4% | 1.8% | 2.2% | 13.88 (10.37 to 17.50%) | 0.73 (0.67–0.78) |
| Part-time | 65,227 | 1.5% | 1.9% | 2.3% | 2.8% | 11.67% (7.31 to 16.21%) | 1.21 (1.11–1.32) |
| Unemployed | 26,167 | 1.9% | 2.9% | 3.2% | 4.1% | 11.18% (6.40 to 17.49%) | 1.81 (1.58–2.06) |
| Other | 115,178 | 1.4% | 1.6% | 1.7% | 2.8% | 12.62% (8.35 to 17.07%) | 1.11 (1.03–1.19) |
| Family income | |||||||
| <$20,000 | 83,455 | 1.9% | 2.3% | 2.5% | 3.6% | 11.56% (6.59 to 16.76%) | 1.57 (1.43–1.74) |
| $20,000 - $ 49,999 | 129,391 | 1.4% | 1.7% | 2.2% | 2.9% | 14.18% (9.55 to 19.01%) | 1.21 (1.10–1.33) |
| $50,000 - $ 74,999 | 66,687 | 1.0% | 1.4% | 1.5% | 2.5% | 15.12% (9.97 to 20.51%) | 0.87 (0.78–0.98) |
| ≥$75,000 | 146,559 | 0.7% | 1.2% | 1.4% | 1.8% | 14.04% (10.03 to 18.20%) | 0.65 (0.58–0.71) |
| Insurance coverage | |||||||
| Private plan | 230,578 | 0.8% | 1.3% | 1.4% | 2.0% | 14.56% (11.01 to 18.21%) | 0.63 (0.58–0.69) |
| Medicaid | 77,553 | 2.2% | 2.7% | 3.4% | 4.2% | 11.54% (7.69 to 15.53%) | 2.46 (2.27–2.68) |
| Medicare | 35,210 | 1.1% | 1.2% | 1.3% | 2.7% | 17.23% (9.43 to 22.59%) | 0.79 (0.68–0.93) |
| Other | 22,276 | 1.5% | 2.2% | 2.3% | 2.6% | 8.64% (1.82 to 15.92%) | 1.35 (1.16–1.57) |
| Uninsured | 55,460 | 1.8% | 2.1% | 2.6% | 2.6% | 7.01% (2.67 to 11.54%) | 1.26 (1.14–1.39)§ |
| Urban residence | |||||||
| Non-metropolitan | 84,927 | 1.0% | 1.1% | 1.4% | 2.2% | 14.49% (8.29 to 21.06%) | 0.77 (0.69–0.85) |
| Small metropolitan | 149,630 | 1.2% | 1.5% | 1.9% | 2.5% | 13.35% (9.13 to 17.73%) | 1.02 (0.93–1.12) |
| Large metropolitan | 191,535 | 1.2% | 1.7% | 1.9% | 2.5% | 12.34% (8.78 to 16.02%) | 1.11 (1.02–1.22) |
| Self-rated overall health | |||||||
| Excellent | 109,219 | 0.7% | 1.1% | 1.2% | 1.5% | 12.53% (7.36 to 17.96%) | 0.58 (0.53–0.64) |
| Very good | 165,596 | 0.8% | 1.3% | 1.5% | 1.8% | 12.86% (9.17 to 16.67%) | 0.69 (0.63–0.77) |
| Good | 111,142 | 1.4% | 1.7% | 2.0% | 2.6% | 10.76% (6.97 to 14.68%) | 1.12 (1.04–1.21) |
| Fair/poor | 40,041 | 2.7% | 2.7% | 3.2% | 5.5% | 14.69% (9.70 to 19.90%) | 2.30 (2.07–2.56) |
| Past-year major depressive episode | 28,667 | 3.2% | 4.2% | 4.5% | 7.2% | 15.26% (9.71 to 21.08%) | 3.04 (2.76–3.34) |
| Past-year substance use disorder | |||||||
| Alcohol | 27,794 | 2.8% | 4.6% | 4.2% | 4.1% | 4.84% (−0.20 to 10.13%) | 2.25 (2.01–2.51) |
| Tobacco | 27,853 | 3.5% | 3.9% | 4.6% | 6.8% | 12.54% (6.95 to 18.43%) | 2.83 (2.54–3.15) |
| Cocaine | 1,555 | 9.0% | 9.5% | 11.0% | 11.8% | 3.29% (−5.96 to 13.45%) | 6.03 (4.74–7.66) |
| Opioid | 3,882 | 4.4% | 6.7% | 8.0% | 11.8% | 17.34% (9.67 to 25.54%) | 4.43 (3.59–5.45) |
| Otherb) | 3,224 | 6.8% | 5.3% | 7.8% | 10.6% | 10.21% (0.52 to 20.83%) | 4.79 (3.80–6.05) |
| Age of first cannabis use | |||||||
| <18 | 112,920 | 3.5% | 4.3% | 4.8% | 6.9% | 12.57% (9.76 to 15.46%) | 6.26 (5.71–6.88) |
| 18–29 | 62,890 | 1.7% | 2.4% | 2.8% | 3.4% | 11.04% (7.52 to 14.68%) | 1.51 (1.38–1.65) |
| ≥30 | 4,555 | 1.9% | 2.9% | 4.4% | 6.5% | 22.25% (9.38 to 36.64%) | 2.29 (1.93–2.73) |
| Past-year suicide attempt | 2,854 | 3.9% | 5.3% | 7.0% | 11.2% | 20.72% (7.76 to 35.25%) | 3.87 (3.13–4.80) |
| Past-year non-medical use of prescription pain relievers | 19,894 | 3.8% | 4.2% | 5.2% | 7.1% | 11.70% (5.25 to 18.55%) | 3.11 (2.76–3.49) |
| Past-year non-medical use of prescription stimulants | 10,918 | 4.1% | 4.1% | 5.0% | 6.0% | 9.07% (−0.03 to 18.99%) | 2.82 (2.39–3.34) |
Note: Data are from National Survey on Drug Use and Health.
is derived from the modified Poisson model
includes hallucinogen, stimulant, sedative, and/or inhalant use disorders.
indicates significant interaction with survey years. All analyses were adjusted for multi-stage, complex survey sampling techniques.
In the multivariable-adjusted model (Table 2), living in a state that legalized medical cannabis remained significantly associated with greater odds of medical cannabis use (adjusted OR [AOR], 4.10; 95% CI, 3.68–4.56). Clinically relevant subgroups that experienced significantly greater odds of medical cannabis use included: poorer self-rated health statuses, past-year major depressive episode, cocaine use disorder, and use of non-prescription pain relievers (p<0.01 for each). Tests of the interaction of subgroups and time in the multivariable analysis showed negative interaction effects for reported state legalization (p=0.027) as well as for having some college education (p=0.001) while their estimated odds ratios were small (data available by request).
Table 2.
Multivariable-adjusted model for factors associated with past-year medical cannabis use among US adults, 2013–2020
| Variable | Adjusted odds ratio (95% CI; p) |
|---|---|
| Residing in a state that legalized medical cannabis | 4.10 (3.68–4.56; <0.001) |
| Survey year (2013–2014) | |
| 2015–2016 | 1.14 (0.97–1.34; 0.099) |
| 2017–2018 | 1.12 (0.98–1.29; 0.102) |
| 2019–2020 | 1.48 (1.27–1.73; <0.001) |
| Socio-demographic factor | |
| Age, y (18–25) | |
| 26–34 | 1.06 (0.96–1.18; 0.243) |
| 35–49 | 0.83 (0.73–0.94; 0.003) |
| ≥50 | 0.52 (0.41–0.65; <0.001) |
| Sex (Female) | |
| Male | 1.31 (1.20–1.44; <0.001) |
| Race/ethnicity (non-Hispanic white) | |
| Non-Hispanic black | 0.90 (0.78–1.04; 0.165) |
| Hispanic | 0.96 (0.85–1.07; 0.424) |
| Non-Hispanic other | 1.14 (0.97–1.34; 0.133) |
| Marital status (Married) | |
| Widowed | 1.18 (0.84–1.65; 0.340) |
| Divorced/separated | 1.33 (1.15–1.54; <0.001) |
| Never married | 1.21 (1.06–1.37; 0.003) |
| Education (< High school) | |
| High school or equivalent | 1.11 (0.95–1.29; 0.198) |
| Some college | 1.33 (1.15–1.54; <0.001) |
| ≥ Bachelor’s degree | 1.21 (1.06–1.37; 0.003) |
| Employment (Full-time) | |
| Part-time | 1.31 (1.17–1.46; <0.001) |
| Unemployed | 1.35 (1.14–1.60; <0.001) |
| Other | 1.49 (1.31–1.71; <0.001) |
| Family income (<$20,000) | |
| $20,000 - $ 49,999 | 1.06 (0.94–1.19; 0.352) |
| $50,000 - $ 74,999 | 0.88 (0.76–1.03; 0.107) |
| ≥$75,000 | 0.79 (0.69–0.91; 0.001) |
| Insurance coverage (Private plan) | |
| Medicaid | 1.39 (1.23–1.57; <0.001) |
| Medicare | 1.64 (1.30–2.08; <0.001) |
| Other | 1.44 (1.20–1.74; <0.001) |
| Uninsured | 1.25 (1.11–1.40; <0.001) |
| Urban residence (non-metropolitan) | |
| Small metropolitan | 1.09 (0.97–1.23; 0.140) |
| Large metropolitan | 1.14 (1.01–1.29; 0.041) |
| Clinical and behavioral factor | |
| Self-rated overall health (Excellent) | |
| Very good | 1.05 (0.92–1.19; 0.468) |
| Good | 1.42 (1.26–1.60; <0.001) |
| Fair/poor | 2.48 (2.15–2.86; <0.001) |
| Past-year major depressive episode a) | 1.38 (1.23–1.56; <0.001) |
| Past-year substance use disorder a) | |
| Alcohol | 0.91 (0.81–1.01; 0.087) |
| Tobacco | 1.11 (0.99–1.25; 0.067) |
| Cocaine | 1.52 (1.13–2.05; 0.006) |
| Opioid | 0.91 (0.70–1.18; 0.464) |
| Other | 1.31 (0.97–1.75; 0.074) |
| Age of first cannabis use (<18) | |
| 18–29 | 0.55 (0.49–0.61; <0.001) |
| ≥30 | 0.82 (0.67–1.00; 0.053) |
| Past-year suicide attempta) | 1.25 (1.00–1.57; 0.053) |
| Past-year non-medical use of prescription pain relievers a) | 1.28 (1.26–1.45; <0.001) |
| Past-year non-medical use of prescription stimulants a) | 0.87 (0.71–1.05; 0.149) |
Note: Data are from National Survey on Drug Use and Health.
is a binary variable. All analyses were adjusted for multi-stage, complex survey sampling techniques. The reference group is in a parenthesis.
Discussion
Similar to earlier studies,4,5 cannabis use for medical purposes increased over a recent 7-year period, with the greatest increase in cannabis use prevalence in states that had legalized such use. Further, the association of medical cannabis use with depression, cocaine use disorder, and non-medical use of pain relievers suggests that it may have either been prescribed for those conditions or used on patient initiative for these problems; because NSDUH is cross-sectional, the findings cannot establish temporality.
It is notable that individuals living in states that legalized medical cannabis had greater odds of medical cannabis use. In the case of state legalization, the major increases in medical cannabis use nationally5 most likely occurred in the period immediately after 1996 when California and other early adopter states (e.g., Colorado and Washington) adopted this policy. States that legalized medical cannabis in the years 2013–2020, almost two decades after California, were thus associated with greater odds of medical cannabis use comparable to those early adopter states. Furthermore, legalization or decriminalization of cannabis for recreational use, beginning in Colorado in 2012 and now extending to at least 18 other states, the District of Columbia and Guam, has also taken place further reducing the growth of demand for medical cannabis during the years of this study. The reduced increase in medical cannabis among college graduates may similarly suggest that highly educated adults were early adopters of medical cannabis and showed smaller increases in use in more recent years.
There are two important implications of the persistent increase in medical cannabis use nationally. First, while medical cannabis use is assumed to be predominantly used for chronic pain (64.5%), multiple sclerosis (14.4%), and/or nausea or vomiting [for those with terminally illnesses] (6.2%),12 there is a wide variation of qualifying medical or psychiatric conditions across states.13 Further, there is no consensus across the states or strong therapeutic evidence to support medical cannabis use for specific conditions (e.g., arthritis). Because medical cannabis use is increasing in the US, clinical practice guidelines should be developed with evidence-based principles to follow in counseling patients about medical cannabis use.14,15
Second, there is a lack of available data on the effects of long-term medical cannabis use, limiting understanding of the cumulative public health effects of medical cannabis use. While cannabis does not generally lead to overdose deaths (in contrast to opioids), several unintended consequences (e.g., developing psychosis16 and motor vehicle crashes17) have been documented. Given the increasing medical cannabis use coupled with use for recreational purposes,3 a comprehensive, longitudinal surveillance system is needed to determine long-term benefits and harms of medical cannabis use.
Limitations
Several limitations of this study deserve comment. First, the self-report survey design may have resulted in social desirability bias or recall bias impacting study interpretations. There may also be a misclassification bias when participants reported whether they lived in a state with legalized medical cannabis use. Second, there was no information about the frequency and intensity of medical cannabis use over time. Further, NSDUH did not document the full spectrum of relevant medical and psychiatric conditions with which medical cannabis use may be associated.5 Third, there may be some confounding factors (e.g., state transition from legalized medical use to legalized recreational use over time) that were not accounted for. Fourth, survey sampling and data collection of the NSDUH has changed in early 2020 because of the Covid-19 pandemic. Sensitivity analyses between the years 2019 and 2020 were conducted to (1) identify any potential anomaly due to changes in sampling designs and data collections in 2020, and (2) to examine possible associations between these factors and the onset of the COVID-19 pandemic;18 the data did not show any substantial changes in cannabis use for medical purposes when comparing years between 2019 and 2020.
Conclusions
This study documents a continued nationwide increase in use of cannabis for diverse medical purposes between 2013 and 2020, two decades after California passed legalizing legislation. Substantially increased use of cannabis for medical purposes warrants further research to assess its diverse potential benefits and risks.
Acknowledgement and disclosures
Obtained funding: Dr. Rhee developed and implemented this study under the expected/pending grant from the National Institute on Drug Abuse (R21DA057540).
Patient and public involvement: This is a secondary data analysis using existing data. Patients or the public were not directly involved in the design, or conduct, or reporting, or dissemination plans of research.
Source of Funding:
In the past 3 years, Dr. Rhee was supported in part by the National Institute on Aging (#T32AG019134 and R21AG070666), National Institute of Mental Health (#R21MH117438), and Institute for Collaboration on Health, Intervention, and Policy (InCHIP) of the University of Connecticut. Dr. Rhee serves as a review committee and methodology panel member for Patient-Centered Outcomes Research Institute (PCORI) and Substance Abuse and Mental Health Services Administration (SAMHSA) and has received honoraria payments from both entities. Dr. Rhee has also served as a stakeholder/consultant for PCORI and received consulting fees from PCORI. Dr. Rhee is currently a co-editor-in-chief of Mental Health Science and has received honorarium payments annually from the publisher, John Wiley & Sons, Inc.
Footnotes
CRediT Author Statement: Study concept and design: Rhee & Rosenheck; Data acquisition and statistical analyses: Rhee; Interpretation of data: Rhee & Rosenheck; Drafting of manuscript: Rhee; Critical revision of manuscript for important intellectual content: Rhee & Rosenheck. Rhee had full access to all the data in the study and takes responsibility for the integrity of the data and the accuracy of the data analysis.
Conflicts of Interest: Dr. Rosenheck reported no financial disclosures.
Publisher's Disclaimer: This is a PDF file of an unedited manuscript that has been accepted for publication. As a service to our customers we are providing this early version of the manuscript. The manuscript will undergo copyediting, typesetting, and review of the resulting proof before it is published in its final form. Please note that during the production process errors may be discovered which could affect the content, and all legal disclaimers that apply to the journal pertain.
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