research paper marijuana

• Research article
• Open access
• Published: 04 February 2020

Marijuana legalization and historical trends in marijuana use among US residents aged 12–25: results from the 1979–2016 National Survey on drug use and health

• Xinguang Chen 1 ,
• Xiangfan Chen 2 &
• Hong Yan 2  

BMC Public Health volume  20 , Article number:  156 ( 2020 ) Cite this article

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Marijuana is the most commonly used illicit drug in the United States. More and more states legalized medical and recreational marijuana use. Adolescents and emerging adults are at high risk for marijuana use. This ecological study aims to examine historical trends in marijuana use among youth along with marijuana legalization.

Data ( n  = 749,152) were from the 31-wave National Survey on Drug Use and Health (NSDUH), 1979–2016. Current marijuana use, if use marijuana in the past 30 days, was used as outcome variable. Age was measured as the chronological age self-reported by the participants, period was the year when the survey was conducted, and cohort was estimated as period subtracted age. Rate of current marijuana use was decomposed into independent age, period and cohort effects using the hierarchical age-period-cohort (HAPC) model.

After controlling for age, cohort and other covariates, the estimated period effect indicated declines in marijuana use in 1979–1992 and 2001–2006, and increases in 1992–2001 and 2006–2016. The period effect was positively and significantly associated with the proportion of people covered by Medical Marijuana Laws (MML) (correlation coefficients: 0.89 for total sample, 0.81 for males and 0.93 for females, all three p values < 0.01), but was not significantly associated with the Recreational Marijuana Laws (RML). The estimated cohort effect showed a historical decline in marijuana use in those who were born in 1954–1972, a sudden increase in 1972–1984, followed by a decline in 1984–2003.

The model derived trends in marijuana use were coincident with the laws and regulations on marijuana and other drugs in the United States since the 1950s. With more states legalizing marijuana use in the United States, emphasizing responsible use would be essential to protect youth from using marijuana.

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Introduction

Marijuana use and laws in the united states.

Marijuana is one of the most commonly used drugs in the United States (US) [ 1 ]. In 2015, 8.3% of the US population aged 12 years and older used marijuana in the past month; 16.4% of adolescents aged 12–17 years used in lifetime and 7.0% used in the past month [ 2 ]. The effects of marijuana on a person’s health are mixed. Despite potential benefits (e.g., relieve pain) [ 3 ], using marijuana is associated with a number of adverse effects, particularly among adolescents. Typical adverse effects include impaired short-term memory, cognitive impairment, diminished life satisfaction, and increased risk of using other substances [ 4 ].

Since 1937 when the Marijuana Tax Act was issued, a series of federal laws have been subsequently enacted to regulate marijuana use, including the Boggs Act (1952), Narcotics Control Act (1956), Controlled Substance Act (1970), and Anti-Drug Abuse Act (1986) [ 5 , 6 ]. These laws regulated the sale, possession, use, and cultivation of marijuana [ 6 ]. For example, the Boggs Act increased the punishment of marijuana possession, and the Controlled Substance Act categorized the marijuana into the Schedule I Drugs which have a high potential for abuse, no medical use, and not safe to use without medical supervision [ 5 , 6 ]. These federal laws may have contributed to changes in the historical trend of marijuana use among youth.

Movements to decriminalize and legalize marijuana use

Starting in the late 1960s, marijuana decriminalization became a movement, advocating reformation of federal laws regulating marijuana [ 7 ]. As a result, 11 US states had taken measures to decriminalize marijuana use by reducing the penalty of possession of small amount of marijuana [ 7 ].

The legalization of marijuana started in 1993 when Surgeon General Elder proposed to study marijuana legalization [ 8 ]. California was the first state that passed Medical Marijuana Laws (MML) in 1996 [ 9 ]. After California, more and more states established laws permitting marijuana use for medical and/or recreational purposes. To date, 33 states and the District of Columbia have established MML, including 11 states with recreational marijuana laws (RML) [ 9 ]. Compared with the legalization of marijuana use in the European countries which were more divided that many of them have medical marijuana registered as a treatment option with few having legalized recreational use [ 10 , 11 , 12 , 13 ], the legalization of marijuana in the US were more mixed with 11 states legalized medical and recreational use consecutively, such as California, Nevada, Washington, etc. These state laws may alter people’s attitudes and behaviors, finally may lead to the increased risk of marijuana use, particularly among young people [ 13 ]. Reported studies indicate that state marijuana laws were associated with increases in acceptance of and accessibility to marijuana, declines in perceived harm, and formation of new norms supporting marijuana use [ 14 ].

Marijuana harm to adolescents and young adults

Adolescents and young adults constitute a large proportion of the US population. Data from the US Census Bureau indicate that approximately 60 million of the US population are in the 12–25 years age range [ 15 ]. These people are vulnerable to drugs, including marijuana [ 16 ]. Marijuana is more prevalent among people in this age range than in other ages [ 17 ]. One well-known factor for explaining the marijuana use among people in this age range is the theory of imbalanced cognitive and physical development [ 4 ]. The delayed brain development of youth reduces their capability to cognitively process social, emotional and incentive events against risk behaviors, such as marijuana use [ 18 ]. Understanding the impact of marijuana laws on marijuana use among this population with a historical perspective is of great legal, social and public health significance.

Inconsistent results regarding the impact of marijuana laws on marijuana use

A number of studies have examined the impact of marijuana laws on marijuana use across the world, but reported inconsistent results [ 13 ]. Some studies reported no association between marijuana laws and marijuana use [ 14 , 19 , 20 , 21 , 22 , 23 , 24 , 25 ], some reported a protective effect of the laws against marijuana use [ 24 , 26 ], some reported mixed effects [ 27 , 28 ], while some others reported a risk effect that marijuana laws increased marijuana use [ 29 , 30 ]. Despite much information, our review of these reported studies revealed several limitations. First of all, these studies often targeted a short time span, ignoring the long period trend before marijuana legalization. Despite the fact that marijuana laws enact in a specific year, the process of legalization often lasts for several years. Individuals may have already changed their attitudes and behaviors before the year when the law is enacted. Therefore, it may not be valid when comparing marijuana use before and after the year at a single time point when the law is enacted and ignoring the secular historical trend [ 19 , 30 , 31 ]. Second, many studies adapted the difference-in-difference analytical approach designated for analyzing randomized controlled trials. No US state is randomized to legalize the marijuana laws, and no state can be established as controls. Thus, the impact of laws cannot be efficiently detected using this approach. Third, since marijuana legalization is a public process, and the information of marijuana legalization in one state can be easily spread to states without the marijuana laws. The information diffusion cannot be ruled out, reducing the validity of the non-marijuana law states as the controls to compare the between-state differences [ 31 ].

Alternatively, evidence derived based on a historical perspective may provide new information regarding the impact of laws and regulations on marijuana use, including state marijuana laws in the past two decades. Marijuana users may stop using to comply with the laws/regulations, while non-marijuana users may start to use if marijuana is legal. Data from several studies with national data since 1996 demonstrate that attitudes, beliefs, perceptions, and use of marijuana among people in the US were associated with state marijuana laws [ 29 , 32 ].

Age-period-cohort modeling: looking into the past with recent data

To investigate historical trends over a long period, including the time period with no data, we can use the classic age-period-cohort modeling (APC) approach. The APC model can successfully discompose the rate or prevalence of marijuana use into independent age, period and cohort effects [ 33 , 34 ]. Age effect refers to the risk associated with the aging process, including the biological and social accumulation process. Period effect is risk associated with the external environmental events in specific years that exert effect on all age groups, representing the unbiased historical trend of marijuana use which controlling for the influences from age and birth cohort. Cohort effect refers to the risk associated with the specific year of birth. A typical example is that people born in 2011 in Fukushima, Japan may have greater risk of cancer due to the nuclear disaster [ 35 ], so a person aged 80 in 2091 contains the information of cancer risk in 2011 when he/she was born. Similarly, a participant aged 25 in 1979 contains information on the risk of marijuana use 25 years ago in 1954 when that person was born. With this method, we can describe historical trends of marijuana use using information stored by participants in older ages [ 33 ]. The estimated period and cohort effects can be used to present the unbiased historical trend of specific topics, including marijuana use [ 34 , 36 , 37 , 38 ]. Furthermore, the newly established hierarchical APC (HAPC) modeling is capable of analyzing individual-level data to provide more precise measures of historical trends [ 33 ]. The HAPC model has been used in various fields, including social and behavioral science, and public health [ 39 , 40 ].

Several studies have investigated marijuana use with APC modeling method [ 17 , 41 , 42 ]. However, these studies covered only a small portion of the decades with state marijuana legalization [ 17 , 42 ]. For example, the study conducted by Miech and colleagues only covered periods from 1985 to 2009 [ 17 ]. Among these studies, one focused on a longer state marijuana legalization period, but did not provide detailed information regarding the impact of marijuana laws because the survey was every 5 years and researchers used a large 5-year age group which leads to a wide 10-year birth cohort. The averaging of the cohort effects in 10 years could reduce the capability of detecting sensitive changes of marijuana use corresponding to the historical events [ 41 ].

Purpose of the study

In this study, we examined the historical trends in marijuana use among youth using HAPC modeling to obtain the period and cohort effects. These two effects provide unbiased and independent information to characterize historical trends in marijuana use after controlling for age and other covariates. We conceptually linked the model-derived time trends to both federal and state laws/regulations regarding marijuana and other drug use in 1954–2016. The ultimate goal is to provide evidence informing federal and state legislation and public health decision-making to promote responsible marijuana use and to protect young people from marijuana use-related adverse consequences.

Materials and methods

Data sources and study population.

Data were derived from 31 waves of National Survey on Drug Use and Health (NSDUH), 1979–2016. NSDUH is a multi-year cross-sectional survey program sponsored by the Substance Abuse and Mental Health Services Administration. The survey was conducted every 3 years before 1990, and annually thereafter. The aim is to provide data on the use of tobacco, alcohol, illicit drug and mental health among the US population.

Survey participants were noninstitutionalized US civilians 12 years of age and older. Participants were recruited by NSDUH using a multi-stage clustered random sampling method. Several changes were made to the NSDUH after its establishment [ 43 ]. First, the name of the survey was changed from the National Household Survey on Drug Abuse (NHSDA) to NSDUH in 2002. Second, starting in 2002, adolescent participants receive $30 as incentives to improve the response rate. Third, survey mode was changed from personal interviews with self-enumerated answer sheets (before 1999) to the computer-assisted person interviews (CAPI) and audio computer-assisted self-interviews (ACASI) (since 1999). These changes may confound the historical trends [ 43 ], thus we used two dummy variables as covariates, one for the survey mode change in 1999 and another for the survey method change in 2002 to control for potential confounding effect.

Data acquisition

Data were downloaded from the designated website ( https://nsduhweb.rti.org/respweb/homepage.cfm ). A database was used to store and merge the data by year for analysis. Among all participants, data for those aged 12–25 years ( n  = 749,152) were included. We excluded participants aged 26 and older because the public data did not provide information on single or two-year age that was needed for HAPC modeling (details see statistical analysis section). We obtained approval from the Institutional Review Board at the University of Florida to conduct this study.

Variables and measurements

Current marijuana use: the dependent variable. Participants were defined as current marijuana users if they reported marijuana use within the past 30 days. We used the variable harmonization method to create a comparable measure across 31-wave NSDUH data [ 44 ]. Slightly different questions were used in NSDUH. In 1979–1993, participants were asked: “When was the most recent time that you used marijuana or hash?” Starting in 1994, the question was changed to “How long has it been since you last used marijuana or hashish?” To harmonize the marijuana use variable, participants were coded as current marijuana users if their response to the question indicated the last time to use marijuana was within past 30 days.

Chronological age, time period and birth cohort were the predictors. (1) Chronological age in years was measured with participants’ age at the survey. APC modeling requires the same age measure for all participants [ 33 ]. Since no data by single-year age were available for participants older than 21, we grouped all participants into two-year age groups. A total of 7 age groups, 12–13, ..., 24–25 were used. (2) Time period was measured with the year when the survey was conducted, including 1979, 1982, 1985, 1988, 1990, 1991... 2016. (3). Birth cohort was the year of birth, and it was measured by subtracting age from the survey year.

The proportion of people covered by MML: This variable was created by dividing the population in all states with MML over the total US population. The proportion was computed by year from 1996 when California first passed the MML to 2016 when a total of 29 states legalized medical marijuana use. The estimated proportion ranged from 12% in 1996 to 61% in 2016. The proportion of people covered by RML: This variable was derived by dividing the population in all states with RML with the total US population. The estimated proportion ranged from 4% in 2012 to 21% in 2016. These two variables were used to quantitatively assess the relationships between marijuana laws and changes in the risk of marijuana use.

Covariates: Demographic variables gender (male/female) and race/ethnicity (White, Black, Hispanic and others) were used to describe the study sample.

Statistical analysis

We estimated the prevalence of current marijuana use by year using the survey estimation method, considering the complex multi-stage cluster random sampling design and unequal probability. A prevalence rate is not a simple indicator, but consisting of the impact of chronological age, time period and birth cohort, named as age, period and cohort effects, respectively. Thus, it is biased if a prevalence rate is directly used to depict the historical trend. HAPC modeling is an epidemiological method capable of decomposing prevalence rate into mutually independent age, period and cohort effects with individual-level data, while the estimated period and cohort effects provide an unbiased measure of historical trend controlling for the effects of age and other covariates. In this study, we analyzed the data using the two-level HAPC cross-classified random-effects model (CCREM) [ 36 ]:

Where M ijk represents the rate of marijuana use for participants in age group i (12–13, 14,15...), period j (1979, 1982,...) and birth cohort k (1954–55, 1956–57...); parameter α i (age effect) was modeled as the fixed effect; and parameters β j (period effect) and γ k (cohort effect) were modeled as random effects; and β m was used to control m covariates, including the two dummy variables assessing changes made to the NSDUH in 1999 and 2002, respectively.

The HAPC modeling analysis was executed using the PROC GLIMMIX. Sample weights were included to obtain results representing the total US population aged 12–25. A ridge-stabilized Newton-Raphson algorithm was used for parameter estimation. Modeling analysis was conducted for the overall sample, stratified by gender. The estimated age effect α i , period β j and cohort γ k (i.e., the log-linear regression coefficients) were directly plotted to visualize the pattern of change.

To gain insight into the relationship between legal events and regulations at the national level, we listed these events/regulations along with the estimated time trends in the risk of marijuana from HAPC modeling. To provide a quantitative measure, we associated the estimated period effect with the proportions of US population living with MML and RML using Pearson correlation. All statistical analyses for this study were conducted using the software SAS, version 9.4 (SAS Institute Inc., Cary, NC).

Sample characteristics

Data for a total of 749,152 participants (12–25 years old) from all 31-wave NSDUH covering a 38-year period were analyzed. Among the total sample (Table  1 ), 48.96% were male and 58.78% were White, 14.84% Black, and 18.40% Hispanic.

Prevalence rate of current marijuana use

As shown in Fig.  1 , the estimated prevalence rates of current marijuana use from 1979 to 2016 show a “V” shaped pattern. The rate was 27.57% in 1979, it declined to 8.02% in 1992, followed by a gradual increase to 14.70% by 2016. The pattern was the same for both male and female with males more likely to use than females during the whole period.

Prevalence rate (%) of current marijuana use among US residents 12 to 25 years of age during 1979–2016, overall and stratified by gender. Derived from data from the 1979–2016 National Survey on Drug Use and Health (NSDUH)

HAPC modeling and results

Estimated age effects α i from the CCREM [ 1 ] for current marijuana use are presented in Fig.  2 . The risk by age shows a 2-phase pattern –a rapid increase phase from ages 12 to 19, followed by a gradually declining phase. The pattern was persistent for the overall sample and for both male and female subsamples.

Age effect for the risk of current marijuana use, overall and stratified by male and female, estimated with hierarchical age-period-cohort modeling method with 31 waves of NSDUH data during 1979–2016. Age effect α i were log-linear regression coefficients estimated using CCREM (1), see text for more details

The estimated period effects β j from the CCREM [ 1 ] are presented in Fig.  3 . The period effect reflects the risk of current marijuana use due to significant events occurring over the period, particularly federal and state laws and regulations. After controlling for the impacts of age, cohort and other covariates, the estimated period effect indicates that the risk of current marijuana use had two declining trends (1979–1992 and 2001–2006), and two increasing trends (1992–2001 and 2006–2016). Epidemiologically, the time trends characterized by the estimated period effects in Fig. 3 are more valid than the prevalence rates presented in Fig. 1 because the former was adjusted for confounders while the later was not.

Period effect for the risk of marijuana use for US adolescents and young adults, overall and by male/female estimated with hierarchical age-period-cohort modeling method and its correlation with the proportion of US population covered by Medical Marijuana Laws and Recreational Marijuana Laws. Period effect β j were log-linear regression coefficients estimated using CCREM (1), see text for more details

Correlation of the period effect with proportions of the population covered by marijuana laws: The Pearson correlation coefficient of the period effect with the proportions of US population covered by MML during 1996–2016 was 0.89 for the total sample, 0.81 for male and 0.93 for female, respectively ( p  < 0.01 for all). The correlation between period effect and proportion of US population covered by RML was 0.64 for the total sample, 0.59 for male and 0.49 for female ( p  > 0.05 for all).

Likewise, the estimated cohort effects γ k from the CCREM [ 1 ] are presented in Fig.  4 . The cohort effect reflects changes in the risk of current marijuana use over the period indicated by the year of birth of the survey participants after the impacts of age, period and other covariates are adjusted. Results in the figure show three distinctive cohorts with different risk patterns of current marijuana use during 1954–2003: (1) the Historical Declining Cohort (HDC): those born in 1954–1972, and characterized by a gradual and linear declining trend with some fluctuations; (2) the Sudden Increase Cohort (SIC): those born from 1972 to 1984, characterized with a rapid almost linear increasing trend; and (3) the Contemporary Declining Cohort (CDC): those born during 1984 and 2003, and characterized with a progressive declining over time. The detailed results of HAPC modeling analysis were also shown in Additional file 1 : Table S1.

Cohort effect for the risk of marijuana use among US adolescents and young adults born during 1954–2003, overall and by male/female, estimated with hierarchical age-period-cohort modeling method. Cohort effect γ k were log-linear regression coefficients estimated using CCREM (1), see text for more details

This study provides new data regarding the risk of marijuana use in youth in the US during 1954–2016. This is a period in the US history with substantial increases and declines in drug use, including marijuana; accompanied with many ups and downs in legal actions against drug use since the 1970s and progressive marijuana legalization at the state level from the later 1990s till today (see Additional file 1 : Table S2). Findings of the study indicate four-phase period effect and three-phase cohort effect, corresponding to various historical events of marijuana laws, regulations and social movements.

Coincident relationship between the period effect and legal drug control

The period effect derived from the HAPC model provides a net effect of the impact of time on marijuana use after the impact of age and birth cohort were adjusted. Findings in this study indicate that there was a progressive decline in the period effect during 1979 and 1992. This trend was corresponding to a period with the strongest legal actions at the national level, the War on Drugs by President Nixon (1969–1974) President Reagan (1981–1989) [ 45 ], and President Bush (1989) [ 45 ],and the Anti-Drug Abuse Act (1986) [ 5 ].

The estimated period effect shows an increasing trend in 1992–2001. During this period, President Clinton advocated for the use of treatment to replace incarceration (1992) [ 45 ], Surgeon General Elders proposed to study marijuana legalization (1993–1994) [ 8 ], President Clinton’s position of the need to re-examine the entire policy against people who use drugs, and decriminalization of marijuana (2000) [ 45 ] and the passage of MML in eight US states.

The estimated period effect shows a declining trend in 2001–2006. Important laws/regulations include the Student Drug Testing Program promoted by President Bush, and the broadened the public schools’ authority to test illegal drugs among students given by the US Supreme Court (2002) [ 46 ].

The estimated period effect increases in 2006–2016. This is the period when the proportion of the population covered by MML progressively increased. This relation was further proved by a positive correlation between the estimated period effect and the proportion of the population covered by MML. In addition, several other events occurred. For example, over 500 economists wrote an open letter to President Bush, Congress and Governors of the US and called for marijuana legalization (2005) [ 47 ], and President Obama ended the federal interference with the state MML, treated marijuana as public health issues, and avoided using the term of “War on Drugs” [ 45 ]. The study also indicates that the proportion of population covered by RML was positively associated with the period effect although not significant which may be due to the limited number of data points of RML. Future studies may follow up to investigate the relationship between RML and rate of marijuana use.

Coincident relationship between the cohort effect and legal drug control

Cohort effect is the risk of marijuana use associated with the specific year of birth. People born in different years are exposed to different laws, regulations in the past, therefore, the risk of marijuana use for people may differ when they enter adolescence and adulthood. Findings in this study indicate three distinctive cohorts: HDC (1954–1972), SIC (1972–1984) and CDC (1984–2003). During HDC, the overall level of marijuana use was declining. Various laws/regulations of drug use in general and marijuana in particular may explain the declining trend. First, multiple laws passed to regulate the marijuana and other substance use before and during this period remained in effect, for example, the Marijuana Tax Act (1937), the Boggs Act (1952), the Narcotics Control Act (1956) and the Controlled Substance Act (1970). Secondly, the formation of government departments focusing on drug use prevention and control may contribute to the cohort effect, such as the Bureau of Narcotics and Dangerous Drugs (1968) [ 48 ]. People born during this period may be exposed to the macro environment with laws and regulations against marijuana, thus, they may be less likely to use marijuana.

Compared to people born before 1972, the cohort effect for participants born during 1972 and 1984 was in coincidence with the increased risk of using marijuana shown as SIC. This trend was accompanied by the state and federal movements for marijuana use, which may alter the social environment and public attitudes and beliefs from prohibitive to acceptive. For example, seven states passed laws to decriminalize the marijuana use and reduced the penalty for personal possession of small amount of marijuana in 1976 [ 7 ]. Four more states joined the movement in two subsequent years [ 7 ]. People born during this period may have experienced tolerated environment of marijuana, and they may become more acceptable of marijuana use, increasing their likelihood of using marijuana.

A declining cohort CDC appeared immediately after 1984 and extended to 2003. This declining cohort effect was corresponding to a number of laws, regulations and movements prohibiting drug use. Typical examples included the War on Drugs initiated by President Nixon (1980s), the expansion of the drug war by President Reagan (1980s), the highly-publicized anti-drug campaign “Just Say No” by First Lady Nancy Reagan (early 1980s) [ 45 ], and the Zero Tolerance Policies in mid-to-late 1980s [ 45 ], the Anti-Drug Abuse Act (1986) [ 5 ], the nationally televised speech of War on Drugs declared by President Bush in 1989 and the escalated War on Drugs by President Clinton (1993–2001) [ 45 ]. Meanwhile many activities of the federal government and social groups may also influence the social environment of using marijuana. For example, the Federal government opposed to legalize the cultivation of industrial hemp, and Federal agents shut down marijuana sales club in San Francisco in 1998 [ 48 ]. Individuals born in these years grew up in an environment against marijuana use which may decrease their likelihood of using marijuana when they enter adolescence and young adulthood.

This study applied the age-period-cohort model to investigate the independent age, period and cohort effects, and indicated that the model derived trends in marijuana use among adolescents and young adults were coincident with the laws and regulations on marijuana use in the United States since the 1950s. With more states legalizing marijuana use in the United States, emphasizing responsible use would be essential to protect youth from using marijuana.

Limitations

This study has limitations. First, study data were collected through a household survey, which is subject to underreporting. Second, no causal relationship can be warranted using cross-sectional data, and further studies are needed to verify the association between the specific laws/regulation and the risk of marijuana use. Third, data were available to measure single-year age up to age 21 and two-year age group up to 25, preventing researchers from examining the risk of marijuana use for participants in other ages. Lastly, data derived from NSDUH were nation-wide, and future studies are needed to analyze state-level data and investigate the between-state differences. Although a systematic review of all laws and regulations related to marijuana and other drugs is beyond the scope of this study, findings from our study provide new data from a historical perspective much needed for the current trend in marijuana legalization across the nation to get the benefit from marijuana while to protect vulnerable children and youth in the US. It provides an opportunity for stack-holders to make public decisions by reviewing the findings of this analysis together with the laws and regulations at the federal and state levels over a long period since the 1950s.

Availability of data and materials

The data of the study are available from the designated repository ( https://nsduhweb.rti.org/respweb/homepage.cfm ).

Abbreviations

Audio computer-assisted self-interviews

Age-period-cohort modeling

Computer-assisted person interviews

Cross-classified random-effects model

Contemporary Declining Cohort

Hierarchical age-period-cohort

Historical Declining Cohort

Medical Marijuana Laws

National Household Survey on Drug Abuse

National Survey on Drug Use and Health

Recreational Marijuana Laws

Sudden Increase Cohort

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Estimated Age, Period, Cohort Effects for the Trend of Marijuana Use in Past Month among Adolescents and Emerging Adults Aged 12 to 25 Years, NSDUH, 1979-2016. Table S2. Laws at the federal and state levels related to marijuana use.

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Processing and extraction methods of medicinal cannabis: a narrative review

• Masoumeh Pourseyed Lazarjani 1 ,
• Owen Young 2 ,
• Lidya Kebede 1 &
• Ali Seyfoddin   ORCID: orcid.org/0000-0003-4343-9905 1  

Journal of Cannabis Research volume  3 , Article number:  32 ( 2021 ) Cite this article

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Introduction

As the cannabis industry transitions from a black market to a legal market, product development, and methods of extraction have become a focal point. To date, more than thousands of chemical constituents have been identified from the cannabis plant, all of which possess different chemical properties that require different conditions for preservation during drying and extraction. However, scientific publications that explore these areas for the cannabis plant are currently lacking.

This is a narrative review paper which focuses on critiquing drying and extraction methods of Cannabis sativa L. plant. Relevant keywords such as medicinal cannabis, extraction, solvent, cannabinoids, and terpenes have been searched in PubMed, EMBASE, MEDLINE, Google Scholar, and Cochrane Library (Wiley) databases.

To find relevant papers for this narrative review, 93 papers have been reviewed. Among them, 12 irrelevant papers were discarded. The excluded papers were either about hemp seed oil or hemp fiber and protein. Based on this review, solvent extraction is the most common method for cannabis plants. Although solventless and hydrodynamic extraction are known for their high yield and feasibility, more investigation is needed in these areas. Regarding the drying process, hang-drying is the most convenient method; however, it may be substituted by freeze-drying in the near future.

This review analyses various drying and extraction processes to guide the selection of suitable methods for various types of cannabis products and applications. This is done by outlining traditional and modern methods of drying techniques, exploring the importance of solvents for extraction, visiting solventless extraction procedures, and finally comparing conventional and alternative methods of extraction.

In conclusion, based on the current knowledge, using organic solvents is the most convenient method for medicinal cannabis extraction. However, more research is needed for some of the drying and extraction methods. Also, developing a green and sustainable cannabis extraction method should be considered for future studies.

Cannabis is a flowering plant from the Cannabaceae family and genus Cannabis . Cannabis sativa and Cannabis indica are generally well known, while subspecies Cannabis ruderalis is often overlooked due to its limited ability in producing active compounds (Gloss 2015 ). Hybrid species are variable depending on the parent plant; they can be sativa dominant, indica dominant, or balanced. Within the genus, the number of species is disputed, and the traditional nomenclature of sativa and indica may not be correct or useful in determining therapeutic potential. In any case, cannabis is dioicous, meaning it exhibits both male and female reproductive structures in separate individual plants. Female cannabis plants produce more glandular trichomes compared to the male plant. Among all the known compounds in the cannabis plant, cannabinoids and terpenes are the most active compounds with therapeutic potential which largely synthesized in those glandular trichomes. These compounds have shown to have therapeutic effects on a range of conditions such as metabolic disorders, neurodegenerative disorders, movement disorders, anorexia in HIV patients, nausea, and pain after chemotherapy in cancer patients (Namdar et al. 2018 ; Romano and Hazekamp 2013 ) (Table 1 ).

As the cannabis industry transitions from a black market to a legal market, product development, and methods of extraction have become a focal point. Traditionally, the dried cannabis flower has been a popular product for the use of smoking and vaping. However, as the industry expands, the need for cannabis products in different forms and higher potency also increases. Currently available products, medicinal or recreational, come in the forms of topicals, edibles, beverages, and vaporization cartridges. Each product type presents its own set of advantages and disadvantages allowing for customization to serve a particular purpose (Blake and Nahtigal 2019 ). For pharmaceutical and food applications, the extraction and isolation of active components and combinations of identified cannabinoids are critical steps that should be explored (Fathordoobady et al. 2019 ).

The separation of bioactive compounds has recently become rapidly sought after by the pharmaceutical and food industries. This is due to the increased understanding of the dynamic nature and potential of diverse bioactive molecules from natural sources (Azmir et al. 2013 ). To further continue scientific research on the selection, identification, and characterization of bioactive compounds, the selection of a suitable extraction process is imperative (Azmir et al. 2013 ). Failing to designate a fitting method of sample preparation can jeopardize any analytical procedure resulting in unfavorable outcomes. However, the field of extraction is often neglected and is not studied as thoroughly as other processes. This creates a gap in the literature that should be explored more extensively (Smith 2003 ). The process of extraction is commonly employed to obtain target bioactive compounds from complex plant matter, yet it can also be altered to cater for many purposes, for instance, increasing the selectivity and sensitivity of bioassays by increasing the concentration of a target compound, as well as providing a potent and reproducible sample matrix (Smith 2003 ). Valizadehderakhshan et al. ( 2021 ) compared different extraction methods for seed and trichomes in Cannabis sativa L. They also reviewed various parameters that affect cannabinoid transformation after extraction (Valizadehderakhshan et al. 2021 ).

Different methods of extraction will yield varying degrees of extract quality and composition depending on the procedure and substances used (Blake and Nahtigal 2019 ). This review focuses on various drying and extraction methods while comparing conventional and most recent methods. For example, conventional methods of extraction including Soxhlet and dynamic maceration have longer extraction time and large amounts of solvent are required to complete the extraction process (Agarwal et al. 2018 ). Recent methods including ultrasonic-assisted, microwave-assisted, supercritical fluid, and pressurized liquid extraction processes can be considered as an alternative, slightly greener, options as opposed to the conventional methods. These procedures reduce the need for synthetic and organic solvents, cut down on operational time, and produce a better quality extract with a higher yield (Azmir et al. 2013). Solventless methods such as dry sieve and water extraction are particularly known to extract entire trichomes. Hydrocarbon extraction methods can be used to avoid unwanted water and pigments such as chlorophyll. Ethanol can extract flavonoids, while carbon dioxide can be manipulated to extract different compounds depending on the conditions (Blake and Nahtigal 2019 ).

The characteristics of the product must be considered when deciding on a method. For example, depending on the application, cannabinoids can be extracted in either acidic or neutral form. The preservation of acidic cannabinoids requires extraction to be completed at room temperature (Citti et al. 2016 ). To decarboxylate acidic cannabinoids into neutral form, high temperatures are recommended for extraction, although a higher temperature may result in the loss of some terpenes and minor constituents (Fathordoobady et al. 2019 ). Therefore, the selection of an appropriate extraction procedure will benefit future stages of development by minimizing the requirements for refinements (Blake and Nahtigal 2019 ). To further understand the processes and possible outcomes, this review will explore different methods of drying and extraction procedures used for the cannabis plant.

This paper is a narrative review paper which focuses on drying, extraction, and post-extraction methods for Cannabis sativa L. plant. A combination of keywords such as medicinal cannabis, extraction, solvent, and cannabinoids have been searched in databases such as PubMed, EMBASE, MEDLINE, Google Scholar, and Cochrane Library (Wiley) from 1977 to 2021 in English.

The focus of this narrative review was on Cannabis sativa , initially where 93 papers were identified. Papers on various drying and extraction methods specifically for Cannabis sativa L. were included while those for using hemp as fiber and protein sources were excluded. Overall, 12 papers about cannabis seed oil, hemp seed oil, or hemp plant were excluded as this review focuses on the oil coming from flowers. In the end, 81 related papers about various drying, extraction, and post-harvest processes were carefully reviewed.

Influence of external factors on cannabis

External factors such as light duration, oxygen, and harvest time (floral maturity) have been shown to influence the secondary metabolite production in cannabis (Liu et al. 2015 ; Namdar et al. 2019 ). A 4-year study by Lindholst ( 2010 ) found that cannabinoid stability is affected by temperature, light, and air. Three conditions were used to store cannabis resin (hashish slabs) and extract (by the solvent): room temperature and 4 °C both with visible light exposure and darkness, and − 20 °C in darkness. The study identified that in cannabis resin, light exposure can affect the decarboxylation of THCA and the degradation of THC. This is evident as the half-life increased by 40% in darkness. However, it was observed that light was only partially influential. The resin samples that were placed at room temperature, in either light or dark settings, only exhibited little differences in the degradation of neutral THC. The dense color and structure of resin are thought to be the reason behind the reduced light sensitivity of THC. Accordingly, it is suspected that the exposure of light on resin only reaches the cannabinoids on the surface resulting in low degradation levels. This theory is further illustrated when a comparison was done between the degradation levels of both acidic and neutral THC levels in cannabis resin and cannabis extract. It was observed that both the neutral and acidic forms of THC in the cannabis extract degraded significantly more through light exposure. Furthermore, compared to resin, cannabis extract had a 10 times lower half-life (35 days for extract and 330 days for resin), while THCA decreased to nondetectable levels after 140 days. The neutral forms, in the extract, increased during this period, although THC concentrations were reduced to 1.7% after 2 years at room temperature with light exposure. It was also found that extracts stored at 4 °C showed the same pattern, but degradation was slower, while at − 20 °C all measured cannabinoids remained unchanged during the study period (Lindholst 2010 ). Danziger and Bernstein ( 2021a , b ) evaluated the effect of light on three chemovars of cannabis under four different light conditions. In this study, light as the key factor affected the profile and yield of cannabis chemovars. To be precise, using blue to red lights (1:1 and 1:4 ratios) had the highest yield compared to white LED light. In addition, CBGA as a primary cannabinoid and precursor for many cannabinoids increased by using blue light (Danziger and Bernstein 2021a ). The same authors in another study investigated the effect of architectural manipulation of the plant on the cannabinoid’s standardization. Defoliation, removing primary and secondary branches, and pruning have been considered as a part of eight various architectural manipulation treatments in different light intensities. Results showed that plant architectural modulation affects cannabinoid profile while no changes has been reported in the decarboxylation of cannabinoids (Danziger and Bernstein 2021b ). Saloner and Bernstein ( 2021 ) evaluated the effect of nitrogen supply as an environmental factor on cannabinoids and terpenes. Results showed that the concentration of THCA and CBDA decreases by increasing the amount of nitrogen 69% and 63%, respectively. Bernstein et al. ( 2019 ) evaluated the effect of common minerals on the cannabinoid profile by adding humic acid (HA), phosphor (P), nitrogen (N), and potassium (K) to the commercial treatment into irrigation solution for a high THC cannabis chemovar. Each of the supplements affected the cannabinoid concentrations differently based on the organ and its location in the plant. For example, adding NPK supplement increased 71% the amount of CBG in the flower, while it decreased the amount of CBN in the flowers and leaves by 38% and 36%, respectively (Bernstein et al. 2019 ).

For many applications, the dried version of the cannabis herb is required; however, like many plants, cannabis contains approximately 80% water. For this reason, drying is considered an essential step for product development (Hawes and Cohen 2015 ). Drying the plant not only prevents the growth of microorganisms that would otherwise rot plant tissue (based on ASTM D8196-18 which is a standard practice for determination of water activity (aw) in cannabis flower), it would also enable long term storage while maintaining potency, taste, medicinal properties, and efficacy (Hawes and Cohen 2015 ). This is done by maintaining the water activity level between 0.55 and 0.65 aw, minimizing the risk of mold or fungal infection while preserving the quality of the flower (ASTM D8196-18).

Air-drying, also known as hang-drying

Hang-drying or air-drying is considered the oldest way of drying cannabis plants after harvest (Fig.  1 ) that requires no dedicated equipment (Ross and ElSohly 1996 ). Slow-drying includes placing whole plants or separated inflorescence in a cool dark room with a temperature between 18 and 25 °C and humidity between 45 and 55%, either hung from a string or laid out on drying screens (Hawes and Cohen 2015 ). Ross and ElSohly ( 1996 ) applied four treatments for air-drying to evaluate the efficacy of each condition in producing the highest yield of cannabis products. The treatments were extracted immediately, after the flower harvest at room temperature (0.29% yield, w/v) (A), after 1 week of air-drying at room temperature (0.20% yield based on wet material, v/w) (B), after 1 week of air-drying followed by storage for 1 month at room temperature (0.16% yield based on wet material, w/v) (C), and air-drying for 1 week and stored in paper bags for 3 months at room temperature (0.13% yield based on wet material, v/w) (D). From this experiment, it was found that the yield from treatments A to D decreased from 29 to 13%, respectively (Ross and ElSohly 1996 ). Inconveniences of this method include the manual removal of leaves and buds from the stem as well as the time taken to complete the overall process. The separation is crucial as different parts dry at different rates; therefore, a lack of completing this step may result in uneven drying. Consequently, a disadvantage of removing buds from stems is the possibility of producing a product with a harsher taste. Another detriment of this method is the involvement of gravity. The water from the top part of the plant will absorb into the lower parts leading to a slower and uneven drying process. To speed up the procedure, heaters, fans, and dehumidifiers can be used. However, fast-drying can lead to a harsher taste as opposed to slow-drying which produces smoother tasting products. It is also believed that speeding up the drying process can prevent the plant from reaching peak potency in the curing phase (Hawes and Cohen 2015 ). Coffman and Gentner ( 1974 ) evaluated the effect of drying conditions on the cannabinoid profile. They stored the cannabis hang dried leaves in 65, 85, and 105 °C for 1, 4, 16, and 64 h to compare the mean percentage of total cannabinoid content. The results were shown that the percentage of total cannabinoids was decreased by increasing time and temperature. To be precise, the percentage mean weight loss of total cannabinoids increased from 7.5 to 11% in 65 °C after 1 h and 105 °C after 64 h, respectively.

Air-drying (hang-drying) of the cannabis plant

Oven-drying

A faster direct method of drying is the oven-drying approach (Mujumdar 2006 ). This method can be carried out in either a vacuum chamber, vacuum desiccator, or in a drying oven with or without air circulation (Hawes and Cohen 2015 ). To illustrate the outcomes of the process, an early study tested out four different oven conditions to compare the end products. Inflorescences were dried for 1, 4, 16, and 64 h at 65, 85, and 105 °C. After extraction with ethanol, gas chromatography showed that the yield of CBD and THC decreased as the temperature and time of drying increased. It was also observed that at temperature 105 °C, the thermal degradation of THC increased the CBN content (Coffman and Gentner 1974 ). CBN is considered a less potent psychoactive and mild analgesic; therefore, conversion of THC to CBN will decrease the therapeutic potential (Citti et al. 2016 ).

Additionally, using high temperatures and excessive drying can result in the loss of key components (Hawes and Cohen 2015 ). This statement can be the reason for the lack of information about using oven dying in the cannabis industry. This was highlighted in a study that compared the ratio of cannabinoid and by-product produced during vaporization. The cannabis material was placed in the desiccator for 5 days to dry out, while the smoke condensate and vaporized condensate trapped in the organic solvent were dried with a rotary evaporator at 40 °C. These approaches had produced intense fragrance which is indicative of the loss of terpenoids and other volatile components (Pomahacova et al. 2009 ).

Freeze-drying

Freeze-drying (also known as lyophilization) has become a popular option due to the increasing demand for high-quality medicinal cannabis. The freeze-drying method holds the cannabis plant at temperatures far below those of air or oven, while removing the water content, in the form of vapor, via sublimation in a vacuum chamber (Mujumdar 2006 ). The nascent legal cannabis industry claims that freeze-drying preserves the volatile compounds and acidic form of cannabinoids (Tambunan et al. 2001 ). It is generally agreed that the end products of freeze-drying are considered high quality compared to other methods of drying. This is due to the structural rigidity found on the surface of frozen materials where sublimation occurs, preventing the disintegration of the solid matrix and resulting in a porous, unaltered structure (Mujumdar 2006 ). When assessing the end product produced by freeze-drying, it was found that the composition is largely unaffected from that found in the plant (Tambunan et al. 2001 ). A disadvantage of freeze-drying is the cost of operation. This procedure requires an intense amount of energy to maintain such temperatures, vacuum, and long-running time (Mujumdar 2006 ).

Comparing the different drying methods, we can safely state that the approach elected will affect the yield and cannabinoid profiles in the extracts. Therefore, the selection of a drying procedure will largely alter the outcomes (Coffman and Gentner 1974 ). The process of hang-drying cannabis was found to be time-consuming as it can take several days, while the main factors that increase the rate of drying were determined to be moving air and low humidity (Ross and ElSohly 1996 ). In contrast, the oven-drying method was observed to be faster, but readily volatile compounds and neutral forms of cannabinoids decreased in extracts to almost non-detectable concentrations, affecting therapeutic potential (Coffman and Gentner 1974 ). To address this issue, freeze-drying is thought to be the preferred method. Freeze-drying enables the preservation of flavor qualities in many foods, themselves often due to the presence of volatile compounds (Tambunan et al. 2001 ).

In all the drying methods mentioned above, humidity, temperature, ventilation rate, and time are the most important parameters to be optimized. Incorrect drying conditions may cause decarboxylation of acidic cannabinoids and loss of terpenes. The presence of light, oxygen, and heat may also cause degradation in cannabinoids and terpenes and can affect the taste (Jin and Chen 2019 ).

Curing is the final post-harvest procedure that allows for the development of the maximum flavor in the cannabis plant (Vogel 2018 ). Jin et al. ( 2019 ) believed that the best temperature and humidity for curing are at 18 °C and 60% RH for 14 days. Green et al. ( 2018 ) suggested keeping the trimmed flowers in a can for up to 4 weeks in a dark cupboard while opening the lid every day for about 6 h is the best method for curing (Jin and Chen 2019 ). At temperatures between 15–21 °C and 45–55% humidity, enzymes and aerobic bacteria will be in the optimum condition to breakdown undesired sugars and degrade minerals. Curing can reduce the harsh smell and the sense of throat burning during smoking or vaping as well as increasing the shelf life by minimizing mold growth. It is also believed that curing can increase cannabis potency as the number of cannabinoids such as THC and CBN will increase by curing. Although curing is one of the most significant post-harvest stages for the cannabis plant, there are not enough academic investigations around this area.

Extraction methods

Cannabis extraction can be used to concentrate target components for product development. There are important parameters that can affect the yield of the cannabis extract such as mean particle size, size distribution, temperature, rate of agitation, and extraction time (Fathordoobady et al. 2019 ). Solventless, solvent-based, convention, and alternative methods of extraction are explored concerning cannabis extraction.

Solventless extraction

Long-established solventless methods such as dry-sieving, water extraction, and rosin press extraction lack coverage in literature due to outdated techniques and difficulty in scaling despite having simple procedures. Dry sieve extraction produces a powder-like Kief with a potency of approximately 35–50% THC. The process of dry-sieving begins by beating dried cannabis against a mesh screen and forcing the trichomes to separate and fall off. The final product can either be pressed further into hashish or mixed with dried flowers. This simple procedure is time-consuming and labor-intensive, therefore, not popular for the industrial level. Water extraction produces roughly the same potency of THC as the dry sieve method, although it also depends on the potency of the starting material. The procedure begins by placing the cannabis plant in a mesh bag immersing it in ice water and finally stirring it to knock the trichome off. The trichome is further filtered through a series of screens then allowed to settle before collecting and drying the final product, commonly known as water hash or bubble hash. Similarly, to dry sieving, this process is difficult to upscale as well as limited control of potency (Blake and Nahtigal 2019 ).

Solventless extraction exploits the fact that cannabinoids are semi-liquid and can be extracted by suitable heating and pressure. Rosin extraction uses compression and heat to obtain oils and rosin. Rosin extraction can be as simple as using a hair straightener for recreational extractions. For more commercial medicinal applications, a modified hat press is adopted. For both methods, high pressure at low temperatures is not achievable; therefore, the retention of terpenes is limited (analytical cannabis.com) (Lamy et al. 2018 ). To prevent high-temperature changes, a typical pneumatic press can be used, exerting some lower temperatures and preserving the terpenes. Pressures up to 137.8 MPa can be generated in some pneumatic presses.

Solvent-based extraction

Solvent-based extraction methods such as Soxhlet, maceration both static and dynamic, ultrasonic-assisted extraction, and microwave-assisted extraction require a solvent to complete the extraction process. A variety of solvents can be used to extract cannabinoids including ethanol, butane, propane, hexane, petroleum ether, methyl tertbutyl ether, diethyl ether, carbon dioxide (CO 2 ), and olive oil (Dussy et al. 2005 ; Lehmann and Brenneisen 1992 ; Romano and Hazekamp 2013 ; Rovetto and Aieta 2017 ). Gaseous solvents such as butane and propane can also be used for extraction purposes (Raber et al. 2015 ). Gas solvent extractions start in the gas phase at room temperature and are either cooled or pressurized into a liquid state as they run through the sample material (Rovetto and Aieta 2017 ). The extracted sample is collected, and the solvent is evaporated (Chan et al. 2017 ). The process of pressurizing these flammable and potentially explosive gases poses safety hazards (Jensen et al. 2015 ). In addition, the gases used in cannabis extractions are often industrial grade and contain impurities that end up in the cannabis extracts. Moreover, the solvents themselves may become a residue in the final extract (Raber et al. 2015 ).

The differing solubilities of individual cannabinoids and other phytochemicals are thought to be an important factor that needs to be considered when selecting a solvent. The stickiness and viscosity of cannabis oil result in binding to solvents; therefore, it is important to consider the toxicity, affinity, and temperature profile of the solvents being used (Fathordoobady et al. 2019 ). The efficiency of conventional methods of extraction is presented to be heavily dependent on the solvent of choice. Solubility, molecular affinity, mass transfer, co-solvent, toxicity, and environmental safety are major factors that should also be considered during the solvent selection process (Azmir et al. 2013 ). Commonly used solvents to extract cannabis can be divided into three groups, low molecular mass organic solvents, vegetable fats (oils), and supercritical fluids, notably supercritical carbon dioxide (Reichardt and Welton 2011 ).

Low molecular mass organic solvents

Low molecular mass organic solvents are hydrocarbon-based with limited polarity due to the presence of oxygen. Halogen substituted hydrocarbons are also included in this group.

These solvents are known for their ability to dissolve generally nonpolar compounds, following the chemistry adage: like dissolves like. Inspection of cannabinoids in Table 2 shows that they are dominated by carbon and hydrogen, making them generally nonpolar. However, the presence of alcohol and acid groups requires some polarity in extraction solvents and solvent mixtures.

Table 2 shows some of the properties of the most popular organic solvents in cannabis extraction. Notably absent from this popular group are dichloromethane and chloroform, both halogenated hydrocarbons are commonly used in analytical fat/oil extraction from plant and animal tissue. These solvents are observed to have low boiling points and high volatility, indicating their ability to be easily separated from the extract at low temperatures after the extraction process (Reichardt and Welton 2011 ).

To illustrate how different solvents can affect the yield of compounds from the source material, consider the example of phenolic extraction from grape pomace and elderberry. Phenols are nominally water soluble. The solvent combinations ethanol–water and acetone–water mixtures had a higher yield than ethyl acetate-water mixture (Vatai et al. 2009 ). In another example, isopropanol-hexane, chloroform–methanol, and hexane were used as solvents for crude fat extraction from insect, egg yolk, and krill powders in one-step organic solvent extraction. The highest fat yield was achieved with a chloroform–methanol mixture (Rose 2019 ). Thus, with a mixture of cannabinoids, terpenes, chlorophyll, carotenoids, and other fat-soluble classes in cannabis flowers, different extraction efficiencies can be confidently predicted. If seeds have matured, the fats (triacylglycerols) that comprise the energy stored in seeds will also be extractable to some extent.

Namdar et al. ( 2018 ) reported that for cannabis plant extraction, the ratio and the nature of the solvents can determine the evaporation time after extraction, which should be minimized. A mixture of polar and non-polar solvents achieved the highest yield for all the compounds in the cannabis plant (Namdar et al. 2018 ).

Vegetable fats (oils)

Vegetable oils are routinely extracted from seeds or fruits such as rapeseed, sunflower, or olive, and even brans, making them an inexpensive option. These oils are considered lipophilic due to their nonpolar characteristic, which enables selective dissolving properties. Approximately, 95 to 98% of vegetable oils consist of triglycerols whose composition is dominated by six fatty acids (Yara-Varón et al. 2017 ). Figure  2 shows the major fatty acids in different vegetable oils (Yara-Varón et al. 2017 ). Each of these has a degree of emulsifying capacity that may play a role in cannabinoid extraction. Interestingly, apart from olive oil, some specialized oils, nearly all commercial oils, are refined to eliminate the minor components. Whether this could affect cannabinoid extraction is unknown.

Vegetable oils composition by fatty acid profile, inspired by Yara-Varón et al. ( 2017 )

Olive oil is a well-known solvent in the cannabis extraction field. It is also one of the least refined oils with characteristically high oleic acid content. Terpenes can be preserved during extraction with olive oil due to their low volatile nature. Romano and Hazekamp ( 2013 ) used two different protocols with olive oil for cannabis extraction. In the first experiment, 5 g cannabis with 20 ml olive oil and 50 ml water were mixed and heated up to 60 min. In the second experiment, 10 g cannabis with 100 ml olive oil were mixed and heated for up to 120 min. The extract concentration to the solvent ratio for the first and second protocols was 5 g/20 ml and 10 g/100 ml, respectively. The high yield of terpenes obtained from using olive oil as a solvent is thought to be due to its efficient capabilities in solubilizing and limiting loss of product by protecting the compounds from evaporation (Romano and Hazekamp 2013 ).

Supercritical carbon dioxide (CO 2 )

In common with other solvents, CO 2 —which is nominally a polar gas—enters a so-called supercritical state at a defined temperature and pressure. In a supercritical state, distinct liquid and gas phases do not exist. In the case of CO 2 , the critical temperature is 31.06 °C, the critical pressure is 73.83 bar, and the critical density is 0.460 g/cm 3 (Raventós et al. 2002 ). Supercritical CO 2 behaves like a non-polar solvent, capable of extracting a broad range of non-polar solutes, cannabinoids included. In comparison, strongly polar water becomes supercritical and useful as a non-polar solvent but at a much higher temperature and pressure, 647 K and 22.1 MPa (Fig.  3 ). Therefore, CO 2 is the solvent of choice due to low critical temperature and pressure. It is also non-flammable, non-toxic, inert, renewable, easy to remove, abundant, and relatively low-cost. As an example, consider supercritical extraction of linalyl acetate from lavender oil compared with its extraction by conventional steam distillation (Reverchon et al. 1995 ). The yields for supercritical extraction were 34.7% compared with 12.1% for the conventional steam distillation. The reason proposed was that the higher temperature of steam distillation caused the undesirable hydrolysis of the linalyl acetate to linalool and acetic acid.

CO 2 pressure–temperature phase diagram, the critical temperature is 304.13 K or 31.0 °C or 87.8°F, and the critical pressure is 7.3773 MPa or 72.8 atm or 1070 psi or 73.8 bar. (Adopted from Wikimedia commons URL: https://upload.wikimedia.org/wikipedia/commons/1/13/Carbon_dioxide_pressure-temperature_phase_diagram.svg )

Thus, the low base temperature of supercritical CO 2 is probably an intrinsic advantage (Reverchon et al. 1995 ).

Conventional methods of extraction

Soxhlet extraction.

Soxhlet extraction was first proposed by Franz Ritter Von Soxhlet, a German chemist, as a method of extraction of, primarily, lipids. However, over the years, this procedure has become widely employed for various extraction purposes, commonly used for the separation of bioactive compounds from plant matter. Soxhlet is also extensively used as a model for the comparison and development of alternative methods of separation (Azmir et al. 2013 ). The process begins by placing a small amount of the dried sample in a thimble that is then transferred to a distillation flask containing a particular solvent. When the overflow level is reached by the solution, a siphon is used to aspirate the solute and unload it into the distillation flask with the extracted analyte carried along into the bulk liquid. This procedure is repeated several times until total extraction is complete (Luque de Castro and Garcı́a-Ayuso 1998 ). For cannabis extractions using the Soxhlet apparatus, Lewis-Bakker et al. ( 2019 ) compared different types of organic solvents for the procedure and found ethanol had exhibited the highest yields of cannabinoids (Lewis-Bakker et al. 2019 ). As commonly witnessed by other conventional processes, the long-running time and the large amount of solvent required are limitations that not only increase the cost of operation but also cause environmental complications (Luque de Castro and Garcı́a-Ayuso 1998 ). These drawbacks were demonstrated by a study conducted by Wianowska et al. ( 2015 ) that compared the extraction profiles of THCA and THC using the Soxhlet extraction procedure. It was clear that the long-lasting high temperature accentuated the degradation pathway from THCA to THC and finally to CBN, resulting in high levels of THC and CBN (Wianowska et al. 2015 ).

The simplicity in methodology alongside the ease of system optimization can result in high sample throughput and yield. The minimal requirement for a trained personal for process operation is also considered advantageous when compared to recently developed methods of extraction. Soxhlet methods can be manual or automatic, and the latter is less hazardous and allows multiple treatments to be examined simultaneously to optimize solvent composition, solvent to plant ratio, and extraction time (Luque de Castro and Garcı́a-Ayuso 1998 ).

Dynamic maceration (DM)

Dynamic maceration is a conventional solid-lipid extraction procedure that is based on soaking a sample in organic solvents (solvent varies depending on the polarity of the target compound) for a specific time at a specific temperature and followed by agitation (Fathordoobady et al. 2019 ). This process of separation is inexpensive and a popular method used to obtain essential oils and bioactive compounds (Azmir et al. 2013 ). Recently, the use of vegetable oils (e.g., olive oil) as maceration extraction solvents was found to be more useful for extracting higher amounts of terpenes than alcoholic solvents, notably when using extended heating time. However, vegetable oils are not volatile and are difficult to remove from extracted isolates (Romano and Hazekamp 2013 ). Alternatively, ethanol is suggested as a preferred solvent for cannabinoid extraction. A study conducted by Fathordoobady et al. ( 2019 ) demonstrated that there was no significant difference between other organic solvents (n-hexane, acetone, methanol) and ethanol when used for neutral cannabinoid recovery. However, when the recovery of acidic cannabinoids was tested, ethanol had the highest yield. The use of ethanol for maceration extraction of cannabinoids was found to produce the highest yield when used twice compared to other methods of extractions, for instance, ultrasonic-assisted extraction (UAE) or supercritical fluid extraction (SFE) (Fathordoobady et al. 2019 ).

Romano and Hazekamp ( 2013 ) compared five different solvents (naphtha, petroleum ether, ethanol, olive oil + water, and olive oil) using DM (Table 3 ). Except for naphtha, other extracts contained a small amount of THC and THCA around 5–10%. Naphtha was an exception which had 33% THC plus THCA. With ethanol as solvent, unwanted chlorophyll was extracted along with the cannabinoids. The unwanted chlorophyll not only added an unpleasant flavor and a green tinge to the end product, but it also demonstrated accounts of interference with gas chromatography–mass spectrometry analysis, hence removal is considered necessary (Ciolino et al. 2018 ). To eliminate unwanted chlorophyll, the ethanol extract can be treated with activated charcoal. However, the use of activated charcoal can result in the reduction of cannabinoid content by approximately 50%. Consequently, although yields are high with ethanol, the removal of unwanted chlorophyll with charcoal comes at the expense of cannabinoid loss. In respect of toxicity, Romano and Hazekamp ( 2013 ) found significant amounts of petroleum hydrocarbon residues in the extracts obtained with naphtha and petroleum ether, indicating that special attention must be paid to ensure safe residual concentrations (Romano and Hazekamp 2013 ).

In the same study, when compared to other solvents, the olive oil extract was shown to contain the largest number of terpenes, making it a superior crude extract. Olive oil is a cost-effective nonflammable solvent that is considered nontoxic when applied topically or consumed orally, and not through the lungs. As an added benefit, Citti et al. ( 2016 ) recognized that olive oil-based cannabis extracts maintained their cannabinoid concentration longer than ethanol-based extracts. A disadvantage associated with olive oil extracts, however, is that extracts cannot be concentrated by evaporation. This means that larger volumes of olive oil extracts need to be consumed to have the same therapeutic effects as other extracts (Romano and Hazekamp 2013 ). In another study by Hazekamp et al. ( 2009 ), hexane—the usual form of petroleum ether—was used as a solvent for the maceration method in fiber and drug varieties of cannabis. The yields of cannabinoids were discovered to be 3% and 17%, respectively. For this study, hexane was particularly used as it does not extract chlorophyll and is easily evaporated after extraction (Hazekamp et al. 2009 ).

Methods to extract chlorophyll from plants generally required acetone as the preferred solvent; however, as acetone is considered carcinogenic, it is not recommended to be used in cannabinoid extraction. Namdar et al. ( 2018 ) extracted cannabinoids with ethanol (partly polar) and hexane (non-polar), and their mixture. The highest yield was achieved with the mixture, but for cannabinoids, the polar solvent was best (Namdar et al. 2018 ). Likewise, Brighenti et al. ( 2017 ) concluded that dynamic maceration with ethanol for 45 min at ambient temperature was the best way of extracting non-psychoactive cannabinoids especially the acidic forms compared to more elaborate methods like ultrasonic-assisted extraction (UAE) (Brighenti et al. 2017 ).

Alternative methods of extraction

Ultrasonic-assisted extraction (uae).

Ultrasound technology is widely adopted in the food and chemical industry for its ability to significantly influence the rate of various processes (Chemat et al. 2008 ). The main feature that sets ultrasonic-assisted extraction (UAE) apart from other processes is the use of sound waves, commonly with frequencies between 20 to 100 kHz. This enables the penetration of solvents into a sample matrix to extract the compounds of interest. This is done during the process of cavitation. Cavitation is described as the formation, expansion, and collapse of bubbles within the solution that allows for intense mass transfer and accelerated solvent access into cell material (Azmir et al. 2013 ). The effective mixing ability of the UAE can be explained by the faster energy transfer, micro-mixing, and reduced extraction temperature (Otles 2016 ). Factors such as moisture content of a sample, particle size, milling degree, solvent, temperature, pressure, and time of sonication must be considered and manipulated to achieve efficient extractions (Azmir et al. 2013 ). A study that employed the ultrasonication method to leach and hydrolyze phenolic compounds presented evidence of low analyte decomposition during the extraction procedure when compared to other methods such as subcritical water, and microwave-assisted and solid–liquid extractions. After assessing the degradation of phenolic compounds, the decrease in decomposition was found to be due to the low energy type produced by the sonication mechanism and the short duration time. However, this was only evident when the exposure time to ultrasound was less than 10 min (Herrera et al. 2005 ).

De Vita et al. ( 2018 ) compared different methods for the extraction of commercially available hemp and medicinal cannabis to evaluate the changes in cannabinoid composition. The experimentation demonstrated the optimal conditions for the highest yield of cannabinoids using ultrasonication to be 50 min at 60 °C with ethanol as a solvent. Despite the optimal conditions, the total amounts of THC and CBD extracted were slightly lower when compared to the controls, which were obtained under reflux at 90 °C for 50 min in ethanol. Although low yield was obtained, the ultrasonication procedure had provided extracts using lower temperatures in an environmentally friendly, safe, and energy-efficient way. This study also found that ethanol extract yield was 3 to 4 times higher than olive oil extract (De Vita et al. 2020 ). To further explore the concept of solvent influence in UAE, Lewis-Bakker et al. ( 2019 ) conducted an extraction procedure with the following parameters: UAE in 80 W of ultrasonic bath power, 63 W of heating power, at 40 kHz for 5 min. A mix of ethanol, hexane, and isopropanol: hexanes (1:1) were used as solvents. The results showed that the yield for ethanol and hexane was almost the same, and isopropanol: hexanes achieved the highest yield of the extract. However, an HPLC analysis showed a reverse relationship between the extract yield and cannabinoids: the isopropanol: hexanes product had the lowest cannabinoid content, due to coextracted non-cannabinoid content. The authors also indicated that the acidic forms of cannabinoids (four shown in Fig.  2 ) were almost intact with UAE extraction compared to other methods (Lewis-Bakker et al. 2019 ). To optimize the extraction of target cannabis compounds, it is suggested to use UAE as a conditioning step for conventional extraction methods. For example, it was found that using UAE before a Soxhlet extraction improved the crude lipid yield by more than 24% without affecting the quality of extract (Fathordoobady et al. 2019 ).

Microwave-assisted extraction (MAE)

In 1980, the increasing demand for environmentally friendly and sustainable industrial processes had provoked the development of the Microwave-assisted extraction procedure (Otles 2016 ). The electromagnetic energy provided in the form of microwaves, with frequencies between 300 MHz and 300 GHz, is used to produce rapid heating following ionic conduction and dipole rotation (Azmir et al. 2013 ). This procedure directly exposes each molecule to a microwave field which is converted to kinetic energy that can break cell walls and release their contents into a liquid phase. The enhanced performance of this green extraction process can be attributed to improved solubility, efficient mass transfer, and increased surface equilibrium. These factors result in a system that uses less energy with fast processes requiring less solvent consumption but also producing a final product with high purity (Fig.  4 ) (Ani et al. 2012 ). De Vita et al. ( 2018 ) used MAE to explore time, temperature, ramping time, and solvent as variables. The study demonstrated that the extraction yield of CBD increased with increasing temperature and duration by at least 4 times when compared to the reference sample, which was prepared by ethanol reflux at 90 °C for 50 min. It was also noted that olive oil had superior properties when compared to ethanol during an MAE (De Vita et al. 2020 ).

MAE process where the flask is housed in the microwave oven (Krishnan and Rajan 2017 ). Placing the flask containing the sample in the microwave, attached to a condenser outside of microwave to capture the solution of interest compounds after distillation

Neutral phytocannabinoids have been established as important for their medicinal properties; therefore, using extraction procedures to obtain these compounds is considered essential. Methods used for the extraction of neutral cannabinoids can be explored by investigating their decarboxylation efficiencies of phytocannabinoid acids. For example, Lewis-Bakker et al. ( 2019 ) had studied the processes of different isolation methods and found MAE to be superior in terms of yielding high neutral cannabinoids. The study had found high temperature (> 130 °C) led to decarboxylation of more than 99% of acidic cannabinoids during MAE. To further promote the decarboxylation of acidic phytocannabinoids, MAE was used for 10 min at 150 °C with extracts from prior Soxhlet, UAE, and SFE extractions. However, only the isolates from the Soxhlet method had completely decarboxylated. Although prolonging the duration time to 30 min in MAE, extracts yielded 0.6% CBN. As CBN is produced from the oxidation changes of THC, this can be due to a radical-mediated or oxidation during MAE (Lewis-Bakker et al. 2019 ).

Pressurized liquid extraction (PLE)

Pressurized liquid extraction (PLE), also known as accelerated solvent extraction (ASE) (Duarte et al. 2014 ), is documented to be a highly efficient and rapid method of compound extraction. In this approach, high pressures facilitate the extraction while the high temperatures promote solubility and mass transfer to increase analyte solubility, as well as reduce solvent viscosity and surface tension (Azmir et al. 2013 ). Accordingly, altering temperature and pressure enables influence over the solubility of the compound of interest (Wianowska et al. 2015 ). This procedure also does not require a filtration step as the insoluble matrix components are contained inside the extraction cell. This feature allows for the process automation for continuous operation (Fathordoobady et al. 2019 ). Figure  5 visualizes the PLE process.

PLE process using organic solvent as extracting solvent coupled with supercritical antisolvent (SAS) precipitation process (1) heat exchanger for cooling, (2) pump, (3) heat exchanger for heating, (4) extractor, (5) T-mixer, (6) precipitation vessels, and (7) filter (Santos and Meireles 2015 )

When comparing PLE to conventional methods such as Soxhlet, features such as shorter duration, reduced solvent consumption, and decreased sample handling are observed (Rodrigues et al. 2016). To demonstrate this, Wianowska et al. ( 2015 ) compared the amount of THCA, THC, and CBN obtained from a Soxhlet and PLE process with two types of extractants, methanol, and n-hexane. Employing methanol as an extractant, the first set of results had indicated, even in high temperatures, the concentration of THC was lower than THCA using the PLE method. The Soxhlet process had contrasting results as the concentration of THC was much higher than THCA. The data obtained illustrates the influence of parameters such as time and pressure have on the end product. The high pressure applied enables the use of temperatures above the boiling point of the extractant. This increases the penetration ability of the selected solvent into the plant matrix in a short time. The high temperature used in PLE does not avoid the transformation of THCA and THC to CBN; however, the degree at which this occurs is found to be much lower than that demonstrated by the Soxhlet extraction (Wianowska et al. 2015 ).

For the extraction of cannabis constituents, Fathordoobady ( 2019 ) demonstrated that by using methanol and acetone/methanol (50:50) as solvents with PLE parameters of 1250 bar at 60 °C temperature, 17 various compounds, and three cannabinoids (Δ9-THC and its metabolites 11-nor-9-carboxy-THC and 11-hydroxy-THC) were identified from the cannabis plant (Fathordoobady et al. 2019 ).

Supercritical fluid extraction

Green approaches, such as supercritical fluid extraction (SFE), are used to displace conventional methods of pressing and organic solvent extractions. These procedures decrease environmental impacts and reduce toxic residue on products by using supercritical fluids (Aladić et al. 2015 ). The process behind SFE can be condensed into two steps: (1) the plant material of interest is solubilized in a supercritical solvent of choice, commonly CO + , to extract the desired compound. (2) Those compounds are then recovered from the solvent to produce the end product. The use of supercritical fluids is advantageous as at room temperature they are in a gaseous, allowing for recovery of extract via simple evaporation (Santos and Meireles 2015 ). The differing solubilities of different solvents allow for selective extraction, as small variations to pressure and/or temperature can allow for selectivity (Perrotin-Brunel 2011 ). The employment of low temperatures is also considered advantageous as it results in low energy consumption as well as allowing for the preservation of thermosensitive compounds, such as cannabinoids (Aladić et al. 2015 ).

Under conditions except for supercritical, CO 2 behaves as a polar compound. In instances where supercritical CO 2 is not sufficiently polar to act as a solvent, polarity modifiers, such as alcohols, water, and acids, can be used as co-solvents (Rovetto and Aieta 2017 ). However, CBD and THC are soluble in supercritical CO 2 because they are dominantly nonpolar, making this the solvent of an appropriate choice (Grijó et al. 2018 ). Rovetto and Aieta ( 2017 ) evaluated the effect of pressure and the use of ethanol as a co-solvent on cannabinoid extraction. Extractions were run at 17, 24, and 34 MPa pressure. The yields increased almost linearly to 34 MPa, 0.185 g/g of cannabis at this pressure, compared with yield from a traditional ethanol extraction of 0.132 g/g. Increased pressure can increase the solvation power but decreases the selectivity of the extraction, so a higher pressure may not be the ideal condition. Ethanol was indicated to be useful as a co-solvent: When added in pulses, it can increase the rate of supercritical CO 2 extraction of cannabinoids (Rovetto and Aieta 2017 ). Omar et al. ( 2013 ) also demonstrated that using a co-solvent can increase the yield (Omar et al. 2013 ). The optimum yield of these cannabinoids was achieved by using ethanol as co-solvent at 55 °C and 34 MPa (Fathordoobady et al. 2019 ). However, when comparing SFE with other methods of extraction, Brighenti et al. ( 2017 ) revealed that the lowest amount of CBDA, CBD, and CBG was obtained (Brighenti et al. 2017 ). Figure  6 visualizes the supercritical fluid extraction process.

Diagram of a supercritical fluid extraction (Adopted from Wikiwand.com URL: https://www.wikiwand.com/en/Supercritical_fluid_extraction# )

Hydrodynamic cannabis extraction

Hydrodynamic cannabis extraction is a recent development within the cannabis industry that can be used to produce full-spectrum cannabis extracts with high bioavailability. There have been accounts of companies, such as IASO (Incline Village, Nevada), claiming to have developed a unique extraction system that produces products with high yield and increased potency. This alternative method involves freezing fresh plant material and converting it into a nanoemulsion in water by ultrasonication. Hydrodynamic force is then used to break the cell wall and release its contents. This is followed by liquid–liquid extraction using solvents, centrifugal separation, and finally low-temperature drying. The initial step of freezing the plant matter helps preserve the volatile compounds as well as acidic cannabinoids during the following steps. Hydrodynamic extraction is claimed to exceed conventional methods mainly due to the lack of high temperatures, short contact distillation, and low organic solvent consumption (admin, n.d.). Ishida and Chapman ( 2012 ) used this technique to extract carotenoids from tomatoes and found that the extractable lycopene, other carotenoids, and accessibility of carotenoids significantly improved (Ishida and Chapman 2012 ). However, to this date, there has been no scientific publication that explores this method of extraction. Therefore, to fully understand the efficacy of this method, more research is required.

Traditionally, the dried cannabis flower was the product of choice; however, as the industry expands, the demand for various products with distinct properties also increases. Therefore, multiple factors should be considered when selecting a drying technique or an extraction method to produce a specific product. Among different drying methods for post-harvest processing, freeze-drying is considered more appropriate when compared to other methods; however, there is currently a lack of academic research and evidence to support this. Hang-drying as a traditional technique is still the most convenient way to reduce the prevalence of mold and bacteria during storage before extraction. Solventless extraction and hydrodynamic extraction are of interest due to their high yield, easy, and fast process but lack the scientific publication to promote their employment for large-scale production. According to cannabinoids’ lipophilic or hydrophobic properties, slightly polar solvents are recommended for extraction. Although for terpenes with more than 15 carbons, non-polar solvents are suggested. Soxhlet and dynamic maceration are being used as traditional methods which are time- and solvent-consuming but accurate enough to be compared with modern techniques. Among modern methods, SFE, MAE, and UAE are well recognized as feasible and convenient techniques.

In this narrative review paper, the advantages and disadvantages of various drying and extraction methods have been discussed. The best methods for industries based on the final products have been reviewed and suggested. Some gaps are found in this review paper including the lack of information and knowledge about using freeze dryer for drying plant material after harvest, hydrodynamic extraction method, and a developed green extraction technique in the cannabis research area as well as cannabis industry which needs more investigations in the future studies.

Availability of data and materials

Data sharing is not applicable to this article as no datasets were generated or analyzed during the current study.

Abbreviations

(-)-Trans-Δ 9 -tetrahydrocannabinol

(-)-Trans-Δ 9 -tetrahydrocannabinolic acid A

(-)-Trans-Δ 8 -tetrahydrocannabinol

Cannabidiol

Cannabidiolic acid

Cannabigerol

Cannabigerolic acid

Cannabichromene

Cannabichromenic acid

Endocannabinoid system

Ultrasound-assisted extraction

Microwave-assisted extraction

Dynamic maceration

High-performance liquid chromatography

Pressurized liquid extraction

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Lazarjani, M.P., Young, O., Kebede, L. et al. Processing and extraction methods of medicinal cannabis: a narrative review. J Cannabis Res 3 , 32 (2021). https://doi.org/10.1186/s42238-021-00087-9

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Cannabis (Marijuana) Research Report Is marijuana safe and effective as medicine?

The potential medicinal properties of marijuana and its components have been the subject of research and heated debate for decades. THC itself has proven medical benefits in particular formulations. The U.S. Food and Drug Administration (FDA) has approved THC-based medications, dronabinol (Marinol ® ) and nabilone (Cesamet ® ), prescribed in pill form for the treatment of nausea in patients undergoing cancer chemotherapy and to stimulate appetite in patients with wasting syndrome due to AIDS.

In addition, several other marijuana-based medications have been approved or are undergoing clinical trials. Nabiximols (Sativex ® ), a mouth spray that is currently available in the United Kingdom, Canada, and several European countries for treating the spasticity and neuropathic pain that may accompany multiple sclerosis, combines THC with another chemical found in marijuana called cannabidiol (CBD).

The FDA also approved a CBD-based liquid medication called Epidiolex ®  for the treatment of two forms of severe childhood epilepsy, Dravet syndrome and Lennox-Gastaut syndrome. It’s being delivered to patients in a reliable dosage form and through a reproducible route of delivery to ensure that patients derive the anticipated benefits. CBD does not have the rewarding properties of THC.

Researchers generally consider medications like these, which use purified chemicals derived from or based on those in the marijuana plant, to be more promising therapeutically than use of the whole marijuana plant or its crude extracts. Development of drugs from botanicals such as the marijuana plant poses numerous challenges. Botanicals may contain hundreds of unknown, active chemicals, and it can be difficult to develop a product with accurate and consistent doses of these chemicals. Use of marijuana as medicine also poses other problems such as the adverse health effects of smoking and THC-induced cognitive impairment. Nevertheless, a growing number of states have legalized dispensing of marijuana or its extracts to people with a range of medical conditions.

An additional concern with "medical marijuana" is that little is known about the long-term impact of its use by people with health- and/or age-related vulnerabilities—such as older adults or people with cancer, AIDS, cardiovascular disease, multiple sclerosis, or other neurodegenerative diseases. Further research will be needed to determine whether people whose health has been compromised by disease or its treatment (e.g., chemotherapy) are at greater risk for adverse health outcomes from marijuana use.

Medical Marijuana Laws and Prescription Opioid Use Outcomes

A 2019 analysis, also funded by NIDA, re-examined this relationship using data through 2017. Similar to the findings reported previously, this research team found that opioid overdose mortality rates between 1999-2010 in states allowing medical marijuana use were 21% lower than expected. When the analysis was extended through 2017, however, they found that the trend reversed, such that states with medical cannabis laws experienced an overdose death rate 22.7% higher than expected. 79 The investigators uncovered no evidence that either broader cannabis laws (those allowing recreational use) or more restrictive laws (those only permitting the use of marijuana with low tetrahydrocannabinol concentrations) were associated with changes in opioid overdose mortality rates.

These data, therefore, do not support the interpretation that access to cannabis reduces opioid overdose. Indeed, the authors note that neither study provides evidence of a causal relationship between marijuana access and opioid overdose deaths. Rather, they suggest that the associations are likely due to factors the researchers did not measure, and they caution against drawing conclusions on an individual level from ecological (population-level) data. Research is still needed on the potential medical benefits of cannabis or cannabinoids.

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Cannabis Facts and Stats

At a glance.

A variety of information sources are available to monitor the prevalence and trends of cannabis use in the United States. The resources below cover cannabis-related issues, including data around use, emergency department visits, substance use and misuse, policy measures, and other related tools.

• Cannabis is the most commonly used federally illegal drug in the United States; 52.5 million people, or about 19% of Americans, used it at least once in 2021. 1
• Recent research estimated that approximately 3 in 10 people who use cannabis have cannabis use disorder. 2
• The risk of developing cannabis use disorder is even greater for people who begin to use it before age 18. 3
• Cannabis use directly affects the parts of the brain responsible for memory, learning, attention, decision-making, coordination, emotion, and reaction time. 4 5
• Infants, children, and teens (who still have developing brains) are especially susceptible to the adverse effects of cannabis. 4 5
• Long-term or frequent cannabis use has been linked to increased risk of psychosis or schizophrenia in some users. 6
• Using cannabis during pregnancy may increase the person's risk for pregnancy complications. Pregnant and breastfeeding persons should avoid cannabis. 7

National Surveys That Collect Information About Cannabis Use

Cdc sponsored surveys.

Behavioral Risk Factor Surveillance System (BRFSS)

World's largest, continuously conducted telephone survey that tracks health behaviors, chronic diseases, and preventive health practices among noninstitutionalized adults in the United States.

Youth Risk Behavior Surveillance System (YRBSS)

Monitors six categories of priority health risk behaviors, including cannabis use, among high school youth at national, state, and local levels.

Pregnancy Risk Assessment Monitoring System (PRAMS)

Collects state-specific, population-based data on cannabis use before, during, and shortly after pregnancy.

National Health and Nutrition Examination Survey (NHANES)

Assesses the health and nutritional status of adults and children, aged 12 years and older, in the United States. The survey is unique in that it combines interviews and physical examinations. Voluntary drug use questions ask lifetime cannabis use, age of first use, age when starting to use cannabis regularly, amount used, frequency of use, and time since last use. These data are available from 2005-2007 survey period onward.

Other National Surveys

National Survey on Drug Use and Health (NSDUH)

Ongoing and long-term system, sponsored by the Substance Abuse and Mental Health Services Administration (SAMHSA) NSDUH is the primary source of information on the prevalence, patterns, and consequences of alcohol, tobacco, and illegal drug use and abuse in the general U.S. civilian noninstitutionalized population, ages 12 and older.

Monitoring the Future Survey

Ongoing and long-term system, sponsored by the National Institute on Drug Abuse (NIDA) that collects data on the behaviors, attitudes, and values regarding substance use of American teens, college students, and adults. Each year a total of approximately 50,000 students in 8th, 10th, and 12th grades are surveyed about substance use, including cannabis, and a subset are sent follow-up questionnaires through age 45 years.

National Drug Early Warning System (NDEWS)

NDEWS monitors drug use trends in 12 sentinel communities across the United States. Sentinel Site profiles describing drug abuse trends and emerging issues are available on NDEWS website.

National Programs That Collect Information About Cannabis Policies

Alcohol Policy Information System (APIS)

A policy monitoring system sponsored by the National Institute on Alcohol Abuse and Alcoholism (NIAA) that provides detailed information on a wide variety of alcohol-related policies in the United States at both state and federal levels. The system was expanded in 2016 to include policies related to legalizing the cultivation, sale, or use of cannabis for prohibitions and restrictions on such practices.

State Cannabis Policy Enactment Database

A policy monitoring system sponsored by the National Conference of State Legislatures that provides up-to-date information on cannabis legislation that has been enacted in the 50 states, District of Columbia, and its territories. The database is sortable by state, topic, keyword, and primary sponsor.

• Substance Abuse and Mental Health Services Administration. Key substance use and mental health indicators in the United States: Results from the 2021 National Survey on Drug Use and Health (HHS Publication No. PEP22-07-01-005, NSDUH Series H-57). Center for Behavioral Health Statistics and Quality, Substance Abuse and Mental Health Services Administration. 2022. https://www.samhsa.gov/data/report/2021-nsduh-annual-national-report . Accessed on February 9, 2024.
• Hasin DS, Saha TD, Kerridge BT, et al. Prevalence of marijuana use disorders in the United States between 2001-2002 and 2012-2013. JAMA Psychiatry. 2015 Dec;72(12):1235-1242. doi: 10.1001/jamapsychiatry.2015.1858.
• Winters KC, Lee C-YS. Likelihood of developing an alcohol and cannabis use disorder during youth: Association with recent use and age. Drug Alcohol Depend. 2008;92(1-3):239-247. doi: 10.1016/j.drugalcdep.2007.08.005.
• National Academies of Sciences, Engineering, and Medicine. The health effects of cannabis and cannabinoids: the current state of evidence and recommendations for research. Washington, DC: The National Academies Press; 2017. https://nap.nationalacademies.org/catalog/24625/the-health-effects-of-cannabis-and-cannabinoids-the-current-state. Accessed February 8, 2024.
• Giedd JN. The teen brain: Insights from neuroimaging. J Adolesc Health. 2008;42(4):335–343. doi: 10.1016/j.jadohealth.2008.01.007.
• Volkow ND, Swanson JM, Evins AE, et al. Effects of cannabis use on human behavior, including cognition, motivation, and psychosis: A review. JAMA Psychiatry. 2016 Mar;73(3):292-297. doi: 10.1001/jamapsychiatry.2015.3278.
• Ryan SA, Ammerman SD, O’Connor ME, et al. Marijuana use during pregnancy and breastfeeding: Implications for neonatal and childhood outcomes. Pediatrics. 2018;142(3):e20181889. doi: 10.1542/peds.2018-1889.

Cannabis and Public Health

Cannabis—which can also be called marijuana —is the most commonly used federally illegal drug in the United States.

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Real World Evidence in Medical Cannabis Research

Rishi banerjee.

1 Department of Surgery and Cancer, Imperial College London, London, UK

Simon Erridge

2 Sapphire Medical Clinics, UK Medical Cannabis Registry, London, UK

Oliver Salazar

Nagina mangal, daniel couch.

3 The Centre for Medicinal Cannabis, 18 Hanway Street, London, W1T 1UF UK

Barbara Pacchetti

4 Curaleaf International, London, UK

Mikael Hans Sodergren

5 Division of Surgery, Department of Surgery & Cancer, Imperial College London, St Mary’s Hospital, Academic Surgical Unit, 10th Floor QEQM, South Wharf Road, London, W2 1NY UK

Associated Data

Not Applicable.

Whilst access to cannabis-based medicinal products (CBMPs) has increased globally subject to relaxation of scheduling laws globally, one of the main barriers to appropriate patient access remains a paucity of high-quality evidence surrounding their clinical effects.

Whilst randomised controlled trials (RCTs) remain the gold-standard for clinical evaluation, there are notable barriers to their implementation. Development of CBMPs requires novel approaches of evidence collection to address these challenges. Real world evidence (RWE) presents a solution to not only both provide immediate impact on clinical care, but also inform well-conducted RCTs. RWE is defined as evidence derived from health data sourced from non-interventional studies, registries, electronic health records and insurance data. Currently it is used mostly to monitor post-approval safety requirements allowing for long-term pharmacovigilance. However, RWE has the potential to be used in conjunction or as an extension to RCTs to both broaden and streamline the process of evidence generation.

Novel approaches of data collection and analysis will be integral to improving clinical evidence on CBMPs. RWE can be used in conjunction or as an extension to RCTs to increase the speed of evidence generation, as well as reduce costs. Currently, there is an abundance of potential data however, whilst a number of platforms now exist to capture real world data it is important the right tools and analysis are utilised to unlock potential insights from these.

Cannabis-based medicinal products (CBMPs) are a collective term to describe a preparation or other product that contains cannabis or its derivatives for medicinal use in humans [ 1 ]. There are significant barriers to the integration of CBMPs within treatment pathways including ongoing stigma, cost, education, complex pharmacology and a paucity of evidence to inform international and national guidelines [ 2 , 3 ]. Limited evidence, does, however, support the role of CBMPs in conditions such as chronic pain, neurological disorders, and psychiatric disease [ 4 ]. There is also growing evidence of side effects and how the severity and incidence of side effects may differ between patients [ 4 ]. The quality of evidence, however, is often insufficient in the opinion of insurers, regulators, and guideline bodies [ 5 ].

The National Institute for Health and Care Excellence in the UK has only recommended licensed CBMPs for a limited range of indications [ 6 ]. Changes to scheduling as recommended by the World Health Organisation, and within individual countries, recognises the potential medicinal value of cannabis and removes barriers for clinical and research use [ 1 , 7 ]. However, widespread stigma, complex pharmacology, funding, and challenges in sustaining adequate supply of consistent products continue to act as barriers for clinical research.

Randomised controlled trials (RCTs) are necessary and should continue to be the standard against which medical evidence is upheld. However, they are expensive, time consuming and subject to their own limitations [ 8 ]. Whilst these are awaited, there is a requirement to generate evidence of potential benefits and harms to inform policy and clinical practice.

Barriers to Controlled Clinical Trials for Medical Cannabis

RCTs are not infallible—they are expensive and time consuming. Globally $100 billion USD is spent on biomedical research [ 9 ]. In the UK, the National Institute for Health Research (NIHR) provides £80 million GBP in funding for clinical trials [ 10 ]. Yet, their narrow scope can lack ecological validity to real-world circumstances and therefore lack generalisability in more diverse populations. There are also specific barriers to conducting RCTs using CBMPs.

Complex Pharmacology

In addition to cannabidiol (CBD) and (−)-trans-Δ 9 -tetrahydrocannabinol (THC) there are over 140 cannabinoids, as well as flavonoids, terpenes, and other compounds within the flower of different cannabis plants [ 8 ]. These can each potentially affect the clinical outcomes observed between CBMPs due to their individual and collective effects [ 11 ]. The concentrations of each compound are influenced by the genetics and environment each plant is grown in producing a distinct chemical profile. The result of a clinical trial for one finished pharmaceutical product, therefore, cannot be extrapolated to all CBMPs, due to their heterogeneity. However, current evidence reviews often fail to account for this [ 12 , 13 ].

The route of administration further affects the pharmacokinetics of CBMPs and the associated outcome of any trial. CBMPs can be administered sublingually, trans-dermally, via inhalation, or orally [ 14 ]. This subsequently affects the distribution, biotransformation and elimination of active compounds. Heat exposure and vaporisation of dried flower or extracted oils changes the underlying phytocannabinoid composition compared to the original unprocessed dry flowers, increasing the proportion of decarboxylated cannabinoids [ 15 , 16 ]. Assessment of efficacy using RCTs in isolation will therefore ultimately fail to identify the most appropriate CBMP for each clinical scenario [ 17 ].

Placebo-control

An appropriately blinded assessment against placebo or active therapy is the optimal design for RCTs. It has been difficult to identify a placebo that cannot be distinguished against an active CBMP according to absence of both vasoactive and psychoactive effects, as well as the typical aroma associated with cannabis [ 15 ]. This presents a challenge to adequate blinding.

Production methods and import costs mean that CBMPs are typically expensive, adding further to high research costs [ 18 ]. Research has therefore focused on compounds under patent as opposed to generic CBMPs where research outcomes fail to provide a similar return on investment for licensed producers and pharmaceutical companies. Historically, clinical trials on CBMPs were funded privately, which may be associated with potential reporting biases [ 19 ].

RCTs are possible with CBMPs; however, the above issues present legitimate challenges. In many chronic diseases there is a need for novel therapeutics and CBMPs are therefore being utilised based on best available evidence. Due to the challenges in developing CBMPs through a traditional drug development pipeline, the exploration of its utility should not be limited to traditional methods. It is important that we capture a suite of real-world evidence (RWE) to inform prescribing guidelines, regulations, and clinical trials. By leaning on RWE there is an opportunity to improve the quality and design of RCTs and clinical evidence in general, via a top-down approach [ 20 ].

Real World Evidence

RWE is defined as evidence derived from health data sourced from non-interventional studies, registries, electronic health records and insurance data as opposed to the highly controlled setting of RCTs [ 21 ]. There is an abundance of this unstructured data, however, the necessary frameworks and governance are needed for the application of this data [ 22 ]. It is currently used extensively to monitor post-approval pharmacovigilence [ 23 ]. There is clear evidence of benefit in using population-based data to detect safety events associated with specific medications to implement restrictions to reduce harm [ 21 ].

Consistent use of RWE to aid regulatory decision making is yet to be normalised, but the promise is apparent [ 21 ]. Recently, regulator-supported initiatives have highlighted the desire to incorporate RWE into licensing and guidelines, developing a framework which can incorporate its insights into decisions regarding safety and effectiveness [ 21 , 22 ]. It is important that studies standardise their methodology according to those set out by regulatory authorities to ensure research has the greatest impact [ 21 , 22 ]. Moreover, they should seek to directly address questions set out by governing bodies as areas where there is insufficient research [ 24 ].

Types of Real-World Evidence for Medical Cannabis

NHS England and NHS improvement published a review on the barriers to accessing CBMPs in the UK [ 3 ]. Their recommendations included the need for the collection of structured data, and the development of methods to further support the generation of new evidence, for patients who cannot enrol onto relevant RCTs.

RWE is already being incorporated into the scientific literature on cannabis (Table ​ (Table1). 1 ). Early examples utilised state-level records to examine the effects of cannabis laws on opioid misuse. Subsequently there have been examples of online and self-administered survey tools analysing national outcomes. More recently there has been a focus on collecting evidence from clinical registries and databases with evidence generated from patient-reported outcome measures and long-term pharmacovigilance.

Examples of Real World Evidence Generation for Cannabis-Based Medicinal Products

Comparison of Real-World Evidence and Controlled Clinical Trials

Between these study designs it is important to be aware of potential divergence in reported outcomes. RWE has broader inclusion criteria, accounting for factors like non-standard dosing, and is not limited by scope of disease, thereby improving ecological validity [ 25 ]. However, some studies have concluded there is little difference between results obtained via RCTs and observational studies [ 26 ]. RWE typically has longer patient follow-up and may consequently capture rare but important adverse effects that are not detected within RCTs. Pharmacovigilance is therefore widely accepted as one of the most important roles of RWE.

RWE can bring further clarity on questions that remain unanswered in RCTs. A recent study utilised anonymised surveys of patients with fibromyalgia who consumed cannabis flower [ 27 ]. In addition to reporting positive outcomes on depression and pain the study also reported negative aspects of cannabis consumption, for example driving under the influence (72% of patients) [ 27 ]. These are findings which are unlikely to be reported by patients in controlled clinical trials for fear of repercussions, or strict inclusion criteria. It can also be useful in collecting data in rare conditions whereby recruitment to RCTs can be limited by the need for defined trial sites.

RWE can improve the efficiency of clinical trials by generating hypotheses, refining eligibility criteria, and exploring drug development tools. Registries can be used to form an infrastructure to conduct a clinical trial, lowering costs whilst maintaining high evidence quality [ 28 ]. In supplemented single arm trials the controls are derived from RWE-data sets, providing the opportunity for patient centric study designs. RCTs can also be augmented with real-world data to increase the size of the control group to increase the power of the study. These study designs are particularly useful for rare diseases where participant recruitment is challenging [ 29 ].

Limitations of Real-World Evidence

RWE, however, does have limits to its utility. There is variation in the quality and provenance of the data stored in electronic medical records [ 5 ]. Furthermore, insurance records typically use coding specific for reimbursement purposes and may not provide all clinically relevant information. RWE can require complex statistical expertise to deduce valid conclusions.

Another limitation is the lack of randomisation, controlled variables and internal validity. This can make it more difficult to derive causative mechanisms behind clinical outcomes. However, this is also one of the strengths of these studies, allowing for generalisability to true clinical practice [ 22 ]. Treatment assignment based on the physician as opposed to randomisation, creates selection bias and more specifically stigma biases. RCTs, therefore, are still necessary to establish a strong causal relationship between medication and outcomes [ 30 ].

CBMPs are a complex range of pharmaceuticals which pose challenges to traditional pathways of drug development and translation. Development of CBMPs requires novel approaches of evidence collection to address these challenges. RWE can be used in conjunction or as an extension to RCTs to both broaden and streamline the process of evidence generation. Currently, there is an abundance of potential data, however, it is important the right tools and analysis are utilised to unlock potential insights from these.

Acknowledgements

Abbreviations, author contributions.

RB and SE prepared the manuscript. OS, NM, DC, BP, MS read and approved the final manuscript.

Availability of Data and Materials

Declarations.

SE: Sapphire Medical Clinics. DC: Medical Lead Centre for Medicinal Cannabis. BP: Chief Scientific Officer at Emmac Life Sciences. MHS: Sapphire Medical Clinics Managing Director and Research lead at Emmac Life Sciences.

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