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• 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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BY designed the study, collected the data, conducted the data analysis, drafted and reviewed the manuscript; XGC designed the study and reviewed the manuscript. XFC and HY reviewed the manuscript. All authors read and approved the final version of the manuscript.

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Additional file 1: table s1..

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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Yu, B., Chen, X., Chen, X. et al. 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. BMC Public Health 20 , 156 (2020). https://doi.org/10.1186/s12889-020-8253-4

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New study highlights significant increases in cannabis use in United States

Long-term trends parallel changes in policy over 43 years.

A new study by a researcher at Carnegie Mellon University assessed cannabis use in the United States between 1979 and 2022, finding that a growing share of cannabis consumers report daily or near-daily use and that their numbers now exceed those of daily and near-daily alcohol drinkers. The study concludes that long-term trends in cannabis use parallel corresponding changes in policy over the same period. The study appears in Addiction .

"The data come from survey self-reports, but the enormous changes in rates of self-reported cannabis use, particularly of daily or near-daily use, suggest that changes in actual use have been considerable," says Jonathan P. Caulkins, professor of operations research and public policy at Carnegie Mellon's Heinz College, who conducted the study. "It is striking that high-frequency cannabis use is now more commonly reported than is high-frequency drinking."

Although prior research has compared cannabis-related and alcohol-related outcomes before and after state-level policy changes to changes over the same period in states without policy change, this study examined long-term trends for the United States as a whole. Caulkins looked at days of use, not just prevalence, and drew comparisons with alcohol, but did not attempt to identify causal effects.

The study used data from the U.S. National Survey on Drug Use and Health (and its predecessor, the National Household Survey on Drug Abuse), examining more than 1.6 million respondents across 27 surveys from 1979 to 2022. Caulkins contrasted rates of use in four milestone years that reflected significant policy change points: 1979 (when the first data became available and the relatively liberal policies of the 1970s ended), 1992 (the end of 12 years of conservative Reagan-Bush-era policies), 2008 (the year before the U.S. Department of Justice signaled explicit federal non-interference with state-level legalizations), and 2022 (the year for the most recent data available). Among the study's findings:

• Reported cannabis use declined to a low in 1992, with partial increases through 2008 and substantial growth since then, particularly for measures of more intensive use.
• Between 2008 and 2022, the per capita rate of reporting past-year use increased 120%, and days of use reported per capita increased 218% (in absolute terms, the rise was from 2.3 billion to 8.1 billion days per year).
• From 1992 to 2022, the per capita rate of reporting daily or near-daily use rose 15-fold. While the 1992 survey recorded 10 times as many daily or near-daily alcohol users as cannabis users (8.9 million versus 0.9 million), the 2022 survey, for the first time, recorded more daily and near-daily users of cannabis than of alcohol (17.7 million versus 14.7 million).
• While far more people drink than use cannabis, high-frequency drinking is less common. In 2022, the median drinker reported drinking on 4-5 days in the previous month versus using cannabis on 15-16 days in the previous month. In 2022, prior-month cannabis consumers were almost four times as likely to report daily or near-daily use (42% versus 11%) and 7.4 times more likely to report daily use (28% versus 3.8%).

"These trends mirror changes in policy, with declines during periods of greater restriction and growth during periods of policy liberalization," explains Caulkins. He notes that this does not mean that policy drove changes in use; both could have been manifestations of changes in underlying culture and attitudes. "But whichever way causal arrows point, cannabis use now appears to be on a fundamentally different scale than it was before legalization."

Among the study's limitations, Caulkins says that because the study relied on general population surveys, the data are self-reported, lack validation from biological samples, and exclude certain subpopulations that may use at different rates than the rest of the population.

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Science Friday

Federal law makes weed research complicated. can a van help.

Scientists want to understand how commercially available cannabis products affect users. They have to get creative to research it legally.

Illustration by Sahra Denner for Science Friday

To understand the effects of cannabis use on exercise, scientists drove stoned people to a tiny gym and watched them sprint.

The experiment was a part of a recent study from the University of Colorado Boulder, which upended expectations that the drug would cause sluggishness and low energy . While cannabis didn’t enhance users’ performance, it did improve their mood during the run, which mimicked the sensation of a “runner’s high.” Getting those precise results took a lot of planning, including outfitting a special van so researchers could shuttle high study volunteers from their homes to the research space. These extra steps (and vehicles) were necessary to make the study legal. Because even though it’s legal to use cannabis in Colorado, there are federal restrictions on researching it—including which cannabis can be studied at all.

Cannabis use in the U.S. has risen dramatically among both young people and older adults as more states have legalized it over the past decade. And researchers across the country want to understand how the products millions of people now have access to can affect our health. “There’s all of these questions that users and patients want to know the answers to that we just don’t have yet,” says Dr. Angela Bryan, a co-author of the exercise study and principal investigator at CU Boulder’s health and risk behavior lab, CUChange .

In order to study the weed that’s legally available at dispensaries, she designs her studies so cannabis never enters her lab.

Driving Around Roadblocks

Cannabis is classified as a Schedule I drug by the Drug Enforcement Administration (DEA), meaning that it’s deemed to have a high potential for abuse, and there is no federally accepted medical use for it—regardless of whether it’s legal to use in a given state. Researchers at universities that receive federal funding can’t give study participants cannabis on campus unless they register with the DEA. And even then, they can only use limited cannabis products provided by a short list of approved growers.

Using A Lab On Wheels To Study Weed From Dispensaries

For scientists who do obtain cannabis through the DEA for on-campus research, lengthy registration and transaction processes along with the limited choice of products can be a substantial challenge. Before 2022, there was only one lab that grew and produced DEA-approved cannabis products, and researchers complained that those were of lower quality and had a much lower THC content than what’s on the legal market. Also, research-grade manufacturers historically haven’t been able to replicate the diversity of commercial products like vapes, high-potency THC concentrate, and edibles that are popular in legal states. To research products that are comparable to what users have access to on the legal market, some scientists have elected to forgo a DEA registration entirely.

Bryan’s research questions were specifically about how commercial cannabis products affect users. So, CUChange worked with the CU Boulder legal team and their human subjects committee to develop the “CannaVan,” also referred to as the mobile research laboratory.

“We landed on the solution of, ‘Well, if we can’t bring the people to the lab, we’ll bring the lab to the people,’” Bryan says. In 2017, CU Boulder’s fleet of CannaVans hit the road , helping researchers study the effects of cannabis on consumers in Boulder.

Conducting research with the mobile lab sometimes involves parking outside a participant’s home, where the person will independently use their product and immediately go out to the van to complete an experimental procedure, like a cognitive test or a blood draw. Other times, the van will simply transport participants from where they use their cannabis to campus, where the researchers can perform tests in a lab. The researchers don’t buy the cannabis themselves, but instruct study participants to purchase the product from a given list of vendors.

Some of the researchers have noticed that study participants share their curiosity about cannabis. Madeline Stanger, a professional research assistant on a project focused on older adults, says that the participants she’s worked with are curious about trying a new treatment option that might improve their quality of life.

“It’s so encouraging when people are like, ‘This is a miracle.’ And then we get people that are like, ‘This isn’t having any effect at all.’ It’s really satisfying when people are benefiting from it, but it’s also good to know what isn’t working,” Stanger says.

So far, CUChange studies have investigated questions about a number of different aspects of cannabis use. Along with the effects of cannabis on physical activity , researchers have learned more about how high-potency THC concentrates affect the body, and how cannabis affects sleep . One of the lab’s studies from 2020 found that smokers who used 70%-90% THC concentrate reported similar levels of intoxication as smokers who took a product at about a quarter the potency. Those results could point to a “tolerance” effect for regular cannabis users, or a saturation point in cannabinoid receptors, but more research is needed.

Even though the team has learned a lot , Bryan acknowledges there are limitations to driving around the DEA. For example, some of their experiments require participants to buy their own cannabis products and document how much they consume. Drug trials where participants don’t know which product they’re consuming are generally considered better at measuring the drug’s isolated effect, because they eliminate the factor of the participant’s awareness. “It’s hard for us to have that experimental control,” Bryan says. “We always have to be cautious when we talk about our findings, understanding that people knew exactly what they were taking.”

Studying Cannabis Nationwide

Bryan and her colleagues’ research goals and generous funding have led them to unique methods, but the laws that make that necessary affect scientists across the US. Teams studying cannabis at different institutions take different approaches based on the questions they want to answer and the resources they have available.

Dr. Carrie Cuttler, an associate professor at Washington State University and the director of its Health and Cognition Lab, has watched research participants use cannabis over Zoom for some of her studies. Her lab has investigated links between cannabis and creativity , as well as the drug’s effects on cognition, mental health, and stress. She developed her research methods with Washington State authorities, and created a procedure where she watches participants use cannabis remotely. “I just observe a legal act,” she says.

Cuttler says the Zoom method lets her avoid illegal entanglement with a Schedule I drug, but a drawback is she’s unable to take the physiological measurements, like blood draws or heart rate, that the mobile laboratory enables. However, because the participant is on camera, Cuttler’s team is able to see one thing the CannaVan team doesn’t: how the user is actually consuming the product. “We time the duration of inhalations. We time the duration of holds. We count puffs,” she says. “We make sure they’re using the product that they were randomly assigned to use.”

Other approaches to researching without a DEA registration include analyzing international cannabis use data from countries like the Netherlands or Canada, and requesting self-reported data from users in the US. However, despite the hurdles, many scientists’ cannabis research interests lead them to opt for DEA registration.

For example, Dr. Ziva Cooper, director of the UCLA Center for Cannabis and Cannabinoids is DEA registered, and for her experiments she can securely store cannabis on campus, check its THC and CBD content, and administer it in an exact quantity.

“Here, it’s like an uber controlled environment,” Cooper says. Her research questions are about the isolated, controlled effect of cannabinoids on the human body, not the effects of typical legal drug use. “Why do I use that [DEA] farm?” she says, “It essentially goes back to, why do I do the type of science I do?”

Will Research Keep Up With Evolving Cannabis Use?

Bryan says scientists trying to understand the health effects of cannabis are barely able to keep up with the booming cannabis market, which is producing easily accessible, chemically diverse products that are more potent than ever . At the same time, cannabis is being used in a medical context in over 35 states.

In 2018 and 2022, respectively, the Farm Bill and Medical Marijuana and Cannabidiol Research Expansion Act  were signed into federal law, expanding access to cannabinoids for researchers. But Bryan says it looks like the sale and use of cannabis in Colorado will continue to evolve faster than the DEA and FDA’s product offerings for researchers. Cannabis’s Schedule I status has made research harder, but Cooper says there are other issues “above and beyond that” that make the work difficult, like producing a research-grade cannabis supply and finding funding to begin with.

Earlier this month, the U.S. Department of Justice proposed that cannabis be rescheduled to Schedule III , the same class as codeine. In a 2023 interview before the reschedule was proposed, Dr. Igor Grant, director of University of California Center for Medicinal Cannabis Research said such a change would make research a lot more practical. For one, the tightest security requirements on storage of the drug would be relaxed, making research less costly, Cooper says. But even if cannabis is reclassified, the impracticalities of research wouldn’t disappear overnight, Grant said. “You’re still dealing with something that’s federally seen as an addictive substance, and regulated.”

One thing that could change is how cannabis products are made. Right now, the FDA does not apply any safety standards to them because the drug is federally illegal. But if it moves to Schedule III, the FDA could publish standards for cannabis products under the Federal Food, Drug, and Cosmetic Act. That could make cannabis products safer, Cooper says, but urgent questions about how legal products affect users continue to surface.

“Until cannabis is taken off the schedule completely (like nicotine or alcohol) we can’t bring legal market products into the lab,” Bryan said in an email. Those who want to research state-legal products will have to continue using workarounds.

“We really want to do work that ultimately improves public health,” Bryan says. “We want to do it in a way that’s rigorous in terms of the science, but has direct application to improving people’s lives.”

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• v.73(4); 2014 Apr

Therapeutic Benefits of Cannabis: A Patient Survey

Clinical research regarding the therapeutic benefits of cannabis (“marijuana”) has been almost non-existent in the United States since cannabis was given Schedule I status in the Controlled Substances Act of 1970. In order to discover the benefits and adverse effects perceived by medical cannabis patients, especially with regards to chronic pain, we hand-delivered surveys to one hundred consecutive patients who were returning for yearly re-certification for medical cannabis use in Hawai‘i.

The response rate was 94%. Mean and median ages were 49.3 and 51 years respectively. Ninety-seven per cent of respondents used cannabis primarily for chronic pain. Average pain improvement on a 0–10 pain scale was 5.0 (from 7.8 to 2.8), which translates to a 64% relative decrease in average pain. Half of all respondents also noted relief from stress/anxiety, and nearly half (45%) reported relief from insomnia. Most patients (71%) reported no adverse effects, while 6% reported a cough or throat irritation and 5% feared arrest even though medical cannabis is legal in Hawai‘i. No serious adverse effects were reported.

These results suggest that Cannabis is an extremely safe and effective medication for many chronic pain patients. Cannabis appears to alleviate pain, insomnia, and may be helpful in relieving anxiety. Cannabis has shown extreme promise in the treatment of numerous medical problems and deserves to be released from the current Schedule I federal prohibition against research and prescription.

Introduction

Research into the therapeutic benefits of cannabis has been severely limited by the federal Schedule I classification, which essentially prohibits any ability to acquire or to provide cannabis for studies investigating possible therapeutic effects. Limited studies have been done in Canada and in Europe, as well as several in California.

Hawai‘i is one of twenty states (plus the District of Columbia) which allow certifications for use of medical cannabis. The authors have been certifying patients for use of medical cannabis in Hawai‘i for more than four years. In an attempt to discover the perceived benefits and adverse effects of medical cannabis, we conducted a survey of medical cannabis patients.

Sample Selection

Between July of 2010 and February of 2011, we hand-delivered questionnaires to one hundred consecutive patients who had been certified for the medical use of cannabis for a minimum of one year and were currently re-applying for certification.

Survey Design and Administration

The subjects were verbally instructed to complete the questionnaire in the office at the time of re-certification or were provided a stamped and addressed envelope so they could complete the questionnaire at home. All patients were instructed to remain anonymous and to answer the questions as honestly as possible.

A universal pain scale was used to assess pain before and after treatment (0 = no pain, 10 = worst pain ever). Open-ended questions were asked to ascertain the following:

• “Any adverse effects you have had from using medical cannabis?”
• “Does medical cannabis help you with any other problems? If so, what?”

The purpose of the last question was to explore benefits outside the parameters of the state of Hawai‘i's medical cannabis qualifying conditions.

The overall response rate was 94%. The mean age was 49.3 years and the median age was 51. No data was collected on sex or race/ethnicity. Almost all respondents (97%) used medical cannabis primarily for relief of chronic pain.

Average reported pain relief from medical cannabis was substantial. Average pre-treatment pain on a zero to ten scale was 7.8, whereas average post-treatment pain was 2.8, giving a reported average improvement of 5 points. This translates to a 64% average relative decrease in pain.

Other reported therapeutic benefits included relief from stress/anxiety (50% of respondents), relief of insomnia (45%), improved appetite (12%), decreased nausea (10%), increased focus/concentration (9%), and relief from depression (7%). Several patients wrote notes (see below) relating that cannabis helped them to decrease or discontinue medications for pain, anxiety, and insomnia. Other reported benefits did not extend to 5% or more of respondents.

Six patients (6%) wrote brief notes relating how cannabis helped them to decrease or to discontinue other medications. Comments included the following: “Medical cannabis replaced my need for oxycodone. Now I don't need them at all.” “I do not need Xanax anymore.” “In the last two years I have been able to drop meds for anxiety, sleep, and depression.” “I've cut back 18 pills on my morphine dosage.”

A majority (71%) reported no adverse effects, while 6% reported a cough and/or throat irritation and 5% reported a fear of arrest. All other adverse effects were less than 5%. No serious adverse effects were reported.

According to the Institute of Medicine, chronic pain afflicts 116 million Americans and costs the nation over $600 billion every year in medical treatment and lost productivity. 1 Chronic pain is a devastating disease that frequently leads to major depression and even suicide. 2 Unfortunately, the therapeutic options for chronic pain are limited and extremely risky.

Spurred by efforts to encourage physicians to become more pro-active in treating chronic pain, US prescription opioids (synthetic derivatives of opium) have increased ten-fold since 1990. 3 By 2009 prescription opioids were responsible for almost half a million emergency department visits per year. 4 In 2010 prescription opioid overdoses were responsible for well over 16,000 deaths. 5 A 2010 article in the New England Journal of Medicine addressing this problem is aptly titled “A Flood of Opioids, a Rising Tide of Deaths.” 3 Drugs such as OxyContin R are so dangerous that the manufacturer's boxed warning states that “respiratory depression, including fatal cases, may occur with use of OxyContin, even when the drug has been used as recommended and not misused or abused.” 6 Clearly safer analgesics are needed.

The Hippocratic Oath reminds to “first, do no harm.” It cannot be over-emphasized that there has never been a death from overdose attributed to cannabis. 7 In fact, no deaths whatsoever have been attributed to the direct effects of cannabis. 7 Cannabis has a safety record that is vastly superior to all other pain medications.

Many physicians worry that cannabis smoke might be as dangerous as cigarette smoke; however, epidemiologic studies have found no increase in oropharyngeal or pulmonary malignancies attributable to marijuana. 8 – 10 Still, since smoke is something best avoided, medical cannabis patients are encouraged to use smokeless vaporizers which can be purchased on-line or at local “smoke-shops.” In states that (unlike Hawai‘i) allow cannabis dispensaries, patients can purchase “vapor pens,” analogous to e-cigarettes and fully labeled regarding doses of THC and other relevant cannabinoids.

Tests have proven that smoke-free vaporizers deliver THC as well or even more efficiently than smoking, and that most patients prefer vaporizers over smoking. 11 Like smoking, vaporizers allow patients to slowly titrate their medicine just to effect, analogous to IV patient-controlled analgesia (PCA) that has been so successful in hospital-based pain control. This avoids the unwanted psychoactive side-effects often associated with oral medication such as prescription Marinol R (100% THC in oil) capsules which tend to be slowly and erratically absorbed and are often either ineffectually weak or overpoweringly strong. 12 , 13 Because inhaled cannabis is rapid, reliable, and titratable, most patients strongly prefer inhaled cannabis over Marinol R capsules. 14

While the relative safety of cannabis as medication is easily established, the degree of efficacy is still being established. The reported pain relief by patients in this survey is enormous. One reason for this is that patients were already self-selected for success: they had already tried cannabis and found that it worked for them. For this sample, the benefits of cannabis outweighed any negative effects. The study design may therefore lend itself to over-estimating the benefits and under-estimating the negative side-effects if extrapolated to the general population.

Another reason that the reported pain relief is so significant is that cannabis has been proven effective for many forms of recalcitrant chronic pain. A University of Toronto systematic review of randomized controlled trials (RCT's) examining cannabinoids in the treatment of chronic pain found that fifteen of eighteen trials demonstrated significant analgesic effect of cannabinoids and that there were no serious adverse effects. 15

While opioids are generally considered to have little benefit in chronic neuropathic pain, several RCT's have shown that cannabinoids can relieve general neuropathic pain, 16 as well as neuropathic pain associated with HIV and with multiple sclerosis (MS). 17 , 18 One study found that cannabis had continuing efficacy at the same dose for at least two years. 19

Even low dose inhaled cannabis has been proven to reduce neuropathic pain. In a randomized, double-blind, placebo-controlled crossover trial involving patients with refractory neuropathic pain, Ware, et al, found that therapeutic blood levels of THC (mean 45 ng/ml achieved by a single inhalation three times a day) were much lower than those necessary to produce a cannabis euphoria or “high”(> 100 ng/ml). 19

Cannabis is relatively non-addicting, and patients who stop using it (eg, while traveling) report no withdrawal symptoms. One author (Webb C.) worked for 26 years in a high volume emergency department where he never witnessed a single visit for cannabis withdrawal symptoms, whereas dramatic symptoms from alcohol, benzodiazepine, and/or opioid withdrawal were a daily occurrence.

So why is cannabis still held hostage by the DEA as a Schedule I substance? On June 18, 2010, the Hawai‘i Medical Association passed a resolution stating in part that:

“Whereas, 1) Cannabis has little or no known withdrawal syndrome and is therefore considered to be minimally or non-addicting; and Whereas, 2) Cannabis has many well-known medical benefits (including efficacy for anorexia, nausea, vomiting, pain, muscle spasms, and glaucoma) and is currently recommended by thousands of physicians; and Whereas 3) Cannabis has been used by millions of people for many centuries with no history of recorded fatalities and with no lethal dosage ever discovered; and Whereas, Cannabis therefore fulfills none of the required three criteria (all of which are required) to maintain its current restriction as a Schedule I substance…

The Hawai‘i Medical Association recommends that Medical Cannabis be re-scheduled to a status that is either equal to or less restrictive than the Schedule III status of synthetic THC (Marinol R ), so as to reduce barriers to needed research and to humanely increase availability of cannabinoid medications to patients who may benefit.” 20

Medical cannabis remains controversial mainly because the federal government refuses to recognize cannabis as an accepted medication. To this we would echo the words of Melanie Thernstrom in her excellent book The Pain Chronicles , 2 “How could treating pain be controversial?” one might ask, “ Why wouldn't it be treated? Who are the opponents of relief?”

Conclusions

Cannabis is an extremely safe and effective medication for many patients with chronic pain. In stark contrast to opioids and other available pain medications, cannabis is relatively non-addicting and has the best safety record of any known pain medication (no deaths attributed to overdose or direct effects of medication). Adverse reactions are mild and can be avoided by titration of dosage using smokeless vaporizers.

More research needs to be pursued to discover degrees of efficacy in other areas of promise such as in treating anxiety, depression, bipolar disorder, autism, nausea, vomiting, muscle spasms, seizures, and many neurologic disorders. Patients deserve to have cannabis released from its current federal prohibition so that scientific research can proceed and so that physicians can prescribe cannabis with the same freedom accorded any other safe and effective medications.

Authors' Biography

Dr. Webb graduated from Dartmouth Medical School (BS Medicine) and from UC San Francisco School of Medicine (MD 1974). General Residency US Public Health Hospital (San Francisco) and Highland Hospital (Oakland). Emergency Medicine Physician 1975-2006 (Colorado), Urgent Care Physician 2007-present (Kailua Kona). Sandra Webb RN, since 1979 (emergency and radiology nurse). Dr. Webb and nurse Webb have been certifying patients for medical use of cannabis since 2009.

Conflict of Interest

None of the authors identify a conflict of interest.

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Weed Science Survey Identifies Gap Between Research Priorities and Skillsets

Brian German May 24, 2024 Industry

The Weed Science Society of America (WSSA) conducted a survey among U.S. and Canadian weed science leaders, highlighting the need for expanded technical competencies in weed science. Precision weed management and robotics emerged as crucial areas requiring expertise in artificial intelligence (AI), machine learning, and UAV technologies. However, there’s a notable gap in these skillsets among current leaders.

“That’s especially true with UAV-based herbicide applications, which require specific licenses and training, and data analytics expertise,” Virginia Tech Weed Science Assistant Professor, Vijay Singh, Ph.D. said in a press release . “We do not find many people who possess these attributes. A similar challenge is finding engineering graduates—who have knowledge in areas such as AI and machine learning and are ready to work on interdisciplinary research.”

Survey findings show a shift in research priorities, with herbicides ranking lower than cultural and preventative weed management and precision weed management. Despite advancements like UAV-based herbicide applications showing promise, public funding for weed research has declined, raising concerns about the lack of support for vital areas like integrated weed management. Weed scientists emphasize the necessity for increased public funding to address these challenges and accelerate the development and application of AI and machine learning technologies in weed management.

Listen to the report below.

Brian German Ag News Director / AgNet West

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