Analyzing the Impact of Medical Legalization of Marijuana
By: S Arunima
Tags: Marijuana Legalization, Health Outcomes, Econometrics, Stata, Pregnancy

By Aakriti Jain and S Arunima

Ashoka University

1 Introduction

“These last couple of years, the amount of attention that’s been given to medical marijuana has been huge. And when I’ve done focus groups with high school students in states where medical marijuana is legal, they say “Well, if it’s called medicine and it’s given to patients by caregivers, then that’s really the wrong message for us as high school students.”

– R. Gil Kerlikowske, Director of the Office of National Drug Control Policy

In the late 1980s and the early 1990s, smoke-able marijuana was discovered to have a positive effect on patients suffering from nausea, a common symptom of many chronic diseases. Marijuana legalization advocacy groups such as the National Organization for the Reform of Marijuana Laws (NORML) used these evidences to increase their lobbying powers. In response, many states in the United States started implementing a new law regarding medical marijuana legislation. According to this law, patients of certain diseases (recognized under the law) were allowed to use marijuana for treatment purposes.

Medical marijuana legalization in the United States has been a topic for heated debates ever since its inception. The critics argue that such a law sends a wrong message to the masses regarding the social acceptance of marijuana and that any legalization of marijuana will increase marijuana addiction, misuse of related substances, healthcare costs, crime and violence, road accidents, and risky sexual behavior. It has also been a popular belief among public media that medical legalization has increased illegal marijuana use among non-patients. Although these medical marijuana laws do not change the legal status of the non-medical use of marijuana, there is a huge gray area and the legal boundaries are blurred by the loosely worded laws. In particular, potential risks from leaking of medical marijuana from patients and dispensaries for illegal consumption are huge and cannot be ignored.

It has been widely observed that constant subjection to substance abuse makes a person unmindful and reckless. Many times such people adapt to risky sexual behavior and end up having unprotected sex leading to teen pregnancies. The life outcomes of a child so born are a question of concern because most often the parents themselves are too young and immature to shoulder the responsibilities of a child. It has also been found that substance use and unwanted pregnancies, both, place the youth at the risk of negative impact on various academic, socioeconomic, and health outcomes.

In such a scenario, it becomes extremely important to control for these drug-induced pregnancies. Even the U.S. Department of Health and Human Services and Office of Disease Prevention and Health Promotion recognizes the reduction of adolescent substance use and teen pregnancy as leading health indicators. Apart from pregnancy other health outcomes like self-reported health and depression are equally likely to be affected by the medical legalization of marijuana. Hence we also try to draw a correlation between the medical use of marijuana and these other health outcomes.

On the other hand, people who support the medical legalization of marijuana highlight the potential health benefits of medical marijuana, in particular in terms of managing symptom burden. The available clinical studies suggest that medical marijuana is effective in treating symptoms regarding several health conditions. Kramer, J.L. (2015) reviews various studies that check if medical marijuana can be used to treat cancer and finds that a number of symptoms like pain, nausea, and vomiting, loss of appetite, etc. can be treated using marijuana-based drugs. Okafor, Chukwuemeka N., et al(2017) also found the prevalence of use of medical marijuana among HIV patients for similar reasons.

In the light of these very valid pros and cons of legalizing marijuana for medical use, we, in this paper examine the impact of such a law on various health outcomes with main focus on pregnancy using the cross-sectional data (2002–2018) from the National Survey on Drug Use and Health (NSDUH).

2 Contribution to the literature

Due to the looming uncertainty about the impact of medical marijuana legalization and its strategic implications for relevant policies and laws, a growing economic literature explore its effect on a range of outcomes. The major limitation of all such studies is the schedule-I status of marijuana, the strictest regulatory category. Nonetheless, various studies have tried to bring about various insights regarding the impacts and effects of this law.

Using NSDUH, Wen, Hockenberry, and Cummings (2015) show that among adults (21 years and older) medical legalization of marijuana has led to a 14–15% significant increase in marijuana use. Choi (2014), also used the NSDUH data and found a similar relationship between medical marijuana legalization and marijuana use. Additionally, they also establish that this law leads to increase in marijuana-related arrests and also higher substance use disorder admissions. Anderson and Rees (2014) show that the incidence of this law leads to an increased number of marijuana plants eradicated under the Drug Enforcement Agency’s Domestic Cannabis Eradication/Suppression Program. They also found a decline in completed suicides among men aged 20 to 29 and 30 to 39 associated with this law. This finding, however, did not hold for other demographic groups.

Among prominent researches that examine the impact of this law on various health outcomes is Sabia et al. (2017). The study found that medical marijuana use via the passage of increased marijuana use leads to a significant decline in the probability of being obese. Abouk and Adams (2018) show that post medical marijuana legalization, deaths caused by cardiovascular diseases increased significantly among both men and women. These effects were significantly larger among older adults (ageed 65+). Using the Current Population Survey (CPS), Ullman (2017) establish that the legalization of medical marijuana reduces work absenteeism among workers in the age group 15–65.

Among the papers which pay special attention to pregnancy and substance use, Hawkins, Catalano, Arthur, 2002; Resnick et al., 1997 highlight in their paper how excessive drug use leads to risky sexual behavior and the inter-dependence of substance use and teen pregnancies. Houck et al., 2006 also contributed towards the same hypothesis by establishing that substance use increases likelihood of risky sexual behavior by exposing youth to peer groups that endorse lenient sexual norms in the name of trend and fashion. Houck et al., 2006 further establishes that exposure to such peer groups weakens one’s relationship with his/her family, which further pushes the individual deeper into the abyss of drug use. DeLisi Vaughn, 2014; Prado et al., 2008; Shneyderman Schwartz, 2013; Vaughn, DeLisi, Matto, 2013 also found evidence supporting the claim that various biological and eco-development factors influence the likelihood of substance use and pregnancy-related outcomes.

While there have been enough researches that establish possible linkages between the increase in substance abuse due to legalization of medical marijuana, we in our paper, wish to explore the effect of increased marijuana use owing to legalization on various health outcomes. The major outcome variable of interest in our analysis is pregnancy. We wish to test the hypothesis that medical legalization of drugs made access to drugs comparatively easier and has thus contributed to the increase in risky behavior which ultimately leads to an increase in pregnancy. We also perform a cost-benefit analysis to check if the stated benefits from medical marijuana are actually being realized or not. We also analyze the impact of marijuana on the much neglected aspect of overall well-being, that is the mental health.

3 Data

This study uses data from the NSDUH survey, a series of annual nationally representative surveys of the US civilian, noninstitutionalized population aged 12 years or older conducted by the Substance Abuse and Mental Health Services Administration (SAMHSA). For the purpose of the analysis we pool the cross-sectional data from 2002–2018. The data is organized at the individual level. It is one of the best surveys available, that promises confidentiality to the respondents and collects sensitive data about illicit drug use and mental health. It contains information about the use of drugs such as marijuana, cocaine, etc., perceptions of risks, pregnancy, health care access and coverage. Apart from providing sensitive information on illicit drug use, the data also contains information on individual and household characteristics, gender, race, age, educational level, job status, income level, veteran status, household composition, and population density.

The survey uses a state-based design with independent, multistage area probability sampling methods within each state and the District of Columbia to produce national, state, and substate estimates. Since the survey asks sensitive and controversial questions, it makes immense provisions to ensure the confidentiality of the respondents. NSDUH uses an audio computer-assisted self-interviewing (ACASI) administration mode for this purpose. It also restricts identification variables like state in its publicly available datasets for the very same purpose of maintaining respondent confidentiality. The total sample consists of 949,285 observations but for the purpose of analysis done in this paper, we have restricted the sample size to females between the ages of 12 and 49 (n= 433,481).

4 Empirical Strategy

4.1 Measures

The main outcome variable of interest is a dichotomous variable, pregnancy, which records if a particular female was pregnant at a given time period. Other outcome variables used in this study are self-reported health and an index for depression. The main independent variables are marijuana use and legalization. Marijuana use indicates if a person used marijuana in the past year and legalization represents if the respondent belonged to a state where medical marijuana was legalized at the time of the survey.

Out of the sample of 433,481 females aged between 12 and 49, 14,458 females reported as pregnant during the survey and 389,109 females reported that they were not pregnant. Out of the sample used for the study, 77,702 respondents resided in a state where the medical legalization law was passed, and the remaining lived in states where it wasn’t passed. 74,355 reported consuming marijuana while 359,126 said that they don’t consume Marijuana. In our sample, legalization laws came into effect starting in the year 2013 onwards. Hence, we have data for studying the effect of legalization from 2013–2018. Other control variables for age, ethnicity, race, education, income, risky behavior are also used. We used getting arrested as a proxy for the risk attitude of the respondent.

4.2 Methodology

Statistical analysis was conducted in several steps. First, we looked at some descriptive statistics by the status of legalization. Then we ran a set of ordinary least square (OLS) regressions. First, we looked at the effect of legalization of medical marijuana on marijuana use. Then we examined whether marijuana use and pregnancy are correlated. Finally, we looked at whether legalization and marijuana use together effect the pregnancy rates among females aged between 12–49 in the U.S. Our identification strategy relies on the variation in outcomes of respondents residing in states where medical marijuana legalization law is passed.

To see whether legalization of medical marijuana effected marijuana use, we ran the following OLS regression :

where α is the intercept term, β1 captures the marginal effect of the legalization of medical marijuana on marijuana use.

Then we ran the following OLS equation :

where α is the intercept term, β1 captures the marginal effect of marijuana use on pregnancy. Finally, our main equation of interest is given below :

where α is the intercept term, β1 captures the change in pregnancy due to the joint effect of marijuana use and legalization.

Certain controls such as age, marital status, income, education, and risky behavior (past record of being arrested) are added in order to control for any heterogeneity between individuals. County fixed affects are also added to account for the heterogeneity between the counties in which the law was passed. In order to capture any time trends, we ran each of the above equations with a county*year fixed effects as well.

We analyze between individual variations. Due to confidentiality reasons, state level and district level identifying variables were restricted for use. Hence, we are not able to capture within variation among the counties.

Equations (2) and (3) were ran for two other health outcomes: Self health and Depression.

5 Results

5.1 Descriptive Statistics

In our dataset, medical legalization of marijuana has been recorded for the year 2013 and beyond. Figure 1 shows, the proportion of respondents from states which legalized medical marijuana. The steep increase in the graph over time indicates that over time, more and more states may have been implementing this law. In figure 2, we have plotted marijuana use over time. Comparing it with figure 1 for 2013 and beyond we notice that, after an initial dip, marijuana use has been increasing over time. In figure 3, we have plotted marijuana use over for respondents who belong to states where medical marijuana is legalized and respondents who belong to states where medical marijuana is not legalized. We notice that marijuana use among respondents from states where medical marijuana has been implemented has been higher in all years. This might suggest that medical marijuana legalization leads to an increase in overall marijuana use. We have also plotted number of pregnant females in figure 4. We observe that the trend of pregnancy over time is fluctuating, and it is difficult to comment on its relation with marijuana use or legalization based on these graphs alone. This also makes economic sense because it is only after controlling for education, income and demographic characteristics that the prevalence of marijuana might affect pregnancy. Table 1 presents descriptive stats of all major variables used in this analysis.

5.2 Regression Results

To check if the legalization of medical marijuana has had any significant impact on overall marijuana use, we regress marijuana use on legalized variable, results of which are presented in column 1 of Table 2. The results suggest a small, but positive and significant impact of legalization of medical marijuana on overall marijuana use. After accounting for county fixed effects and adding controls (Model 2) such as age, income, education, race, marital status, and arrests in the past year, the coefficient remains positive and significant and rather has increased a bit in magnitude. In column 3, we introduce time fixed effects and time-specific county fixed effects (Model 3) because as noted by Anderson, Hansel and Daniel (2015) county-specific experiences could change over time. The correlation between legalization and marijuana use is still positive and significant. In particular, if the likelihood of legalizing medical marijuana goes up by 1 unit, then, ceteris paribus, on average, the overall marijuana use goes up by 0.0661 units. Hence, we can safely conclude that there exists a positive correlation between medical marijuana legalization and overall marijuana use.

The next set of regression results capture the impact of overall marijuana use on pregnancy. The results are provided in table 3. In model 1, the coefficient of marijuana turns out to be insignificant. After adding the controls and introducing fixed effects in Model 2 and 3, we observe a negative correlation between the two. In particular, from column 3, we can say that if the likelihood of using marijuana goes up by 1 unit, then, ceteris paribus, on average, the likelihood of being pregnant goes down by 0.00625 units. This is in contradiction to our initial hypothesis that increased usage of marijuana induces risky behavior which might lead to increased pregnancies. The results rather suggest that excessive marijuana use may adversely impact the fertility of females. One possible explanation for this could be that women consume less marijuana during their pregnancy.

Further, we check the combined effect of legalization and marijuana use on pregnancy by introducing an interaction term between the two in the regression. We find that the interaction term turns out to be insignificant. Nevertheless, the individual relationship between marijuana use — legalization and marijuana use — pregnancy is significant and it can’t be ruled out that legalization of medical marijuana may have an adverse impact on the fertility rates of a woman.

All the variation in legalization and marijuana use observed till now is the between variation. To check for within variation, in table 5, we regress marijuana use on legalization year wise. We notice that, ceteris paribus, on average, between 2013 and 2014, the likelihood of overall marijuana use declined from 0.0714 points to 0.0566. In 2015 it surged back up to 0.0702 points. 2016 onwards it stayed constant at about 0.06 points. Corresponding to this, we present the year-wise correlation between marijuana use and pregnancy in table 6. A clear opposite trend to that of marijuana use and legalization is evident. As the magnitude of marijuana use decreased between 2013 and 2014, ceteris paribus, on average, the magnitude of decline in pregnancy due to marijuana use, increased from 0.00166 units (which is indistinguishable from 0) to 0.00881 units. As marijuana use surged back up between 2014 and 2015, the magnitude of decline in pregnancy due to marijuana use also returned back to original levels of 0.00107 points. Thereafter, the likelihood of pregnancy due to marijuana use also stayed constant at about 0.0078 points. This hints towards a clear negative correlation between Marijuana use and pregnancy, suggesting that exposure to marijuana might adversely affect the fertility of the females.

We also collected information on which states legalized (Table 9) between this time period so as to attribute the changes in overall marijuana use to these states. We find that Illionis, Maryland, Minnesota and New York legalized medical marijuana between 2013 and 2014, a period of decline in overall marijuana use due to legalization. So, it could be the case that these states didn’t observe much increase in marijuana use owing to legalization. In fact, some of these states may have witnessed a decline in marijuana usage, which might be responsible for pulling down the estimates for the entire country. In 2015, Alaska legalized marijuana for both medical and recreational usage. This may have contributed to the sudden increase in the estimates for overall marijuana use at the country level. Arkansas and Ohio in 2016, and Florida in 2017 passed the medical marijuana law. This is a period of almost constant country-level estimates of overall marijuana use. Hence, it is difficult to comment on the relationship between marijuana use and legalization in these states.

The only argument in favor of medical marijuana legalization is that it has advantages in treating symptoms like pain, nausea, vomiting, etc. So, we check if the stated benefits of medical marijuana are being realized or not. Potential users of medical marijuana could be people who have cancer, HIV/AIDS or suffer from pain. For this part of the analysis, we restrict our sample by including only those people who have cancer, HIV/AIDS or are frequent users of pain relievers and check the impact of marijuana use and legalization on self-reported health and depression, results of which are presented in table 7 and 8 respectively. In both the tables, model I represents regression of outcome variable on marijuana use; model II represents regression of the outcome variable on legalization; and model III includes an interaction term of marijuana use and legalization. In table 7, we find that marijuana, legalization and the interaction of the two, all have an insignificant impact on self reported health. On the other hand, in table 8, we observe that both marijuana use and legalization has a significant and positive impact on depression. Although legalization and the interaction term turns out to be insignificant, it cannot be ignored that marijuana use (which has a positive correlation with legalization) may have a positive impact on depression which is detrimental to overall well-being.

Thus, what we infer from here is that the stated benefits of medical marijuana are not being realized in reality and it is rather leading to a increase in mental illness. Coupled with huge other risks of increased substance abuse, this analysis suggests that, while legalizing medical marijuana may seem harmless on paper, the risks arising from such a policy clearly outweigh it’s benefits and policy makers should reconsider legalization of medical marijuana.

6 Conclusion

The present study provides new perspectives to the long-going debate of whether marijuana should be legalized in the U.S for medical purposes. We find that legalizing marijuana in more and more states in the U.S leads to an increase in marijuana use. However, this increase in the consumption of marijuana is associated with lower pregnancy rates among females aged 12–49 years. The study does not find any significant results for change in pregnancy rates due to the interaction of the legalization and usage of marijuana.

As per Gallup poll in the U.S, 70% of the Americans support legalization of marijuana for medical use. This support was due to the clinical evidence that legalization of marijuana helps to treat patients suffering from pain and nausea. However, we find that there is no impact of the legalization on self-reported health. In fact, legalization has significantly increased depression among the females in our sample. So, clearly marijuana is used for recreational purposes as well and not specifically for medical treatments. These result holds policy relevance, as such laws will cause increased dependence on marijuana and probably other substances as well which might lead to depression. In such a case, the state has to make provisions for treatments for patients having high dependence on these substances.

Our study has certain limitations. Firstly, due to confidentiality and anonymity reasons, the state identifies of all respondents were restricted for public use. So, we couldn’t include state fixed effects. Secondly, using a dichotomous variable hides away possible variation arising from the difference in the policy guidelines which is further dependent on the past experiences of each state. Thirdly, the legalized variable used in the study captures only the legalization laws meant for ”medical” use of marijuana. In some states, marijuana law allowed for recreational use as well. In our study, these states are getting subsumed in the ”not legalized” category. Hence, there is a possibility of estimates being biased either downwards or upwards. Endogeneity may also be a cause of concern. The negative effect of marijuana use on pregnancy could be because pregnant women do not use marijuana resulting in the problem of Freverse causality Lastly, The data we used was a pooled cross-sectional data, hence, we could only comment on variation between individuals. A panel data structure would help capture the within variations among individuals on the impact of legalization on marijuana use and health outcomes by tracking individuals over time.

As the current topic of discussion is relatively new, we are not able to take a definitive stand for the ongoing debate on whether such laws should be adopted. However, we do provide some evidence that such policies may be causing more harm than benefits. Even if states are passing legalization laws, they should ensure it is not available to the younger generation without prescription and is used for medical purposes only.

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