Impact of medical and recreational cannabis laws on inpatient visits for asthma.

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Learn more: PMC Disclaimer | PMC Copyright Notice Health Serv Res . 2024 Dec 30;60(3):e14427. doi: 10.1111/1475-6773.14427 Impact of medical and recreational cannabis laws on inpatient visits for asthma Jayani Jayawardhana 1, ✉ , Jose Fernandez 2 Author information Article notes Copyright and License information 1 Department of Health Management and Policy, College of Public Health, University of Kentucky, Lexington, Kentucky, USA 2 Department of Economics, College of Business, University of Louisville, Louisville, Kentucky, USA * Correspondence , Jayani Jayawardhana, Department of Health Management and Policy, College of Public Health, University of Kentucky, 111 Washington Avenue, Lexington, KY 40536, USA. Email: jayani.jayawardhana@uky.edu ✉ Corresponding author. Issue date 2025 Jun. © 2024 Health Research and Educational Trust. PMC Copyright notice PMCID: PMC12120506  PMID: 39739251 Abstract Objective To examine the impact of medical and recreational cannabis laws on inpatient visits for asthma and by payer‐type. Study Setting and Design Quasi‐experimental difference‐in‐differences regression analysis was conducted while accounting for variations in cannabis laws implementation timing by states. Inpatient visits for asthma in states with a given type of cannabis law were compared with those in states that did not implement the specific law. Four different cannabis laws were examined in the study—initial passage of medical cannabis law, opening of a medical cannabis dispensary, home cultivation of medical cannabis, and recreational cannabis legalization. Data Sources and Analytic Sample State‐level quarterly inpatient visit data for asthma patients were utilized from the Healthcare Cost and Utilization Project Fast Stats database. The primary analysis included inpatient visits for asthma by all payer adult patients aged 19 and above in 38 states from 2005 to 2017, and the secondary analysis included inpatient visits for asthma by payer‐type (i.e., private, Medicare, Medicaid, uninsured). Principal Findings States with medical cannabis dispensaries and legalized recreational cannabis experienced 14.12% (2.14; 95% CI, 0.74–3.53; p < 0.01) and 20.45% (3.08; 95% CI, 1.47–4.69; p < 0.001) increases in inpatient visits for asthma compared with states without these policies, respectively. These increases in inpatient visits for asthma were primarily driven by populations covered by Medicare and private insurance, with Medicare population showing larger effects of both recreational cannabis laws and medical cannabis dispensaries. Conclusions States with medical cannabis dispensaries and legalized recreational cannabis experienced higher rate of inpatient visits for asthma compared with states without these policies. Clinicians and policymakers should consider strategies to curb adverse health outcomes of cannabis, that is likely to result in increased costs of healthcare. Keywords: asthma, inpatient visits, medical cannabis dispensaries, medical cannabis laws, recreational cannabis laws What is known on this topic Cannabis use was a risk factor for bronchial asthma and was associated with increased incidences of asthma among non‐tobacco users, and higher prescription fills for asthma medications. Although many states in the United States have implemented medical and recreational cannabis laws, the impact of these laws on asthma related hospitalizations is unknown. What this study adds States with medical cannabis dispensaries and legalized recreational cannabis experienced significant increases in inpatient visits for asthma compared with states without these policies. The increased asthma inpatient visits primarily came from populations covered by private and Medicare insurance. Practitioners and policymakers should implement strategies to curb adverse health outcomes of cannabis legalizations, that is likely to result in increased costs of healthcare. 1. INTRODUCTION Cannabis use in the United States has rapidly increased due to its legalization. 1 , 2 , 3 Currently, 40 states and the District of Columbia (DC) have passed medical cannabis laws (MCLs). Twenty‐four states and DC have legalized recreational cannabis. While cannabis legalization and cannabis use have been associated with opioid prescriptions, opioid related mortality, and healthcare utilization, its association with respiratory diseases such as asthma is not evident. 4 , 5 , 6 , 7 In the United States, over 25 million people or one in 13 people live with asthma including 21 million adults. 8 Asthma is a chronic lung disease that affects the airways and is not curable but can be managed through continuous medical treatment. 9 Asthma disproportionately affects low‐income individuals, older adults, and minority populations. 9 Asthma accounted for 4.9 million doctor visits, over 169,000 inpatient visits, and 1.5 million emergency department visits in the United States in 2019. 9 About 10 people die from asthma each day in the United States on average 9 and the annual economic cost of asthma is estimated to be more than $81.9 billion including loss of work and school days in addition to medical care costs. 9 Although, some anecdotal evidence suggests that cannabis has been used as a treatment for asthma, it is not evident if cannabis use benefits asthma patients. 10 The U.S. Food and Drug Administration has not approved medical cannabis as a treatment for asthma. 11 The American Lung Association recognizes all types of smoke as risk factors for asthma. 12 Although cigarette and smoking tobacco have been recognized as key risk factors for asthma, cannabis smoke can also be a risk factor. Current cannabis use is a risk factor for bronchial asthma. 13 Current cannabis users were 71% more likely to fill prescriptions for asthma medications than non‐cannabis users, especially when other known risk factors for asthma such as tobacco smoking, self‐reported earlier asthma and allergies, and body mass index were taken into consideration. 13 The prevalence of asthma among youth aged 12–17 was higher in states with recreational cannabis laws (RCLs) compared with states without RCLs. 14 Frequent cannabis use was significantly associated with symptoms of bronchitis 15 and inappropriate use of cannabis was associated with increased incidences of asthma among non‐tobacco users. 16 Some studies show a link between cannabis and other respiratory diseases such as chronic obstructive pulmonary disease (COPD), pneumonia, and cardiovascular outcomes. It is reported that MCLs are associated with increased cardiac death compared with states without MCLs 17 and that the effects of MCLs are stronger in states where there is less restrictions on dispensaries and cardholders. 17 Regular cannabis use regardless of tobacco co‐use was significantly associated with higher risk for asthma, COPD, and pneumonia. 18 Regular cannabis use was significantly associated with higher risk of adverse cardiovascular diagnoses and overall mortality, especially among non‐tobacco users. 19 Although a few studies examine the link between cannabis and asthma, little information exists on the association of cannabis legalization and asthma related health service utilization. Therefore, this study examines the association of cannabis laws and asthma inpatient visits. 2. METHODS 2.1. Data The study utilizes state‐level quarterly inpatient visit data for asthma patients from the Healthcare Cost and Utilization Project (HCUP) Fast Stats database available from the Agency for Healthcare Research and Quality. 20 This database provides state‐level, quarterly inpatient‐stays for asthma by payer drawn from state‐level inpatient visit data from the HCUP State Inpatient Databases (SID). The HCUP‐SID data are limited to patients treated in community non‐rehabilitation hospitals in every state and excludes transfers to other acute care hospitals. Our primary analysis included inpatient visits for asthma by all payer adult patients aged 19 and above in 38 states from 2005 to 2017, and our secondary analysis included inpatient visits for asthma by payer‐type (i.e., private, Medicare, Medicaid, uninsured). The payer‐type is determined by the HCUP database using the expected primary payer such as Medicare, Medicaid, private insurance, or uninsured. The uninsured category includes self‐pay/no charge as well as charity or no expected payment. 21 , 22 We merged quarterly rates of asthma inpatient visits with state‐level socioeconomic and relevant policy variables for the analysis. State‐level annual socioeconomic data on population, percent female, percent Black, percent other race, median household income, and percent uninsured were gathered from the US Census Bureau, and state annual unemployment rates were gathered from the U.S. Bureau of Labor Statistics. 23 , 24 State‐level annual poverty rate and state‐level enrollees by payer‐type were gathered from the Kaiser Family Foundation website. 25 , 26 Private insurance enrollees included both employer‐sponsored and non‐group insured population. 26 State‐level smoking rates were included as a control variable since it is likely to be correlated with asthma inpatient visits. Smoking rates were gathered from the Kaiser Family Foundation website which collects and reports data from the Behavioral Risk Factor Surveillance System ( BRFSS ) of the Centers for Disease Control and Prevention. 27 Following literature, we included state‐level obesity rates and state air quality index (a measure of air pollution) as control variables to account for possible confounding factors. 13 Obesity and poor air quality are risk factors for asthma. 28 , 29 State‐level obesity rate data were gathered from BRFSS, and air quality index (AQI) data were gathered from the U.S. Environmental Protection Agency. AQI is based on five major pollutants that are regulated by the Clean Air Act: ground‐level ozone, particulate matter, carbon monoxide, sulfur dioxide, and nitrogen dioxide. AQI ranges from 0 to 500, where the value of 100 corresponds to the federal standard of ambient air concentration for each of the five pollutants considered. When the level is above 100 individuals with asthma should limit outdoor activities. AQI can increase because of an increase of air emissions or high levels of pollen. We take the median AQI across counties in a given state in a given year and take the average of those median values to calculate the AQI for that state in that year. Thus, by including AQI as a control variable, we hope to account for air quality which may capture other factors such as wildfires, heat indexes, ozone, carbon monoxide, etc. that may affect our outcome variable—hospitalizations for asthma. A drawback of this measure is that the readings are very localized. The monitors are typically found near cities, but away from industrial areas. Since state socioeconomic characteristics, enrollees by payer‐type, smoking rate, obesity rate, and AQI are annual data, we used the linear interpolation command in STATA to estimate quarterly rates of these variables at the state level. We used annual values for the first quarter and estimated values for the remaining three quarters using linear interpolation. Moreover, we included state policy variables that are likely to affect the outcome variable. These include initial legalization of MCLs, RCLs, presence of medical cannabis dispensary in the state (MCD), home cultivation of medical cannabis legalization (HC‐MCL), and Medicaid expansion. The MCL, RCL, and MCD data were gathered from the RAND‐USC Schaeffer Opioid Policy Tools and Information Center (OPTIC). 30 HC‐MCL data were gathered from previous literature and crossed‐checked with multiple websites. 6 Medicaid expansion data were gathered from the Kaiser Family Foundation. 31 The final analysis data sample included 1810 state‐quarter observations from 38 states and the unit of analysis was state‐quarter. 2.2. Measures The primary dependent variable of interest was inpatient visit rate for asthma per 100,000 population per quarter. The secondary dependent variables of interest were inpatient visit rate for asthma by payer‐type per 100,000 enrollees per quarter. We calculated the total inpatient visit rate for asthma by dividing the total number of inpatient visits for asthma for a given state in each quarter by the total population in the state in that quarter and multiplying by 100,000. Inpatient visit rate for asthma by payer‐type was calculated by dividing the number of inpatient visits for asthma by payer‐type for a given state in each quarter by the total number of enrollees in the given payer‐type in that state and quarter and multiplying by 100,000. The key independent variables of interest are RCL, MCL, MCD, and HC‐MCL in each state, which are indicator variables that take the value of one for all quarters in the state after the relevant policy implementation and zero otherwise. Seven states out of the 38 states included in the analysis implemented RCL during the study period. Since not all states that legalize medical cannabis open dispensaries or allow home cultivation of medical cannabis, we included three policy variables (i.e., MCL, MCD, HC‐MCL) to capture the heterogenous effects of these policies on our outcome variables. The other state‐level factors that are likely to affect the outcome variables of interest were included in the analysis as confounding variables. These variables include demographic characteristics: population size (log transformed), percent female population, percent Black population, percent other race population; socioeconomic factors: median household income (in constant 2020 US dollars and log transformed), unemployment rate, and poverty rate; access to healthcare measure: percent uninsured; other risk factors for asthma: smoking rate, obesity rate, and AQI. We use log‐transformed values of median household income and population to account for skewness in these data and for better fit with the linear outcome variables in the study. Additional state policy variable included as a confounding variable in the analysis is an indicator variable for Medicaid expansion which also serves as a measure of access to healthcare in the state. This indicator variable takes a value of one for all quarters in the state after Medicaid expansion and zero otherwise. 2.3. Analysis We utilized a difference‐in‐differences (DID) framework to estimate the effects of cannabis laws on asthma inpatient visit rate. First, we used a heterogeneous DID approach that accounted for the variation in the timing of the cannabis laws implementation by states. 32 , 33 , 34 The DID approach assumes that in the absence of the policy implementation, the states that chose to implement the policy would move the same way (i.e., parallel) as the states that did not implement the policy. 35 Second, we used a two‐way fixed effects (TWFE) DID regression approach for the estimation. 35 , 36 Recent developments in the DID literature suggest that variation in policy implementation timing may result in biased estimates with TWFE regression approach. 32 , 33 , 34 , 36 We utilized Gardner (2021) two‐stage DID approach that accounts for the staggered timing of the cannabis laws implementation by states as our primary specification and the TWFE DID approach as a comparison. 32 In both approaches, we included state fixed effects and year‐quarter fixed effects to account for unobserved state specific factors that are time invariant and unobserved time specific factors that are common to all states, respectively. We included state‐specific socioeconomic and policy variables listed above under “measures” as control variables in the analysis to account for possible confounding factors. We present and discuss results of our primary specification, the Garner methodology since it accounts for variation in policy implementation timing. We carry out an event study analysis to check on the parallel trend assumption for using DID methodology by estimating treatment effects for 15 quarters before and after policy implementation. The coefficient estimates of the policy implementation are presented graphically to assess if parallel trend assumption is violated in the pre‐policy implementation period between states that implemented (i.e., treatment) and not implemented (i.e., control) the policy. To investigate which payer‐type populations are affected by the cannabis laws, we examined the effects of cannabis laws on inpatient visit rate for asthma by payer‐type using a similar DID approach as described above. 2.4. Sensitivity analysis To examine if any one of the states (i.e., an outlier state) might be affecting our primary result disproportionately, we reestimated the primary model excluding one state at a time. Since this study uses publicly available aggregated data, it did not require institutional review board approval. All statistical analyses were conducted in Stata version 17.0 (StataCorp LP, College Station, TX, USA). 3. RESULTS The average asthma inpatient visit rate was higher among the states without RCLs compared with states with RCLs (Table 1 ) during 2005–2017 period. The states without RCLs experienced 15.9 asthma inpatient visits per 100,000 population per quarter on average while the states with RCLs experienced 11.3 asthma inpatient visits per 100,000 population per quarter. TABLE 1. Summary statistics of the study sample by states with and without recreational cannabis laws. Variable RCL = 0 RCL = 1 Obs. Mean SD Min Max Obs. Mean SD Min Max Asthma inpatient visit rate 1479 15.89 7.17 1.59 44.00 331 11.32 5.48 1.22 31.23 MCL effective 1479 0.22 0.41 0.00 1.00 331 0.90 0.30 0.00 1.00 MC—Dispensary open 1479 0.08 0.26 0.00 1.00 331 0.49 0.50 0.00 1.00 MC—Home cultivation 1479 0.14 0.34 0.00 1.00 331 0.90 0.30 0.00 1.00 Medicaid expansion 1479 0.16 0.37 0.00 1.00 331 0.24 0.43 0.00 1.00 Smoking rate 1479 0.22 0.06 0.07 0.45 331 0.20 0.06 0.10 0.39 LN (Population) 1479 15.55 0.78 13.87 17.16 331 15.53 0.93 14.10 17.49 LN (Median income in $2020) 1479 10.98 0.15 10.49 11.38 331 11.10 0.10 10.89 11.29 Unemployment rate 1479 6.26 2.04 2.30 13.70 331 6.88 2.35 2.70 13.50 % Uninsured 1479 12.66 4.46 3.50 26.10 331 12.41 5.18 2.50 23.50 % Obese 1479 0.29 0.03 0.20 0.38 331 0.25 0.03 0.18 0.30 Air Quality Index 1479 38.06 5.24 14.25 51.88 331 35.07 6.77 23.76 50.91 % Female 1479 0.51 0.00 0.50 0.52 331 0.50 0.01 0.49 0.52 Poverty rate 1479 14.65 3.16 8.00 24.50 331 13.23 1.89 10.00 17.10 % Other race population 1479 0.07 0.12 0.01 0.67 331 0.09 0.04 0.02 0.18 % Black population 1479 0.14 0.09 0.02 0.38 331 0.06 0.03 0.01 0.11 Open in a new tab Note : Asthma inpatient visit rate is per 100,000 population per quarter. Abbreviations: MC, medical cannabis; MCL, medical cannabis law; Obs., observations; RCL, recreational cannabis law. Figure 1 and Appendix Table 1 present the results of the DID regression analyses. The results show that RCLs and MCDs are significantly associated with increased inpatient visits for asthma in states with RCLs and MCDs compared with states without RCLs and MCDs, respectively. States with RCLs experience 3.08 additional asthma inpatient visits per 100,000 population per quarter compared with states without RCLs (95% CI, 1.47–4.69; p < 0.001), resulting a 20.45% increase. States with MCDs experience 2.14 additional asthma inpatient visits per 100,000 population per quarter compared with states without MCDs (95% CI, 0.74–3.53; p < 0.01), resulting a 14.12% increase. The results from the TWFE methodology show that RCLs are significantly associated with increased inpatient visits for asthma ( p < 0.001), but no significant association between any of the medical cannabis laws and asthma inpatient visits was observed. The magnitude of the coefficient for RCL from the TWFE regression is consistent with the results from the Gardner approach. FIGURE 1. Open in a new tab The association of cannabis laws with inpatient visit (IP) rate for asthma per 100,000 population per quarter. Results of the difference‐in‐differences regression analysis using both Gardner (2021) methodology accounting for staggered implementation of the policy and the two‐way fixed effects (TWFE) approach. Standard errors are in parentheses. All regressions included state fixed effects, year‐quarter fixed effects, and other control variables (state‐level socioeconomic and concurrent policy variables), included in Table 1 . HC_MC, home cultivation of medical cannabis; MCD, medical cannabis dispensary; MCL, medical cannabis law; RCL, recreational cannabis law. * p ‐value < 0.05, ** p ‐value < 0.01, and *** p ‐value < 0.001. Figure 2 and Appendix Table 2 present the results of the regression analyses by payer‐type. The results show that RCLs are significantly associated with increased inpatient visits for asthma among patients with private and Medicare insurance though no significant association was observed for uninsured and Medicaid‐insured patients. Patients with private insurance living in states with RCLs experience 1.18 additional inpatient visits for asthma per 100,000 enrollees per quarter compared with states without RCLs (95% CI, 0.22–2.12; p < 0.05), resulting in a 15% increase. Patients with Medicare insurance living in states with RCLs experience 13.51 additional inpatient visits for asthma per 100,000 enrollees per quarter compared with states without RCLs (95% CI, 6.54–20.48; p < 0.001), resulting in a 29.1% increase. Additionally, results show that MCDs are significantly associated with increased inpatient visits for asthma among patients with Medicare insurance, while no significant association was observed for other payer‐type populations. Patients with Medicare insurance living in states with MCDs experience 6.93 additional inpatient visits for asthma per 100,000 enrollees per quarter compared with states without MCDs (95% CI, 0.14–13.72; p < 0.05), resulting in a 14.96% increase. FIGURE 2. Open in a new tab The association of cannabis laws with inpatient visit (IP) rate for asthma by payer‐type per 100,000 enrollees per quarter. Results of the difference‐in‐differences regression analysis by payer‐type using Gardner (2021) methodology accounting for staggered adoption of the treatment. HC_MC, home cultivation of medical cannabis; MCD, medical cannabis dispensary; MCL, medical cannabis law; RCL, recreational cannabis law. Figure 3 shows the coefficient estimates for both RCL and MCD policy implementations in the test for parallel trend assumption (i.e., event study). We do not observe significant differences between states that chose to implement RCLs or MCDs and states that did not implement RCLs or MCDs, respectively prior to each of the policy implementations suggesting that parallel trend assumption is not violated. However, we do observe anticipatory effects of RCL implementation starting one quarter before policy implementation. We observe a significant increase in asthma inpatient visit rate starting one quarter ahead of RCL implementation. Though asthma inpatient visit rate tends to drop around quarter 10 after implementation of RCL, it increases backup starting quarter 11. We observe a lagged effect from the implementation of MCDs. We observe a significant increase in asthma inpatient visit rate only after the fourth quarter of the implementation of MCDs. FIGURE 3. Open in a new tab Event study graphs. Treatment effect coefficients are presented for 15 quarters before and after the recreational cannabis laws (RCL) and medical cannabis dispensaries (MCD) became effective including a 95% confidence interval. 3.1. Sensitivity analysis results One may be concerned that our results are primarily driven by outlier states that perhaps have particularly high (or low) levels of asthma. We address this concern by completing a one‐left out analysis. That is, we reestimate our primary specification leaving out one state at a time. If our findings were driven by an outlier state, then when we reestimate the model leaving out that one state, our results should drastically change. The coefficient estimates of the RCLs and MCDs with one state excluded at a time are presented in Appendix Figures 1 and 2 along with the 95% confidence intervals, respectively. The coefficient estimates of the RCLs are not drastically different from each other and are significant and vary between 2.644 and 3.78. The coefficient estimates of the MCDs are significant, consistent, and vary between 1.847 and 2.438. In both cases, the original point estimates were contained within the 95% confidence bounds. As Appendix Figures 1 and 2 show, we do not observe any drastic changes in our results after cycling through each state (leaving out one state at a time) in our sample. Our estimates appear to be robust to these concerns. 4. DISCUSSION This is the first study to investigate the link between cannabis laws and asthma inpatient visits. The findings show that the states with RCLs and MCDs experience increased inpatient visits for asthma compared with states without these laws. States with RCLs experience an increase of 20.45% and states with MCDs experience an increase of 14.12% in inpatient visits for asthma compared with states without RCLs and MCDs, respectively. These effects are likely driven by increased use of cannabis because of increased access to cannabis through RCLs and opening of MCDs in states. The positive association between RCLs and inpatient visits for asthma is consistent with previous findings of higher prevalence of childhood asthma in states with RCLs compared with states without RCLs. 14 The findings of both RCLs and MCDs associated with increased asthma inpatient visits are in line with previous finding of cannabis users filling higher rates of prescriptions for asthma medications compared with non‐cannabis users indicating that increased cannabis use is likely to result in higher healthcare service utilization for asthma. 13 The study findings are consistent with literature that suggests frequent cannabis use is positively associated with asthma related symptoms, which is likely to increase healthcare service utilization for asthma. 15 The findings also show that the effects of RCLs and MCDs on inpatient visits for asthma primarily come from populations covered by Medicare and private insurance, with Medicare population showing larger effects of both RCLs and MCDs. These results indicate that increased access to cannabis through legalization of RCLs and opening of MCDs may increase cannabis use among Medicare population, 3 , 37 which in turn results in adverse health effects related to asthma needing inpatient care. It is important to note that Medicare population is a vulnerable group that is experiencing a higher number of comorbidities compared to younger populations (<65). 38 Medications treating comorbidities in Medicare population can interact with cannabis resulting in adverse health effects, especially if the population is cannabis naïve. Recent studies show that cannabis use among older adults (≥65) are increasing, especially among those with chronic conditions, 3 , 37 cannabis‐related ED visit rate has increased significantly among older adults (aged ≥65), 39 and those with higher number of comorbidities experienced higher rate of ED visits. 39 Cannabis use has also increased among younger populations, 40 who are likely covered by private insurance. Unlike with prescription drugs, there are no dose, quantity, or potency limits for cannabis products in the market. Therefore, if the populations consuming cannabis are unaware of the potency of the products they consume, they may experience higher incidence of adverse health effects. A back‐of‐the‐envelope calculation help frame our findings in a clinical context. For example, in 2017, the US population over age 18 in states that did not adopt RCLs is 183,804,800. 41 Therefore, if these non‐RCL states adopt RCLs, then three additional visits per 100,000 per quarter would result in 5514.14 additional inpatient visits per quarter among adults due to asthma, which would result in 22,056.58 additional visits over the entire year of 2017. Similarly, there were 33,260,800 Medicare enrollees in non‐RCL states in 2017. 26 We calculate that if all these non‐RCL states were to adopt an RCL, there would be an additional 17,974 inpatient visits for asthma among Medicare enrollees in 2017. The cost of an asthma related inpatient visit in 2017 is reported as $17,756. 42 Therefore, these additional inpatient visits due to adoption of RCLs by non‐RCL states is likely to result in $391.6 million in healthcare costs. This is the first study to show that RCLs and MCDs are significantly associated with increased inpatient visits for asthma. Increased asthma inpatient visits may result in higher costs of care for asthma and related comorbidities. These results suggest that the effects of cannabis laws vary by the type of cannabis law, and that states considering implementation of cannabis laws should take these differential adverse health effects of cannabis laws, outside of the opioid epidemic, into consideration when making policy decisions. 4.1. Limitations The study has a few limitations. First, it uses state‐level aggregated asthma inpatient visits and focuses on the 2005–2017 period. If patient level data or data from later years are available, results may vary. Second, it includes data from only 38 states and results may differ if data from all states were available. Third, the AQI data provide localized information. We aggregate these data to the state level, which causes us to lose some of the valuable variation in the data. Fourth, the DID framework assumes that the composition of the treatment and control groups remains stable within the study period. However, this assumption is not likely to hold in the payer‐type analysis for the Medicaid and uninsured populations. The passage of the Affordable Care Act and individual state Medicaid expansions have changed the composition of individuals covered by Medicaid or report to be uninsured. These policy changes are unlikely to affect Medicare recipients or individuals covered by private/employer sponsored plans. We report the results for completeness but warn the reader to be skeptical of Medicaid and uninsured results. Future studies may focus on the role of cannabis on asthma related ED and ambulatory care visits and evaluate the impact by subpopulation categories such as age, sex, and race/ethnicity. 5. CONCLUSIONS Our research shows that states with MCDs and RCLs are experiencing increased inpatient visits for asthma compared with states without MCDs and RCLs, respectively. These increased asthma inpatient visits primarily come from populations covered by private and Medicare insurance and are likely resulting in increased cost of care for asthma. As more US states are considering legalization of cannabis laws, these adverse health effects, especially outside of the opioid epidemic, should be taken into consideration in the policy debate on cannabis legalization. FUNDING INFORMATION No funding to report. CONFLICT OF INTEREST STATEMENT The authors declare no conflicts of interest. Supporting information Appendix Table 1. Association of cannabis laws with inpatient visit (IP) rate for asthma per 100,000 population per quarter. Appendix Table 2 . Association of cannabis laws with inpatient visit (IP) rate for asthma by payer‐type per 100,000 enrollees per quarter. Appendix Figure 1 . Coefficient estimates of RCL when leaving one state out at a time. Appendix Figure 2 . Coefficient estimates of MCD when leaving one state out at a time. HESR-60-0-s001.docx (53.5KB, docx) ACKNOWLEDGMENTS We acknowledge the Agency for Healthcare Research and Quality's Healthcare Cost and Utilization Project (HCUP) and HCUP Data Partners for making the HCUP Fast Stats Data available. We would like to thank Tahiya Anwar and Drew Farr for excellent research assistant work in gathering some of the data for this study. We thank anonymous referees, conference participants at American Society of Health Economists Conference, Association for Public Policy Analysis & Management Conference, Addiction Health Services Research Conference, Southern Economic Association Annual Meeting, and seminar participants at University of Kentucky. Jayawardhana J, Fernandez J. Impact of medical and recreational cannabis laws on inpatient visits for asthma. 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