ABSTRACT
Objective(s)
With growing cannabis use in the US, it is crucial to understand the impact of recreational use on sinonasal diseases like chronic rhinosinusitis (CRS), allergic rhinitis (AR), and chronic rhinitis (CR).
Methods
This cross‐sectional study leveraged the NIH AllOfUs database to query patient surveys assessing cannabis usage frequency (lifetime never, monthly, weekly, or daily within the past 3 months) and consumption route (smoking or non‐smoking). Cannabis users were matched to never users for demographics, healthcare visit frequency, and insurance. A stringent logistic regression model calculated odds ratios (OR) of developing AR, CRS, or CR after survey completion. Cox regression hazard ratios (HR) compared consumption routes.
Results
Twenty‐five thousand one hundred sixty‐four cannabis users were matched with 113,418 never users. Users demonstrated significantly lower odds of AR, CRS, and CR than never users. For CRS, the ORs compared to never users are as follows: daily users 0.64 (95% CI 0.53–0.78), weekly users 0.61 (95% CI 0.48–0.77), and monthly users 0.80. For AR, the ORs were 0.64 (95% CI 0.58–0.71) for daily users, 0.62 (95% CI 0.54–0.71) for weekly users, and 0.69 (95% CI 0.58–0.80) for monthly users. For CR, the ORs were 0.61 (95% CI 0.47–0.79) for daily users, 0.64 (95% CI 0.47–0.87) for weekly users, and 0.41 (95% CI 0.26–0.65) for monthly users. There was no significant difference between smokers and non‐smokers (HR 0.64, 95% CI 0.27–1.5).
Conclusion
There is an inverse, associative relationship between cannabis use and sinonasal disease. This relationship is insufficiently understood, and there remain significant concerns about the impact of cannabis use, especially smoking, on airway pathologies.
Level of Evidence
4.
Keywords: allergic rhinitis, cannabis, chronic rhinitis, chronic sinusitis, inflammation, marijuana, sinonasal disease
1. Introduction
Sinonasal diseases including allergic rhinitis (AR), chronic rhinitis (CR), and chronic rhinosinusitis (CRS) affect a quarter of the global population and contribute to morbidity, economic burdens, poor quality of life, and psychiatric comorbidities [1, 2, 3, 4, 5, 6]. Although often related diseases with similar symptomatology, each has distinct pathophysiologies. AR is an atopic disease primarily characterized by mast cell inflammatory cascades along with positive IgE antibodies to specific allergens [7, 8, 9, 10]. CR is a broad diagnosis characterizing both allergic and nonallergic rhinitis, including vasomotor disease likely caused by imbalances in nasal parasympathetic and sympathetic nerves [11]. Unlike AR and CR, CRS primarily affects the paranasal sinus mucosa due to overactivity of specific cytokines related to type 1, 2, and/or 3 inflammation and can be visualized through computed tomography (CT) or endoscopic findings [12]. Current treatments include trigger avoidance, medical management, and surgical intervention. However, symptoms persist for many patients despite aggressive treatments, accentuating the need for multimodal management. There is a growing research focus on understanding and altering patients' lifestyles to augment treatment given the significant impact of environmental factors on disease state [13, 14, 15, 16].
Decades of data on tobacco smoking have highlighted the detrimental impact of both active and passive smoking on overall health and within specific pathologies including upper airway diseases [17, 18]. Findings have found that tobacco smoking triggers inflammatory cascades, alters nascent respiratory epithelium, and decreases mucociliary clearance [19, 20]. Although tobacco usage has declined, cannabis usage has increased in recent years, with 45% of Americans reporting cannabis usage at least once in their life [21]. Despite the overlap in route of consumption and certain properties between tobacco and cannabis, these two substances are molecularly distinct and act on differing receptors in the body. Yet, the effects of cannabis on the sinonasal mucosa are neither well documented nor consistent, with limited high‐power data [22, 23, 24, 25, 26]. There is a need to better understand the health impacts of recreational cannabis use, especially with growing usage among Americans. Therefore, the present study aims to investigate the dose effect of recreational cannabis use in patients with diagnosed CRS, AR, or CR by employing the National Institutes of Health (NIH) All of US (AoU) Research Database.
2. Methods
2.1. Data Source
A retrospective analysis was conducted using deidentified, cross‐sectional survey data from participants in the AoU Research Program. AoU integrates electronic health record (EHR) data with research‐specific information such as patient‐reported outcomes, genetic data, and wearable device metrics. Participants provide written informed consent during enrollment and allow deidentified data to be shared with registered researchers for extensive research purposes, contributing to over 215 peer‐reviewed publications with 7600 ongoing projects [27]. AoU uniquely includes patients of marginalized racial, ethnic, and socioeconomic groups who are often underrepresented in research and research databases [28, 29]. This study complies with the Strengthening the Reporting of Observational Studies in Epidemiology (STROBE) reporting guidelines and is exempt from institutional review board reviews. Therefore, local IRB approval did not need to be obtained through the Houston Methodist Research Institute [30, 31].
2.2. Study Population
Adult participants ≥ 18 years old enrolled in the AoU database between May 31, 2017, and July 1, 2024, who completed questionnaires reporting their cannabis usage were included. Participants with incomplete demographic information (age, sex, race, and ethnicity) were excluded. Cannabis use was gauged by utilizing (1) the Lifestyle survey that queries lifetime cannabis use as well as frequency of cannabis use in the past 3 months and (2) the COVID‐19 Participant Experience (COPE) Survey that queries whether smoking was included in participants' recent cannabis use (yes or no). Cohorts were categorized based on their reported frequency of cannabis use: those who have never used cannabis and those who have used cannabis in the past 3 months. These users were divided into usage frequency subgroups of once or twice, monthly, weekly, or daily. The cannabis user cohort was 1:3 propensity score matched (PSM) with a control cohort of lifetime never users for age, sex at birth, race, health insurance, and healthcare visit frequency using the nearest‐neighbor algorithm. Geographic distribution was examined using 3‐digit zip code information. Given there were no significant differences in patient zip codes between never users and cannabis users, zip codes were not included in PSM. For analyzing the route of cannabis consumption, patients were stratified into smoker and non‐smoker cohorts.
2.3. Covariates and Primary Outcomes
Demographic variables including age, sex, race, and ethnicity, as well as healthcare comorbidity diagnoses, were sourced from patient EHR data. Age was stratified by categories of 18–39 years, 40–60, and over 60 years old. Sex at birth was categorized as female, male, and other. Participants self‐reported ethnicity as Hispanic or Latino, not Hispanic or Latino, or other, and race as White, Black or African American, Asian, multi‐racial, or other. Health insurance was included as a binary (yes or no), and those with no information regarding health insurance status were excluded. Healthcare visit frequency accounted for hospital visits, emergency room visits, urgent care, ambulatory visits, and other outpatient healthcare visits. Patients were categorized based on visit frequency per year (0–12, 13–24, and greater than 25). Comorbidities (defined by ICD‐9 and ICD‐10 diagnosis codes in Table S1) included tobacco dependence syndrome, alcohol use disorder, anxiety, depression, asthma, chronic obstructive pulmonary disease (COPD), type 2 diabetes mellitus (T2DM), essential hypertension, dyssomnia, obstructive sleep apnea (OSA), and obesity. In compliance with AoU data use policies, groups with 20 patients or fewer were not reported.
The primary outcome for this study was the prevalence of new onset CRS, AR, and CR to determine the dose‐effect association between sinonasal disorders and cannabis use. Patients diagnosed with any of these sinonasal pathologies before survey completion were excluded from the study. CRS, AR, and CR were identified using ICD‐9 and ICD‐10 codes described in Table S1. To accurately define these sinonasal diseases, participants were only included if they had at least 2 distinct visits for each diagnosis, as has been previously validated for accuracy in CRS diagnosis using datasets that lack objective findings with a sensitivity of 77% and specificity of 79% [32]. The secondary outcome utilized a survival analysis to determine whether there is a difference in the incidence of CRS over a 3‐year period (2021–2024) between cannabis smokers and non‐smokers.
2.4. Statistical Analysis
Participant demographics and comorbidities were analyzed using descriptive statistics and reported as total numbers and percentages. PSM effectiveness and baseline cohort differences in demographics and comorbidities were evaluated using χ 2 analysis. A multivariable logistic regression model was applied to the matched cannabis usage and route of usage cohorts, and risks of CRS, AR, and CR were determined using odds ratios (ORs) and 95% CIs. Demographic information and relevant comorbidities were included in the model to determine the specific, independent impact of each variable on CRS, AR, and CR. To compare dose–response differences in ORs, Wald tests were performed to determine if there were significant differences between logistic regression odds ratios for once‐or‐twice users, monthly users, weekly users, and daily users. Survival analysis of the consumption route was analyzed using Kaplan–Meier curves and Cox proportional Hazard Ratios (HR). All analyses were conducted using the Python programming language on the AoU Researcher Workbench.
3. Results
3.1. Cannabis Frequency
A total of 138,582 participants fit criteria and completed the Lifestyles survey. The majority were female (62%) and white (55%) with a mean age of 57. Twenty‐five thousand one hundred sixty‐four participants had used cannabis in the past 3 months (6523 daily users; 3842 weekly users; 2889 monthly users, and 11,910 once‐or‐twice users) with 113,418 matched control participants. Baseline participant characteristics for each cohort (prior to matching) are displayed in Table 1. Most notably, as cannabis usage frequency increased, participants tended to be younger (40% of daily users versus 18% of never users were between 18 and 39 years), uninsured (11.3% vs. 4.1%), black (51% versus 22%), and tobacco users (12% versus 3.5%). The most common comorbidities among all patients were anxiety, depression, essential hypertension, obesity, allergic rhinitis, and asthma. Cannabis users were more likely to have tobacco dependence syndrome, alcohol use disorder, anxiety, depression, asthma, and COPD.
TABLE 1.
Baseline (before matching) demographic information and co‐morbid diagnoses of patients who completed the lifestyle questions regarding cannabis usage frequency.
| Patient number (%) | ||||||
|---|---|---|---|---|---|---|
| Never (n = 113,418) | Once‐or‐twice (n = 11,910) | Monthly (n = 2889) | Weekly (n = 3842) | Daily (n = 6523) | p | |
| Age, year | ||||||
| 18–39 | 20,911 (18.4) | 4599 (38.7) | 1126 (39.0) | 1406 (36.6) | 2593 (39.8) | < 0.0001 |
| 40–60 | 31,720 (28.0) | 4014 (33.8) | 936 (32.4) | 1279 (33.3) | 2473 (37.9) | < 0.0001 |
| 60+ | 60,787 (53.6) | 3297 (27.6) | 827 (28.6) | 1157 (30.1) | 1457 (22.3) | < 0.0001 |
| Sex at birth | ||||||
| Female | 73,722 (65.0) | 7222 (60.7) | 1603 (55.5) | 2023 (52.7) | 3876 (58.0) | < 0.0001 |
| Male | 39,632 (34.9) | 4666 (39.2) | 1285 (44.5) | 1814 (47.2) | 2732 (41.9) | < 0.0001 |
| Other | 64 (0.1) | 4 (0.0) | 1 (0.0) | 5 (0.1) | 5 (0.1) | 0.508 |
| Race | ||||||
| White | 76,069 (67.1) | 6448 (54.2) | 1278 (44.2) | 1936 (50.4) | 2780 (42.6) | < 0.0001 |
| Asian | 7750 (6.8) | 476 (4.0) | 81 (2.8) | 79 (2.1) | 56 (0.9) | < 0.0001 |
| Black or African American | 24,850 (21.9) | 4326 (36.4) | 1387 (48.0) | 1625 (42.3) | 3298 (50.6) | < 0.0001 |
| Multiracial | 2018 (1.8) | 384 (3.2) | 89 (3.1) | 118 (3.1) | 218 (3.3) | < 0.0001 |
| Other | 2731 (2.4) | 258 (2.2) | 54 (1.9) | 84 (2.2) | 171 (2.6) | 0.275 |
| Ethnicity | ||||||
| Hispanic or Latino | 2684 (2.4) | 476 (4.0) | 92 (3.2) | 118 (3.1) | 288 (4.4) | < 0.0001 |
| Not Hispanic or Latino | 109,397 (96.5) | 11,269 (94.8) | 2770 (95.9) | 3669 (95.5) | 6102 (93.5) | < 0.0001 |
| Other | 1337 (1.2) | 147 (1.2) | 27 (0.9) | 55 (1.4) | 133 (2.0) | < 0.0001 |
| Health insurance | ||||||
| No | 4682 (4.1) | 997 (8.4) | 302 (10.5) | 391 (10.2) | 736 (11.3) | < 0.0001 |
| Yes | 108,736 (95.9) | 10,895 (91.6) | 2587 (89.5) | 3451 (89.8) | 5787 (88.7) | < 0.0001 |
| General visits | ||||||
| 0–12 | 99,996 (88.2) | 10,954 (92.1) | 2686 (93.0) | 3516 (91.5) | 5957 (91.3) | < 0.0001 |
| 12–24 | 8770 (7.7) | 610 (5.1) | 135 (4.7) | 231 (6.0) | 354 (5.4) | < 0.0001 |
| 24+ | 4652 (4.1) | 328 (2.8) | 68 (2.4) | 94 (2.5) | 212 (3.3) | 0.001 |
| Comorbidities | ||||||
| Tobacco dependence syndrome | 3967 (3.5) | 823 (6.9) | 266 (9.2) | 342 (8.9) | 747 (11.5) | < 0.0001 |
| Alcoholism | 2402 (2.1) | 571 (4.8) | 167 (5.8) | 235 (6.1) | 412 (6.3) | < 0.0001 |
| Allergic rhinitis | 15,622 (13.8) | 1197 (10.1) | 242 (8.4) | 342 (8.9) | 610 (9.4) | < 0.0001 |
| Anxiety | 26,559 (23.4) | 3283 (27.6) | 751 (26.0) | 1132 (29.5) | 2043 (31.3) | < 0.0001 |
| Asthma | 13,213 (11.6) | 1346 (11.3) | 307 (10.6) | 482 (12.5) | 898 (13.8) | < 0.0001 |
| Chronic obstructive pulmonary disease | 6099 (5.4) | 5030 (4.2) | 145 (5.0) | 214 (5.6) | 389 (6.0) | 0.042 |
| Chronic rhinitis | 2411 (2.1) | 149 (1.3) | 20 (0.7) | 48 (1.2) | 76 (1.2) | < 0.0001 |
| Chronic rhinosinusitis | 4783 (4.2) | 311 (2.6) | 70 (2.4) | 87 (2.3) | 158 (2.4) | < 0.0001 |
| Depression | 27,092 (23.9) | 3404 (28.6) | 787 (27.2) | 1163 (30.3) | 2094 (32.1) | < 0.0001 |
| Type 2 diabetes mellitus | 16,770 (14.8) | 1163 (9.8) | 252 (8.7) | 343 (8.9) | 680 (10.4) | < 0.0001 |
| Dyssomnia | 13,573 (12.0) | 1182 (9.9) | 261 (9.0) | 441 (11.5) | 664 (10.2) | < 0.0001 |
| Essential hypertension | 36,709 (32.4) | 2564 (21.6) | 608 (21.0) | 903 (23.5) | 1581 (24.2) | < 0.0001 |
| Obstructive sleep apnea | 13,082 (11.5) | 895 (7.5) | 165 (5.7) | 289 (7.5) | 470 (7.2) | < 0.0001 |
| Obesity | 22,875 (20.2) | 1892 (15.9) | 375 (13.0) | 566 (14.7) | 1059 (16.2) | < 0.0001 |
Note: χ 2 test p values were performed between never users and daily users.
Abbreviations: COPD, chronic obstructive pulmonary disease; CR, chronic rhinitis; CRS, chronic rhinosinusitis; HTN, hypertension; OSA, obstructive sleep apnea.
Results from the multivariate regression analysis are displayed in Table 2. Females, white participants, and ages 40 and above were more likely to have CRS, AR, and CR. Participants with asthma, dyssomnia, essential hypertension, anxiety, depression, and/or OSA were also more likely to have CRS, AR, and CR. Accounting for these differences using the regression model, participants who used cannabis daily, weekly, monthly, or once or twice in the past 3 months each demonstrated significantly reduced odds of CRS, AR, and CR compared to never users. For CRS, the ORs when compared to never users are as follows: daily users 0.64 (95% CI 0.53–0.78), weekly users 0.61 (95% CI 0.48–0.77), monthly users 0.80 (95% CI 0.62–1.04), and once or twice users 0.75 (95% CI 0.65–0.87). Similarly, for AR, the ORs compared to never users were 0.64 (95% CI 0.58–0.71) for daily users, 0.62 (95% CI 0.54–0.71) for weekly users, 0.69 (95% CI 0.58–0.80) for monthly users, and 0.78 (95% CI 0.72–0.85) for once or twice users. Lastly, for CR, the ORs were 0.61 (95% CI 0.47–0.79) for daily users, 0.64 (95% CI 0.47–0.87) for weekly users, 0.41 (95% CI 0.26–0.65) for monthly users, and 0.67 (95% CI 0.55–0.82) for once or twice users.
TABLE 2.
Multivariable logistic regression for the odds of developing CRS, AR, and CR for patients who completed the lifestyles questionnaire reporting the frequency of cannabis usage in the past 3 months.
| Variable | CRS | AR | CR | |||
|---|---|---|---|---|---|---|
| Odds ratio | (95% CI) | Odds ratio | (95% CI) | Odds ratio | (95% CI) | |
| Cohort | ||||||
| Control‐ lifetime never | 1.00 | (Reference) | 1.00 | (Reference) | 1.00 | (Reference) |
| Once‐or‐twice | 0.75 | (0.65–0.87) | 0.78 | (0.72–0.85) | 0.67 | (0.55–0.82) |
| Monthly | 0.80 | (0.62–1.04) | 0.69 | (0.59–0.80) | 0.41 | (0.26–0.65) |
| Weekly | 0.61 | (0.48–0.77) | 0.62 | (0.54–0.71) | 0.64 | (0.47–0.87) |
| Daily | 0.64 | (0.53–0.78) | 0.64 | (0.58–0.71) | 0.61 | (0.47–0.79) |
| Sex at birth | ||||||
| Male | 1.00 | (Reference) | 1.00 | (Reference) | 1.00 | (Reference) |
| Female | 1.16 | (1.02–1.31) | 1.22 | (1.13–1.31) | 1.13 | (0.95–1.34) |
| Other | 0.91 | (0.11–7.35) | 0.40 | (0.08–1.89) | 0.00 | (0.00—inf) |
| Race | ||||||
| White | 1.00 | (Reference) | 1.00 | (Reference) | 1.00 | (Reference) |
| Asian | 0.49 | (0.28–0.87) | 0.78 | (0.61–1.00) | 0.78 | (0.40–1.53) |
| Black or African American | 0.48 | (0.42–0.55) | 0.81 | (0.76–0.87) | 0.65 | (0.55–0.78) |
| Multiracial | 0.80 | (0.57–1.12) | 0.91 | (0.76–1.10) | 0.86 | (0.53–1.40) |
| Other | 0.74 | (0.38–1.43) | 0.71 | (0.49–1.05) | 1.11 | (0.51–2.44) |
| Age | ||||||
| 18–40 | 1.00 | (Reference) | 1.00 | (Reference) | 1.00 | (Reference) |
| 40–60 | 1.41 | (1.22–1.71) | 1.06 | (0.98–1.15) | 0.98 | (0.78, 1.22) |
| 60+ | 1.44 | (1.10–2.34) | 1.19 | (1.09–1.31) | 1.88 | (1.49, 2.36) |
| Ethnicity | ||||||
| Not Hispanic or Latino | 1.00 | (Reference) | 1.00 | (Reference) | 1.00 | (Reference) |
| Hispanic or Latino | 0.62 | (0.43–0.91) | 0.91 | (0.76–1.10) | 0.63 | (0.37–1.10) |
| Other | 0.82 | (0.36–1.86) | 1.06 | (0.66–1.71) | 0.86 | (0.33–2.28) |
| Health insurance | ||||||
| No | 1.00 | (Reference) | 1.00 | (Reference) | 1.00 | (Reference) |
| Yes | 0.97 | (0.75–1.26) | 1.64 | (1.41–1.91) | 1.75 | (1.11–2.77) |
| General visits | ||||||
| 0–12 | 1.00 | (Reference) | 1.00 | (Reference) | 1.00 | (Reference) |
| 12–24 | 2.46 | (2.11–2.87) | 2.05 | (1.85–2.27) | 2.33 | (1.89–2.88) |
| 24+ | 2.32 | (1.93–2.79) | 1.81 | (1.58–2.06) | 3.00 | (2.37–3.79) |
| Comorbidities | ||||||
| OSA | 1.04 | (0.89–1.21) | 1.22 | (1.11–1.34) | 1.40 | (1.15–1.72) |
| Dyssomnia | 1.72 | (1.50–1.98) | 2.02 | (1.86–2.20) | 1.93 | (1.60–2.33) |
| Asthma | 2.74 | (2.41–3.12) | 3.33 | (3.09–3.60) | 2.93 | (2.45–3.50) |
| Anxiety | 1.60 | (1.38–1.86) | 1.72 | (1.59–1.87) | 1.25 | (1.02–1.53) |
| Depression | 1.36 | (1.18–1.57) | 1.26 | (1.16–1.37) | 1.19 | (1.97–1.45) |
| Tobacco dependence syndrome | 1.11 | (0.92–1.33) | 1.16 | (1.04–1.30) | 1.08 | (0.84–1.39) |
| Obesity | 1.56 | (1.35–1.79) | 1.75 | (1.62–1.90) | 1.38 | (1.14–1.68) |
| Alcoholism | 1.16 | (0.93–1.45) | 0.90 | (0.78–1.04) | 0.88 | (0.64–1.23) |
| Diabetes | 1.03 | (0.89–1.19) | 0.81 | (0.74–0.89) | 0.98 | (0.81–1.19) |
| Essential hypertension | 1.55 | (1.34–1.80) | 1.89 | (1.74–2.05) | 1.57 | (1.28–1.93) |
| COPD | 0.98 | (0.82–1.17) | 0.84 | (0.75–0.95) | 0.96 | (0.76–1.21) |
Note: Target cohorts (cannabis users stratified based on usage frequency) were 1:3 propensity score matched to the control cohort (lifetime never cannabis users).
Abbreviations: COPD, chronic obstructive pulmonary disease; CRS, chronic rhinosinusitis; OSA, obstructive sleep apnea.
Dose–response differences in ORs for CRS showed a statistically significant difference between once‐or‐twice users and daily users (p value = 0.046), between once‐or‐twice users and weekly users (p value = 0.011), and between monthly users and weekly users (p value = 0.042). Similarly, for AR, there was a significant difference between once‐or‐twice users and daily users (p value < 0.0001) and between once‐or‐twice users and weekly users (p value < 0.0001). For CR, a significant difference was only noted between the ORs for once‐or‐twice users and monthly users (p value = 0.002). The remaining comparisons were not statistically significant (data not shown).
3.2. Cannabis Route
A total of 7006 participants were included from the COPE survey who specified their route of cannabis usage—smoking (4535) and non‐smoking (2471). At baseline, smokers were older, less likely to be white, more likely to have insurance, and more likely to have anxiety, depression, asthma, dyssomnia, and OSA (Table 3). Although the Kaplan–Meier curve displays a greater probability of being CRS free among smoking users, the results of the Cox HR did not show a significant difference between cohorts: HR 0.64 (95% CI 0.27–1.5) (Figure 1).
TABLE 3.
Baseline (before matching) demographic information and co‐morbid diagnoses for patients who completed the COPE survey questions regarding route of cannabis use compared to the never cannabis users from the lifestyles survey.
| Patient number (%) | |||
|---|---|---|---|
| Non‐smokers (n = 2471) | Smokers (n = 4535) | p | |
| Age, year | |||
| 18–39 | 569 (23.0) | 1305 (28.8) | 0.000 |
| 40–60 | 777 (31.4) | 1413 (31.2) | 0.825 |
| 60+ | 1125 (45.5) | 1817 (40.1) | 0.000 |
| Sex at birth | |||
| Female | 1592 (64.4) | 4535 (62.8) | 0.285 |
| Male | 879 (35.6) | 1685 (37.2) | 0.198 |
| Other | 0 (0.0) | 2 (0.0) | NA |
| Race | |||
| White | 2214 (89.6) | 3757 (82.8) | 0.000 |
| Asian | 66 (2.7) | 100 (2.2) | 0.253 |
| Black or African American | 87 (3.5) | 467 (10.3) | 0.000 |
| Multiracial | 75 (3.0) | 138 (3.0) | 1.000 |
| Other | 29 (1.2) | 73 (1.6) | 0.176 |
| Ethnicity | |||
| Hispanic or Latino | 59 (2.4) | 169 (3.7) | 0.003 |
| Not Hispanic or Latino | 2392 (96.8) | 4321 (95.3) | 0.003 |
| Other | 20 (0.8) | 45 (1.0) | 0.527 |
| Health insurance | |||
| No | 36 (1.5) | 161 (3.6) | 0.000 |
| Yes | 2435 (98.5) | 4374 (96.4) | 0.000 |
| General visits | |||
| 0–12 | 2133 (86.3) | 4018 (88.6) | 0.006 |
| 12–24 | 228 (9.2) | 343 (7.6) | 0.017 |
| 24+ | 110 (4.5) | 174 (3.8) | 0.237 |
| Comorbidities | |||
| Tobacco dependence syndrome | 112 (4.3) | 411 (8.7) | 0.000 |
| Alcoholism | 69 (2.7) | 232 (4.9) | 0.000 |
| Allergic rhinitis | 397 (15.4) | 618 (13.2) | 0.009 |
| Anxiety | 1072 (41.6) | 2138 (45.5) | 0.002 |
| Asthma | 340 (13.2) | 543 (11.6) | 0.043 |
| Chronic obstructive pulmonary disease | 109 (4.2) | 237 (5.0) | 0.135 |
| Chronic rhinitis | 73 (2.8) | 99 (2.1) | 0.061 |
| Chronic rhinosinusitis | 115 (4.5) | 174 (3.7) | 0.126 |
| Depression | 1203 (46.7) | 2365 (50.3) | 0.003 |
| Type 2 diabetes mellitus | 212 (8.2) | 410 (8.7) | 0.500 |
| Dyssomnia | 443 (17.2) | 598 (12.7) | 0.000 |
| Essential hypertension | 561 (21.8) | 1040 (22.1) | 0.756 |
| Obstructive sleep apnea | 317 (12.3) | 482 (10.3) | 0.008 |
| Obesity | 402 (15.6) | 748 (15.9) | 0.757 |
Note: χ 2 test p values between non‐smokers and smokers are included.
FIGURE 1.
Kaplan–Meier curve over the 2‐year period after the COPE survey completion for patients who indicated cannabis smoking user status or non‐smoking user with the corresponding Cox regression hazard ratio calculations.
4. Discussion
Due to federal restrictions and FDA guidelines for individual cannabinoids, previous research on the role of cannabis on airway disease is limited, especially at a population level [1, 21]. This study accounted for comorbidities, demographics, and usage frequency to specifically demonstrate lower risks of CRS, AR, and CR when compared to matched controls using a diversely representative national database. Route of consumption did not affect CRS incidence. To our knowledge, this is the first study to demonstrate this finding.
Given the known detrimental impact of tobacco smoking use on sinonasal tissue and inflammation, it was expected that patients who more regularly used cannabis would also be more likely to have sinonasal inflammatory diseases, especially in those who smoked cannabis. However, the present study results do not support this hypothesis. Instead, they are similar to the results from Orozco et al. which was a national population study that demonstrated fewer nasal symptom reports in cannabis users. Limitations of the Orozco et al. study included no information about ICD‐10 diagnosed sinonasal diseases and comorbidities, insurance coverage, geographic distribution, and healthcare visit frequency [22]. However, even with our stringent matching criteria and regression model ensuring independent analysis of cannabis use on sinonasal disease, the present study continues to demonstrate an inverse relationship between cannabis use and sinonasal diseases. This relationship demonstrated that certain user cohorts were almost half as likely to develop CRS, AR, and CR as never users. Furthermore, the ORs for frequent users (daily and weekly) trended towards lower odds of sinonasal disease when compared to infrequent users (once‐or‐twice or monthly). This finding was proven statistically significant for multiple comparisons for each sinonasal condition, which improves outcome validity.
Research in other fields has supported the medicinal use of cannabis for prevention of chemotherapy‐induced nausea, cachexia in malnourished populations, rheumatological disease, and neuropathic pain [33, 34, 35, 36]. However, given known risks of smoking on airway inflammation, cannabis research has conflicting data for this anatomical region, with early data suggesting cannabis inhalation induced bronchodilation in asthmatics and more recent data showing a detrimental impact on pulmonary function [37, 38]. The data on upper airway disease remains even more ambiguous. Cannabis pollination has induced allergic reactions in select patients, but there have not been direct studies on the relationship between cannabis use and AR [39]. Awad et al. demonstrated worsening of CRS symptoms in concomitant tobacco and cannabis users with diagnosed CRS, but sole cannabis use was not evaluated [40]. Therefore, the present study is the largest and most direct analysis, showing an inverse, dose‐dependent associative relationship between cannabis use (regardless of route) and sinonasal disease.
It is important to consider the molecular physiology of cannabinoids in the human body to better understand the potential protective role of cannabis in immune‐mediated sinonasal disease. Prior studies have demonstrated that the active components of cannabis act on cannabinoid receptors (CB1 and CB2). CB1 is primarily found within presynaptic neurons of the CNS, and CB2 is prevalent among immune cells [41, 42]. CB2 receptors play a role in the induction of apoptosis in activated immune cells, downregulation of mast cell activation, and suppression of inflammatory cytokines [43, 44]. These effects have been studied in vitro, and specifically, THC‐induced apoptosis has been demonstrated in macrophages, B cells, T cells, and antigen‐presenting cells (APC) [45, 46, 47, 48]. When examining individual cannabis active components (namely THC, cannabinol, and cannabidiol), studies have shown downregulation in several inflammatory cytokines involved in Th1, Th2, and Th17 immune responses (IFN‐γ, GM‐CSF, TNF‐α, IL‐1β, IL‐4, IL‐5, IL‐6, and IL‐13) in vivo and upregulation of the anti‐inflammatory cytokine, IL‐10 [49, 50, 51, 52, 53]. Although Th2 immunity is often primarily responsible in CRS, AR, and CR, Th1 and Th17 can also play important roles in these sinonasal diseases [54, 55, 56, 57]. Furthermore, several aforementioned cytokines are specific targets for new‐age biologics like dupilumab that targets IL‐4 and IL‐13 and mepolizumab that targets IL‐5 [58, 59]. These biologics are indicated for the treatment of recalcitrant CRSwNP and significantly improve patient symptom burden [60, 61]. Furthermore, cannabinol creates vasodilatory effects opposing mast cell activation and histamine degranulation that occur in sinonasal disease and result in decreased venous drainage and increased mucosal swelling [62, 63, 64, 65, 66]. Keeping in mind the role of these immune and inflammatory processes in CRS, AR, and CR, the results of this study may support the potential anti‐inflammatory role cannabis plays in these sinonasal diseases [67, 68].
Despite the results of this study and similar research pointing to anti‐inflammatory and potentially immune‐modulating effects of cannabinoids, there remain significant concerns for recreational and frequent cannabis use, especially given the paucity of literature understanding this drug. Cannabis smoke and tobacco smoke display overlapping carcinogen and respiratory toxin profiles with similar histopathologic effects on airway mucosa [25]. Furthermore, a recent population study demonstrated an associative relationship between cannabis use and head and neck cancer [26]. Similarly, a scoping review of cannabis‐related otolaryngologic side effects found a relationship between cannabis use and hearing loss [69]. Because many of these studies comment on associative relationships and have limited capabilities in differentiating the type of cannabis usage and frequency, further trials are necessary to examine specific active ingredients within cannabinoids to determine the risks and benefits of using cannabis to manage chronic, inflammatory conditions. Given limitations in sample size and patient reporting smoking versus non‐smoking consumption of cannabis, recommendations should remain the same that inhalation of cannabis smoke can perpetuate airway inflammation. However, the present study and similar studies of cannabinoid receptors may offer important molecular targets for the development of adjunctive treatments for inflammatory sinonasal disease.
This study provides interesting insight into cannabis use and sinonasal disease that adds to the current literature given the strength of a large population database that includes patients underrepresented in research. However, there are several limitations. The cross‐sectional design of this study limits causative conclusions for the relationship between cannabis use and sinonasal disease. Coding errors are an inherent limitation in database studies and may affect diagnostic accuracy. By using a validated coding algorithm, we enhance result validity [32]. Although this method has not been validated for AR and CR, it is reasonable to assume that it could be similarly applicable to these diagnoses. Nonetheless, our study likely overestimated the overall prevalence of these conditions, but prevalence was compared between cohorts drawn from the same database, mitigating the impact of overestimation on study results. Furthermore, adjunctive results of the regression analysis accentuate model validity with age and female sex, and patients with asthma, hypertension, dyssomnia, OSA, obesity, anxiety, and depression being more likely to develop sinonasal disease [70, 71, 72, 73, 74, 75].
Additional limitations include the fact that survey studies are limited to patient reporting rather than objective measures, and survey completion date does not give specific insight into the chronicity or truthfulness of cannabis usage, which limits temporal analysis of the association between cannabis usage/route and sinonasal disease. Given this study analyzed recreational cannabis use that is not legal nationwide, participants may underreport cannabis usage in certain geographic regions, which may confound results. However, upon 3‐digit zip code analysis of survey participants, there were no significant geographic distribution differences between user and non‐user cohorts. Although we included a sub‐analysis of route of consumption, recreational cannabis has variable chemical components depending on strain, route, and concentration that may influence cytokine release, limiting the commentary on these results [53].
5. Conclusion
This is the largest study to specifically comment on the association between cannabis use and three of the most common sinonasal diseases—AR, CRS, and CR. We found lower odds of AR, CRS, and CR in patients who use cannabis compared to those who do not, which is strengthened by the size of our cohorts and by incorporating demographic and comorbidity information in our analysis. Route of consumption did not change CRS incidence. Although the study presents intriguing findings, caution remains warranted due to the well‐documented and significant adverse effects of recreational cannabis use and the caustic nature of inhaling combustion products. The intent of this research is to encourage further investigation into the potential anti‐inflammatory mechanisms involving cannabinoid receptors in sinonasal disease. As cannabis use increases among Americans, robust molecular and translational research will further clarify the risks and possible benefits of cannabinoid use in chronic conditions.
Conflicts of Interest
Omar G. Ahmed MD is a consultant for Aerin Medical and Medtronic. Masayoshi Takashima MD is a consultant for Aerin Medical, LivaNova, and Medtronic ENT. Michael T. Yim MD is a consultant for Aerin Medical and Spirair.
Supporting information
Table S1: All ICD‐9 and ICD‐10 codes used for identifying patient comorbidities.
Acknowledgments
We would like to thank the Keeley and Carl Carter for their private donation to fund research related to chronic sinusitis at Houston Methodist Hospital.
Mehdi Z., Majeethia H., Dwarampudi J. M. R., et al., “The Associative Impact of Recreational Cannabis Use on Sinonasal Diseases,” Laryngoscope Investigative Otolaryngology 10, no. 5 (2025): e70261, 10.1002/lio2.70261.
Funding: The authors received no specific funding for this work.
Data Availability Statement
The data that support the findings of this study are available from The All of Us Research Database. Restrictions apply to the availability of these data, which were used under license for this study. Data are available from the author(s) with the permission of The All of Us Research Database.
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Associated Data
This section collects any data citations, data availability statements, or supplementary materials included in this article.
Supplementary Materials
Table S1: All ICD‐9 and ICD‐10 codes used for identifying patient comorbidities.
Data Availability Statement
The data that support the findings of this study are available from The All of Us Research Database. Restrictions apply to the availability of these data, which were used under license for this study. Data are available from the author(s) with the permission of The All of Us Research Database.