Impact of tobacco use on inpatient outcomes in inflammatory bowel disease: a retrospective matched cohort study
Mohamed H. Eldesouki1
, Mohammad Kloub1, Abdul-Rahman I. Abusalim2, Mohammed Y. Youssef3, Mona T. Ahmed4, Khaled Elfert5, Kanwarpreet Tandon5
Contributions: (I) Conception and design: MH Eldesouki, K Elfert, K Tandon; (II) Administrative support: K Elfert, K Tandon; (III) Provision of study materials or patients: None; (IV) Collection and assembly of data: MH Eldesouki, M Kloub; (V) Data analysis and interpretation: MH Eldesouki, ARI Abusalim, MY Youssef, MT Ahmed; (VI) Manuscript writing: All authors; (VII) Final approval of manuscript: All authors.
Background: Tobacco plays a complex role in patients with inflammatory bowel disease (IBD). Its impact on inpatient outcomes of IBD needs additional study. We aimed to assess the impact of smoking on clinical outcomes in hospitalized patients with IBD.
Methods: We conducted a retrospective cohort study using data from the National Inpatient Sample (NIS) spanning from 2016 to 2019. Patients with UC and CD were identified utilizing ICD-10 codes. Patients were stratified according to the smoking status in two groups. A propensity score matching was utilized to balance comorbidities between study groups. Study outcomes included rates of steroid use, surgeries, gastrointestinal (GI) bleeding, perianal abscess, and overall mortality. All outcomes were assessed during the index hospitalization. Statistical analysis was performed using Stata 17 software. Results were reported as adjusted odds ratios (aORs) with 95% confidence intervals (CIs).
Results: A total of 413,208 patients were included in our study, 180,558 patients had UC, and 232,650 patients had CD. After propensity score matching, we had a total of 151,106 patients: 39,616 patients had UC, with a total of 19,808 in each group. The CD patients were 111,490, with a total of 55,745 patients in each group. For UC patients, smokers had lower odds of steroid use (aOR =0.69, 95% CI: 0.61–0.79, P=0.001), and all-cause mortality (aOR =0.54, 95% CI: 0.32–0.96, P=0.03). For CD patients, smokers had higher odds of steroid use (aOR =1.13, 95% CI: 1.03–1.25, P=0.009), perianal abscess (aOR =1.12, 95% CI: 1.10–1.36, P=0.02), and all-cause mortality (aOR =1.51, 95% CI: 1.27–1.84, P=0.04). All other outcomes were not significant between the study cohorts.
Conclusions: Tobacco use in hospitalized patients with UC was associated with lower steroid use, while in patients with CD, it correlated with higher steroid use and increased odds of perianal abscesses. These findings highlight the complex impact of tobacco use on IBD outcomes.
Keywords: Inflammatory bowel disease (IBD); Crohn’s disease (CD); ulcerative colitis (UC); smoking
Submitted Sep 18, 2025. Accepted for publication Dec 26, 2025. Published online Feb 25, 2026.
doi: 10.21037/atm-25-141
Highlight box
Key findings
• Among hospitalized patients with ulcerative colitis (UC), smoking was associated with lower inpatient mortality and reduced use of systemic corticosteroids. In contrast, among hospitalized patients with Crohn’s disease (CD), smoking was associated with higher inpatient mortality, greater corticosteroid use, and an increased burden of perianal complications.
What is known and what is new?
• Tobacco use has opposing effects across inflammatory bowel disease (IBD), consistently worsening outcomes in CD while demonstrating complex and sometimes protective associations in UC.
• This study provides nationally representative inpatient evidence showing that these divergent effects of smoking also affect short-term hospital outcomes, including inpatient mortality, treatment intensity, and complication burden, rather than being limited to long-term disease course.
What is the implication, and what should change now?
• Smoking status should be recognized as a clinically relevant modifier of inpatient risk in IBD. Hospitalization represents a critical opportunity to implement targeted smoking cessation interventions, particularly for patients with CD. In patients with UC, these findings underscore the need for nuanced counseling that balances short-term inpatient outcomes with the well-established long-term risks of smoking.
Introduction
Inflammatory bowel disease (IBD) is a chronic and debilitating inflammatory disease that affects the gastrointestinal (GI) tract. Ulcerative colitis (UC) and Crohn’s disease (CD) are the two main components of IBD (1,2). Over the past several decades, the incidence of IBD has steadily increased in the newly industrialized nations and contributes substantially to health care utilization and costs. Over 5 million individuals worldwide are impacted, with 1.4 million living in the US alone (3). The pathogenesis of IBD is multifactorial and involves a complex interplay between genetic susceptibility, immunologic dysregulation, environmental exposures, and microbial factors. A key feature of IBD pathogenesis is impairment of the intestinal epithelial barrier, which promotes increased permeability, microbial translocation, and aberrant mucosal immune activation. These abnormalities have been linked to genetic variants that affect epithelial barrier integrity and immune regulation, contributing to chronic intestinal inflammation (4).
Diet and smoking are key modifiable environmental factors influencing the risk and progression of IBD. Smoking plays complex and controversial roles in patients with IBD (4). The effects of smoking on IBD have been shown to closely resemble its impact on chronic obstructive pulmonary disease (COPD), suggesting shared pathogenic mechanisms (4). The respiratory and GI epithelia share important structural and functional similarities, including their roles as selective barrier surfaces and a common embryologic origin from the primitive foregut (5). In addition, protease activity is essential for connective tissue integrity and tissue remodeling. Dysregulated protease activity has been described in both IBD and COPD, supporting the hypothesis that smoking may exert similar deleterious effects on both conditions through overlapping molecular pathways (6).
Despite extensive literature describing the long-term effects of smoking on disease onset, progression, and relapse in IBD, its influence on acute inpatient outcomes during IBD-related hospitalizations remains incompletely characterized (7-10). Most prior studies have focused on outpatient cohorts, disease incidence, or long-term therapeutic response, with limited evaluation of hospital-level outcomes that drive morbidity, mortality, and healthcare utilization. To address these gaps, we conducted a large, nationally representative study to evaluate the association between active tobacco use and inpatient outcomes among hospitalized patients with UC and CD by examining steroid utilization, disease-related complications, surgical interventions, and inpatient mortality. Our study adds novel insights into the complex and divergent effects of smoking in hospitalized patients with IBD, offering clinically relevant data that may inform risk stratification, inpatient management strategies, and future mechanistic investigations. We present this article in accordance with the STROBE reporting checklist (available at https://atm.amegroups.com/article/view/10.21037/atm-25-141/rc).
Methods
Data source and study design
Our data were obtained from the National Inpatient Sample (NIS) dataset for the period spanning January 2016 through December 2019. NIS database is developed by the Agency for Healthcare Research and Quality as a part of Healthcare Cost and Utilization Project (HCUP). It represents the largest publicly available all-payer inpatient database in the United States, constructed as a 20% stratified sample of discharges from U.S. community hospitals, drawn from a sampling frame that captures approximately 90% of all hospitalizations nationwide. Following its 2012 redesign, the NIS provides nationally representative estimates by sampling discharges rather than hospitals, yielding approximately 7–8 million unweighted hospitalizations annually, which correspond to over 35 million weighted discharges per year. Each hospitalization includes patient-level demographic data, hospital characteristics, recorded using the International Classification of Diseases, Tenth Revision, Clinical Modification/Procedure Coding System (ICD-10-CM/PCS). As the NIS contains fully de-identified data, this study was exempt from Institutional Review Board (IRB) review. The NIS has been extensively used in prior studies assessing substance use disorders, inpatient outcomes, and therapy-related complications, supporting its reliability for evaluating national trends and clinical outcomes in IBD (11). This study was conducted in accordance with the Declaration of Helsinki and its subsequent amendments.
Study design, cohorts, and outcomes
This was a retrospective cohort study utilizing the NIS. Adult patients (≥18 years) hospitalized with a principal diagnosis of IBD, including CD and UC, were identified using ICD-10-CM diagnostic codes. Patients younger than 18 years were excluded to ensure a uniform adult cohort. Patients were stratified based on active tobacco use documented during the index hospitalization into tobacco users and non-users. Tobacco exposure was defined using ICD-10-CM codes F17 (nicotine dependence) and Z72.0 (tobacco use). Importantly, we did not include ICD-10-CM code Z87.891 (personal history of nicotine dependence) in our smoking exposure definition, as this code reflects former tobacco use.
The study outcomes were in-hospital complications including systemic steroid use, IBD-related surgical interventions (including colectomy, proctectomy, enterectomy, resection, and ileostomy), GI hemorrhage, fistula of small intestine, perianal abscess, toxic megacolon, colonoscopy rates, and all-cause inpatient mortality, between the two study cohorts during the index hospitalization. All outcome definitions were based on ICD-10-CM/PCS codes, which are provided in Table S1.
Statistical analysis
All statistical analyses were performed using Stata 17 (StataCorp, College Station, TX, USA). Baseline characteristics were summarized using descriptive statistics. Propensity score matching was performed to balance baseline demographic and clinical characteristics between the two study cohorts. The propensity score was estimated using covariates including age, sex, race/ethnicity, median household income, primary insurance status, and relevant comorbidities known to influence IBD outcomes, including congestive heart failure, diabetes mellitus, hypertension, chronic kidney disease, and liver cirrhosis. A 1:1 nearest-neighbor matching without replacement was conducted using a caliper width of 0.01 on the propensity score scale. Covariate balance between matched cohorts was assessed using standardized mean differences, with values <0.1 indicating adequate balance. Following matching, categorical variables were compared using the Chi-square test, and continuous variables were compared using the Student’s t-test, as appropriate. Outcomes were expressed using adjusted odds ratio (aORs) with its 95% confidence interval (CI). A P value <0.05 was set to consider statistical significance. No subgroup or interaction analyses were prespecified or performed.
Results
Baseline characteristics
Before the propensity score matching, we had a total of 413,208 patients: 180,558 were UC patients, and 232,650 were CD patients. In the UC group, 30,916 were smokers and 149,642 were non-smokers, while in the CD group, 55,745 were smokers and 176,905 were non-smokers (Tables 1,2). After propensity score matching, a total of 39,616 patients had UC, 19,808 in each group. The CD patients were 111,490, with a total of 55,745 patients in each group. Tables 1,2 list all baseline characteristics for the study cohort.
Table 1
| Variable | Before matching | After matching | |||||||
|---|---|---|---|---|---|---|---|---|---|
| UC with smoking (n=30,916) | UC without smoking (n=149,642) | P value | Std. diff. | UC with smoking (n=19,808) | UC without smoking (n=19,808) | P value | Std. diff. | ||
| Demographics | |||||||||
| Age, years | 44.70±15.6 | 48.87±20.9 | <0.01 | 0.18 | 45.48±16.7 | 47.68±16.2 | 0.44 | 0.03 | |
| Female | 14,680 (47.5) | 81,379 (54.4) | <0.01 | 0.49 | 9,545 (48.2) | 10,230 (51.7) | 0.51 | 0.04 | |
| White | 22,548 (73.0) | 107,103 (71.6) | <0.01 | 0.34 | 14,452 (73.0) | 14,176 (71.6) | 0.61 | 0.02 | |
| African American | 4,241 (13.7) | 16,822 (11.2) | <0.01 | 0.07 | 2,719 (13.7) | 2,223 (11.2) | 0.37 | 0.03 | |
| Hispanic | 2,738 (8.9) | 16,878 (11.3) | <0.01 | 0.56 | 1,754 (8.9) | 2,235 (11.3) | 0.42 | 0.03 | |
| Comorbidities | |||||||||
| Heart failure | 1,266 (4.1) | 7,552 (5.1) | 0.08 | 0.85 | 824 (4.2) | 911 (4.6) | 0.36 | 0.02 | |
| Hypertension | 8,931 (28.9) | 40,306 (26.9) | 0.01 | 0.66 | 5,792 (29.2) | 5,456 (27.6) | 0.48 | 0.03 | |
| Diabetes mellitus | 1,869 (6.1) | 11,287 (7.5) | 0.02 | 0.37 | 1,248 (6.3) | 1,783 (7.0) | 0.33 | 0.04 | |
| Renal failure | 1,313 (4.3) | 9,098 (6.1) | 0.01 | 0.72 | 832 (4.2) | 971 (4.9) | 0.40 | 0.03 | |
| Liver disease | 2,364 (7.7) | 7,260 (4.9) | 0.01 | 0.69 | 1,460 (7.4) | 1,192 (6.0) | 0.55 | 0.04 | |
| Obesity | 2,510 (8.1) | 14,683 (9.8) | 0.02 | 0.37 | 1,779 (9.0) | 1,605 (8.1) | 0.46 | 0.03 | |
| Socioeconomic status (income quartile) | |||||||||
| Lowest (0–25) | 10,236 (33.1) | 34,676 (23.2) | 0.01 | 0.89 | 6,546 (33.1) | 5,196 (26.3) | 0.59 | 0.04 | |
| Lower-middle (26–50) | 8,360 (27.1) | 36,699 (24.5) | 0.01 | 0.57 | 5,201 (26.3) | 5,040 (25.5) | 0.62 | 0.03 | |
| Upper-middle (51–75) | 7,114 (23.0) | 39,161 (26.2) | 0.01 | 0.46 | 4,678 (23.6) | 5,046 (25.5) | 0.40 | 0.02 | |
| Highest (76–100) | 5,206 (16.8) | 39,106 (26.1) | 0.01 | 0.58 | 3,383 (17.0) | 4,512 (22.8) | 0.52 | 0.04 | |
| Insurance plan | |||||||||
| Medicare | 7,046 (22.8) | 43,375 (29.0) | 0.01 | 0.67 | 4,437 (22.4) | 5,048 (25.5) | 0.03 | 0.12 | |
| Medicaid | 8,585 (27.8) | 22,067 (14.8) | 0.01 | 0.99 | 5,521 (27.9) | 3,164 (16.0) | 0.04 | 0.13 | |
| Private insurance | 10,203 (33.0) | 71,835 (48.0) | 0.01 | 0.38 | 6,550 (33.1) | 9,796 (49.5) | 0.03 | 0.15 | |
| No insurance | 424 (1.4) | 7,482 (5.0) | 0.01 | 0.16 | 317 (1.6) | 1,796 (9.1) | 0.02 | 0.14 | |
Data are presented as mean ± standard deviation or n (%). Std. diff., standardized difference; UC, ulcerative colitis.
Table 2
| Variable | Before matching | After matching | |||||||
|---|---|---|---|---|---|---|---|---|---|
| CD with smoking (n=55,745) | CD without smoking (n=176,905) | P value | Std. diff. | CD with smoking (n=55,745) | CD without smoking (n=55,745) | P value | Std. diff. | ||
| Demographics | |||||||||
| Age, years | 45.80±16.7 | 49.15±21.8 | <0.01 | 0.09 | 42.88±21.8 | 42.59±22.1 | 0.44 | 0.04 | |
| Female | 26,470 (47.5) | 96,100 (54.4) | <0.01 | 0.10 | 29,376 (52.7) | 27,198 (48.9) | 0.08 | 0.07 | |
| White | 41,140 (73.9) | 124,760 (70.6) | <0.01 | 0.08 | 41,676 (74.8) | 41,071 (73.8) | 0.20 | 0.05 | |
| African American | 8,255 (14.8) | 21,650 (12.2) | <0.01 | 0.07 | 8,191 (14.7) | 8,487 (15.2) | 0.32 | 0.06 | |
| Hispanic | 4,315 (7.8) | 18,310 (10.4) | <0.01 | 0.06 | 3,164 (5.7) | 3,767 (6.8) | 0.27 | 0.07 | |
| Comorbidities | |||||||||
| Heart failure | 2,899 (5.2) | 10,630 (6.0) | 0.08 | 0.04 | 1,366 (2.5) | 1,163 (2.1) | 0.18 | 0.05 | |
| Hypertension | 15,501 (27.8) | 49,170 (27.8) | 0.99 | 0.00 | 13,321 (23.9) | 13,090 (23.5) | 0.40 | 0.04 | |
| Diabetes mellitus | 3,961 (7.1) | 14,180 (8.0) | 0.02 | 0.04 | 4,145 (7.4) | 3,906 (7.0) | 0.29 | 0.05 | |
| Renal failure | 2,987 (5.4) | 12,580 (7.1) | 0.01 | 0.07 | 2,540 (4.6) | 2,357 (4.2) | 0.22 | 0.06 | |
| Liver disease | 4,872 (8.7) | 10,140 (5.7) | 0.01 | 0.09 | 2,857 (5.1) | 3,043 (5.5) | 0.33 | 0.07 | |
| Obesity | 4,029 (7.2) | 15,380 (8.7) | 0.02 | 0.05 | 4,944 (8.9) | 4,587 (8.2) | 0.15 | 0.06 | |
| Socioeconomic status (income quartile) | |||||||||
| Lowest (0–25) | 19,085 (34.2) | 42,819 (24.2) | 0.01 | 0.10 | 12,899 (23.1) | 13,545 (24.3) | 0.21 | 0.05 | |
| Lower-middle (26–50) | 14,639 (26.3) | 41,570 (23.5) | 0.01 | 0.06 | 16,120 (28.9) | 13,674 (24.6) | 0.19 | 0.07 | |
| Upper-middle (51–75) | 13,440 (24.1) | 48,230 (27.3) | 0.01 | 0.06 | 13,234 (23.7) | 15,382 (27.6) | 0.12 | 0.08 | |
| Highest (76–100) | 10,215 (18.4) | 48,286 (27.3) | 0.01 | 0.09 | 9,140 (16.4) | 14,289 (25.6) | 0.28 | 0.09 | |
| Insurance plan | |||||||||
| Medicare | 12,700 (22.8) | 51,260 (29.0) | 0.01 | 0.07 | 13,340 (23.9) | 12,454 (22.3) | 0.31 | 0.15 | |
| Medicaid | 15,475 (27.8) | 27,850 (15.8) | 0.01 | 0.09 | 17,113 (30.7) | 10,653 (19.1) | 0.02 | 0.17 | |
| Private insurance | 18,280 (32.8) | 82,420 (46.6) | 0.01 | 0.08 | 18,178 (32.6) | 27,768 (49.8) | 0.01 | 0.18 | |
| No insurance | 808 (1.5) | 7,945 (4.5) | 0.01 | 0.07 | 725 (1.3) | 4,853 (8.7) | 0.01 | 0.17 | |
Data are presented as mean ± standard deviation or n (%). CD, Crohn’s disease; Std. diff., standardized difference.
Outcomes
UC patients
Among patients with UC, tobacco use was associated with a lower likelihood of systemic corticosteroid use (8.22% vs. 11.46%; aOR: 0.69, 95% CI: 0.61–0.79, P=0.001). No significant differences were observed in the incidence of GI bleeding (7.03% vs. 7.05%; aOR: 0.76, 95% CI: 0.59–1.08, P=0.90), intestinal perforation (0.66% vs. 0.83%; aOR: 0.79, 95% CI: 0.51–1.20, P=0.30), intestinal obstruction (0.15% vs. 0.11%; aOR: 1.37, 95% CI: 0.45–2.10, P=0.57), or colonoscopy rates (4.20% vs. 4.65%; aOR: 0.9, 95% CI: 0.75–1.08, P=0.30). The odds of toxic megacolon (0.03% vs. 0.14%; aOR: 0.18, 95% CI: 0.02–1.44, P=0.07) and surgical interventions (0.21% vs. 0.46%; aOR: 1.32, 95% CI: 0.90–1.63, P=0.09) were non-significant between the UC smokers and non-smokers. The overall mortality was significantly lower in the UC smoker than the non-smokers (0.24% vs. 0.45%; aOR: 0.54, 95% CI: 0.32–0.96, P=0.03) (Table 3, Figure 1).
Table 3
| Outcome | Smokers, n=19,808 | Non-smokers, n=19,808 | aOR | 95% CI | P value | |||
|---|---|---|---|---|---|---|---|---|
| Events | Risk (%) | Events | Risk (%) | |||||
| Steroid use | 1,628 | 8.22 | 2,269 | 11.46 | 0.69 | 0.61–0.79 | 0.001 | |
| Surgical interventions | 42 | 0.21 | 91 | 0.46 | 1.32 | 0.90–1.63 | 0.09 | |
| Colonoscopy | 832 | 4.20 | 921 | 4.65 | 0.90 | 0.75–1.08 | 0.30 | |
| Toxic megacolon | 5 | 0.03 | 28 | 0.14 | 0.18 | 0.02–1.44 | 0.07 | |
| Intestinal obstruction | 30 | 0.15 | 22 | 0.11 | 1.37 | 0.45–2.10 | 0.57 | |
| GI bleeding | 1,393 | 7.03 | 1,396 | 7.05 | 0.76 | 0.59–1.08 | 0.90 | |
| Intestinal perforation | 130 | 0.66 | 239 | 0.83 | 0.79 | 0.51–1.20 | 0.30 | |
| Overall mortality | 48 | 0.24 | 89 | 0.45 | 0.54 | 0.32–0.96 | 0.03 | |
aOR, adjusted odds ratio, CI, confidence interval; GI, gastrointestinal.
CD patients
CD smokers were associated with an increased likelihood of systemic corticosteroid use (10.49% vs. 9.40%; aOR: 1.13, 95% CI: 1.03–1.25, P=0.009). The odds of perianal abscesses were significantly higher in the CD smokers when compared with non-smokers (2.5% vs. 2.23%; aOR: 1.12, 95% CI: 1.10–1.36, P=0.02). No significant differences were observed between smokers and non-smokers in the incidence of intestinal obstruction (0.62% vs. 0.51%; aOR: 1.2, 95% CI: 0.84–1.8, P=0.29), small intestinal fistulas (6.79% vs. 6.96%; aOR: 0.97, 95% CI: 0.87–1.09, P=0.65). Non-significant differences between the rates of surgical interventions (1.48% vs. 2.05%; aOR: 0.72, 95% CI: 0.57–1.11, P=0.30), GI bleeding (2.78% vs. 3.38%; aOR: 0.82, 95% CI: 0.69–1.20, P=0.20), intestinal perforation (1.36% vs. 1.73%; aOR: 0.78, 95% CI: 0.62–1.20, P=0.10), and colonoscopy utilization (3.4% vs. 4.0%; aOR: 0.86, 95% CI: 0.74–1.00, P=0.06) were observed between smokers and non-smokers. CD smokers had higher overall mortality rates when compared with the non-smokers (0.28% vs. 0.14%; aOR: 1.51, 95% CI: 1.27–1.84, P=0.04) (Table 4, Figure 2).
Table 4
| Outcome | Smokers, n=55,745 | Non-smokers, n=55,745 | aOR | 95% CI | P value | |||
|---|---|---|---|---|---|---|---|---|
| Events | Risk (%) | Events | Risk (%) | |||||
| Steroid use | 5,848 | 10.49 | 5,240 | 9.40 | 1.13 | 1.03–1.25 | 0.009 | |
| Surgical interventions | 825 | 1.48 | 1,143 | 2.05 | 0.72 | 0.57–1.11 | 0.30 | |
| Colonoscopy | 1,895 | 3.40 | 2,230 | 4.00 | 0.86 | 0.74–1.00 | 0.06 | |
| Toxic megacolon | 17 | 0.03 | 78 | 0.14 | 0.23 | 0.03–1.48 | 0.08 | |
| Intestinal obstruction | 346 | 0.62 | 284 | 0.51 | 1.20 | 0.84–1.81 | 0.29 | |
| GI bleeding | 1,550 | 2.78 | 1,884 | 3.38 | 0.82 | 0.69–1.20 | 0.20 | |
| Intestinal perforation | 758 | 1.36 | 964 | 1.73 | 0.78 | 0.62–1.20 | 0.10 | |
| Fistula of small intestine | 3,785 | 6.79 | 3,879 | 6.96 | 0.97 | 0.87–1.09 | 0.65 | |
| Perianal abscess | 1,394 | 2.50 | 1,282 | 2.23 | 1.12 | 1.10–1.36 | 0.02 | |
| Overall mortality | 156 | 0.28 | 78 | 0.14 | 1.51 | 1.27–1.84 | 0.04 | |
aOR, adjusted odds ratio, CI, confidence interval; GI, gastrointestinal.
Discussion
Tobacco use has long been recognized as an important factor in the pathogenesis and clinical course of IBD, including CD and UC. This association was first observed in 1982, when a lower prevalence of UC was observed among smokers (12). Subsequent studies demonstrated that smoking increases the risk of developing CD (12). With the global burden of IBD and continued widespread use of tobacco products, estimated at 50.6 million U.S. adults in 2019 (13), further evaluation of the relationship between smoking and IBD outcomes remains important. In this study, we assessed the impact of smoking on clinical outcomes in hospitalized patients with both UC and CD.
Our study findings revealed the complex interaction between smoking and clinical outcomes in hospitalized patients with IBD. For UC, smoking was associated with lower odds of steroid use. In contrast, smokers with CD had higher odds of systemic steroid use and perianal abscesses compared to non-smokers, indicating a more inflammatory course. Rates of other inpatient complications including surgical interventions, toxic megacolon, colonoscopy, GI hemorrhage, and fistula of small intestine, were not significant between the study cohorts. Although prior studies have reported adverse effects of smoking on the course of CD (14,15), these findings have not been uniform, with some studies demonstrating no significant differences in surgical or immunosuppressive therapy requirements between smokers and non-smokers (14). Our results align with literature describing increased inflammatory burden and relapse risk among smokers with CD (14,15), and further demonstrate an association between smoking and higher all-cause inpatient mortality in this population.
The mechanisms underlying the associations observed in this study and prior literature remain incompletely understood, with several hypotheses proposed (16,17). Nicotine is thought to play a central role by modulating immune responses and inflammatory cytokine pathways in IBD (18). Additionally, smoking influences important factors such as blood flow (19), gut permeability (20), and gut motility through interactions with nitric oxide (21), all of which contribute to disease progression. The effect of smoking on IBD also depends on genetic factors, as some genetic variations may interact with smoking and modify disease risk (22). Smoking cessation was shown to help improve outcomes in CD, especially by reducing flare-ups and complications (23). On the other hand, in UC cessation was shown to have an increase in disease activity, hospital admissions, and the need for steroids, within the first years following the cessation of smoking (24). In a clinical trial it was reported that the addition of transdermal nicotine to conventional maintenance therapy improves symptoms in patients with UC (25). Our findings underscore the need for personalized treatment strategies that consider smoking status as a factor influencing disease course and hospitalization outcomes in UC and CD patients.
This study has several limitations. First, the NIS data captures hospitalization-level rather than patient-level data, limiting longitudinal assessment. The use of ICD-10 codes, primarily used for administrative purposes and billing, introduces misclassification. The database also lacks clinical granular data such as therapeutic interventions, labs, vitals, and radiological reports that may affect outcome and complication rates. The study does not include long-term outcomes after discharge which could provide further insight. Also, we did not have details on smoking intensity, which could show different effects for light, moderate, and heavy smokers. Despite these limitations, this study has notable strengths, including the use of a large, nationally representative dataset, enhancing generalizability to the U.S. inpatient population. The use of strong propensity score matching improved comparability between the study cohorts. The study also included various clinical outcomes, giving a comprehensive assessment of inpatient outcomes.
Conclusions
In summary, our study showed that in hospitalized patients with UC, tobacco use was associated with a lower likelihood of systemic steroid use, whereas in CD, smoking was linked to a higher probability of steroid use and perianal abscesses, and overall mortality, indicating a more inflammatory disease course. These findings underscore the complex and differential impact of smoking on IBD outcomes, suggesting that tobacco use may influence disease severity and healthcare utilization.
Acknowledgments
We thank the Agency for Healthcare Research and Quality (AHRQ) and the Healthcare Cost and Utilization Project (HCUP) for access to the National Inpatient Sample (NIS) 2016–2019. The authors alone are responsible for the content and writing of this paper; the views expressed do not necessarily represent those of AHRQ or HCUP. This study was previously presented as a poster at the American College of Gastroenterology Annual Scientific Meeting (ACG 2025).
Footnote
Reporting Checklist: The authors have completed the STROBE reporting checklist. Available at https://atm.amegroups.com/article/view/10.21037/atm-25-141/rc
Peer Review File: Available at https://atm.amegroups.com/article/view/10.21037/atm-25-141/prf
Funding: None.
Conflicts of Interest: All authors have completed the ICMJE uniform disclosure form (available at https://atm.amegroups.com/article/view/10.21037/atm-25-141/coif). The authors have no conflicts of interest to declare.
Ethical Statement: The authors are accountable for all aspects of the work in ensuring that questions related to the accuracy or integrity of any part of the work are appropriately investigated and resolved. This study was conducted in accordance with the Declaration of Helsinki and its subsequent amendments.
Open Access Statement: This is an Open Access article distributed in accordance with the Creative Commons Attribution-NonCommercial-NoDerivs 4.0 International License (CC BY-NC-ND 4.0), which permits the non-commercial replication and distribution of the article with the strict proviso that no changes or edits are made and the original work is properly cited (including links to both the formal publication through the relevant DOI and the license). See: https://creativecommons.org/licenses/by-nc-nd/4.0/.
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