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Predictors of Stress, Anxiety, Depression and Quality of Life in Patients Diagnosed with Chronic Inflammatory Bowel Disease in Romania: A Prospective Observational Case-Report Study

A peer-reviewed version of this preprint was published in:
Journal of Clinical Medicine 2026, 15(5), 1996. https://doi.org/10.3390/jcm15051996

Submitted:

06 February 2026

Posted:

09 February 2026

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Abstract
Background&Aims: Inflammatory bowel disease (IBD), encompassing Crohn's disease (CD) and ulcerative colitis (UC), is strongly linked to psychological comorbidities such as depression, anxiety, and stress. These mental health factors negatively impact disease progression, healthcare utilization, and quality of life (QoL). Methods: We conducted a cross-sectional case-control study (Nov 2023–Feb 2025) involving 355 participants: 55 with CD, 90 with UC, and 210 healthy controls. Participants completed the Depression Anxiety Stress Scales 21 (DASS-21) and EuroQol (EQ-5D-5L) questionnaires. Statistical analyses included multivariate linear regressions to identify predictors of psychological distress. Results: IBD patients reported significantly higher levels of stress (p< 0.01), anxiety (p=0.016), and depression (p< 0.01) compared to controls. Severe or very severe symptoms were more prevalent in CD and UC. Relative risk for stress was high (RR=2.1) and risk for depression was significantly elevated (RR=1.54) in IBD population. QoL analysis revealed lower EQ-VAS scores and increased difficulties across all EQ-5D-5L domains, particularly in emotional well-being and pain. Multivariate analysis showed UC diagnosis, female sex, and corticosteroid use as predictors of higher stress and depression scores, while self-reported rest was consistently protective. Conclusions: This study confirms the psychological burden of IBD and underscores the importance of regular screening for stress, anxiety, and depression in clinical care. Self-reported rest emerged as a key protective factor, suggesting potential benefits from interventions targeting sleep quality and emotional support. Future research should explore longitudinal outcomes and personalized psychological interventions in IBD populations.
Keywords: 
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1. Introduction

Inflammatory bowel diseases (IBD), primarily represented by Crohn’s disease (CD) and ulcerative colitis (UC), are significantly associated with depression, suggesting a bidirectional relationship between these conditions. Studies indicate a prevalence of 15.2% for depressive disorders and 21.6% for depressive symptoms among IBD patients [1]. Genetically predicted depression increases the risk of developing IBD [2].. Conversely, IBD patients also have an elevated risk of depression [3]. Female gender, lack of social support, and active disease are independent predictors of depression in IBD patients [4]. Depression rates are higher during active disease compared to remission [1,5]. Depression adversely affects disease outcomes, increasing the risk of relapse, medical costs, and emergency department visits [4,5]. Immunosuppressive therapies, particularly anti-TNF treatments, can reduce depressive symptoms [6].
Anxiety is also significantly associated with IBD, with studies reporting a prevalence of 20.9%, higher than the 15% seen in the general population [7]. A bidirectional relationship exists between anxiety and IBD, with active disease strongly correlated with higher anxiety rates compared to remission [8]. Female gender, smoking, extraintestinal manifestations, and a history of surgical interventions independently predict anxiety in IBD patients [9]. Anti-TNF and immunomodulator therapies have shown significant reductions in anxiety symptoms over periods of up to five years [10].
Stress significantly influences the onset and progression of IBD. Extended stressful events are linked to higher relapse rates (90% vs. 40% in low-stress individuals) [11]. Recent research highlights elevated stress rates among IBD patients [11,12]. A survey on patients during the COVID-19 pandemic found that 63.7% reported increased stress, with 21.1% experiencing worsened gastrointestinal symptoms [13]. Early life stressors are more common among IBD patients, suggesting childhood stress may contribute to disease development [14].
Given their high prevalence and impact in IBD, routine screening and management of psychological conditions are recommended as part of comprehensive patient care [8].

2. Materials and Methods

To assess the impact of IBD on mental health, we conducted a prospective cross-sectional case-control study (Nov 2023 – Feb 2025) in Cluj-Napoca, involving several clinical hopsitals. Medical staff distributed anonymous questionnaires to patients with confirmed IBD diagnoses during routine follow-up visits. The IBD group included adults (≥18 years) with confirmed diagnoses of CD or UC who consented to participate. The control group consisted of adults without IBD who also provided informed consent.
Participants completed a demographic and disease-specific section (for IBD patients), followed by Depression-Anxiety-Stress Scale (DASS-21), which includes 21 items divided into 3 subscales, depression, anxiety, and stress, each with 7 items scored from 0 to 3; final scores are multiplied by 2 and the EQ-5D-5L (which evaluates five dimensions: mobility, self-care, usual activities, pain/discomfort, and anxiety/depression, each with 5 severity levels).

Statistic Analysis

Data were analyzed using IBM SPSS v26. For normally distributed continuous variables, mean and standard deviation were reported; for non-normal distributions, median and interquartile range (IQR) were used. Categorical variables were presented as counts and percentages. Group comparisons were performed using independent t-tests for continuous variables and Chi-square or Fisher’s exact test for categorical data (significance threshold p<0.05). For non-normally distributed variables across three groups, the Kruskal-Wallis test with nonparametric post-hoc tests was applied. Multivariate linear models were used to assess associations between disease group (CD, UC, Control) and psychological scores (depression, anxiety, stress). When residuals were non-normally distributed, the square root transformation was applied. Models were adjusted for confounders based on clinical relevance and literature. Multicollinearity was assessed using correlation matrices and variance inflation factor. Heteroscedasticity was tested with the Breusch-Pagan test and QQ plots. Linearity was checked using component-plus-residual plots.

3. Results

3.1. Demographic Characteristics of Groups

The study included 355 participants, stratified in 3 groups, 55 with CD, 90 with UC and 210 in Control Group. There were no significant differences in gender, age, residence environment, proffesional activity, BMI and sleep hours between groups. Demographic data can be consulted in Table 1.

3.2. Characteristics of the IBD Groups

Table 2 summarizes key clinical features of CD and UC patients. Most patients did not follow a specific diet. Complications, such as fistulas, abscesses, and extraintestinal manifestations (uveitis, arthralgia, sacroiliitis) were reported more frequently in CD.

3.3. Risk Factors Associated with CD, UC, and the Control Group

Risk factor analysis revealed some statistically significant differences between groups. Weight category was similar across groups. Smoking status showed no significant difference. Reported standard of living differed significantly, with CD and UC patients more likely to report poor or average living conditions, while the control group reported better living standards (Table 3).

3.4. DASS-21 Score Distribution and Risk of Psychological Disorders.

DASS-21 analysis showed worse psychological symptoms in IBD patients (Table 4).
Three separate analyses were conducted to assess the relative risk (RR) of depression, stress, and anxiety in CD and UC patients versus controls.
o
Depression: Significantly increased risk (RR=1.54, 95% CI:1.17–2.02, p<0.01), indicating a 54% higher likelihood of depression in IBD patients. Both CD (RR = 1.47, 95% CI: 1.02–2.13, p=0.03) and UC (RR=1.58, 95% CI: 1.16–2.14, p<0.01) groups showed significantly higher risk compared to controls.
o
Stress: Even more pronounced risk (RR=2.1, 95% CI: 1.54–2.87, p < 0.01), suggesting IBD patients are over twice as likely to experience severe stress. This pattern was consistent for both CD vs. control (RR = 1.99, p<0.01) and UC vs. control (RR=2.18, p<0.01).
o
Anxiety: The overall increased risk did not reach statistical significance (RR=1.17, 95% CI: 0.97–1.42, p=0.1). CD patients (RR=1.11, p=0.42) showed no significant difference, while UC patients had a borderline increase (RR =1.21, 95% CI: 0.97–1.49, p = 0.07), not statistically significant.

3.5. Quality of Life (QOL) Analysis

QOL scores (Table 5) revealed significant differences between CD, UC, and control groups, highlighting the burden of IBD on general well-being. Overall health, assessed via the EQ-VAS, was significantly lower in CD and UC patients compared to controls, with no difference between CD and UC groups. Anxiety/depression symptoms were absent in 49.1% of CD and 54.4% of UC patients, vs. 81.4% in controls (Table 5). Usual activities were unaffected in 56.4% (CD), 66.7% (UC), and 84.3% (controls), with significant differences between IBD groups and controls. Self-care was less impacted, but still showed significant group differences: 74.5% (CD), 77.8% (UC), and 89.5% (controls) reported no difficulties. Pain/discomfort was reported by 47.8% (CD), 52.2% (UC), and 21.4% (controls). Mobility was impaired in 21.8% (CD), 17.8% (UC), and 9.5% (controls), with significant differences overall, though UC vs. control was not statistically significant.

3.6. Multivariate Analysis of Stress, Anxiety, and Depression Scores

To confirm the robustness of univariate results, multiple linear regression models were developed to predict depression, anxiety, and stress scores based on disease group, adjusted for demographic, behavioral, and biological predictors. The Durbin-Watson statistic ranged from 1.7–1.8 across models, indicating no significant autocorrelation. All variance inflation factors were near 1, suggesting no multicollinearity.
For stress, the model explained 21.0% of score variability (R²=0.210, adjusted R²=0.160, p<0.01). Significant predictors of higher stress included UC, CD, female gender, younger age, corticosteroid use, and better reported standard of living. Self-reported rest was associated with lower stress levels (Table 6).
For anxiety, the model explained 14.6% of the variance (R²=0.146, adjusted R²=0.103, p<0.01). Significant predictors of higher anxiety included UC, female gender, smoking , and higher BMI. Self-reported rest was associated with lower anxiety levels (Table 7).
For depression, the model explained 17.3% of score variability (R²=0.173, adjusted R²=0.132, p<0.02), indicating a moderate effect. Key predictors of higher depression included UC and female gender. Age was inversely associated with lower depression levels. Self-reported rest significantly reduced depression (Table 8).

4. Discussion

The study successfully met its goal of collecting over 100 questionnaires per group. However, all groups showed suboptimal questionnaire completion, possibly reflecting limited participant engagement, perhaps due to the lack of incentives.
An interesting observation was that over half of UC patients reported alcohol consumption, with significant differences even compared to CD patients. This could influence mental health, warranting more detailed investigation in future studies. Complications were more frequent in CD patients, reflecting greater disease severity. Anxiety, depression, and stress scores from DASS-21 were significantly higher in both IBD groups compared to controls, but not between CD and UC, aligning with prior literature [11,12,13,14,15,16] and the study’s aims.
DASS-21 findings confirmed a high prevalence of psychological symptoms in IBD, consistent with existing evidence. Stress scores showed a notably higher proportion of severe and very severe cases in IBD groups. This aligns with findings from Black et al. [15], who reported stress as a trigger for symptom exacerbation and lower quality of life in UC patients.
Regarding anxiety, while normal levels were comparable between groups, very severe anxiety was significantly more prevalent in IBD patients. Overall, findings highlight the psychological burden of IBD, supporting the need for early psychological interventions to improve disease management and quality of life. Moreover, stressful external situations such as the COVID-19 pandemic were associated with a significant decline on mental health and high levels of anxiety in individuals with IBD underscores the importance of healthcare strategies during global crises [17].
Quality of life analysis showed poorer general health in IBD patients, unsurprising given the disease burden and contributing factors like marital status and rest quality. IBD patients more frequently reported emotional issues, reduced ability to perform daily activities, impaired self-care and mobility, and more frequent pain/discomfort.
Multivariate analysis aimed to identify predictors of stress, depression, and anxiety. Self-reported rest was a protective factor across all outcomes. Biologic treatment was linked to lower stress and anxiety scores but had an inverse relationship with depression, potentially due to hidden medication effects or masking. Paradoxically, better standard of living was associated with higher stress and anxiety, though not significantly. A slightly increased depression risk was also observed. This might relate to higher responsibilities or expectations associated with affluence. Alcohol consumption was linked to lower stress and anxiety but higher depression scores, though not statistically significant. Smoking emerged as a risk factor for all psychological outcomes, consistent with literature noting its adverse effects on IBD progression [18,19]. Paradoxically, more reported sleep hours were associated with higher psychological scores. However, perceived rest was a strong protective factor, underscoring sleep quality over quantity, in line with previous studies [20].
Participant recruitment was challenging due to reluctance and incomplete questionnaires, limiting full engagement. A final limitation was the lack of disease activity data, preventing stratification of IBD patients into active vs. remission phases.

5. Conclusions

This study provides valuable insights into the prevalence of stress, depression, and anxiety in IBD patients, emphasizing the need for regular screening.
Psychological disorders are more frequent in IBD populations compared to controls. Sleep quality emerged as an important predictor, meriting focus in future interventional research.
Future studies should prioritize longitudinal designs, standardized assessment protocols for psychological distress, and deeper exploration of sleep quality to clarify affective patterns in IBD and guide targeted interventions.

Author Contributions

OFS, DL: Conceptualization, Methodology, Formal analysis, Writing – Original Draft. ADS, CB: Investigation, Data Curation, Writing – Review & Editing. AIT: Supervision, Resources, Writing – Review & Editing, Project Administration. All authors read and approved the final manuscript.
Founding: We would like to thank „Iuliu Hatieganu” University of Medicine and Pharmacy Cluj-Napoca for providing financial support, with grant numbers 881/46/12 Jan 2022 and 772/37/11 Jan 2023. .

Funding

We would like to thank „Iuliu Hatieganu” University of Medicine and Pharmacy Cluj-Napoca for providing financial support, with grant numbers 881/46/12 Jan 2022 and 772/37/11 Jan 2023.

Institutional Review Board Statement

The study was conducted in accordance with the Declaration of Helsinki, and approved by the Ethics Committee of CF Cluj Hospital Institutional Review Board (protocol code 243) approval date: 11 Jan 2023.

Acknowledgments

We would like to thank all study participants and all nurses and medical registrators who provided help with distribution of questionnaires.

Conflicts of interest

The authors declare no conflict of interest.

References

  1. Neuendorf, R.; Harding, A.; Stello, N.; Hanes, D.; Wahbeh, H. Depression and anxiety in patients with Inflammatory Bowel Disease: A systematic review. J. Psychosom. Res. 2016, 87, 70–80. [Google Scholar] [CrossRef] [PubMed]
  2. Zhang, B.; Wang, H.H.E.; Bai, Y.M.; Tsa, S.J.; Su, T.P.; Chen, T.J.; Wang, T.Y.; Chen, M.H. Bidirectional association between inflammatory bowel disease and depression among patients and their unaffected siblings. J. Gastroenterol. Hepatol. 2022, 37, 1307–1315. [Google Scholar] [CrossRef] [PubMed]
  3. Luo, J.; Xu, Z.; Noordam, R.; Van Heemst, D.; Li-Gao, R. Depression and Inflammatory Bowel Disease: A Bidirectional Two-sample Mendelian Randomization Study. J. Crohn’s Colitis 2022, 16, 633–642. [Google Scholar] [CrossRef] [PubMed]
  4. Wong, J.J.; Sceat, s L.; Dehghan, M.; Wren, A.A.; Sellers, Z.M.; Limketkai, B.N.; Bensen, R.; Kin, C.; Park, K.T. Depression and Health Care Use in Patients With Inflammatory Bowel Disease. J. Crohn’s Colitis 2019, 13, 19–26. [Google Scholar] [CrossRef] [PubMed]
  5. Kochar, B.; Barnes, E.L.; Long, M.D.; Cushing, K.C.; Galanko, J.; Martin, C.F.; Raffals, L.E.; Sandler, R.S. Depression Is Associated With More Aggressive Inflammatory Bowel Disease. Am. J. Gastroenterol. 2018, 113, 80–85. [Google Scholar] [CrossRef] [PubMed]
  6. Horst, S.; Chao, A.; Rosen, M.; Nohl, A.; Duley, C.; Wagnon, J.H.; Beaulieu, D.B.; Warren, T.; Gaines, L.; Schartz, D.A. Treatment with immunosuppressive therapy may improve depressive symptoms in patients with inflammatory bowel disease. Dig. Dis. Sci. 2015, 60, 465–470. [Google Scholar] [CrossRef] [PubMed]
  7. Tarar, Z.I.; Zafar, M.U.; Farooq, U.; Ghous, G.; Aslam, A.; Inayat, F.; Ghouri, Y.A. Burden of depression and anxiety among patients with inflammatory bowel disease: results of a nationwide analysis. Int. J. Colorectal. Dis. 2022, 37, 313–321. [Google Scholar] [CrossRef] [PubMed]
  8. Graff, L.A.; Geist, R.; Kuenzig, M.E.; Benchimol, E.I.; Kaplan, G.G.; Windsor, J.W.; Bitton, A.; Coward, S.; Jones, J.L.; Lee, K; et al. The 2023 Impact of Inflammatory Bowel Disease in Canada: Mental Health and Inflammatory Bowel Disease. J. Can. Assoc. Gastroenterol. 2023, 6 (Suppliment 2), S64–75. [Google Scholar] [CrossRef] [PubMed]
  9. Navabi, S.; Gorrepati, V.S.; Yadav, S.; Chintanaboina, J.; Maher, S.; Demuth, P.; Stern, B.; Stuart, A.; Tinsley, A.; Clarke, K.; et al. Influences and Impact of Anxiety and Depression in the Setting of Inflammatory Bowel Disease. Inflamm. Bowel. Dis. 2018, 24, 2303–2308. [Google Scholar] [CrossRef] [PubMed]
  10. Siebenhüner, A.R.; Rossel, J.B.; Schreiner, P.; Butter, M.; Greuter, T.; Krupka, N.; Jordi, S.B.U.; Biedermann, L; Rogler, G.; Misselwitz, B.; et al. Effects of anti-TNF therapy and immunomodulators on anxiety and depressive symptoms in patients with inflammatory bowel disease: a 5-year analysis. Therap. Adv. Gastroenterol. 2021, 14, 7562848211033763. [Google Scholar] [CrossRef] [PubMed]
  11. Fernández, L.J.; Ferrer, J.Á.; Calle, J.L.P.; Álvarez, L.M.; Serrano López, P. Psychological disorders and coping strategies in patients with inflammatory bowel disease. Their impact on health-related quality of life. Rev. Esp. Enfermedades. Dig. 2024, 116, 193–200. [Google Scholar] [CrossRef] [PubMed]
  12. Oligschlaeger, Y.; Yadati, T.; Houben, T.; Oliván, C.M.C.; Shiri-Sverdlov, R. Inflammatory Bowel Disease: A Stressed “Gut/Feeling”. Cells 2019, 8, 659. [Google Scholar] [CrossRef] [PubMed]
  13. El-Dallal, M.; Saroufim, A.; Systrom, H.; Ballou, S.; Farhoud, A.; Pasam, R.T.; Gadupudi, S.S.; Osman, K.; Chaudrey, K.; Cheifetz, A.; et al. Assessing the repercussions of COVID-19 pandemic on symptoms, disease management, and emotional well-being in patients with inflammatory bowel disease: a multi-site survey study. Scand. J. Gastroenterol. 2022, 57, 406–414. [Google Scholar] [CrossRef] [PubMed]
  14. Bednarikova, H.; Kascakova, N.; Furstova, J.; Zelinkova, Z.; Falt, P.; Hasto, J.; Travel, P. Life Stressors in Patients with Inflammatory Bowel Disease: Comparison with a Population-Based Healthy Control Group in the Czech Republic. Int. J. Environ. Res. Public. Health.. 2021, 18, 1–12. [Google Scholar] [CrossRef] [PubMed]
  15. Black, J.; Sweeney, L.; Yuan, Y.; Singh, H.; Norton, C.; Czuber-Dochan, W.N. Systematic review: the role of psychological stress in inflammatory bowel disease. Aliment Pharmacol. Ther. 2022, 56, 1235–1249. [Google Scholar] [CrossRef] [PubMed]
  16. Watson, N.; Mawdsley, J.; Kent, A.; Duff, A.; Norton, C.; Moulton, C.; Czuber-Dochan, W.N. Managing pain in people with Crohn’s Disease: feasibility testing of an Acceptance and Commitment Group Therapy intervention. J. Crohn’s Colitis 2025, 19, i1621–i16622. [Google Scholar] [CrossRef]
  17. Sârb, O.F.; Văcaras, V.; Filip, V.P.; Sârb, A.D.; Zaharie, R.D.; Drăghici, N.; Mureșan, D.F.; Tanțău, A.I. The impact of the COVID-19 pandemic on the mental health of patients diagnosed with inflammatory bowel diseases. J Med Life 2023, 16, 1864–1868. [Google Scholar] [PubMed]
  18. Rozich, J.J.; Holmer, A.; Singh, S. Effect of Lifestyle Factors on Outcomes in Patients With Inflammatory Bowel Diseases. Am. J. Gastroenterol. 2020, 115(6), 832–40. [Google Scholar] [CrossRef] [PubMed]
  19. Carney, H.; Marrie, R.A.; Bolton, J.M.; Patten, S.B.; Graff, L.A.; Bernstein, C.N.; Kowalesc, K. Prevalence and Risk Factors of Substance Use Disorder in Inflammatory Bowel Disease. Inflamm. Bowel. Dis. 2020, 27, 58. [Google Scholar] [CrossRef] [PubMed]
  20. Araki, M.; Shinzaki, S.; Yamada, T.; Arimitsu, S.; Komori, M.; Shibukawa, N.; et al. Psychologic stress and disease activity in patients with inflammatory bowel disease: A multicenter cross-sectional study. PLoS One 2020, 15, 1–12. [Google Scholar] [CrossRef] [PubMed]
Table 1. Demographic data of included patients.
Table 1. Demographic data of included patients.
CD (n=55) UC (n=90) Control (n=210) P
Age 37,40 (33,99 - 40,81) 41,20(37,80 - 44,60) 40,86(38,82 - 42,90) 0,586
Female gender 33 (60%) 55 (61,1%) 130 (61,9%) 0,96
Civil status <0,01
Single 17 (30,9%) 21 (23,4%) 31 (14,7%)
Stable relationship 10 (18,2%) 15 (16,7%) 18 (8,6%)
Married 24 (43,6%) 45 (50%) 154 (73,3%)
Divorced 2 (3,6%) 6 (6,6%) 2 (1%)
Widowed 2 (3,6%) 3 (3,3%) 5 (2,4%)
Urban living area 51 (92,7%) 75 (83,3%) 180 (85,7%) 0,26
Proffesional activity 0,44
Employee 41 (74,5%) 55 (61,1%) 155 (69%)
Retired 6 (12,7%) 16 (17,8%) 40 (19%)
Unemployed 1 (1,8%) 5 (5,6%) 2 (1%)
Student, trainee 6 (10,9%) 12 (13,3%) 18 (8,6%)
Education (years) 13,91(13,05 - 14,77) 15,42(14,71 - 16,13) 15,51(15,03 - 15,99) 0,006
BMI (kg/m2) 24,72(23,64 - 25,81) 24,12(23,12 - 25,12) 25,77(25,02 - 26,52) 0,097
Hours of sleep 6,79(6,58 - 7) 6,70(6,51 - 6,89) 6,73(6,61 - 6,85) 0,975
Table 2. IBD Patients characteristics.
Table 2. IBD Patients characteristics.
CD (n=55) UC (n=90) P
Time since IBD diagnosis 0,69
Less than 1 year 3 (5,4%) 9 (10%)
1-5 years 24 (43,6%) 41 (45,5%)
6-10 years 15 (27,2%) 19 (21,1%)
Over 10 years 13 (23,6%) 21 (23,3%)
Specific dietary regimen 10 (18,1%) 19 (21,1%) 0,66
IBD complications 29 (52,7%) 24 (26,6%) <0,01
Surgical treatment of complications 13 (23,6%) 4 (4,4%) <0,01
Corticodependence 10 (18,1%) 9 (10%) 0,15
Disease modifying therapy 0,43
5ASA 12 (21,6%) 43 (47,7%)
Biologic 32 (59%) 32 (35,4%)
Imnunosupresor 4 (7,2%) 4 (4,4%)
Homeopatic or probiotic 0 (0%) 4 (4,4%)
None 7 (12,7%) 7 (7,7%)
Table 3. Risk factors among the three groups.
Table 3. Risk factors among the three groups.
CD (n=55) UC (n=90) Control (n=210) P
Smoking status 0,18
Yes 17 (30,9%) 21 (23,3%) 57 (27,1%)
No 29 (52,7%) 62 (68,8%) 140 (66,6%)
Abstinent 8 (14,5) 7 (7,7%) 13 (6,1%)
Standard of living <0,0001
Difficult 12 (21,8%) 13 (14,4%) 6 (2,8%)
Decent 18 (32,7%) 31 (34,4%) 83 (39,5%)
Good 24 (43,6%) 43 (47,7%) 100 (47,6%)
Very good 1 (1,8%) 3 (3,3%) 21 (10%)
Reported rest (Yes) 30 (54,5%) 52 (57,7%) 141 (67,1%) 0,11
Physical activity (Yes) 19 (34,5%) 48 (53,3%) 111 (52,8%) 0,04
Alcohol consumption 21 (38,2%) 39 (56,7%) 142 (32,4%) <0,01
Table 4. Stress, anxiety and depression scores among the three groups. (a) No significant differences between two groups; (b) No significant differences between two groups.
Table 4. Stress, anxiety and depression scores among the three groups. (a) No significant differences between two groups; (b) No significant differences between two groups.
CD (n=55) UC (n=90) Control (n=210) P
Stress level < 0,01
Normal 31 (56,4%) (a) 47 (52,2%) (a) 164 (78,1%) (b)
Mild 8 (14,5%) (a) 11 (12,2%) (a) 19 (9%) (a)
Moderate 7 (12,7%) (a) 8 (8,9%) (a) 17 (8,1%) (a)
Severe 3 (5,5%) (a) (b) 11 (12,2%) (b) 4 (1,9%) (a)
Very severe 6 (10,9%) (a) 13 (14,4%) (a) 6 (2,9%) (b)
Anxiety level 0,016
Normal 24 (43,6%) (a) 35 (38,9%) (a) 104 (49,5%) (a)
Mild 5 (9,1%) (a) 11 (12,2%) (a) 46 (21,9%) (a)
Moderate 9 (16,4%) (a) 16 (17,8%) (a) 27 (12,9%) (a)
Severe 6 (10,9%) (a) 8 (8,9%) (a) 13 (6,2%) (a)
Very severe 11 (20%) (a) (b) 20 (22,2%) (a) 20 (9,5%) (a)
Depression level <0,01
Normal 31 (56,4%) (a) (b) 48 (53,3%) (b) 148 (70,5%) (a)
Mild 6 (10,9%) (a) 5 (5,6%) (a) 23 (11%) (a)
Moderate 6 (10,9%) (a) 14 (15,6%) (a) 25 (11,9%) (a)
Severe 4 (7,3%) (a) 7 (7,8%) (a) 5 (2,4%) (a)
Very severe 8 (14,5%) (a) 16 (17,8%) (a) (4,3%) (b)
Table 5. Quality of Life Assessment in the Three Groups. (a) No significant difference between groups; (b) No significant difference between groups.
Table 5. Quality of Life Assessment in the Three Groups. (a) No significant difference between groups; (b) No significant difference between groups.
CD (n=55) UC (n=90) Control (n=210) P
General Health Status 76,16
(70,49 - 81,84) (a)
79,72
(76,22 - 83,22) (a)
90,31
(88,18 - 92,44) (b)
<0,01
Anxiety and Depression <0.01
I am not anxious or depressed 28 (50,9%) (a) 41 (45,6%) (a) 141 (81,4%) (b)
I am slightly anxious or depressed 14 (25,5%) (a) 25 (27,8%) (a) 22 (10,5%) (b)
I am moderately anxious or depressed 8 (14,5%) (a) (b) 14 (15,6%) (b) 11 (5,2%) (a)
I am severely anxious or depressed 4 (7,3%) (a) 6 (6,7%) (a) 6 (2,9%) (a)
I am extremely anxious or depressed 1 (1,8%) (a) (b) 4 (4,4%) (b) 0 (0%) (a)
Usual Activities <0,01
I have no problems doing my usual activities 31 (56,4%) (a) 60 (66,7%) (a) 177 (84,3%) (b)
I have slight problems doing my usual activities 18 (32,7%) (a) 21 (23,7%) (a), (b) 27 (12,9%) (b)
I have moderate problems doing my usual activities 6 (10,9%) (a) 8 (8,9%) (a) 4 (1,9%) (b)
I have severe problems doing my usual activities 0 (0%) (a) 1 (1,1%) (a) 1 (0,5%) (a)
I am unable to do my usual activities 0 (0%) (a) 0 (0%) (a) 1 (0,5%) (a)
Self-Care 0,02
I have no problems washing or dressing myself 41 (74,5%) (a) 70 (77,8%) (a) 188 (89,5%) (b)
I have slight problems washing or dressing myself 11 (20%) (a) 16 (17,8%) (a) 20 (9,5%) (a)
I have moderate problems washing or dressing myself 1 (1,8%) (a) 1 (1,1%) (a) 2 (1%) (a)
I have severe problems washing or dressing myself 2 (3,6%) (a) 3 (3,3%) (a) 0 (0%) (b)
Pain and Discomfort <0,01
I have no pain or discomfort 29 (52,7%) (a) 43 *(47,8%) (a) 165 (78,6%) (b)
I have slight pain or discomfort 13 (23,6%) (a), (b) 31 (34,4%) (b) 34 (16,2%) (a)
I have moderate pain or discomfort 11 (20%) (a) 15 (16,7%) (a) 7 (3,3%) (b)
I have severe pain or discomfort 2 (3,6%) (a) 1 (1,1%) (a) 4 (1,9%) (a)
Mobility 0,015
I have no problems walking 43 (78,2%) (a) 74 (82,2%) (a), (b) 190 (90,5%) (b)
I have slight problems walking 9 (16,4%) (a) 12 (13,3%) (a) 16 (7,6%) (a)
I have moderate problems walking 3 (5,5%) (a) 4 (4,4%) (a) 3 (1,4%) (a)
I have severe problems walking 0 (0%) (a) 0 (0%) (a) 1 (0,5%) (a)
Table 6. Multiple Linear Regression for Predicting the Square Root of Stress Score, Adjusted for Multiple Covariates.
Table 6. Multiple Linear Regression for Predicting the Square Root of Stress Score, Adjusted for Multiple Covariates.
Variable B- CI 95% p
Stress Score 2.841 (1.14, 4.54) <0.01
UC vs. Control 1.040 (0.59, 1.49) <0.01
CD vs. Control 0.725 (0.14, 1.31) 0.015
Female sex 0.718 (0.39, 1.05) <0.01
Corticosteroid treatment 0.438 (-0.28, 1.16) 0.023
Smoking 0.329 (-0.01, 0.67) 0.06
Standard of living 0.253 (-0.08, 0.58) 0.013
Physical activity 0.237 (-0.09, 0.56) 0.15
Alcohol consumption 0.129 (-0.21, 0.47) 0.45
Reported hours of sleep 0.107 (-0.07, 0.28) 0.24
BMI 0.005 (-0.03, 0.04) 0.75
Relationship status -0.003 (-0.38, 0.37) 0.98
Age -0.016 (-0.027, -0.005) <0.01
Education (years) -0.044 (-0.09, 0.01) 0.08
Urban residence -0.063 (-0.54, 0.41) 0.79
Special diet -0.149 (-0.75, 0.45) 0.62
Biologic treatment -0.408 (-0.91, 0.10) 0.11
Self-reported rest -0.509 (-0.84, -0.18) <0.01
Table 7. Multiple Linear Regression for Predicting the Square Root of Anxiety Score, Adjusted for Multiple Covariates.
Table 7. Multiple Linear Regression for Predicting the Square Root of Anxiety Score, Adjusted for Multiple Covariates.
Variable B- CI 95% p
Anxiety Score 2.521 (0,736 - 4,306) <0,01
UC vs. Control 0.686 (0.22 - 1.15) <0.01
CD vs. Control 0.527 (-0.09 - 1.14) 0.09
Female sex 0.527 (0.19 - 0.86) <0.01
Smoking 0.509 (0.15 - 0.87) <0.01
Corticosteroid treatment 0.396 (-0.36 - 1.16) 0.3
Alcohol consumption 0.177 (-0.18 - 0.54) 0.32
Special diet 0.158 (-0.48 - 0.79) 0.62
Reported hours of sleep 0.128 (-0.06 - 0.32) 0.18
Physical activity 0.067 (-0.28 - 0.41) 0.7
Relationship status 0.048 (-0.35 - 0.45) 0.81
Standard of living 0.043 (-0.31 - 0.40) 0.8
Age -0.006 (-0.02 - 0.01) 0.34
BMI -0.009 (-0.04 - 0.02) 0.6
Education (years) -0.046 (-0.10 - 0.01) 0.08
Urban residence -0.076 (-0.57 - 0.42) 0.76
Biologic treatment -0.472 (-1.00 - 0.06) 0.08
Self-reported rest -0.629 (-0.98 - -0.28) <0.01
Table 8. Multiple Linear Regression for Predicting the Square Root of Depression Score, Adjusted for Multiple Covariates.
Table 8. Multiple Linear Regression for Predicting the Square Root of Depression Score, Adjusted for Multiple Covariates.
Variable B- CI 95% p
Depression Score 2,764 (0,740 – 4,788) <0,01
UC vs. Control 0,812 (-0,284 – 1,340) <0,01
Female sex 0,642 (0,256 – 1,027) <0,01
Corticosteroid treatment 0,523 (-0,331 -1,376) 0,22
Biologic treatment 0,493 (-0,109 – 1,096) 0,1
Physical activity 0,350 (-0,042 – 0,742) 0,08
CD vs. Control 0,321 (-0,374 – 1,016) 0,36
Smoking 0,158 (-0,253 – 0,569) 0,44
Reported hours of sleep 0,112 (-0,102 – 0,326) 0,3
Relationship status 0,051 (-0,394 – 0,496) 0,82
Urban residence 0,019 (-0,544 – 0,583) 0,94
Standard of living 0,017 (-0,378 – 0,413) 0,93
BMI -0,005 (-0,042 – 0,032) 0,8
Age -0,016 (-0,029 - -0,002) 0,021
Alcohol consumption -0,035 (-0,439 – 0,369) 0,86
Education (years) -0,056 (-0,116 – 0,004) 0,06
Special diet -0,480 (-1,202 – 0,242) 0,19
Self-reported rest -0,817 (-1,217 – -0,417) <0,01
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