Sleep quality, treatment burden, and quality of life in patients with inflammatory bowel disease: A cross-sectional study

Abstract

BACKGROUND

The management of inflammatory bowel disease (IBD) requires balancing a patient’s treatment workload with his physical and psychological coping capacity. However, the synergistic impact of treatment burden and sleep disturbance on the quality of life (QoL) remains ill-defined in clinical gastroenterology practice.

AIM

To determine the associations of sleep quality and treatment burden with QoL in IBD.

METHODS

This cross-sectional study enrolled 158 patients with IBD at a tertiary hospital in China between December, 2023 and June, 2024. Participants completed the IBD Questionnaire, the Pittsburgh Sleep Quality Index, and the Treatment Burden Questionnaire. Descriptive statistics, Spearman’s correlation, and multiple linear regression analysis were utilized to identify the independent predictors of QoL.

RESULTS

Overall, 34.81% of the participants reported poor QoL, and 61.39% (n = 97) experienced poor sleep quality. The mean treatment burden score was 39.81 ± 30.54. Multiple linear regression analysis revealed that a higher treatment burden (β = -0.287, P < 0.001), poorer sleep quality (β = -0.286, P < 0.001), and a higher number of hospitalizations in the past year (β = -0.162, P = 0.025) were independent predictors of lower QoL. These modifiable clinical variables collectively explained 25.4% of the variance in the overall QoL scores.

CONCLUSION

High treatment burden and poor sleep quality correlate with lower QoL in patients with IBD, suggesting that managing sleep and treatment-related stressors may optimize patient outcomes.

Key Words: Inflammatory bowel disease; Quality of life; Sleep quality; Treatment burden; Cumulative Complexity Model

Core Tip: After applying the novel Cumulative Complexity Model, this study showed that a severe imbalance between patient “workload” (escalating treatment burden) and depleted “capacity” (fragmented sleep) are independently associated with the deterioration of quality of life in patients with inflammatory bowel disease. With 61.39% of patients experiencing poor sleep, our findings complement the traditional methods that focus solely on mucosal healing. We thus urge a paradigm shift in inflammatory bowel disease management: Multidisciplinary teams must urgently integrate routine sleep screening and systemic burden-relief strategies, such as streamlining care pathways, to help restore patient resilience and optimize long-term quality of life.

INTRODUCTION

Inflammatory bowel disease (IBD), which primarily comprises ulcerative colitis (UC) and Crohn’s disease (CD), is a chronic disease characterized by recurrent intestinal inflammation. Although IBD has been traditionally more common in Western developed countries, its incidence rate has risen rapidly in emerging industrialized countries, especially in China, which has one of the fastest-growing incidence rates in the world[1-3]. The impact of IBD extends beyond intestinal inflammation, greatly impairing patients’ mental health and overall quality of life (QoL)[4-6]. Therefore, improving QoL alongside mucosal healing has been established by the International Organization for the Study of IBDs as a long-term treatment goal[7].

However, improving QoL also requires addressing the complex psychosocial and daily realities of living with IBD[8,9]. In this context, the Cumulative Complexity Model (CCM) provides a highly practical framework[10]. The CCM frames patient outcomes as a delicate equilibrium between patient workload. For individuals with IBD, this workload is particularly intensive, encompassing intricate polypharmacy regimens, strict dietary modifications, and the logistical demands of frequent, often invasive, endoscopic monitoring and clinical visits[11]. When the burden of treatment increases, patients may become unable to cope as well as unable to afford the treatment[12].

Sleep quality serves as a vital factor of patient capacity. Sleep disturbances are highly prevalent among patients with IBD[13] and are typically driven by nocturnal gastrointestinal symptoms, corticosteroid use, or ongoing subclinical inflammation[14]. Fragmented sleep further drains the cognitive and physical energy necessary to navigate the illness[15-18]. Furthermore, patients frequently encounter geographic barriers to tertiary referral centers as well as medical expenses issues. These systemic barriers substantially amplify both the objective workload and the subjective perception of treatment burden. Unfortunately, understanding how these unique systemic pressures interact with sleep capacity to shape QoL constitutes a gap in the current literature.

Therefore, in conducting this study we aimed to: (1) Evaluate the level of QoL among Chinese patients with IBD; and (2) Examine the independent associations of treatment burden and sleep quality with QoL. Guided by the CCM, we hypothesized that a higher treatment burden, and poorer sleep quality would collectively predict lower QoL. By mapping these modifiable, patient-reported dimensions, we also aim to provide clear evidence for gastroenterologists and specialized care teams to shift toward a multidisciplinary care model designed to enhance patient capacity and alleviate the burden of care, such as care coordination and behavioral sleep support.

MATERIALS AND METHODS

Design and participants

An observational, cross-sectional study was conducted from December, 2023 to June, 2024 at a tertiary hospital in Tianjin, China. According to Kendall’s sample size calculation method, the total number of participants should be between five and ten times the number of measured variables in order to ensure adequate statistical power. In this study design, a maximum of 14 candidate independent variables were considered [12 demographic and clinical characteristics, the total Pittsburgh Sleep Quality Index (PSQI) score, and the total Treatment Burden Questionnaire (TBQ) score]. The total number of variables included in this study is 14, so that the required sample size was between 70 and 140. Inclusion criteria consisted of the following: Meeting the diagnostic criteria in the “Consensus on the Diagnosis and Treatment of Inflammatory Bowel Disease in China”; being in a relatively stable disease phase without acute severe exacerbation judged by attending physicians; and being conscious and able to communicate normally with full comprehension. The exclusion criteria were: Comorbid severe organic diseases, severe psychiatric disorders, cognitive impairment, communication difficulties, and pregnancy or lactation, and patients were enrolled using convenience sampling. Patients were enrolled using convenience sampling from a single center that resulted in a significantly higher proportion of patients with UC. This study was strictly conducted and reported in accordance with the STROBE guidelines.

Data collection

This study was a cross-sectional survey in which the data were collected using convenience sampling through the online platform Wenjuanxing (www.wjx.cn). Data collection followed standardized operation procedures and used unified questionnaires and instructions. Patients who met the inclusion criteria were informed of the study information by their attending physicians or nurses during regular diagnosis and treatment or follow-up visits. All participants voluntarily joined on the basis of a full understanding of the research purpose. Before accessing the online questionnaire, electronic informed consent was strictly required. Individuals who declined participation were automatically redirected and denied access to the survey. Each qualified participant could only submit the anonymous questionnaire once. All the returned questionnaires were verified for completeness and logical consistency. In total participants were asked to complete a general information questionnaire, the IBD Questionnaire (IBDQ), the TBQ, and the PSQI.

The general information questionnaire

Sociodemographic and clinical data were collected using a self-designed general information questionnaire. These included sex, age, disease type (UC/CD), educational level, marital status, employment status, household and personal monthly income, medical payment method, family history of IBD, surgery history, and number of IBD-related hospitalizations in the past year.

IBDQ

This study utilized the Chinese version of the IBDQ to assess QoL. The questionnaire consists of four dimensions: Intestinal symptoms, systemic symptoms, emotional function, and social function, with a total of 32 items[19]. Each item is scored using a 7-point Likert scale, with a total score ranging from 32 to 224 points. The higher the score, the better the QoL. According to the current standards, a total score lower than 169 is defined as poor QoL[20]. The Chinese version has been validated for reliability and validity in the IBD population in China[9]. In our present study, the questionnaires demonstrated extremely high internal consistency, with a Cronbach’s coefficient of 0.96.

PSQI

Sleep quality was measured using the Chinese version of the PSQI, a 19-item instrument comprising seven components: Sleep quality, latency, duration, efficiency, disorders, hypnotic drugs taken, and daytime functional impairment in the past month. Each component is scored 0-3, yielding a global score of 0-21, where > 5 indicates poor sleep quality[21]. The Chinese PSQI has also been validated for use in IBD populations[15], and in our study, the Cronbach’s α was 0.786.

TBQ

The Chinese TBQ was translated by Chin et al[22] from the English TBQ developed by Tran et al[23]. The total TBQ score ranges from 0-150 points and comprises 15 items across four domains: Medication, medical visits and follow-up, medical-related behaviors and lifestyle, and health problems[23]. Each item is rated from 0 to 10, and higher scores indicate greater treatment burden. The Chinese TBQ has already demonstrated good reliability and validity[24]. In previous validation, the overall Cronbach’s α was 0.884[25]; in our study, the Cronbach’s α was 0.950.

Statistical analysis

Data was collected through an online questionnaire platform. All items were set as mandatory, so the obtained dataset was complete with no missing data. Statistical analysis was completed entirely using SPSS 27.0 software. Continuous variables were expressed as mean ± SD, and categorical variables were expressed as n (%). Independent sample t-tests or one-way analysis of variance were used to examine the differences in IBDQ scores between different demographic and clinical subgroups. The bivariate relationship between treatment burden, sleep quality, and QoL was evaluated through Spearman correlation analysis. Subsequently, multiple linear regression was carried out to determine the factors that are independently associated with QoL.

Through Spearman’s rank correlation analysis, the bivariate relationships between key variables such as QoL (IBDQ), sleep quality (PSQI), and treatment burden (TBQ), were preliminarily explored. On this basis, in order to identify the predictive factors independently related to the QoL, we constructed a multiple linear regression model that included variables that had a significant association (P < 0.05) with the total IBDQ score in univariate analysis. All statistical tests were two-sided, and a P value < 0.05 was defined as indicative of a statistically significant result.

RESULTS

Characteristics of participants

A total of 168 questionnaires were distributed in this study, and 158 of them were fully retrieved (94.05%). Participants (n = 158) were predominantly 60 years or younger (76.6%), a slight majority (58.9%) were male, and a majority had UC (89.2%) or CD (10.8%). The number of hospitalizations in the past year was a significant factor of influence over QoL for patients with IBD (P < 0.05). Other demographic and clinical characteristics, such as disease type, gender, age, and income, showed no association with QoL (all P > 0.05; Table 1).

Table 1 Demographic, clinical characteristics and Inflammatory Bowel Disease Questionnaire scores of participants (n = 158).

Variables	n (%)	mean ± SD	F/t	P value
Disease type			t = -0.814	0.417
UC	141 (89.2)	174.74 ± 33.59
CD	17 (10.8)	181.65 ± 27.94
Gender			t = -0.448	0.655
Male	93 (58.9)	174.49 ± 33.81
Female	65 (41.1)	176.89 ± 32.06
Age (years)			F = 0.294	0.746
< 40	57 (36.1)	173.02 ± 37.48
41-60	64 (40.5)	176.09 ± 28.82
> 60	37 (23.4)	178.22 ± 33.13
Education			F = 0.527	0.591
Junior high or below	40 (25.3)	178.35 ± 24.86
High school or technical secondary school	45 (28.5)	177.64 ± 35.90
College or above	73 (46.2)	172.58 ± 35.20
Marital status			F = 0.208	0.812
Married	129 (81.6)	174.72 ± 31.73
Unmarried	25 (15.8)	178.32 ± 40.38
Divorced	4 (2.5)	182.25 ± 30.19
Employment status			F = 0.655	0.581
Employed	108 (68.4)	177.43 ± 30.78
Unemployed	7 (4.4)	172.86 ± 20.64
Retired	35 (22.2)	173.14 ± 33.57
Student	8 (5.1)	161.75 ± 61.84
Household monthly income (RMB)			F = 0.581	0.561
< 3000	50 (31.6)	171.92 ± 36.95
3000-5000	57 (36.1)	175.44 ± 30.82
> 5000	51 (32.3)	179.02 ± 31.57
Personal monthly income (RMB)			F = 0.054	0.947
< 3000	28 (17.7)	174 ± 35.75
3000-5000	39 (24.7)	174.9 ± 29.97
> 5000	91 (57.6)	176.19 ± 33.73
Medical payment			F = 0.966	0.428
Self-paying	9 (5.7)	186.00 ± 35.03
Rural cooperative medical	26 (16.5)	178.58 ± 28.58
Urban resident medical insurance	29 (18.4)	169.28 ± 41.43
Urban employee medical insurance	91 (57.6)	174.73 ± 31.37
Other	3 (1.9)	200.00 ± 7.94
Family history of IBD			t = -0.427	0.670
Yes	4 (2.5)	168.50 ± 45.17
No	154 (97.5)	175.66 ± 32.83
Surgery history			t = -1.360	0.176
Yes	11 (7.0)	162.45 ± 29.18
No	147 (93.0)	176.46 ± 33.17
Hospitalizations past 1 year			F = 5.654	0.004
0	82 (51.9)	183.26 ± 27.40
1	47 (29.7)	170.38 ± 36.82
≥ 2	29 (18.4)	161.76 ± 36.05

t: Independent t-test; F: One-way ANOVA; IBD: Inflammatory bowel disease; UC: Ulcerative colitis; CD: Crohn’s disease.

Key scores in IBD patients

The mean ± SD of patients’ scores on key study variables are presented in Table 2. According to the PSQI cutoff, 61.39% (n = 97) of the participants were identified as having poor sleep quality (total PSQI score > 5).

Table 2 Levels of study variables.

Variables	mean ± SD
QoL	175.48 ± 33.02
Bowel symptoms	57.70 ± 10.71
Systemic symptoms	25.15 ± 5.54
Emotional function	64.90 ± 12.18
Social function	27.73 ± 7.41
Sleep	7.15 ± 4.22
Subjective sleep quality	1.15 ± 0.82
Sleep latency	1.34 ± 0.98
Sleep duration	1.11 ± 0.91
Habitual sleep efficiency	0.77 ± 1.05
Sleep disturbances	1.29 ± 0.58
Use of sleeping medication	0.43 ± 0.95
Daytime dysfunction	1.06 ± 1.00
Treatment burden	39.81 ± 30.54
Medication burden	8.05 ± 8.26
Medical visits and follow-up	13.79 ± 11.53
Medical-related behaviors and lifestyle	15.49 ± 11.42
Health problems	2.47 ± 2.56

QoL: Quality of life.

Correlations of study variables

Spearman correlation analysis revealed significant negative correlations between QoL and both sleep quality (r = -0.415, P < 0.01) and treatment burden (r = -0.430, P < 0.01). Additionally, sleep was also positively correlated with treatment burden (r = 0.188, P < 0.05). Detailed correlations are shown in Table 3.

Table 3 Spearman correlations among key variables.

Variables	QoL	Sleep	Treatment burden
QoL	1
Sleep	-0.415b	1
Treatment burden	-0.430b	0.188a	1

^aP < 0.05.

^bP < 0.01.

QoL: Quality of life.

Multiple linear regression analysis of factors associated with QoL

Multiple linear regression analysis revealed that sleep quality (β = -0.286, P < 0.001), treatment burden (β = -0.287, P < 0.001), and number of hospitalizations in the past year (β = -0.162, P = 0.025) were all predictors of QoL, collectively explaining 25.4% of the variance in the QoL scores (R² = 0.254, adjusted R² = 0.239, F = 17.436, P < 0.001). The variance inflation factor for all predictors ranged from 1.02 to 1.41 (all < 10), and tolerance values were all > 0.10, indicating the absence of multicollinearity. The results of this analysis are shown in Table 4.

Table 4 Multiple linear regression predicting Inflammatory Bowel Disease Questionnaire total score.

Predictors	B (95%CI)	β	t	P value	Tolerance	Variance inflation factor
Constant	207.472 (197.392, 217.551)		40.663	< 0.001
Sleep	-2.239 (-3.358 to -1.120)	-0.286	-3.953	< 0.001	0.927	1.079
Treatment burden	-0.310 (-0.462 to -0.158)	-0.287	-4.027	< 0.001	0.956	1.046
Hospitalizations past year	-4.449 (-8.330 to -0.568)	-0.162	-2.264	0.025	0.944	1.059

R² = 0.254, adjusted R² = 0.239, F = 17.436, P < 0.001.

CI: Confidence interval.

DISCUSSION

This study used the CCM to determine the most important variables associated with the QoL in Chinese patients with IBD. The proportion of participants who reported poor QoL was 34.81%, which closely aligned with the 37.7% observed in earlier Chinese studies[26]. Our findings also fit well with the CCM. Sleep quality, treatment burden, and recent hospital stays were the main factors that affect QoL, and together explained 25.4% of the differences in QoL scores. These findings suggest that IBD management needs to shift from focusing on clinical and endoscopic results to also considering the daily realities of living with the disease. Importantly, our study translates the STRIDE-II concept of improving QoL from a consensus statement into a practical clinical tool, demonstrating that sleep quality and treatment burden can be specific, modifiable targets for achieving this long-term goal.

Another key finding here is that nearly 70% of patients had poor sleep, and this was a major factor in lower QoL scores (β = -0.286, P < 0.001). This result is highly consistent with current research that shows that sleep disturbances are prevalent among patients with IBD and are closely associated with deteriorating physical and psychological well-being[27,28]. In the CCM model, sleep is an essential resource that contributes to building one’s “capacity” for managing illness. In patients with IBD, such capacity can be exhausted through a “vicious cycle”. Nocturnal symptoms of pain and urgency, inflammation that disrupts the sleep cycle, and steroid side-effects all combine to destroy sleep[14,27]. Our findings highlight how critical sleep is for patients; those who do not have sufficient quality sleep often lack enough physical or psychological resources for coping with day-to-day life in relation to their disease. This ultimately affects their social and emotional health. Therefore, future interventional research should move beyond routine sleep assessments and explore whether nonpharmaceutical interventions such as cognitive behavioral therapy for insomnia can effectively rebuild patient capacity.

In agreement with our initial hypothesis, treatment burden had a high impact on QoL (β = -0.287, P < 0.001) which in the context of CCM is considered to be the “workload” to be managed by the patient. This aligns with recent studies that indicate that the logistical and emotional demands of IBD treatments independently decrease patient well-being[29]. The average score obtained from our subjects using the TBQ questionnaire was 39.81 points, indicating an extremely heavy workload. Multiple factors increase this burden, including the need to travel far away to reach centers where specific treatments can be administered and the need for frequent visits due to the nature of some biologicals. These findings suggest that the “work of being a patient” is often overwhelming and that tasks such as booking appointments or keeping track of numerous different pills and having to undergo medical tests may all have an impact on well-being that is at least as damaging as the disease symptoms themselves[11,12]. In order to help with this, healthcare providers and hospital administrators should strive to make treatment regimens as simple as possible. For instance, future research could investigate whether same-day diagnostic tests, home-administered subcutaneous biologics, or digital health navigation can effectively ease daily patient burdens.

Frequent hospital stays were linked to lower QoL (β = -0.162, P = 0.025), and this result corroborates previous findings that inpatient admissions contribute heavily to physical and psychological distress[30]. Hospitalization is not only a proxy for a severe disease exacerbation and therapeutic failure but also an acute and massive spike of patient work load. Similar to prior cohorts, our results suggest that hospital stays arrive suddenly and put an immediate stop to patients’ work, social life, and family duties. In many occasions they are also quite a financial hardship. This finding supports the clinical need for durable remission and for performing proactive, community based, or outpatient care to avoid inpatient admission if at all possible.

Despite these strong findings, some limitations of this study must be acknowledged. First, although there was a 25.4% explanation of variance, future work would benefit from exploring additional potential drivers for QoL, such as mental health, support networks, specific dietary constraints, and clinical parameters (e.g., disease severity and drug therapies) that may specifically interact with sleep quality. Second, we sampled from only one tertiary hospital, which limits the generalizability of our results to those who are treated in similar primary care clinics. Third, the sample was highly imbalanced regarding disease type (89.2% UC vs 10.8% CD) and therefore may not be fully generalizable to all IBD patients. Fourth, our study was cross-sectional, so we cannot make causal claims about any of the associations between sleep, burden, and QoL.

CONCLUSION

Treatment burden, sleep quality, and recent hospitalization are important, modifiable variables that are each significantly associated with the QoL of Chinese IBD patients, primarily those with UC. Using the CCM, this research shows how the misalignment of treatment work with the personal resources reduces QoL in this specific, single-center patient population. A change in clinical practice is needed, one that moves the focus of care away from the management of the symptoms only. Gastroenterologists and multidisciplinary care teams should urgently put in place routine sleep screening in outpatient visits. Furthermore, our findings provide a strong rationale for future longitudinal and interventional studies to test whether systemic burden-relief strategies such as streamlining care, consolidating clinical visits, and instituting digital health plans can effectively help patients recover their capacity for dealing with IBD and ultimately optimize QoL.