Abstract
Background
Individuals with ulcerative colitis (UC) seek complementary treatment methods, including diet and physical activity, to manage the burden of living with UC. This study examined associations between diet-associated inflammation, physical activity (PA), and UC-related health outcomes.
Methods
Data were obtained from 2052 IBD Partners e-cohort participants with UC. To quantify the inflammatory potential of food intake, dietary data were converted into Dietary Inflammatory Index (DII) and energy adjusted (E-DII) scores. Physical activity data were collected using the Godin-Shephard Leisure Time Activity Index. Outcome variables included the Simple Clinical Colitis Activity Index, Short Inflammatory Bowel Disease Questionnaire, and psychosocial PROMIS domains.
Results
Higher E-DII scores, as indicator of increased dietary inflammatory potential, were associated with increased disease activity (β = 0.166; P < .001), anxiety (β = 0.342; P = .006), depression (β = 0.408; P = .004), fatigue (β = 0.386; P = .005), sleep disturbance (β = 0.339; P = .003), and decreased social satisfaction (β = -0.370; P = .004) and quality of life (β = −0.056; P < .001). Physical activity was inversely associated with disease activity (β = −0.108; P < .001), anxiety (β = −0.025; P = .001), depression (β = −0.025; P = .001), fatigue (β = −0.058; P < .001), and sleep disturbance (β = −0.019; P = .008), while positively associated with social satisfaction (β = 0.063; P < .001) and quality of life (β = 0.005; P < .001). Beneficial effects were generally greater for strenuous PA intensity.
Conclusions
An anti-inflammatory diet and increased PA are associated with decreased disease activity, anxiety symptoms, depression symptoms, and fatigue, and associated with improved quality of life, sleep, and social satisfaction for patients with UC. Such modalities may reduce the daily burden of illness and aid in managing systemic and localized inflammation associated with UC.
Keywords: ulcerative colitis, diet, inflammation, dietary inflammatory index, physical activity
Key Messages.
What is already known?
Individuals living with ulcerative colitis experience a significant physical and psychosocial burden of illness, yet evidence for the influence of diet and physical activity on reducing the burden of living with ulcerative colitis is limited.
What is new here?
Our study, consisting of 2052 patients with UC, employed a state-of-the-art method to compute energy-adjusted dietary inflammatory index scores and revealed that an anti-inflammatory diet and increased physical activity are associated with a lower burden of illness.
How can this study help patient care?
Findings may inform clinicians’ recommendations for patient self-management, and continued research in this area will contribute to creating evidence-based dietary and physical activity guidelines for UC treatment.
Introduction
Ulcerative colitis (UC) is an inflammatory bowel disease (IBD) characterized by chronic inflammation and ulcerations in the colon’s mucosal lining due to abnormal inflammatory and immune system response.1 Though most UC cases are currently diagnosed in Western nations, in part reflecting reporting bias, IBD is becoming a global health issue, with incidence rising across the world.2
Individuals with UC experience lifelong unpredictable fluctuations between periods of disease remission and exacerbations of disease activity with varying degrees of severity.1 Disease activity generates physical symptoms such as abdominal pain, rectal bleeding, bowel urgency, bowel frequency, diarrhea, and fatigue, along with various extraintestinal manifestations of disease, which interfere with maintaining normal daily activities.3 Regardless of disease activity, most individuals with UC report decreased work productivity, increased symptoms of anxiety and depression, isolation, strained relationships, “brain fog,” poor sleep quality, and negative body image.3 Ulcerative colitis has been found to influence an individual’s career and family planning choices, as well as social engagement.3
Although some medications can provide temporary relief from disease activity, many patients report that pharmaceutical agents are insufficient to induce or maintain remission and overcome the burden of UC in everyday life.3 Additionally, the cost of medication is a key driver of health care spending on UC.4 Many individuals living with UC seek information on behavioral health methods (eg, diet, physical activity) as complementary treatments to reduce symptoms, avoid medication side effects, achieve disease remission, reduce the burden of illness on the activities of everyday life, and improve overall quality of life.3,5
Despite limited evidence to support specific dietary approaches for the management of UC, dietary change is a widespread self-management method among UC patients.6 Popular diets currently recommended for UC include the specific carbohydrate diet,7 low-FODMAP diet,8 and low-fiber diets.9 Low-fiber and exclusion diets tend to be strongly pro-inflammatory,9 which may tend to exacerbate and amplify symptoms over time.
The Dietary Inflammatory Index (DII) is a scoring algorithm that can be used with any dietary assessment to quantify the inflammatory potential of individuals’ food intake.10 Outside of a study showing that a pro-inflammatory diet was a risk factor for developing UC11 and another producing results suggesting that reducing dietary inflammation can reduce disease activity,12 the DII has never been studied in a large UC population.
Physical activity is used by UC patients attempting to reduce and manage the physical and psychosocial burden of illness. Physical activity is known to reduce stress and depression, regulate systemic inflammation, reduce the risk of comorbidities, improve social relationships, and demonstrate quality of life benefits in the general population.13 Existing studies on physical activity and IBD suggest that although patients struggle with motivation to exercise during periods of active disease, physical activity is associated with improvements in quality of life, fatigue, and mental health and may improve the disease course of UC.14
This research examines associations between diet-related inflammation, as indicated by the Dietary Inflammatory Index and energy adjusted (E-DII) scores, physical activity at varying intensities, and both physical and psychosocial health outcomes associated with the burden of living with UC.
Materials and Methods
The IBD Partners e-cohort provides the basis for analyses conducted to test associations between diet-associated inflammation, physical activity, and UC. IBD Partners, previously named the Crohn’s and Colitis Foundation of America (CCFA) Partners, is a longitudinal internet-based cohort of IBD patients that serves as a resource for IBD-related research.15 Data obtained in 2011 from participants in the IBD Partners e-cohort were analyzed using a cross-sectional design to examine associations between the inflammatory capacity of individuals’ diets, physical activity, and UC-related health outcomes. For this study, survey data from participants 18 years and older years who self-reported a diagnosis of UC but had not undergone UC-related surgery were included. Human subject approval was granted by the University of South Carolina’s Institutional Review Board (IRB).
Variables of Interest
The following variables were extracted from validated measures administered within the IBD Partners survey.
Outcome variables
Disease activity was reported using the Simple Clinical Colitis Activity Index (SCCAI),16 a validated self-report measure that rates bowel frequency during day and night, bowel urgency, rectal bleeding, general well-being, and extracolonic manifestations. Remission in UC is associated with a SCCAI score <2; clinical relapse is defined by a SCCAI score ≥5.16
Disease-related quality of life was measured using the Short Inflammatory Bowel Disease Questionnaire (SIBDQ), a 10-item questionnaire used to assess disease-related quality of life among individuals with IBD across 4 domains (ie, bowel, emotional, systemic, and social) for a summed quality of life score relative to the 2 weeks prior to self-report.17
We also evaluated patient-reported outcome domains. The National Institutes of Health Patient Reported Outcome Measurement Information System (PROMIS) is a systematic measure of patient-reported physical, mental, and social well-being with high reliability.18 Various domains of well-being were measured using validated item banks, or groupings of questionnaire items that reflect the construct of interest. IBD Partners administered short-form PROMIS item banks to measure 5 individual constructs of health-related quality of life relevant to IBD: anxiety symptoms, depression symptoms, fatigue, sleep disturbance, and satisfaction with social role. High scores for fatigue, anxiety, depression, and sleep disturbance represent poor health, whereas high scores for social function represent good health.19
Predictor variables
We used the Dietary Inflammatory Index (DII) score and the Energy-Adjusted DII (E-DII) score. Dietary data were collected using a National Health and Nutrition Examination Survey (NHANES) Dietary Screener Questionnaire20 that served as a basis to compute both the DII score and the Energy-Adjusted DII (E-DII) score.10,21 The DII was developed based on an extensive literature search to quantify the effect of diet on inflammation using an algorithm that considers up to 45 food parameters identified in the search, including a combination of nutrients and food intake.11 Due to unique differences observed in the relationship between total energy intake (a determinant of the DII) and nutrient intake, the E-DII also was developed.21 The DII scores can range from a theoretical minimum −8.87, indicating a strongly anti-inflammatory intake, to a theoretical maximum +7.98, indicating a strongly pro-inflammatory intake.22 The DII and E-DII are scored similarly and scaled identically; so, the scores are comparable across studies.21 At least 41 studies have demonstrated construct validity of the DII or E-DII against inflammatory biomarkers in different populations under varying conditions.23
Physical activity data were collected using the Godin-Shephard Leisure Time Physical Activity Questionnaire, which measures self-reported leisure-time physical activity amongst healthy adults and has been validated to assess exercise behavior in different populations, with significant correlation to VO2max and percent body fat.24 Participants indicated the number of times during a 7-day period the participant engaged in varying intensities of physical activity (mild, moderate, and strenuous) for at least 15 minutes. In addition to Total Leisure Time Activity, frequencies of engaging in physical activity at each intensity were tested as continuous variables.
Covariates included age, sex, body mass index (BMI, weight [kg]/height[m]2), race, education, smoking status, disease duration, medication class, and presence of conditions limiting participation in physical activity. Age (in years) was indicated by a numeric value. Sex was classified as either male or female. Body mass index (kg/m2) was calculated from participant-reported height and weight. Given that 84% of participants indicated race as “white,” a dummy variable for race was created (“white” or “not white”). Education was categorized as “high school or less,” “some college,” “college,” and “graduate school.” Smoking status was denoted as “never,” “ever,” or “current.” Disease duration was classified as number of years since first IBD diagnosis. Participants reported “yes” or “no” to indicate current use of various listed medications and treatment methods. For this analysis, medications and treatment methods were grouped into medication classes (see Table 1). Participants also reported “yes” or “no” to indicate the general presence of other conditions unrelated to IBD that could limit participation in physical activity (eg, pregnancy, injury).
Table 1.
Characteristics of participantsa with ulcerative colitis and mean scores for independent and dependent variables from IBD Partner’s 2011 e-cohort data (n = 2052).
| Mean (SD) or % | |
|---|---|
| Age (years) | 43.82 (14.41) |
| Sex % female | 71.39 |
| Race % white | 84.35 |
| Disease Duration (years) | 11.75 (10.61) |
| BMI (kg/m2) | 25.56 (5.91) |
| Education % | |
| HS or Less | 7.4 |
| Some College | 18.17 |
| College | 40.74 |
| Graduate School | 29.09 |
| Never smokers, % | 63.59 |
| Current smokers, % | 4.3 |
| Prior smokers % | 32.06 |
| Conditions limiting physical activity %yes | 9.9 |
| Medication/Treatment Class b | |
| Corticosteroids | 17.1 |
| Aminosalicylates | 73.4 |
| Immunomodulator | 25.4 |
| Biologics | 17.3 |
| Antibiotics | 2.2 |
| Complimentary/Alternative | 30.5 |
| Opioids | 4.68 |
| DII score | 2.279 (1.28) |
| E-DII score | −0.251 (1.68) |
| Leisure Time Physical Activity | 33.16 (26.98) |
| Strenuousc | 1.39 (1.91) |
| Moderate | 2.36 (2.79) |
| Mild | 3.02 (3.24) |
| SCCAI | 3.34 (2.77) |
| SIBDQ | 4.96 (1.14) |
| Anxiety | 53.39 (9.4) |
| Depression | 51.37 (9.3) |
| Fatigue | 53.89 (10.53) |
| Sleep Disturbance | 51.35 (8.29) |
| Satisfaction with Social Role | 49.05 (9.5) |
aRespondents who had undergone UC-related surgery were excluded.
bRespondents were allowed to report current use of any or all medications/treatments. Concurrent use of multiple medications is evident as total percent currently using medication/treatments is 170.58%.
cFrequency scores indicate the number of times in the last 7 days an individual participated in at least 15 minutes of physical activity at the associated intensity.
Statistical Analysis
Simple descriptive statistics were computed for all covariates. Associations between DII/E-DII scores and health outcomes were tested using multivariable linear regression. Disease activity, quality of life, and PROMIS domains were each predicted by a vector of covariates (age, sex, BMI, race, education, smoking status, disease duration, medication class, and physical activity) and DII/E-DII score. Models were assessed for multicollinearity using variance inflation factors (VIF) and tested for explanatory power robustness (R2) when using the E-DII score vs DII scores. The E-DII score was selected for preferred specifications given the variable’s greater explanatory ability, as well as lower skewness and improved distributional characteristics in comparing scores. The E-DII scores were analyzed as continuous variables and categorized into quartiles, with subsequent analyses to test linear trends across quartiles.
Associations between physical activity and health outcomes also were tested using multivariable linear regression. Again, disease activity, quality of life, and patient reported outcomes were each predicted by a set of covariates (age, sex, BMI, race, education, smoking status, medication class, disease duration, E-DII score, and presence of conditions limiting participation in physical activity), and physical activity. Physical activity was analyzed against each health outcome and modeled in 2 ways—first, as a total leisure-time activity score, and second, as intensity levels (ie, moderate and strenuous intensity relative to light intensity).
Results
Participant Characteristics
Data were collected from a total of 2368 patients with UC. After excluding patients who had undergone UC-related surgery, data from 2052 respondents were included. Participant characteristics are described in Table 1, along with mean scores for each independent and dependent variable.
Diet-related Inflammation
The DII scores ranged from −2.94 to 4.48 (mean, 2.28; median, 2.59). The E-DII scores ranged from −4.13 to 4.47 (mean, −0.25; median, −0.41). As shown in Table 2, an increase of 1 point in E-DII score (indicating increased pro-inflammatory dietary intake potential) was significantly associated with increased SCCAI scores (0.17; 95% CI, 0.97-0.24; P < .001; t = 4.71), anxiety symptoms (0.34; 95% CI, 0.096-0.59; P = .006; t = 2.73), depression symptoms (0.41; 95% CI, 0.17-0.65; P = .001; t = 3.32), fatigue (0.39; 95% CI, 0.12-0.66; P = .005; t = 2.82), and sleep disturbance (0.34; 95% CI, 0.12-0.56; P = .003; t = 2.99). An increase of 1 point in E-DII score was associated with decreased satisfaction with social role (−0.37; 95% CI, −0.62 to −0.12; P = .004; t = −2.92) and SIBDQ scores (−0.06; 95% CI, −0.08 to −0.03; P < .001; t = −3.87; Table 2). Quartile analysis indicated a robust distribution and linear trends across quartiles (Table 3).
Table 2.
Comparison between dietary inflammatory index and energy-adjusted dietary inflammatory index scores’ associations with UC-related health outcomes from IBD Partners 2011 e-cohort.a
| Associations between Dietary Inflammatory Index Scores and UC-Related Health Outcomes | |||||
|---|---|---|---|---|---|
| Coef. | 95% CI | P | R2 | Adj. R2 | |
| SCCAI | 0.15 | 0.06-0.24 | .001 | 0.195 | 0.183 |
| SIBDQ | −0.05 | −0.09 to −0.01 | .008 | 0.208 | 0.196 |
| Anxiety | 0.14 | −0.18-0.46 | .40 | 0.092 | 0.079 |
| Depression | 0.16 | −0.16-0.47 | .33 | 0.091 | 0.078 |
| Fatigue | 0.32 | −0.03-0.67 | .08 | 0.148 | 0.136 |
| Sleep Disturbance | 0.35 | 0.058-0.63 | .02 | 0.082 | 0.068 |
| Satisfaction w/Social Role | −0.39 | −0.71 to −0.07 | .02 | 0.119 | 0.106 |
| Associations between Energy-Adjusted Dietary Inflammatory Index Scores and UC-Related Health Outcomes | |||||
|---|---|---|---|---|---|
| SCCAI | 0.17 | 0.097-0.24 | <.001 | 0.200 | 0.188 |
| SIBDQ | -0.06 | −0.08 to −0.03 | <.001 | 0.211 | 0.199 |
| Anxiety | 0.34 | 0.096-0.59 | .006 | 0.095 | 0.082 |
| Depression | 0.41 | 0.17-0.65 | .001 | 0.095 | 0.082 |
| Fatigue | 0.39 | 0.12-0.66 | .005 | 0.151 | 0.138 |
| Sleep Disturbance | 0.34 | 0.12-0.56 | .003 | 0.084 | 0.070 |
| Satisfaction w/Social Role | −0.37 | −0.62 to −0.12 | .004 | 0.120 | 0.107 |
aSpecifications include age, sex, BMI, race, education, smoking status, medication class, disease duration, and physical activity.
Table 3.
Associations between energy-djusted dietary inflammatory index (E-DII) quartilesa and UC-related health outcomes from IBD Partners 2011 e-cohort.
| Quartilesa | Coef. | 95% CI | P≥|t| | R2 | Adj. R2 | |
|---|---|---|---|---|---|---|
| SCCAI | E-DII Quart2 | 0.07 | −0.24-0.39 | 0.64 | 0.201 | 0.189 |
| E-DII Quart3 | 0.38 | 0.06-0.70 | 0.02 | |||
| E-DII Quart4 | 0.73 | 0.4-1.06 | <0.001 | |||
| SIBDQ | E-DII Quart2 | −0.02 | −0.15-0.11 | 0.73 | 0.211 | 0.199 |
| E-DII Quart3 | −0.10 | −0.23-0.03 | 0.14 | |||
| E-DII Quart4 | −0.26 | −0.39 to −0.12 | <0.001 | |||
| Anxiety | E-DII Quart2 | −0.01 | −1.12-1.1 | 0.99 | 0.096 | 0.082 |
| E-DII Quart3 | 0.63 | −0.51-1.8 | 0.28 | |||
| E-DII Quart4 | 1.56 | 0.40, 2.73 | <0.01 | |||
| Depression | E-DII Quart2 | 0.46 | −0.64-1.55 | 0.41 | 0.095 | 0.081 |
| E-DII Quart3 | 0.59 | −0.53-1.71 | 0.30 | |||
| E-DII Quart4 | 1.80 | −0.11 to −0.05 | <0.01 | |||
| Fatigue | E-DII Quart2 | −0.22 | −1.44-0.996 | 0.72 | 0.151 | 0.137 |
| E-DII Quart3 | 0.27 | −0.97-1.52 | 0.67 | |||
| E-DII Quart4 | 1.54 | 0.26-2.81 | 0.02 | |||
| Sleep Disturbance | E-DII Quart2 | −0.11 | −1.12-0.89 | 0.82 | 0.084 | 0.070 |
| E-DII Quart3 | 0.20 | −0.82-1.12 | 0.70 | |||
| E-DII Quart4 | 1.40 | 0.35-2.46 | <0.01 | |||
| Satisfaction with Social Role | E-DII Quart2 | 1.09 | −0.030, 2.21 | 0.06 | 0.124 | 0.110 |
| E-DII Quart3 | 0.54 | −0.61-1.69 | 0.36 | |||
| E-DII Quart4 | −1.25 | −2.38 to −0.25 | 0.05 |
aSpecifications include age, sex, BMI, race, education, smoking status, medication class, disease duration, and physical activity. Energy-adjusted dietary inflammatory index quartiles calculated from IBD Partners e-cohort 2011 dietary data. Values for E-DII across quartiles: Quartile 1 = −4.13 to -1.46, Quartile 2 = −1.46 to -0.35, Quartile 3 = −0.35 to 0.96, Quartile 4 = 0.96 to 4.47.
Physical Activity
As shown in Table 4, total leisure time activity was inversely associated with disease activity (−0.01; 95% CI, −0.15 to −0.01; P < .001; t = −4.71), anxiety symptoms (−0.03; 95% CI, −0.04 to −0.01; P = .001; t = −3.29), depression symptoms (−0.03; 95% CI, −0.04 to −0.01; P = .001; t = −3.23), fatigue (−0.06; 95% CI, −0.08 to −0.04; P < .001; t = −6.74), and sleep disturbance (−0.02; 95% CI, −0.03 to −0.01; P = .008; t = −2.67), while being positively associated with IBD-related quality of life (0.01; 95% CI, 0.003-0.01; P < .001; t = 5.33) and satisfaction with social role (0.06; 95% CI, 0.07-0.08; P < .001; t = 7.94). When comparing frequency of physical activity at mild, moderate, and strenuous intensity levels, the strongest associations existed between strenuous intensities of physical activity and each health outcome (though associations were insignificant for depression symptoms; Table 4).
Table 4.
Associations between total leisure time exercise activity, frequencies of intensity, and UC-related health outcomes from IBD Partners 2011 e-cohort.a
| SCCAI | Coef. | 95% CI | P≥|t| | R2 | Adj. R2 |
|---|---|---|---|---|---|
| Leisure Time Activity | −0.01 | −0.15 to −0.01 | <0.001 | 0.208 | 0.195 |
| Strenuous | −0.14 | −0.20 to −0.07 | <0.001 | 0.212 | 0.199 |
| Moderate | −0.08 | −0.13 to −0.03 | <0.01 | 0.212 | 0.199 |
| SIBDQ | |||||
| Leisure Time Activity | 0.01 | 0.003-0.01 | <0.001 | 0.221 | 0.209 |
| Strenuous | 0.06 | 0.03-0.08 | <0.001 | 0.227 | 0.213 |
| Moderate | 0.04 | 0.018-0.06 | <0.001 | 0.227 | 0.213 |
| Anxiety | |||||
| Leisure Time Activity | −0.03 | −0.04 to −0.01 | <0.01 | 0.109 | 0.096 |
| Strenuous | −0.39 | −0.62 to −0.16 | <0.01 | 0.112 | 0.097 |
| Moderate | −0.09 | −0.24-0.05 | 0.21 | 0.112 | 0.097 |
| Depression | |||||
| Leisure Time Activity | −0.03 | −0.040 to −0.01 | <0.01 | 0.108 | 0.094 |
| Strenuous | −0.20 | −0.43 to −0.02 | 0.08 | 0.109 | 0.095 |
| Moderate | −0.16 | −0.30 to −0.02 | 0.03 | 0.109 | 0.095 |
| Fatigue | |||||
| Leisure Time Activity | −0.06 | −0.08 to −0.04 | <0.001 | 0.166 | 0.153 |
| Strenuous | −0.82 | -1.06 to −0.57 | <0.001 | 0.173 | 0.160 |
| Moderate | −0.28 | −0.44 to −0.12 | <0.01 | 0.173 | 0.160 |
| Sleep Disturbance | |||||
| Leisure Time Activity | −0.02 | −0.03 to −0.01 | <0.01 | 0.090 | 0.075 |
| Strenuous | −0.32 | −0.52 to −0.11 | <0.01 | 0.094 | 0.079 |
| Moderate | −0.06 | −0.22-0.097 | 0.45 | 0.094 | 0.079 |
| Satisfaction w/Social Role | |||||
| Leisure Time Activity | 0.06 | 0.07-0.08 | <0.001 | 0.134 | 0.120 |
| Strenuous | 0.73 | 0.50-0.96 | <0.001 | 0.140 | 0.125 |
| Moderate | 0.40 | 0.23-0.58 | <0.001 | 0.140 | 0.125 |
aSpecifications include age, sex, BMI, race, education, smoking status, medication class, disease duration, E-DII score, and presence of conditions limiting participation in physical activity.
Interaction Effects
No significant interaction (P < .05) was observed between diet and physical activity across any of the outcomes except for fatigue (P = .03). Although diet and physical activity are understood to be correlated and have the potential to interact in their effect on health, the way they statistically impact UC-related health outcomes appears to be independent of each other in the context of this analysis (ie, each exerts an independent effect after accounting for the effect of the other).
Discussion
These findings suggest that an anti-inflammatory diet and increased physical activity are associated with a lower burden of illness associated with UC. Significant associations were found between increases in E-DII scores (ie, indicating pro-inflammatory dietary potential) and increases in disease activity, anxiety symptoms, depression symptoms, fatigue, and sleep disturbance, along with decreases in satisfaction with social role and health-related quality of life. Higher total leisure time physical activity was associated with higher IBD-related quality of life and satisfaction with social role, along with lower disease activity, anxiety and depression symptoms, fatigue, and sleep disturbance. As a corollary, these results suggest that an anti-inflammatory diet and increased physical activity may each decrease disease activity, anxiety, depression, and fatigue, as well as improve disease-related quality of life, sleep, and satisfaction with social role.
To put results into a clinically meaningful context, for disease activity, a 1-point change in SCCAI score is considered clinically significant. According to findings from this study, a patient with UC would need an approximate 6-point increase in E-DII score to achieve a 1-point change in SCCAI score for disease activity. The DII and E-DII scores in this study ranged about 7.5 and 8.6 points, respectively. Though a range of this magnitude is what we typically observe, the full range is approximately 17 points (from a maximally pro-inflammatory diet score of +7.98 to a maximally anti-inflammatory diet score of −8.87).10 Based on prior studies with the E-DII, a 6-point change in E-DII score is feasible and realistic for an individual to make.23
Our results suggest the adoption of an anti-inflammatory diet may be an effective approach to mitigating disease activity. This dietary approach differs from currently recommended diets, which tend to focus solely on the short-term goal of reducing roughage (fiber) that passes through the colon and easing the GI symptoms associated with UC such as diarrhea, bloating, and gassiness, through restriction of various types of fruits, vegetables, and processed foods. Attention to the inflammatory potential of diet broadens the understanding of diet’s influence on UC beyond immediate colonic symptoms. In this regard, it is crucially important to keep in mind that a diet with low inflammatory potential exerts its anti-inflammatory effect over a prolonged period.25 The adoption of an anti-inflammatory diet among patients with UC could improve immune system functioning, reduce chronic systemic and tissue-specific simmering inflammation, and improve overall health-related quality of life.
A weakness of current recommended diets is the lack of evidence that they decrease inflammation, which is essential for mucosal healing within the colon. The DII/E-DII is a literature-derived index developed to measure the inflammatory potential of diet and has been found to predict multiple inflammatory biomarkers, such as C-reactive protein, Interleukin-4, 6, 8, and 10, antitumor necrosis factor (TNF)-α, and calprotectin, among others.26 Given the established associations between the DII/E-DII and inflammatory biomarkers (ie, >40 construct validation studies), along with the results of this study, there is evidence suggesting that an anti-inflammatory diet may aid in managing systemic and localized chronic “simmering”25 inflammation associated with UC and reduce the burden of UC on daily living. Results of this study are consistent with existing findings that indicate an anti-inflammatory diet is associated with decreased anxiety, depression, and risk of colon cancer, among other health outcomes.25 Before making firm dietary recommendations, additional research is needed to examine the clinical impact of anti-inflammatory dietary intake on the course of UC.
This study also addresses calls for greater understanding of the frequency, intensity, and type of physical activity best suited for optimal health outcomes among UC patients. Our findings support results of existing studies, indicating that more intense physical activity is preferable. A recent Japanese study examined total physical activity and physical activity intensities against clinical outcomes, finding that strenuous activity and increased total physical activity were each independently associated with improved mucosal healing in patients with UC.27 Such findings are consistent with health-related quality of life benefits associated with all exercise intensities.28 Additional research is needed to develop evidence-based physical activity recommendations for individuals with UC, with attention focused on exercise frequencies and intensities that may best reduce the daily burden of illness.14
Apart from the one significant interaction effect between E-DII and physical activity on fatigue, we found no interaction between DII/E-DII scores and physical activity; yet there is no indication that improving diet and physical activity together would result in unfavorable health outcomes. Numerous studies have indicated the coupled benefits of diet and physical activity on health, energy, vitality, and overall well-being among the general population and in individuals with UC.29
To our knowledge, no other study has examined the associations between UC-related outcomes and both diet and physical activity in such a large cohort. Little research exists using the DII/E-DII among UC patients, and no other research associated with IBD Partners has examined and compared the associations between physical activity, particularly the frequencies of exercise intensities, and UC-related health outcomes. This study’s findings are also accompanied by high R2 values, indicating strong explanatory power of our statistical models.
Despite a large sample size, the utilization of a comprehensive data set with many participant characteristics, innovative use of self-report data, and novelty in applying the E-DII to the UC population, the study has several weaknesses. Its cross-sectional design limits causal inference. For example, the association between total physical activity, particularly strenuous physical activity, and lower disease activity might be explained by a patient’s capacity to engage in exercise. Although patients with UC tend to recognize the benefits of physical activity on well-being, they often face barriers associated with disease activity.14 Research utilizing longitudinal data is needed to better determine the mitigating influence of physical activity on the disease course and related outcomes.
The study’s largely female and white population precluded stratifying analyses by gender or race; therefore gender and race were accounted for as covariates in all models. The limited inclusion of non-white individuals limits generalizability and remains a primary concern for IBD-related research. Although patients with UC often report feeling that their condition is not taken seriously by others,3 this concern is often compounded for African-American women and other minoritized individuals.30 Although statistical models controlled for race as “white” and “non-white,” concerted efforts are still needed to recruit individuals from underrepresented minority groups into IBD-related research.
In addition, all data were collected using self-report measures, subjecting all results to potential reporting biases. Findings are also limited by the type of dietary data derived from the NHANES DSQ to calculate DII scores. The DSQ, administered by IBD Partners, includes data only on frequency of consumption of selected foods and food groups. To compute the DII/E-DII scores, this study converted frequency data using databases of representative portion sizes and detailed nutrient data. Additional studies using a comprehensive dietary assessment method (eg, 24-hour recall with portion sizes) are needed to confirm associations between the DII/E-DII and UC-related health outcomes.
Inflammatory bowel disease research calls for expanded consideration of treatment and management methods for gastrointestinal manifestations of illness, as well as methods to improve emotional, social, and psychological well-being among IBD patients.31 Study findings support future research aimed at expanding models of patient care and self-management programs to include anti-inflammatory dietary intake and physical activity as complementary lifestyle methods that may reduce disease symptoms, maintain remission, and improve psychosocial well-being. These results can inform clinicians’ recommendations for patient self-care, but additional research in this area will contribute to creating evidence-based diet and physical activity health promotion programs for individuals with UC.
Acknowledgments
Use of the Inflammatory Bowel Disease Questionnaire, authored by Dr. Jan Irvine et.al, was made under license from McMaster University, Hamilton, Canada.
Contributor Information
Kelli E DuBois, Prevention Research Center, Arnold School of Public Health, University of South Carolina, Columbia, SC, USA; Department of Health Promotion, Education, and Behavior, Arnold School of Public Health, University of South Carolina, Columbia, SC, USA.
Christine E Blake, Department of Health Promotion, Education, and Behavior, Arnold School of Public Health, University of South Carolina, Columbia, SC, USA.
Caroline Rudisill, Department of Health Promotion, Education, and Behavior, Arnold School of Public Health, University of South Carolina, Columbia, SC, USA.
Sayward E Harrison, Department of Psychology, University of South Carolina, Columbia, SC, USA.
Michael D Wirth, Cancer Prevention and Control Program, Arnold School of Public Health, University of South Carolina, Columbia, SC, USA; Department of Epidemiology and Biostatistics, Arnold School of Public Health, University of South Carolina, Columbia, SC, USA; Department of Nutrition, Connecting Health Innovations, LLC, Columbia, SC, USA; College of Nursing, University of South Carolina, Columbia SC, USA.
James R Hébert, Cancer Prevention and Control Program, Arnold School of Public Health, University of South Carolina, Columbia, SC, USA; Department of Epidemiology and Biostatistics, Arnold School of Public Health, University of South Carolina, Columbia, SC, USA; Department of Nutrition, Connecting Health Innovations, LLC, Columbia, SC, USA.
Funding
This research was supported in part by grants from the Crohn’s & Colitis Foundation and the Patient-Centered Outcomes Research Institute (PCORI). Drs. J.R.H. and M.D.W. were funded by NCI grant number: U01 CA272977-01: A Transdisciplinary Approach to Investigating Metabolic Dysregulation in Obese Parent and Child Dyads and Risk of Colorectal Cancer.
Conflicts of Interest
J.H. owns controlling interest in Connecting Health Innovations LLC (CHI), a company licensing the right to his invention of the Dietary Inflammatory Index (DII) from the University of South Carolina in order to develop computer and smart phone applications for patient counselling and dietary intervention in clinical settings. In addition to their University of South Carolina appointments, M.W. was an employee of CHI and continues to consult with C.H.I. with the understanding of potential stock options in the future. CHI owns all derivative products, including the energy-adjusted DII (E-DII). Any and all CHI-related activity occurred outside the scope of the submitted work. The subject matter of this paper has not and will not have any direct bearing on the work of CHI, nor has CHI’s activities exerted any influence on this project; no financial relationships with any organizations that might have an interest in the submitted work in the previous three years; no other relationships or activities that could appear to have influenced the submitted work.
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