Journal of Pediatric Gastroenterology & Nutrition:
Original Articles: Gastroenterology
No Relation Between Disease Activity Measured by Multiple Methods and REE in Childhood Crohn Disease
Wiskin, Anthony E.; Wootton, Stephen A.; Cornelius, Victoria R.; Afzal, Nadeem A.; Elia, Marinos; Beattie, R. Mark
NIHR Biomedical Research Unit (Nutrition, Diet & Lifestyle) Institute of Human Nutrition University of Southampton, Southampton, UK.
Address correspondence and reprint requests to Dr Robert M. Beattie, Paediatric Medical Unit, Southampton General Hospital, Tremona Road, Southampton, S016 6YD, UK (e-mail: firstname.lastname@example.org).
Received 26 June, 2011
Accepted 29 August, 2011
The National Institute for Health Research (NIHR) through the Biomedical Research Unit in Southampton funded this research and provides salary for A.E.W. and V.R.C. Bühlmann Laboratories and Techlab subsidised faecal calprotectin and lactoferrin kits, respectively.
Poster presented at the British Society of Gastroenterology meeting, Birmingham, UK, March 14–17, 2011.
The authors report no conflicts of interest.
Background and Aims: Increased resting energy expenditure (REE) unmatched by dietary intake is implicated as a cause of poor nutrition in childhood inflammatory conditions. Adequate description of disease activity and correction of REE data for body composition are important to reach reliable conclusions about changes in REE associated with disease. The present study aimed to determine the effect of disease activity measured by clinical status, systemic and stool inflammatory markers on REE in children with Crohn disease using appropriate correction for confounding factors.
Methods: Sixty children with Crohn disease were recruited from the regional paediatric gastroenterology unit and studied on 1 occasion. REE was measured by indirect calorimetry. Fat-free mass (FFM) was estimated by skinfold thickness. Disease activity was measured using systemic (C-reactive protein [CRP], erythrocyte sedimentation rate [ESR]) and faecal markers of inflammation (lactoferrin, calprotectin) and clinical scores (Paediatric Crohn Disease Activity Index).
Results: Using a multiple regression model, there was no significant change in REE from active or inactive disease (β = 0.03, P = 0.7) nor from CRP (β = −0.05, P = 0.52), ESR (β = −0.07, P = 0.43), faecal calprotectin (β = −0.07, P = 0.38), and faecal lactoferrin (β = 0.01, P = 0.88). REE/kg FFM0.5 was not associated with the Paediatric Crohn Disease Activity Index (r = 0.1, P = 0.44), CRP (r = −0.3, P = 0.84) or ESR (r = 0.12, P = 0.4), faecal calprotectin (r = 0.04, P = 0.97), or faecal lactoferrin (r = 0.02, P = 0.87).
Conclusions: REE corrected for physiologically relevant confounders is not associated with degree of disease activity using clinical tools or systemic and local inflammatory markers, and therefore is an unlikely mechanism for poor nutritional state.
The incidence of Crohn disease in childhood is increasing (1). Recent cohorts demonstrate that even many years after diagnosis, 15% (2) of children with Crohn disease are still malnourished, highlighting the need to improve the nutritional care of this patient group. The aetiology of malnutrition and the factors that contribute to growth failure in Crohn disease are poorly understood (3). Increased resting energy expenditure (REE) that is unmatched by dietary intake is amongst many proposed mechanisms. In present practice, many children are offered a period of exclusive enteral nutrition as treatment for Crohn disease. This treatment typically involves the prescription of a polymeric or elemental liquid formula as sole nutrient intake for a period of 6 to 8 weeks. The basis for this prescription, however, is limited, and it is unknown whether requirements change with progression from active to inactive disease. We have reported that REE did not relate to clinical scores of disease activity in both Crohn disease and ulcerative colitis (4). The measurement of Crohn disease activity by clinical scores may not necessarily reflect the underlying inflammatory process, and 2 children with the same score may have different inflammatory components. In the present study, we observed the relation between markers of gastrointestinal inflammation (faecal lactoferrin and faecal calprotectin), systemic inflammation (C-reactive protein [CRP] and erythrocyte sedimentation rate [ESR]), and the Paediatric Crohn Disease Activity Index (PCDAI) and their relation with REE. The aim of the present study was to determine the effect of disease activity measured by multiple methods on REE in children with Crohn disease using appropriate correction for confounding factors.
Patients were recruited from the regional paediatric gastroenterology unit at Southampton University Hospitals NHS Trust (tertiary referral centre). There are approximately 200 children with Crohn disease under active follow-up by our service. Between March 2009 and July 2010, a consecutively recruited cohort of 60 children was recruited to the study and completed the full protocol. This is a separate cohort from that previously reported (4). Children ages 0 to 18 years at any stage of disease activity, receiving any or no treatment, were included in the present study. All of them had Crohn disease confirmed histologically according to international criteria (5) and were treated following published guidelines (6). Children with medical conditions in addition to Crohn disease were excluded as were children receiving parenteral nutrition. All of the children were studied on 1 occasion, in the morning, following an overnight fast.
Ethics approval was granted from the Isle of Wight, Portsmouth and South-East Hampshire local research ethics committee. The children themselves agreed to participate in the study. Informed written consent was obtained from their parents or legal guardians.
REE was measured by indirect calorimetry. This technique is based on the assumption that all inspired oxygen is used to oxidise substrates, and that all of the carbon dioxide is produced from these reactions. Measurement requires adherence to strict conditions including environmental temperature, fasting, and rest to obtain repeatable values. In our study, children lay supine for a 30-minute period. This occurred following an overnight fast to minimise any effect attributable to the thermic effect of food. A ventilated canopy system (Deltatrac II, Datex Ohmeda Ltd/GE Healthcare, Helsinki, Finland) was used to record oxygen utilisation and carbon dioxide production, once stable energy expenditure was achieved. Equipment was calibrated using reference gases before each use. Carbon dioxide recovery from alcohol burns performed during the study period ranged from 97% to 104% with a coefficient of variation of 2.5%. REE was calculated using the Weir equation (7). The Schofield equation based on weight was used to provide a normative estimate of energy expenditure for each patient (8,9).
Height was measured with the head in the Frankfort plane, and weight was measured with the children wearing lightweight clothing after voiding. Skinfold thickness measurements were taken in triplicate from the nondominant side of the body using a skinfold calliper (Holtain Ltd, Crymych, UK). A fold of skin was measured following the method of Tanner and Whitehouse at 4 sites: triceps, subscapular, biceps, and suprailiac (10,11). Fat mass was calculated from the sum of skinfold thicknesses (12,13). Fat-free mass (FFM) was therefore the residual of weight and fat mass. FFM was also estimated from bioelectrical impedance analysis (Quadscan 4000, Bodystat Ltd, Douglas, Isle of Man, UK), and the correlation between the 2 estimates was high (r = 0.97, P = 0.00). Agreement between these 2 methods was assessed using the Bland-Altman technique and was found to be good, with no differences outside the accepted limits of agreement.
Disease location was recorded using the Paris classification (14). Disease activity was measured in several ways. The PCDAI (15) uses a combination of symptoms, growth, and serological data to produce an activity score that can be categorised (16). This scoring system has been used as an endpoint in many clinical trials. Disease was also assessed using CRP and ESR as markers of systemic inflammation. Faecal calprotectin (Bühlmann Laboratories, Schönenbuch, Switzerland) and faecal lactoferrin (Techlab, Blacksburg, VA) were measured as markers of intestinal inflammation.
Standard deviation scores for weight, height, and body mass index were calculated from UK 1990 growth data using LMS growth software (Harlow Healthcare, South Shields, UK http://www.healthforallchildren.co.uk/). Interpretation of REE data requires correction for body mass, the largest known confounder. Our data showed a clear correlation between REE and weight (r = 0.83, P < 0.01) and between REE and FFM (r = 0.83, P < 0.01). There was a negative correlation between REE/kg FFM and FFM (r = −0.63, P < 0.01) but no correlation between REE/kg FFM0.5 and FFM (r = −0.07, P = 0.61). We have advocated the use of REE/kg FFM0.5 as an appropriate way to correct REE for body composition (4). The exponent 0.5 is derived from log-log regression of FFM and REE (17,18). A multiple regression model was established including factors that independently influence REE (FFM, age, sex, and pubertal status). In turn, measures of disease activity were added to this model separately to evaluate the effect they had on REE.
Data are reported as mean ± standard deviation unless otherwise stated. Differences between groups were evaluated using t tests for parametric and Kruskal-Wallis tests for nonparametric data. Correlation was tested using Spearman rank correlation coefficient. Significance was accepted at P < 0.01. Statistical analysis was performed using SPSS 16.0 for windows (SPSS Inc, Chicago, IL).
Sixty children were studied (39 boys), mean age of 13 years (range 6–17 years). Thirty-nine had ileocolonic disease (L3), 22 of whom had upper gastrointestinal (GI) involvement (L3 + L4), 18 had colonic disease (L2), 9 of whom had upper GI involvement (L2 + L4), 1 had terminal ileal and upper GI disease (L1 + L4), and 2 had upper GI disease only (L4). Seven children required bowel resections because of their disease. Thirteen children were seen at diagnosis. Overall, children had been under follow-up for a median of 1.3 years, with a range of 0 to 10 years.
Nineteen children had inactive disease (PCDAI <10), 30 had mild disease (PCDAI ≥10 <30), and 11 had moderate/severe disease (PCDAI ≥30). Mean ± standard deviation PCDAI was 17 ± 3. Table 1 shows data split by PCDAI groups. Children with active disease (PCDAI ≥10) were significantly younger (P = 0.01), had lower FFM (P < 0.01), and had higher CRP (P < 0.01), ESR (P < 0.01), faecal calprotectin (P < 0.01), and faecal lactoferrin (P < 0.01) values than those with inactive disease (PCDAI <10). Children with PCDAI ≥30 were younger and had lower FFM and higher inflammatory markers than those with PCDAI <10.
REE and Normative Equations
Measured REE values were compared with those estimated by the Schofield equation. Mean measured REE was 1369.4 ± 279.5 kcal, significantly lower than the mean from the Schofield equation (1402 ± 283.6 kcal, P < 0.01). Fifteen values lay outside the limits of agreement on Bland-Altman analysis. REE expressed as a percentage of that predicted from Schofield had a mean value of 98% ± 11.1%.
REE and Disease Activity (PCDAI)
Children with active disease (PCDAI ≥10) had lower REE (P = 0.02), and higher REE/kg FFM (P = 0.08) but similar REE/kg FFM0.5 (P = 0.26) when compared with children with PCDAI <10. REE/kg FFM0.5 was not associated with PCDAI (r = 0.1, P = 0.44) (Fig. 1). Using the multiple regression model including FFM, age, sex, and pubertal stage (Table 2), analysis showed no significant change in REE because of active or inactive disease (β = 0.03, 95% CI −71% to 105%, P = 0.7). The same result was found using the multiple regression model with PCDAI as a continuous variable (β = −0.1, 95% CI −5.3% to 1.0%, P = 0.17) and using the PCDAI categories proposed by Turner et al (16) (β = −0.09, 95% CI −82.3% to 21.7%, P = 0.25). REE/kgFFM0.5 was not associated with duration of disease (time since diagnosis) (r = −0.11, P = 0.41), neither was REE related to time since diagnosis in the regression model (β = 0.02, 95% CI −21.4% to 14.4%, P = 0.76).
REE and Markers of Inflammation
REE/kg FFM0.5 was not associated with CRP (r = 0.07, P = 0.60), ESR (r = 0.12, P = 0.40), faecal calprotectin (r = −0.01, P = 0.94), or faecal lactoferrin (r = −0.03, P = 0.80) (Fig. 1). The regression model was used to evaluate the effect of these markers of disease activity. There was no significant effect of CRP (β = −0.05 95% CI −3.4% to 1.7%, P = 0.52) or ESR (β = −0.07, 95% CI −3.8 to 1.6%, P = 0.43) on REE. REE was not influenced by intestinal inflammation measured by both faecal calprotectin (β = −0.07, 95% CI −0.03% to 0.01%, P = 0.38) and faecal lactoferrin (β = 0.01, 95% CI −0.13 to 0.16, P = 0.88).
This is the largest cross-sectional study of REE in inflammatory bowel disease to our knowledge. The results do not demonstrate a relation between disease activity and REE in children with Crohn disease when appropriate consideration is made for confounding factors such as age, sex, pubertal status, and body composition.
Studies that have examined REE in patients with Crohn disease in both paediatric and adult cohorts are shown in Tables 3 and 4. Two issues are often reported together. First, is REE different between patients and controls, or patients and predictive equations, and second, does REE change with disease activity? Studies comparing measured energy expenditure of patients with Crohn to controls suggest that both adults (19–23) and children (24) with disease have higher REE. Studies reporting REE relative to predictive equations often express REE as a percentage of that predicted. In 6 paediatric studies (4,24–28), measured and predicted REE were not different. In the present study, measured REE was significantly lower than that predicted; however, this difference is unlikely to be metabolically or clinically significant. Other studies have examined the effect of disease activity in children with Crohn disease and have shown either no change in REE with disease activity (4,26,28,29) or increased REE at times of active disease (24); however, results from studies comparing measurements of REE depend on the way REE data are expressed to correct for body size and composition. Expressing energy expenditure as REE/kg FFM results in higher values for those with the lowest FFM. We have demonstrated that children with active disease have lower FFM than those with inactive disease and have the highest REE/kg FFM. An explanation for this considers the constituents of FFM. FFM contains both organs and skeletal muscle. Organ mass is more metabolically active than skeletal muscle (30). In individuals with lower FFM (lighter and or shorter), the relative contribution organ mass makes to total REE increases in relation to skeletal muscle. Therefore, expressing energy expenditure as REE/kg FFM results in higher values for those with the lowest FFM. The results of the multiple regression analysis that adequately corrects for FFM and other variables confirm that this does not truly represent hypermetabolism as has been suggested previously (21,31–33). Therefore, we do not recommend REE/kg FFM as a helpful way of correcting REE data for body composition.
Cross-sectional REE data that are adequately corrected for biologically important confounders are helpful to examine the effect of disease activity on REE. Longitudinal data may be able to provide greater insights. In 18 children studied at least 6 months apart in this and our previous study, we found no change in REE/kg FFM0.5 relative to change in PCDAI between the 2 measurements (r = −0.37, P = 0.12) (34).
Increased REE that is unmatched by dietary intake is amongst many proposed mechanisms for the poor nutritional status of children with Crohn disease. Severe disease is associated with the poorest nutritional outcomes; therefore, if alterations in REE are a key factor, REE should be increased in those with the most active disease. Defining disease activity in Crohn disease is inherently difficult; therefore, in the present study we used several different markers. This included using PCDAI as a continuous variable and as categories. Alternative measures of disease activity including markers of the systemic inflammatory response (CRP/ESR) and intestinal inflammation (faecal calprotectin/lactoferrin) showed the same results. The present study demonstrates no correlation between disease activity and REE in children with Crohn disease when appropriate consideration is made for confounding factors.
The authors thank the paediatric nurses of the NIHR BRU (nutrition, diet, and lifestyle), Liz Blake, Rachel Haggarty, and Claire Willis, for their help with data collection, and also Christine Glenn for laboratory analysis.
1. Benchimol EI, Fortinsky KJ, Gozdyra P, et al. Epidemiology of pediatric inflammatory bowel disease: a systematic review of international trends. Inflamm Bowel Dis 2011; 17:423–439.
2. Vasseur F, Gower-Rousseau C, Vernier-Massouille G, et al. Nutritional status and growth in pediatric Crohn's disease: a population-based study. Am J Gastroenterol 2010; 105:1893–1900.
3. Wiskin AE, Wootton SA, Beattie RM. Nutrition issues in pediatric Crohn's disease. Nutr Clin Pract 2007; 22:214–222.
4. Wiskin AE, Wootton SA, Culliford DJ, et al. Impact of disease activity on resting energy expenditure in children with inflammatory bowel disease. Clin Nutr 2009; 28:652–656.
5. Silverberg MS, Satsangi J, Ahmad T, et al. Toward an integrated clinical, molecular and serological classification of inflammatory bowel disease: report of a working party of the 2005 Montreal World Congress of Gastroenterology. Can J Gastroenterol 2005; 19 (suppl A):5–36.
6. Bremner AR, Beattie RM. Recent advances in the medical therapy of Crohn's disease in childhood. Exp Opin Pharmacother 2007; 8:2553–2568.
7. Weir JB. New methods for calculating metabolic rate with special reference to protein metabolism. J Physiol 1949; 109:1–9.
8. Schofield WN. Predicting basal metabolic rate, new standards and review of previous work. Hum Nutr Clin Nutr 1985; 39 (suppl 1):5–41.
9. Hill RJ, Lewindon PJ, Withers GD, et al. Ability of commonly used prediction equations to predict resting energy expenditure in children with inflammatory bowel disease. Inflamm Bowel Dis 2011; 17:1587–1593.
10. Tanner JM, Whitehouse RH. Standards for subcutaneous fat in British children. Percentiles for thickness of skinfolds over triceps and below scapula. Br Med J 1962; 1:446–450.
11. Durnin JV, Womersley J. Body fat assessed from total body density and its estimation from skinfold thickness: measurements on 481 men and women aged from 16 to 72 years. Br J Nutr 1974; 32:77–97.
12. Lohman TG, Slaughter MH, Boileau RA, et al. Bone mineral measurements and their relation to body density in children, youth and adults. Hum Biol 1984; 56:667–679.
13. Johnston JL, Leong MS, Checkland EG, et al. Body fat assessed from body density and estimated from skinfold thickness in normal children and children with cystic fibrosis. Am J Clin Nutr 1988; 48:1362–1366.
14. Levine A, Griffiths A, Markowitz J, et al. Pediatric modification of the Montreal classification for inflammatory bowel disease: the Paris classification. Inflamm Bowel Dis 2011; 17:1314–1321.
15. Hyams JS, Ferry GD, Mandel FS, et al. Development and validation of a pediatric Crohn's disease activity index. J Pediatr Gastroenterol Nutr 1991; 12:439–447.
16. Turner D, Griffiths AM, Walters TD, et al. Appraisal of the pediatric Crohn's disease activity index on four prospectively collected datasets: recommended cutoff values and clinimetric properties. Am J Gastroenterol 2010; 105:2085–2092.
17. Hill RJ, Cleghorn GJ, Withers GD, et al. Resting energy expenditure in children with inflammatory bowel disease. J Pediatr Gastroenterol Nutr 2007; 45:342–346.
18. Zakeri I, Puyau MR, Adolph AL, et al. Normalization of energy expenditure data for differences in body mass or composition in children and adolescents. J Nutr 2006; 136:1371–1376.
19. Sasaki M, Johtatsu T, Kurihara M, et al. Energy metabolism in Japanese patients with Crohn's disease. J Clin Biochem Nutr 2010; 46:68–72.
20. Barot LR, Rombeau JL, Feurer ID, et al. Caloric requirements in patients with inflammatory bowel disease. Ann Surg 1982; 195:214–218.
21. Al-Jaouni R, Hebuterne X, Pouget I, et al. Energy metabolism and substrate oxidation in patients with Crohn's disease. Nutrition 2000; 16:173–178.
22. Capristo E, Addolorato G, Mingrone G, et al. Effect of disease localization on the anthropometric and metabolic features of Crohn's disease. Am J Gastroenterol 1998; 93:2411–2419.
23. Capristo E, Mingrone G, Addolorato G, et al. Metabolic features of inflammatory bowel disease in a remission phase of the disease activity. J Intern Med 1998; 243:339–347.
24. Varille V, Cezard JP, de Lagausie P, et al. Resting energy expenditure before and after surgical resection of gut lesions in pediatric Crohn's disease. J Pediatr Gastroenterol Nutr 1996; 23:13–19.
25. Hart JW, Bremner AR, Wootton SA, et al. Measured versus predicted energy expenditure in children with inactive Crohn's disease. Clin Nutr 2005; 24:1047–1055.
26. Diamanti A, Basso MS, Gambarara M, et al. Positive impact of blocking tumor necrosis factor alpha on the nutritional status in pediatric Crohn's disease patients. Int J Colorectal Dis 2009; 24:19–25.
27. Azcue M, Rashid M, Griffiths A, et al. Energy expenditure and body composition in children with Crohn's disease: effect of enteral nutrition and treatment with prednisolone. Gut 1997; 41:203–208.
28. Steiner SJ, Pfefferkorn MD, Fitzgerald JF, et al. Protein and energy metabolism response to the initial dose of infliximab in children with Crohn's disease. Inflamm Bowel Dis 2007; 13:737–744.
29. Cormier K, Mager D, Bannister L, et al. Resting energy expenditure in the parenterally fed pediatric population with Crohn's disease. JPEN J Parenter Enteral Nutr 2005; 29:102–107.
30. Hsu A, Heshka S, Janumala I, et al. Larger mass of high-metabolic-rate organs does not explain higher resting energy expenditure in children. Am J Clin Nutr 2003; 77:1506–1511.
31. Chan AT, Fleming CR, O’Fallon WM, et al. Estimated versus measured basal energy requirements in patients with Crohn's disease. Gastroenterology 1986; 91:75–78.
32. Kushner RF, Schoeller DA. Resting and total energy expenditure in patients with inflammatory bowel disease. Am J Clin Nutr 1991; 53:161–165.
33. Stokes MA, Hill GL. Total energy expenditure in patients with Crohn's disease: measurement by the combined body scan technique. JPEN J Parenter Enteral Nutr 1993; 17:3–7.
34. Wiskin AE, Wootton SA, Beattie RM. Change in disease activity and resting energy expenditure in children with Crohn's disease. Gut 2011; 60:A100.
35. Barot LR, Rombeau JL, Steinberg JJ, et al. Energy expenditure in patients with inflammatory bowel disease. Arch Surg 1981; 116:460–462.
36. Mingrone G, Capristo E, Greco AV, et al. Elevated diet-induced thermogenesis and lipid oxidation rate in Crohn disease. Am J Clin Nutr 1999; 69:325–330.
37. Schneeweiss B, Lochs H, Zauner C, et al. Energy and substrate metabolism in patients with active Crohn's disease. J Nutr 1999; 129:844–848.
38. Wiese D, Lashner B, Seidner D. Measurement of nutrition status in Crohn's disease patients receiving infliximab therapy. Nutr Clin Pract 2008; 23:551–556.
This article has been cited 2 time(s).
Alimentary Pharmacology & TherapeuticsSystematic review: body composition in adults with inflammatory bowel diseaseAlimentary Pharmacology & Therapeutics
Digestive Diseases and SciencesFecal Calprotectin in Pediatric Inflammatory Bowel Disease: A Systematic ReviewDigestive Diseases and Sciences
basal metabolism; inflammatory bowel disease; nutritional status; paediatrics; resting energy expenditure
Copyright 2012 by ESPGHAN and NASPGHAN
Highlight selected keywords in the article text.
Connect With Us
Visit JPGN.org on your smartphone. Scan this code (QR reader app required) with your phone and be taken directly to the site.