Gender differences in body composition deficits at diagnosis in children and adolescents with Crohn's disease

Inflamm Bowel Dis. 2007 Sep;13(9):1121-8. doi: 10.1002/ibd.20149.

Abstract

Background: Childhood Crohn's disease (CD) is associated with poor growth and decreased body mass index (BMI); however, lean mass (LM) and fat mass (FM) deficits prior to therapy have not been characterized.

Objectives: To quantify LM and FM in incident pediatric CD subjects and controls, and to identify determinants of LM and FM deficits.

Methods: Whole body LM and FM were assessed using DXA in 78 CD subjects and 669 healthy controls, ages 5-21 yr. Gender specific z-scores for LM (LM-Ht) and FM (FM-Ht) relative to height were derived using log linear regression models in the controls. Multivariate linear regression models adjusted for potential confounders.

Results: CD was associated with significantly lower height and BMI for age. Within CD subjects, FM-Ht and LM-Ht were significantly lower in females compared with males (FM-Ht z: -0.66+/-0.83 vs. -0.08+/-0.95, p<0.01; LM-Ht z: -1.12+/-1.12 vs. -0.57+/-0.99, p<0.05). In females, CD was associated with significantly lower LM-Ht (p<0.001) and FM-Ht (p=0.001), adjusted for age, race and Tanner stage, compared with controls. LM and FM deficits were significantly greater in older females with CD; 47% of adolescent females had LM-Ht<or=5th percentile. In non-black males, CD was also associated with lower LM-Ht (p<0.02); FM-Ht deficits were not significant.

Conclusions: Incident CD was associated with significant LM deficits in males and females, and FM deficits in females. Future studies are needed to identify etiologies for the age and gender differences and to evaluate therapies for these deficits.

MeSH terms

  • Adipose Tissue / metabolism
  • Adolescent
  • Adult
  • Age Factors
  • Anthropometry
  • Body Composition
  • Body Mass Index
  • Cachexia
  • Child
  • Child, Preschool
  • Crohn Disease / diagnosis*
  • Crohn Disease / pathology*
  • Female
  • Humans
  • Male
  • Regression Analysis
  • Sex Factors