Food intake and functional constipation: a cross-sectional study of 3,835 Japanese women aged 18-20 years

J Nutr Sci Vitaminol (Tokyo). 2007 Feb;53(1):30-6. doi: 10.3177/jnsv.53.30.

Abstract

Although we previously observed significant associations between intakes of several foods and constipation, definition of constipation was completely based on subjective perception assessed by a quite simple and single question: do you often have constipation? In this study, we examined the associations between food intake and functional constipation as defined according to symptom-based criteria (Rome I criteria: straining, hard stools, incomplete evacuation, and infrequency of bowel movement). Subjects were 3,835 female Japanese dietetic students aged 18-20 y from 53 institutions in Japan. Dietary intake was estimated with a validated, self-administered diet history questionnaire. The prevalence of functional constipation was 26.2%. Dietary intakes of several foods were significantly associated with functional constipation. A multivariate adjusted odds ratio (95% confidence interval; p for trend) for women in the highest quintile of dietary intake compared with those in the lowest was 0.59 (0.46-0.75; <0.0001) for rice, 0.77 (0.61-0.97; 0.003) for pulses, 1.64 (1.30-2.08; <0.0001) for confectioneries, and 1.41 (1.11-1.78; 0.01) for bread. In conclusion, intake of rice and pulse was negatively and that of confectioneries and bread was positively associated with functional constipation among a population of young Japanese women, which was generally consistent with our previous study where constipation was assessed by a quite simple question.

Publication types

  • Multicenter Study

MeSH terms

  • Adolescent
  • Adult
  • Confounding Factors, Epidemiologic
  • Constipation / epidemiology
  • Constipation / physiopathology*
  • Cross-Sectional Studies
  • Diet Records
  • Eating
  • Feeding Behavior*
  • Female
  • Food Preferences
  • Gastrointestinal Motility
  • Humans
  • Japan / epidemiology
  • Life Style
  • Logistic Models
  • Multivariate Analysis
  • Prevalence
  • Surveys and Questionnaires