Irritable bowel syndrome in a community: symptom subgroups, risk factors, and health care utilization

Am J Epidemiol. 1995 Jul 1;142(1):76-83. doi: 10.1093/oxfordjournals.aje.a117548.

Abstract

The clinical relevance of subdividing the irritable bowel syndrome (IBS) into subgroups based on bowel habit is largely unknown. We therefore obtained an age- and sex-stratified random sample of Olmsted County, Minnesota, residents aged 20-95 years. All subjects were mailed a valid self-report questionnaire during the years 1988-1993; the response rate was 74% (n = 3,022). Among subjects with IBS (n = 536), four symptom-based subgroups of similar size were identified: constipation predominant, diarrhea predominant, alternating constipation and diarrhea, and neither. The prevalence of IBS was significantly greater in females, primarily because of a higher prevalence of constipation-predominant IBS in women. Of persons > or = 60 years of age, 23% reported the initial onset of IBS in the previous year compared with 10% in younger subjects; the age at onset of IBS was similar among the subgroups. Marital status, education level, smoking, and alcohol use were not significantly different among the subgroups. Of those with IBS, 25% reported visiting a physician for abdominal pain or disturbed defecation in the prior year compared with only 8% of persons without IBS. Female sex, an increased number of Manning's symptom criteria, and the individual IBS subgroups were not associated with higher rates of physician visits. We conclude that the onset of IBS may not be limited to early adulthood and that subgroups of IBS based on bowel patterns may not identify clinically distinct entities.

Publication types

  • Research Support, U.S. Gov't, P.H.S.

MeSH terms

  • Adult
  • Age Distribution
  • Aged
  • Aged, 80 and over
  • Colonic Diseases, Functional / classification
  • Colonic Diseases, Functional / epidemiology*
  • Colonic Diseases, Functional / physiopathology
  • European Continental Ancestry Group
  • Female
  • Health Services / statistics & numerical data
  • Humans
  • Likelihood Functions
  • Logistic Models
  • Male
  • Matched-Pair Analysis
  • Middle Aged
  • Prevalence
  • Risk Factors