Incidence of lower urinary tract symptoms in a population-based study of men and women

Urology. 2013 Sep;82(3):560-4. doi: 10.1016/j.urology.2013.05.009. Epub 2013 Jul 19.

Abstract

Objective: To report the incidence of lower urinary tract symptoms (LUTS) in a racially and ethnically and age-diverse U.S. population-based sample of men and women.

Materials and methods: We conducted a prospective cohort study with 5 years of follow-up. A stratified 2-stage cluster random sampling method was used to recruit 5502 Boston residents aged 30-79 years of black, Hispanic, or white race or ethnicity. Of these, 4144 (1610 men and 2534 women) completed the follow-up protocol. The American Urological Association Symptom Index was used to define moderate-to-severe LUTS.

Results: Of the 3301 men and women with no or mild LUTS at baseline, the 5-year incidence of moderate-to-severe LUTS (American Urological Association Symptom Index ≥8) was 11.4% overall and was higher for women than for men (13.9% vs 8.5%, P = .02). Although the incidence increased with age (P <.001), it had a plateau among women aged 50-70 years and then doubled to 35.0% among women aged ≥70 years. White men had a distinctly lower incidence (7%) than all other sex and race subgroups (13%).

Conclusion: Approximately 1 in 10 adults had newly developed LUTS at 5 years follow-up of in our study, with differences by sex and race or ethnicity, indicating a greater occurrence of urologic problems among black and Hispanic participants and women.

Publication types

  • Research Support, N.I.H., Extramural

MeSH terms

  • Adult
  • Age Factors
  • Aged
  • Black or African American / statistics & numerical data*
  • Boston / epidemiology
  • Female
  • Follow-Up Studies
  • Hispanic or Latino / statistics & numerical data*
  • Humans
  • Incidence
  • Lower Urinary Tract Symptoms / epidemiology*
  • Lower Urinary Tract Symptoms / ethnology
  • Male
  • Middle Aged
  • Prospective Studies
  • Severity of Illness Index
  • Sex Factors
  • White People / statistics & numerical data*