Association between lumbopelvic pain, disability and sick leave during pregnancy – a comparison of three Scandinavian cohorts

J Rehabil Med. 2014 May;46(5):468-74. doi: 10.2340/16501977-1801.

Abstract

Objective: To explore the association between disability and sick leave due to lumbopelvic pain in pregnant women in 3 cohorts in Sweden and Norway and to explore possible factors of importance to sick leave. A further aim was to compare the prevalence of sick leave due to lumbopelvic pain.

Design/subjects: Pregnant women (n = 898) from two cohorts in Sweden and one in Norway answered to questionnaires in gestational weeks 10–24; two of the cohorts additionally in weeks 28–38.

Methods: Logistic regression models were performed with sick leave due to lumbopelvic pain as dependent factor. Disability, pain, age, parity, cohort, civilian status, and occupational classification were independents factors.

Results: In gestational weeks 10–24 the regression model included 895 cases; 38 on sick leave due to lumbopelvic pain. Disability, pain and cohort affiliation were associated with sick leave. In weeks 28–38, disability, pain and occupation classification were the significant factors. The prevalence of lumbopelvic pain was higher in Norway than in Sweden (65%, vs 58% and 44%; p < 0.001).

Conclusion: Disability, pain intensity and occupation were associated to sick leave due to lumbopelvic pain. Yet, there were significant variations between associated factors among the cohorts, suggesting that other factors than workability and the social security system are also of importance.

Publication types

  • Comparative Study
  • Research Support, Non-U.S. Gov't

MeSH terms

  • Adult
  • Cohort Studies
  • Cross-Sectional Studies
  • Female
  • Humans
  • Logistic Models
  • Low Back Pain / epidemiology*
  • Norway / epidemiology
  • Pelvic Pain / epidemiology*
  • Persons with Disabilities / statistics & numerical data
  • Pregnancy
  • Prevalence
  • Sick Leave / statistics & numerical data*
  • Social Security / statistics & numerical data
  • Sweden / epidemiology