Changes in the probability of hysterectomy in the city of Mainz and Mainz-Bingen region, Germany

Luana F. Tanaka, Olaf Schoffer, Jochem König, Veronika Weyer-Elberich, Maria Blettner, Stefanie J. Klug

Research output: Contribution to journalArticlepeer-review

3 Scopus citations

Abstract

Background: To assess the hysterectomy probability by calendar period and age, the overall and the age-specific prevalence of hysterectomy in women aged 30–65 years. Methods: Baseline data (2005–2007) from the population-based MARZY study conducted in Mainz and Mainz-Bingen, Germany, were analysed. 6429 women aged 30–65 years were asked whether they had undergone a hysterectomy and the date and indication of the procedure. We calculated the 5-year age-specific prevalence of hysterectomy and estimated the probability of undergoing a hysterectomy combining two approaches: 1) Kaplan–Meier and 2) Inverse probability weighting (IPW). We assessed potential changes over calendar periods by simulating survival curves, having hysterectomy as the event, employing a Cox proportional hazard model. Results: Data on hysterectomy were available for 4719 women. Of these, 961 (20.4%) had undergone a hysterectomy between 1960 and 2006. The hysterectomy prevalence was highest among the 60–64 year-olds (40.7%). The IPW-corrected probability of having a hysterectomy up to the age of 65 years was 36.4%. The age-specific probability of hysterectomy increased from 0.1% (20–24 years), peaking at 45–49 years (7.8%) and declining thereafter to less than 5% among women aged 50 and older. Over time, women were hysterectomised at an increasingly older age. Most hysterectomies (86.7%) were done due to benign disease. Conclusions: A shift to older age at hysterectomy with an advancing calendar period likely reflects changes in clinical practice in Germany. Trial registration: Landesärztekammer Rheinland-Pfalz: 837.438.03 (4100).

Original languageEnglish
Article number84
JournalBMC Public Health
Volume23
Issue number1
DOIs
StatePublished - Dec 2023

Keywords

  • Epidemiology
  • Gynaecological surgery
  • Inverse-probability-weighting
  • Kaplan–Meier
  • Missing data

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