A pragmatic approach to the classification of menopausal status for community-based research

Summary

The aim of this paper was to describe a pragmatic approach which can be used in research to classify the menopausal status of women who have gynaecological circumstances that complicate their natural menstrual pattern.

The classification algorithm developed was applied to data from the first questionnaire of the MBF Health and Wellbeing after Breast Cancer study. 1684 women diagnosed with invasive breast cancer between 2004 and 2006 in the state of Victoria joined the study and completed the baseline questionnaire within 12 months of their diagnosis. The self-reported data used to classify the women in the study as either premenopausal, perimenopausal or postmenopausal, included gynaecological history, menstrual cycle pattern, presence or absence of vasomotor symptoms and systemic hormone use.

The menopausal status in 71.8% of the women in the study was classified by reported bilateral oophorectomy, age, more than 12 months of amenorrhoea, or regular menstrual cycles and the absence of symptoms. The status in the remainder of the women was classified according to the developed decision tree.

The menopausal classification algorithm described is a useful tool for community-based research as it allows for the classification of women who have had a hysterectomy and of women using systemic hormones for contraception or hormone therapy.