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The menopause transition

G A Greendale1, M Sowers

  • 1Department of Obstetrics and Gynecology, UCLA School of Medicine, USA.

Endocrinology and Metabolism Clinics of North America
|June 1, 1997
PubMed
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New menopause research models view the transition as a long process, not a single event. This approach helps understand hormone changes and their links to chronic diseases and other health issues.

Area of Science:

  • Reproductive Endocrinology
  • Women's Health Research
  • Longitudinal Health Studies

Background:

  • Menopause is increasingly understood as a prolonged transition, not an isolated event.
  • Traditional views focused on discrete menopausal events, limiting understanding of long-term health associations.
  • The complexity of menopause requires updated research models to accurately capture its multifaceted nature.

Purpose of the Study:

  • To introduce new research paradigms for studying menopause and its associated health outcomes.
  • To address the challenges in measuring temporal hormonal changes during the menopause transition.
  • To integrate a broader range of factors, including hormones, comorbidities, and behaviors, into menopause research models.

Main Methods:

  • Shifting from a discrete event model to a longitudinal transition model for menopause.

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  • Expanding hormonal assessments beyond estrogen to include androgens and other key hormones.
  • Incorporating comorbid medical/psychiatric conditions, environmental factors, and behaviors as covariates.

    • Main Results:

    • New models facilitate the measurement of temporal hormone patterns and their relation to health events.
    • Expanded hormonal considerations, including androgens, provide a more comprehensive view of menopausal changes.
    • Integration of covariates enhances the ability to explain complex exposures and effect modifiers.

    Conclusions:

    • Updated menopause research paradigms are crucial for understanding the links between menopausal transition, symptoms, and chronic diseases.
    • Longitudinal and multifactorial models offer clearer insights into previously confusing data in menopause research.
    • These advanced models promise to elucidate critical research questions by properly accounting for complex interactions.