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Exploring the Ovarian Reserve Within Health Parameters: A Latent Class Analysis
Theresa M Hardy1, Mauricio Garnier-Villarreal2, Donna O McCarthy2
11 NYU Rory Meyers College of Nursing, New York City, NY, USA.
Western Journal of Nursing Research
|August 10, 2018
Summary
Ovarian aging is complex. This study identified three subgroups of postpartum women, finding that lower ovarian reserve correlates with poorer cardiometabolic and psychological health, aiding ovarian aging risk stratification.
Area of Science:
- Reproductive endocrinology and metabolism.
- Human ovarian aging.
- Biomarker analysis.
Background:
- Ovarian aging is influenced by endocrine, metabolic, and environmental factors.
- Understanding subgroups affected by ovarian aging is crucial.
- Anti-Müllerian hormone (AMH) is a key biomarker for ovarian reserve.
Purpose of the Study:
- To explore the feasibility of using latent class analysis (LCA) to identify subgroups.
- To examine cardiometabolic, psychological, and reproductive health parameters within these subgroups.
- To describe patterns of AMH levels within identified subgroups.
Main Methods:
- Latent class analysis (LCA) was used.
- Included 69 lean and severely obese postpartum women.
- Analyzed cardiometabolic, psychological, and reproductive health parameters, and AMH levels.
Main Results:
- A three-class model provided the best fit.
- Class 1 (n=23, 33.5%), Class 2 (n=30, 42.2%), Class 3 (n=16, 24.3%).
- Lower ovarian reserve (AMH) was associated with less favorable cardiometabolic and psychological profiles.
Conclusions:
- Distinct subgroups of postpartum women can be identified based on health parameters.
- Examining ovarian reserve within these subgroups may aid risk stratification.
- This approach can improve understanding of factors influencing ovarian aging.
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