Abstract
The process of ovarian aging is influenced by a complex and poorly understood interplay of endocrine, metabolic, and environmental factors. The purpose of this study was to explore the feasibility of using latent class analysis to identify subgroups based on cardiometabolic, psychological, and reproductive parameters of health and to describe patterns of anti-Müllerian hormone levels, a biomarker of the ovarian reserve, within these subgroups. Sixty-nine lean (body mass index [BMI] ⩽ 25 kg/m2) and severely obese (BMI ⩾ 40 kg/m2) postpartum women in Edinburgh, Scotland, were included in this exploratory study. The best fitting model included three classes: Class 1, n = 23 (33.5%); Class 2, n = 30 (42.2%); Class 3, n = 16 (24.3%). Postpartum women with lower ovarian reserve had less favorable cardiometabolic and psychological profiles. Examining the ovarian reserve within distinct subgroups based on parameters of health that affect ovarian aging may facilitate risk stratification in the context of ovarian aging.
Original language | English |
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Pages (from-to) | 1903-1918 |
Number of pages | 16 |
Journal | Western Journal of Nursing Research |
Volume | 40 |
Issue number | 12 |
DOIs | |
Publication status | Published - 1 Dec 2018 |
Externally published | Yes |
Funding
The author(s) disclosed receipt of the following financial support for the research, authorship, and/or publication of this article: Research reported in this dissertation was partially supported by the National Institute of Nursing Research of the National Institutes of Health under award number F31NR016621.
Funders | Funder number |
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National Institutes of Health | |
National Institute of Nursing Research | F31NR016621 |
Office of Extramural Research, National Institutes of Health |
Keywords
- cardiometabolic
- latent class analysis
- ovarian reserve
- psychological