Exploring the Ovarian Reserve Within Health Parameters: A Latent Class Analysis. (December 2018)

• Record Type: Journal Article
• Authors: Hardy, Theresa M.; Garnier-Villarreal, Mauricio; McCarthy, Donna O.; Anderson, Richard A.; Reynolds, Rebecca M.
• Is Part Of: Western journal of nursing research. Volume 40:Number 12(2018)
• Page Start: 1903
• Page End: 1918
• Publication Date: 2018-12
• Subjects: ovarian reserve -- latent class analysis -- cardiometabolic -- psychological; Nursing -- Research -- Periodicals; Nursing -- Periodicals; Nursing -- Research -- West (U.S.) -- Periodicals; Nursing -- West (U.S.) -- Periodicals; Nursing -- Periodicals; Nursing Research -- Periodicals; Soins infirmiers -- Recherche -- Périodiques; Soins infirmiers -- Périodiques; Soins infirmiers -- Recherche -- États-Unis (Ouest) -- Périodiques; Soins infirmiers -- États-Unis (Ouest) -- Périodiques; Soins infirmiers; Recherche; États-Unis (Ouest); Périodique électronique (Descripteur de forme); Ressource Internet (Descripteur de forme); 610.730702
• DOI: 10.1177/0193945918792303
• Languages: English
• ISSNs: 0193-9459

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/m 2 ) and severely obese (BMI ⩾ 40 kg/m 2 ) 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.