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Published on: March 5, 2022
The association between percentage body fat and lipid profiles in different phenotypes of PCOS
Dagmara Pluta1, Jakub Daniluk2, Tahar Ben Rhaiem3
1Department of Gynecological Endocrinology, Faculty of Medical Sciences in Katowice, Medical University of Silesia, Katowice, Poland.
Objectives:
Polycystic ovary syndrome (PCOS) is a heterogeneous endocrine disorder linked to metabolic disturbances and increased cardiovascular risk. While the Rotterdam criteria classify PCOS into distinct phenotypes, the impact of percentage body fat (PBF) on lipid profiles across these subtypes remains unclear. This study aims to assess whether the association between PBF and lipid parameters differs among PCOS phenotypes. The research question is: "Does the relationship between PBF and lipid profile vary across PCOS phenotypes defined by the Rotterdam criteria?".
Material And Methods:
A cross-sectional analysis was conducted on 343 PCOS patients, categorized into four phenotypes using the Rotterdam criteria. Body composition was assessed using bioelectrical impedance analysis (InBody 170). Clinical and laboratory data were analyzed to explore phenotype-specific metabolic differences.
Results:
Results show that higher PBF correlates with adverse lipid profiles, including elevated triglycerides (TG) and low-density lipoproteins (LDL) levels and decreased high-density lipoproteins (HDL) levels. Phenotype A exhibited the strongest inverse relationship between PBF and HDL, while Phenotype D showed the most pronounced positive correlation between PBF and triglycerides. These findings highlight the heterogeneity in metabolic risk among Rotterdam phenotypes of PCOS patients.
Conclusions:
There is phenotype-specific association between PBF and lipid components in PCOS. Phenotype A is particularly vulnerable to HDL reduction, while phenotype D shows the strongest triglyceride elevation. This study underscores the importance of individualized management strategies targeting body fat reduction to improve lipid profiles and reduce cardiovascular risk in PCOS patients. Specific interventions tailored based on phenotype and body composition may optimize treatment outcomes.
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