Anthropometric Characteristics of Polycystic Ovary Syndrome and Their Associations with Insulin Resistance and Lipid Profile

Author:

Sánchez-Ferrer María L.ORCID,Arense-Gonzalo Julián J.ORCID,Prieto-Sánchez María T.ORCID,Gómez-Carrascosa InmaculadaORCID,Hernández-Peñalver Ana I.,Mendiola JaimeORCID,Torres-Cantero Alberto M.ORCID

Abstract

This study evaluates whether women with PCOS have a different body composition than non-PCOS women (controls), estimated by anthropometric methods, and whether body composition and PCOS condition could be predictors of insulin resistance (IR) and lipid profile (LP) in an independent manner. A case-control study was conducted in which women (126) were diagnosed with PCOS by the Rotterdam criteria and controls (159) were women without PCOS attending the gynecological clinic for routine examinations. Women with PCOS had higher body mass index, percentage of fat mass, and testosterone than controls. A higher fat mass predicted higher levels of triglycerides, LDL-c, and lower levels of HDL-c independently of PCOS condition. HOMA-IR was related to fat mass and was more significant in patients with PCOS. A higher bone mass was associated with lower total cholesterol and LDL-c independent of PCOS condition. Lower HOMA-IR remained associated with PCOS regardless of bone mass. Lean mass percentages predicted a better metabolic profile (lower triglycerides and higher HDL-c), and was also modulated by PCOS condition. Our results highlight the importance of body composition as an anthropometrical characteristic of PCOS, and the relationship of fat mass with a worse metabolic profile. In addition, PCOS condition was associated with worse HOMA-IR independent of body composition.

Funder

Ministerio de Economía y Competitividad

Fundación Séneca

Publisher

MDPI AG

Subject

Fluid Flow and Transfer Processes,Computer Science Applications,Process Chemistry and Technology,General Engineering,Instrumentation,General Materials Science

同舟云学术

1.学者识别学者识别

2.学术分析学术分析

3.人才评估人才评估

"同舟云学术"是以全球学者为主线,采集、加工和组织学术论文而形成的新型学术文献查询和分析系统,可以对全球学者进行文献检索和人才价值评估。用户可以通过关注某些学科领域的顶尖人物而持续追踪该领域的学科进展和研究前沿。经过近期的数据扩容,当前同舟云学术共收录了国内外主流学术期刊6万余种,收集的期刊论文及会议论文总量共计约1.5亿篇,并以每天添加12000余篇中外论文的速度递增。我们也可以为用户提供个性化、定制化的学者数据。欢迎来电咨询!咨询电话:010-8811{复制后删除}0370

www.globalauthorid.com

TOP

Copyright © 2019-2024 北京同舟云网络信息技术有限公司
京公网安备11010802033243号  京ICP备18003416号-3