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Cited by 38Ovarian function and disordersDiabetes, Cardiovascular Risks, and LipoproteinsBody Composition Measurement Techniques

The DOI matches its Crossref record; 25 of the 26 references it cites were found in a registry or an index.

Body fat indices as effective predictors of insulin resistance in obese/non-obese polycystic ovary syndrome women in the Southwest of China

Abstract

Purpose Insulin resistance (IR) is a common feature of polycystic ovary syndrome (PCOS). Body fat indices can be predictive markers of IR. This study is aimed to predict IR in Chinese women with PCOS of different body types based on body fat indices. Methods A total of 723 women diagnosed with PCOS according to Rotterdam criteria were recruited in this study and were further divided into two groups based on their BMI. All participants underwent physical examinations and ultrasound; and blood was collected from them on the days 3-5 of the menstrual cycle. Their BMI, waist-to-hip ratio (WHR), waist-to-height ratio (WHtR), lipid accumulation product (LAP) index, visceral adiposity index (VAI), and the homeostasis model assessment index of insulin resistance (HOMA-IR) were calculated. The correlations between body fat indices and HOMA-IR and receiver operating characteristic (ROC) curves were evaluated. Results In normal weight group (BMI < 24, n = 333), VAI (best cut-off value: 1.681, area under curve (AUC) = 0.754, P < 0.01) and LAP index (best cut-off value: 18.53, AUC = 0.734, P < 0.001) were the reliable indicators of IR based on HOMA-IR ≥ 2.77, while in overweight/obese group (BMI ≥ 24, n = 390), the BMI, WC, WHtR and LAP index had a significant correlation with HOMA-IR. The representative markers to assess IR were BMI (best cut-off value: 26.43, AUC = 0.644, P = 0.001) and WHtR (best cut-off value: 0.544, AUC = 0.604, P = 0.021). Conclusions Body fat indices are predictive markers of IR in Chinese PCOS women, especially in those with normal weight.

Overview

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Crossref · 10.1007/s12020-019-01912-1

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25 of 25 references verified0 citation errors · 0 not checkable

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Citations

Cites

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Research works printed but not linked: 1

  1. S.S.C. Yen, B.B. Jaffe, R.L. Barbieri. Reproductive Endocrinology. 4th edn. (Science, Harcourt Asia, W. B. Saunders, Print, Beijing, 2001)

Cited by

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Metadata

Authors
Huang, X., Wang, Q., Liu, T., Pei, T., Liu, D., Zhu, H., & Huang, W.
Affiliations
West China Second University Hospital of Sichuan University (CN)
Corresponding author
Huang, Wei
Venue
Endocrine
Published
2019-03-28
Volume
65
Issue
1
Pages
81-85
ISSN
  • 0969-711X (ISSN-L)
  • 1355-008X
  • 1559-0100
OpenAlex
W2933685574
Cited by
34
References
26
Citations by year
2026: 1 · 2025: 3 · 2024: 6 · 2023: 3 · 2022: 7 · 2021: 6 · 2020: 6 · 2019: 2
FWCI
5.03
Type
journal article
Language
en
Open access
closed
Licence
www.springer.com/tdm (tdm)
Locations
  • Endocrine (publishedVersion)
  • PubMed (publishedVersion)
Topics
  • Health Sciences › Medicine › Reproductive Medicine › Ovarian function and disorders
  • Health Sciences › Medicine › Endocrinology, Diabetes and Metabolism › Diabetes, Cardiovascular Risks, and Lipoproteins
  • Health Sciences › Medicine › Physiology (medical) › Body Composition Measurement Techniques
Keywords
polycystic ovary syndrome, insulin resistance, visceral adiposity index, lipid accumulation product, waist-to-hip ratio, waist-to-height ratio, body mass index, HOMA-IR, predictive biomarkers, Chinese women, obesity
MeSH terms
Adipose Tissue, Adult, China, Cross-Sectional Studies, Female, Health Status Indicators, Humans, Insulin Resistance, Obesity, Polycystic Ovary Syndrome, Prognosis, Body Mass Index, Adiposity, Young Adult

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Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).

Semantic Scholar’s data is described in: Kinney, R., et al. (2023). The Semantic Scholar Open Data Platform. arXiv:2301.10140.