Cited by 158Ovarian function and disordersDiabetes, Cardiovascular Risks, and LipoproteinsAdipokines, Inflammation, and Metabolic Diseases

The central issue? Visceral fat mass is a good marker of insulin resistance and metabolic disturbance in women with polycystic ovary syndrome

Lord, J, Thomas, R, Fox, B, Acharya, U, Wilkin, T·2006·BJOG: An International Journal of Obstetrics & Gynaecology

Abstract

Objective To establish whether visceral fat mass is the most significant variable correlating with insulin resistance and other metabolic parameters in women with polycystic ovary syndrome (PCOS). Design Prospective cross‐sectional trial. Setting Reproductive medicine clinic. Population Forty women with anovulatory PCOS. Methods Measurements were taken at recruitment, and analysis was performed to define correlations between the outcome measures and the explanatory variables. Main outcome measures Visceral and subcutaneous fat by computed tomography scan, insulin resistance, anthropometric measures, markers of the metabolic syndrome and androgens. Results Strong linear correlation of visceral fat to insulin resistance (r= 0.68, P < 0.001) was observed. There were also statistically significant correlations with fasting insulin (r= 0.73, P < 0.001), homeostasis model assessment β‐cell function (r= 0.50, P= 0.007), triglycerides (r= 0.45, P= 0.003), high‐density lipoprotein cholesterol (r=−0.42, P= 0.007), urate (r= 0.47, P= 0.002), Sex hormone binding globulin (r=−0.39, P= 0.01) and luteinising hormone (r=−0.32, P= 0.02). There were no significant correlations of testosterone with fat distribution or metabolic parameters. Insulin resistance showed closest correlation to visceral fat mass (r= 0.68, P < 0.001), then to waist circumference (r= 0.62, P < 0.001), with the weakest correlation being waist:hip ratio (r= 0.36, P= 0.01). The best regression model for predicting insulin resistance is with visceral fat mass and triglycerides as the explanatory variables (r= 0.72, P < 0.001). Conclusions Visceral fat is the most significant variable correlating with metabolic dysfunction in women with PCOS. Our data support the hypothesis that visceral fat either causes insulin resistance or is a very early effect of it. It also implies that reducing visceral fat should reduce insulin resistance which may account for the observations that exercise and weight loss appear to be more effective interventions than pharmacological treatments. The best anthropometric measure of insulin resistance is waist circumference.

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Crossref · 10.1111/j.1471-0528.2006.00973.x

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Authors
Lord, J., Thomas, R., Fox, B., Acharya, U., & Wilkin, T.
Affiliations
  • Royal Cornwall Hospital Trust (GB)
  • Royal Devon & Exeter NHS Foundation Trust (GB)
  • Derriford Hospital (GB)
Corresponding author
Lord, J
ORCID
Lord, J
Venue
BJOG: An International Journal of Obstetrics & Gynaecology
Publisher
Wiley
Published
2006-08-10
Volume
113
Issue
10
Pages
1203-1209
ISSN
  • 0306-5456 (ISSN-L)
  • 1470-0328
  • 1471-0528
OpenAlex
W2083827626
Cited by
158
References
6
Citations by year
2026: 4 · 2025: 4 · 2024: 7 · 2023: 7 · 2022: 5 · 2021: 12 · 2020: 9 · 2019: 7 · 2018: 6 · 2017: 3 · 2016: 8 · 2015: 11 · 2014: 8 · 2013: 12 · 2012: 10
FWCI
10.48
Type
journal article
Language
en
Open access
closed
Locations
  • BJOG An International Journal of Obstetrics & Gynaecology (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 › Epidemiology › Adipokines, Inflammation, and Metabolic Diseases
Keywords
polycystic ovary syndrome, visceral fat mass, insulin resistance, metabolic syndrome, subcutaneous adipose tissue, triglycerides, beta-cell function, androgens, sex hormone-binding globulin, luteinizing hormone, uric acid, waist circumference, body fat distribution, weight loss, exercise intervention, women's health
MeSH terms
Adult, Blood Glucose, Cross-Sectional Studies, Female, Humans, Insulin Resistance, Polycystic Ovary Syndrome, Prospective Studies, Tomography, X-Ray Computed, Metabolic Syndrome, Intra-Abdominal Fat

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