Please use this identifier to cite or link to this item: https://hdl.handle.net/2440/106264
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Type: Journal article
Title: The association between Polycystic Ovary Syndrome (PCOS) and metabolic syndrome: a statistical modelling approach
Author: Ranasinha, S.
Joham, A.
Norman, R.
Shaw, J.
Zoungas, S.
Boyle, J.
Moran, L.
Teede, H.
Citation: Clinical Endocrinology, 2015; 83(6):879-887
Publisher: Wiley/Blackwell
Issue Date: 2015
ISSN: 0300-0664
1365-2265
Statement of
Responsibility: 
S. Ranasinha, A.E. Joham, R.J. Norman, J.E. Shaw, S. Zoungas, J. Boyle, L. Moran and H.J. Teede
Abstract: Objective: Polycystic ovary syndrome (PCOS) affects 12-21% of women. Women with PCOS exhibit clustering of metabolic features. We applied rigorous statistical methods to further understand the interplay between PCOS and metabolic features including insulin resistance, obesity and androgen status. Design: Retrospective cross-sectional analysis. Patients: Women with PCOS attending reproductive endocrine clinics in South Australia for the treatment of PCOS (n = 172). Women without PCOS (controls) in the same Australian region (n = 335) from the Australian Diabetes, Obesity and Lifestyle Study (AusDiab), a national population-based study (age- and BMI-matched within one standard deviation of the PCOS cohort). Measurements: The factor structure for metabolic syndrome for women with PCOS and control groups was examined, specifically, the contribution of individual factors to metabolic syndrome and the association of hyperandrogenism with other metabolic factors. Results: Women with PCOS demonstrated clustering of metabolic features that was not observed in the control group. Metabolic syndrome in the PCOS cohort was strongly represented by obesity (standardized factor loading = 0·95, P < 0·001) and insulin resistance factors (loading = 0·92, P < 0·001) and moderately by blood pressure (loading = 0·62, P < 0·001) and lipid factors (loading = 0·67, P = 0·002). On further analysis, the insulin resistance factor strongly correlated with the obesity (r = 0·70, P < 0·001) and lipid factors (r = 0·68, P < 0·001) and moderately with the blood pressure factor (loading = 0·43, P = 0·002). The hyperandrogenism factor was moderately correlated with the insulin resistance factor (r = 0·38, P < 0·003), but did not correlate with any other metabolic factors. Conclusions: PCOS women are more likely to display metabolic clustering in comparison with age- and BMI-matched control women. Obesity and insulin resistance, but not androgens, are independently and most strongly associated with metabolic syndrome in PCOS.
Keywords: Polycystic Ovary Syndrome
Rights: © 2015 John Wiley & Sons Ltd
DOI: 10.1111/cen.12830
Published version: http://dx.doi.org/10.1111/cen.12830
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Paediatrics publications

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