Horm Metab Res 2024; 56(06): 445-454
DOI: 10.1055/a-2207-0739
Original Article: Endocrine Care

Anthropometric, Metabolic, and Endocrine Parameters as Predictors of Estimated Average Glucose and Other Biomarkers of Dysglycemia in Women with Different Phenotypes of Polycystic Ovary Syndrome

Sebastião Freitas de Medeiros
1   First Department of Gynecology and Obstetrics, Medical School – Brazil, Federal University of Mato Grosso – Brazil, Cuiabá, Brazil
Ana Lin Winck Yamamoto de Medeiros
2   Gynecology and Obstetrics, University of Cuiabá, Cuiabá MT, Brazil
Matheus Antônio Souto de Medeiros
3   Tropical Institute of Reproductive Medicine, Cuiabá, Brazil
Anna Bethany da Silva Carvalho
4   Biomedicina, UNIVAG, Varzea Grande, Brazil
Marcia W. Yamamoto
3   Tropical Institute of Reproductive Medicine, Cuiabá, Brazil
José M. Soares
5   Department of Obstetrics and Gynecology, Medical School, University of São Paulo, São Paulo, Brazil
Edmund C. Baracat
5   Department of Obstetrics and Gynecology, Medical School, University of São Paulo, São Paulo, Brazil
› Author Affiliations


The aim of the study was to evaluate the efficacy of anthropometric, metabolic, and endocrine abnormalities as predictors of estimated average glucose and other biomarkers of dysglycemia in women with different phenotypes of polycystic ovary syndrome (PCOS). This cross-sectional study included 648 women with PCOS and 330 controls. A single protocol of investigation was applied for all subjects. PCOS women were divided by phenotypes according to the Rotterdam criteria. Biomarkers of dysglycemia were considered dependent variables and anthropometric, lipid, and hormone alterations as independent variables using univariate and multivariate logistic regressions. Univariate logistic regression analysis, controlled for age and BMI, showed that many biomarkers of dysglycemia could be predicted by anthropometric, lipid, and endocrine variables. Multivariate logistic models showed that in non-PCOS women estimated average glucose (eAG) was predicted by lower TSH levels (OR=0.39; p=0.045); fasting glucose was predicted by increased T (OR=2.3). For PCOS, phenotype A, eAG was predicted by decreased HDL-C (OR=0.17, p=0.023) and high levels of free estradiol (OR=7.1, p<0.001). Otherwise, in PCOS, phenotype D, eAG was predicted by higher levels of HDL-C. The current study demonstrated that eAG was poorly predicted by anthropometric, lipid, and hormone parameters. Nevertheless, without adding significant benefits, it was comparable with other established markers of dysglycemia in women with different PCOS phenotypes.

Supplementary Material

Publication History

Received: 25 July 2023

Accepted after revision: 07 November 2023

Accepted Manuscript online:
08 November 2023

Article published online:
10 January 2024

© 2024. Thieme. All rights reserved.

Georg Thieme Verlag
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