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Body mass index is a good predictor of metabolic abnormalities in polycystic ovary syndrome

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Abstract

Aim

To assess which parameters among hyperandrogenism (total testosterone—tT—or free androgen index—FAI), sex hormone binding globulin (SHBG) or body mass index (BMI) could better predict a worse metabolic profile in women with polycystic ovary syndrome (PCOS).

Methods

Five hundred and eighty-six women with PCOS and clinical or biochemical hyperandrogenism were included. Receiver Operating Characteristics (ROC) curves with tT, FAI, SHBG and BMI were performed for metabolic parameters and a cut-off with sensitivity and specificity was obtained for each parameter. The women were then divided into three groups and compared according to their BMI.

Results

Based on the ROC curves, tT proved not to be a good predictor of metabolic alterations. FAI and SHBG resulted to be good predictors of some markers of metabolic damage. The area under the curves (AUC) of SHBG were greater than those of FAI. SHBG levels affects the values of homeostasis model assessment of insulin resistance (HOMA-IR), fasting insulin, high density lipoproteins (HDL), low density lipoproteins (LDL), and total cholesterol also when corrected for BMI. However, the highest AUCs of the ROC curves were observed when BMI was used, which was significantly related to all the metabolic parameters analyzed. Dividing women according to their BMI, BMI between 25.00 and 30.00 kg/m2 had a worse metabolic profile but still in a normal range, while BMI ≥ 30 kg/m2 women had a significant metabolic derangement.

Discussion

BMI is a good predictor factor of metabolic changes in PCOS women at any age, and obesity is associated to the appearance of metabolic complications. Overweight and obese PCOS women should be addressed to perform a complete metabolic assessment.

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Data availability

Data will be made available by the authors upon reasonable request.

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Funding

No funding was required for the study.

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Author notes

  1. F. Fruzzetti and T. Fidecicchi are joint first authors.

Authors and Affiliations

  1. Department of Obstetrics and Gynecology, Pisa University Hospital of S. Chiara, Azienda Ospedaliera Universitaria, Via Roma 65, 56126, Pisa, Italy

    F. Fruzzetti, T. Fidecicchi & F. Baldari

  2. Department of Endocrinology, Pisa University Hospital of Cisanello, Azienda Ospedaliera Universitaria, Via Paradisa 2, 56124, Pisa, Italy

    E. Benelli & M. Tonacchera

Authors
  1. F. Fruzzetti
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  2. T. Fidecicchi
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  3. E. Benelli
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  4. F. Baldari
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  5. M. Tonacchera
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Contributions

All authors contributed to the study conception and design. FF and TF participated in study, execution, analysis, manuscript drafting, and critical discussion. EB and FB participated in study execution. MT participated in manuscript drafting and critical discussion.

Corresponding author

Correspondence to F. Fruzzetti.

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The authors have no conflict of interest to disclose.

Research involving human participants and/or animals

All procedures were performed in accordance with the ethical standards of the Committee on Institutional Human Experimentation, and with the Helsinki Declaration of 1975, as revised in 1983.

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All patients gave informed consent for data to be collected and for their anonymous data to be used for clinical publication.

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Fruzzetti, F., Fidecicchi, T., Benelli, E. et al. Body mass index is a good predictor of metabolic abnormalities in polycystic ovary syndrome. J Endocrinol Invest 47, 927–936 (2024). https://doi.org/10.1007/s40618-023-02210-4

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  • DOI: https://doi.org/10.1007/s40618-023-02210-4

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