Extent of metabolic risk in adolescent girls with features of polycystic ovary syndrome

Fertil Steril. 2011 Jun;95(7):2347-53, 2353.e1. doi: 10.1016/j.fertnstert.2011.03.001. Epub 2011 Mar 29.

Abstract

Objective: To determine prevalence of metabolic syndrome in adolescents with polycystic ovary syndrome (PCOS) and derive features suggestive of propensity for development of metabolic syndrome.

Design: Prospective cohort study.

Setting: Population-based cohort of adolescents in Western Australia.

Participant(s): Metabolic data from 1,377 children aged 14 years, features of PCOS obtained from 244 girls aged 14 to 17 years.

Intervention(s): Assessment for features of PCOS and subsequent fasting blood samples.

Main outcome measure(s): Relationship between features of PCOS and features of metabolic syndrome.

Result(s): With use of five definitions of metabolic syndrome the maximal prevalence of metabolic syndrome recorded was 11.8% in girls with PCOS (National Institutes of Health [NIH]) and 6.6% (Rotterdam) (non-PCOS 0.6% and 0.7%, respectively). With use of cluster analysis of metabolic risk (a technique to cluster the adolescents according to multidimensional relationships of established cardiovascular risk factors), 35.3% with PCOS-NIH were at risk for metabolic syndrome and 26.2% with PCOS-Rotterdam (non-PCOS 15.4% and 15.4%, respectively). Menstrual irregularity and high free T (PCOS-NIH) were associated with high metabolic syndrome risk (odds ratio 3.00, confidence interval 1.3-6.4), not after controlling for body mass index. Of PCOS features, an elevated free T level was most predictive of insulin resistance. Menstrual irregularity and polycystic ovary morphology were not associated with insulin resistance (56.3% vs. 52.9% and 60.0% vs. 34.4%, respectively).

Conclusion(s): Despite the low prevalence of metabolic syndrome in girls with PCOS, one third have features putting them at high risk for development of metabolic syndrome.

Publication types

  • Research Support, Non-U.S. Gov't

MeSH terms

  • Adolescent
  • Age Factors
  • Biomarkers / blood
  • Chi-Square Distribution
  • Cluster Analysis
  • Female
  • Humans
  • Insulin Resistance
  • Logistic Models
  • Menstrual Cycle
  • Metabolic Syndrome / blood
  • Metabolic Syndrome / epidemiology*
  • Metabolic Syndrome / physiopathology
  • Odds Ratio
  • Overweight / epidemiology
  • Polycystic Ovary Syndrome / blood
  • Polycystic Ovary Syndrome / epidemiology*
  • Polycystic Ovary Syndrome / physiopathology
  • Prevalence
  • Risk Assessment
  • Risk Factors
  • Testosterone / blood
  • Up-Regulation
  • Western Australia / epidemiology

Substances

  • Biomarkers
  • Testosterone