Disparities in cardio metabolic risk between Black and White women with polycystic ovary syndrome: a systematic review and meta-analysis

Am J Obstet Gynecol. 2021 May;224(5):428-444.e8. doi: 10.1016/j.ajog.2020.12.019. Epub 2020 Dec 13.

Abstract

Objective: We conducted a systematic review and meta-analysis to summarize and quantitatively pool evidence on cardiometabolic health disparities between Black and White women with polycystic ovary syndrome in the United States in response to the call for further delineation of these disparities in the international evidence-based guideline for the assessment and management of polycystic ovary syndrome.

Data sources: Databases of MEDLINE, Web of Science, and Scopus were searched initially through March 05, 2020, and confirmed on September 11, 2020.

Study eligibility criteria: Observational studies documenting cardiometabolic risk profile (glucoregulatory, lipid profile, anthropometric, and blood pressure status) in Black and White women with polycystic ovary syndrome were included. Studies on children (<17 years old) and pregnant or menopausal-aged women (>50 years) were excluded. The primary outcome was fasting glucose. Furthermore, data on major cardiovascular events (stroke, coronary heart disease, heart failure) and mortality rate (cardiovascular death, total mortality) were evaluated.

Methods: Data were pooled by random-effects models and expressed as mean differences and 95% confidence intervals. Studies were weighted based on the inverse of the variance. Heterogeneity was evaluated by Cochran Q and I2 statistics. Study methodologic quality was assessed by the Newcastle-Ottawa scale.

Results: A total of 11 studies (N=2851 [652 Black and 2199 White]) evaluated cardiometabolic risk profile and all had high quality (Newcastle-Ottawa scale score of ≥8). No studies reported on cardiovascular events and mortality rate. Black women had comparable fasting glucose (-0.61 [-1.69 to 2.92] mg/dL; I2=62.5%), yet exhibited increased fasting insulin (6.76 [4.97-8.56] μIU/mL; I2=59.0%); homeostatic model assessment of insulin resistance (1.47 [0.86-2.08]; I2=83.2%); systolic blood pressure (3.32 [0.34-6.30] mm Hg; I2=52.0%); and decreased triglyceride (-32.56 [-54.69 to -10.42] mg/dL; I2=68.0%) compared with White women (all, P≤.03). Groups exhibited comparable total cholesterol, low-density lipoprotein cholesterol, high-density lipoprotein cholesterol, and diastolic blood pressure (all, P≥.06).

Conclusions: Black women with polycystic ovary syndrome have a greater tendency for an adverse cardiometabolic risk profile (increased insulin, homeostatic model assessment of insulin resistance, and systolic blood pressure) despite lower triglycerides than White women. Our observations support the consideration of these disparities for diagnostic, monitoring, and management practices in Black women and for future guideline recommendations. Given the heterogeneity among studies, future research should address the relative contributions of biologic, environmental, socioeconomic, and healthcare factors to the observed disparities. Furthermore, longitudinal research is required to address patient-pressing complications, including cardiovascular events and mortality rate in Black women with polycystic ovary syndrome as a high-risk yet understudied population.

Keywords: blood pressure; cardiovascular diseases; cardiovascular disorders; cholesterol; dyslipidemias; heart diseases; insulin; metabolic syndrome; mortality; obesity; polycystic ovary syndrome.

Publication types

  • Systematic Review

MeSH terms

  • Black or African American / statistics & numerical data*
  • Blood Glucose / metabolism
  • Blood Pressure
  • Cardiometabolic Risk Factors*
  • Cardiovascular Diseases / epidemiology*
  • Cardiovascular Diseases / mortality
  • Fasting
  • Female
  • Health Status Disparities*
  • Humans
  • Insulin / blood
  • Insulin Resistance
  • Polycystic Ovary Syndrome / epidemiology*
  • Polycystic Ovary Syndrome / physiopathology
  • Triglycerides / blood
  • United States / epidemiology
  • White People / statistics & numerical data*

Substances

  • Blood Glucose
  • Insulin
  • Triglycerides