O-182 No higher prevalence of metabolic dysfunction among subfertile women in an urban population
Authors: Van Bree B , Pattinaja D , Bons J , Spaanderman M , Valkenburg O , Van Golde R 
Published: June 2022

Study question

What is the prevalence of metabolic dysfunction, like insulin resistance, hyperglycaemia, hypertension, and/or dyslipidaemia, among subfertile women compared to healthy controls?

Summary answer

Signs of metabolic dysfunction were not observed more frequently in subfertile women than in controls. Overweight and obese patients were at risk for metabolic dysfunction.

What is known already

Metabolic dysfunction is known to impair female fecundity as it is linked to a longer time-to-pregnancy and to subfertility. Three times as many PCOS patients are diagnosed with metabolic syndrome than age matched controls. Moreover, a recent study showed a higher prevalence among the entire subfertile population. Metabolic disorders have been connected to the impairment of normal ovarian function and pituitary-hypothalamic axis. Obesity is correlated with menstrual irregularities, ovulation disorders and infertility. On top, it can increase risk of miscarriage and reduce chances with assisted reproductive technologies. Therefore, metabolic dysfunction might also be a driving factor behind unexplained subfertility.

Study design, size, duration

This cross-sectional observational case control study was performed in a secondary and tertiary care fertility clinic (MUMC+, Maastricht, The Netherlands). Patients were referred to the fertility clinic with either primary or secondary subfertility (inability to conceive after one year of regular unprotected intercourse), controls were healthy, parous women. All participants were aged between 18 and 41 years at time of inclusion. 119 patients and 68 controls were included over a time span of 3 years.

Participants/materials, setting, methods

A basic medical history was collected using questionnaires. Physical examination included measurement of weight, height, waist and hip circumference, blood pressure and pulse. Venipuncture was performed after an overnight fast on cycle day 2-4; including insulin, glucose, triglycerides, high-density lipid cholesterol, total cholesterol, glomerular filtration rate, urea, uric acid, creatinine, follicle stimulating hormone, estradiol and anti-Mullarian hormone. Urine was collected to measure protein and creatinine. Metabolic syndrome was diagnosed according to Adult Treatment Panel-III guidelines.

Main results and the role of chance

Body weight and BMI were similarly distributed between patients and controls. Main causes of subfertility comprised male factor (12%), anovulation (20%) and unexplained subfertility (47%). Comparing patients to controls, unexplained subfertility only had slightly higher HDL cholesterol levels (p = 0.046). Anovulatory patients showed 2% higher glucose (p = 0.003) and 133% higher AMH levels (p &lt; 0.001). Metabolic syndrome was diagnosed in 6% of unexplained subfertility patients, in 4% of male factor patients and in 5% of anovulatory patients. No controls were diagnosed with metabolic syndrome.

In a comparison of overweight and obese patients to normal weight patients we observed resp. 16% and 37% higher waist circumference (p &lt; 0.001), 7% and 11% higher waist-to-hip ratio (p &lt; 0.01), 37% and 197% higher fasting insulin (p &lt; 0.01), 30% and 198% higher HOMA-IR (p &lt; 0.02) and 8% and 24% higher uric acid levels (p &lt; 0.03). Concomitantly, obese patients showed dyslipidemia with 98% higher triglyceride levels (p &lt; 0.001) and 24% lower HDL cholesterol (p &lt; 0.01). 181% higher AMH levels were found in obese patients (p &lt; 0.01). Metabolic syndrome was diagnosed in 1% of normal weight patients, 4% of overweight patients and in 25% of obese patients.

Limitations, reasons for caution

Participants were young and remarkably healthy, which might account for the low prevalence of metabolic disorders. It is known that the prevalence of metabolic dysfunction is strongly dependent on socioeconomic and geographic determinants in various populations. Our findings apply to a largely ethnically homogeneous Caucasian female population in the Netherlands.

Wider implications of the findings

We found that the presence or specific cause of subfertility per se, cannot be regarded as a reliable and strong predictor of metabolic dysfunction, even in anovulatory subfertility. As can be expected, metabolic dysfunction is highly associated with BMI and obese patients should consider lifestyle intervention to prevent future complications.

Trial registration number

Not applicable