Abstract:
Objective To investigate the impact of body mass index (BMI) on the outcome of intrauterine insemination (IUI) for infertility patients.
Methods A total of 1 393 infertility patients undergoing their first cycle of IUI were selected as study subjects, and were divided into normal BMI group (n=824), overweight group (n=394) and obese group (n=175) based on BMI. Age, duration of infertility, type of infertility, sex hormones, fasting blood glucose, fasting insulin, thyroid function, timing of insemination, number of progressively motile spermatozoa, biochemical pregnancy rate, clinical pregnancy rate and miscarriage rate were compared among the three groups. Multiple linear regression analysis was used to analyze the influencing factors of BMI; the effects of age, BMI, fasting blood glucose and fasting insulin on IUI outcome were analyzed by binary Logistic regression. Receiver operating characteristic (ROC) curve was drawn to analyze the predictive value of BMI for biochemical pregnancy and clinical pregnancy, and the cut-off value was calculated.
Results There were no significant differences in age, time of insemination, number of progressively motile spermatozoa, clinical pregnancy rate and miscarriage rate among the three groups (P>0.05). The duration of infertility, fasting blood glucose and fasting insulin levels in the obese and overweight groups were significantly longer or higher than those in the normal BMI group (P < 0.05). The follicle-stimulating hormone (FSH) level in the obese group was significantly lower, while the free thyroxine (FT4) level in the obese group was significantly higher than that in the overweight group and normal BMI group (P < 0.05). The biochemical pregnancy rate in the obese group was significantly higher than that in the normal BMI group (P < 0.05). Multiple linear regression analysis showed that BMI was negatively correlated with FSH and estradiol (E2) (P < 0.01) and positively correlated with fasting blood glucose and fasting insulin (P < 0.01). Multivariate binary logistic regression analysis showed that age and BMI were influencing factors for clinical pregnancy (P < 0.05), while age, BMI, and fasting insulin were influencing factors for biochemical pregnancy (P < 0.05). The ROC curve showed that the area under the curve (AUC) for BMI predicting biochemical pregnancy and clinical pregnancy was 0.608 and 0.610, respectively, with a cut-off value of 23.05 kg/m2 for both.
Conclusion BMI affects the endocrine and glycolipid metabolism of infertility patients. BMI can be used as an independent factor to predict biochemical pregnancy and clinical pregnancy in IUI.