In recent decades, China has changes in dietary intake and decreased physical activity [16]. The report released in China shows that comprising 72.1 million female patients, have prediabetes. Among women between the ages of 20 and 39 years, approximately 5.6 million have DM (3.2%) and 15 million have prediabetes (9%) [17].
Regarding the specific eating habits of Chinese people and the lack of sufficient exercise during pregnancy, obesity in the GDM group was higher than in the NP group. A previous study revealed that normal weight accounted for most NPs [18]. In this study, however, 67.6% and 87.2% of the patients in the NP and GDM groups, respectively, were overweight and obesity.
A higher BMI, AC, and fasting glucose in the first trimester of pregnancy increased GDM risk [19]. Excessive gestational weight gain, according to the targets set by the Institute of Medicine (IOM), was associated with cesarean section, LGA and macrosomia. Modification of the IOM criteria, including more restrictive targets, did not improve perinatal outcomes [20]. Our results indicated that there was a high percentage of obesity in the GDM group and was 1.96-fold that of control group for predicting macrosomia, and that obesity can also lead to adverse pregnancy outcomes. In addition, other groups have reported the relationship between obesity and adverse pregnancy outcomes [21].
In a previous study, the incidence of fetal macrosomia (the main outcome) was significantly higher in the GDM group (20.0%) than in the control group (3.6%) [22]. In our research, fetal macrosomia was observed in 9.7% of women in the control group and 19.1% of women with GDM.
SFH and AC are two routine measurements in obstetrical departments. They have clinical significance for predicting infant size and as a reflection of the pregnant woman’s nutritional status for reference. These findings support the internal validation of the SFH chart, which may be implemented in the prenatal care of patients with diabetes and pregnancy [12]. But the reference shows that there is no evidence that SFH is useful to identify macrosomia [13]. The SFH measurement is primarily practiced to detect fetal intrauterine growth restriction (IUGR). Undiagnosed IUGR may lead to fetal death, as well as increased perinatal mortality and morbidity [23].
To our knowledge, this is the first time that the notion of combining SFH and AC to calculate the ISFHAC was put forth as a new indicator of pregnancy outcome.
Regarding the AUCs of different parameters, the AUC for the ISFHAC is the largest among the NP and GDM groups. Thus, we think that the relationship between the ISFHAC and macrosomia is relevant. In this study, the cutoff points for the ISFHAC are 37 and 41.7 in the control and GDM groups, respectively. Women in the high bin of the index were prone to adverse pregnancy outcomes. Interestingly, 41.7 was the lower bound of the ISFHAC, which is consisted with obesity in GDM, and 37 was the lower bound of the ISFHAC in the control group, which is also in accordance with obesity. In analysis group, our results indicated that ISFHAC is superior to other parameters (e.g. BMI) for prediction macrosomia. Thus, we only analyzed the new index in the validation group.
We were interested in the high index group. Here, the high ISFHAC predicted (75.9%) most of the macrosomia cases in the GDM group, and this rate was higher than that of the obesity-based grouping (60.1%).
In the NP group, the high ISFHAC predict 81.3% of macrosomia cases, and obesity predicted 25% of macrosomia. The high ISFHAC prediction ability for macrosomia was better than that of the obesity-based grouping.
In another validation dataset, the high ISFHAC predicted most of the macrosomia cases in the NP and GDM groups. High ISFHAC was a risk factor for macrosomia.
All measures used should aim to prevent excessive SFH and AC, and the high ISFHAC group needs exercise or dietary intervention. Chinese GDM prevention and treatment programs should target overweight and obese adults with central obesity. Pregnancy SFH and AC control is an important target to reduce the risk of an adverse perinatal outcome in a subsequent pregnancy. SFH and AC were constantly been used as a marker for the fetal weight, but they were useless to identify macrosomia [13]. The combining these two parameters (SFH, AC) may also have limitations. Adipose panniculus may reflect the SFH and AC, which would be positively associated with obesity-related adverse pregnancy outcomes. Thus, the new index has a potential to improve for our future research.
Ultrasound is not the routine examination. In addition, ultrasound measurements are routinely performed on all pregnant women at 18–22 weeks gestation as a screening tool for fetal anomalies. A simple clinical risk score may help obstetrician suspect macrosomia at the time of delivery in remote areas where antenatal care services are less than adequate [24].
There may be some limitations in this study. Although this study includes a large sample size it contains only patients from a single tertiary hospital and thus cannot represent the total population. Future studies would have to determine the effects of factors, for example, using different hospital data, selecting patients who choose different occupations from different regions.
Consequently, this study provides evidence that ISFHAC is more strongly associated with the risk of macrosomia than BMI. It is possible that the ISFHAC might be useful as a surrogate for developing adverse pregnancy outcomes, such as in predicting macrosomia. To further confirm our results, Future studies are warranted to predict fetal weight in different GA groups. We hope to provide the ISFHAC chart using the index at different GAs to predict fetal weight.