In recent decades, China has experienced changes in dietary intake and decreased physical activity [16]. The report released in China shows that 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 that 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 obese.
A higher BMI, AC, and fasting glucose in the first trimester of pregnancy increased the GDM risk [19]. Excessive gestational weight gain, according to the targets set by the Institute of Medicine (IOM), was associated with caesarean 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, that this percentage was 1.96-fold that of the 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 foetal macrosomia (the main outcome) was significantly higher in the GDM group (20.0%) than in the control group (3.6%) [22]. In our research, foetal macrosomia was observed in 9.7% of women in the control group and in 19.1% of women with GDM.
Antenatal care was important for the maternal and foetal outcomes, and 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. 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]. However, one reference shows that there is no evidence that SFH is useful to identify macrosomia [13]. The SFH measurement is primarily used to detect foetal intrauterine growth restriction (IUGR). Undiagnosed IUGR may lead to foetal death, as well as to 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 has been put forth as an indicator of pregnancy outcome.
Regarding the AUCs of different parameters, the AUC for the ISFHAC was 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 cut-off points for the ISFHAC were 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 consistent 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 the analysis group, our results indicated that the ISFHAC is superior to other parameters (e.g., BMI) for predicting macrosomia. Thus, we only analysed 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 predicted 81.3% of macrosomia cases, and obesity predicted 25% of macrosomia cases. The high ISFHAC prediction ability for macrosomia was better than that of the obesity-based grouping.
In another validation dataset, a high ISFHAC predicted most of the macrosomia cases in the NP and GDM groups. A high ISFHAC was a risk factor for macrosomia.
All measures used should aim to prevent an excessive SFH and AC, and the high ISFHAC group needs exercise or dietary intervention. Chinese GDM prevention and treatment programmes should target overweight and obese adults with central obesity. Pregnancy SFH and AC control is an important method for reducing the risk of an adverse perinatal outcome in a subsequent pregnancy. SFH and AC are constantly used as indicators of foetal weight, but they are useless for identifying macrosomia [13]. Combining these two parameters (SFH and AC) may also have limitations. Adipose panniculus may reflect SFH and AC, which would be positively associated with obesity-related adverse pregnancy outcomes. Thus, the new index has the potential to improve our future research.
Ultrasound is not a routine examination. In addition, ultrasound measurements are routinely performed on all pregnant women at 18–22 weeks gestation as a screening tool for foetal anomalies. A simple clinical risk score may help obstetricians predict 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 need to determine the effects of various factors, for example, using different hospital data and selecting patients who choose different occupations from different regions.
Consequently, this study provides evidence that the 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 foetal weight in different GA groups. We hope to provide an ISFHAC chart using the index at different GAs to predict foetal weight.