Written informed consent was obtained from all study participants and the research approval was obtained from the Institutional Ethics Committee of Kasturba Medical College, Mangalore (IEC KMC MLR 10-19/492).

This study was conducted at 2 tertiary care centers and teaching hospitals affiliated with Kasturba Medical College, Mangalore, located in the state of Karnataka, the southern part of India. The study included the maternal – neonatal pair admitted during the study period (September 2019–September 2021). Primigravida with single intrauterine gestation and term neonates delivered via normal vaginal delivery were included in the study. Mothers with underlying comorbidities and no documented anthropometric values during pregnancy as well as neonates requiring resuscitation or neonatal intensive care unit stay were excluded from our study.

Prepregnancy weight, gestational age from first-trimester ultrasonography and underlying illnesses (e.g., gestational, and overt diabetes, hypertension-chronic and pregnancy-induced, thyroid disorders) were obtained from medical records. Maternal height was documented during their first-trimester visit using a stadiometer through a standard measurement technique. Body mass index was calculated and interpreted using the World Health Organization BMI chart for the Asian population [17]. The date and time of birth of the newborn were obtained from neonatal records. Birth weight was measured in grams using an electronic weighing machine after calibrating to zero. Gestational age documented in the maternal records was confirmed using New Modified Ballard’s score to include only term neonates [18].

With the help of pre-BMI, the study population was grouped into 3 groups-underweight (BMI<18.5 kg/m²), normal (BMI=18.5–24.9 kg/m²) and overweight (BMI≥25 kg/m²) groups. GWG in every trimester was obtained from the antenatal records, and we calculated the total GWG (GWG-T) and RWG during pregnancy, then categorized using American College of Obstetricians and Gynaecologists/IOM guidelines [19] into 3 groups, GWG less than or more than or equal to IOM recommendations (GWG<IOM, GWG>IOM, and GWG= IOM).

According to gestational age and birth weight, the babies were classified as small/appropriate/large for gestational age (SGA/AGA/LGA) using Lubchenco's charts [20]. Birth weight below 2,500 g was considered LBW, and above 4,000 g was considered macrosomia.

Cord blood was obtained from newborns in the delivery room after enrolling the mothers in the study with written informed consent. Blood was collected from the umbilical vein using a 22G needle and syringe under sterile aseptic precautions. Serum was obtained after centrifugation at 4.000 rpm and was stored frozen in micro vials at -60 degrees centigrade for analysis. Serum cortisol was measured using the DRG Cortisol ELISA kit. Lipid levels of total cholesterol (TC), HDL-C, triglycerides (TG) were analyzed using an auto-analyzer, and low-density lipoprotein cholesterol (LDL-C) and very-low-density lipoprotein cholesterol (VLDL-C) were mathematically calculated using the Friedwald formula. A total of 169 samples were collected and among the 169 lipid samples processed, 51 (30%) values had to be discarded from the study. Because the Friedwald formula has its limitations at very low LDL-C or very high TG concentrations, resulting in negative LDL-C values and as there are no reference levels for cord blood lipid concentration have been established in the literature, those values had to be discarded for the sake of reliability, comparability, and consistency of our results [21]. One hundred sixty-nine cord blood cortisol and 118 cord blood lipid levels were analyzed.

We represented the continuous variables, i.e., cortisol and lipid levels, by median and interquartile range, and categorical variables using frequency and percentage. After stratifying the variables into 3 groups based on pre-BMI and GWG/IOM, their differences were tested using 1-way analysis of variance with Tukey B. Karl Pearson correlation coefficient was used to find the correlation between pre-BMI, RWG, GWG, cortisol, and lipid levels, and their relationship was tested using multiple variable linear regression analysis.

Mediation analysis was conducted to investigate the extent of association between maternal pre-BMI and GWG with birth weight using cord blood cortisol. It was performed with SPSS PROCESS MACRO with cortisol (M variable), pre-BMI/GWG/RWG (X variable), and birth weight (Y variable). Total effect (TE), direct effect (DE) and indirect effects (IE) were estimated. The proportion of mediation is IE divided by TE.

All statistical analyses were done using IBM SPSS Statistics ver. 25.0 (IBM Co., Armonk, NY, USA). A P value of <0.05 was considered statistically significant for a 2-tailed test.

The baseline characteristics of the study population stratified based on pre-BMI are represented in Table 1. We found that the median GWG of the normal BMI group was 12.0 kg (10.0–13.5 kg) with a median age of 26 years (23–29 years). Among the 3 groups, there was a statistically significant difference in total GWG and the RWG. There was a rising trend in GWG and RWG from the underweight group up to the overweight group (P<0.001).

Most of the newborns had a birth weight appropriate for their gestational age. Overall, there was a significant difference in birth weight among the 3 BMI groups, however, there was no statistical significance in birth weight between the normal and overweight groups when looked at it separately (P=0.44). In the overweight group, there was a predominance of LGA babies with a specific predilection for the female sex (0% vs. 13% vs. 26%, P<0.001).

We observed that for every unit increase in maternal pre-BMI, birth weight increased by 90.50 g (95% confidence interval [CI], 71.019–110.00) (P<0.001), and for each kilogram rise in gestational weight, birth weight increased by 128.44 g (95% CI, 109.761–147.119) (P<0.001) as depicted in Table 2.

Cord blood cortisol concentration among the 3 groups was stratified based on pre-BMI and GWG/IOM guidelines. A median value of 381.0 ng/dL (196.0–617.0 ng/dL) in the overweight group and 332.0 ng/dL (192.0–598.25 ng/dL) in GWG> IOM was noted. We observed no significant difference in cortisol levels among the 3 BMI groups (P=0.56) and the GWG/IOM groups (P=0.63). From our study, no significant correlation was found between the maternal pre-BMI, GWG, and the birth weight of the newborn with cord blood cortisol levels.

Mediation analysis was carried out to determine the proportion of association between maternal pre-BMI, GWG-T, RWG and birth weight by cord blood cortisol concentration. As revealed in Fig. 2, cord blood cortisol had no significant effect on mediation between maternal pre-BMI/GWG/RWG and birth weight. Hence, the proportion of mediation cannot be established. This indicates that cortisol does not mediate the association between maternal pre-BMI/GWG/RWG and birth weight.

The cord blood lipid levels stratified by pre-BMI and GWG/IOM showed no significant difference among the 3 groups. Maternal pre-BMI (20 kg/m² [18–23 kg/m²]) and birth weight had a significant negative correlation with HDL-C levels (53 mg/dL [44–63 mg/dL]) as shown in Table 3. That is for every unit increase in maternal pre-BMI, HDL-C is reduced by 1.1 mg/ dL (95% CI, 1.99 to -0.201) (P=0.017), and for every 100-g increase in birth weight, HDL-C decreased by 0.6 mg/dL (95% CI, 0.011–0.0001) (P=0.046)

In our study, a significant positive correlation was found between cord blood lipid levels and cord blood cortisol levels except for LDL-C. For every unit increase in cortisol (340 ng/dL [249–463 ng/dL]), there was an increase in HDL-C, TG, TC, and VLDL-C levels (P<0.05) as depicted in Table 4.

Although changes in lipid parameters with an increase in cortisol were not in the clinically significant range, a positive correlation has been identified signifying cortisol levels play a pivotal role in controlling fetal lipid homeostasis.