Correlation of low birth weight with infertility and ART treatment: single-center cohort analysis of 7697 singleton live births.

Among the eligible participants in this study, a total of 7,697 women who underwent IVF/ICSI treatment and achieved their first singleton live birth were included based on the predefined criteria. Comprehensive details pertaining to the selection process, encompassing the number of cycles and rationales for inclusion or exclusion, are available in Fig.  1 . Fig. 1 Flow chart of patients enrollment Flow chart of patients enrollment The indications of patient and cycle characteristics were summarized in Table  1 . Among all participants, 3,867 (50.24%) experienced primary infertility, while 3,830 (49.76%) had secondary infertility. In terms of diagnosis, tubal factors accounted for the majority of cases (52.50%), followed by male factors (21.33%), ovulatory dysfunction (11.15%), other factors (10.19%), and endometriosis (4.83%). In this study, the long protocol was the most commonly used ovarian stimulation protocol (70.46%), followed by the GnRH antagonist protocol (7.56%), with the remaining protocols comprising 21.98% of the total. In terms of fertilization methods, IVF was utilized in 82.73% of cycles, followed by ICSI in 13.88%, and a combination of IVF and ICSI in 3.39%. Among all cycles, 3,598 (46.75%) were fresh cycles, while 4,099 (53.25%) were frozen cycles. The proportion of transferred blastocysts was comparable to that of cleavage embryos (52.92% vs. 47.08%), and a similar distribution was observed for the number of transferred embryos (50.95% vs. 49.05%). Vanishing multiple pregnancies accounted for 9.08% of all singleton live births, and the male-to-female infant ratio was 1.10 (4,035 males to 3,662 females). Table 1 Patient and cycle characteristics of study participants Characteristics Value No. Of cases 7697 Maternal age (years) 30.40 ± 4.19 Paternal age (years) 31.27 ± 4.85 Maternal BMI (kg/m 2 ) 23.04 ± 3.47 Paternal BMI (kg/m 2 ) 25.28 ± 4.21 Type of infertility, n (%)  Primary infertility 3867 (50.24)  Secondary infertility 3830 (49.76) Infertility diagnosis, n (%)  Tubal factor 4041 (52.50)  Male factor 1642 (21.33)  Ovulatory dysfunction 858 (11.15)  Endometriosis 372(4.83)  Others 784 (10.19) COS protocol, n (%)  GnRH agonist protocol 5423 (70.46)  GnRH antagonist 582 (7.56)  Others 1692 (21.98) Method of Fertilization, n (%)  IVF 6368 (82.73)  ICSI 1068 (13.88)  IVF+ICSI 261 (3.39) AMH (ng/mL) 4.80 ± 2.80 Type of cycle, n (%)  Fresh cycle 3598 (46.75)  Frozen cycle 4099 (53.25) Stage of transfer embryo, n (%)  Cleavage embryo 4073 (52.92)  Blastocyst 3624 (47.08) Endometrial thickness (mm) 10.43 ± 2.40 No. of transferred embryo, n (%)  1 3922 (50.95)  2 3775(49.05) Type of pregnancy, n (%)  Singleton pregnancy 6998 (90.92)  Vanishing multiple pregnancy 699 (9.08) Baby gender, n (%)  Male 4035 (52.42)  Female 3662 (47.58) Abbreviations: BMI Body mass index, COS Controlled ovarian stimulation, IVF In vitro fertilization, ICSI Intracytoplasmic sperm injection, AMH Anti-Müllerian hormone Patient and cycle characteristics of study participants Abbreviations: BMI Body mass index, COS Controlled ovarian stimulation, IVF In vitro fertilization, ICSI Intracytoplasmic sperm injection, AMH Anti-Müllerian hormone The total rate of LBW among singleton live births after IVF/ICSI and embryo transfer was 5.81% (447/7,697). The LBW rate showed significant variations based on maternal BMI, endometrial thickness, type of pregnancy after transfer (singleton or multiple), and number of embryos transferred, as illustrated in Fig.  2 . The BMI was classified based on the recommendations provided by The Working Group on Obesity in China 13 . Low birth weight is associated with maternal characteristics, embryo transfer and type of pregnancy. More details can be found in the Supplementary Table. Patient and cycle factors affecting Low birth weight. Fig. 2 Low birth weight is associated with maternal characteristics, embryo transfer and type of pregnancy. Abbreviations: BMI: body mass index, LBW: low birth weight Low birth weight is associated with maternal characteristics, embryo transfer and type of pregnancy. Abbreviations: BMI: body mass index, LBW: low birth weight Factors associated with infertility and ART-related factors examined through multiple regression analysis, including maternal/paternal age, maternal/paternal BMI, type of infertility, infertility diagnosis, COS protocol, method of Fertilization, AMH, type of cycle, stage of transferred embryo, endometrial thickness, number of embryos transferred, type of pregnancy and baby gender. The results of logistic regression analysis, shown in Table  2 , revealed that the prevalence of LBW was significantly higher among singletons in the overweight group (BMI within 24–27.9 kg/m 2 , OR 1.391, 95% CI 1.118–1.731, P  = 0.003) and the obese group (BMI ≥ 28 kg/m 2 , OR 1.489, 95% CI 1.098–2.018, P  = 0.010) compared to the normal group (BMI within 18.5–23.9 kg/m 2 ). Conversely, there was an inverse relationship observed between endometrial thickness and the likelihood of LBW, with a significantly lower occurrence of LBW when the endometrial thickness exceeded 8 mm ( P  < 0.001). Table 2 Unadjusted and adjusted odds ratios of potential risk factors of low birth weight Variable Unadjusted analysis Adjusted analysis  Crude OR (95%CI) P value  Adjusted OR (95%CI) P value Maternal age (years) 0.360 0.543  < 35 Reference Reference  35–37 1.232 (0.915, 1.660) 0.170 1.188 (0.834, 1.694) 0.340  38–40 0.992 (0.624, 1.576) 0.972 1.152 (0.663, 2.001) 0.616  41–42 0.347 (0.085, 1.412) 0.139 0.394 (0.091, 1.710) 0.213  > 42 1.372 (0.323, 2.827) 0.668 1.398 (0.296, 2.609) 0.672 Paternal age (years) 0.317 0.448  < 35 Reference Reference  35–37 1.220 (0.911, 1.635) 0.182 1.136 (0.816, 1.581) 0.450  38–40 0.991 (0.657, 1.494) 0.965 0.930 (0.579, 1.496) 0.766  41–42 0.471 (0.192, 1.153) 0.099 0.463 (0.179–1.199) 0.113  > 42 1.030 (0.569, 1.863) 0.923 1.068 (0.540, 2.111) 0.849 Maternal BMI (kg/m 2 ) 0.001 0.001  18.5–23.9 Reference Reference  < 18.5 0.740 (0.459, 1.191) 0.215 0.753 (0.466, 1.217) 0.247  24-27.9 1.391 (1.118, 1.731) 0.003 1.421 (1.139, 1.772) 0.002  ≥ 28 1.489 (1.098, 2.018) 0.010 1.470 (1.080, 2.000) 0.014 P for trend 0.003 Paternal BMI (kg/m 2 ) 0.903 0.933  18.5–23.9 Reference Reference  < 18.5 1.041 (0.501, 2.166) 0.914 1.092 (0.522, 2.284) 0.815  24-27.9 1.080 (0.868, 1.345) 0.488 1.075 (0.862, 1.341) 0.521  ≥ 28 1.082 (0.830, 1.411) 0.558 1.052 (0.805, 1.375) 0.709 Type of infertility  Primary infertility Reference Reference  Secondary infertility 0.932 (0.770, 1.128) 0.469 0.849 (0.690, 1.045) 0.123 Infertility diagnosis 0.184 0.867  Tubal factor Reference Reference  Male factor 0.824 (0.619, 1.097) 0.171 0.957 (0.673, 1.362) 0.808  Ovulatory dysfunction 1.021 (0.730, 1.429) 0.903 0.347 (0.047, 2.545) 0.298  Endometriosis 0.326 (0.045, 2.372) 0.268 1.032 (0.758, 1.404) 0.842  Others 0.985 (0.779, 1.245) 0.901 1.041 (0.782, 1.386) 0.774 COS protocol 0.737 0.865  GnRH agonist protocol Reference Reference  GnRH antagonist 0.891 (0.610, 1.302) 0.552 0.902 (0.608, 1.338) 0.609  Others 0.932 (0.736, 1.181) 0.559 1.014 (0.743, 1.385) 0.928 Method of Fertilization 0.355 0.837  IVF Reference Reference  ICSI 0.821 (0.611, 1.102) 0.189 0.534 (0.067, 4.218) 0.552  IVF+ICSI 0.824 (0.467, 1.452) 0.503 0.535 (0.064, 4.481) 0.564 AMH (ng/mL) 0.442 0.362   4.5 1.281 (0.874, 1.878) 0.204 1.344 (0.895, 2.020) 0.154 Type of cycle  Fresh cycle Reference Reference  Frozen cycle 0.990 (0.818, 1.199) 0.918 0.913 (0.722, 1.154) 0.448 Stage of transferred embryo  Cleavage embryo Reference Reference  Blastocyst 0.879 (0.725, 1.065) 0.189 1.001 (0.765, 1.310) 0.994 Endometrial thickness (mm) < 0.001 < 0.001  < 8 Reference Reference  8–12 0.526 (0.385, 0.719) < 0.001 0.500 (0.363, 0.689)  12 0.477 (0.346, 0.657) < 0.001 0.432 (0.308, 0.604) < 0.001 P for trend < 0.001 Number of embryos transferred  1 Reference Reference  2 1.303 (1.075, 1.579) 0.007 1.119 (0.859, 1.456) 0.405 Type of pregnancy  Singleton Reference Reference  Multiple 2.103 (1.617, 2.734) < 0.001 1.946 (1.462, 2.589) < 0.001 Baby gender  Male Reference Reference  Female 1.082 (0.894, 1.310) 0.416 1.061 (0.875, 1.286) 0.550 Abbreviations: BMI Body mass index, COS Controlled ovarian stimulation, IVF In vitro fertilization, ICSI Intracytoplasmic sperm injection, AMH Anti-Müllerian hormone Unadjusted and adjusted odds ratios of potential risk factors of low birth weight Abbreviations: BMI Body mass index, COS Controlled ovarian stimulation, IVF In vitro fertilization, ICSI Intracytoplasmic sperm injection, AMH Anti-Müllerian hormone Our unadjusted analysis revealed that the rate of LBW was significantly higher in singletons resulting from vanishing pregnancies achieved through ARTs in the first trimester compared to single pregnancies. The OR was 2.103, with a 95% CI of 1.617–2.734, and a p -value of less than 0.001. In our adjusted analysis, patients with vanishing pregnancies had a nearly doubled higher risk of LBW (OR 1.946, 95% CI 1.462–2.589, P  < 0.001). When compared to patients with a normal BMI, patients with BMI between 24 and 27.9 kg/m2 (OR 1.421, 95% CI 1.139–1.772, P  = 0.002) and BMI ≥ 28 kg/m2 (OR 1.470, 95% CI 1.080-2.000, P  = 0.014) had a higher risk of LBW. In comparison to the EMT < 8 mm group, the EMT between 8 and 12 mm group (OR 0.500, 95% CI 0.363–0.689, P   12 mm group (OR 0.432, 95% CI 0.308–0.604, P  < 0.001) had a lower risk of LBW. Smoothing fitted curves were applied to determine the relationship between maternal BMI, endometrial thickness, and LBW, as depicted in supplementary Figure. Although transferring two embryos initially showed higher LBW risks in the logistic regression analysis (OR 1.303, 95% CI 1.075–1.594, P  = 0.007), the association between transferring two embryos and LBW became insignificant after adjusting for potential confounding factors (OR 1.119, 95% CI 0.859–1.456, P  = 0.405). The nomogram of the model is depicted in Fig.  3 , including all the significant parameters analyzed previously. Each parameter was assigned a vertical extension (refer to the top points bar) individually. The total score was acquired by summing up the scales of each factor. The overall point projected on the bottom scale suggests the likelihood of a suboptimal response. Fig. 3 Nomogram for predicting the LBW incidence of IVF patients. The points for each variable were calculated by drawing a vertical line from the value to the axis labeled “Total Points”. The total score corresponds to the probability of a suboptimal response in the lowest axis Nomogram for predicting the LBW incidence of IVF patients. The points for each variable were calculated by drawing a vertical line from the value to the axis labeled “Total Points”. The total score corresponds to the probability of a suboptimal response in the lowest axis

Data for this retrospective cohort study was collected from the Reproductive Medicine Center at Henan Provincial People’s Hospital. The study protocol was approved by the Institutional Review Board of the Ethics Committee in the hospital (approval number SYSZ-LL-2021091501). All participants provided consent for their medical record data to be used anonymously for research purposes and signed informed consent forms. The study included only patients with reproductive age (20 ~ 45 years old ) who had their first singleton live birth through IVF/ICSI treatment at the Reproductive Medicine Center of Henan Provincial People’s Hospital between January 2016 and December 2020. Patients with stillbirths, multiple live births, preimplantation genetic testing, egg donation or sperm donation, mocrosomia or incomplete records were excluded from the study. The same team conducted controlled ovulation stimulation (COS) protocols for the study. These protocols included the gonadotropin-releasing hormone (GnRH) agonist protocol, GnRH antagonist protocol, progestin-primed ovarian stimulation (PPOS) protocol, mild-stimulation protocol, and natural cycle, which were selected based on each patient’s condition. The GnRH agonist protocol and GnRH antagonist protocol were used for normal responders and high responders, while all protocols except the GnRH agonist protocol were allowed for low responders. The dose of gonadotropin (Gn), ranging from 75 to 300 IU, was administered for ovarian stimulation based on factors such as the patient’s age, ovarian reserve, body mass index (BMI), and anti-Mullerian hormone (AMH) level. The dose of Gn was adjusted according to the response of the follicles. Once at least two follicles measured ≥ 18 mm or three follicles measured ≥ 17 mm, a dose of 4000 to 10,000 IU of urinary human chorionic gonadotropin (hCG) was administered, with or without GnRH agonist, to induce ovulation, taking into consideration the peak estradiol level and age. Vaginal ultrasound-guided oocyte retrieval took place 34 to 37 h later. Subsequently, either conventional IVF or intracytoplasmic sperm injection (ICSI) was performed approximately 4 to 6 h after oocyte retrieval, depending on the semen quality. Fresh embryo transfer occurred on day 3 to 5 following oocyte retrieval. In cases where patients froze all embryos or did not achieve a live birth after embryo transfer but still had surplus embryos, frozen embryo transfer was performed following standard practices at our center. Further details regarding endometrial preparation and luteal support procedures can be found in a previous study [ 12 ]. Singleton live birth was defined as the complete expulsion or extraction of a product of conception from the mother, regardless of the duration of the pregnancy.The birth weight of the newborns was recorded in grams, and a birth weight below 2500 g (up to and including 2499 g) was considered as low birth weight. The LBW rate served as the primary outcome measure for this study [ 13 ]. The classification of BMI was based on the criteria established by the China Obesity Task Force, which defines overweight as a BMI of ≥ 24 kg/m² and obesity as a BMI of ≥ 28 kg/m² [ 14 ]. The statistical analysis was performed using SPSS 24.0 (IBM, Chicago, IL, USA). Continuous variables were reported as means ± standard deviations, and the student’s t-test was used to compare differences between the two groups. Categorical data were presented as frequencies and percentages, and the chi-square test was employed to assess differences. Univariate and multivariate logistic regression analyses were conducted to examine the association between the variables and LBW. Smooth curve fitting was utilized to evaluate the linear relationship between BMI/endometrium thickness (EMT) and LBW outcomes. A P -value of less than 0.05 was considered statistically significant. Furthermore, a nomogram was created to offer graphical representations of the selected factors and to facilitate users in calculating probabilities.

The use of assisted reproductive technology (ART) has increased as more couples seek fertility treatment. Since the first successful in vitro fertilization (IVF) birth in 1978, over 10 million infants have been born through ART [ 1 , 2 ], offering hope to infertile couples. However, concerns persist regarding the health and development of children conceived through ART [ 3 ], which encompasses techniques such as IVF, intracytoplasmic sperm injection (ICSI) and cryopreservation. Compared to naturally conceived children, those conceived through ART have higher rates of adverse birth outcomes, including a greater likelihood of LBW [ 4 , 5 ]. This increased risk is partly due to the higher incidence of multiple births in ART pregnancies [ 6 , 7 ]. Yet, it remains unclear how much of the remaining difference in birth outcomes is attributed to the reproductive technology itself or factors related to infertility, which is known to increase the risk of poor birth outcomes [ 8 ]. Understanding this distinction is crucial for developing targeted interventions to improve birth outcomes for ART-conceived infants. Current literature highlights the higher risk of LBW in ART babies, but the exact contributions of ART procedures versus underlying infertility remain ambiguous. The differentiation is crucial because it influences clinical approaches and counseling for infertile couples considering. Registry-based studies [ 9 – 11 ] have provided population-level insights but often lack the granularity needed to pinpoint specific clinical factors due to variations in data quality and completeness across different institutions. To address these limitations, our study utilized detailed electronic medical records (EMRs) from a single institution. EMRs offer rich, individual-specific clinical data, allowing for comprehensive analyses and the ability to track longitudinal health outcomes. This study used EMRs from both the reproductive and obstetric departments of the same hospital, ensuring consistent data collection and assessment. By performing all ART procedures at a single reproductive medicine institution with standardized clinical and laboratory protocols, we minimized variability and bias, enhancing the reliability of our findings. This study aims to dissect the underlying causes of the increased risk of LBW in infants conceived through ART by focusing on two primary aspects: infertility diagnosis and ART treatment. By differentiating between the contributions of infertility itself and the ART procedures to the risk of LBW, our study aims to clarify whether the elevated risk is primarily due to underlying infertility or the ART treatments. This distinction is crucial for developing targeted interventions to mitigate the risk of LBW. For instance, if specific infertility diagnoses are strongly linked to LBW, tailored pre-conception care and treatment modifications can be implemented. Conversely, if ART procedures are found to be the primary risk drivers, refining these techniques could improve birth outcomes. The findings will inform clinical practices, enhancing the care and counseling provided to couples undergoing infertility treatment and potentially improving neonatal outcomes.

This study represents our initial endeavor to conduct a comprehensive root cause analysis of LBW in infants associated with infertility treatment. Our primary objective was to discern the distinct impact of patient and cycle characteristics from specific ART procedures. This retrospective cohort study revealed that the LBW rate was 5.81% among 7,697 singleton live births conceived through infertility treatment. Through univariate and multivariate logistic regression analyses, maternal BMI, EMT, and vanishing multiple pregnancy were independent risk factors for LBW in singleton live infants. Specifically, a significantly higher incidence of LBW was observed when the mother had a pre-pregnancy BMI indicating overweight or obesity, or when the estimated EMT measured less than 8 mm. Through ongoing root cause analysis, a key trend identified is that maternal BMI is a primary factor contributing to LBW in IVF children. The proportions of underweight, normal weight, overweight and obese women were 6.33%, 59.67%, 24.54%, and 9.46%, respectively. Surprisingly, individuals with obesity, as indicated by high maternal BMI, have a significantly higher probability of experiencing an elevated rate of LBW, contrary to what might be expected, not paternal BMI. The prevalence of overweight and obesity has risen sharply over the past four decades and has become a major global public health concern. The latest national prevalence estimates showed that overweight individuals accounted for 34.3% of all adults, while 16.4% of adults were obese [ 15 ]. Numerous studies show pre-pregnancy overweight or obese women are at a higher risk of cesarean section, gestational diabetes, gestational hypertension, postpartum hemorrhage, etc [ 16 – 18 ]., and their infants are more likely to be stillbirth, large for gestational age, macrosomia, admitted to the neonatal intensive care unit and LBW [ 18 – 22 ]. Interestingly, a study found that a 60-day weight reduction intervention prior to IVF/ICSI could significantly increase neonatal birth weight in overweight or obese infertile women ( P < 0.001) [ 23 ]. Here, based on our finding, it is worthwhile emphasizing to establish appropriate strategies for either BMI management prior to initiation of infertility treatment or as part of treatment plan. The mechanisms linking maternal BMI to LBW in newborns are not yet fully understood. In addition to genetic factors, placental function, maternal nutrition, and nutrient transfer from mother to fetus are considered key factors influencing fetal growth [ 24 , 25 ]. Considering the direct impact of the endometrium on LBW, previous studies have consistently emphasized the significance of EMT in relation to LBW outcomes [ 26 ]. In our analysis, after adjusting for confounding factors, we observed a significant decrease in the LBW rate among two groups: the group with EMT between 8 and 12 mm (OR 0.500; 95% CI 0.363–0.689, P < 0.001) and the group with EMT greater than 12 mm (OR 0.432; 95% CI 0.308–0.604, P < 0.001), compared to the reference group with EMT < 8 mm. These studies have consistently shown that embryos transferred to a thinner endometrium are associated with a higher likelihood of LBW. This association remains consistent irrespective of whether the embryo transfer is conducted in a fresh cycle [ 27 ] or a frozen cycle [ 28 ]. The unfavorable outcomes related to LBW, as supported by our findings and other reports [ 29 ], indicate the critical role of the endometrium in the development and growth of the fetus. A thinner endometrium may influence fetal growth and weight by impairing angiogenesis and reducing placental blood flow [ 30 ]. Therefore, patients with a thin endometrium should receive special attention to grow a perfect endometrium to ensure it is sufficiently thick to give the best chance of success before considering embryo transfer, aimed of improving both pregnancy outcomes and reducing the risk of LBW. Next aspect that connects to LBW is the occurrence of LBW associated with vanishing pregnancies [ 31 ]. Reducing the rate of multiple pregnancies is a globally laudable goal. However, singletons born after ART are still more susceptible to adverse perinatal outcomes compared to spontaneously-conceived singletons [ 8 , 32 ]. In 2017, Martin et al. reported that the incidence of LBW in singletons was correlated with the number of transferred embryos 6 . In our initial univariate analysis, we found that both transferring two embryos and vanishing multiple pregnancy were associated with an increased risk of LBW. However, in our subsequent multivariate regression analysis, where we accounted for confounding factors, we discovered that only vanishing multiple pregnancy remained a significant risk factor for LBW, suggesting that vanishing multiple pregnancy itself, rather than the number of embryos transferred, is the primary factor contributing to the increased risk of LBW in our study population. Other study also found that singleton live births with vanishing pregnancies had a higher risk of LBW in both fresh and frozen cycles [ 33 , 34 ], which was similar or consistent with our results, indicating that the disappearance of an embryo in vanishing pregnancies has a negative impact on the surviving embryo, leading to intrauterine growth disturbances in the surviving singleton. Our results are consistent with other studies in that vanishing pregnancies carry a higher risk of LBW [ 33 , 35 , 36 ]. A possible underlying mechanism may be related to the aberrant function of the placenta or inflammatory cytokines. The survived twin placenta is impaired due to blood shunting from vascular anastomoses [ 37 ]. Moreover, cytokines released from the vanishing twin may influence placental function and the growth of the surviving fetus, which ultimately leads to a reduction in birth weight [ 38 ]. As a consequence, guidelines have been issued on addressing the maximal number of embryos for transfer to promote success and limit the risk of multiple gestation. Nowadays, elective single embryo transfer is being universally promoted [ 39 ]. The results of this study lay a theoretical foundation for meaningful clinical practices to further enhance children safety following ART treatment. The strengths of our study include the large number data from EMRs in a single reproductive center. EMRs from standardized clinical and laboratory protocols were implemented to balance personalized infertility treatment and evidence-based practices. Performing all IVF procedures at a single reproductive medicine institution with standardized laboratory factors minimized bias. Though multicenter data typically involve a large number of participants, different centers may have different protocols, equipment, expertise levels, and patient populations, leading to heterogeneity in the data challenging to draw definitive conclusions or establish cause-effect relationships. However, there are some limitations in this study that need to be taken into account. To begin, this was a single institutional retrospective cohort study, and some confounders during pregnancy were not adjusted for, which may have impacted our results. Secondly, this study only explored the risk factors of LBW and the mechanisms by which these risk factors affect the incidence of LBW were not assessed. Additionally, because multiple factors influence birth weight, not all potential variables—such as maternal smoking—were included in this study. Moreover, BMI was classified according to Chinese criteria rather than the WHO classification system. In the future, well-designed studies with in-depth exploration may shed more light on this issue. Nonetheless, there may be biases related to the effects of extend embryo culture resulted zone hardening and embryo splitting as well as epigenetic modifications. These factors can influence pregnancy outcomes but were not specifically addressed in this study. Moreover, while vanishing pregnancies generally exhibit poorer pregnancy outcomes, this study does not provide a clear understanding of whether the vanishing pregnancy is solely related to the ART itself, the underlying infertility condition, or other IVF-related factors such as the type of cycle (fresh or frozen) or specific stimulation protocols.

In summary, this study identified three main risk factors associated with LBW in infants conceived through ARTs: maternal BMI, EMT, and vanishing multiple pregnanc, highlighting the importance of preconception weight optimization and appropriate transfer strategy to improve neonatal outcomes.

Below is the link to the electronic supplementary material. Supplementary Material 1. Supplementary Material 1. Supplementary Material 2. Supplementary Material 2.