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Pre-pregnancy BMI modifies the associations between triglyceride–glucose index in early pregnancy and adverse perinatal outcomes: a 5-year cohort study of 67,936 women in China

Diabetology & Metabolic Syndrome volume 16, Article number: 311 (2024) Cite this article

Abstract

Background

Triglyceride-glucose (TyG) index was suggested as a possible surrogate for insulin resistance and a predictor for cardiovascular diseases and diabetes in the non-pregnant population. However, the relationship between TyG index in early pregnancy and adverse pregnancy outcomes (APOs), and the contribution of pre-pregnancy body mass index (BMI) was still illusive.

Methods

A large retrospective cohort study involving 67,936 pregnant Chinese women between 2017 and 2022 was conducted. Data collection and laboratory tests were performed during the usual patient care. TyG index was calculated using ln [fasting plasma triglyceride (TG; mmol/L) × 88.5 × glucose (FPG; mmol/L) × 18.02/2]. Multivariable logistic regression models were applied to explore the relationship between TyG index and APOs. Interaction and stratification analyses were performed to assess the influence of pre-pregnancy BMI on the association. In addition, ROC curves were used to evaluate the potential predictive value of the TyG index and pre-pregnancy BMI.

Results

Positive associations between maternal early pregnancy TyG index and APOs, including gestational diabetes mellitus (GDM), hypertensive disorders of pregnancy (HDP), large for gestational age (LGA) and preterm birth (PTB) were demonstrated (all P < 0.001). Besides, there was a significant interaction effect of maternal pre-pregnancy BMI and TyG on the risk of GDM, HDP and LGA (P < 0.05). Women of pre-pregnancy overweight/obesity (OWO) with TyG index in the fourth quartile were at an increased risk for GDM [adjusted OR (aOR) and 95% CI, 3.82 (3.14–4.64)], HDP [aOR 95% CI, 1.34 (1.10–1.64)], for LGA [aOR 95% CI, 1.78 (1.44–2.19)], and PTB [aOR 95% CI, 1.53 (1.11–2.09)], compared with OWO mothers with TyG in the lowest quartile. In addition, the combination of BMI and TyG enhanced predictive performance for APOs, particularly in women with normal plasma TG and FPG levels.

Conclusions

Dose–response relationships were identified between elevated maternal TyG index in early pregnancy and APOs. A combination of early pregnancy TyG index and pre-pregnancy BMI may provide predictive value for APOs, even in low-risk women. Thus, early screening of fasting blood lipids and glucose simultaneously may be useful and convenient for the early identification of APOs, both among OWO and low-risk normal-weight women.

Background

Adverse pregnancy outcomes (APOs) affect approximately 30% of women during gestation [1, 2]. Gestational diabetes mellitus (GDM) is characterized by impaired maternal glucose tolerance which is onset during pregnancy [3]. Over the last few years, the prevalence of GDM has been on the rise worldwide, and it affects nearly 14.8% of Chinese pregnant women [4]. It deteriorates the well-being of maternity and fetuses, leading to preeclampsia, macrosomia, and perinatal mortality [5]. It also increases the risk of illnesses in the future, including hyperglycemia and metabolic disorders in both mothers and their offspring [6, 7]. Besides, mounting evidence suggested that other APOs, including hypertensive disorders of pregnancy (HDP), large for gestational age (LGA), and preterm birth (PTB), were also associated with higher risks of cardiometabolic disorders in the neonatal future lives [8,9,10,11,12,13]. Hereafter, timely identification of women at high risk for APOs is important in mitigating the negative consequences of current pregnancy and even the potential inter-generational transmission of metabolic disorders.

Pregnant women, who underwent metabolic burden and adaptation, are susceptible to insulin resistance (IR), which can lead to the onset of metabolic disorders, chronic inflammation, etc. [14]. The triglyceride-glucose (TyG) index, computed by a combination of fasting plasma glucose (FPG) and triglyceride (TG), was recently proposed as a surrogate marker for recognizing IR in the non-pregnant population [15]. This index was identified as a valuable predictor in stratifying the risks of metabolic disorders [16], atherosclerosis [17], and cardiovascular diseases [18]. Pregnancy is featured by multiple metabolic adaptions, including the development of insulin resistance (IR) which increases gradually throughout gestation. Studies have shown that elevated levels of certain steroid hormones (e.g., progesterone and corticosteroids) [19], and placental secretion of cytokines and hormones might be attributable to IR [20]. Maternal hypertriglyceridemia is regarded as an essential moderating variable of IR, commonly accompanied by dysglycemia. Wu et al. suggested increased maternal TG contributed to significantly elevated risks of GDM and HDP regardless of the glucose levels. Furthermore, maternal pre-pregnancy body mass index (BMI) has also been well associated with IR [21] as well as maternal and neonatal well-beings. However, the interplay between early-pregnancy TyG index and pre-pregnancy BMI remains unexplored. It is crucial to understand whether the association between maternal TyG index and APO is different in women with pre-pregnancy BMI status.

Based on a large hospital-based retrospective birth cohort study, the purposes of this study were to elucidate the dose–response relationship between the early pregnancy TyG index and risk of APOs (including GDM, HDP, LGA, and PTB), and whether these associations might differ in accordance with maternal pre-pregnancy BMI category. The findings may help obstetricians easily assess the risk of APOs in early pregnancy and implement prevention strategies accordingly.

Methods

Study design and participant inclusion

This large hospital-based cohort study was conducted at the International Peace Maternity and Child Health Hospital (IPMCH), a tertiary university-affiliated maternity center in Shanghai, China. We adopted 79,364 pregnant women who underwent first-trimester antenatal health visits and blood biochemistry tests and delivered between January 2017 and December 2022 with FBG and TG measurements. We excluded women with missing records of pre-pregnancy body-matrix index (BMI), and FBG and TG tests. Women with either condition including in vitro fertilization (IVF), multiple pregnancies, chromosome abnormality or fetal loss, pre-existing diabetes or hypertension, or a history of hyperlipidemia or hepatic steatosis were further excluded. As a result, a total of 67,936 women who gave birth to singleton babies were eligible for the final analysis. The participant flowchart is shown in Fig. S1 in the Supplementary Material. The study was approved by the Medical Ethics Committee of IPMCH (GKLW#2023-006). As a retrospective cohort study, written informed consent was waived following the principles of the Ethics Committee. The Strengthening the Reporting of Observational Studies in Epidemiology (STROBE) guideline was followed for presenting research results in this study.

Data retrieval from electronic medical records

Demographic and clinical biochemical test data were collected during routine prenatal hospital visits by experienced medical staff. Maternal characteristics, including age at pregnancy, parity, last menstrual period, educational status and disease history before pregnancy were collected via clinic interview at the first clinical visit. The pre-pregnancy BMI was calculated using nurse measurements of height during early pregnancy and self-reported pre-pregnancy weight by the women. The FPG and TG concentrations were assayed at the first antenatal screening visit between 9- and 14-week gestation using a commercial kit at the hospital’s accredited clinical laboratory. Data was extracted from electronic medical record systems by information technologists and cleaned by epidemiologists.

Diagnostic criteria

TyG index was calculated by using the following formula [18]: ln [fasting plasma TG (mmol/L) × 88.5 × glucose (mmol/L) × 18.02/2]. Diagnostic criteria of GDM followed the International Association of Diabetes and Pregnancy Study Groups (IADPSG) criteria, utilizing a 2-h oral glucose tolerance test (OGTT) by intaking 75 g glucose after 8–10 h of fasting at 24–28 weeks of gestation. The disease is diagnosed if one of the following criteria is reached: FBG reaches or above 5.1 mmol/L (92 mg/dL), the 1-h glucose level 10.0 mmol/L (180 mg/dL), or the 2-h glucose level 8.5 mmol/L (153 mg/dL) [3]. All tests were done in the same lab.

HDP was diagnosed in women with elevated blood pressure (systolic blood pressure ≥ 140 mmHg and/or a diastolic blood pressure ≥ 90 mmHg on two occasions at least 4 h apart) after 20 weeks in pregnancy [22], with or without proteinuria (≥300 mg protein in a 24-h urine sample or + on a urine dipstick). Preterm birth (PTB) was defined as delivery before 37 gestational weeks of [23].

LGA was defined as a birth weight above 90th percentile, adjusting for sex and gestational age, following the birth weight reference curve of Chinese neonates [24]. Pre-pregnancy BMI was categorized into 3 groups according to the Working Group on obesity in China [25]: underweight (BMI < 18.5 kg/m2), normal weight (18.5 kg/m2 ≤ BMI < 24.0 kg/m2), and overweight/obesity (OWO; BMI ≥ 24.0 kg/m2).

Statistical analysis

Statistical analyses were conducted using R Software (v4.3.2; R Project for Statistical Computing with open-source packages, including Table 1, ggplot2, rms, forestplot, etc.). Continuous variables in the demographic data with skewed distribution were presented as median [interquartile range (IQR)], and the normally distributed data were shown as mean (standard deviation). Categorical variables were presented as frequencies (percentages). Statistical tests were two-sided, with P < 0.05 considered statistically significant. For variables with missing data, imputation was performed using the missing forest method.

Table 1 Basic characteristics of study population (N = 67,936)
Full size table

The association between predefined TyG categories and APOs was examined using a multivariable logistic regression model. The adjusted odds ratio (OR) and 95% confidence interval (CI) were computed for APOs based on maternal early pregnancy TyG index compared with a reference group with a TyG index below P25. All these multivariable models were adjusted for maternal age, education level, parity, and health insurance status. These potential confounders were selected by considering its biological plausibility, and reports in previous studies.

In addition, we investigate the joint effect of maternal TyG index in early pregnancy and pre-pregnancy BMI on multiple APOs by adding a product interaction term for each of them to the model. A heatmap was constructed to show the differences in each APO. Furthermore, we analyzed the performance of pre-pregnancy BMI, FPG, TG, TyG, interaction term of TyG and pre-pregnancy BMI (TyG × BMI) by comparing their discriminative capabilities using the receiver operating characteristic (ROC) curve and calculating the area under the curve (AUC) in the test cohort (women delivered between January 2017 to December 2020) and the validation cohort (women delivered between January 2021 to December 2022).

For sensitivity analysis, we excluded women with either abnormal FPG [defined as FPG above 5.1 mmol/L (92 mg/dL) in early pregnancy], or TG [defined as TG above 1.7 mmol/L (150 mg/dL) in early pregnancy], and those with both conditions to further assess the association as well as potential predictive capability of early-pregnancy TyG on APOs.

Results

Basic characteristics of study population

The final study population consisted of 67,936 pregnant women. The baseline characteristics of the study population are presented in Table 1. In this study, the average maternal age (mean ± SD) was 31.0 ± 3.9 years, 12,667 (18.6%) women were 35 years old and above; the average pre-pregnancy BMI (mean ± SD) was 21.2 ± 2.7 kg/m2, 9487 (14.0%) women were underweight, and 9402 (13.9%) women were OWO. A total of 46,599 (68.6%) women were primiparous, 4655 (6.9%) were below college education, 52,305 (77.0%) held medical insurance.

The median (IQR) of FPG level was 4.6 (4.3–4.8) mmol/L, the median (IQR) of TG level was 1.2 (1.0–1.5) mmol/L, and the TyG index (mean ± SD) was 8.4 ± 0.4. The average fetal birthweight (mean ± SD) was 3309.5 ± 434.1 g, 35,043 (51.6%) fetal were male and 32,893 (48.4%) were female. A total of 10,680 (15.7%) women had GDM, 4104 (6.0%) women had HDP, 3449 (5.1%) fetuses were born PTB and 6021 (8.9%) fetuses were LGA.

Association between early pregnancy TyG index and the adverse pregnancy outcomes

After adjusting for potential confounders, the multivariable logistic models demonstrated significant positive relationships between continuous TyG index in early pregnancy and risk of all the APOs, including GDM, HDP, LGA, and PTB (all P < 0.001; Fig. 1). As shown in Fig. 2, the incidences of GDM, HDP, LGA and PTB in women with TyG index less than 25th percentile (P25) were 8.32, 4.22, 6.1 and 4.32%. And the ratios for GDM, HDP, LGA and PTB were 37.39, 11.71, 16.39 and 7.47% for women with TyG index above P95, respectively. Compared with women with TyG index < P25, the adjusted ORs (aORs) of GDM were as follows: P25 to P50 (1.46; 95% CI, 1.36–1.57), P50 to P75 (1.90; 95% CI, 1.77–2.04), P75 to P90 (2.59; 95% CI, 2.41–2.79), P90 to P95 (3.47; 95% CI, 3.16–3.82), P95 or higher (4.88; 95% CI, 4.45–5.35). Similarly, compared with women having TyG index < P25, the highest risks of HDP, LGA and PTB were identified among women with higher TyG index (≥P95), with the aORs 2.31 (95% CI, 2.02–2.65), 1.95 (95% CI, 1.74–2.19), 1.56 (95% CI, 1.34–1.82), respectively (all P < 0.001; Fig. 2).

Fig. 1
figure 1

Association between Triglyceride-glucose index in early pregnancy the risk of adverse pregnancy outcomes. Multivariable logistic regression models with restricted cubic splines were applied to explore the dose–response relationship between maternal Triglyceride-glucose (TyG) index in early pregnancy and the risk of GDM (A), HDP (B), LGA (C) and PTB (D). These models were adjusted for maternal age, education, parity, and insurance status. BMI body mass index (calculated as weight in kilograms divided by height in meters squared), TyG Triglyceride-glucose, GDM gestational diabetes mellitus, HDP hypertensive disorders in pregnancy, LGA large for gestation age, PTB preterm birth

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Fig. 2
figure 2

Effect of triglyceride-glucose index in early pregnancy on pregnancy complications. Multivariable analysis was used to estimate the association of TyG in early pregnancy with risk of pregnancy complications and outcomes. All analyses were adjusted for age, education, parity, health insurance status, and pre-pregnancy BMI. TyG values in early pregnancy were divided into different quartiles (Q) categories. All analyses were adjusted for maternal age, education, parity, insurance status, and ALT level. Adjusted odds ratios (aOR) and risk differences of GDM, HDP, LGA and PTB for different TyG categories are calculated by comparing with the reference group (TyG < 25th). All risk differences, adjusted odds ratios, and the corresponding 95% CIs for each were calculated from the results of the multivariable model and adjusted for baseline risk imprecision. BMI body mass index, TyG Triglyceride-glucose, aOR adjusted odds ratios, Q quartiles, GDM gestational diabetes mellitus, HDP hypertensive disorders in pregnancy, LGA large for gestational age, PTB preterm birth

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Interaction and stratification analysis of pre-pregnancy BMI and TyG index on risk for adverse pregnancy outcomes

We further investigated the potential modification effect of pre-pregnancy BMI on the association of early pregnancy TyG index with APOs. As displayed by heatmaps (filled contour plot) in Fig. 3, there was a significant interaction between TyG index in early pregnancy and pre-pregnancy BMI on the risk of GDM, HDP, and LGA (all P < 0.05). The probability of GDM (P for interaction = 0.001; Fig. 3A), HDP (P for interaction = 0.018; Fig. 3B), and LGA (P for interaction = 0.010; Fig. 3C), were considerably different according to the levels of early pregnancy TyG index and pre-pregnancy BMI. However, the probability of PTB did not differ when a combination of the TyG index and pre-pregnancy BMI were assessed (P for interaction = 0.095; Fig. 3D).

Fig. 3
figure 3

The combined effect of early pregnancy FPG and pre-pregnancy BMI on pregnancy complications. Heatmap (filled contour plot) for the correlation of risk of pregnancy outcomes, including GDM (A), HDP (B), LGA (C), and PTB (D) according to the interaction of early-pregnancy FPG and pre-pregnancy BMI. Red indicates an increased risk of a pregnancy outcome, while blue indicates a decreased risk. The analysis was adjusted for maternal age, education, parity, and insurance status. BMI body mass index (calculated as weight in kilograms divided by height in meters squared), TyG Triglyceride-glucose, GDM gestational diabetes mellitus, HDP hypertensive disorders in pregnancy, LGA large for gestational age, PTB preterm birth, CI confidence intervals

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The association between early-pregnancy TyG index and risk of APOs were further stratified by different pre-pregnancy BMI categories (Table 2). Among women with OWO, higher TyG index quartile (Q4) was notably associated with an incremental risk of GDM (crude OR, cOR, 3.99, 95% CI, 3.29–4.85; aOR, 3.82; 95% CI, 3.14–4.64), HDP (cOR, 1.20, 95% CI, 0.99–1.47; aOR, 1.34; 95% CI, 1.10–1.64), LGA (cOR, 1.92, 95% CI, 1.56–2.36; aOR, 1.78; 95% CI, 1.44–2.19) and PTB (cOR, 1.58, 95% CI, 1.16–2.16; aOR, 1.53; 95% CI, 1.11–2.09) compared with those having lower TyG index (Q1). Similar patterns were found among women with normal pre-pregnancy BMI, moderately increased risks of GDM (cOR, 3.45, 95% CI, 3.20–3.73; aOR, 3.16; 95% CI, 2.92–3.42), HDP (cOR, 1.75, 95% CI, 1.56–1.96; aOR, 1.94; 95% CI, 1.72–2.18), LGA (cOR, 1.75, 95% CI, 1.60–1.92; aOR, 1.55; 95% CI, 1.41–1.70) and PTB (cOR, 1.40, 95% CI, 1.25–1.58; aOR, 1.31; 95% CI, 1.17–1.48) in women with TyG index in Q4.

Table 2 Associations between maternal blood TyG index in early pregnancy and the risk of adverse maternal and fetal outcomes stratified by maternal pre-pregnancy BMI
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Predictive value of the combination of pre-pregnancy BMI and early pregnancy TyG index for adverse pregnancy outcomes

Subsequently, we assessed the potential predictive value of TyG and BMI, individually or in combination, on APOs risk using a multivariable logistic regression model adjusted for maternal age, education level, parity, and health insurance status. In the test cohort (Fig. 4), we demonstrated that the AUCs were significantly improved with the addition of BMI × TyG index for GDM [AUC = 0.684 (95% CI, 0.677–0.691)], HDP [AUC = 0.690 (95% CI, 0.68–0.701)], and LGA [AUC = 0.658 (95% CI, 0.650–0.666)] indicating the superior efficacy of the combined index in this study. The ROC curve of PTB indicated an AUC of 0.567 for the combined metric, suggesting limited prediction capability of TyG × BMI for PTB. Similar findings were observed in the validated cohort (Fig. S2 in the Supplementary material).

Fig. 4
figure 4

Predictive performance of the combined early-pregnancy TyG and pre-pregnancy BMI for pregnancy complications in the test cohort (N = 50,569). The enhanced predictive value of combining pre-pregnancy BMI and early-pregnancy TyG compared to their individual performance, with regards to GDM (A), HDP (B), LGA (C) and PTB (D), the receiver operating characteristic (ROC) curve evaluating the discriminative capabilities by calculating the AUC. TyG × BMI indicates the combined effect of TyG and BMI. AUC area under curve, CI confidence interval, BMI body mass index (calculated as weight in kilograms divided by height in meters squared), FPG fasting plasma glucose, TG triglyceride, TyG Triglyceride-glucose, BMI × TyG interaction term of pre-pregnancy BMI and TyG in early pregnancy, GDM gestational diabetes mellitus, HDP hypertensive disorders in pregnancy, LGA large for gestational age, PTB preterm birth

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Sensitivity analyses

Furthermore, sensitivity analyses were performed to test the solidity of the modification effect of pre-pregnancy BMI on the association between early-pregnancy TyG index and risks of APOs by exclusions of women with elevated FPG (Table S1 in the Supplementary material), TG (Table S2 in the Supplementary material) and either hyperglycemia or hypertriglyceridemia (Table S3 in the Supplementary material), respectively. We showed that higher TyG index quartile (Q4) was still robustly associated with incremental risks of APOs, especially GDM among women with normal pre-pregnancy BMI or OWO.

Moreover, we found that the predictive values of TyG × BMI on APOs remained prominent among women with normal TG and FPG in early pregnancy, after exclusion of women with high FPG (AUC for GDM: 0.664, 95% CI, 0.658–0.670; Figure S3 in the Supplementary material), high TG (for GDM: 0.660, 95% CI, 0.654–0.667; Figure S4 in the Supplementary material) and those with either condition (for GDM: 0.642, 95% CI, 0.635–0.650; Figure S5 in the Supplementary material), better than individual parameters, including pre-pregnancy BMI, TG, FBG, and TyG index.

Discussion

In the current study, we demonstrated a positive relationship between maternal early pregnancy TyG index and subsequent APOs. In addition, pre-pregnancy BMI modified the association between early pregnancy TyG index and the APOs. Specifically, among women with pre-pregnancy OWO, higher early pregnancy TyG index (Q4) exhibited a nearly four-fold heightened susceptibility to GDM when compared with those with TyG in Q1. A combination of the early pregnancy TyG index and the pre-pregnancy BMI may provide potential values for identifying women at high risk of developing APOs.

Adopting this real-world clinical data from 67,936 pregnant women in Shanghai, China, who underwent routine screening for lipids and FPG levels in the first trimester, we were able to comprehensively explore the relationship between TyG index in early pregnancy and APOs. To the best of our knowledge, this is the largest cohort study to date that has revealed an association between maternal TyG index during early pregnancy and various APOs stratified by pre-pregnancy BMI. Indeed, the coexistence of pre-pregnancy OWO and higher TyG index during early pregnancy may elicit an increased risk of APOs. In accordance with findings in previous studies [26,27,28,29,30,31,32,33], our study also highlighted the association between higher TyG index during early pregnancy and an increased risk of GDM. In addition, we also found that elevated maternal TyG index during early pregnancy was associated with increased risk of HDP, LGA, and PTB. In addition, the findings proposed a potential predictive value of the TyG index on APOs in early pregnancy, suggesting that both FPG and TG levels should be tested in early pregnancy, especially in pre-pregnancy OWO.

This study also provides novel insights into the potential role of IR in APOs and may highlight the significance of a combined assessment of pre-pregnancy BMI and TyG index to further stratify high-risk women. Wang et al. have established a correlation between elevated pre-pregnancy BMI in mothers and the development of hyperglycemia and hyperlipidemia in their offspring, along with inflammation, which can lead to a profound impact on organ structure, function, and homeostasis [34]. Besides, maternal obesity may enhance placental growth, resulting in a larger placental area that facilitates greater nutrient exchange [35]. This process can lead to overnutrition of the fetus, increased production of insulin and insulin-like growth factors, and IR, thereby increasing the likelihood of fetal overgrowth, e.g., LGA. Impaired metabolism of nitric oxide and lipids may disrupt the production of prostaglandin E2, causing heightened peripheral vascular resistance and increased blood pressure [36]. In addition, another study revealed that GDM characterized by IR in the second trimester was associated with an increased likelihood of other APOs, including HDP, and LGA [37]. In addition, hyperglycemia and IR in the fetus may disrupt normal surfactant synthesis, leading to adverse outcomes in neonates [38].

Indeed, this large cohort, established at our hospital, allowed us to explore potential dose–response associations between maternal TyG index in early pregnancy and multiple APOs in women with different pre-pregnancy BMI, after adjustment for a wide range of potential confounders. Still, there may be some limitations. First, the study was conducted at a tertiary university-affiliated maternity center in a major city in eastern China, which primarily serves a large population of Han Chinese women. It is important to note that variability in the TyG index can arise due to individual differences, diverse populations, and variations in experimental methodology. Despite the wide reach of the institution, the potential for selection bias remains a concern, necessitating future research involving multiple obstetric centers and even multiple ethnicities. Second, the presence of residual confounding cannot be definitively eliminated despite the inclusion of various potential confounders in the adjusted model. In addition, the study did not investigate the effect of longitudinal changes in mid- and late pregnancy TyG and was limited to maternal TyG measured in early pregnancy for our primary study purpose of identifying high-risk women in early pregnancy and also due to missing TG and FBG data. Finally, the findings of this study were derived from observational data collected at a singular maternal and child health center, thus limiting the ability to establish causality.

Conclusions

An interactive relationship was identified between maternal TyG index during pregnancy and pre-pregnancy BMI for APO risk, including GDM, HDP, and LGA. In addition, a combination of pre-pregnancy BMI and TyG index in early pregnancy may provide potentially improved value for early identification of women at high risk of developing APOs. Pre-pregnancy OWO women with high TyG index during early pregnancy are most susceptible to GDM. This study brings to the fore a nuanced view of how maternal TyG index and pre-pregnancy BMI intertwine and influence risk assessment of APOs, particularly GDM, providing important implications for clinical practice and public health strategies. Further studies may be needed to investigate the trajectory of TyG from early to late pregnancy and its impact on maternal and neonatal outcomes, as well as to implement early intervention in high-risk women.

Availability of data and materials

In compliance with hospital regulations, the corresponding author is able to furnish the dataset for the study upon a reasonable request.

Abbreviations

TyG index:

Triglyceride-glucose index

IR:

Insulin resistance

BMI:

Body mass index

GDM:

Gestational diabetes mellitus

HDP:

Hypertension during pregnancy

LGA:

Large for gestational age

PTB:

Preterm birth

IPMCH:

International Peace Maternity and Child Health Hospital

IVF:

In vitro fertilization

LMP:

Last menstrual period

OWO:

Overweight and obesity

OGTT:

Oral glucose tolerance test

FBG:

Fasting plasma glucose

TG:

Triglyceride

OR:

Odds ratio

AOR:

Adjusted odds ratio

CI:

Confidence interval

IQRs:

Interquartile ranges

ROC:

Receiver operating characteristic

AUC:

Area under the ROC curve

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Acknowledgements

The authors gratefully acknowledge the contributions of all pregnant women who donated their data for this study and the dedicated doctors and nurses who undertook cautious data collection during routine patient care.

Funding

This work was supported by grants from the National Natural Science Foundation of China (82271706), and the Programs for Science and Technology Development of Songjiang District, Shanghai (2024SJKJGG094). The funder was not involved in study design, data collection and analysis, preparation of the manuscript, or decision to publish.

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Author notes

  1. Li Li, Yulai Zhou, and Huan Li are contributed equally to this work.

Authors and Affiliations

  1. The International Peace Maternity and Child Health Hospital, School of Medicine, Shanghai Jiao Tong University, No. 910, Hengshan Rd., Shanghai, 200030, China

    Li Li, Yulai Zhou, Juan Li, Lishi Huang & Weibin Wu

  2. Shanghai Key Laboratory of Embryo Original Diseases, Shanghai, 200030, China

    Li Li, Yulai Zhou, Juan Li, Lishi Huang & Weibin Wu

  3. Songjiang Maternity and Child Health Hospital, Shanghai, 200030, China

    Huan Li

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  1. Li Li
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  4. Juan Li
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  5. Lishi Huang
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  6. Weibin Wu
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Contributions

L.L, Y.Z. and W.W. designed the study, W.W., H.L. and L.L. supervised data collection. Y.Z., J.L. and W.W. conducted statistical analyses and data interpretation. Y.Z., L.H. and W.W prepared the original manuscript. All authors contributed to revision and approved the final version for publication. W.W. and L.H. are the guarantors for this work and accept full responsibility for the conduct of the study, had access to the data, and controlled the decision to publish.

Corresponding authors

Correspondence to Lishi Huang or Weibin Wu.

Ethics declarations

Ethics approval and consent to participate

The study protocol was endorsed by the IPMCH Medical Ethics Committee (GKLW2023-006, the date of approval was 7 Febrary 2023). Analysis of data in this study were conducted from 2023 to 2024. The requirement for informed consent was waived for using anonymized and de-identified data as approved by the IPMCH Ethics Committee.

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Not applicable.

Competing interests

The authors declare no competing interests.

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Li, L., Zhou, Y., Li, H. et al. Pre-pregnancy BMI modifies the associations between triglyceride–glucose index in early pregnancy and adverse perinatal outcomes: a 5-year cohort study of 67,936 women in China. Diabetol Metab Syndr 16, 311 (2024). https://doi.org/10.1186/s13098-024-01550-2

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Keywords

Diabetology & Metabolic Syndrome

ISSN: 1758-5996

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