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Original Article

The mediating role of pregnancy-induced hypertension on pre-pregnancy body mass index and adverse neonatal outcomes in women with assisted reproductive technology

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Article: 2289348 | Received 12 Sep 2023, Accepted 25 Nov 2023, Published online: 06 Dec 2023

Abstract

Objective

To explore whether pregnancy-induced hypertension (PIH) mediates the association between pre-pregnancy body mass index (BMI) and adverse neonatal outcomes in women undergoing assisted reproductive technology (ART) for singleton pregnancies.

Methods

This cohort study collected 79437 maternal data from the National Vital Statistics System (NVSS) between 2020 and 2021. Univariable and multivariable logistic regression models were applied to estimate the association between pre-pregnancy BMI and PIH in women receiving ART as well as the associations between pre-pregnancy BMI and PIH and adverse neonatal outcomes. The mediation effect of PIH on the association between pre-pregnancy BMI and adverse neonatal outcomes was estimated according to the total effect, natural direct effect, natural indirect effect, and percentage of mediation.

Results

There were 25769 participants had adverse neonatal outcomes at the end of the follow-up. After adjusting for confounding factors, an increased risk of PIH in women receiving ART was identified in those with pre-pregnancy BMI ≥25 kg/m2 [odds ratio (OR)=1.92, 95% confidence interval (CI):1.84–2.01]. Pre-pregnancy BMI ≥25 kg/m2 was associated with an increased risk of adverse neonatal outcomes (OR = 1.26, 95%CI:1.22–1.30). Women with PIH had an increased risk of adverse neonatal outcomes (OR = 1.79, 95%CI:1.71–1.87). The percentage mediated by PIH in the association between pre-pregnancy BMI and adverse neonatal outcomes was 21.30%.

Conclusion

PIH partially mediated the association between pre-pregnancy BMI and adverse neonatal outcomes in women receiving ART, which recommends that women control weight before receiving ART.

Introduction

With the increasing prevalence of infertility and delayed timing of childbirth worldwide, the use of assisted reproductive technology (ART) has gradually increased in recent years [Citation1, Citation2]. A previous study estimated that there were more than 439,039 births among 1,929,905 ART patients in 2014 based on data from national and regional ART registries (containing 76 countries and 2,746 ART centers) [Citation3]. In the past, the main focus was on improving clinical pregnancy and cumulative live birth rates. However, some non-physiological interventions during ART, particularly the administration of supraphysiological doses of hormonal drugs, may affect the overall pregnancy environment, disrupt gametogenesis or embryonic development, and adversely affect both maternal and neonatal outcomes [Citation4]. Increasing evidence has demonstrated that compared with natural conception, ART-induced pregnancy is associated with an increased risk of pregnancy complications, such as pregnancy-induced hypertension (PIH) and adverse neonatal outcomes, including preterm birth and low birth weight [Citation5–8]. To pay more attention to women receiving ART and to decrease adverse maternal and neonatal outcomes is of great value.

Maternal obesity is an increasing public health problem worldwide, and weight management is considered a potential modifiable factor for adverse pregnancy outcomes [Citation9]. Evidence suggests that being overweight and/or obese before pregnancy is associated with an increased risk of PIH and adverse neonatal outcomes [Citation10–13]. PIH is a common complication during pregnancy, which is a major cause of adverse maternal and neonatal outcomes and is associated with the risk of cardiovascular disease after delivery [Citation14, Citation15]. Overweight and obesity was associated with inflammation, oxidative stress, and insulin resistance, as well as with changes in the levels of various bioactive compounds and some cytokines [Citation16], which participate in numerous metabolic pathways and adversely affect the endothelium [Citation17]. Inflammation, oxidative stress, and endothelial dysfunction are important elements of pregnancy hypertension [Citation18]. A prospective cohort study in China showed that preeclampsia partially mediates the effect of pre-pregnancy obesity on the risk of neonatal preterm birth [Citation19]. Based on these findings, we speculated that PIH may mediate the association between pre-pregnancy body mass index (BMI) and the risk of adverse neonatal outcomes.

The purpose of the present study was to explore whether PIH mediated the association between pre-pregnancy BMI and adverse neonatal outcomes in women undergoing ART with singleton pregnancies based on data from the National Vital Statistics System (NVSS). A subgroup analysis was conducted according to maternal age.

Methods

Study design and population

In this cohort study, we collected 7289754 maternal data points in the National Vital Statistics System (NVSS) database between 2020 and 2021. The NVSS database offers medical and health information for mothers and neonates, including vital statistics on births, deaths, marriages, divorces, and fetal deaths in the medical records across 50 states, New York City, the District of Columbia, and five territories (Puerto Rico, Virgin Islands, Guam, American Samoa, and Northern Mariana Islands) in the United States [Citation20]. The inclusion criteria were as follows:1) women aged ≥18 years and 2) ART-induced singleton pregnancies in the NVSS database. The exclusion criteria were:1) missing information on pre-pregnancy BMI, PIH, and newborn outcomes; 2) multifetal pregnancies; 3) chronic hypertension before pregnancy; 4) missing information of key covariates; and 5) gestational age recorded as <20 weeks or ≥45 weeks. Finally, 79437 participants were included in the study. The requirement for ethical approval for this study was waived by the Institutional Review Board of Shengjing Hospital of China Medical University because the data were accessed from the NVSS (a publicly available database). The need for written informed consent was waived by the Institutional Review Board of the Shengjing Hospital of China Medical University due to the retrospective nature of the study.

Potential covariates and definitions

Maternal age (years), mother’s race (White, Black or others), mother’s education (12th grade with no diploma or less, high school graduate or general equivalent diploma (GED) completed, Associate degree or some college credit, Bachelor’s degree and above or unknown), marital status (married, unmarried or unknown), father’s age (<40 years, ≥40 years or unknown), father’s race (White, Black or others), father’s education (12th grade with no diploma or less, high school graduate or GED completed, Associate degree or some college credit, Bachelor’s degree and above or unknown), smoke before pregnancy (yes, no or unknown), smoke during pregnancy (yes, no or unknown), timing of initiation of prenatal care (no prenatal care, 1st trimester during pregnancy, 2nd trimester during pregnancy or 3rd trimester during pregnancy), number of prenatal visits (times), pre-pregnancy diabetes (yes or no), gestational diabetes (yes or no), previous preterm birth (yes or no), previous cesarean (yes or no), parity (unipara or multipara), and gestational weight gain (GWG, inadequate, normal, or excessive).

Main and outcome variables

The pre-pregnancy BMI and PIH were the main variables in this study. Pre-pregnancy BMI was calculated according to the NVSS formula: mother’s pre-pregnancy weight (lb)/[mother’s height (in)]2 × 703. According to the WHO criteria, all participants were divided into <25kg/m2 and ≥25kg/m2 groups. PIH was defined as the occurrence of systolic blood pressure ≥140 mmHg or diastolic blood pressure ≥90 mmHg at or after 20 weeks of gestation in women with previously normal blood pressure before 20 weeks [Citation21]. In this study, women with gestational hypertension and/or eclampsia were considered to have PIH.

Adverse neonatal outcomes included low birth weight <2500 g, macrosomia >4000 g, preterm birth (defined as gestational age < 37 weeks), Apgar score at 5 min <7, assisted ventilation required immediately following delivery, assisted ventilation required for more than six hours, neonatal ICU admission, newborn given surfactant replacement therapy, antibiotics received by the newborn for suspected neonatal sepsis, and seizure or serious neurologic dysfunction [Citation22–24]. The occurrence of one of these outcomes was considered to be an adverse neonatal outcome.

Statistical analysis

Normally distributed measurement data are expressed as mean ± SD, and non-normal measurement data are expressed as median and quartiles [M (Q1, Q3)]. Enumeration data are presented as the number and percentage of samples [n (%)]. Normally distributed measurement data were compared using the t-test. Non-normal measurement data were compared using the Mann-Whitney U rank-sum test. Enumeration data were compared using the χ2 test or Fisher exact probability method. Sensitivity analysis was performed to compare the data before and after some participants were excluded, and found no significant difference between the data before and after some participants were excluded (Supplementary Table S1). Univariate Logistic regression model was used to explore the covariates that might be related to PIH or adverse neonatal outcomes. Variables statistically associated with PIH were regarded as covariates of PIH, which including maternal age, mother’s race, mother’s education, marital status, father’s age, father’s race, smoking before pregnancy, smoking during pregnancy, timing of prenatal care initiation, number of prenatal visits, pre-pregnancy diabetes, gestational diabetes, previous preterm birth, previous cesarean delivery, parity, and GWG. The confounding factors were variables associated with adverse neonatal outcomes were maternal age, mother’s race, marital status, father’s age, father’s race, father’s education, smoking before pregnancy, smoking during pregnancy, timing of prenatal care initiation, number of prenatal visits, pre-pregnancy diabetes, gestational diabetes, chorioamnionitis, previous preterm birth, previous cesarean delivery, parity, GWG, and delivery method [Citation25–28]. Considering PIH as the outcome, the corresponding covariates were adjusted to explore the correlation between pre-pregnancy BMI and PIH using a multivariable logistic regression model. The mediation effect of PIH on the association between pre-pregnancy BMI and adverse neonatal outcomes was estimated according to the total effect, natural direct effect, natural indirect effect, and percentage of mediation. The natural direct effect was defined as the amount of the effect of pre-pregnancy BMI on adverse neonatal outcomes directly, while the natural indirect effect was defined as the amount of the effect of pre-pregnancy BMI on adverse neonatal outcomes via the mediator PIH. Total effect = natural direct effect + natural indirect effect. The percentage of medication was computed as natural indirect effect/total effect × 100%. Subgroup analysis was stratified according to maternal age (<35 years and ≥35 years), and the mediating effect of PIH on pre-pregnancy BMI and adverse neonatal outcomes under different stratification conditions was examined. The odds ratio (OR), natural direct effect, natural indirect effects, percentage of mediation, and 95% confidence interval (CI) level were the effect sizes. The confidence level was set at alpha= 0.05. SAS software (version 9.4; SAS Institute Inc., Cary, NC, USA) was used for the statistical analysis.

Results

Comparisons of the characteristics of participants with and without adverse neonatal outcomes

A total of 7289754 maternal data points were recorded in the NVSS in 2020 and 2021. Among them, women aged <18 years (n = 161322), those not receiving ART (n = 7025439), and participants with multifetal pregnancies (n = 16150) were excluded. Women without BMI data (n = 1305), or adverse neonatal outcomes data (n = 108) were excluded. Women with pre-pregnancy hypertension (n = 3301), gestational age < 19 weeks or ≥45 weeks (n = 997), and those without data on the timing of prenatal care initiation (n = 935), number of prenatal visits (n = 333), GWG (n = 389), chorioamnionitis (n = 14), and delivery method (n = 24) were also excluded. Finally, 79437 participants were included in the study. The screening process is illustrated in .

Figure 1. The screen process of the participants.

Figure 1. The screen process of the participants.

The mean maternal age of those without adverse neonatal outcomes was lower than that of those with adverse neonatal outcomes (35.13 years vs 35.31 years). The percentage of women who smoked before pregnancy in the non-adverse neonatal outcome group was lower than that in the adverse neonatal outcome group (0.59% vs. 0.73%). The percentage of participants with a BMI ≥25 kg/m2 in the non-adverse neonatal outcomes group was lower than that in the adverse neonatal outcomes group (46.49% vs. 55.04%). The percentage of women with excessive GWG in the non-adverse neonatal outcome group was lower than that in the adverse neonatal outcome group (47.21% vs. 50.86%). The percentage of women with PIH in the non-adverse neonatal outcome group was lower than that in the adverse neonatal outcome group (10.86% vs. 19.12%) ().

Table 1. Comparisons of the characteristics of participants with and without adverse neonatal outcomes.

The association between pre-pregnancy BMI and PIH in women receiving ART

A univariate Logistic regression model was used to explore the covariates that might be related to PIH. The results revealed that maternal age, mother’s race, mother’s education, marital status, father’s age, father’s race, smoking before pregnancy, smoking during pregnancy, timing of prenatal care initiation, number of prenatal visits, pre-pregnancy diabetes, gestational diabetes, previous preterm birth, previous cesarean delivery, parity, and GWG were confounding factors associated with PIH (Supplementary Table S2). In the crude model, pre-pregnancy BMI ≥25 kg/m2 might be correlated with an elevated risk of PIH in women receiving ART (OR = 2.21, 95%CI:2.12–2.30). After adjusting for these confounding factors, an increased risk of PIH in women receiving ART was identified in women with pre-pregnancy BMI ≥25 kg/m2 (OR = 1.92, 95%CI:1.84–2.01) ().

Table 2. The association between pre-pregnancy BMI and PIH in women receiving ART.

The associations of pre-pregnancy BMI and PIH with adverse neonatal outcomes

As shown in Supplementary Table S3, the confounding factors associated with adverse neonatal outcomes were maternal age, mother’s race, marital status, father’s age, father’s race, father’s education, smoking before pregnancy, smoking during pregnancy, timing of prenatal care initiation, number of prenatal visits, pre-pregnancy diabetes, gestational diabetes, chorioamnionitis, previous preterm birth, previous cesarean delivery, parity, GWG, and delivery method. Compared with women with pre-pregnancy BMI <25 kg/m2, those with pre-pregnancy BMI ≥25 kg/m2 were associated with an increased risk of adverse neonatal outcomes (OR = 1.26, 95%CI:1.22–1.30). Women with PIH were correlated with an increased risk of adverse neonatal outcomes compared to those without PIH (OR = 1.79, 95%CI:1.71–1.87) in the adjusted model ().

Table 3. The associations of pre-pregnancy BMI and PIH with adverse neonatal outcomes.

The mediating role of PIH on pre-pregnancy BMI and adverse neonatal outcomes

According to the data in , the OR of total effect of PIH on pre-pregnancy BMI and adverse neonatal outcomes was 1.28 (95%CI:1.23–1.32). The OR of natural direct effect OR of PIH on pre-pregnancy BMI and adverse neonatal outcomes was 1.22 (95%CI:1.18–1.26) and OR of the natural indirect effect of PIH on pre-pregnancy BMI and adverse neonatal outcomes was 1.05 (95%CI:1.04–1.05). The percentage mediated by PIH in the association between pre-pregnancy BMI and adverse neonatal outcomes was 21.30% ().

Figure 2. The conceptual graph of the mediating role of PIH on the association between pre-pregnancy BMI and adverse neonatal outcomes.

Figure 2. The conceptual graph of the mediating role of PIH on the association between pre-pregnancy BMI and adverse neonatal outcomes.

Table 4. The mediating role of PIH on pre-pregnancy BMI and adverse neonatal outcomes.

Subgroup analysis of the mediating role of PIH on pre-pregnancy BMI and adverse neonatal outcomes

In maternal age <35 years group, the OR of total effect of PIH on pre-pregnancy BMI and adverse neonatal outcomes was 1.30 (95%CI:1.24–1.37), the OR of natural direct effect of PIH on pre-pregnancy BMI and adverse neonatal outcomes was 1.25 (95%CI:1.19–1.31), and the OR of natural indirect effect of PIH on pre-pregnancy BMI and adverse neonatal outcomes was 1.04 (95%CI:1.04–1.05). The percentage mediated by PIH on the association between pre-pregnancy BMI and adverse neonatal outcomes was 17.82% (95%CI:13.82%–21.82%). In the maternal age ≥ 35 years group, the total effect OR of PIH on pre-pregnancy BMI and adverse neonatal outcomes was 1.25 (95%CI:1.19–1.31), the natural direct effect OR of PIH on pre-pregnancy BMI and adverse neonatal outcomes was 1.19 (95%CI:1.13–1.24) and the natural indirect effect OR of PIH on pre-pregnancy BMI and adverse neonatal outcomes was 1.05 (95%CI:1.04–1.06). The percentage mediated by PIH in the association between pre-pregnancy BMI and adverse neonatal outcomes was 25.14% (95%CI:19.50%–30.79%) ().

Table 5. Subgroup analysis of the mediating role of PIH on pre-pregnancy BMI and adverse neonatal outcomes.

Discussion

In the present study, the association between pre-pregnancy BMI and PIH, the association between pre-pregnancy BMI and adverse neonatal outcomes, and the association between PIH and adverse neonatal outcomes in women receiving ART were evaluated. Whether PIH mediates the association between pre-pregnancy BMI and adverse neonatal outcomes was also explored. The results showed that pre-pregnancy BMI ≥25 kg/m2 was associated with an increased risk of PIH in women receiving ART. Pre-pregnancy BMI ≥25 kg/m2 or PIH correlated with an elevated risk of adverse neonatal outcomes. Noteworthy new finding of this study was that PIH mediated the association between pre-pregnancy BMI and adverse neonatal outcomes. The findings in this study suggested that the role of PIH as mediator constitutes clinical and public health significance that should be recognized and considered in healthcare for women receiving ART, which may provide a clinical reference for early interventions in women receiving ART with pre-pregnancy obesity and PIH, and hope to reduce the risk of adverse neonatal outcomes.

Obesity is an independent risk factor for infertility [Citation29]. Although ART is an integral component of modern medicine, reports have consistently shown lower success rates and higher miscarriage rates in women with obesity than in those with a normal BMI [Citation30]. A previous systematic review and meta-analysis indicated that women with a higher waist circumference had a significantly higher risk of hypertensive disorders during pregnancy [Citation31]. Lara-Barea et al. identified pre-pregnancy BMI as a useful biomarker for identifying normotensive pregnant women with an increased risk of developing hypertensive disorders of pregnancy [Citation32]. Another study demonstrated a correlation between pre-pregnancy body mass and the incidence of hypertensive disorders during pregnancy [Citation33]. Among pregnant women in the US who received ART, a higher BMI level was independently correlated with an increased risk of adverse maternal outcomes such as preeclampsia and eclampsia [Citation34]. This evidence supports the findings of our study, which showed that pre-pregnancy BMI was associated with the risk of PIH in women receiving ART. In addition, we found that pre-pregnancy BMI was correlated with the risk of adverse neonatal outcomes in women receiving ART. This finding is consistent with those of previous studies. Mayo et al. conducted a population-based study in California and found an association between high BMI and risk of preterm birth [Citation35]. An association between maternal pre-pregnancy BMI and the risk of adverse pregnancy outcomes has also been observed in Chinese women [Citation36]. The results from a previous systematic review and meta-analysis including 86 studies representing 20,328,777 pregnant women confirmed the association between elevated pre-pregnancy maternal BMI and higher odds of adverse fetal/neonatal outcomes [Citation37]. Meanwhile, an association between PIH and adverse neonatal outcomes in women receiving ART was identified in our study. A previous prospective cohort study showed that a higher incidence of adverse perinatal outcomes occurred among women with PIH in the Tigray regional state of Ethiopia [Citation38]. Lu et al. found that preterm infants born to women with PIH born less than 34 weeks born to PIH women had a higher risk of intrauterine growth restriction and lower birth weight [Citation39]. In singleton pregnancies, the occurrence of PIH increases the risk of adverse neonatal outcomes, including preterm birth, low birth weight, and small for gestational age [Citation40]. These findings support the results of the current study, which demonstrated that women with PIH had an increased risk of adverse neonatal outcomes compared to those without PIH.

In addition, the mediating role of PIH in the association between pre-pregnancy BMI and adverse neonatal outcomes was found in women receiving ART. In a previous population-based study, the mediation effect of PIH on the association between ART and adverse neonatal outcomes was identified [Citation41]. Another study also found that preeclampsia partially mediates the effect of pre-pregnancy obesity on the risk of neonatal preterm birth [Citation19]. These results indicate that PIH may be an important mediator in the association between pre-pregnancy BMI and adverse neonatal outcomes. High pre-pregnancy BMI is associated with a systemic low-grade metabolic inflammatory state and subclinical endotoxemia [Citation42], while inflammation has been reported to be an important risk factor for adverse neonatal outcomes [Citation43, Citation44]. These findings suggest that for overweight/obese women, preconception assessments and counseling to obtain good pregnancy outcomes by losing weight before pregnancy and controlling weight gain throughout pregnancy are necessary. Women should maintain a normal BMI before ART to avoid adverse perinatal outcomes. For women with PIH, intensive interventions should be provided to prevent possible infant morbidities. Early interventions and more care in women receiving ART with pre-pregnancy obesity and PIH should be provided to reduce the risk of adverse neonatal outcomes.

The present study explored the association between pre-pregnancy BMI and PIH, the association between pre-pregnancy BMI and adverse neonatal outcomes, and the association between PIH and adverse neonatal outcomes in women receiving ART. The mediating role of PIH in the association between pre-pregnancy BMI and adverse neonatal outcomes was evaluated. This study included a large and representative sample size from NVSS. This study has several limitations. First, this was a retrospective study; the data analyzed were obtained from medical records, and there might be recording errors. Second, only singleton pregnancies due to ART were included, and population heterogeneity was observed between single and multiple pregnancies. Thirdly, there were some participants were excluded, and although sensitivity analysis showed no significant difference between the data before and after some participants were excluded, the potential bias might exist. Therefore, the association between pre-pregnancy BMI, PIH, and risk of adverse neonatal outcomes in multiple pregnancies requires further exploration.

Conclusions

This study evaluated the mediating role of PIH in the association between pre-pregnancy BMI and adverse neonatal outcomes and found that PIH partially mediated the association between pre-pregnancy BMI and adverse neonatal outcomes in women with ART. The findings might recommend that women control their weight before receiving ART.

Supplemental material

Supplementary Material

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Availability of data and materials

The datasets generated and analyzed during the current study are available from the NVSS database (https://www.cdc.gov/nchs/nvss/index.htm).

Disclosure statement

No potential conflict of interest was reported by the author(s).

Additional information

Funding

This study was also supported by the National Key Research and Development Plan (2018YFC1002902).

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