Abstract
Objective
We aim to explore the mediating effect of hypertensive disorders of pregnancy (HDP) on the relationship between pre-pregnancy body mass index (BMI) and the risk of preterm birth (PTB) in women with singleton live births.
Methods
Demographic and clinical data of 3,249,159 women with singleton live births were extracted from the National Vital Statistics System (NVSS) database in this retrospective cohort study. The associations between pre-pregnancy BMI and HDP, HDP, and PTB, and pre-pregnancy BMI and PTB were evaluated using univariate and multivariate logistic regression analyses, with odds ratios (ORs) and 95% confidence intervals (CIs). Structural equation modeling (SEM) was used to explore the mediating effect of HDP on the relationship between pre-pregnancy BMI and PTB.
Results
In total, 324,627 women (9.99%) had PTB. After adjustment for covariables, there were significant associations between pre-pregnancy BMI and HDP [OR = 2.07, 95% CI: 2.05–2.09)], HDP and PTB [OR = 2.54, 95% CI: (2.52–2.57)], and pre-pregnancy BMI and PTB [OR = 1.03, 95% CI: 1.02–1.03)]. The effect of pre-pregnancy BMI on PTB was significantly mediated by HDP with a mediation proportion of 63.62%, especially in women of different ages and having gestational diabetes mellitus (GDM) or not.
Conclusion
HDP may play a mediating role in the effect of pre-pregnancy BMI on PTB risk. Women preparing for pregnancy should pay close attention to BMI, and pregnant women should monitor and develop interventions for HDP to reduce the risk of PTB.
Introduction
Preterm birth (PTB), defined as delivery at less than 37 weeks of gestation [Citation1], is one of the leading causes of neonatal morbidity and mortality, with a global incidence of 10.6% [Citation2] and approximately 1 million infant deaths due to PTB each year [Citation3,Citation4]. Many surviving premature infants may have long-term cerebral palsy, visual or hearing impairment, delayed development, behavioral problems, and an increased risk of chronic disease in adulthood [Citation5–9]. Therefore, the public health burden of PTB relates not only to the initial neonatal intensive care unit (NICU), but also to the long-term increased costs associated with medical, social, and specialist educational services, as well as lost economic productivity [Citation4].
Maternal obesity is a global health problem [Citation10], and the pre-pregnancy body mass index (BMI) of women of childbearing age has shown an increasing trend in recent years [Citation11]. Hypertensive disorder of pregnancy (HDP) is a multifactorial pregnancy complication and refers to one of four conditions: preexisting hypertension, gestational hypertension and pre-eclampsia (PE), preexisting hypertension plus superimposed gestational hypertension with proteinuria, and unclassifiable hypertension [Citation12]. A recent study on the effects of pre-pregnancy BMI and gestational weight gain (GWG) on maternal and infant complications showed that overweight and obesity before pregnancy and excessive GWG are related to a greater risk of developing gestational hypertension [Citation11]. Studies suggested that maternal overweight and obesity were linked to a significantly higher risk of gestational hypertension and extremely PTB [Citation11,Citation13–15]. Lewandowska et al. [Citation14] found that excessive pre-pregnancy maternal weight affects the risk of pregnancy hypertension, which can impact fetal outcomes. A large prospective cohort study in China showed that preeclampsia is associated with a higher risk of PTB [Citation16]. Poudel et al. [Citation17] showed that mothers with hypertensive disorders during pregnancy had increased odds of giving birth to PTB babies. A meta-analysis of a cohort study by Li et al. also indicated that hypertensive disorders in pregnancy significantly increase the risk of PTB [Citation18]. Moreover, pre-pregnancy BMI is associated with adverse birth outcomes, such as PTB, macrosomia, and large gestational age [Citation19]. Jeong et al. [Citation20] indicated that BMI before pregnancy was associated with a risk of PTB. However, whether HDP play a mediating role in the association between pre-pregnancy BMI and the risk of PTB has not been unclarified.
Herein, this study aims to explore the mediating effect of HDP on the relationship of pre-pregnancy BMI and PTB, in order to provide a clinical reference for monitoring and developing interventions to reduce the risk of PTB in women.
Methods
Study design and population
Demographic and clinical data of the women in this retrospective cohort study were extracted from the National Vital Statistics System (NVSS) database in 2020. Natality data of NVSS are based on information for all births registered within the United States in 50 states and the District of Columbia in the U.S. (https://www.cdc.gov/nchs/nvss/index.htm). NVSS uses the mother’s worksheet and the facility worksheet to collect data, and the medical and health information of the mother and infant is extracted from the worksheet completed by the hospital staff [Citation21]. This study analyzed de-identified information downloaded from the NVSS database, and informed consent is waived by the ethics committee of the First People’s Hospital of Jiangxia District. All methods in this research were carried out in accordance with relevant guidelines and regulations in the Declaration of Helsinki.
shows a flowchart of the participants’ screening. In total, 3,504,248 women with singleton live births were initially included. Women aged <18 years (n = 39,827), gestational age <20 or ≥45 weeks (n = 29,208), and missing information on pre-pregnancy BMI (n = 65,324), history of hypertension (n = 87,122), WG (n = 28,432), ART (n = 2670), and history of delivery (n = 2506) were excluded. Finally, there were 3,249,159 eligible women. As the NVSS database is publicly available, no Institutional Review Board approval was required for this study.
Figure 1. Flow chart of the participants screening.
Measurement of pre-pregnancy BMI and diagnosis of HDP
Pre-pregnancy BMI (kg/m2) values were calculated by measuring or self-reporting the pre-pregnancy height and weight of the women. BMI values before pregnancy were classified into two groups (BMI <25 and BMI ≥25) according to WHO standards [Citation22,Citation23]. HDP was diagnosed if women have at least one of four conditions: (a) preexisting hypertension, (b) gestational hypertension and PE, (c) preexisting hypertension plus superimposed gestational hypertension with proteinuria, (d) unclassifiable hypertension [Citation12]. Gestational hypertension was defined as systolic blood pressure (SBP) ≥140 mmHg, diastolic blood pressure (DBP) ≥90 mmHg, or both, on two occasions at least 4 h apart after 20 weeks of gestation in a woman with normal blood pressure (BP) [Citation24]. Eclampsia refers to the development of generalized tonic-clonic seizures, not due to another cause in women with preeclampsia (new-onset hypertension and proteinuria after 20 weeks of gestation) [Citation25].
Variable selection
We collected data on maternal age (years), mother’s race, mother’s educational level, marital status, father’s race, smoking (before pregnancy, during pregnancy), GWG (kg), WG (kg), the timing of initiation of prenatal care (month), prenatal care visits for pregnancy, BMI (kg/m2), multipara, gestational diabetes mellitus (GDM), pre-pregnancy diabetes mellitus (DM), gestational hypertension, eclampsia, previous preterm birth, previous cesarean section, final route and method of delivery (spontaneous, forceps or vacuum, cesarean, and unknown), and assisted reproductive treatment (ART).
GWG is defined as the difference between the weight measured at the last prenatal examination before delivery and that measured at the initial prenatal examination [Citation11]. GWG values were classified based on the 2009 Institute of Medicine (IOM) guidelines [Citation26]. Excessive GWG was defined as a total GWG of > 11.5 kg for women with a pre-pregnancy BMI between 25 and 29.9 kg/m2 or a total GWG of > 9 kg for women with a pre-pregnancy BMI of ≥ 30 kg/m2 [Citation27].
Outcomes and follow-up
The outcome of this study was PTB occurrence. PTB is defined as birth before 37 gestational weeks [Citation28], consistent with the ICD-9 (International Classification of Diseases, Ninth Revision) and ICD-10 (International Classification of Diseases, Tenth Revision) definitions [Citation29].
Statistical analysis
The normal distribution data were described using the mean ± standard deviation (mean ± SD) and t-test for comparison between groups. Non-normal distribution data were described by median and quartiles [M (Q1, Q3)] and the Mann-Whitney U rank test was used for comparison. Categorical data were expressed as number and constituent ratio [N (%)], and the chi-square test was used for comparison.
Univariate logistic regression analyses were used for the screening of covariate linked to PTB and HDP respectively. The variables that related to PTB or HDP with a p value <.05 were included in the adjusted model. We used both univariate and multivariate logistic regression analyses to explore the association between pre-pregnancy BMI and HDP, HDP, and PTB, and pre-pregnancy BMI and PTB. Model 1 was a crude model. Model 2 was adjusted for the variables including maternal age, mother’s race, mother’s educational level, marital status, father’s race, smoking, GWG, GDM, pre-pregnancy DM, previous PTB, previous cesarean, ART, the timing of initiation of prenatal care, and multiparity. Model 3 was additionally adjusted for HDP compared to the covariates in Model 2.
To explore the mediating effect of HDP on the association between pre-pregnancy BMI and PTB risk, generalized structural equation modeling (SEM) was performed. SEM is a set of statistical techniques used to measure and analyze the relationships between observed and latent variables, and it can examine linear causal relationships among variables while simultaneously accounting for measurement errors [Citation30]. The standardized regression coefficients and standard errors (SE) of the path between the independent and mediating variables and the path between the mediating variable and outcome were written into the R Mediation package [Citation31] to calculate the estimates of the products of the two paths and 95% confidence intervals (CIs). We further explored the mediating effect of HDP on the association between pre-pregnancy BMI and PTB in age and GDM subgroups. The classification standard of the age subgroup was according to the cutoff value of elderly parturient (≥35 years old) [Citation32]. And the classification standard of the GDM subgroup was according to the “risk factors in this pregnancy” entry in the U.S. Standard Certificate of Live Birth [Citation33].
The evaluation index was odds ratio (ORs) with 95% CIs. Statistical significance was set at p < .05. Statistical analyses were performed using SAS 9.4 (SAS Institute, Cary, NC, USA). Missing data, including ART (n = 2670) and multipara (n = 2509) were deleted, and sensitivity analysis was performed on the participants’ characteristics before and after deletion (Table S1).
Results
Characteristics of study population
A comparison of the characteristics between women with PTB and non-PTB is shown in . In this study, 324,627 women (9.99%) had PTB. The average maternal age of women with PTB and non-PTB were respectively 29.41 and 29.27 years old. Most of the women’s GWG were above the IOM guidelines: 127,151 (39.17%) had PTB and 1,406,837 (48.10%) without PTB. There were 31,088 (9.58%) women with GDM in the PTB group, and 215,473 (7.37%) in the non-PTB group. In the PTB group, 54,406 (16.76%) had gestational hypertension and 2695 (0.83%) had eclampsia, while in the non-PTB group, there were 219,932 (7.52%) and 5478 (0.19%), respectively. Additionally, the mother’s race, mother’s education level, marital status, father’s race, father’s education level, smoking status, WG, the timing of initiation of prenatal care, prenatal care visits for pregnancy, BMI, multiparity, pre-pregnancy DM, previous cesarean section, final route and method of delivery, and ART were significantly different between the two groups (all p < .001).
Table 1. Characteristics of singleton pregnancies women with live births.
Association between pre-pregnancy BMI and HDP, HDP and the risk of PTB, and pre-pregnancy BMI and the risk of PTB
We first screened for potential confounding factors associated with PTB and HDP (). The results showed that maternal age, mother’s race, marital status, mother’s education level, father’s race, smoking status, GWG, the timing of initiation of prenatal care, multipara, pre-pregnancy DM, GDM, previous PTB, previous cesarean section, and ART were significantly associated with both PTB and HDP (all p < .05).
Table 2. Covariates screening for PTB and HDP.
After adjusting for the screened covariates, we explored the associations between pre-pregnancy BMI and HDP, HDP, and PTB, and pre-pregnancy BMI and PTB respectively (). Pre-pregnancy overweight or obesity was significantly associated with an increased risk of HDP [OR = 2.10, 95% CI: (2.08–2.12)]. HDP was also correlated with an increased risk of PTB [OR = 2.56, 95% CI: (2.53–2.59)]. Meanwhile, there was a significant association between pre-pregnancy overweight or obesity and an increased risk of PTB [OR = 1.04, 95% CI: 1.03–1.05)].
Table 3. Association between pre-pregnancy BMI and HDP, HDP and PTB, and pre-pregnancy BMI and PTB.
Mediating effect of HDP on the association between pre-pregnancy BMI and the risk of PTB, and in age and GDM subgroups
shows the mediation structural model of HDP in terms of the mediating effect on pre-pregnancy BMI and the risk of PTB. shows the mediating effects of HDP. HDP had a significant mediating effect on the association between pre-pregnancy BMI and PTB risk, with a proportion of mediation accounted for 63.62%, 95% CI: (59.12%–68.11%). Additionally, the interaction between pre-pregnancy BMI and risk of HDP was negligible (p = .279).
Figure 2. Mediation structural model of the effect of HDP on the association between pre-pregnancy BMI and the risk of PTB.
Table 4. The mediating effect of HDP on the relationship between pre-pregnancy BMI and PTB.
We further analyzed the mediating effect of HDP in the age and GDM subgroups (). The mediating effect of HDP on the association between pre-pregnancy BMI and the risk of PTB was found in women aged <35 years [proportion of mediation = 76.78%, 95% CI: (69.32%–84.25%)] and ≥35 years [proportion of mediation = 38.53%, 95% CI: (35.06%–42.00%)]. The effect of pre-pregnancy BMI on the risk of PTB was significantly mediated by HDP whether in women with GDM or not, with a proportion of mediation of 62.38% and 64.39% severally.
Table 5. Mediating effect of HDP on the association between pre-pregnancy BMI and the risk of PTB in age and GDM subgroups.
Discussion
This retrospective cohort study aimed to explore the mediating effect of HDP on the association between pre-pregnancy BMI and PTB risk in women with singleton live births. The results showed that there were significant associations between pre-pregnancy BMI and HDP and between HDP and the risk of PTB. The mediating effect analysis found that the association between pre-pregnancy BMI and PTB risk was significantly mediated by HDP, especially in women of different ages and GDM status.
Connections between overweight/obesity before pregnancy and the risk of HDP have been found in published articles [Citation32–34]. The association between HDP and PTB risk has been reported in recent studies [Citation16,Citation35,Citation36]. Similarly, our study showed that pre-pregnancy overweight and obesity were related to the risk of HDP and PTB, while HDP was significantly associated with the risk of PTB. A study examined pre-pregnancy BMI and adverse pregnancy outcomes, and the association between pre-pregnancy overweight and obesity and the risk of PTB remained significant after adjusting for preeclampsia, GDM, and other confounding conditions [Citation37]. The gradient boosting machine was further used to explore the significance of variables and it was found that preeclampsia may be a more important influencing factor than pre-pregnancy BMI [Citation37]. A cohort study on gestational WG and adverse pregnancy outcomes in women with chronic hypertension suggested that the relationship between GWG and PTB may depend on pre-pregnancy BMI [Citation38]. Another study in Chinese pregnant women showed that pre-pregnancy obesity and gestational abnormal glucose metabolism (GAGM) were independently associated with an increased risk of PTB [Citation39]. The combination of pre-pregnancy obesity and GAGM further worsens adverse pregnancy outcomes compared to each condition alone [Citation36]. However, whether HDP mediates the relationship between pre-pregnancy BMI and PTB remains unclear. This study found a significant mediating role of HDP in the effect of pre-pregnancy BMI on PTB risk. Mayo et al. [Citation40] showed that after excluding mothers with previous hypertension and diabetes, the association between high BMI and PTB was slightly weakened, and after the removal of combined HDP and GDM, the hazard ratio was further reduced.
The mechanisms linking pre-pregnancy BMI to adverse pregnancy outcomes and complications are complex and unclear. Overweight and obesity affect insulin signaling pathways and have been associated with inflammation, insulin resistance, and oxidative stress [Citation41,Citation42]. Oxidative stress, endothelial dysfunction, and inflammation are important factors in the occurrence and development of HDP and DM [Citation1]. Several metabolic perturbations have also been suggested to be responsible for the association between obesity and preeclampsia, such as elevated leptin levels, proinflammatory status, or dysfunction of the nitric oxide synthase system [Citation43]. Moreover, in the development of the placenta, endothelial dysfunction, including histopathological changes in blood vessels and intravascular coagulation, induces elevated blood pressure (BP) [Citation44,Citation45]. HDP decreases placental perfusion and reduces the amount of nutrients needed for fetal growth, resulting in fetal growth restriction and, ultimately, PTB occurrence [Citation44,Citation45]. We hypothesized that the relationship between being overweight or obese before pregnancy and the risk of HDP may affect oxidative balance, inflammatory processes, and/or endothelial dysfunction, leading to adverse pregnancy outcomes, such as PTB [Citation14]. In addition, due to PE is a clear indication of pregnancy termination, that the mediation effect of HDP in the association between obesity and PTB may be partly explained by pregnancy terminations in women who had a PE [Citation46]. Further studies on the mechanisms of the mediation effect of HDP are needed.
We also explored the mediating effect of HDP on the association between pre-pregnancy BMI and PTB in subgroups of age and GDM. The results showed that the mediation effect of HDP on the association between pre-pregnancy BMI and the risk of PTB was also found in women of different ages, with or without GDM. Age and GDM are common risk factors of HDP and adverse pregnancy outcomes [Citation47,Citation48]. Thakur et al. [Citation35] found the pregnancy outcome in women with HDP versus normotensive pregnancy, indicating that HDP was more common in primigravida in the young age group of 20–24 years, and PTB was the most common fetal complication seen in HDP. Smithson et al. [Citation49] found that gestational hypertension, preeclampsia with and without severe features, and eclampsia were all significantly higher in the very advanced maternal age (≥45 years) group than in the advanced maternal age group (35–44 years old). A population-based study also showed that pregnant mothers with chronic hypertension (CHTN) were at or above 35 years of age at the time of delivery 58.9% compared to non-CHTN 18.7%, and PTB was noted in 26% compared to 8% in CHTN compared to non-CHTN women [Citation50]. Vambergue et al. [Citation51] demonstrated that HDP is related to the level of glucose intolerance during pregnancy independent of other known factors of hypertension. GDM also increases preeclampsia risk [Citation52]. GDM and preeclampsia share many risk factors such as advanced maternal age, multifetal pregnancies, and pre-pregnancy obesity [Citation53,Citation54]. Combined with our findings, suggestions should be taken into consideration for women who are preparing for pregnancy, and controlling weight to achieve an appropriate BMI may reduce the risk of HDP, while those who are pregnant should actively and dynamically monitor the BP level to reduce the risk of HDP and further PTB.
The study population was from the NVSS database, and the sample size was large and representative. To some extent, this study clarified the pathway of the connection between pre-pregnancy BMI, HDP, and PTB, which may provide some references for the management of pregnant women and the formulation of strategies to decrease the risk of PTB. However, this study had some limitations. Information on women, such as HDP and PTB, was obtained from the medical records in this retrospective study, and biases may exist. We used logistic regression models with ORs to reflect the risk of PTB, which may overestimate relative risks. In addition, only women with singleton pregnancies were included in this study, considering that the risk of PTB in multiple pregnancies was significantly higher than that in singleton pregnancies [Citation55]. Therefore, further research focusing on the mediating effect of HDP on the correlation between pre-pregnancy BMI and PTB in multiple pregnancies is warranted.
Conclusion
HDP may play a mediating role in the effect of pre-pregnancy BMI on PTB risk. Women preparing for pregnancy should pay close attention to BMI, and pregnant women should monitor and develop interventions for HDP to reduce the risk of PTB.
Supplemental Material
Download MS Word (25.8 KB)Disclosure statement
The authors report there are no competing interests to declare.
Data availability statement
Data in this study were extracted from the National Vital Statistics System (NVSS) database. The datasets generated and/or analyzed during the current study are available in the NVSS repository, https://www.cdc.gov/nchs/nvss/index.htm.
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References
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