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30 May 2024: Database Analysis  

Maternal Exposure to Environmental Air Pollution and Premature Rupture of Membranes: Evidence from Southern China

Xiaowu Yang1ABCDEG*, Fengsheng Xu2DF, Gongyan Ma3CD, Feng Pu1B

DOI: 10.12659/MSM.943601

Med Sci Monit 2024; 30:e943601

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Abstract

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BACKGROUND: Exposure to air pollution (AP) during pregnancy is associated with pre-labor rupture of membranes (PROM). However, there is limited research on this topic, and the sensitive exposure windows remain unclear. The present study assessed the association between AP exposure and the risk of PROM, as well as seeking to identify the sensitive time windows.

MATERIAL AND METHODS: This retrospective study analyzed 4276 pregnant women’s data from Tongling Maternal and Child Health Hospital from 2020 to 2022. We obtained air pollution data, including particulate matter (PM) with an aerodynamic diameter of ≤2.5 μm (PM₂․₅), particulate matter with an aerodynamic diameter of ≤10 μm (PM₁₀), nitrogen dioxide (NO₂), and ozone (O₃), from the Tongling Ecology and Environment Bureau. Demographic information was extracted from medical records. We employed a distributed lag model to identify the sensitive exposure windows of prenatal AP affecting the risk of PROM. We conducted a sensitivity analysis based on pre-pregnancy BMI.

RESULTS: We found a significant association between prenatal exposure to AP and increased PROM risk after adjusting for confounders, and the critical exposure windows of AP were the 6th to 7th months of pregnancy. In the underweight group, an increase of 10 µg/m³ in PM₂․₅ was associated with a risk of PROM, with an odds ratio (OR) of 1.48 (95% CI: 1.16, 1.89). Similarly, a 10 µg/m³ increase in PM₁₀ was associated with a risk of PROM, with an OR of 1.45 (95% CI: 1.05, 1.77).

CONCLUSIONS: Prenatal exposure to AP, particularly during months 6-7 of pregnancy, is associated with an increased risk of PROM. This study extends and strengthens the evidence on the association between prenatal exposure to AP and the risk of PROM, specifically identifying the critical exposure windows.

Keywords: Air Pollution, Pregnancy Outcome, Fetal Membranes, Premature Rupture

Introduction

Pre-labor rupture of membranes (PROM), preceding the onset of labor, occurs in about 2–3% of pregnancies and is a precursor to many preterm births [1]. Globally, PROM is identified as a leading contributor to preterm births [2], and its consequences can be severe, including intra-amniotic infection, fetal distress, neonatal sepsis, and heightened perinatal mortality and morbidity [3,4]. The prevailing hypothesis in the recent literature suggests that the genesis of PROM is multifactorial, with environmental air pollution emerging as a notable variable of concern [5]. Among the pollutants, particulate matter (PM), especially fine particles with a diameter of less than 2.5 micrometers (PM2.5), has been closely monitored due to its ability to penetrate deep into the lung alveoli and enter the systemic circulation, potentially affecting placental function and fetal development (Ritz et al, 2007). While the impact of air pollution on respiratory and cardiovascular health is well-documented, its role in obstetric outcomes, such as PROM, needs further investigation.

Air pollution’s impact on public health is a critical concern, particularly in the rapidly industrializing regions of southern China where industrial emissions and vehicular pollutants significantly deteriorate air quality [6,7]. These environmental stressors are not only a cause for respiratory and cardiovascular diseases [8] but are increasingly being scrutinized for their effects on maternal and fetal health outcomes [9]. Adverse impacts of maternal air pollution exposure on fetal growth, preterm birth, and other birth outcomes have been reported [10]. Understanding risk factors for PROM is important for prevention. Previous studies have provided initial insights into the association between pollutants and PROM, but further exploration of the key exposure windows remains to be completed. A large-scale cohort study in the United States identified the first and second months, as well as the seventh and eighth months, as crucial exposure windows for the association between AP exposure and PROM [11]. Additionally, a Chinese cohort study spanning nearly a decade found that the exposure window of AP to PROM primarily occurs between the 21st and 24th weeks of pregnancy [12]. However, research in this field is limited. Additional research is required to advance our understanding of the critical exposure windows during pregnancy.

The objective of this study was to elucidate the association between maternal exposure to AP and the risk of PROM by analyzing data from pregnant women who delivered at Tongling Maternal and Child Health Hospital over the past 3 years. Additionally, the study aimed to identify critical exposure windows and quantify associated risks.

Material and Methods

STUDY POPULATION:

From 2020 to 2022, more than 70% of expectant mothers in the city received medical care at Tongling Maternal and Child Health Hospital, a tertiary level-A institution that combines medical services, healthcare, teaching, and research. We accessed comprehensive medical information from the hospital’s electronic health records, encompassing maternal demographic factors, residential history, medical and obstetric records, and personal health-related behaviors. After excluding cases involving multiple pregnancies, stillbirths, and instances where demographic information was incomplete, a total of 4276 pregnant women with complete information were included in the study.

ASSESSMENT OF PROM:

Women diagnosed with preterm premature rupture of membranes (preterm PROM) and term premature rupture of membranes (term PROM) were identified using clinical records from Tongling Maternal and Child Health Hospital. The diagnosis of PROM was coded as O42, following the International Classification of Diseases and Related Health Problems, 10th Revision (ICD-10). Preterm PROM and term PROM are defined by the rupture of fetal membranes occurring before 37 weeks and at or after 37 weeks of gestation, respectively. Instances of PROM due to medical interventions were not considered in our study [13]. The study’s pregnancy period commenced from the date of the last menstrual period confirmed by ultrasonography and concluded on the date of rupture of membranes [14].

EXPOSURE ASSESSMENT:

Environmental air pollution data for PM2.5, PM10, NO2, and O3 levels at 8 air monitoring stations in Tongling City can be accessed on the Tongling City Environmental Forecast Management Bureau website (http://218.22.184.155:8231/kqlist.aspx). For the air pollution data from 2020 to 2022, we employed empirical Bayesian kriging (EBK) to calculate the monthly mean concentrations of PM2.5, PM10, NO2, and O3. The cross-validation r2 values for different air pollutants using the EBK method were 0.65–0.75. Detailed information on residential mobility throughout the entire pregnancy was geocoded.

Monthly air pollution data were temporally interpolated to obtain exposure estimates for each participant based on their geocoded residential address for each pregnancy month. This was primarily done to simplify monthly analyses. The pregnancy months were calculated based on a 30-day cycle, utilizing approximate cutoff points for each trimester (eg, first trimester: pregnancy months 1–3 [1–90 days]; second trimester: pregnancy months 4–6 [91–180 days]; third trimester: pregnancy months 7–9 [181–270 days]).

CONFOUNDING VARIABLES:

Due to a local government project investigating factors influencing adverse pregnancy outcomes, revisions were made to the hospital’s electronic system with the aim of collecting potential confounding factors as comprehensively as possible. Utilizing the confounding factors gathered from the study, this research specifically chose variables associated with the outcome variable PROM. These chosen variables are: maternal age (in years), maternal education level (categorized as ≥13 years to indicate completion of high school or <13 years), family income (classified into 3 levels: low, medium, and high according to the local yearbook and converted into USD), pre-pregnancy body mass index (BMI, measured in Kg/m2), premature birth (yes or no), gestational diabetes mellitus (yes or no), diastolic blood pressure (measured in mmHg) and systolic blood pressure (measured in mmHg), measurements of temperature (in Celsius) and humidity (g/m3), family history of diabetes (yes or no), passive smoking (yes or no), parity (number of pregnancies), physical activity frequency (<3, 3–6, ≥6 days/week, at least 30 minutes per session), and season of delivery (spring, summer, autumn, winter).

STATISTICAL ANALYSIS:

Descriptive statistics were employed to summarize the demographic characteristics of participants with and without PROM. The chi-square test was utilized to compare the characteristics of women with and without PROM. The correlation between exposure to each pollutant throughout the entire pregnancy was assessed using Pearson correlation analysis. To identify susceptibility windows, we used a discrete-time method with a fitted logit function to estimate the association between air pollution exposure and PROM for each period, including the entire pregnancy, individual pregnancy months, and the trimesters.

We used a distributed lag non-linear model to investigate, in both unadjusted and adjusted models, the period from June to July as a sensitive window for the association between air pollution exposure and PROM. The model incorporated age, pre-pregnancy BMI, premature birth, diastolic blood pressure, systolic blood pressure, family history of diabetes, parity, season of delivery, and temperature. Moreover, we employed 2-pollutant models to examine the association between air pollution exposure and PROM. To evaluate how pre-pregnancy health status influences pregnant women’s susceptibility to PROM, we performed a subgroup analysis stratified by pre-pregnancy BMI to explore potential moderating effects. Heterogeneity among BMI subgroups was assessed using Cochran’s Q test. Statistical significance was assessed at a 2-sided P value <0.05. The analyses were carried out using the SPSS statistical software (SPSS, version 23.0, IBM Corp: Armonk, NY, USA) and the R statistical software package (version 3.5.0; “ggplot2”, “dlnm”).

Results

Table 1 summarizes the study population characteristics. A total of 4267 pregnancies with 693 (16.2%) PROM cases from 2020 to 2022 were included. Women experiencing PROM were older and tended to have higher BMI, a history of premature birth, elevated diastolic and systolic blood pressure levels, a familial predisposition to diabetes, multiparity, and a propensity for delivering during the winter season.

Table 2 illustrates air pollutant exposure levels throughout the entire pregnancy for the PROM and non-PROM groups. The mean levels of PM2.5, PM10, NO2, and O3 for the entire pregnancy were 50.70± 30.62μg/m3, 78.70±38.68μg/m3, 41.42±17.75 μg/m3, and 100.86±45.96 μg/m3, respectively. There are statistically significant differences in the levels of the pollutants between PROM and non-PROM pregnant women, with all P values being less than 0.05.

We utilized distributed lag non-linear models to investigate the association between PM2.5, PM10, NO2, and O3 exposure and PROM risk across all 3 trimesters, both in unadjusted and adjusted models (Table 3). After adjusting for age, pre-pregnancy BMI, premature birth, diastolic blood pressure, systolic blood pressure, family history of diabetes, parity, season of delivery and temperature, elevated risks of PROM were associated with exposure to each pollutant during the second and third trimesters. The cumulative risk of PROM displayed a significant correlation with prenatal exposure to air pollutants during the second and third trimesters. The strongest associations were found for PM2.5 and PM10, followed by NO2 and O3. For instance, during the second and third trimester periods, for each 10 μg/m3 increase in PM2.5, the cumulative odds ratios (OR) were 1.11 (95% CI: 1.04, 1.18) and 1.17 (95% CI: 1.12, 1.23), respectively. Likewise, significant associations were observed for each 10 μg/m3 increment in PM10, with OR of 1.09 (95% CI: 1.03, 1.16) in the second trimester and 1.14 (95% CI: 1.10, 1.80) in the third trimester.

Figure 1 depicts the monthly associations between air pollution and PROM, as estimated using the distributed lag model. Overall, throughout the monthly associations and trimester-specific findings, consistent critical exposure windows were identified. Increased risks associated with AP were observed during mid-pregnancy and late pregnancy (gestational months 4–8). The critical exposure windows of PM2.5 and PM10 were in months 6 and 7, respectively. For NO2 and O3, the critical exposure windows were also months 6 and 7, respectively.

We performed subgroup analyses based on pre-pregnancy BMI, as illustrated in Figure 2. Significant correlations were identified in most subgroups for various air pollutants, with the exception of O3. The women with the lowest pre-pregnancy BMI tended to have higher risks of PROM associated with PM2.5 and PM10. For example, among women in the underweight group, an increase of 10 μg/m3 in PM2.5 was associated with an increased risk of PROM, with an odds ratio (OR) of 1.48 (95% CI: 1.16, 1.89). Similarly, a 10 μg/m3 increase in PM10 was associated with higher risk of PROM, with an OR of 1.45 (95% CI: 1.05, 1.77). Substantial variability in the relationships with PM2.5 and PM10 exposure was identified among distinct BMI subgroups, with P values <0.01.

Discussion

We observed a significant association between prenatal exposure to air pollution (AP) and an increased risk of preterm rupture of membranes (PROM), particularly during the critical exposure windows of the 6th to 7th months of pregnancy. Sensitivity analysis indicates that pregnant women with low pre-pregnancy BMI are at increased risk of preterm rupture of membranes associated with exposure to PM2.5 and PM10.

PROM is a common pregnancy complication caused by complex pathophysiological factors. The increasing interest in this condition is driven by its association with elevated levels of environmental air pollution [15,16]. To date, the evidence regarding the impact of air pollution remains limited, and the findings are not consistent. The contrasting results presented in these studies may be attributed to significant variations in levels of air pollution, disparate household conditions, and differences in population characteristics. Dadvand et al [17]were the first to establish a link between exposure to air pollution and the risk of preterm premature rupture of membranes. Similarly, in a more recent study in China, a focus on air pollutants such as PM2.5, PM10, NO2, and O3 revealed consistent associations with an increased risk of PROM [11]. Furthermore, a longitudinal study conducted in the United States, encompassing 3264 women and 7121 singleton births, demonstrated that heightened PM2.5 exposure during pregnancy was linked to an elevated risk of preterm birth. A retrospective cohort study documented an association between long-term exposure to NOx and PROM; the authors suggested that varying levels of NOx pollution might yield inconsistent interpretations, noting that the NOx concentration in their study was 28.9 μg/m3, with the median level surpassing that of other investigations[18].

We found that the maximum impact windows for PM2.5, PM10, NO2, and O3 occur during the 6th to 7th months of pregnancy. The findings of a meta-analysis indicated that, across various stages of pregnancy, the correlation during the late pregnancy period exhibited the highest precision and significance in the relationship between air pollution and pregnancy outcomes [19]. A cohort study conducted in Guangzhou further substantiated these findings, indicating that the mid-to-late pregnancy period is the most sensitive exposure window for PROM [20]. Moreover, a longitudinal cohort study conducted in Wuhan, China explored the specific impact of AP exposure on PROM risk during different trimesters, revealing heightened vulnerability during the second and third trimesters [21]. These findings align with our study’s emphasis on exposure windows, supporting the notion that distinct gestational periods may exhibit varying susceptibility to air pollution-induced PROM. Prenatal exposure to air pollution during this sensitive period may disrupt the delicate balance of membrane integrity, making them more susceptible to premature rupture [22]. One potential reason for this is that during the exposure window, heightened immune responses may lead to accelerated aging of fetal membranes [23,24].

The observed impact of PM2.5 and PM10 among the 4 air pollutants underscores the specific risks associated with fine particulate matter exposure during pregnancy. These findings align with existing literature highlighting the adverse effects of particulate pollution on maternal and fetal health [25,26]. The impact of PM2.5 and PM10 implies that these particles harbor distinctive characteristics or mechanisms of action, amplifying the risks to the integrity of fetal membranes and consequently increasing the susceptibility to PROM [27]. Previous studies have indicated that inflammation plays a substantial role in the pathophysiology of adverse pregnancy outcomes, including PROM [28,29]. Exposure to PM2.5 could undermine membrane structure or placental functions by promoting oxidative stress or inflammation [30]. Exposure during the critical 6–7-month window could intensify inflammatory responses, additionally damaging the elasticity of the fetal membranes [31].

Our study findings indicate a stronger association between increased exposure to AP and the risk of PROM within the underweight subgroup. There could be several reasons for this phenomenon. Underweight pregnant women, due to their fragility and potential immune system compromise, may have reduced antioxidant reserves, thereby increasing the risk of PROM induced by particle exposure [32]. Secondly, being underweight may reflect the nutritional status of pregnant women, and malnutrition could weaken the immune system, thereby increasing sensitivity to environmental pollutants[33]. Additionally, the BMI of underweight individuals could intensify lung deposition and retention of particles [34]. Further research is warranted to delve deeper into the mechanisms underlying these associations, ultimately paving the way for informed strategies to mitigate the risks posed by prenatal air pollution exposure on maternal and fetal health.

Our study has several strengths. Firstly, the inclusion of complete information from 4267 pregnant women contributed to a large and statistically robust sample, increasing the study’s representativeness and reliability of results. Secondly, the study explored the key exposure windows for each pollutant, contributing to a nuanced understanding of when during pregnant women may be more sensitive to air pollution. Additionally, by harnessing the healthcare system and drawing on insights from other investigations, we collected a broad spectrum of potential confounding factors. Nevertheless, this study has several limitations. Firstly, the research was conducted in a specific region, potentially limiting its generalizability to other areas. Geographic and demographic differences may have influenced the study’s external validity. Secondly, despite accounting for some confounding factors, there may be other unconsidered variables that could have impacted the study results, such as individual lifestyle and nutritional status. Moreover, we did not assess air and noise pollution associated with traffic, which has been shown to be related to preterm premature rupture of membranes. Thirdly, while the study addressed sensitive windows for PROM, a deeper understanding of the specific biological mechanisms and pathophysiological processes involved in preterm premature rupture of membranes awaits further investigation. Additionally, we employed a broad definition of pregnancy months, and we did not examine narrower exposure windows or any acute effects of air pollution exposure, including weekly or daily associations, as we only had access to monthly air pollution data. Finally, assigning exposure data to the nearest air quality monitor instead of estimating individual air pollution exposure may have yielded inaccurate results.

Conclusions

Prenatal exposure to AP, particularly during months 6–7 of pregnancy, is associated with an increased risk of PROM. Pregnant women with low pre-pregnancy BMI are at an increased risk of PROM when exposed to PM2.5 and PM10 environments. These findings highlight the need for further research to elucidate the underlying mechanisms and inform targeted interventions aimed at reducing adverse pregnancy outcomes associated with air pollution exposure.

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