Vaping during pregnancy and its impact on neonatal outcomes: A systematic review and meta-analysis

Abstract

BACKGROUND

Vaping during pregnancy is becoming more prevalent, with nearly 7% of individuals using e-cigarettes. This increase may result from tobacco companies targeting younger users with e-cigarette marketing, similar to their strategies with traditional tobacco. While e-cigarette use continues to rise, evidence regarding its effects on neonatal outcomes remains inconsistent.

AIM

To examine research on the connection between vaping during pregnancy and negative neonatal outcomes, exploring the potential adverse effects.

METHODS

According to PRISMA guidelines, we conducted a thorough review of studies from PubMed/MEDLINE, Google Scholar, Scopus, EMBASE, and Web of Science for eligible studies that reported on vaping during pregnancy and its effects on neonatal outcomes, including low birth weight (LBW), preterm birth (PTB), and small for gestational age (SGA). We utilized binary random-effects models to estimate pooled odds ratios (OR) and 95% confidence intervals (CI). A P value of ≤ 0.05 was deemed statistically significant.

RESULTS

A total of 14 studies with 523273 pregnant women were included in the analysis. Of them, 3840 (0.7%) vaped during pregnancy. In comparison to pregnant women who did not vape, neonates born to those who vaped had significantly higher odds of LBW (OR: 1.60; 95%CI: 1.23-2.09; P = 0.0005) and SGA (OR: 1.73; 95%CI: 1.34-2.22; P < 0.0001), as well as higher odds of PTB (OR: 1.95; 95%CI: 0.74-5.14; P = 0.17).

CONCLUSION

Vaping during pregnancy is significantly associated with adverse neonatal outcomes, LBW, and SGA, emphasizing the potential risks of vaping during pregnancy and highlighting the necessity for public health initiatives to increase awareness and develop preventive strategies.

Key Words: Vaping; Neonatal outcomes; Low birth weight; Small for gestational age; Preterm birth; Meta-analysis

Core Tip: Vaping during pregnancy is associated with significantly increased odds of low birth weight and small for gestational age, highlighting potential adverse neonatal outcomes. Pregnant individuals who vape, despite a lower overall prevalence, face heightened risks for these complications. These findings underscore the need for targeted public health interventions and further research to understand the long-term impacts of prenatal e-cigarette exposure.

INTRODUCTION

The landscape of nicotine consumption has dramatically shifted with the advent of electronic nicotine delivery systems (ENDS), commonly known as e-cigarettes or vapes[1]. Marketed as a safer alternative to traditional cigarettes, ENDS have witnessed a surge in popularity across diverse demographics, including pregnant women[1]. This trend of rising ENDS use has also been observed in pregnant women[2,3], with a 4.9% prevalence rate, according to the population assessment of tobacco and health (PATH) study[4]. This increasing prevalence highlights an urgent public health concern due to the potential for significant long-term impacts of prenatal exposure to e-cigarettes on both maternal and neonatal health. Despite the growing prevalence, a critical knowledge gap persists regarding the specific risks associated with ENDS use during pregnancy. This is particularly concerning given the perception, often fueled by marketing and accessibility, that ENDS represents a lower-risk cessation tool[5,6]. In contrast, cigarette smoking during pregnancy and postpartum is well-studied, with established associations with various short- and long-term adverse outcomes. However, the risks associated with ENDS use during pregnancy remain largely unknown.

Although extensive research elucidates the detrimental effects of ENDS exposure to a spectrum of toxic substances, including carbonyl compounds, volatile organic compounds, and heavy metals, leading to conditions like vaping associated lung injury and heightened risks of cardiovascular disease and cancer[7], these studies largely exclude pregnant populations. Furthermore, the limited availability of research on the direct impact of ENDS on pregnancy and neonatal outcomes presents a concerning picture, with conflicting evidence regarding potential harms compared to traditional smoking. This meta-analysis aims to address this critical knowledge gap by comprehensively examining the association between ENDS use during pregnancy and adverse neonatal outcomes, thereby providing essential evidence for public health initiatives and informed decision-making. By synthesizing existing research, we aim to clarify potential risks, enable evidence-based counseling for pregnant individuals, inform health policy development, and ultimately empower pregnant individuals to make informed decisions for optimal maternal and child health.

MATERIALS AND METHODS

Per the PRISMA (Preferred Reporting Items for Systematic Reviews and Meta-analyses) guidelines[8], a comprehensive literature search was performed across several prominent databases, including PubMed/MEDLINE, Google Scholar, Web of Science, and Science Direct, to identify relevant studies. The search strategy was formulated using appropriate Boolean operators with the following keywords: “pregnancy”, “e-cigarette”, “vaping”, “electronic nicotine delivery system”, “neonatal outcomes”, “low birth weight”, and “preterm birth”. The references of the selected studies were manually reviewed to ensure no pertinent information was overlooked.

For the study selection process, titles and abstracts (TiAb) were screened independently by two reviewers, MC and SV, with conflicts resolved by mutual consensus. Full-text screening was independently done by two reviewers, AB and MM, with conflicts resolved by mutual consensus. Original research studies that examined vaping during pregnancy and its effects on neonatal outcomes were included. Figure 1 depicts the PRISMA flow chart[9] outlining the study selection process. Our outcomes of interest were low birth weight (LBW), preterm birth (PTB), and small for gestational age (SGA). Supplementary Tables 1 and 2 outline the detailed search strategy and study selection criteria, respectively.

Figure 1 PRISMA flow chart of study selection process.

Data extraction was performed using a standardized form. The extracted data included author, year, study design, sample size, vaping exposure assessment, outcome definitions, adjusted covariates, and effect estimates. Pooled odds ratios (OR) and 95% confidence intervals (CI) were calculated to estimate the overall effect size. A leave-one-out sensitivity analysis was done to assess the robustness of the results, and I² statistics were used to study the heterogeneity in the effect estimate. Heterogeneity was categorized as follows: 25%-50% was deemed mild, 50%-75% was considered moderate, and values exceeding 75% were classified as severe heterogeneity. Forest plots were created depicting the effect measures of each study along with pooled HRs and leave-one-out sensitivity analysis. The risk of bias assessment was conducted using the adaptations of New Castle Ottawa[10] and visualized using the Robvis software[11], with the domains, potential confounding (D1), exposure measurement (D2), participant selection (D3), post-exposure interventions (D4), missing data (D5), outcome measurement (D6), and selective reporting (D7). A meta-analysis was conducted using binary random-effects models to account for variability across studies. Funnel plots were utilized to evaluate for publication bias, where the degree of plot asymmetry was directly proportional to the degree of publication bias. All the statistical analyses were performed using the Review Manager (RevMan) version 5.4.1[12]. A P value < 0.05 was considered to be statistically significant.

RESULTS

Fourteen studies (eight cross-sectional and six cohort) were included in our review[13-26]. Twelve studies were conducted in the United States, one in the United Kingdom, and one in the Netherlands. Table 1 outlines the key characteristics of the included studies. A total of 523273 pregnant women were included in the analysis. Of them, 3840 (0.7%) vaped during pregnancy. In comparison to pregnant women who did not vape, neonates born to those who vaped had significantly higher odds of LBW (OR: 1.60; 95%CI: 1.23-2.09; P = 0.0005) and SGA (OR: 1.73; 95%CI: 1.34-2.22; P < 0.0001), as well as higher odds of PTB (OR: 1.95; 95%CI: 0.74-5.14; P = 0.17). Figure 2 illustrates adverse neonatal outcomes.

Figure 2 Adverse neonatal outcomes. A: Low birth weight; B: Small for gestational age; C: Pre-term births.

Table 1 Key characteristics of included studies.

Ref.	Study type	Country	Vapers	Non users
Ammar et al[13], 2023	Cross-sectional study	United States	977	173574
Cardenas et al[14], 2019	Cohort study	United States	6	106
Cardenas et al[15], 2020	Cross-sectional study	United States	18	1062
Hawkins et al[17], 2022	Cross-sectional study	United States	301	51153
Kim et al[18], 2020	Cross-sectional study	United States	337	51430
McDonnell et al[19], 2020	Cohort study	United States	218	108
Nanninga et al[20], 2023	Cross-sectional study	Netherlands	10	1706
Opondo et al[21], 2021	Cross sectional study	United Kingdom	99	4322
Regan and Pereira[22], 2021	Cross sectional study	United States	189	8938
Regan et al[23], 2021	Cross-sectional study	United States	906	76113
Shittu et al[24], 2022	Cross-sectional study	United States	216	86354
Wang et al[25], 2020	Cross-sectional study	United States	126	28770
Wang et al[26], 2022	Cohort study	United States	285	26365
Wen et al[16], 2023	Cohort study	United States	152	9432

The risk of bias assessment, detailed in Figure 3, revealed varying degrees of methodological rigor across the included studies. While several studies demonstrated low risk in most domains, concerns arose regarding allocation concealment and blinding in some instances, impacting overall study validity. The overall risk of bias is low (Supplementary Figure 1).

Figure 3 Risk of bias assessment.

The leave-one-out analysis for LBW showed that removing each study individually led to pooled odds ratios ranging from 1.49 (95%CI: 1.32-1.68) to 1.72 (95%CI: 1.33-2.24). Likewise, for PTB, the removal of each study individually resulted in pooled odds ratios from 1.53 (95%CI: 1.29-1.80) to 2.13 (95%CI: 0.75-6.03). For SGA, the individual results varied from 1.58 (95%CI: 1.27-1.96) to 1.86 (95%CI: 1.46-2.37) (Supplementary Table 3). The funnel plots for LBW, PTB, and SGA exhibit a degree of asymmetry (Supplementary Table 3).

DISCUSSION

Our meta-analysis, comprising fourteen studies and 523273 pregnant women, found significant associations between vaping during pregnancy and adverse neonatal outcomes. Specifically, neonates born to women who vaped during pregnancy had significantly higher odds of LBW and SGA, findings robust to leave-one-out sensitivity analysis.

The current findings of our study are consistent with previous research demonstrating that vaping during pregnancy is associated with adverse perinatal outcomes. A meta-analysis by Deprato et al[27] also reported increased odds of adverse perinatal outcomes (OR: 1.44; 95%CI: 1.21-1.72), pregnancy-related conditions (OR: 1.37; 95%CI: 1.06-1.76), and neonatal conditions (OR: 1.57; 95%CI: 1.37-1.80) in women who vaped during pregnancy. Similar to our results, Deprato et al[27] also found significantly increased odds of LBW (OR: 1.64; 95%CI: 1.24-2.16), preterm birth (OR: 1.39; 95%CI: 1.16-1.66), and SGA (OR: 1.59; 95%CI: 1.29-1.97) in association with vaping during pregnancy. Furthermore, studies have also compared vaping to combustible cigarettes (CC) regarding the impact on maternal and neonatal outcomes. Studies have reported that although vaping-related adverse maternal and neonatal outcomes are not as adverse as CC smoking, they are still significantly adverse, and studies have concluded that vaping should not be considered a viable gestational smoking cessation strategy[28-30].

Despite being marketed as a safer alternative, e-cigarettes contain nicotine, which is a central component in the detrimental effects of maternal tobacco smoke exposure on fetal development, primarily manifested as intrauterine growth restriction (IUGR) and associated reductions in birth weight. Nicotine, along with other toxic components of tobacco smoke, disrupts the intricate processes of fetal nutrient and oxygen delivery. This disruption leads to decreased fetal lean body mass, characterized by reduced head circumference, abdominal circumference, and limb length[29,30]. The observed dose-dependent relationship by Kharrazi et al[31] underscores the direct toxicity of nicotine, with higher exposure levels correlating with more severe growth restrictions. Additionally, e-liquids often contain other potentially harmful substances such as heavy metals and flavorings, which could exacerbate adverse outcomes when combined with nicotine. These specific toxic components contribute to the ongoing concern regarding vaping during pregnancy, even if the overall harm is perceived to be less than that of traditional smoking[30].

Furthermore, genetic predispositions, such as polymorphisms in detoxification enzyme genes like CYP1A1 and GSTT1, modulate the fetal response to nicotine, explaining the variability in neonatal outcomes among exposed pregnancies[32]. These genetic interactions suggest that personalized risk assessments may be necessary to identify vulnerable populations. The long-term implications of nicotine exposure extend beyond birthweight, potentially contributing to increased risks of chronic diseases in adulthood, including short stature, cognitive delays, and cardiovascular disorders. While the specific constituents and delivery mechanisms of e-cigarettes differ from combustible cigarettes, the shared presence of nicotine warrants serious concern. This suggests that even lower levels of exposure from vaping could potentially lead to IUGR and reduced birth weight. The observed reductions in lean body mass, particularly head circumference and limb length, highlight the potential for long-term developmental consequences[33]. The critical window of vulnerability during the third trimester, as seen with traditional smoking, likely extends to vaping as well. The possibility of genetic susceptibilities further complicates the risk profile, suggesting that some fetuses may be more vulnerable to the effects of nicotine from vaping than others. Given that many e-liquids contain additional potentially harmful substances, such as heavy metals and flavorings, the combined effects of these toxins with nicotine could exacerbate adverse outcomes. Additionally, gestational age at birth is a critical determinant of a child's long-term health trajectory. Preterm birth, often associated with vaping, carries significant implications, increasing the risk for neurodevelopmental impairments, respiratory problems, and other chronic conditions throughout life. Hence, the impact of vaping on gestational age is at least as significant as its impact on birth weight, and its implications for future health warrant equal attention.

The significant improvements in fetal outcomes observed with smoking cessation during pregnancy underscore the importance of eliminating nicotine exposure. Studies consistently show that quitting smoking, especially early in pregnancy, results in higher birth weights and improved fetal growth parameters[34,35]. This demonstrates the plasticity of fetal growth and the potential for recovery when nicotine exposure is mitigated. The benefits are maximized with early cessation, ideally before 16 weeks, suggesting that early intervention is crucial. Even reducing the number of cigarettes smoked provides some benefit, reinforcing the notion that any reduction in nicotine exposure can positively influence fetal growth. This evidence supports the hypothesis that cessation of vaping during pregnancy, even if initiated later in gestation, could mitigate some of the adverse effects on fetal development. Future research should focus on quantifying the specific effects of vaping cessation on neonatal outcomes, similar to the established data for traditional smoking cessation.

Limitations

Our meta-analysis, while providing significant evidence linking vaping during pregnancy to adverse neonatal outcomes, is subject to a few limitations. The observed heterogeneity across included studies, despite using a random-effects model, suggests potential variations in study design, participant demographics, and exposure assessments, which could influence the pooled estimates. The reliance on observational studies introduces the risk of residual confounding, as complete adjustment for all potential confounders is challenging. Furthermore, the asymmetry observed in funnel plots indicates a possibility of publication bias, potentially overestimating the reported associations. The predominantly United States-based studies limit the generalizability of findings to diverse populations with varying e-cigarette regulations and usage patterns. The reliance on self-reported vaping data introduces potential recall and social desirability biases, underestimating actual exposure. Crucially, while the overall risk of bias was assessed as low, several included studies exhibited issues with allocation concealment and blinding. The lack of proper blinding in some instances could introduce reporting or detection bias, potentially skewing the reported associations. Similarly, problems with allocation concealment in certain studies may lead to selection bias, thereby undermining the internal validity and overall reliability of the pooled results. A more detailed exploration of these specific methodological shortcomings is warranted to strengthen our findings’ interpretation and acknowledge their potential impact on the study's conclusions.

Future research

Future research should prioritize prospective studies with standardized exposure assessments to establish the causality between vaping during pregnancy and adverse short-term and long-term neonatal outcomes. These studies must incorporate detailed data collection on e-liquid composition, including nicotine concentrations and flavorings, and vaping patterns, such as frequency and duration, to enable the exploration of dose-response relationships and the specific effects of e-cigarette components. Additionally, extended follow-up periods are essential to analyze the long-term impacts of prenatal vaping exposure on neonatal development, addressing the current limitation of immediate post-birth assessments.

CONCLUSION

Our meta-analysis demonstrates a significant association between vaping during pregnancy and adverse neonatal outcomes. These findings underscore the potential risks of e-cigarette use during pregnancy and highlight the urgent need for public health initiatives to raise awareness and implement preventive strategies. Given the rising prevalence of vaping among pregnant women and the potential for long-term developmental consequences, further research is imperative. Future studies should focus on elucidating the causal relationships, exploring the effects of specific e-cigarette components, and examining the long-term impacts of prenatal vaping exposure on neonatal development.