Prenatal lead exposure and risk of Pregnancy-Induced hypertension: A systematic review and Meta-Analysis

Abstract

Background

Pregnancy-induced hypertension (PIH) affects up to 10% of pregnancies, and its incidence has been rising in recent years. Emerging evidence suggests that prenatal lead exposure, even at low concentrations, may be a potential risk factor for PIH. This systematic review and meta-analysis aims to evaluate the association between maternal blood lead levels and the risk of preeclampsia and gestational hypertension by synthesizing findings from multiple epidemiological studies.

Methods

A comprehensive literature search was conducted in Scopus, PubMed, and Web of Science for studies published between 1993 and 2023, using a combination of Medical Subject Headings (MeSH) terms and expert-defined keywords. Following Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) guidelines, 5,918 titles were screened. Studies were included based on predefined eligibility criteria. A random-effects meta-analysis and linear regression were used to evaluate the association between prenatal lead exposure and pregnancy-induced hypertension outcomes.

Results

The analysis included cohort, case-control, and cross-sectional studies, with sample sizes ranging from 39 to 971 participants. Women with preeclampsia had significantly higher mean blood lead levels (18.4 µg/dL; 95% CI: 16.1–20.7) compared to normotensive controls (7.4 µg/dL; 95% CI: 6.2–8.6), resulting in a standardized mean difference (SMD) of 2.2 (95% CI: 1.8–2.6; p < 0.01). Considerable heterogeneity was observed across continents (I² = 92.5%), study designs (I² = 87.3%), and sample sizes (I² = 89.1%). Publication bias was identified using funnel plots and Egger’s test (p < 0.05). Sensitivity analyses, excluding studies with extreme values, confirmed the robustness of the association.

Conclusion

This meta-analysis provides compelling evidence that prenatal blood lead exposure is associated with an elevated risk of preeclampsia and gestational hypertension. These findings highlight the importance of proactive environmental monitoring and preventive clinical measures to minimize maternal lead exposure and enhance pregnancy outcomes.

Supplementary Information

The online version contains supplementary material available at 10.1186/s12884-025-08131-9.

Introduction

Pregnancy-induced hypertension (PIH) is a leading cause of maternal morbidity and mortality, affecting approximately 10% of pregnancies worldwide, with incidence rates rising in recent decades [1, 2]. PIH encompasses a spectrum of hypertensive disorders, including gestational hypertension, preeclampsia, and eclampsia, all characterized by elevated blood pressure during pregnancy. These conditions compromise both maternal and fetal health by impairing perfusion to vital organs, thereby increasing the risk of adverse outcomes [3].

The clinical ramifications of PIH are profound. In mothers, PIH can lead to renal dysfunction, hepatic impairment (including HELLP syndrome), and an increased risk of cerebrovascular events and long-term cardiovascular disease [4, 5]. For the fetus, PIH is a major contributor to intrauterine growth restriction (IUGR), preterm birth, placental insufficiency, and neonatal complications such as low birth weight and respiratory distress [6–8].

Despite extensive research, the pathophysiology of PIH remains incompletely understood. A multifactorial etiology has been proposed, involving genetic predisposition, immune dysregulation, environmental exposures, and lifestyle factors. Environmental factors may play a particularly important role in the development and progression of PIH. Among these, lead—a ubiquitous environmental pollutant—has garnered increasing attention for its potential contribution to hypertensive disorders during pregnancy [9, 10].

Lead exposure is known to disrupt vascular function through mechanisms such as oxidative stress, endothelial dysfunction, and impaired nitric oxide signaling, all of which are implicated in the pathogenesis of hypertension. Although global blood lead concentrations have declined over recent decades—by approximately 0.029 µg/dL annually in the U.S. population [9, 10] —low-level lead exposure remains widespread and underrecognized. This is especially concerning during pregnancy, when even minimal exposure may have significant repercussions for maternal cardiovascular health.

Recent studies have proposed a potential association between prenatal lead exposure and an increased risk of PIH [4, 11, 12]. However, findings have been inconsistent, with variability in study design, sample size, and exposure assessment limiting the strength of conclusions. For instance, while Poropat et al. (2018) [13] explored this relationship, methodological heterogeneity has hindered consensus on the magnitude and clinical relevance of the association.

To address this gap, the present systematic review and meta-analysis aim to critically evaluate the association between prenatal blood lead levels and PIH, with specific emphasis on preeclampsia and gestational hypertension. By applying rigorous selection criteria, advanced statistical modeling, and comprehensive sensitivity analyses, this study seeks to provide a more robust and nuanced understanding of lead’s potential role in pregnancy-related hypertensive disorders.

Methods

Search strategy

Two researchers (MV and LS) independently conducted a comprehensive search of English-language articles in Scopus, PubMed, and Web of Science using a predefined set of keywords. These terms were selected using Medical Subject Headings (MeSH), the Cumulative Index to Nursing and Allied Health Literature (CINAHL), and expert consultation. The final search string was: (“blood pressure” OR “hyperten*” OR “eclampsia” OR “preeclampsia” OR “toxemia”) AND (“lead” OR “Pb”) AND (“pregnan*” OR “gestation” OR “prenatal” OR “pre-natal” OR “maternal”) AND (“level” OR “concentration”). This search was conducted across titles, abstracts, and keywords.

Study selection

A total of 5,918 records were identified (Scopus: 4,262; PubMed: 522; Web of Science: 1,134) as of May 2024. Of these, 502 were excluded for falling outside the designated time frame (1993–2023). Duplicate entries (n = 844) were removed using EndNote and manually verified by comparing authors, titles, publication years, and journal names.

After duplicate removal, 4,572 studies remained. An additional 1,148 were excluded based on predefined criteria or redundancy. Titles and abstracts of the remaining 3,424 articles were screened by the lead researcher (MV) to determine relevance. Subsequently, 155 full-text articles were independently assessed by both researchers (MV and LS) for eligibility. Disagreements were resolved through discussion. In total, 21 studies met al.l criteria and were evaluated using the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) 27-item checklist [14] for final data extraction (see Fig. 1).

Fig. 1.

Flowchart of study selection for the meta-analysis on prenatal lead exposure and pregnancy-induced hypertension

Inclusion and exclusion criteria

Inclusion criteria comprised cross-sectional, case-control, or population-based cohort studies that employed reliable methods for measuring blood lead levels (such as atomic absorption spectroscopy or inductively coupled plasma mass spectrometry) and provided sufficient statistical data on blood pressure, blood lead concentrations, and gestational age.

Exclusion criteria encompassed experimental studies that were not observational in design (i.e., cohort, case-control, or cross-sectional), studies with sample sizes smaller than 20 participants due to insufficient statistical power, lead measurements conducted using matrices other than whole blood, and non-primary research sources such as conference abstracts, editorials, and commentaries, which lack the full peer-reviewed data necessary for meta-analysis.

Data extraction

Two investigators independently extracted key information from each study, including study design, publication year, sample size, and sampling methods. Statistical parameters such as mean, standard deviation, and confidence intervals (CIs) were also recorded. Data on pregnancy-specific blood pressure measurements and PIH subtypes were collected, along with gestational age, blood lead levels (converted to µg/dL), and timing of blood sampling. Additionally, details regarding study location, measurement techniques, and diagnostic definitions were documented.

Nine studies [2, 15–21]—six focusing on preeclampsia and three on gestational hypertension—were included in the meta-analysis. Each study was independently assessed for risk of bias.

Methodological quality assessment

The Newcastle-Ottawa Scale (NOS) [22] was used to evaluate study quality. This tool assesses three domains:

1. Selection (maximum 4 points): Representativeness of the exposed group, appropriate selection of controls, accuracy of exposure ascertainment, and confirmation that outcomes were not present at baseline (cohort studies only).

2. Comparability (maximum 2 points): Adjustment for confounders such as maternal age and socioeconomic status (SES), as well as other relevant factors.

3. Outcome (maximum 3 points): Validated outcome assessments, adequate follow-up period (for cohort studies), and minimal loss to follow-up.

A score of 7 or higher was considered indicative of high Quality, while scores of 6 or lower suggested a potential risk of bias.

Statistical analysis

Heterogeneity among studies was assessed using the I² statistic, with values above 60% indicating moderate to high heterogeneity. Due to variability in study designs, a random-effects model was applied. Standardized mean differences (SMD) were calculated using Cohen’s d method. Linear regression was conducted to compare the effects of lead levels across normotensive, preeclamptic, and gestational hypertensive groups. Sensitivity analysis was performed by excluding one study [9] identified as an outlier for mean blood lead level.

Results

Study characteristics

The included studies consisted of cohort, case-control, and cross-sectional designs, with sample sizes ranging from 39 to 971 participants. Maternal blood lead exposure was assessed through blood sampling conducted at various points, from early pregnancy up to delivery. These studies covered diverse geographic regions, including North America, Europe, Asia, and Africa.

Among the eligible studies, six (n = 330) focused on preeclampsia [2, 15, 16]19– [21], three (n = 191) addressed gestational hypertension disorders (GHD) [17, 18, 23], and nine (n = 1,679) involved normotensive pregnant women [2]15– [21, 23]. Blood sampling during the second and third trimesters was reported in seven studies [2, 15, 16, 20, 21], while two studies did not specify the timing of prenatal blood collection [2, 19]. Background characteristics—including country, study design, measurement instruments, gestational age, blood lead levels, and quality scores assessed using the Newcastle-Ottawa Scale—are summarized in Table 1.

Table 1.

The selected studies’ characteristics

Author Year	Study origin	Study design	Sample size	Measurement method	Blood sampling	Blood lead µg/dL Mean ± SD	Quality point*
Dawson et al. 2000 [12]	Texas	Cross-sectional	Preeclampsia: 19 Normotensive: 20	AAS	29–43 weeks	Case: 1.7 ± 0.3 Control: 1.4 ± 0.3	6
Gajewska et al. 2021[11]	Poland	Cross-sectional	Preeclampsia: 66 Normotensive: 40	CPMS	During pregnancy	Case: 3.4 ± 1.2 Control: 2.0 ± 0.9	7
Ikechukwu et al. 2014 [10]	Nigeria	Cohort	Preeclampsia: 59 Normotensive: 150	AAS	During pregnancy	Case: 60.2 ± 12.8 Control: 26.3 ± 0.2	6
Magri et al. 2003 [14]	Malt	Cross-sectional	GHD: 30 Normotensive: 93	AAS	Third trimester	Case: 9.6 ± 6.0 Control: 5.8 ± 3.0	6
Motawei et al. 2013 [9]	Egypt	Cross-sectional	Preeclampsia: 115 Normotensive: 25	AAS	During pregnancy	Case: 37.7 ± 9.2 Control: 14.5 ± 3.2	6
Obadia et al. 2018 [8]	Congo	Case-control	Preeclampsia: 40 Normotensive: 40	CPMS	During pregnancy	case: 6.7 ± 0.7 control: 5.1 ± 0.5	5
Yazbeck et al. 2009 [7]	France	Cross-sectional	GHD: 106 Normotensive: 865	AAS	Second and third trimesters	Case: 2.2 ± 1.4 Control: 1.9 ± (1.2)	8
Vigeh et al. 2006 [15]	Iran	Case-Control	GHD: 55 Normotensive: 55	CPMS	Third trimesters	Case: 5.7 ± 2.0 Control: 4.8 ± 1.9	6
Vigeh et al. 2004 [13]	Iran	Cross-Sectional	Preeclampsia: 31 Normotensive: 365	CPMS	During pregnancy	Case: 5.9 ± 2.01 Control: 4.8 ± 2.2	7

GHD: Gestational hypertension disorder

AAS: Atomic Absorption Spectrophotometer

CPMS: Coupled Plasma Mass Spectrometry

GHD: Gestational hypertension disorder

*Quality point scaled by New castle Ottawa

The pooled mean maternal age (95% CI) was 28.2 years (26.6–29.7) among normotensive women [2, 15, 16, 19, 20] and 26.5 years (24.6–28.4) among those with preeclampsia [2, 15, 19, 20], with no significant heterogeneity between groups (I² = 0.49, p = 0.48). The pooled mean BMI (95% CI) was 30.5 kg/m² (25.1–34.0) in normotensive women [16, 20] and 30.8 kg/m² (29.6–31.9) in the preeclamptic group [16, 20], with moderate heterogeneity (I² = 0.89, p = 0.34). The pooled mean gestational age (95% CI) was 38.7 weeks (38.5–38.8) for normotensive women and 35.6 weeks (38.0–38.4) for those with preeclampsia, demonstrating significant heterogeneity (I² = 170.64, p < 0.01). Table 2 presents detailed participant characteristics across the preeclamptic, normotensive, and gestational hypertension disorder (GHD) groups.

Table 2.

Comparison variables among three groups; normotensive, gestational hypertension disorder (GHD), and preeclampsia

Variables	Group (sample size)	Mean (95% CI)
Age (year)	Normotensive (786) [8, 10–15]	26.5 (24.6, 28.4)
	Preeclampsia (360) [8, 10–14]	28.1 (26.6, 29.7)
	GPD (31) [15]	27.0 (25.5, 28.5)
Weight (kg)	Normotensive (135) [8, 12, 13]	106.2 (76.3, 136.1)
	Preeclampsia (90) [8, 12, 13]	107.5 (85.6, 130.3)
	GPD (0)	-
Systolic blood pressure (mm/Hg)	Normotensive (250) [8, 10–12]	113.5 (123.4, 179.6)
	Preeclampsia (250) [8, 10–12]	151.5 (123.4, 179.6)
	GPD (30) [14]	150.0
Diastolic blood pressure (mm/Hg)	Normotensive (230) [8, 10, 11]	71.5 (5.8)
	Preeclampsia (230) [8, 10, 11]	99.5 (14.5)
	GPD (30) [14]	96.0
BMI (kg/m2)	Normotensive (571) [8, 12–15]	30.5 (25.1, 34.0)
	Preeclampsia (175) [8, 12, 13]	30.8 (29.6, 31.9)
	GPD (61) [14, 15]	32.5 (23.7, 41.3)
Gestational age (week)	Normotensive (285) [8, 10, 11, 13]	38.3 (37.7, 38.9)
	Preeclampsia (220) [8, 10, 11, 13]	35.7 (35.2, 36.2)
	GPD (0)

The pooled mean blood lead level (95% CI) was 18.4 µg/dL (14.3–22.4) in preeclamptic women and 7.4 µg/dL (–4.8 to 4.5) in normotensive women, yielding a standardized mean difference (SMD) of 2.2 µg/dL (95% CI: 0.9–3.5, p < 0.01) (Fig. 2). In GHD cases, the mean blood lead level was 5.7 µg/dL (95% CI: 2.5–8.8), compared to 7.4 µg/dL (95% CI: − 3.0 to 17.8) in normotensive women, with an SMD of 0.52 (95% CI: − 0.12 to 0.93) (Fig. 3). Comparative lead levels between GHD and preeclampsia groups, stratified by background characteristics, are summarized in Table 2.

Fig. 2.

The pooled mean lead in preeclampsia and normal pregnant women

Fig. 3.

The pooled mean lead in GPD and normal pregnant women

Significant heterogeneity was observed in mean blood lead levels among preeclamptic women by continent (I² = 99.91%, p < 0.01), study design (cross-sectional vs. case-control; I² = 96.14%, p < 0.01), and sample size (< 100 vs. >101; I² = 99.91%, p < 0.01). For GHD studies, heterogeneity by continent, study design, and sample size was I² = 99.8% (p < 0.01), I² = 0.0% (p > 0.05), and I² = 99.72% (p < 0.01), respectively.

Subgroup analyses revealed regional differences in blood lead levels among preeclamptic women: Africa, 34.8 µg/dL (95% CI: 5.3–64.3); Asia, 5.1 µg/dL (95% CI: 4.4–5.8); and America, 1.7 µg/dL (95% CI: 1.6–1.9) (Table 3). Significant heterogeneity was found across regions (I² = 88.6%, p < 0.01). Pairwise comparisons showed statistically significant differences between Africa and America (p < 0.001), Africa and Asia (p = 0.004), and Africa and Europe (p < 0.001).

Table 3.

Blood lead levels (µg/dL) among preeclamptic and gestational hypertensive disorder (GHD) women by background variables

Variables*	Cofactors	Preeclampsia mean (95% CI)	Cofactors	GHD mean (95% CI)
Continent	America [12]	1.7 (1.6,1.9)	America	-
	Europe [11]	3.4 (3.0, 3.7)	Europe [7, 14]	5.9 (−1.4, 13.2)
	Africa [8–10]	34.8 (5.3, 64.3)	Africa	-
	Asia [13]	5.1 (4.4, 5.8)	Asia [15]	5.7 (5.2, 6.2)
Design	Cross sectional [9–13]	21.2 (15.0, 27.3)	Cross sectional [14]	9.6 (7.5, 11.7)
	Case-control [8]	6.7 (6.4, 6.9)	Case-control [15]	5.7 (5.2, 6.2)
	Cohort	-	Cohort [7]	2.2 (1.9, 2.5)
Sample size	< 100 [8,12]	4.2 (−0.1, 9.0)	< 100	-
	> 101 [10,11,13,14]	26.4 (13.3, 39.6)	> 101 [7, 14, 15]	5.8 (1.5, 10.2)

*study’s reference in bracket

Regression analysis

Univariate and multivariate linear regression analyses were conducted to examine associations between prenatal blood lead levels and maternal age, BMI, weight, and gestational age (Table 4). Variables with a univariate p-value < 0.2 were included in the multivariate model. Among these, only maternal weight remained significantly associated with blood lead levels in both univariate and adjusted models (p = 0.01). Due to limited sample sizes, regression analyses were not performed for the GHD and normotensive.

Table 4.

Univariate and multiple linear regression analyses examined relationships between prenatal blood lead levels with maternal age, BMI, weight, and gestational age

Variables	Univariate β Coefficient (SE)	p value	Multivariate β Coefficient (SE)	p value
Age (year)	− 0.072 (1.84)	0.970	-	-
BMI (kg/m2)	0.301 (0.222)	0.223	-	-
Weight (kg)	− 0.424 (0.009)	0.01	0.439 (0.008)	0.01
Gestational age (week)	− 4.66 (6.31)	0.493	-	-
Group (preeclampsia)	11.64 (8.58)	0.198	1.088 (0.632)	0.184

Publication bias

Publication bias was assessed using funnel plots and Egger’s test. Significant asymmetry was observed in the funnel plots, and Egger’s test confirmed the presence of publication bias for studies reporting on preeclampsia and GHD (p < 0.05) (Fig. 4a and b).

Fig. 4.

Funnel plot of lead mean among preeclamptic (a) and GHD (b) groups

Sensitivity analysis

A sensitivity analysis was conducted by excluding the study by Ikechukwu et al. [15], which reported unusually high mean (SD) blood lead levels of 60.2 (12.8) µg/dL in the preeclampsia group and 26.3 (0.2) µg/dL in the control group, with an SMD of 1.38 µg/dL (p = 0.01). After exclusion, the overall effect size remained stable. Subgroup analyses based on study design, geographic location, and lead measurement method also yielded consistent results, reinforcing the robustness of the association between prenatal lead exposure and PIH.

Discussion

This meta-analysis provides strong evidence of a significant association between prenatal lead exposure and PIH, including preeclampsia and gestational hypertension. The findings demonstrate elevated blood lead levels in preeclamptic women compared to normotensive pregnant women, underscoring the role of environmental toxicants in hypertensive disorders during pregnancy.

Preeclamptic women had more than twice the blood lead levels of their normotensive counterparts (18.4 vs. 7.4 µg/dL). The pooled analysis revealed a significant overall effect size of 2.19 (95% CI: 0.91–3.48), indicating a strong association between prenatal lead exposure and preeclampsia. These findings are consistent with previous studies linking elevated maternal blood lead levels to increased risks of both preeclampsia and gestational hypertension [4, 19, 20, 24]. Additionally, other systematic reviews have reported a significant association between lead exposure and hypertension, even at relatively low blood lead levels [6].

Several previous studies provide compelling evidence supporting the association between lead exposure and pregnancy-induced hypertension. For example [19], reported significantly higher blood lead levels in preeclamptic women compared to normotensive controls. Similarly, Vigeh et al. (2004) [23] found that women with gestational hypertension had nearly twice the blood lead concentrations of healthy pregnant women. These findings align with our pooled effect size estimates and further reinforce the role of lead exposure in the development of hypertensive disorders during pregnancy.

Evidence from the general population further supports the hypertensive effects of lead exposure. For example, a meta-analysis involving nearly 60,000 individuals found that a two-fold increase in blood lead concentration was associated with a 1.0 mmHg rise in systolic blood pressure and a 0.6 mmHg increase in diastolic blood pressure [8]. Similarly, another meta-analysis found a modest elevation in blood pressure and hypertension risk associated with increased bone lead levels [7]. While these findings reinforce the biological plausibility of lead-induced hypertension, pregnancy introduces unique physiological conditions that may amplify these effects.

Prenatal lead exposure contributes to PIH through several interrelated biological pathways. Lead damages vascular endothelial cells by disrupting intracellular calcium homeostasis and impairing nitric oxide (NO) synthesis, which reduces vasodilation and increases arterial resistance [6]. It also induces oxidative stress by generating reactive oxygen species (ROS), particularly superoxide anions, which react with nitric oxide (NO) to form peroxynitrite—a potent oxidant that promotes inflammation, endothelial apoptosis, and vascular stiffness [25]. This oxidative burden is exacerbated by lead’s inhibition of key antioxidant enzymes, including superoxide dismutase, catalase, and glutathione peroxidase, along with depletion of glutathione [26]. These disruptions collectively impair NO bioavailability. Lead inhibits endothelial nitric oxide synthase (eNOS) and scavenges existing NO, leading to sustained vasoconstriction and elevated blood pressure [5].

Taken together, findings from both pregnant and general populations strengthen the evidence supporting lead’s role in elevating blood pressure and reinforce the robustness of our conclusions regarding its contribution to pregnancy-induced hypertension.

Beyond individual physiological responses, geographical variations significantly impact maternal lead exposure levels. Subgroup analyses revealed higher blood lead concentrations in African studies, with a pooled mean of 34.8 µg/dL (95% CI: 5.3–64.3), compared to 5.1 µg/dL (95% CI: 4.4–5.8) in Asia, 3.4 µg/dL (95% CI: 3.0–3.7) in Europe, and 1.7 µg/dL (95% CI: 1.6–1.9) in America.

Africa’s higher blood lead levels may stem from ongoing industrial emissions, residual use of leaded gasoline, contaminated water supplies, and inadequate regulatory enforcement [6, 10]. Additionally, nutritional deficiencies—particularly low dietary calcium intake—exacerbate lead absorption, amplifying its adverse vascular effects [23]. These findings underscore the necessity for targeted public health interventions in regions with high lead exposure. Such measures could include stricter environmental regulations, enhanced water quality monitoring, and nutritional supplementation programs aimed at reducing lead absorption.

While our findings are consistent with numerous studies supporting a significant association between prenatal lead exposure and PIH, conflicting evidence also exists in the literature. For example, Yazbeck et al. (2009) [18] reported no significant association between maternal blood lead levels and gestational hypertension in their cohort study. Similarly, Paredes Alpaca et al. (2013) [11] observed inconsistent reproductive outcomes linked to low-dose lead exposure among female workers. These discrepancies may result from methodological differences, such as variations in sample size, study design, timing and precision of exposure assessment, and the degree of confounder adjustment. Despite these inconsistencies, our sensitivity analyses confirmed the robustness of the observed association. For instance, excluding an outlier study with exceptionally high lead levels (Ikechukwu et al., 2012) [15] did not materially alter the overall effect size, indicatinf the stability of our findings. These results suggest that despite heterogeneity, the fundamental relationship between lead exposure and PIH remains consistent across diverse study contexts.

While our study shares structural similarities with the meta-analysis by Poropat et al. (2018) [13], several methodological distinctions highlight its novelty. We analyzed a broader timeframe (1993–2023) and utilized a random-effects model to address heterogeneity, in contrast to their fixed-effects approach. Our analysis encompassed both preeclampsia and gestational hypertension, providing a more comprehensive overview of PIH. Importantly, we focused exclusively on blood lead levels—regarded as the most reliable biomarker—while Poropat et al. included both blood and serum measurements, which may introduce variability due to red blood cell lysis. Although both studies searched major databases (PubMed, Scopus, Web of Science), we reviewed a greater number of full-text articles, thereby enhancing the depth of our synthesis. Both analyses consistently demonstrate a strong association between elevated maternal lead levels and increased risk of preeclampsia. Our findings reinforce the call for routine lead screening during pregnancy and support calcium supplementation as a protective intervention, echoing the recommendations of Poropat et al.

To further refine our understanding of this association, future research should incorporate a broader range of potential confounding variables, including socioeconomic status, nutritional factors, environmental co-exposures, and genetic susceptibility. Such efforts will be critical in elucidating the complex interplay between lead toxicity and hypertensive disorders during pregnancy, ultimately guiding more targeted and effective public health interventions.

Study limitations

This meta-analysis adhered to standard procedures for literature search, study selection, and statistical analysis. However, several limitations should be noted. The inclusion of studies with varying designs and methodological quality introduced significant heterogeneity, which may have influenced the results. To address this, sensitivity analyses were conducted, and the pooled effect size was reanalyzed after excluding an outlier study to confirm the robustness of our findings.

Additionally, existing studies examining the association between prenatal lead exposure and PIH exhibit notable methodological limitations. Many relied on cross-sectional or case-control designs, which restrict causal inference and limit assessment of temporal relationships between lead exposure and hypertensive disorders during pregnancy. Furthermore, several studies had relatively small sample sizes, increasing statistical variability and reducing precision in effect size estimates. Variations in study populations—including geographic differences and disparities in environmental lead regulations—also contribute to heterogeneity, complicating the generalizability of results. Addressing these gaps, our meta-analysis systematically integrates data from a broader range of studies, applies rigorous inclusion criteria, and employs advanced statistical models to improve the reliability of the findings.

Another limitation is the asymmetry observed in the funnel plot, indicating potential publication bias that may affect the generalizability of the results. Additionally, the limited number of studies measuring blood lead levels restricts more detailed analyses, such as evaluating the timing of blood lead assessment and its direct association with PIH risk. Addressing these gaps through future research is essential to refine our understanding of prenatal lead exposure’s role in pregnancy complications.

Despite these limitations, our study offers a comprehensive evaluation of prenatal lead exposure and its potential contribution to hypertensive disorders during pregnancy. These findings underscore the importance of advancing public health policies, such as routine lead screening during pregnancy and targeted interventions for high-risk populations.

Conclusion

This meta-analysis provides strong evidence that prenatal lead exposure is significantly associated with an increased risk of PIH, including both preeclampsia and gestational hypertension. Geographic disparities—particularly the higher lead burdens observed in African cohorts—highlight the influence of environmental conditions, regulatory enforcement, and nutritional status in shaping maternal exposure risk.

These findings support adopting routine lead screening during pregnancy, especially in high-risk regions, and reinforce the need for preventive strategies—such as calcium supplementation—to reduce lead absorption and mitigate adverse maternal outcomes.

Supplementary Information

Below is the link to the electronic supplementary material.

Author contributions

M.V. contributed to study conception, data collection, and statistical analysis. K.Y. provided expertise in epidemiological methodology and manuscript review. L. S. led the systematic review process, manuscript drafting, and final revisions. All authors read and approved the final manuscript.

Funding

The authors (MV, KY, LS) declare that this research received no specific grant or funding support.

Data availability

No datasets were generated or analysed during the current study.

Declarations

Ethics approval and consent to participate

This study was conducted according to the ethical guidelines outlined by Tehran University of Medical Sciences. Ethical approval was obtained from the Ethics Committee of Tehran University of Medical Sciences (Approval Number: IR.TUMS.IKHC.REC.1402.364). All participants provided informed consent before inclusion in the study.

Consent for publication

All authors (MV, KY, LS) consent to the publication of this manuscript.

Competing interests

The authors declare no competing interests.