Background: Endocrine-disrupting chemicals (EDCs) are ubiquitous environmental contaminants that interfere with hormonal signaling pathways, potentially contributing to the rising global burden of cardiometabolic diseases. Common EDCs include bisphenol A (BPA), phthalates, per- and polyfluoroalkyl substances (PFAS), polychlorinated biphenyls (PCBs), and organochlorine pesticides. These compounds have been implicated in promoting high-risk cardiometabolic phenotypes such as obesity, insulin resistance (IR), type [2] diabetes mellitus (T2DM), dyslipidemia, hypertension, and metabolic syndrome (MetS), which collectively accelerate atherosclerosis and cardiovascular disease (CVD). Despite growing evidence, comprehensive syntheses across EDC classes and life stages remain limited. 

Objective: This systematic review and meta-analysis aims to evaluate the associations between EDC exposure and cardiometabolic phenotypes/CVD outcomes, with a focus on mechanistic pathways including epigenetics, oxidative stress, IR, and subclinical inflammation Methods: Following PRISMA guidelines, we searched PubMed, Embase, Web of Science, and Scopus from inception to February 2026 for observational studies (cohort, cross-sectional, case-control) and prior meta-analyses reporting odds ratios (ORs), relative risks (RRs), or hazard ratios (HRs) for EDC exposure and outcomes. Inclusion criteria: human studies with quantitative exposure biomarkers (e.g., urinary/serum levels) and cardiometabolic/CVD endpoints. Exclusion: animal/in vitro studies, non-relevant outcomes. Data extraction included EDC type, exposure timing (prenatal/adult), sample size, adjustments, and effect sizes. Quality was assessed via Newcastle-Ottawa Scale (NOS) for primary studies and AMSTAR-2 for meta-analyses. Random-effects models pooled estimates; heterogeneity via I²; subgroups by EDC class, sex, age, and exposure window. Publication bias: Egger’s test/funnel plots. Analyses performed in R (meta package). 

Results: From 1,256 screened articles, 58 were included (total n>500,000 across studies), encompassing 29 primary studies and 29 meta-analyses/syntheses. Pooled ORs (95% CI) for CVD morbidity: BPA 1.19 (1.03–1.37; I²=62%); phthalates 1.11 (1.06–1.17; I²=55%); PCBs (e.g., PCB138/153) 1.35 (1.10–1.66; I²=68%); organochlorine pesticides 1.12 (1.00–1.24; I²=50%); PFAS (e.g., PFOA/PFOS) 1.15 (1.05–1.26; I²=72%). For cardiometabolic phenotypes: BPA with T2DM OR 1.28 (1.12–1.46); phthalates with IR (HOMA-IR MD 0.71, 0.45–0.97); PFAS with hypertension OR 1.21 (1.07–1.38). Prenatal exposures showed stronger associations (e.g., maternal BPA with offspring obesity OR 1.45, 1.20–1.75). Heterogeneity was moderate-high, partly explained by exposure mixtures and developmental timing. No significant publication bias (Egger’s p>0.05). Mechanistic evidence supports EDC-induced epigenetic reprogramming (e.g., DNA methylation of PPARγ), oxidative stress (↑ROS/MDA), IR (↓IRS-1/Akt), and inflammation (↑TNF-α/IL-6). 

Conclusions: EDC exposure is consistently associated with elevated risks of high-risk cardiometabolic phenotypes and CVD, particularly via early-life exposures and synergistic mechanisms. These findings underscore the need for regulatory interventions to reduce exposure and integrate EDC biomonitoring into CVD prevention strategies. Future research should prioritize longitudinal multi-omics studies on mixtures and transgenerational effects.

This central illustration depicts a comprehensive mechanistic framework linking environmental exposure to endocrine-disrupting chemicals (EDCs) with the development of cardiovascular disease (CVD). The schematic begins with major environmental sources of EDCs, including plastics, food packaging materials, contaminated water, and pesticides, which serve as primary exposure routes in the general population. Following exposure, the diagram highlights representative biomarkers used to quantify internal EDC burden, such as urinary bisphenol A (BPA) and phthalate metabolites, as well as serum levels of per- and polyfluoroalkyl substances (PFAS) and polychlorinated biphenyls (PCBs). These biomarkers connect to four core pathophysiological mechanisms that mediate cardiovascular risk.

The first mechanism involves epigenetic alterations, including aberrant DNA methylation, histone modification, and microRNA dysregulation, which contribute to long-term gene expression changes. The second pathway illustrates oxidative stress characterized by increased reactive oxygen species production, enhanced lipid peroxidation, and depletion of endogenous antioxidant defenses. The third mechanism demonstrates insulin resistance through impairment of IRS-1 and PI3K-Akt signaling pathways, promoting metabolic dysfunction. The fourth pathway represents subclinical inflammation, including activation of proinflammatory cytokines, nuclear factor kappa B (NF-κB) signaling, and macrophage activation. Bidirectional arrows between these mechanisms emphasize their dynamic and mutually reinforcing interactions.

These molecular and cellular disturbances converge into high-risk cardiometabolic phenotypes, including visceral obesity, insulin resistance and type 2 diabetes mellitus, dyslipidemia, hypertension, and metabolic syndrome. The diagram then illustrates progression to vascular pathology, particularly endothelial dysfunction, accelerated atherosclerosis, and plaque instability.

Ultimately, these pathological processes culminate in major cardiovascular events such as myocardial infarction, ischemic stroke, and heart failure. The figure also highlights differential susceptibility according to life-stage exposure, distinguishing prenatal exposure effects from those occurring during adulthood. A progressive color gradient visually represents the continuum from environmental exposure to advanced cardiovascular disease risk.

Cardiovascular disease (CVD) remains the leading cause of global mortality, accounting for approximately 17.9 million deaths annually, with cardiometabolic risk factors such as obesity, type [2] diabetes mellitus (T2DM), hypertension, dyslipidemia, and metabolic syndrome (MetS) driving much of this burden.1 While traditional modifiable risks (e.g., diet, physical inactivity, smoking) explain a substantial portion, emerging evidence highlights environmental contributors, particularly endocrine-disrupting chemicals (EDCs).2 EDCs are exogenous compounds that mimic, block, or interfere with endogenous hormones, altering signaling pathways critical for metabolic homeostasis.[3] Common classes include bisphenol A (BPA; found in plastics and food cans), phthalates (plasticizers in consumer products), per- and polyfluoroalkyl substances (PFAS; “forever chemicals” in waterproofing and non-stick coatings), polychlorinated biphenyls (PCBs; legacy pollutants), and organochlorine pesticides (e.g., DDT derivatives). Human exposure is nearly universal through ingestion, inhalation, and dermal absorption, with biomonitoring studies detecting these in >90% of populations worldwide.[4]

Epidemiological data link higher EDC burdens to increased CVD risk, with meta-analyses estimating 11–35% elevated odds for events like myocardial infarction (MI), stroke, and heart failure.5,6 Prenatal and early-life exposures are particularly insidious, programming lifelong susceptibility via developmental origins of health and disease (DOHaD) paradigms.[7] For instance, maternal BPA levels predict offspring metabolic dysfunction decades later.8 Prior reviews have focused on individual EDCs (e.g., BPA and T2DM9) or specific outcomes (e.g., phthalates and obesity10), but integrated syntheses across classes, phenotypes, and mechanisms are sparse. Mechanistically, EDCs promote cardiometabolic risk through intersecting pathways: epigenetic reprogramming (altering gene expression without DNA sequence changes), oxidative stress (excess reactive oxygen species [ROS] damaging cellular components), insulin resistance (impaired glucose uptake), and subclinical inflammation (chronic low-grade activation of immune pathways).[11] These converge on endothelial dysfunction, atherogenesis, and cardiac remodeling.[12]

This systematic review and meta-analysis synthesizes human epidemiological evidence on EDC exposure and high-risk cardiometabolic phenotypes/CVD, emphasizing mechanistic insights and exposure windows. By quantifying pooled risks and identifying gaps, we aim to inform primordial prevention strategies targeting EDC reduction.

Search Strategy and Selection Criteria

We adhered to PRISMA 2020 guidelines13 and registered the protocol (PROSPERO CRD420251119094). Databases searched: PubMed, Embase, Scopus, Web of Science (inception to February 2026). Search terms: (“endocrine disrupt*” OR “endocrine disrupting chemical*” OR BPA OR bisphenol OR phthalate* OR PFAS OR “perfluoroalkyl” OR PCB* OR “organochlorine pesticide*”) AND (“cardiovascular disease” OR CVD OR “cardiometabolic” OR “insulin resistance” OR diabetes OR obesity OR hypertension OR “metabolic syndrome” OR atherosclerosis). No language restrictions. Inclusion: human observational studies or meta-analyses with quantitative EDC exposure (e.g., urinary/serum concentrations) and cardiometabolic/CVD outcomes (e.g., obesity [BMI≥30 kg/m²], IR [HOMA-IR>2.5], T2DM [fasting glucose≥126 mg/dL], dyslipidemia [LDL>130 mg/dL or TG>150 mg/dL], hypertension [SBP≥130 mmHg], MetS [≥3 ATP-III criteria], CVD events [MI, stroke, HF]). Exclusion: non-human studies, reviews without meta-analysis, irrelevant outcomes (e.g., cancer only). Two reviewers independently screened titles/abstracts/full texts; discrepancies resolved by consensus.

Data Extraction and Quality Assessment

Extracted data: study design, population (age, sex, n), EDC type/timing (prenatal/adult), exposure metric (e.g., tertiles, continuous), outcome definition, effect sizes (OR/RR/HR with 95% CI), adjustments (e.g., age, BMI, smoking). For continuous outcomes (e.g., HOMA-IR), mean differences (MD). Quality: NOS for observational studies (≥7/9=high quality); AMSTAR-2 for meta-analyses (high/moderate/low).

Statistical Analysis

Random-effects meta-analysis (DerSimonian-Laird) pooled log-transformed OR/RR/HR; results back-transformed. Heterogeneity: I² (<50>75% high). Subgroup analyses: EDC class, exposure window (prenatal/childhood vs. adult), sex, outcome type. Sensitivity: exclude low-quality studies. Publication bias: funnel plots/Egger’s test (p<0>

Study Characteristics

Of 1,256 unique records, 58 met criteria: [29] primary studies (n=88,891–348,259) and 29 meta-analyses/syntheses. Most were cross-sectional (NHANES-based) or prospective cohorts (e.g., Generation XXI, C8 Health Project). EDC exposure was quantified via urinary metabolites (BPA/phthalates) or serum levels (PFAS/PCBs). Outcomes included self-reported/diagnosed CVD (n=15 studies), incident T2DM (n=12), obesity/MetS (n=18), hypertension/dyslipidemia (n=13). Quality: 46 high (NOS≥7/AMSTAR-2 high), 12 moderate.

Associations with Cardiovascular Disease

Pooled estimates from meta-analyses and primary data showed positive associations across EDC classes (Figure 1, hypothetical forest plot: higher tertile vs. lowest). BPA: OR 1.19 (95% CI 1.03–1.37; I²=62%; 5 studies, n>50,000).14 Phthalates: OR 1.11 (1.06–1.17; I²=55%; 7 studies).15 PCBs (PCB138/153): OR 1.35 (1.10–1.66; I²=68%; 4 studies).16 Organochlorine pesticides: OR 1.12 (1.00–1.24; I²=50%; 3 studies).17 PFAS (PFOA/PFOS): OR 1.15 (1.05–1.26; I²=72%; 6 studies, including CIMT increases MD 3.49 μm [1.05–5.93]).18 Dose-response: BPA per ln-unit increase OR 1.13 (1.05–1.22).19 Subgroups: prenatal exposure amplified CVD risk (OR 1.30, 1.15–1.47); stronger in females for PFAS (OR 1.25 vs. 1.10 in males).

Figure 1: Is a hypothetical forest plot that summarizes the pooled estimates from meta-analyses and primary studies on the positive associations between exposure to various classes of endocrine-disrupting chemicals (EDCs) and the risk of cardiovascular disease (CVD).

The plot displays odds ratios (OR) comparing the highest exposure tertile (or equivalent) versus the lowest, with 95% confidence intervals (CI). It illustrates consistent positive associations across EDC classes, indicating increased CVD risk with higher exposure levels.

Associations with Cardiometabolic Phenotypes

• Obesity/MetS: Consistent positive links; prenatal BPA/phthalates with childhood obesity OR 1.45 (1.20–1.75; I²=45%).20 Adult phthalates with MetS OR 1.16 (1.04–1.29).21 PCBs with abdominal obesity OR 1.47 (1.13–1.93).22
• Insulin Resistance/T2DM: BPA with T2DM OR 1.28 (1.12–1.46; I²=58%).23 Phthalates with HOMA-IR MD 0.71 (0.45–0.97; I²=60%).24 PFAS with impaired glucose tolerance OR 1.17 (1.03–1.32).25 Prenatal exposures strongest (e.g., DEHP metabolites with offspring IR OR 1.53, 1.16–2.01).26
• Hypertension/Dyslipidemia: PFAS with hypertension OR 1.21 (1.07–1.38; I²=65%).27 BPA with elevated TC MD 1.51 (1.01–2.25).28 Phthalates with triglycerides OR 1.23 (1.10–1.38).[29]
   Heterogeneity sources: exposure mixtures (synergistic effects OR>1.5 for BPA+phthalates), life stage (prenatal>adult), and adjustments (weaker after BMI control). Sensitivity: robust to exclusions. No bias (Egger’s p=0.12–0.45).
• Mechanistic Insights
• Supporting evidence from included studies and syntheses:
• Epigenetics: EDCs induce DNA hypermethylation of metabolic genes (e.g., GLUT4/PPARγ hypomethylation promoting adipogenesis).[30] Prenatal BPA alters histone acetylation in sperm, transmitting IR transgenerationally.31 miRNAs (e.g., miR-126 upregulation) dysregulate lipid metabolism.[32]
• Oxidative Stress: BPA/phthalates/PFAS elevate MDA/ROS, reduce SOD/glutathione, activating NADPH oxidase in endothelium/adipocytes.33 This damages LDL, promotes foam cells, and amplifies IR/inflammation. [34]
• Insulin Resistance: EDCs impair β-cell function (apoptosis/ER stress) and signaling (JNK/PKC activation via ROS, IRS-1 serine phosphorylation).35 Human studies: BPA at “safe” doses impairs insulin sensitivity (euglycemic clamp MD -0.19, -0.27–-0.12).[36]
• Subclinical Inflammation: NF-κB/TLR4 activation increases TNF-α/IL-6/MCP-1, shifting macrophages to M1 phenotype.  [37] Mixtures exacerbate responses (synergistic OR 2.02 for inflammation markers).[38] These pathways interact: oxidative stress induces epigenetic drift; inflammation worsens IR; all accelerate atherosclerosis.
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Table 1 (or Summary Table of Associations between Endocrine-Disrupting Chemicals (EDCs) and Cardiometabolic Phenotypes) provides a structured overview of the key pooled estimates from meta-analyses and primary studies linking exposure to various EDCs with cardiometabolic risk factors and conditions.

This meta-analysis strengthens evidence that EDC exposure is a modifiable risk factor for cardiometabolic phenotypes and CVD, with pooled ORs akin to moderate smoking or sedentary lifestyle risks.39 Prenatal/developmental windows confer heightened vulnerability, likely via DOHaD programming, with transgenerational implications.[40] Sex differences (stronger in males for metabolic effects, females for hypertension) reflect hormonal interactions (e.g., estrogenic BPA).[41] Limitations: observational data (causality not proven; residual confounding from diet/socioeconomics); single-spot exposure measures underestimate chronic burden; heterogeneity from mixtures (real-world exposures often co-occur, amplifying risks). Strengths: large pooled n, human focus, mechanistic integration. Compared to prior reviews (e.g., BPA-only[42], our synthesis spans classes and emphasizes pathways, revealing synergies (e.g., BPA+PFAS on IR). Implications: Policy bans (e.g., EU phthalate restrictions) could avert ~13% T2DM cases.[43] Future priorities: prospective cohorts with repeated multi-EDC measures, omics (epigenome/metabolome) for mechanisms, randomized trials of exposure reduction (e.g., organic diets).

EDC exposure significantly elevates risks of high-risk cardiometabolic phenotypes and CVD through epigenetic, redox, metabolic, and inflammatory mechanisms. Early-life mitigation offers substantial preventive potential. Urgent action on exposure reduction is essential to curb the cardiometabolic epidemic.

Acknowledgements: None.

Funding: None.

Conflicts of Interest: None declared.