Phthalate exposure from plastics and cardiovascular disease: global estimates of attributable mortality and years life lost

Summary

Key Aspects

• Background and Rationale: The study is motivated by emerging evidence linking plastic additives, particularly the phthalate di-2-ethylhexylphthalate (DEHP), to cardiovascular disease (CVD) through mechanisms like oxidative stress and metabolic dysfunction. While US-based estimates exist, this research addresses the critical need for global estimates of DEHP-attributable cardiovascular mortality. This global perspective is essential for informing international policy discussions, specifically the ongoing negotiations for a Global Plastics Treaty, highlighting the study's direct relevance to current environmental health policy challenges.
• Methodological Approach: The study employed a quantitative approach to estimate the global burden of DEHP exposure on cardiovascular health by integrating large-scale datasets. Cardiovascular mortality data were sourced from the Institute for Health Metrics and Evaluation (IHME), while regional DEHP exposure levels were derived from various sources, including published estimates. Hazard ratios linking DEHP exposure to CV mortality were calculated, and these were combined with country-level mortality rates to quantify excess deaths and years of life lost (YLL) attributable to DEHP.
• Key Findings on Global Burden: The study quantifies a substantial global health burden linked to DEHP exposure, estimating approximately 356,238 deaths in 2018 among individuals aged 55-64, which constitutes about 13.5% of all cardiovascular deaths in this age group. A significant portion of these deaths (around 349,113) were specifically attributed to DEHP originating from plastics use. Furthermore, the research estimated that DEHP exposure resulted in approximately 10.47 million years of life lost (YLL) globally, underscoring the significant impact on both mortality and premature death.
• Geographic Disparities and Interpretation: The findings reveal significant geographic disparities in the burden of DEHP-attributable cardiovascular mortality. Regions like South Asia and the Middle East exhibited the highest percentage of CVD deaths linked to DEHP, while these areas, along with East Asia and the Pacific, accounted for the largest absolute number of such deaths. This uneven distribution suggests that plastics pose a disproportionately higher risk to regions with developing plastic production sectors, reinforcing the study's interpretation that urgent regulatory interventions are needed at both global and local levels to address this environmental health issue.

Strengths

• Concise and Structured Overview

  The summary effectively encapsulates the core components of the study—background, methods, findings, and interpretation—in a clear and structured manner, providing readers with a quick understanding of the research.

  "Background New evidence has emerged... Methods Cardiovascular mortality data... Findings In 2018, an estimated... Interpretation Plastics pose a significant risk..." (Page 1)
• Highlights Key Quantitative Findings

  The 'Findings' section prominently features key quantitative results, such as the estimated number of deaths and years of life lost (YLL) attributable to DEHP exposure, immediately conveying the magnitude and significance of the study's results.

  "In 2018, an estimated 356,238 deaths globally were attributed to DEHP exposure, representing 13.497% of all cardiovascular deaths among individuals aged 55–64... Globally, DEHP resulted in 10.473 million YLL." (Page 1)
• Clear Rationale and Context

  The 'Background' clearly articulates the study's motivation by linking emerging evidence on DEHP's cardiovascular risks to the practical need for global data to inform international policy, specifically the Global Plastics Treaty negotiations.

  "Estimates of phthalate-attributable cardiovascular mortality have been made for the US, but global estimates are needed to inform ongoing negotiations of a Global Plastics Treaty." (Page 1)
• Actionable Interpretation

  The 'Interpretation' section directly translates the findings into actionable implications, emphasizing the disproportionate impact on certain regions and underscoring the necessity for regulatory interventions.

  "Plastics pose a significant risk to increased cardiovascular mortality, disproportionately impacting regions which have developing plastic production sectors. The findings underscore the need for urgent global and local regulatory interventions to kerb mortality from DEHP exposure." (Page 1)

Suggestions for Improvement

Introduction

Key Aspects

• CVD Burden and Historical Context: The paper establishes Cardiovascular Disease (CVD) as a primary global health concern, noting its long-standing status as the leading cause of death in the US and its formal recognition by the UN. Despite significant public health achievements leading to decreased mortality rates over decades, attributed to addressing risk factors like hypertension, cholesterol, and smoking, recent trends show an unsettling increase in age-standardized CVD mortality. This underscores the persistence of CVD as a major threat requiring investigation into both established and emerging risk factors.
• Plastics/DEHP as Emerging CVD Risk: A central argument is the identification of exposure to plastic polymers and their chemical additives, particularly phthalates like di-2-ethylhexylphthalate (DEHP), as a significant, emerging environmental risk factor for CVD. DEHP, commonly used to soften PVC plastics, is highlighted due to its widespread use, extensive human exposure data, and strong evidence linking it to adverse cardiovascular outcomes. This positions plastic-associated chemical exposure as a critical area for contemporary public health research and intervention.
• Mechanistic Pathways of DEHP: The introduction outlines the biological plausibility linking DEHP exposure to CVD by summarizing key mechanistic evidence. DEHP acts as an antiandrogen, influences peroxisome-proliferator activated receptors (PPARs) involved in lipid/carbohydrate metabolism, and induces oxidative stress. These molecular actions are connected to observed health outcomes in epidemiological studies, including weight gain, incident diabetes, accelerated atherosclerosis, and ultimately, increased CVD mortality, providing a scientific basis for investigating DEHP's population-level impact.
• Micro/Nanoplastics (MNPs) Context: The text also acknowledges the presence of micro- and nanoplastics (MNPs) in human tissues as another dimension of plastic-related health risks. MNPs are hypothesized to act as physical irritants, analogous to particulate air pollution, and potentially enhance the delivery of toxic chemicals like phthalates. While a recent study linked MNPs in carotid plaque to worse cardiovascular outcomes, the authors note remaining research challenges in distinguishing MNPs and isolating their specific effects, presenting it as a related but complex area requiring further study.
• Rationale for Global Burden Estimation: The study's primary motivation stems from the identified gap in global data regarding the CVD burden attributable to DEHP exposure. While previous research provided estimates for the US, the lack of comprehensive global data hinders international policy efforts. This study aims to address this gap by creating a global disease burden model, leveraging existing exposure and mortality data to estimate country-specific CVD mortality linked to DEHP, thereby providing crucial evidence for ongoing negotiations like the Global Plastics Treaty.

Strengths

• Strong Contextual Framing of CVD Burden

  The introduction effectively establishes the broad context of Cardiovascular Disease (CVD) as a persistent global health challenge, acknowledging past public health successes while highlighting recent concerning trends and the ongoing need for research into contributing factors.

  "Cardiovascular disease (CVD) has been the leading cause of death in the United States of America (US) since 1921, and in 2011, the UN formally recognised CVD as a major global health concern... Despite this effort, the epidemic of CVD remains a global health threat that leads to premature and preventable deaths." (Page 1)
• Clear Introduction of Plastics as Emerging Risk

  The text clearly introduces exposure to plastic chemicals, specifically di-2-ethylhexylphthalate (DEHP), as a novel and previously under-recognized environmental risk factor for CVD, setting the stage for the paper's focus.

  "The past decade has presented a new and previously unrecognised risk for CVD: exposure to plastic polymers and their chemical additives. Of particular concern are phthalates, particularly one class of phthalates di-2-ethylhexylphthalate (DEHP)..." (Page 2)
• Summarizes Mechanistic Links (DEHP & CVD)

  The introduction provides a concise overview of the mechanistic pathways linking DEHP to adverse cardiovascular outcomes, citing evidence related to antiandrogenic effects, PPAR modulation, oxidative stress, and associations with metabolic conditions and atherosclerosis.

  "DEHP and other phthalates are antiandrogens, increase expression of peroxisome-proliferator activated receptors crucial for lipid and carbohydrate metabolism, and are oxidative stressors. Cohort studies have identied phthalates to be associated with weight gain, incident diabetes, accelerated atherosclerosis, and CVD mortality." (Page 2)
• Strong Rationale and Policy Relevance

  The introduction effectively justifies the study's necessity by highlighting the lack of global estimates for DEHP-attributable CVD mortality and explicitly linking this knowledge gap to the need for data to inform policy, specifically the Global Plastics Treaty negotiations.

  "In the US, a previous investigation estimated that 50,200 CVD deaths were attributed to 2008 levels of DEHP... To inform ongoing negotiations, this study therefore leveraged existing data on phthalate exposure to create a global disease burden model which estimates the country-specific burden of CVD mortality linked to DEHP..." (Page 2)
• Acknowledges Related MNP Issue

  The text briefly introduces the related but distinct issue of micro- and nanoplastics (MNPs), acknowledging their potential role as physical irritants and chemical vectors, while also noting the current research challenges, thus providing a more complete picture of plastic-related health concerns.

  "Studies of human specimens have also detected micro- and nano plastics (MNP), which possibly act as physical irritants to the body... though challenges in MNP research remain..." (Page 2)

Suggestions for Improvement

• Clarify Mechanism-Outcome Links

  This low-impact improvement could slightly enhance reader comprehension within the Introduction. While the text mentions various mechanisms (PPAR activation, oxidative stress) linking DEHP to CVD outcomes (atherosclerosis, mortality), explicitly connecting these dots within the introductory flow could strengthen the narrative. Clarifying how, for instance, PPAR modulation or oxidative stress directly contributes to the pathophysiology of atherosclerosis or increases mortality risk would make the link more intuitive for readers less familiar with these specific pathways. This addition fits well within the Introduction's role of establishing the biological plausibility of the association being investigated.

  "DEHP and other phthalates are antiandrogens, increase expression of peroxisome-proliferator activated receptors crucial for lipid and carbohydrate metabolism, and are oxidative stressors. Cohort studies have identied phthalates to be associated with weight gain, incident diabetes, accelerated atherosclerosis, and CVD mortality." (Page 2)

  Implementation: Integrate a brief sentence or clause explicitly linking the cited mechanisms to the CVD outcomes. For example, after listing the mechanisms and associated outcomes, add a phrase like: "...contributing to CVD mortality through pathways involving accelerated atherosclerosis driven by metabolic dysregulation and oxidative damage." Alternatively, briefly elaborate after mentioning a mechanism, e.g., "...increase expression of peroxisome-proliferator activated receptors crucial for lipid and carbohydrate metabolism, processes central to atherogenesis..."

Methods

Key Aspects

• Study Population and Inclusion Criteria: The study defined its population based on World Bank recognized countries, requiring publicly available 2018 population estimates for the 55-64 age group and corresponding cardiovascular mortality rates from the Institute for Health Metrics and Evaluation (IHME). This resulted in the inclusion of 200 countries and territories. The specific age range (55-64 years) was selected to maintain methodological consistency with the prior research (Trasande et al., 2022) used to derive the hazard ratio, ensuring alignment between the exposure-risk relationship and the target population for burden estimation.
• Phthalate Exposure Assessment: Phthalate exposure levels for four key DEHP metabolites (MEHP, MEHHP, MEOHP, MECPP) were determined using a hybrid approach combining direct measurements and estimations. For regions with robust biomonitoring (USA, Canada, Europe), data were sourced directly from national surveys (NHANES, CHMS) and European projects (COPHES/DEMCOPHES) for the year 2008 or adjacent periods. For regions lacking such data, estimates were derived from a global meta-analysis by Acevedo et al. (2025), which used mixed-effects regression models to project 2008 exposure percentiles based on available literature, with specific imputation methods applied where necessary (e.g., MEHP in Australia).
• Hazard Ratio Estimation and Application: The hazard ratio (HR) linking DEHP exposure to cardiovascular mortality over a 10-year period was extrapolated from a previous US-based study (Trasande et al., 2022). This study established an HR of 1.10 for log-transformed DEHP concentration. The current analysis applied this HR, using a formula that incorporates the natural logarithm of the ratio between a region's quantile-specific molar concentration (in nmol/mL) and a threshold of 0.05 nmol/mL (representing the reference exposure level from the source study), below which no effect was assumed (HR=1). This approach allowed the estimation of risk across different exposure levels globally.
• Mortality and Population Data Sourcing: Mortality and population data were sourced from established global databases. Country-level cardiovascular mortality rates (CVMR) for the 55-64 age group in 2018 were obtained from the IHME Global Burden of Disease study, averaging the rates for 55-59 and 60-64 year olds. Corresponding 2018 population estimates for the same age group were retrieved from the World Bank databank. These datasets provided the necessary baseline mortality and population figures for calculating attributable burden.
• Calculation of Attributable Burden (Deaths and YLL): The study calculated the excess cardiovascular mortality and years of life lost (YLL) attributable to DEHP exposure using the Population Attributable Fraction (PAF) methodology. This involved calculating an excess CV mortality rate for each exposure quantile in each region based on the estimated HR and baseline country CVMR. This excess rate was then applied to the corresponding population segment size to estimate excess deaths. Similarly, excess YLL was calculated by applying the percentage excess mortality rate to baseline IHME-derived YLL estimates for CVD.
• Estimation of Plastics-Attributable Burden: To specifically estimate the burden attributable to plastics, the calculated total DEHP-attributable deaths and YLL were adjusted using a plastics-related fraction derived from Trasande et al. (2024). This fraction, estimated at 98% for DEHP metabolites (with a sensitivity range of 96-99%), represents the proportion of DEHP exposure believed to originate from plastic sources. This step allows the study to link a specific portion of the overall chemical exposure burden directly to plastic production and consumption.
• Sensitivity Analyses for Robustness: The methodological rigor was assessed through several sensitivity analyses designed to test the influence of key assumptions and data inputs. These included using an alternative life expectancy dataset (WHO life expectancy at 60) for YLL calculations, applying phthalate exposure estimates derived from an alternative (quadratic) statistical model from the Acevedo et al. meta-analysis, and calculating a range of attributable burden estimates based on the uncertainty in the plastics-related fraction (96-99%). These analyses help gauge the robustness of the main findings.

Strengths

• Clear Identification of Data Sources

  The methods section clearly outlines the data sources for key variables like population estimates (World Bank), cardiovascular mortality rates (IHME GBD), and phthalate exposure levels (Acevedo et al. meta-analysis, NHANES, CHMS, COPHES/DEMCOPHES), enhancing the study's transparency and reproducibility.

  "All countries recognised by the World Bank were originally considered... values for World Bank 2018 population estimates... and Institute for Health Metrics and Evaluation (IHME) cardiovascular mortality rates be publicly available... This analysis relied on estimates from a previous investigation on global phthalate exposures... sourced from the Canadian Health Measures Survey (CHMS)... USA’s National Health and Nutrition Examination Survey (NHANES)... and the European Consortium... (COPHES)/DEMOCOPHES..." (Page 3)
• Transparent Handling of Missing Data

  The paper explicitly details the procedures for handling missing exposure data, such as the imputation method used for MEHP in Australia and MECPP in Canada, demonstrating methodological rigor in constructing a comprehensive global dataset.

  "MEHP concentrations for Australia were therefore estimated by calculating the ratio of average global MEOHP concentrations to global MEHP concentrations excluding Australia and then multiplying this ratio by the concentration of MEOHP in Australia... MECPP concentrations for Canada was therefore estimated by calculating the ratio of average global MEOHP concentrations to global MECPP concentrations excluding Canada and then multiplying this ratio by the concentration of MEOHP in Canada..." (Page 3)
• Detailed Hazard Ratio Calculation

  The derivation of the hazard ratio (HR) for cardiovascular mortality due to DEHP is well-described, including the reliance on and extrapolation from a previous key study (Trasande et al., 2022), the specific formula used, and the application of an exposure threshold.

  "To calculate hazard ratios for CV mortality across different quantiles, values were extrapolated from Trasande et al., 2022... In multivariable models in this analysis, the hazard ratio for continuously measured, log transformed DEHP metabolite concentration was 1.10... No effects were therefore assumed below 0.05 μmol/L... HRRegion,Quantile = 1.10 ^ (ln(nmol per mLRegion,Quantile / 0.05))" (Page 4)
• Clear Calculation Procedures for Burden Estimation

  The step-by-step calculations for population attributable deaths and years of life lost (YLL) are clearly presented using established epidemiological formulas (Population Attributable Fraction), enhancing the clarity and traceability of the burden estimation process.

  "To calculate the excess CV mortality rate due to phthalate exposure... the population attributable fraction was used... excess CVMR = ((HRregion,quantile −1) / HRregion,quantile) ∗ CVMRcountry... Baseline number of CV deaths = CVMRcountry ∗ Population estimatecountry... Excess deaths = excess CVMRcountry,quantile ∗ (Population estimate ∗ quantile size)... Phthalate YLLcountry,quantile = % excess CVMRcountry,quantile ∗ CVD YLLcountry ∗ size of quantile" (Page 5)
• Inclusion of Worked Example

  The inclusion of a worked example for calculating excess cardiovascular deaths in India provides exceptional transparency, allowing readers to follow the practical application of the described methods and formulas.

  "Worked example: estimation of excess cardiovascular (CV) deaths in India due to phthalate exposure" (Page 5)
• Comprehensive Sensitivity Analyses

  The description of planned sensitivity analyses (alternative YLL data source, quadratic exposure model, range of plastic attributable fractions) demonstrates a thorough approach to assessing the robustness of the findings to key assumptions and methodological choices.

  "To assess the impact of multiple variables in modelling on the results obtained, a series of sensitivity analyses were performed. Alternate estimates of excess YLL... using an alternate dataset... percentiles of phthalate exposure derived from the quadratic model... range of plastic attributable fractions..." (Page 6)

Suggestions for Improvement

• Provide Rationale for Quantile Groupings

  This low-impact improvement would enhance methodological clarity. The Methods section details how different exposure percentiles (10th, 25th, 50th, 75th, 95th) were applied to corresponding segments of the country-level populations (11-25%, 26-50%, 51-75%, 76-95%, 96-100%) for calculating excess deaths. While the application is clear, briefly stating the rationale for choosing these specific quantile groupings over other possibilities (e.g., tertiles, quartiles, deciles) would provide readers with a more complete understanding of this methodological choice. This detail belongs in the Methods section as it pertains directly to the calculation of the primary outcomes.

  "In these analyses, the 10th percentile phthalate exposure was applied to the 11th–25th percentile of country-level populations, 25th to the 26–50th, 50th to the 51–75th, 75th to the 76th–95th, and 95th to the 96th–100th percentile of country-level populations." (Page 5)

  Implementation: Add a brief sentence after describing the quantile application (page 5) explaining the reasoning. For example: "This quantile structure was chosen to align with the granularity of the available exposure percentile estimates from the source studies while ensuring sufficient population size within each segment for stable calculations." or "These specific population segments were used to map directly onto the calculated 10th, 25th, 50th, 75th, and 95th percentiles of regional phthalate exposure."

Results

Key Aspects

• Global DEHP-Attributable Mortality Estimates: The study estimates a substantial global mortality burden from DEHP exposure in 2018 among individuals aged 55-64, calculating approximately 356,238 total deaths, which represents 13.5% of all cardiovascular (CV) deaths in this demographic. Crucially, over 349,000 of these deaths (13.2% of global CV deaths) were specifically attributed to DEHP originating from plastic production, consumption, and waste. These findings quantify the significant contribution of plastic-related chemical exposure to global cardiovascular mortality.
• Regional Variation in DEHP Exposure: Significant regional variation exists in population exposure levels to DEHP metabolites, based on 2008 estimates. Regions including the Middle East, South Asia, and Africa generally exhibited the highest exposure burdens across the four measured metabolites (MEHP, MEHHP, MEOHP, MECPP). Conversely, Europe consistently demonstrated the lowest exposure levels. These exposure differences form the basis for understanding the subsequent disparities observed in health outcomes.
• Geographic Disparities in Attributable Mortality: The research reveals pronounced geographic disparities in the burden of DEHP-attributable cardiovascular mortality. The Middle East and South Asia, along with East Asia and the Pacific, accounted for nearly three-quarters (approx. 73%) of all estimated global DEHP-related CV deaths, driven partly by large aging populations in these areas. Furthermore, the Middle East and South Asia experienced the highest percentage of CV deaths attributable to DEHP (16.8%), significantly higher than regions like Europe (8.4%) and the USA (10.4%), indicating a disproportionate relative burden.
• Burden Measured by Years of Life Lost (YLL): Globally, DEHP exposure among 55-64 year olds in 2018 was estimated to result in over 10.47 million Years of Life Lost (YLL), a measure of premature mortality. The distribution of YLL mirrored the mortality patterns, with the highest burdens concentrated in the Middle East/South Asia and East Asia/Pacific regions. Countries like India, China, and Indonesia experienced the largest absolute YLL totals, further emphasizing the substantial impact of DEHP exposure on population health and longevity in specific areas.
• Intra-Regional Disparities by Exposure Quantile: Analysis of exposure quantiles within regions highlighted significant differences in burden inequality. In the USA and Africa, there was a large disparity (~30 and ~28 percentage points, respectively) in attributable mortality between the highest and lowest exposure quantiles, indicating high inequality where the most exposed face a vastly disproportionate risk. In contrast, regions like the Middle East/South Asia, East Asia/Pacific, and Latin America showed much smaller differences (3-4 percentage points), suggesting a more consistent burden across all exposure levels, even affecting those with lower relative exposures.

Strengths

• Clear Presentation of Headline Findings

  The results section clearly presents the main quantitative findings upfront, such as the total estimated global deaths and the percentage attributable to DEHP and plastics, immediately conveying the scale of the issue.

  "From the main estimates calculated in this analysis, a total of 356,238 deaths due to DEHP exposure were identied (Table 1), of which over 349,000 were plastic- attributable deaths. Exposure to MEHP, MEHHP, MEOHP, and MECPP contributed 13.497% of all CV deaths in 2018 worldwide..." (Page 7)
• Effective Use of Tables and Figures

  The section effectively utilizes tables (Table 1 referenced extensively) and figures (Fig 1a, 1b, Fig 2) to visualize and summarize complex data on regional exposures, mortality burden (absolute and relative), and intra-regional disparities, aiding reader comprehension.

  "South Asia and the Middle East had the highest percentage of CV deaths attributable to DEHP exposure (an average of 16.807%)... indicating a disproportionate burden of disease on these areas (Table 1, Fig. 1b)." (Page 8)
• Highlights Geographic Disparities

  The results effectively highlight the significant geographic inequalities in both DEHP exposure levels and the resulting cardiovascular mortality burden, contrasting high-burden regions (e.g., Middle East, South Asia) with lower-burden regions (e.g., Europe, USA).

  "Geographic disparities in DEHP-attributable CV mortality were notable, with the Middle East and South Asia accounting for 41.678 41.699% of all DEHP- related CV deaths (148,474 148,699 deaths) world- wide (Table 1, Supplement 4)." (Page 7)
• Analysis of Intra-Regional Disparities

  The analysis delves beyond aggregate regional data to examine disparities within regions based on exposure quantiles (Fig 2), revealing important differences in burden inequality (e.g., high inequality in USA/Africa vs. more consistent burden in MESA/EPA/Latin America).

  "In certain regions, there is a greater disparity in percent attributable mortality be- tween the lowest and highest quantiles of exposure. In the USA, the difference between the 95th quantile of exposure and the 10th quantile of exposure is 30.541 percentage points, followed by Africa (28.579% difference)..." (Page 9)
• Links Results to Exposure and Demographics

  The results connect the observed mortality patterns back to potential drivers like regional exposure levels and population demographics (specifically the size of the 55-64 age group), providing context for the findings.

  "These trends were driven by these regions large population sizes within the 55 64-year-old age group." (Page 8)

Suggestions for Improvement

• Enhance Narrative Flow Between Exposure and Mortality Findings

  This medium-impact improvement would enhance narrative coherence within the Results section. While the section presents data on both regional DEHP exposure variations and subsequent attributable mortality disparities, explicitly strengthening the textual connection between these two sets of findings would improve reader comprehension. Making the link how the observed exposure patterns directly translate into the reported mortality outcomes more overt would create a smoother, more integrated narrative flow, reinforcing the logic of the results presentation. This belongs in the Results section as it pertains to the clear communication and linkage of the primary findings.

  "Overall, across all four DEHP me- tabolites, the Middle East, South Asia, and Africa bore the most exposure burden, and Europe consistently had comparably low exposures. A detailed breakdown of regional estimated exposures... can be found in Supplement 2. Geographic disparities in DEHP-attributable CV mortality were notable..." (Page 7)

  Implementation: Integrate brief transitional sentences or clauses. For instance, after describing the regional exposure patterns (end of paragraph 2, page 7), add a sentence like: "These significant regional differences in DEHP exposure levels subsequently manifest in notable geographic disparities in the estimated cardiovascular mortality burden." Or, when introducing the mortality disparities (start of paragraph 3, page 7), phrase it as: "Reflecting these varied exposure profiles and regional demographics, geographic disparities in DEHP-attributable CV mortality were notable..."

Non-Text Elements

Table 1: Aggregate cardiovascular mortality burden due to DEHP, main estimates.

Figure/Table Image (Page 7)

First Reference in Text

identified (Table 1), of which over 349,000 were plastic-attributable deaths.

Description

• Overview of Content: This table presents estimated numbers of deaths and Years of Life Lost (YLL) - a measure of premature mortality - linked to cardiovascular disease (CVD) that are specifically attributed to exposure to a chemical called Di(2-ethylhexyl) phthalate (DEHP). DEHP is commonly used to make plastics more flexible. The estimates are for the year 2018, based on DEHP exposure levels from 2008.
• Data Stratification by Region and Exposure Quantile: The data is broken down into major world regions (like Africa, Asia-EPA for East Asia/Pacific, Asia-MESA for Middle East/South Asia, etc.) and also by different levels of DEHP exposure within the population, divided into segments called quantiles (specifically, the 10th, 25th, 50th, 75th, and 95th percentiles). Quantiles represent ranges of exposure, allowing comparison between lower and higher exposed groups.
• Global Burden Estimates: Globally, the table estimates a total of 356,238 deaths and 10,473,621 YLL were attributable to DEHP exposure in 2018 among individuals aged 55-64.
• Regional Disparities: The table highlights significant differences between regions. For instance, the Middle East and South Asia (Asia-MESA) region shows the highest average percentage of CVD deaths attributed to DEHP (16.807%), whereas Europe shows a lower average percentage (8.374%).
• Specific Metrics Presented: For each region and exposure quantile, the table shows the estimated number of deaths, the corresponding YLL, and the percentage of total CVD deaths that these attributable deaths represent.

Scientific Validity

• Data Sources and Integration: The estimates are derived using established methodologies, combining baseline mortality data from a reputable source (IHME), population data (World Bank), and DEHP exposure data from regional biomonitoring or prior meta-analyses (Acevedo et al., 2025). This multi-source approach is standard for global burden studies.
• Methodology for Attributable Burden Calculation: The calculation relies on applying a hazard ratio for DEHP exposure and CVD mortality derived from a specific US cohort study (Trasande et al., 2022) to global populations. While using a single study's HR introduces uncertainty, it is based on available longitudinal data. The use of population attributable fractions is an appropriate epidemiological technique for this type of estimation.
• Temporal Lag Consideration: The use of a 10-year lag between exposure measurement (2008) and mortality outcome (2018) is methodologically appropriate to account for the latency period often associated with chronic disease development following environmental exposures.
• Handling of Missing Data: The footnote acknowledges specific data imputations (e.g., MEHP for Australia, MECPP for Canada), which is important for transparency regarding data limitations and the methods used to address them.
• Model Assumptions and Potential Conservatism: The table presents 'main estimates' likely based on linear exposure models (as suggested by sensitivity analyses mentioned elsewhere in the paper). The validity hinges on the assumptions of these models and the generalizability of the hazard ratio. As noted in the discussion/sensitivity analysis, these estimates might be conservative.

Communication

• Data Consolidation and Structure: The table effectively consolidates complex data on DEHP-attributable cardiovascular mortality and YLL across multiple regions and exposure quantiles into a structured format. Column and row labels are generally clear, facilitating comparison.
• Summary Statistics: Including total deaths, total YLL, and average attributable percentages for each region and globally provides a concise summary of the main findings.
• Granularity by Exposure Quantile: The breakdown by exposure quantiles (10th, 25th, 50th, 75th, 95th) allows for a nuanced view of how the attributable burden varies with exposure levels within different populations.
• Transparency via Footnote: The detailed footnote explaining data sources (IHME, biomonitoring surveys, Acevedo et al. 2024 meta-analysis), calculation methods (hazard ratio application, quantile weighting), and specific imputations (e.g., MEHP for Australia) is essential for transparency and allows readers to understand the basis of the estimates.
• Alignment with Text: The presentation aligns well with and directly supports the key quantitative findings reported in the Results text, such as the total global deaths and regional disparities.

Fig. 1: Aggregate DEHP-attributable mortality world maps among 200 countries...

Full Caption

Fig. 1: Aggregate DEHP-attributable mortality world maps among 200 countries and eight world regions.

Figure/Table Image (Page 8)

First Reference in Text

from DEHP in 2018 occurred in the continent of Asia (Fig. 1a).

Description

• Content Overview: This map (labeled 'a') shows how the total estimated number of cardiovascular disease (CVD) deaths worldwide attributed to Di(2-ethylhexyl) phthalate (DEHP) exposure are distributed across different continents or large regions. It essentially shows the 'global share' of the burden held by each area.
• Visualization Method: The map uses different shades of purple to represent the proportion, or fraction, of the total global DEHP-attributable CVD deaths found in each region. Darker shades indicate a larger share.
• Key Findings Displayed: The legend indicates the scale, ranging from 0.1 (meaning 10% of the global total) to 0.4 (meaning 40% of the global total). The continent of Asia is shown in the darkest shade, indicating it accounts for the largest proportion of these deaths globally, aligning with the reference text stating the majority occurred in Asia.

Scientific Validity

• Representation of Model Output: The map accurately reflects the calculated spatial distribution of the absolute number of DEHP-attributable deaths derived from the underlying burden model. Its validity is contingent upon the accuracy and assumptions of that model (e.g., hazard ratios, exposure estimates, population data).
• Focus on Absolute Impact: This visualization appropriately highlights the impact of population size combined with attributable risk, identifying regions with the largest absolute public health impact in terms of numbers of deaths.
• Data Aggregation Level: The aggregation into broad regions (continents/subcontinents) is a necessary simplification for global visualization but masks potentially significant intra-regional variations.

Communication

• Geographic Visualization of Absolute Burden: The choropleth map effectively visualizes the geographical distribution of the absolute burden of DEHP-attributable CVD deaths, allowing for rapid identification of continents contributing the largest share to the global total.
• Clarity of Legend and Gradient: The color gradient and legend (0.1 to 0.4) are clear and intuitively represent the proportion of the total global deaths occurring in each region.
• Focus on Global Share: This panel clearly communicates where the highest number of attributable deaths are concentrated globally, complementing the relative risk information in Panel B.

Fig. 2: Percent change in attributable cardiovascular mortality due to DEHP...

Full Caption

Fig. 2: Percent change in attributable cardiovascular mortality due to DEHP exposure by quantile in across eight world regions.

Figure/Table Image (Page 9)

First Reference in Text

These patterns over percentiles are visualised in Fig. 2.

Description

• Purpose of the Graph: This graph shows how the estimated percentage of cardiovascular deaths linked to DEHP exposure changes as the level of exposure increases within different populations around the world.
• X-axis Explanation (Exposure Quantile): The horizontal axis (x-axis) represents the 'Quantile of exposure in the population'. A quantile divides the population into groups based on their exposure level; moving from left to right means looking at groups with progressively higher exposure to DEHP (e.g., 25th percentile means higher exposure than 25% of the population, 75th percentile means higher exposure than 75%).
• Y-axis Explanation (Attributable Mortality): The vertical axis (y-axis) shows the 'Percentage attributable CV mortality'. This is the estimated percentage of cardiovascular deaths within a specific exposure group that can be attributed to DEHP exposure.
• Regional Lines: Each colored line represents a different major world region (e.g., Africa, Europe, USA, Asia-MESA). The graph plots how the attributable mortality percentage changes across exposure quantiles for each region.
• Observed Trends and Patterns: The lines generally slope upwards, indicating that for most regions, higher levels of DEHP exposure are associated with a higher percentage of attributable cardiovascular deaths. However, the starting points (attributable percentage at lower quantiles) and the steepness of the lines vary significantly between regions.
• Smoothing Technique (LOESS): The caption mentions that the curves are smoothed using LOESS regression, a statistical technique used to create a smooth line through data points to visualize trends more clearly.

Scientific Validity

• Representation of Model Output: The graph visually represents the calculated population attributable fractions derived from applying region-specific exposure quantile data and hazard ratios. Its validity is directly tied to the robustness of these underlying calculations and the assumptions of the burden model.
• Use of Exposure Quantiles: The use of exposure quantiles (derived from estimated or measured population distributions) is an appropriate way to stratify the population and examine dose-response-like patterns in attributable burden.
• Smoothing Method Appropriateness: The application of LOESS smoothing is a valid technique for visualizing trends in potentially noisy data derived from quantile estimates, but the degree of smoothing could influence the perceived shape of the relationship.
• Visualization of Heterogeneity: The graph accurately depicts the heterogeneity in attributable burden across regions and exposure levels, supporting the study's conclusions about geographic disparities and the differential impact of exposure depending on the region.

Communication

• Trend Visualization: The use of a line graph effectively illustrates the trend of increasing attributable mortality with increasing exposure quantiles for most regions.
• Regional Comparison: Plotting multiple regions on the same axes facilitates direct comparison of both the baseline attributable risk (y-intercept approximation) and the steepness of the exposure-response relationship across different geographical areas.
• Legend Clarity: The legend clearly identifies the color corresponding to each world region.
• Use of Smoothing: The LOESS smoothing helps to visualize the general trend for each region, reducing noise from specific quantile estimates, although it might obscure finer details.
• Support for Textual Findings: The visualization directly supports the textual description of disparities, showing how some regions (e.g., USA, Africa) have a large difference between low and high quantiles, while others (e.g., Asia-MESA) have high attributable mortality even at lower exposure quantiles.
• Color Choice and Accessibility: While distinct, some colors in the plot might be difficult to differentiate for individuals with color vision deficiency. Consider using a combination of colors and line styles (e.g., dashed, dotted) for better accessibility.

Discussion

Key Aspects

• Summary of Global Burden and Disparities: The study concludes that exposure to plastics, specifically via DEHP metabolites, contributed significantly to global cardiovascular (CV) mortality in 2018, accounting for over 356,000 deaths (13.5% of CV mortality) among 55-64 year olds. A key finding emphasized is the pronounced geographic disparity, with regions like the Middle East, South Asia, East Asia, and the Pacific bearing a disproportionately high burden. This highlights plastics as a significant, unequally distributed global health risk requiring urgent attention.
• Alignment with Industrial and Regulatory Trends: The discussion contextualizes the findings within broader global trends, aligning the observed high DEHP exposure and attributable mortality in certain regions with factors like expanding plastics industries, inadequate waste management infrastructure, and varying regulatory landscapes. It notes that while some regulations exist (e.g., EU, Japan, US bans in specific products), many were implemented recently or are inconsistent globally, suggesting the measured 2008 exposures may not reflect the impact of subsequent policies. This connection reinforces the need for harmonized global action.
• Economic Cost Considerations: The paper translates the mortality findings into potential economic consequences, presenting a range of societal costs using two distinct methodologies: Social Cost of a Year of Life Lost (SCYLL) and Value of a Statistical Life (VSL). Estimates range widely, from $10.2 billion (conservative SCYLL) to $3.74 trillion (VSL based on US DOT value). While acknowledging the limitations of extrapolation and value judgments, this analysis underscores the potentially massive economic burden associated with plastic-induced mortality, adding another layer to the argument for intervention.
• Policy Implications and Recommendations: Based on the quantified burden and observed disparities, the discussion strongly advocates for policy interventions at multiple levels. Recommendations include limiting DEHP exposure through regulations (bans, restrictions, labeling), improving waste management, promoting consumer behavior change, and increasing public awareness. It specifically highlights the need for targeted regulations in high-burden regions and support for developing economies facing dual challenges of industrial growth and waste management, emphasizing the need for international cooperation.
• Methodological Limitations and Data Issues: The authors thoroughly address the study's limitations, acknowledging the reliance on regional exposure estimates derived from meta-analysis rather than country-specific data, particularly for regions like Africa with sparse data. Data source heterogeneity (IHME vs. national data, WHO vs. IHME YLL calculations) and potential variations in territorial definitions are discussed as sources of uncertainty. The limited scope, focusing only on four DEHP metabolites and excluding other plastic-related chemicals (bisphenols, MNPs) and climate change impacts, is noted as a potential source of underestimation.
• Limitations Regarding HR Extrapolation and Confounding: Further limitations discussed include the uncertainty in extrapolating the exposure-response relationship (Hazard Ratio) derived primarily from a single US study to a global context, given potential differences in population characteristics and co-exposures across regions. The inability to disaggregate data by sex and the use of aggregate country-level data, which prevents accounting for individual-level confounders like socioeconomic status that might correlate with both exposure and baseline CVD risk, are also acknowledged as factors potentially biasing the magnitude of attributable mortality estimates.
• Overall Conclusion and Call for Action: Despite the acknowledged limitations and the inability to establish causality from this modeling study, the discussion concludes that the findings provide feasible and concerning estimates of the cardiovascular risks associated with DEHP exposure from plastics. It emphasizes that this model captures only a fraction of the potential health risks from plastics and underscores the urgent need for comprehensive strategies, enhanced regulation, and international cooperation to address the global health impacts of plastic pollution, particularly in disproportionately affected regions.

Strengths

• Clear Summary and Contextualization of Findings

  The Discussion effectively synthesizes the key quantitative findings, reiterating the estimated global deaths and attributable percentage, and immediately contextualizes these results by highlighting the disproportionate burden on specific regions (Middle East, South Asia, East Asia/Pacific).

  "In the present disease burden model, it was identied that a total of just over 356,000 global deaths, or 13.497% of worldwide CV mortality in 2018 among 55 64-year-olds was attributable to plastics exposure. The effects of DEHP metabolite exposures on CVD out comes were disproportionately experienced by countries in the Middle East and South Asia as well as East Asia and the Pacic..." (Page 10)
• Inclusion of Economic Cost Analysis

  The section thoughtfully explores the economic implications of the estimated mortality burden by presenting a range of potential societal costs using different valuation methods (SCYLL and VSL), adding a significant dimension to the public health impact assessment.

  "If all the YLLs are valued equally at $50,000 each, then the social costs of plastic-induced mortality would total $510 billion... Based on the U.S. Department of Trans portation s 2018 denition where VSL is valued at $10.5 million... the total cost for 356,238 deaths would amount to $3.74 trillion." (Page 10)
• Integration with Industrial and Regulatory Context

  The discussion effectively connects the study's findings to real-world factors, including global trends in plastic production, waste management issues, industrialization levels, and the existing (often inconsistent) regulatory landscape concerning phthalates like DEHP.

  "This analysis aligns with global trends in plastics production and regulation... Findings from this disease burden model also align with expectations when considering the regulatory landscape in the 2008 2018 period. Globally, phthalate regulations targeting DEHP have primarily been implemented on a country-by-country or small regional basis." (Page 10)
• Strong Policy Relevance and Recommendations

  The authors provide clear, actionable policy recommendations derived from their findings, emphasizing the need for multi-modal interventions, targeted regulations, international collaboration, and improved public awareness to mitigate phthalate exposure risks.

  "It highlights the urgent need for both global and local policy interventions and offers evidence to support targeted regulations in countries with high phthalate exposures. To mitigate the impact of phthalates on CV mortality, multi-modal in terventions are necessary at both regional and global levels." (Page 11)
• Comprehensive Acknowledgement of Limitations

  The Discussion section demonstrates scientific rigor by thoroughly acknowledging and discussing multiple study limitations, including reliance on regional estimates, data source heterogeneity, the limited number of metabolites studied, and the extrapolation from a single US-based study for hazard ratios.

  "The present study has limitations that warrant consideration. To estimate the global health effects due to plastics, it was necessary to rely on regional estimates from meta-analysis rather than country-specic chemi cal exposure data... In addition, heterogeneity of data sources warrants discussion... The present study was also limited in its investiga tion of only four DEHP metabolites." (Page 11)

Suggestions for Improvement

• Explicitly Link Limitations to Potential Impact on Estimates

  This medium-impact improvement would enhance the critical interpretation of the study's findings. The Discussion acknowledges several key limitations (e.g., reliance on regional estimates, heterogeneity, single US study for HR, exclusion of other chemicals/MNPs) and notes that the model might be conservative or that the true burden could be greater. Explicitly connecting how each major limitation likely influences the direction and potential magnitude of the burden estimate (i.e., likely underestimation vs. overestimation) would strengthen the interpretation. This belongs in the Discussion as it involves interpreting results in light of methodological constraints.

  "These were not accounted for in calculation of attributable mortality, potentially under estimating the overall mortality burden due to plastic exposure... While estimates in this model are primarily based on ndings from a single study from the US,41 they are supported by laboratory research ndings and epidemiological studies." (Page 12)

  Implementation: For each major limitation discussed (pages 11-12), add a sentence explicitly stating its likely impact. For example, after discussing the limitation of only four DEHP metabolites and excluding MNPs/other chemicals: "This exclusion means our model likely underestimates the total cardiovascular burden attributable to overall plastic chemical exposure." After discussing reliance on the US HR study: "Extrapolating this US-based HR globally might lead to either under- or overestimation depending on regional differences in susceptibility, co-exposures, and baseline CVD risk, introducing uncertainty directionally difficult to quantify without further region-specific research."

• Briefly Discuss Discrepancy in Economic Cost Estimates

  This low-impact improvement could refine the presentation of the economic analysis. The Discussion presents vastly different economic cost estimates derived from SCYLL ($10.2B - $510B) and VSL ($2.6T - $3.74T) methodologies but doesn't elaborate on why these figures differ so dramatically or the implications of this range for policy considerations. Briefly explaining the conceptual difference between valuing a year of life lost versus a statistical life, and commenting on the policy implications of this billion-vs-trillion dollar discrepancy, would add depth. This analysis fits within the Discussion's role of interpreting the broader significance of the findings.

  "If all the YLLs are valued equally at $50,000 each, then the social costs of plastic-induced mortality would total $510 billion... Based on the U.S. Department of Trans portation s 2018 denition where VSL is valued at $10.5 million... the total cost for 356,238 deaths would amount to $3.74 trillion." (Page 10)

  Implementation: Add a sentence or two after presenting the SCYLL and VSL ranges (page 10). For example: "The substantial difference between SCYLL and VSL estimates reflects fundamental differences in valuation methodology, with SCYLL focusing on productivity/cost-of-illness and VSL reflecting willingness-to-pay for risk reduction. This wide range underscores the uncertainty in monetizing health impacts but highlights that, regardless of the method, the potential economic consequences of DEHP-attributable mortality are substantial, ranging from tens of billions to trillions of dollars, providing strong economic arguments for preventative action."