Evidence map›Paper›PMID 41910985›Full record

SynthesisJAMA2026

Lead-Attributable Cardiovascular Disease Burden: Global Burden of Disease Study 2023.

GBD 2023 Lead Collaborators, Jeffrey D Stanaway, Sandra Spearman, Nicole K DeCleene, Vanessa Garcia, Laura Lara-Castor, Stephen S Lim, Christopher J L Murray, Gregory A Roth, Matthew A Seymour and 2 more

Abstract readMeta-AnalysisSystematic Review
In one paragraph

Synthesis in JAMA, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

1 citing paper in PubMed.

  1. Article
4 · The record

Corrections and comments

5 · Who and what money

Authors and funding

12 authors.

GBD 2023 Lead Collaborators
Jeffrey D StanawayDepartment of Health Metrics Sciences, Institute for Health Metrics and Evaluation, Seattle, Washington.
Sandra SpearmanDepartment of Health Metrics Sciences, Institute for Health Metrics and Evaluation, Seattle, Washington.
Nicole K DeCleeneDepartment of Health Metrics Sciences, Institute for Health Metrics and Evaluation, Seattle, Washington.
Vanessa GarciaDepartment of Health Metrics Sciences, Institute for Health Metrics and Evaluation, Seattle, Washington.
Laura Lara-CastorDepartment of Health Metrics Sciences, Institute for Health Metrics and Evaluation, Seattle, Washington.
Stephen S LimDepartment of Health Metrics Sciences, Institute for Health Metrics and Evaluation, Seattle, Washington.
Christopher J L MurrayDepartment of Health Metrics Sciences, Institute for Health Metrics and Evaluation, Seattle, Washington.
Gregory A RothDepartment of Health Metrics Sciences, Institute for Health Metrics and Evaluation, Seattle, Washington.
Matthew A SeymourDepartment of Health Metrics Sciences, Institute for Health Metrics and Evaluation, Seattle, Washington.
Benjamin StarkDepartment of Health Metrics Sciences, Institute for Health Metrics and Evaluation, Seattle, Washington.
Michael BrauerDepartment of Health Metrics Sciences, Institute for Health Metrics and Evaluation, Seattle, Washington.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Importance: Despite declines, lead exposure remains a major risk factor for cardiovascular disease (CVD) mortality. Quantifying the direct effects of cumulative bone lead exposure on CVD is essential to guide prevention and policy. Objectives: To estimate the association between bone lead levels and CVD, derive an exposure-response curve, and estimate global, regional, and national lead-attributable disease burden for 1990 to 2023. Design, Setting, and Participants: Analysis of 42 028 adults from 9 cycles of the US National Health and Nutrition Examination Survey (NHANES) spanning 1988 through 2013, with follow-up through December 2015 capturing 1748 CVD deaths, was combined with a systematic review and meta-regression. Bone lead was estimated from blood lead, age, and cohort-specific exposure histories. Cox proportional hazards models adjusted for blood pressure and confounders estimated hazard ratios for CVD mortality. A bayesian meta-regression using the Burden of Proof framework pooled NHANES results with published data to estimate the risk curve, which was then applied to lead exposure and CVD estimates to estimate population-attributable fractions and lead-attributable CVD burden. Exposure: Estimated bone lead levels. Main Outcomes and Measures: Lead-attributable CVD mortality, years lived with disability, years of life lost, and disability-adjusted life-years (DALYs) by age, sex, year, and location. Results: NHANES participants were aged 18 to 90 years (median, 46 [IQR, 32-63] years) and 51.5% of participants were female, with estimated bone lead levels ranging from 0.17 μg/g to 301 μg/g (median, 13.3 μg/g). Higher bone lead levels were associated with higher CVD risk: relative to estimated preindustrial levels of 0.027 μg/g, bone lead levels of 5 μg/g, 10 μg/g, 25 μg/g, 50 μg/g, and 100 μg/g corresponded to 7.5% (95% uncertainty interval [UI], 1.7%-14.1%), 15.8% (95% UI, 12.7%-19.1%), 41.3% (95% UI, 34.2%-49.2%), 71.3% (95% UI, 55.4%-90.0%), and 87.9% (95% UI, 61.0%-121.2%) greater CVD mortality risk, respectively. Globally in 2023, 3.5 million (95% UI, 2.6 million to 4.4 million) deaths and 71.6 million (95% UI, 52.4 million to 90.3 million) DALYs were attributable to lead exposure, accounting for 5.8% (95% UI, 4.3%-7.2%) of all deaths and 2.6% (95% UI, 1.8%-3.2%) of all DALYs. Lead was the eighth leading risk for global mortality and second leading environmental risk. Conclusions and Relevance: Cumulative lead exposure remains a major, preventable contributor to global CVD mortality. Strengthened surveillance, regulation, and remediation are urgently required to reduce the lead-attributable burden.

Indexed as

Cardiovascular DiseasesGlobal Burden of DiseaseLeadNutrition SurveysAdolescentAdultAgedAged, 80 and overBayes TheoremBone and BonesDisability-Adjusted Life YearsEnvironmental ExposureEnvironmental PollutantsFemaleFollow-Up StudiesHeart Disease Risk FactorsEnvironmental PollutantsLead

Identifiers

PMID41910985
PMCPMC13036637

What OpenQuestion holds

Textmetadata
Read underepoch 390

Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.