Global health burden and cost of lead exposure in children and adults: a health impact and economic modelling analysis
Bibliographic record
Abstract
BACKGROUND: Lead exposure is a worldwide health risk despite substantial declines in blood lead levels following the leaded gasoline phase-out. For the first time, to our knowledge, we aimed to estimate the global burden and cost of intelligence quotient (IQ) loss and cardiovascular disease mortality from lead exposure. METHODS: In this modelling study, we used country blood lead level estimates from the Global Burden of Diseases, Injuries, and Risk Factors Study (GBD) 2019. We estimated IQ loss (presented as estimated loss in IQ points with 95% CIs) in the global population of children younger than 5 years using the blood lead level-IQ loss function from an international pooled analysis. We estimated the cost of IQ loss, which was calculated only for the proportion of children expected to enter the labour force, as the present value of loss in lifetime income from the IQ loss (presented as cost in US dollars and percentage of gross domestic product with a range). We estimated cardiovascular deaths (with 95% CIs) due to lead exposure among people aged 25 years or older using a health impact model that captures the effect of lead exposure on cardiovascular disease mortality that is mediated through mechanisms other than hypertension. Finally, we used values of statistical life to estimate the welfare cost of premature mortality (presented as cost in US dollars and percentage of GDP). All estimates were calculated by World Bank income classification and region (for low-income and middle-income countries [LMICs] only) for 2019. FINDINGS: We estimated that children younger than 5 years lost 765 million (95% CI 443-1098) IQ points and that 5 545 000 (2 305 000-8 271 000) adults died from cardiovascular disease in 2019 due to lead exposure. 729 million of the IQ points lost (95·3% of the total global IQ loss) and 5 004 000 (90·2% of total) cardiovascular disease deaths due to lead exposure occurred in LMICs. IQ loss in LMICs was nearly 80% higher than a previous estimate. Cardiovascular disease deaths were six times higher than the GBD 2019 estimate. The global cost of lead exposure was US$6·0 trillion (range 2·6-9·0) in 2019, which was equivalent to 6·9% (3·1-10·4) of the global gross domestic product. 77% (range 70-78) of the cost was the welfare cost of cardiovascular disease mortality, and 23% (22-30) was the present value of future income losses from IQ loss. INTERPRETATION: air pollution. However, much work remains to improve the quality of blood lead level measurement data, especially in LMICs. FUNDING: The Korea Green Growth Trust Fund and the World Bank's Pollution Management and Environmental Health Program.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.003 | 0.008 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.004 |
| Bibliometrics | 0.002 | 0.004 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.007 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".