Evidence map›Paper›PMID 32311907›Full record

ArticleEnvironmental research2020

Probabilistic estimates of prenatal lead exposure at 195 toxic hotspots in low- and middle-income countries.

Lauren Zajac, Roni W Kobrosly, Bret Ericson, Jack Caravanos, Philip J Landrigan, Anne M Riederer

Abstract read
In one paragraph

Article in Environmental research, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 8 papers.

0numbers the graph read from it
0cells of the map it votes in
8citing 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

8 citing papers in PubMed.

  1. Article
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  7. Characteristics and Risk Assessment of Soil Polluted by Lead around Various Metal Mines in China.International journal of environmental research and public health · 2021
    Article
  8. Article
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

6 authors.

Lauren ZajacDepartment of Environmental Medicine and Public Health, Icahn School of Medicine at Mount Sinai, One Gustave L. Levy Place, Box 1057, New York, NY, 10029, USA. Electronic address: lauren.zajac@mssm.edu.
Roni W KobroslyDepartment of Environmental Medicine and Public Health, Icahn School of Medicine at Mount Sinai, One Gustave L. Levy Place, Box 1057, New York, NY, 10029, USA.
Bret EricsonPure Earth, 475 Riverside Drive, Suite 860, New York, NY, 10115, USA; Department of Environmental Sciences, Faculty of Science and Engineering, Macquarie University, North Ryde, Sydney, NSW, 2109, Australia.
Jack CaravanosCollege of Global Public Health, New York University, 665 Broadway, New York, NY, 10012, USA.
Philip J LandriganDepartment of Environmental Medicine and Public Health, Icahn School of Medicine at Mount Sinai, One Gustave L. Levy Place, Box 1057, New York, NY, 10029, USA.
Anne M RiedererPure Earth, 475 Riverside Drive, Suite 860, New York, NY, 10115, USA; Department of Environmental and Occupational Health, Milken Institute School of Public Health, George Washington University, 950 New Hampshire Avenue NW, Washington, DC, 20052, USA; Department of Environmental and Occupational Health Sciences, School of Public Health, University of Washington, 1959 NE Pacific Street, Seattle, WA, 98195, USA.

Funding

Research Training Program in Pediatric ExposomicsT32HD049311 · NICHD · ICAHN SCHOOL OF MEDICINE AT MOUNT SINAI · PI KECIA Nicole CARROLL, Robert O Wright · 2007 to 2026
$7.4M
NICHD NIH HHS T32 HD049311
6 · The paper itself

Abstract

backgroundPrior estimates of pediatric lead-related disease burden in low- and middle-income countries (LMICs) used population estimates of maternal blood lead levels (BLLs). This approach may underestimate fetal BLLs by not considering potentially high prenatal lead exposure from toxic hotspots

methodsWe created distributions for each ALM parameter using published literature and extracted soil lead measurements from the TSIP database. Each iteration of the probabilistic ALM randomly selected values from the input distributions to generate a site-specific fetal BLL estimate. For each site, we ran 5000 model iterations, producing a site-specific fetal BLL distribution.

results195 TSIP sites, in 33 LMICs, met our study inclusion criteria; an estimated 820,000 women of childbearing age are at risk for lead exposure at these sites. The predicted geometric means (GM) for site-specific fetal BLLs ranged from 3.3 μg/dL to 534 μg/dL, and 98% of sites had estimated GM fetal BLLs >5 μg/dL, the current reference level of the United States Centers for Disease Control and Prevention (CDC), while 11 sites had estimated GM fetal BLLs above the CDC chelation threshold of 45 μg/dL. DISCUSSION: The TSIP soil lead data and this probabilistic approach to the ALM show that pregnant women living near TSIP sites may have BLLs that put their fetus at risk for neurologic damage and other sequelae, underscoring the need for interventions to reduce lead exposure at toxic hotspots.

Indexed as

Environmental ExposureLeadLead PoisoningMaternal ExposureModels, StatisticalAdultChildDeveloping CountriesEnvironmental PollutionFemaleHumansPovertyPregnancyLeadBlood lead levelPrenatal lead exposureProbabilistic simulationSoil contaminationToxic waste sites

Identifiers

PMID32311907
PMCPMC7176741

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Registered trials

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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.