Evidence map›Paper›PMID 39857469›Full record

ArticleInternational journal of environmental research and public health2024

Visualizing Parcel-Level Lead Risk Using an Exterior Housing-Based Index.

Neal J Wilson, Ryan Allenbrand, Elizabeth Friedman, Kevin Kennedy, Amy Roberts, Stephen Simon

Abstract read
In one paragraph

Article in International journal of environmental research and public health, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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

0 citing papers in PubMed.

No citing paper in PubMed yet.

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.

Neal J WilsonCenter for Economic Information, University of Missouri-Kansas City, 5120 Rockhill Rd, Kansas City, MO 64110, USA.ORCID 0000-0002-6380-9822
Ryan AllenbrandEnvironmental Health Program, Children's Mercy Kansas City, 2401 Gillham Road, Kansas City, MO 64108, USA.
Elizabeth FriedmanEnvironmental Health Program, Children's Mercy Kansas City, 2401 Gillham Road, Kansas City, MO 64108, USA.
Kevin KennedyHealthy Indoors Training and Consulting, LLC., Lawrence, KS 66044, USA.
Amy RobertsKansas City, Missouri Health Department, 2400 Troost Ave., Kansas City, MO 64106, USA.
Stephen SimonDepartment of Biomedical and Health Informatics, University of Missouri-Kansas City, 2411 Holmes St, Kansas City, MO 64108, USA.

Funding

United States Department of Housing and Urban Development Fiscal Year 2020 Lead Technical Studies Grant Program (MOLTS0019-20)
6 · The paper itself

Abstract

Pediatric lead poisoning remains a persistent public health problem. Children in the US spend the preponderance of their time at home; thus, housing is an important social determinant of health. Improving health outcomes derived from housing-based sources involves differentiating the risks posed by the existing housing stock. In this paper, we developed a parcel-level lead risk index (LRI) based on external housing conditions and the year of home construction. The purpose of this study was to introduce a housing-based lead risk index (LRI), developed using retrospective data, to estimate parcel-by-parcel variation in housing-based lead risk. We described how the LRI is constructed, relate it to the likelihood of a pediatric occupant's blood lead level (BLL) > 3.5 µg/dL using Lasso regression (

Indexed as

Environmental ExposureHousingLeadLead PoisoningChildChild, PreschoolHumansRetrospective StudiesRisk AssessmentUnited StatesLeadchildhood blood lead levelsenvironmental public healthhousinglead hazard riskplace-based approachsocial determinates of health

Identifiers

PMID39857469
PMCPMC11765214

What OpenQuestion holds

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LicenceCC BY
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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.