Evidence map›Paper›PMID 39375305›Full record

ArticleJournal of urban health : bulletin of the New York Academy of Medicine2025

Analyzing and Optimizing the Distribution of Blood Lead Level Testing for Children in New York City: A Data-Driven Approach.

Khalifa Afane, Juntao Chen

Abstract read
In one paragraph

Article in Journal of urban health : bulletin of the New York Academy of Medicine, 2025. 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

2 authors.

Khalifa AfaneDepartment of Computer and Information Sciences, Fordham University, New York, USA. mafane@fordham.edu.ORCID http://orcid.org/0009-0005-8959-6895
Juntao ChenDepartment of Computer and Information Sciences, Fordham University, New York, USA.ORCID http://orcid.org/0000-0001-7726-4926

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

This study investigates blood lead level (BLL) rates and testing among children under 6 years of age across the 42 neighborhoods in New York City from 2005 to 2021. Despite a citywide general decline in BLL rates, disparities at the neighborhood level persist and are not addressed in the official reports, highlighting the need for this comprehensive analysis. In this paper, we analyze the current BLL testing distribution and cluster the neighborhoods using a k-medoids clustering algorithm. We propose an optimized approach that improves resource allocation efficiency by accounting for case incidences and neighborhood risk profiles using a grid search algorithm. Our findings demonstrate statistically significant improvements in case detection and enhanced fairness by focusing on under-served and high-risk groups. Additionally, we propose actionable recommendations to raise awareness among parents, including outreach at local daycare centers and kindergartens, among other venues.

Indexed as

LeadLead PoisoningResidence CharacteristicsChildChild, PreschoolFemaleHumansInfantMaleNew York CityLeadBlood lead levels in childrenClusteringGrid search

Identifiers

PMID39375305
PMCPMC11865405

What OpenQuestion holds

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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.