Evidence map›Paper›PMID 39316310›Full record

ArticleJournal of urban health : bulletin of the New York Academy of Medicine2024

SchoolHEAT: Racial and Ethnic Inequity in School Temperature.

Kelly K Jones, Varsha Vijay, Shannon N Zenk

Abstract read
In one paragraph

Article in Journal of urban health : bulletin of the New York Academy of Medicine, 2024. 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

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

3 authors.

Kelly K JonesDivision of Intramural Research, National Institute On Minority Health and Health Disparities, 6707 Democracy Blvd, Suite 800, Bethesda, MD, 20892, USA. kelly.jones2@nih.gov.ORCID http://orcid.org/0000-0002-1552-7847
Varsha VijayScience Based Targets Network, New York City, NY, USA.
Shannon N ZenkDivision of Intramural Research, National Institute On Minority Health and Health Disparities, 6707 Democracy Blvd, Suite 800, Bethesda, MD, 20892, USA.

Funding

Neighborhoods and Health LabZIAMD000021 · NIMHD · NATIONAL INSTITUTE ON MINORITY HEALTH AND HEALTH DISPARITIES · PI ZENK, SHANNON · 2021 to 2025
$1.9M
Intramural NIH HHS ZIA MD000021NIMHD NIH HHS Division of Intramural Research
6 · The paper itself

Abstract

Exposure to high environmental temperature is detrimental to health through multiple pathways. This paper describes disparities in school-based high-temperature exposure at metropolitan schools in the United States. Using school location and sociodemographic data from the National Center for Education Statistics, neighborhood data from the US Census Bureau, and land surface temperature (LST) data from the Aqua Earth-observing satellite mission, we find that for every 10% more Black or Hispanic residents in the neighborhood, schools have LST 0.25 °C and 0.38 °C hotter, respectively. When the Black or Hispanic student population is greater than the neighborhood population, LST is an additional 0.20 °C and 0.40 °C for each 10% increase in students over neighborhood population, respectively. Black and Hispanic students are overrepresented in the hottest schools, making up 58.7% of students in the hottest 20% of schools, compared to only 30.0% of students in the coolest 20% of schools.

Indexed as

Hispanic or LatinoHot TemperatureSchoolsBlack or African AmericanChildEthnicityFemaleHealth Status DisparitiesHumansMaleRacial GroupsResidence CharacteristicsSocioeconomic FactorsStudentsUnited StatesClimateHeat exposureLand surface temperature disparitiesSchool wellness

Identifiers

PMID39316310
PMCPMC11652446

What OpenQuestion holds

Textmetadata
LicenceCC BY
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.