Evidence map›Paper›PMID 39179752›Full record

ArticleJournal of exposure science & environmental epidemiology2025

Using geographic effect measure modification to examine socioeconomic-related surface temperature disparities in New York City.

Nadav L Sprague, Stephen P Uong, Nora C Kelsall, Ahuva L Jacobowitz, James W Quinn, Katherine M Keyes, Andrew G Rundle

Abstract read
In one paragraph

Article in Journal of exposure science & environmental epidemiology, 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

7 authors.

Nadav L SpragueDepartment of Epidemiology, Columbia Mailman School of Public Health, 722 W 168th St., New York, NY, 10032, USA. nls2171@cumc.columbia.edu.ORCID http://orcid.org/0000-0002-9698-9962
Stephen P UongDepartment of Epidemiology, Columbia Mailman School of Public Health, 722 W 168th St., New York, NY, 10032, USA.
Nora C KelsallDepartment of Epidemiology, Columbia Mailman School of Public Health, 722 W 168th St., New York, NY, 10032, USA.
Ahuva L JacobowitzDepartment of Epidemiology, Columbia Mailman School of Public Health, 722 W 168th St., New York, NY, 10032, USA.
James W QuinnDepartment of Epidemiology, Columbia Mailman School of Public Health, 722 W 168th St., New York, NY, 10032, USA.
Katherine M KeyesDepartment of Epidemiology, Columbia Mailman School of Public Health, 722 W 168th St., New York, NY, 10032, USA.
Andrew G RundleDepartment of Epidemiology, Columbia Mailman School of Public Health, 722 W 168th St., New York, NY, 10032, USA.

Funding

Temperature, shade, and adolescent psychopathology: understanding how place shapes healthR01MH128734 · NIMH · COLUMBIA UNIVERSITY HEALTH SCIENCES · PI KEYES, KATHERINE M., RUNDLE, ANDREW G · 2021 to 2025
$3.4M
NIMH NIH HHS R01 MH128734
6 · The paper itself

Abstract

backgroundLower socioeconomic (SES) communities are more likely to be situated in urban heat islands and have higher heat exposures than their higher SES counterparts, and this inequality is expected to intensify due to climate change.

objectivesTo examine the relationship between surface temperatures and SES in New York City (NYC) by employing a novel analytical approach. Through incorporating modifiable features, this study aims to identify potential locations where mitigation interventions can be implemented to reduce heat disparities associated with SES.

methodsUsing the 2013-2017 American Community Survey, U.S Landsat-8 Analysis Ready Data surface temperatures (measured on 8/12/2016), and the NYC Land Cover Dataset at the census tract level (2098 tracts), this study examines the association between two components of tract-level SES (percentage of individuals living below the poverty line and the percentage of individuals without a high school degree) and summer day surface temperature in NYC. First, we examine this association with an unrestricted NYC linear regression, examining the city-wide association between the two SES facets and summer surface temperature, with additional models adjusting for altitude, shoreline, and nature-cover. Then, we assess geographic effect measure modification by employing the same models to three supplemental regression model strategies (borough-restricted and community district-restricted linear regressions, and geographically weighted regression (GWR)) that examined associations within smaller intra-city areas.

resultsAll regression strategies identified areas where lower neighborhood SES composition is associated with higher summer day surface temperatures. The unrestricted NYC regressions revealed widespread disparities, while the borough-restricted and community district-restricted regressions identified specific political boundaries within which these disparities existed. The GWR, addressing spatial autocorrelation, identified significant socioeconomic heat disparities in locations such as northwest Bronx, central Brooklyn, and uptown Manhattan. These findings underscore the need for targeted policies and community interventions, including equitable urban planning and cooling strategies, to mitigate heat exposure in vulnerable neighborhoods. IMPACT STATEMENT: This study redefines previous research on urban socioeconomic disparities in heat exposure by investigating both modifiable (nature cover) and non-modifiable (altitude and shoreline) built environment factors affecting local temperatures at the census tract level in New York City. Through a novel analytical approach, the research aims to highlight intervention opportunities to mitigate heat disparities related to socioeconomic status. By examining the association between surface temperatures and socioeconomic status, as well as investigating different geographic and governmental scales, this study offers actionable insights for policymakers and community members to address heat exposure inequalities effectively across different administrative boundaries. The objective is to pinpoint potential sites for reducing socioeconomic heat exposure disparities at various geographic and political levels.

Indexed as

Hot TemperatureClimate ChangeHumansNew York CityResidence CharacteristicsSeasonsSocioeconomic FactorsClimate change mitigationEducationEnvironmental justiceExtreme heatPovertySummer day surface temperatures

Identifiers

PMID39179752
PMCPMC12414138

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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.