Evidence map›Paper›PMID 37382871›Full record

ArticleJournal of racial and ethnic health disparities2024

Using a Latent Variable Method to Develop a Composite, Multidimensional Measure of Structural Racism at the City Level.

Michael Siegel, Madeline Rieders, Hannah Rieders, Jinan Moumneh, Julia Asfour, Jinseo Oh, Seungjin Oh

Abstract read
In one paragraph

Article in Journal of racial and ethnic health disparities, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 7 papers.

0numbers the graph read from it
0cells of the map it votes in
7citing 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

7 citing papers in PubMed.

  1. Article
  2. Racism and racial disparities in firearm violence: A scoping review.American journal of community psychology · 2026
    Article
  3. Article
  4. Article
  5. Article
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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.

Michael SiegelDepartment of Public Health and Community Medicine, Tufts University School of Medicine, 636 Harrison Avenue, Boston, MA, 02111, USA. Mike.Siegel@tufts.edu.ORCID 0000-0002-2573-9616
Madeline RiedersDepartment of Public Health and Community Medicine, Tufts University School of Medicine, 636 Harrison Avenue, Boston, MA, 02111, USA.
Hannah RiedersDepartment of Public Health and Community Medicine, Tufts University School of Medicine, 636 Harrison Avenue, Boston, MA, 02111, USA.
Jinan MoumnehDepartment of Public Health and Community Medicine, Tufts University School of Medicine, 636 Harrison Avenue, Boston, MA, 02111, USA.
Julia AsfourDepartment of Public Health and Community Medicine, Tufts University School of Medicine, 636 Harrison Avenue, Boston, MA, 02111, USA.
Jinseo OhDepartment of Public Health and Community Medicine, Tufts University School of Medicine, 636 Harrison Avenue, Boston, MA, 02111, USA.
Seungjin OhDepartment of Public Health and Community Medicine, Tufts University School of Medicine, 636 Harrison Avenue, Boston, MA, 02111, USA.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

introductionAlthough structural racism is strongly related to racial health disparities, we are not aware of any composite, multidimensional measure of structural racism at the city level in the United States. However, many of the policies, programs, and institutions that create and maintain structural racism are located at the city level. To expand upon previous research, this paper uses a novel measure to measure structural racism at the city level for the non-Hispanic Black population.

methodsWe used confirmatory factor analysis to model the latent construct of structural racism for 776 U.S. cities. The model included six indicators across five dimensions: racial segregation, incarceration, educational attainment, employment, and economic status. We generated factor scores that weighted the indicators in order to produce the best model fit. The resulting factor scores represented the level of structural racism in each city. We demonstrated the utility of this measure by demonstrating its strong correlation with Black-White disparities in firearm homicide rates.

resultsThere were profound differences in the magnitude of structural racism across cities. There were also striking differences in the magnitude of the racial disparity in firearm homicide across cities. Structural racism was a significant predictor of the magnitude of these racial disparities in firearm homicide. Each one standard deviation increase in the structural racism factor score increased the firearm homicide rate ratio by a factor of approximately 1.2 (95% confidence interval, 1.1-1.3).

conclusionsThese new measures can be utilized by researchers to relate structural racism to racial health disparities at the city level.

Indexed as

Black or African AmericanCitiesHomicideEducational StatusFactor Analysis, StatisticalFirearmsHumansRacismSocial SegregationSystemic RacismUnited StatesAfrican AmericansEmpirical measuresRacial health disparitiesStructural racism

Identifiers

PMID37382871
PMCPMC11236873

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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.