Evidence map›Paper›PMID 34045834›Full record

ArticleEthnicity & disease2021

Political Economies of Acute Childhood Illnesses: Measuring Structural Racism as Mesolevel Mortgage Market Risks.

Alyasah Ali Sewell

Abstract read
In one paragraph

Article in Ethnicity & disease, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 11 papers.

0numbers the graph read from it
0cells of the map it votes in
11citing 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

11 citing papers in PubMed.

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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

1 author.

Alyasah Ali SewellEmory University, Department of Sociology, Atlanta, GA.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Objectives: Health studies of structural racism/discrimination have been animated through the deployment of neighborhood effects frameworks that engage institutionalist concerns about sociopolitical resources and mobility structures. This study highlights the acute illness risks of place-based inequalities and neighborhood-varying race-based inequalities by focusing on access to and the regulation of mortgage markets. Design: By merging neighborhood data on lending processes from the Home Mortgage Disclosure Act with individual health from the Project on Human Development in Chicago Neighborhoods, this article evaluates the acute childhood illness risks of four mutually inclusive, political economies using multilevel generalized linear models. Setting: Chicago, IL, USA. Participants: Youth aged 0 to 17 years. Main Outcome Measures: The prevalence of 11 acute illnesses (cold/flu, sinus trouble, sore throat/tonsils, headache, upset stomach, bronchitis, skin infection, pneumonia, urinary tract infections, fungal disease, mononucleosis) and the past-year frequencies of 6 acute illnesses (cold/flu, sinus trouble, sore throat/tonsils, headache, upset stomach, bronchitis) are evaluated. Methods: Multilevel logistic regression. Results: The most theoretically consistent predictor of illness is a measure identifying neighborhoods with above-city-median levels of racial disparities in the regulation of loans - a mesolevel measure of structural racism. In areas with high levels of minority-White differences in less-regulated credit, youth are more likely to have a range of acute illnesses and experience them at more frequent intervals in the past year. Conclusions: This article highlights the substantive and methodological importance of focusing on multidimensional representations of institutionalized political economic inequalities circumscribed and traversed by the power relations established by institutions and the state.

Indexed as

RacismAdolescentChicagoChildHumansMinority GroupsResidence CharacteristicsChicagoChild HealthHealth DisparitiesHuman DevelopmentNeighborhood EffectsRacismSocial EpidemiologyUrban Health

Identifiers

PMID34045834
PMCPMC8143851

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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.