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Neighborhood Disadvantage, Residential Segregation, and Beyond—Lessons for Studying Structural Racism and Health

Overview of attention for article published in Journal of Racial and Ethnic Health Disparities, June 2017
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About this Attention Score

  • In the top 25% of all research outputs scored by Altmetric
  • High Attention Score compared to outputs of the same age (86th percentile)
  • Above-average Attention Score compared to outputs of the same age and source (64th percentile)

Mentioned by

blogs
1 blog
twitter
12 X users

Citations

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130 Dimensions

Readers on

mendeley
214 Mendeley
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Title
Neighborhood Disadvantage, Residential Segregation, and Beyond—Lessons for Studying Structural Racism and Health
Published in
Journal of Racial and Ethnic Health Disparities, June 2017
DOI 10.1007/s40615-017-0378-5
Pubmed ID
Authors

Alicia R. Riley

Abstract

A recent surge of interest in identifying the health effects of structural racism has coincided with the ongoing attention to neighborhood effects in both epidemiology and sociology. Mindful of these currents in the literature, it makes sense that we are seeing an emergent tendency in health disparities research to operationalize structural racism as either neighborhood disadvantage or racial residential segregation. This review essay synthesizes findings on the relevance of neighborhood disadvantage and residential segregation to the study of structural racism and health. It then draws on recent literature to propose four lessons for moving beyond traditional neighborhood effects approaches in the study of structural racism and health. These lessons are (1) to shift the focus of research from census tracts to theoretically meaningful units of analysis, (2) to leverage historic and geographic variation in race relations, (3) to combine data from multiple sources, and (4) to challenge normative framing that aims to explain away racial health disparities without discussing racism or racial hierarchy. The author concludes that research on the health effects of structural racism should go beyond traditional neighborhood effects approaches if it is to guide intervention to reduce racial and ethnic health disparities.

X Demographics

X Demographics

The data shown below were collected from the profiles of 12 X users who shared this research output. Click here to find out more about how the information was compiled.
Mendeley readers

Mendeley readers

The data shown below were compiled from readership statistics for 214 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 214 100%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 57 27%
Student > Doctoral Student 31 14%
Researcher 21 10%
Student > Master 19 9%
Other 13 6%
Other 35 16%
Unknown 38 18%
Readers by discipline Count As %
Social Sciences 63 29%
Medicine and Dentistry 26 12%
Nursing and Health Professions 23 11%
Psychology 15 7%
Economics, Econometrics and Finance 4 2%
Other 22 10%
Unknown 61 29%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 15. This is our high-level measure of the quality and quantity of online attention that it has received. This Attention Score, as well as the ranking and number of research outputs shown below, was calculated when the research output was last mentioned on 01 June 2020.
All research outputs
#2,441,112
of 25,183,822 outputs
Outputs from Journal of Racial and Ethnic Health Disparities
#221
of 1,241 outputs
Outputs of similar age
#44,410
of 322,401 outputs
Outputs of similar age from Journal of Racial and Ethnic Health Disparities
#7
of 17 outputs
Altmetric has tracked 25,183,822 research outputs across all sources so far. Compared to these this one has done particularly well and is in the 90th percentile: it's in the top 10% of all research outputs ever tracked by Altmetric.
So far Altmetric has tracked 1,241 research outputs from this source. They typically receive a lot more attention than average, with a mean Attention Score of 19.9. This one has done well, scoring higher than 82% of its peers.
Older research outputs will score higher simply because they've had more time to accumulate mentions. To account for age we can compare this Altmetric Attention Score to the 322,401 tracked outputs that were published within six weeks on either side of this one in any source. This one has done well, scoring higher than 86% of its contemporaries.
We're also able to compare this research output to 17 others from the same source and published within six weeks on either side of this one. This one has gotten more attention than average, scoring higher than 64% of its contemporaries.