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Racial Segregation, Income Inequality, and Mortality in US Metropolitan Areas

Overview of attention for article published in Journal of Urban Health, February 2011
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Mentioned by

twitter
1 tweeter

Citations

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23 Dimensions

Readers on

mendeley
55 Mendeley
citeulike
1 CiteULike
Title
Racial Segregation, Income Inequality, and Mortality in US Metropolitan Areas
Published in
Journal of Urban Health, February 2011
DOI 10.1007/s11524-010-9524-7
Pubmed ID
Authors

Amani M. Nuru-Jeter, Thomas A. LaVeist

Abstract

Evidence of the association between income inequality and mortality has been mixed. Studies indicate that growing income inequalities reflect inequalities between, rather than within, racial groups. Racial segregation may play a role. We examine the role of racial segregation on the relationship between income inequality and mortality in a cross-section of US metropolitan areas. Metropolitan areas were included if they had a population of at least 100,000 and were at least 10% black (N = 107). Deaths for the time period 1991-1999 were used to calculate age-adjusted all-cause mortality rates for each metropolitan statistical area (MSA) using direct age-adjustment techniques. Multivariate least squares regression was used to examine associations for the total sample and for blacks and whites separately. Income inequality was associated with lower mortality rates among whites and higher mortality rates among blacks. There was a significant interaction between income inequality and racial segregation. A significant graded inverse income inequality/mortality association was found for MSAs with higher versus lower levels of black-white racial segregation. Effects were stronger among whites than among blacks. A positive income inequality/mortality association was found in MSAs with higher versus lower levels of Hispanic-white segregation. Uncertainty regarding the income inequality/mortality association found in previous studies may be related to the omission of important variables such as racial segregation that modify associations differently between groups. Research is needed to further elucidate the risk and protective effects of racial segregation across groups.

Twitter Demographics

The data shown below were collected from the profile of 1 tweeter who shared this research output. Click here to find out more about how the information was compiled.

Mendeley readers

The data shown below were compiled from readership statistics for 55 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
United States 4 7%
India 1 2%
Unknown 50 91%

Demographic breakdown

Readers by professional status Count As %
Student > Master 12 22%
Student > Ph. D. Student 11 20%
Student > Bachelor 7 13%
Researcher 5 9%
Professor > Associate Professor 5 9%
Other 15 27%
Readers by discipline Count As %
Social Sciences 31 56%
Medicine and Dentistry 5 9%
Psychology 4 7%
Agricultural and Biological Sciences 3 5%
Economics, Econometrics and Finance 2 4%
Other 10 18%

Attention Score in Context

This research output has an Altmetric Attention Score of 1. 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 05 December 2014.
All research outputs
#6,773,145
of 11,042,410 outputs
Outputs from Journal of Urban Health
#688
of 840 outputs
Outputs of similar age
#127,860
of 250,130 outputs
Outputs of similar age from Journal of Urban Health
#8
of 15 outputs
Altmetric has tracked 11,042,410 research outputs across all sources so far. This one is in the 23rd percentile – i.e., 23% of other outputs scored the same or lower than it.
So far Altmetric has tracked 840 research outputs from this source. They typically receive more attention than average, with a mean Attention Score of 9.5. This one is in the 10th percentile – i.e., 10% of its peers scored the same or lower than it.
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 250,130 tracked outputs that were published within six weeks on either side of this one in any source. This one is in the 37th percentile – i.e., 37% of its contemporaries scored the same or lower than it.
We're also able to compare this research output to 15 others from the same source and published within six weeks on either side of this one. This one is in the 33rd percentile – i.e., 33% of its contemporaries scored the same or lower than it.