↓ Skip to main content

Geographic and Racial Variation in Premature Mortality in the U.S.: Analyzing the Disparities

Overview of attention for article published in PLOS ONE, April 2012
Altmetric Badge

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 (94th percentile)
  • High Attention Score compared to outputs of the same age and source (91st percentile)

Mentioned by

policy
3 policy sources
twitter
15 X users
wikipedia
2 Wikipedia pages

Citations

dimensions_citation
86 Dimensions

Readers on

mendeley
99 Mendeley
You are seeing a free-to-access but limited selection of the activity Altmetric has collected about this research output. Click here to find out more.
Title
Geographic and Racial Variation in Premature Mortality in the U.S.: Analyzing the Disparities
Published in
PLOS ONE, April 2012
DOI 10.1371/journal.pone.0032930
Pubmed ID
Authors

Mark R. Cullen, Clint Cummins, Victor R. Fuchs

Abstract

Life expectancy at birth, estimated from United States period life tables, has been shown to vary systematically and widely by region and race. We use the same tables to estimate the probability of survival from birth to age 70 (S(70)), a measure of mortality more sensitive to disparities and more reliably calculated for small populations, to describe the variation and identify its sources in greater detail to assess the patterns of this variation. Examination of the unadjusted probability of S(70) for each US county with a sufficient population of whites and blacks reveals large geographic differences for each race-sex group. For example, white males born in the ten percent healthiest counties have a 77 percent probability of survival to age 70, but only a 61 percent chance if born in the ten percent least healthy counties. Similar geographical disparities face white women and blacks of each sex. Moreover, within each county, large differences in S(70) prevail between blacks and whites, on average 17 percentage points for men and 12 percentage points for women. In linear regressions for each race-sex group, nearly all of the geographic variation is accounted for by a common set of 22 socio-economic and environmental variables, selected for previously suspected impact on mortality; R(2) ranges from 0.86 for white males to 0.72 for black females. Analysis of black-white survival chances within each county reveals that the same variables account for most of the race gap in S(70) as well. When actual white male values for each explanatory variable are substituted for black in the black male prediction equation to assess the role explanatory variables play in the black-white survival difference, residual black-white differences at the county level shrink markedly to a mean of -2.4% (+/-2.4); for women the mean difference is -3.7% (+/-2.3).

X Demographics

X Demographics

The data shown below were collected from the profiles of 15 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 99 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Colombia 1 1%
United States 1 1%
Unknown 97 98%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 16 16%
Student > Master 15 15%
Researcher 14 14%
Student > Bachelor 7 7%
Professor 6 6%
Other 19 19%
Unknown 22 22%
Readers by discipline Count As %
Social Sciences 21 21%
Medicine and Dentistry 19 19%
Economics, Econometrics and Finance 7 7%
Nursing and Health Professions 5 5%
Environmental Science 4 4%
Other 13 13%
Unknown 30 30%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 23. 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 02 December 2023.
All research outputs
#1,584,949
of 24,916,485 outputs
Outputs from PLOS ONE
#19,782
of 216,019 outputs
Outputs of similar age
#8,667
of 166,485 outputs
Outputs of similar age from PLOS ONE
#316
of 3,746 outputs
Altmetric has tracked 24,916,485 research outputs across all sources so far. Compared to these this one has done particularly well and is in the 93rd percentile: it's in the top 10% of all research outputs ever tracked by Altmetric.
So far Altmetric has tracked 216,019 research outputs from this source. They typically receive a lot more attention than average, with a mean Attention Score of 15.7. This one has done particularly well, scoring higher than 90% 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 166,485 tracked outputs that were published within six weeks on either side of this one in any source. This one has done particularly well, scoring higher than 94% of its contemporaries.
We're also able to compare this research output to 3,746 others from the same source and published within six weeks on either side of this one. This one has done particularly well, scoring higher than 91% of its contemporaries.