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Decomposing Indigenous life expectancy gap by risk factors: a life table analysis

Overview of attention for article published in Population Health Metrics, January 2013
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About this Attention Score

  • In the top 5% of all research outputs scored by Altmetric
  • Among the highest-scoring outputs from this source (#16 of 359)
  • High Attention Score compared to outputs of the same age (96th percentile)

Mentioned by

news
3 news outlets
policy
2 policy sources
twitter
11 tweeters
facebook
1 Facebook page

Citations

dimensions_citation
29 Dimensions

Readers on

mendeley
65 Mendeley
citeulike
2 CiteULike
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Title
Decomposing Indigenous life expectancy gap by risk factors: a life table analysis
Published in
Population Health Metrics, January 2013
DOI 10.1186/1478-7954-11-1
Pubmed ID
Authors

Yuejen Zhao, Jo Wright, Stephen Begg, Steven Guthridge

Abstract

The estimated gap in life expectancy (LE) between Indigenous and non-Indigenous Australians was 12 years for men and 10 years for women, whereas the Northern Territory Indigenous LE gap was at least 50% greater than the national figures. This study aims to explain the Indigenous LE gap by common modifiable risk factors.

Twitter Demographics

The data shown below were collected from the profiles of 11 tweeters 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 65 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Australia 4 6%
Spain 1 2%
Unknown 60 92%

Demographic breakdown

Readers by professional status Count As %
Student > Master 10 15%
Researcher 9 14%
Student > Bachelor 9 14%
Student > Ph. D. Student 7 11%
Other 4 6%
Other 11 17%
Unknown 15 23%
Readers by discipline Count As %
Medicine and Dentistry 20 31%
Social Sciences 7 11%
Nursing and Health Professions 5 8%
Psychology 4 6%
Agricultural and Biological Sciences 3 5%
Other 9 14%
Unknown 17 26%

Attention Score in Context

This research output has an Altmetric Attention Score of 38. 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 19 March 2020.
All research outputs
#644,148
of 17,009,769 outputs
Outputs from Population Health Metrics
#16
of 359 outputs
Outputs of similar age
#7,915
of 254,166 outputs
Outputs of similar age from Population Health Metrics
#1
of 1 outputs
Altmetric has tracked 17,009,769 research outputs across all sources so far. Compared to these this one has done particularly well and is in the 96th percentile: it's in the top 5% of all research outputs ever tracked by Altmetric.
So far Altmetric has tracked 359 research outputs from this source. They typically receive a lot more attention than average, with a mean Attention Score of 11.9. This one has done particularly well, scoring higher than 95% 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 254,166 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 96% of its contemporaries.
We're also able to compare this research output to 1 others from the same source and published within six weeks on either side of this one. This one has scored higher than all of them