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Infant mortality in South Africa - distribution, associations and policy implications, 2007: an ecological spatial analysis

Overview of attention for article published in International Journal of Health Geographics, November 2011
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About this Attention Score

  • In the top 25% of all research outputs scored by Altmetric
  • Good Attention Score compared to outputs of the same age (79th percentile)
  • Good Attention Score compared to outputs of the same age and source (66th percentile)

Mentioned by

policy
1 policy source
twitter
3 X users

Citations

dimensions_citation
27 Dimensions

Readers on

mendeley
146 Mendeley
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Title
Infant mortality in South Africa - distribution, associations and policy implications, 2007: an ecological spatial analysis
Published in
International Journal of Health Geographics, November 2011
DOI 10.1186/1476-072x-10-61
Pubmed ID
Authors

Benn KD Sartorius, Kurt Sartorius, Tobias F Chirwa, Sharon Fonn

Abstract

Many sub-Saharan countries are confronted with persistently high levels of infant mortality because of the impact of a range of biological and social determinants. In particular, infant mortality has increased in sub-Saharan Africa in recent decades due to the HIV/AIDS epidemic. The geographic distribution of health problems and their relationship to potential risk factors can be invaluable for cost effective intervention planning. The objective of this paper is to determine and map the spatial nature of infant mortality in South Africa at a sub district level in order to inform policy intervention. In particular, the paper identifies and maps high risk clusters of infant mortality, as well as examines the impact of a range of determinants on infant mortality. A Bayesian approach is used to quantify the spatial risk of infant mortality, as well as significant associations (given spatial correlation between neighbouring areas) between infant mortality and a range of determinants. The most attributable determinants in each sub-district are calculated based on a combination of prevalence and model risk factor coefficient estimates. This integrated small area approach can be adapted and applied in other high burden settings to assist intervention planning and targeting.

X Demographics

X Demographics

The data shown below were collected from the profiles of 3 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 146 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
United States 3 2%
South Africa 3 2%
United Kingdom 2 1%
Kenya 1 <1%
Unknown 137 94%

Demographic breakdown

Readers by professional status Count As %
Student > Master 34 23%
Researcher 18 12%
Student > Postgraduate 18 12%
Student > Bachelor 16 11%
Student > Ph. D. Student 8 5%
Other 22 15%
Unknown 30 21%
Readers by discipline Count As %
Medicine and Dentistry 34 23%
Social Sciences 23 16%
Nursing and Health Professions 12 8%
Biochemistry, Genetics and Molecular Biology 7 5%
Agricultural and Biological Sciences 5 3%
Other 28 19%
Unknown 37 25%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 6. 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 26 March 2018.
All research outputs
#5,447,195
of 25,374,917 outputs
Outputs from International Journal of Health Geographics
#184
of 654 outputs
Outputs of similar age
#42,055
of 243,921 outputs
Outputs of similar age from International Journal of Health Geographics
#4
of 12 outputs
Altmetric has tracked 25,374,917 research outputs across all sources so far. Compared to these this one has done well and is in the 75th percentile: it's in the top 25% of all research outputs ever tracked by Altmetric.
So far Altmetric has tracked 654 research outputs from this source. They typically receive more attention than average, with a mean Attention Score of 9.7. This one has gotten more attention than average, scoring higher than 70% 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 243,921 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 79% of its contemporaries.
We're also able to compare this research output to 12 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 66% of its contemporaries.