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Population risk factors for late-stage presentation of cervical cancer in sub-Saharan Africa

Overview of attention for article published in Cancer Epidemiology, April 2018
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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 (82nd percentile)
  • Good Attention Score compared to outputs of the same age and source (77th percentile)

Mentioned by

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14 tweeters

Citations

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2 Dimensions

Readers on

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55 Mendeley
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Title
Population risk factors for late-stage presentation of cervical cancer in sub-Saharan Africa
Published in
Cancer Epidemiology, April 2018
DOI 10.1016/j.canep.2018.01.014
Pubmed ID
Authors

Tessa S. Stewart, Jennifer Moodley, Fiona M. Walter

Abstract

Cervical cancer is the most prevalent malignancy in sub-Saharan Africa (SSA) with many women only seeking professional help when they are experiencing symptoms, implying late-stage malignancy and higher mortality rates. This ecological study assesses population-level exposures of SSA women to the numerous risk factors for HPV infection and cervical cancer, against late-stage presentation of cervical cancer. A literature review revealed the relevant risk factors in SSA. Open-access databases were mined for variables closely representing each risk factor. A proxy for late-stage presentation was used (ratio of incidence-to-mortality, IMR), and gathered from IARC's GLOBOCAN 2012 database. Variables showing significant correlation to the IMR were used in stepwise multiple regression to quantify their effect on the IMR. Countries with high cervical cancer mortality rates relative to their incidence have an IMR nearer one, suggesting a larger proportion of late-stage presentation. Western Africa had the lowest median IMR (1.463), followed by Eastern Africa (IMR = 1.595) and Central Africa (IMR = 1.675), whereas Southern Africa had the highest median IMR (1.761). Variables selected for the final model explain 65.2% of changes seen in the IMR. Significant predictors of IMR were GDP (coefficient = 2.189 × 10-6, p = 0.064), HIV infection (-1.936 × 10-3, p = 0.095), not using a condom (-1.347 × 10-3, p = 0.013), high parity (-1.744 × 10-2, p = 0.008), and no formal education (-1.311 × 10-3, p < 0.001). Using an IMR enables identification of factors predicting late-stage cervical cancer in SSA including: GDP, HIV infection, not using a condom, high parity and no formal education.

Twitter Demographics

The data shown below were collected from the profiles of 14 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 55 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 55 100%

Demographic breakdown

Readers by professional status Count As %
Unspecified 18 33%
Student > Bachelor 7 13%
Researcher 6 11%
Student > Master 6 11%
Lecturer 4 7%
Other 14 25%
Readers by discipline Count As %
Unspecified 20 36%
Medicine and Dentistry 20 36%
Nursing and Health Professions 8 15%
Social Sciences 3 5%
Computer Science 2 4%
Other 2 4%

Attention Score in Context

This research output has an Altmetric Attention Score of 10. 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 14 April 2018.
All research outputs
#1,588,901
of 13,458,433 outputs
Outputs from Cancer Epidemiology
#93
of 648 outputs
Outputs of similar age
#60,022
of 348,623 outputs
Outputs of similar age from Cancer Epidemiology
#2
of 9 outputs
Altmetric has tracked 13,458,433 research outputs across all sources so far. Compared to these this one has done well and is in the 88th percentile: it's in the top 25% of all research outputs ever tracked by Altmetric.
So far Altmetric has tracked 648 research outputs from this source. They typically receive more attention than average, with a mean Attention Score of 9.6. This one has done well, scoring higher than 85% 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 348,623 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 82% of its contemporaries.
We're also able to compare this research output to 9 others from the same source and published within six weeks on either side of this one. This one has scored higher than 7 of them.