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Testing for fertility stalls in demographic and health surveys

Overview of attention for article published in Population Health Metrics, December 2011
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About this Attention Score

  • Above-average Attention Score compared to outputs of the same age (61st percentile)

Mentioned by

3 tweeters


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Readers on

21 Mendeley
Testing for fertility stalls in demographic and health surveys
Published in
Population Health Metrics, December 2011
DOI 10.1186/1478-7954-9-59
Pubmed ID

Michel L Garenne


This study compares two methods for testing fertility trends and fertility stalls using Demographic and Health Surveys data. The first method is based on linear regression and uses the equivalence of period and cohort estimates with the same cumulative fertility at age 40, the same number of births, and the same distribution of women by parity. The second method is based on logistic regression. It assumes that the age pattern of fertility is constant over short periods of time. Both methods were applied to fertility trends in several African countries (Ghana, Kenya, Madagascar, Nigeria, Rwanda, Senegal, Tanzania, and Zambia). The two methods were found to predict similar values of cumulative fertility, to produce consistent slopes, to document fertility trends the same way, and to characterize fertility stalls with similar statistical evidence. They can also be used to refute apparent fertility stalls obtained when comparing two point estimates from two successive surveys.

Twitter Demographics

The data shown below were collected from the profiles of 3 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 21 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
United States 2 10%
Rwanda 1 5%
Unknown 18 86%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 5 24%
Researcher 3 14%
Student > Master 3 14%
Professor 2 10%
Unspecified 2 10%
Other 6 29%
Readers by discipline Count As %
Social Sciences 6 29%
Arts and Humanities 3 14%
Medicine and Dentistry 3 14%
Nursing and Health Professions 2 10%
Agricultural and Biological Sciences 2 10%
Other 5 24%

Attention Score in Context

This research output has an Altmetric Attention Score of 2. 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 2015.
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Outputs from Population Health Metrics
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Outputs of similar age
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Outputs of similar age from Population Health Metrics
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Altmetric has tracked 6,650,505 research outputs across all sources so far. This one has received more attention than most of these and is in the 56th percentile.
So far Altmetric has tracked 189 research outputs from this source. They typically receive more attention than average, with a mean Attention Score of 9.8. This one is in the 35th percentile – i.e., 35% 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 241,053 tracked outputs that were published within six weeks on either side of this one in any source. This one has gotten more attention than average, scoring higher than 61% of its contemporaries.
We're also able to compare this research output to 5 others from the same source and published within six weeks on either side of this one.