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Geostatistical modelling of the association between malaria and child growth in Africa

Overview of attention for article published in International Journal of Health Geographics, February 2018
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  • In the top 25% of all research outputs scored by Altmetric
  • Good Attention Score compared to outputs of the same age (78th percentile)
  • High Attention Score compared to outputs of the same age and source (85th percentile)

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16 X users
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1 Facebook page

Citations

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24 Dimensions

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131 Mendeley
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Title
Geostatistical modelling of the association between malaria and child growth in Africa
Published in
International Journal of Health Geographics, February 2018
DOI 10.1186/s12942-018-0127-y
Pubmed ID
Authors

Benjamin Amoah, Emanuele Giorgi, Daniel J. Heyes, Stef van Burren, Peter John Diggle

Abstract

Undernutrition among children under 5 years of age continues to be a public health challenge in many low- and middle-income countries and can lead to growth stunting. Infectious diseases may also affect child growth, however their actual impact on the latter can be difficult to quantify. In this paper, we analyse data from 20 Demographic and Health Surveys (DHS) conducted in 13 African countries to investigate the relationship between malaria and stunting. Our objective is to make inference on the association between malaria incidence during the first year of life and height-for-age Z-scores (HAZs). We develop a geostatistical model for HAZs as a function of both measured and unmeasured child-specific and spatial risk factors. We visualize stunting risk in each of the 20 analysed surveys by mapping the predictive probability that HAZ is below - 2. Finally, we carry out a meta-analysis by modelling the estimated effects of malaria incidence on HAZ from each DHS as a linear regression on national development indicators from the World Bank. A non-spatial univariate linear regression of HAZ on malaria incidence showed a negative association in 18 out of 20 surveys. However, after adjusting for spatial risk factors and controlling for confounding effects, we found a weaker association between HAZ and malaria, with a mix of positive and negative estimates, of which 3 out of 20 are significantly different from zero at the conventional 5% level. The meta-analysis showed that this variation in the estimated effect of malaria incidence on HAZ is significantly associated with the amount of arable land. Confounding effects on the association between malaria and stunting vary both by country and over time. Geostatistical analysis provides a useful framework that allows to account for unmeasured spatial confounders. Establishing whether the association between malaria and stunting is causal would require longitudinal follow-up data on individual children.

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X Demographics

The data shown below were collected from the profiles of 16 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 131 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Kenya 1 <1%
Unknown 130 99%

Demographic breakdown

Readers by professional status Count As %
Student > Master 18 14%
Researcher 14 11%
Student > Ph. D. Student 13 10%
Student > Bachelor 11 8%
Student > Doctoral Student 6 5%
Other 20 15%
Unknown 49 37%
Readers by discipline Count As %
Nursing and Health Professions 18 14%
Medicine and Dentistry 15 11%
Agricultural and Biological Sciences 9 7%
Social Sciences 7 5%
Immunology and Microbiology 5 4%
Other 24 18%
Unknown 53 40%
Attention Score in Context

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 18 May 2018.
All research outputs
#3,466,079
of 23,925,854 outputs
Outputs from International Journal of Health Geographics
#119
of 638 outputs
Outputs of similar age
#70,021
of 333,272 outputs
Outputs of similar age from International Journal of Health Geographics
#2
of 7 outputs
Altmetric has tracked 23,925,854 research outputs across all sources so far. Compared to these this one has done well and is in the 85th percentile: it's in the top 25% of all research outputs ever tracked by Altmetric.
So far Altmetric has tracked 638 research outputs from this source. They typically receive more attention than average, with a mean Attention Score of 9.5. This one has done well, scoring higher than 81% 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 333,272 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 78% of its contemporaries.
We're also able to compare this research output to 7 others from the same source and published within six weeks on either side of this one. This one has scored higher than 5 of them.