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Structural Equation Modeling of the Effects of Family, Preschool, and Stunting on the Cognitive Development of School Children

Overview of attention for article published in Frontiers in Nutrition, May 2017
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Title
Structural Equation Modeling of the Effects of Family, Preschool, and Stunting on the Cognitive Development of School Children
Published in
Frontiers in Nutrition, May 2017
DOI 10.3389/fnut.2017.00017
Pubmed ID
Authors

Oluwakemi Rachel Ajayi, Glenda Beverley Matthews, Myra Taylor, Jane Dene Kvalsvig, Leslie Davidson, Shuaib Kauchali, Claude Mellins

Abstract

A recent study based on a sample of 1,580 children from five adjacent geographical locations in KwaZulu-Natal, South Africa, was carried out to examine the association of nutrition, family influence, preschool education, and disadvantages in geographical location with the cognitive development of school children. Data were collected on the children from 2009 to 2011 for this developmental study and included cognitive scores and information on the health and nutrition of the children. The current study analyzed the association of demographic variables (geographical location (site)), child variables (sex, preschool education and socioeconomic status), parental level of education (maternal and paternal), child's health (HIV status and hemoglobin level) and anthropometric measures of nutritional status (height-for-age) with children's cognitive outcomes. The hypothesis is that the nutritional status of children is a pathway through which the indirect effects of the variables of interest exert influence on their cognitive outcomes. Factor analysis based on principal components was used to create a variable based on the cognitive measures, correlations were used to examine the bivariate association between the variables of interest in the preliminary analysis and a path analysis was constructed, which was used for the disaggregation of the direct and indirect effects of the predictors for each cognitive test in a structural equation model. The results revealed that nutritional status directly predicts cognitive test scores and is a path through which other variables indirectly influence children's cognitive outcome and development.

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X Demographics

The data shown below were collected from the profiles of 4 X users who shared this research output. Click here to find out more about how the information was compiled.
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Mendeley readers

Mendeley readers

The data shown below were compiled from readership statistics for 123 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 123 100%

Demographic breakdown

Readers by professional status Count As %
Student > Bachelor 15 12%
Researcher 11 9%
Student > Master 9 7%
Lecturer 9 7%
Student > Ph. D. Student 8 7%
Other 23 19%
Unknown 48 39%
Readers by discipline Count As %
Nursing and Health Professions 23 19%
Medicine and Dentistry 13 11%
Social Sciences 6 5%
Psychology 6 5%
Agricultural and Biological Sciences 5 4%
Other 23 19%
Unknown 47 38%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 3. 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 11 August 2017.
All research outputs
#13,477,666
of 22,971,207 outputs
Outputs from Frontiers in Nutrition
#1,783
of 4,611 outputs
Outputs of similar age
#157,207
of 309,986 outputs
Outputs of similar age from Frontiers in Nutrition
#13
of 19 outputs
Altmetric has tracked 22,971,207 research outputs across all sources so far. This one is in the 41st percentile – i.e., 41% of other outputs scored the same or lower than it.
So far Altmetric has tracked 4,611 research outputs from this source. They typically receive a lot more attention than average, with a mean Attention Score of 13.8. This one has gotten more attention than average, scoring higher than 60% 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 309,986 tracked outputs that were published within six weeks on either side of this one in any source. This one is in the 48th percentile – i.e., 48% of its contemporaries scored the same or lower than it.
We're also able to compare this research output to 19 others from the same source and published within six weeks on either side of this one. This one is in the 31st percentile – i.e., 31% of its contemporaries scored the same or lower than it.