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Genetic epidemiology of cardiometabolic risk factors and their clustering patterns in Mexican American children and adolescents: the SAFARI Study

Overview of attention for article published in Human Genetics, June 2013
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About this Attention Score

  • In the top 5% of all research outputs scored by Altmetric
  • High Attention Score compared to outputs of the same age (96th percentile)
  • High Attention Score compared to outputs of the same age and source (94th percentile)

Mentioned by

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6 news outlets
facebook
1 Facebook page

Citations

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30 Dimensions

Readers on

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91 Mendeley
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Title
Genetic epidemiology of cardiometabolic risk factors and their clustering patterns in Mexican American children and adolescents: the SAFARI Study
Published in
Human Genetics, June 2013
DOI 10.1007/s00439-013-1315-2
Pubmed ID
Authors

Sharon P. Fowler, Sobha Puppala, Rector Arya, Geetha Chittoor, Vidya S. Farook, Jennifer Schneider, Roy G. Resendez, Ram Prasad Upadhayay, Jane VandeBerg, Kelly J. Hunt, Benjamin Bradshaw, Eugenio Cersosimo, John L. VandeBerg, Laura Almasy, Joanne E. Curran, Anthony G. Comuzzie, Donna M. Lehman, Christopher P. Jenkinson, Jane L. Lynch, Ralph A. DeFronzo, John Blangero, Daniel E. Hale, Ravindranath Duggirala

Abstract

Pediatric metabolic syndrome (MS) and its cardiometabolic components (MSCs) have become increasingly prevalent, yet little is known about the genetics underlying MS risk in children. We examined the prevalence and genetics of MS-related traits among 670 non-diabetic Mexican American (MA) children and adolescents, aged 6-17 years (49 % female), who were participants in the San Antonio Family Assessment of Metabolic Risk Indicators in Youth study. These children are offspring or biological relatives of adult participants from three well-established Mexican American family studies in San Antonio, TX, at increased risk of type 2 diabetes. MS was defined as ≥3 abnormalities among 6 MSC measures: waist circumference, systolic and/or diastolic blood pressure, fasting insulin, triglycerides, HDL-cholesterol, and fasting and/or 2-h OGTT glucose. Genetic analyses of MS, number of MSCs (MSC-N), MS factors, and bivariate MS traits were performed. Overweight/obesity (53 %), pre-diabetes (13 %), acanthosis nigricans (33 %), and MS (19 %) were strikingly prevalent, as were MS components, including abdominal adiposity (32 %) and low HDL-cholesterol (32 %). Factor analysis of MS traits yielded three constructs: adipo-insulin-lipid, blood pressure, and glucose factors, and their factor scores were highly heritable. MS itself exhibited 68 % heritability. MSC-N showed strong positive genetic correlations with obesity, insulin resistance, inflammation, and acanthosis nigricans, and negative genetic correlation with physical fitness. MS trait pairs exhibited strong genetic and/or environmental correlations. These findings highlight the complex genetic architecture of MS/MSCs in MA children, and underscore the need for early screening and intervention to prevent chronic sequelae in this vulnerable pediatric population.

Mendeley readers

Mendeley readers

The data shown below were compiled from readership statistics for 91 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
United States 2 2%
United Kingdom 1 1%
New Zealand 1 1%
Canada 1 1%
Unknown 86 95%

Demographic breakdown

Readers by professional status Count As %
Student > Master 12 13%
Researcher 10 11%
Student > Doctoral Student 9 10%
Student > Ph. D. Student 8 9%
Student > Bachelor 7 8%
Other 23 25%
Unknown 22 24%
Readers by discipline Count As %
Medicine and Dentistry 25 27%
Nursing and Health Professions 14 15%
Biochemistry, Genetics and Molecular Biology 6 7%
Social Sciences 4 4%
Sports and Recreations 4 4%
Other 10 11%
Unknown 28 31%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 41. 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 06 August 2013.
All research outputs
#851,602
of 22,714,025 outputs
Outputs from Human Genetics
#68
of 2,950 outputs
Outputs of similar age
#7,205
of 197,564 outputs
Outputs of similar age from Human Genetics
#1
of 17 outputs
Altmetric has tracked 22,714,025 research outputs across all sources so far. Compared to these this one has done particularly well and is in the 96th percentile: it's in the top 5% of all research outputs ever tracked by Altmetric.
So far Altmetric has tracked 2,950 research outputs from this source. They typically receive a little more attention than average, with a mean Attention Score of 6.2. This one has done particularly well, scoring higher than 97% 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 197,564 tracked outputs that were published within six weeks on either side of this one in any source. This one has done particularly well, scoring higher than 96% of its contemporaries.
We're also able to compare this research output to 17 others from the same source and published within six weeks on either side of this one. This one has done particularly well, scoring higher than 94% of its contemporaries.