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Body adiposity indicators and cardiometabolic risk: Cross-sectional analysis in participants from the PREDIMED-Plus trial

Overview of attention for article published in Clinical Nutrition, July 2018
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  • Good Attention Score compared to outputs of the same age (67th percentile)
  • Above-average Attention Score compared to outputs of the same age and source (56th percentile)

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8 X users

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Title
Body adiposity indicators and cardiometabolic risk: Cross-sectional analysis in participants from the PREDIMED-Plus trial
Published in
Clinical Nutrition, July 2018
DOI 10.1016/j.clnu.2018.07.005
Pubmed ID
Authors

Jadwiga Konieczna, Itziar Abete, Aina M. Galmés, Nancy Babio, Antoni Colom, Maria Angeles Zulet, Ramón Estruch, Josep Vidal, Estefanía Toledo, Andrés Díaz-López, Miguel Fiol, Rosa Casas, Josep Vera, Pilar Buil-Cosiales, Vicente Martín, Albert Goday, Jordi Salas-Salvadó, J. Alfredo Martínez, Dora Romaguera, PREDIMED-Plus Investigators

Abstract

Excess adiposity is associated with poor cardiometabolic (CM) health. To date, several techniques and indicators have been developed to determine adiposity. We aimed to compare the ability of traditional anthropometric, as well as standard and novel DXA-derived parameters related to overall and regional adiposity, to evaluate CM risk. Using the cross-sectional design in the context of the PREDIMED-Plus trial, 1207 Caucasian senior men and women with overweight/obesity and metabolic syndrome (MetS) were assessed. At baseline, anthropometry- and DXA-measured parameters of central, visceral, peripheral and central-to-peripheral adiposity together with comprehensive set of CM risk factors were obtained. Partial correlations and areas under the ROC curve (AUC) were estimated to compare each adiposity measure with CM risk parameters, separately for men and women, and in the overall sample. DXA-derived indicators, other than percentage of total body fat, showed stronger correlations (rho -0.172 to 0.206, p < 0.001) with CM risk than anthropometric indicators, after controlling for age, diabetes and medication use. In both sexes, DXA-derived visceral adipose tissue measures (VAT, VAT/Total fat, visceral-to-subcutaneous fat) together with lipodystrophy indicators (Trunk/Legs fat and Android/Gynoid fat) were strongly and positively correlated (p < 0.001) with glycated hemoglobin (HbA1c), the triglyceride and glucose index (TyG), triglycerides (TG), the ratio TG/HDL-cholesterol (TG/HDL-C), and were inversely related to HDL-C levels (p < 0.001). Furthermore, in AUC analyses for both sexes, VAT/Total fat showed the highest predictive ability for abnormal HbA1c levels (AUC = 0.629), VAT for TyG (AUC = 0.626), both lipodystrophy indicators for TG (AUCs = 0.556), and Trunk/Legs fat for HDL-C (AUC = 0.556) and TG/HDL-C (AUC = 0.581). DXA regional adiposity measures offer advantages beyond traditional anthropometric and DXA overall adiposity indicators for CM risk assessment in senior overweight/obese subjects with MetS. In particular, in both sexes, visceral adiposity better stratifies individuals at risk for glucose abnormalities, and indicators of lipodystrophy better predict markers of dyslipidemia.

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X Demographics

The data shown below were collected from the profiles of 8 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 120 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 120 100%

Demographic breakdown

Readers by professional status Count As %
Student > Bachelor 19 16%
Student > Master 18 15%
Researcher 17 14%
Student > Postgraduate 10 8%
Student > Ph. D. Student 8 7%
Other 17 14%
Unknown 31 26%
Readers by discipline Count As %
Medicine and Dentistry 23 19%
Nursing and Health Professions 22 18%
Biochemistry, Genetics and Molecular Biology 5 4%
Sports and Recreations 5 4%
Business, Management and Accounting 3 3%
Other 17 14%
Unknown 45 38%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 5. 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 03 September 2019.
All research outputs
#6,850,695
of 25,385,509 outputs
Outputs from Clinical Nutrition
#1,521
of 3,675 outputs
Outputs of similar age
#109,144
of 339,438 outputs
Outputs of similar age from Clinical Nutrition
#40
of 91 outputs
Altmetric has tracked 25,385,509 research outputs across all sources so far. This one has received more attention than most of these and is in the 72nd percentile.
So far Altmetric has tracked 3,675 research outputs from this source. They typically receive a lot more attention than average, with a mean Attention Score of 18.2. This one has gotten more attention than average, scoring higher than 58% 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 339,438 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 67% of its contemporaries.
We're also able to compare this research output to 91 others from the same source and published within six weeks on either side of this one. This one has gotten more attention than average, scoring higher than 56% of its contemporaries.