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Predictors and risks of body fat profiles in young New Zealand European, Māori and Pacific women: study protocol for the women’s EXPLORE study

Overview of attention for article published in SpringerPlus, March 2015
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Title
Predictors and risks of body fat profiles in young New Zealand European, Māori and Pacific women: study protocol for the women’s EXPLORE study
Published in
SpringerPlus, March 2015
DOI 10.1186/s40064-015-0916-8
Pubmed ID
Authors

Rozanne Kruger, Sarah P Shultz, Sarah A McNaughton, Aaron P Russell, Ridvan T Firestone, Lily George, Kathryn L Beck, Cathryn A Conlon, Pamela R von Hurst, Bernhard Breier, Shakeela N Jayasinghe, Wendy J O’Brien, Beatrix Jones, Welma Stonehouse

Abstract

Body mass index (BMI) (kg/m(2)) is used internationally to assess body mass or adiposity. However, BMI does not discriminate body fat content or distribution and may vary among ethnicities. Many women with normal BMI are considered healthy, but may have an unidentified "hidden fat" profile associated with higher metabolic disease risk. If only BMI is used to indicate healthy body size, it may fail to predict underlying risks of diseases of lifestyle among population subgroups with normal BMI and different adiposity levels or distributions. Higher body fat levels are often attributed to excessive dietary intake and/or inadequate physical activity. These environmental influences regulate genes and proteins that alter energy expenditure/storage. Micro ribonucleic acid (miRNAs) can influence these genes and proteins, are sensitive to diet and exercise and may influence the varied metabolic responses observed between individuals. The study aims are to investigate associations between different body fat profiles and metabolic disease risk; dietary and physical activity patterns as predictors of body fat profiles; and whether these risk factors are associated with the expression of microRNAs related to energy expenditure or fat storage in young New Zealand women. Given the rising prevalence of obesity globally, this research will address a unique gap of knowledge in obesity research. A cross-sectional design to investigate 675 NZ European, Māori, and Pacific women aged 16-45 years. Women are classified into three main body fat profiles (n = 225 per ethnicity; n = 75 per body fat profile): 1) normal BMI, normal body fat percentage (BF%); 2) normal BMI, high BF%; 3) high BMI, high BF%. Regional body composition, biomarkers of metabolic disease risk (i.e. fasting insulin, glucose, HbA1c, lipids), inflammation (i.e. IL-6, TNF-alpha, hs-CRP), associations between lifestyle factors (i.e. dietary intake, physical activity, taste perceptions) and microRNA expression will be investigated. This research targets post-menarcheal, premenopausal women, potentially exhibiting lifestyle behaviours resulting in excess body fat affecting metabolic health. These behaviours may be characterised by specific patterns of microRNA expression that will be explored in terms of tailored solutions specific to body fat profile groups and ethnicities. ACTRN12613000714785.

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Mendeley readers

Mendeley readers

The data shown below were compiled from readership statistics for 75 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 75 100%

Demographic breakdown

Readers by professional status Count As %
Student > Bachelor 12 16%
Student > Master 11 15%
Student > Postgraduate 7 9%
Researcher 5 7%
Student > Ph. D. Student 5 7%
Other 11 15%
Unknown 24 32%
Readers by discipline Count As %
Medicine and Dentistry 16 21%
Nursing and Health Professions 10 13%
Agricultural and Biological Sciences 9 12%
Sports and Recreations 5 7%
Biochemistry, Genetics and Molecular Biology 3 4%
Other 7 9%
Unknown 25 33%
Attention Score in Context

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 01 April 2015.
All research outputs
#14,805,023
of 22,794,367 outputs
Outputs from SpringerPlus
#835
of 1,851 outputs
Outputs of similar age
#147,210
of 261,657 outputs
Outputs of similar age from SpringerPlus
#30
of 64 outputs
Altmetric has tracked 22,794,367 research outputs across all sources so far. This one is in the 32nd percentile – i.e., 32% of other outputs scored the same or lower than it.
So far Altmetric has tracked 1,851 research outputs from this source. They typically receive a little more attention than average, with a mean Attention Score of 5.7. This one is in the 49th percentile – i.e., 49% 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 261,657 tracked outputs that were published within six weeks on either side of this one in any source. This one is in the 40th percentile – i.e., 40% of its contemporaries scored the same or lower than it.
We're also able to compare this research output to 64 others from the same source and published within six weeks on either side of this one. This one is in the 40th percentile – i.e., 40% of its contemporaries scored the same or lower than it.