4.1 Article

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

Journal

SPRINGERPLUS
Volume 4, Issue -, Pages -

Publisher

SPRINGER INTERNATIONAL PUBLISHING AG
DOI: 10.1186/s40064-015-0916-8

Keywords

Body fat profile; Predictors; Overweight and obesity; Metabolic disease risk; MicroRNA; Dietary practices; Physical activity; Taste perception; Women

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Background: 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. Methods/Design: A cross-sectional design to investigate 675 NZ European, Maori, 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. Discussion: 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.

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