Journal Articles

Permanent URI for this collectionhttps://mro.massey.ac.nz/handle/10179/7915

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Author: search.filters.author.Jones BSubject: search.filters.subject.Science & Technology

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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
    (SpringerOpen, 1/12/2015) Kruger R; Shultz SP; McNaughton SA; Russell AP; Firestone RT; George L; Beck KL; Conlon CA; von Hurst PR; Breier B; Jayasinghe SN; O Brien WJ; Jones B; Stonehouse W
    Background: Body mass index (BMI) (kg/m2) 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, 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. 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. Trial registration: ACTRN12613000714785
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    Blood donation, being Asian, and a history of iron deficiency are stronger predictors of iron deficiency than dietary patterns in premenopausal women
    (Hindawi Publishing Corporation, 2014) Beck KL; Conlon CA; Kruger R; Heath A-LM; Matthys C; Coad J; Jones B; Stonehouse W
    This study investigated dietary patterns and nondietary determinants of suboptimal iron status (serum ferritin < 20 μg/L) in 375 premenopausal women. Using multiple logistic regression analysis, determinants were blood donation in the past year [OR: 6.00 (95% CI: 2.81, 12.82); P < 0.001], being Asian [OR: 4.84 (95% CI: 2.29, 10.20); P < 0.001], previous iron deficiency [OR: 2.19 (95% CI: 1.16, 4.13); P = 0.016], a "milk and yoghurt" dietary pattern [one SD higher score, OR: 1.44 (95% CI: 1.08, 1.93); P = 0.012], and longer duration of menstruation [days, OR: 1.38 (95% CI: 1.12, 1.68); P = 0.002]. A one SD change in the factor score above the mean for a "meat and vegetable" dietary pattern reduced the odds of suboptimal iron status by 79.0% [OR: 0.21 (95% CI: 0.08, 0.50); P = 0.001] in women with children. Blood donation, Asian ethnicity, and previous iron deficiency were the strongest predictors, substantially increasing the odds of suboptimal iron status. Following a "milk and yoghurt" dietary pattern and a longer duration of menstruation moderately increased the odds of suboptimal iron status, while a "meat and vegetable" dietary pattern reduced the odds of suboptimal iron status in women with children.