ORCID Profile
0000-0002-2699-4352
Current Organisation
Deakin University
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Publisher: MDPI AG
Date: 13-06-2018
DOI: 10.3390/NU10060758
Publisher: Springer Science and Business Media LLC
Date: 20-07-2023
DOI: 10.1007/S11764-023-01428-8
Abstract: To identify dietary patterns derived from protein, polyunsaturated fatty acids (PUFA) and vitamin D and examine associations with malnutrition, low muscle mass and sarcopenia in cancer survivors. This cross-sectional study included cancer survivors ( n = 2415) from the UK Biobank (age [mean ± SD] 59.7 ± 7.1 years 60.7% female). The Oxford WebQ 24-h dietary assessment estimated food and nutrient intakes. Reduced rank regression derived dietary patterns (response variables: protein [g/kg/day], PUFA [g/day] and vitamin D [μg/day]). Adjusted logistic regression analysis examined associations between dietary patterns and malnutrition, low muscle mass and sarcopenia. Three dietary patterns were identified: (i) ‘high oily fish and nuts’, characterised by higher oily fish and nuts and seeds intake (ii) ‘low oily fish’, characterised by lower oily fish intake and higher potato intake and (iii) ‘meat and dairy’, characterised by higher intake of meat, poultry and dairy. Eighteen percent of participants were malnourished, 5% had low muscle mass and 6.5% had sarcopenia. Odds of being malnourished were significantly lower with adherence to a ‘high oily fish and nuts’ pattern (OR: 0.57 95% CI: 0.50, 0.65) and ‘low oily fish’ pattern (OR: 0.81 95% CI: 0.73, 0.90). The ‘meat and dairy’ pattern was not associated with malnutrition. No dietary patterns were associated with low muscle mass or sarcopenia. Energy-rich dietary patterns were associated with lower odds of malnutrition in cancer survivors but did not influence muscle mass or sarcopenia risk. Better understanding of dietary patterns may improve cancer-related outcomes for cancer survivors.
Publisher: Elsevier BV
Date: 09-2022
DOI: 10.1016/J.CLNU.2022.07.005
Abstract: Diet and genetic predisposition to adiposity are independent predictors of body composition, yet few cohort studies have examined the association between overall diet quality indices, genetic risk and body composition. This study examined the prospective association of three diet quality indices and a polygenic risk score (PRS) with trunk fat mass, total fat mass, lean mass and bone mineral content. Adults from UK Biobank cohort were included. Dietary intake was assessed using the Oxford WebQ and three diet quality indices calculated: Recommended Food Score (RFS) Mediterranean Diet Score (MDS) Healthy Diet Indicator (HDI). Bioimpedance data were available for trunk fat, total fat and lean mass (kg). Trunk fat mass (kg), total fat mass (kg) and lean mass (kg) were assessed using bioelectrical impedance (BIA) in 17,478 adults. Bone mineral content (g) was available from dual energy x-ray absorptiometry (DXA) scans in 11,887 participants. Linear regression analyses, adjusted for demographic and lifestyle confounders, were used to estimate prospective associations between each diet quality index and body composition outcomes. A PRS created from 97 adiposity-related single nucleotide polymorphisms was used to examine interaction effects. A total of 17,478 adults (M = 55.9, SD 7.5 years) were followed up for up to 10 years. RFS, HDI and MDS were inversely associated with trunk fat (RFS: B -0.29 95% CI: -0.33, -0.25 HDI: -0.23 -0.27, -0.19 MDS: -0.22 -0.26, -0.18), total fat (RFS: B -0.49 95% CI: -0.56, -0.42 HDI: -0.38 -0.45, -0.32 MDS: -0.38 -0.44, -0.32) and lean (RFS: B -0.10 95% CI: -0.14, -0.06 HDI: -0.07 -0.11, -0.03 MDS: -0.07 -0.11, -0.04) mass. Diet quality was positively associated with bone mineral content (RFS: B 8.23 95% CI: 2.14, 14.3 HDI: 6.77 1.00, 12.5). There was evidence of non-linear associations between diet quality (RFS and HDI only) and trunk fat (p < 0.01) and total fat mass (p < 0.05). There was limited evidence PRS was associated with body composition, with interaction effects of PRS and HDI (p-interaction = 0.039) and MDS (p-interaction = 0.031) on total fat mass. Higher diet quality was associated with lower trunk fat, total fat and lean mass, regardless of the diet quality index examined (RFS, HDI or MDS), while higher diet quality (RFS and HDI only) was associated with higher bone mineral content. The benefit of higher diet quality on reducing total fat mass was most evident in in iduals with higher generic risk of adiposity. These findings underscore the importance of a high-quality diet for maintaining optimal body composition, particularly in in iduals with genetic pre-disposition to adiposity.
Publisher: Springer Science and Business Media LLC
Date: 06-12-2021
DOI: 10.1007/S00394-021-02758-Y
Abstract: To derive dietary patterns based on dietary energy density (DED), free sugars, SFA, and fiber and investigate association with odds of overweight/obesity in young adults. Cross-sectional data from 625 young Australian adults (18–30 years) were used. Dietary patterns were derived using reduced rank regression based on dietary data from a smartphone food diary using DED, free sugars, SFA, and fiber density as response variables. Multivariable logistic regression was used to investigate associations between dietary patterns and odds of self-reported overweight/obesity (BMI ≥ 25 kg/m 2 ). Two dietary patterns were identified (DP1 and DP2). DP-1 was positively correlated with DED, free sugars, and SFA, and inversely correlated with fiber density. It was characterized by higher sugar-sweetened beverages intake and lower vegetable intake, and associated with higher odds of overweight/obesity (OR: 1.22 95% CI 1.05, 1.42). DP-2 was positively correlated with fiber density and free sugars, and inversely correlated with DED and SFA. It was characterized by higher sugar-sweetened beverages intake and lower non-lean red meat intake, and was not significantly associated with overweight/obesity. An energy-dense dietary pattern high in free sugars and SFA and low in fiber was associated with higher odds of obesity in young adults. These findings support dietary interventions that target reductions in energy-dense foods and sugar-sweetened beverages.
Publisher: Frontiers Media SA
Date: 06-2023
DOI: 10.3389/FNUT.2023.1071855
Abstract: The effect of dietary fat on type 2 diabetes (T2D) risk is unclear. A posteriori dietary pattern methods have been increasingly used to investigate how dietary fats impact T2D risk. However, the erse nutrients, foods and dietary patterns reported in these studies requires examination to better understand the role of dietary fats. This scoping review aimed to systematically search and synthesize the literature regarding the association between dietary patterns characterized by dietary fats and T2D risk using reduced rank regression. Medline and Embase were searched for cross-sectional, cohort or case-control studies published in English. Of the included studies ( n = 8), five high-fat dietary patterns, mostly high in SFA, were associated with higher T2D risk or fasting glucose, insulin and Homeostasis Model Assessment (HOMA) levels. These were mostly low-fiber ( n = 5) and high energy-density ( n = 3) dietary patterns characterized by low fruit and vegetables intake, reduced fat dairy products and higher processed meats and butter intake. Findings from this review suggest that a posterior i dietary patterns high in SFA that increase T2D risk are often accompanied by lower fruits, vegetables and other fiber-rich foods intake. Therefore, healthy dietary fats consumption for T2D prevention should be encouraged as part of a healthful dietary pattern.
Publisher: Elsevier BV
Date: 04-2023
Publisher: Springer Science and Business Media LLC
Date: 21-03-2022
DOI: 10.1007/S00394-022-02858-3
Abstract: High-fat and low-fibre discretionary food intake and FTO genotype are each associated independently with higher risk of obesity. However, few studies have investigated links between obesity and dietary patterns based on discretionary food intake, and the interaction effect of FTO genotype are unknown. Thus, this study aimed to derive dietary patterns based on intake of discretionary foods, saturated fatty acids (SFA) and fibre, and examine cross-sectional associations with BMI and waist circumference (WC), and interaction effects of FTO genotype. Baseline data on 1280 adults from seven European countries were included (the Food4Me study). Dietary intake was estimated from a Food Frequency Questionnaire. Reduced rank regression was used to derive three dietary patterns using response variables of discretionary foods, SFA and fibre density. DNA was extracted from buccal swabs. Anthropometrics were self-measured. Linear regression analyses were used to examine associations between dietary patterns and BMI and WC, with an interaction for FTO genotype. Dietary pattern 1 (positively correlated with discretionary foods and SFA, and inversely correlated with fibre) was associated with higher BMI (β:0.64 95% CI 0.44, 0.84) and WC (β:1.58 95% CI 1.08, 2.07). There was limited evidence dietary pattern 2 (positively correlated with discretionary foods and SFA) and dietary pattern 3 (positively correlated with SFA and fibre) were associated with anthropometrics. FTO risk genotype was associated with higher BMI and WC, with no evidence of a dietary interaction. Consuming a dietary pattern low in discretionary foods and high-SFA and low-fibre foods is likely to be important for maintaining a healthy weight, regardless of FTO predisposition to obesity. Clinicaltrials.gov NCT01530139. Registered 9 February 2012 t2/show/NCT01530139
Publisher: Elsevier BV
Date: 06-2023
Publisher: Elsevier BV
Date: 05-2022
DOI: 10.1016/J.YPMED.2022.107035
Abstract: Few studies have derived dietary patterns based on intake of discretionary foods and beverages and examined associations with genetic risk and obesity. We examined associations between dietary patterns based on discretionary foods, saturated fatty acids (SFA), and fiber, with a polygenetic risk score (PRS) for obesity and risk of overall obesity, central obesity and high body fat (BF) up to 9.7 years later. Data from 11,735 adults from the UK Biobank cohort study were used. Dietary patterns were derived from 24-h dietary assessments using reduced rank regression (response variables: discretionary foods and beverages [%E] SFA [%E] fiber density [g/MJ]). Cox proportional hazard models were used to investigate associations between dietary patterns and incident overall obesity, central obesity and high BF, with interactions by PRS. Three dietary patterns (DP) were identified. DP1, correlated positively with discretionary foods and SFA, inversely with fiber, was associated with higher risk of central obesity (hazard ratio: 1.08 95% confidence interval: 1.02, 1.14). DP2, correlated positively with discretionary foods and fiber, inversely with SFA, was not associated with obesity incidence. DP3, correlated positively with SFA and fiber, inversely with discretionary foods, was associated with lower risk of central obesity (hazard ratio: 0.92 95% confidence interval: 0.87, 0.98). There was limited evidence of interactions with PRS. A dietary pattern high in high-SFA and low-fiber discretionary foods and beverages was associated with higher risk of obesity, independent of genetic predisposition.
Publisher: Elsevier BV
Date: 11-2021
DOI: 10.1093/JN/NXAB275
Abstract: The fat type consumed is considered a risk factor for developing obesity and type 2 diabetes (T2D). However, these associations have not been investigated using a dietary patterns approach, which can capture combinations of foods and fat type consumed. This study aimed to investigate associations between dietary patterns with varying proportions of SFAs, MUFAs, or PUFAs and obesity, abdominal obesity, and self-reported T2D incidence. This study included UK Biobank participants with 2 or more 24-h dietary assessments, free from the outcome of interest at recruitment, and with outcome data at follow-up (n = 16,523 mean follow-up: 6.3 y). Reduced rank regression was used to derive dietary patterns with SFAs, MUFAs, and PUFAs (% of energy intake) as response variables. Logistic regression, adjusted for sociodemographic and health characteristics, was used to investigate the associations between dietary patterns and obesity [BMI (kg/m2) ≥30], abdominal obesity (waist circumference men: ≥102 cm women: ≥88 cm) and T2D incidence. Two dietary patterns, DP1 and DP2, were identified: DP1 positively correlated with SFAs (r = 0.48), MUFAs (r = 0.67), and PUFAs (r = 0.56), characterized by higher intake of nuts, seeds, and butter and lower intake of fruit and low-fat yogurt DP2 positively correlated with SFAs (r = 0.76) and negatively with PUFAs (r = -0.64) and MUFAs (r = -0.01), characterized by higher intake of butter and high-fat cheese and lower intake of nuts and seeds. Only DP2 was associated with higher obesity and abdominal obesity incidence (OR: 1.24 95% CI: 1.02, 1.45 and OR: 1.19 95% CI: 1.02, 1.38, respectively). Neither of the dietary patterns was associated with T2D incidence. These findings provide evidence that a dietary pattern characterized by higher SFA and lower PUFA foods is associated with obesity and abdominal obesity incidence, but not T2D.
Publisher: Ovid Technologies (Wolters Kluwer Health)
Date: 07-06-2022
Abstract: Although the impact of dietary fats on cardiovascular disease (CVD) risk is widely researched, longitudinal associations between dietary patterns (DPs) based on fat type and early markers of CVD risk remain unclear. UK Biobank participants (46.9% men, mean age 55 years) with data on early markers of CVD risk (n=12 706) were followed longitudinally (2014–2020 mean 8.4 years). Two DPs (DP1, DP2) were derived using reduced rank regression (response variables: monounsaturated fat, polyunsaturated fat, and saturated fat based on two 24‐hour dietary assessments. Multivariable logistic and linear regression were used to investigate associations between DPs and odds of elevated CVD risk (using the nonlaboratory Framingham Risk Score) and changes in early CVD markers, respectively. DP1 (characterized by higher nuts and seeds and lower fruit and legumes intake) was positively correlated with saturated fat, monounsaturated fat, and polyunsaturated fat DP2 (characterized by higher butter and high‐fat cheese, lower nuts and seeds intake) was positively correlated with saturated fat and negatively with polyunsaturated fat and monounsaturated fat. DP2 was associated with slightly higher odds of elevated CVD risk (odds ratio, 1.04 [95% CI, 1.00–1.07]). DP1 was associated with higher diastolic blood pressure (β, 0.20 [95% CI, 0.01–0.37]) and lower cardiac index (β, −0.02 [95% CI, −0.04 to −0.01]) DP2 was associated with higher carotid intima medial thickness (β, 1.80 [95% CI, 0.01–3.59]) and lower left ventricular ejection fraction (β, −0.15 [95% CI, −0.24 to −0.07]) and cardiac index (β, −0.01 [95% CI, −0.02 to −0.01]). This study suggests small but statistically significant associations between DPs based on fat type and some early markers of CVD risk. Further research is needed to confirm these associations.
Publisher: Springer Science and Business Media LLC
Date: 08-06-2022
DOI: 10.1038/S41387-022-00209-Z
Abstract: There is increasing evidence that skeletal muscle microvascular (capillary) blood flow plays an important role in glucose metabolism by increasing the delivery of glucose and insulin to the myocytes. This process is impaired in insulin-resistant in iduals. Studies suggest that in diet-induced insulin-resistant rodents, insulin-mediated skeletal muscle microvascular blood flow is impaired post-short-term high fat feeding, and this occurs before the development of myocyte or whole-body insulin resistance. These data suggest that impaired skeletal muscle microvascular blood flow is an early vascular step before the onset of insulin resistance. However, evidence of this is still lacking in humans. In this review, we summarise what is known about short-term high-calorie and/or high-fat feeding in humans. We also explore selected animal studies to identify potential mechanisms. We discuss future directions aimed at better understanding the ‘early’ vascular mechanisms that lead to insulin resistance as this will provide the opportunity for much earlier screening and timing of intervention to assist in preventing type 2 diabetes.
No related grants have been discovered for Barbara Brayner.