9 resultados para fat mass

em QUB Research Portal - Research Directory and Institutional Repository for Queen's University Belfast


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Background: Epidemiologic evidence on the influence of dietary glycemic index (GI) and glycemic load (GL) on the development of obesity is limited.

Objective: This prospective study examined the associations between dietary GI and GL and changes in body composition measures during adolescence.

Design: In a representative sample of Northern Irish adolescents aged 12 years at baseline and 15 years at follow-up (n=426), dietary intake was assessed by a diet history interview. Body composition measures included body mass index (BMI; kg m(-2)), BMI z-score, sum of four skinfold thicknesses, percentage body fat, fat mass index (FMI; kg m(-2)) and fat-free mass index (kg m(-2)).

Results: After adjustment for potential confounding factors, baseline GI was associated with increased change in FMI. Mean (95% confidence interval) values of changes in FMI according to tertiles of baseline GI were 0.41 (0.25, 0.57), 0.42 (0.26, 0.58) and 0.67 (0.51, 0.83) kg m(-2), respectively (P for trend=0.03). There was no significant association of baseline GI with changes in other body composition measures (P for trend0.054). Conversely, baseline GL showed no association with changes in any of the measures (P for trend0.41). Furthermore, changes in GI or GL were not associated with changes in any of the measures (P for trend0.16).

Conclusion: Dietary GI at age 12 years was independently associated with increased change in FMI between ages 12 and 15 years in a representative sample from Northern Ireland, whereas dietary GL showed no association with changes in any of the body composition measures examined.

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PURPOSE: Treatment of prostate cancer with androgen deprivation therapy (ADT) is associated with an increased fat mass, decreased lean mass, increased fatigue and a reduction in quality of life (QoL). The aim of this study was to evaluate the efficacy of a 6-month dietary and physical activity intervention for prostate cancer patients receiving ADT, to help minimise these side effects.

METHODS: Patients (n = 94) were recruited to this study if they were planned to receive ADT for prostate cancer for at least 6 months. Men randomised to the intervention arm received a dietary and exercise intervention, commensurate with UK healthy eating and physical activity recommendations. The primary outcome of interest was body composition; secondary outcomes included fatigue, QoL, functional capacity, stress and dietary change.

RESULTS: The intervention group had a significant (p < 0.001) reduction in weight, body mass index and percentage fat mass compared to the control group at 6 months; the between-group differences were -3.3 kg (95 % confidence interval (95 % CI) -4.5, -2.1), -1.1 kg/m(2) (95 % CI -1.5, -0.7) and -2.1 % (95 % CI -2.8, -1.4), respectively, after adjustment for baseline values. The intervention resulted in improvements in functional capacity (p < 0.001) and dietary intakes but did not significantly impact fatigue, QoL or stress scores at endpoint.

CONCLUSIONS: A 6-month diet and physical activity intervention can minimise the adverse body composition changes associated with ADT.

IMPLICATIONS FOR CANCER SURVIVORS: This study shows that a pragmatic lifestyle intervention is feasible and can have a positive impact on health behaviours and other key outcomes in men with prostate cancer receiving ADT.

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A confirmatory method has been developed and validated that allows for the simultaneous detection of medroxyprogesterone acetate (MPA), megestrol acetate (MGA), melengestrol acetate (MLA), chlormadinone acetate (CMA) and delmadinone acetate (DMA) in animal kidney fat using liquid chromatography-tandem mass spectrometry (LC-MS/MS). The compounds were extracted from kidney fat using acetonitrile, defatted using a hexane wash and subsequent saponification. Extracts were then purified on Isolute CN solid-phase extraction cartridges and analysed by LC-MS/MS. The method was validated in animal kidney fat in accordance with the criteria defined in Commission Decision 2002/657/EC. The decision limit (CC) was calculated to be 0.12, 0.48, 0.40, 0.63 and 0.54 g kg-1, respectively, for MPA, MGA, MLA, DMA and CMA, with respective detection capability (CC) values of 0.20, 0.81, 0.68, 1.07 and 0.92 g kg-1. The measurement uncertainty of the method was estimated at 16, 16, 19, 27 and 26% for MPA, MGA, MLA, DMA and CMA, respectively. Fortifying kidney fat samples (n = 18) in three separate assays showed the accuracy of the method to be between 98 and 100%. The precision of the method, expressed as % RSD, for within-laboratory reproducibility at three levels of fortification (1, 1.5 and 2 g kg-1 for MPA, 5, 7.5 and 10 g kg-1 for MGA, MLA, DMA and CMA) was less than 5% for all analytes.

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The aim of our study was to investigate whether intakes of total fat and fat subtypes were associated with esophageal adenocarcinoma (EAC), esophageal squamous cell carcinoma (ESCC), gastric cardia or gastric noncardia adenocarcinoma. From 1995–1996, dietary intake data was reported by 494,978 participants of the NIH-AARP cohort. The 630 EAC, 215 ESCC, 454 gastric cardia and 501 gastric noncardia adenocarcinomas accrued to the cohort. Cox proportional hazards regression was used to examine the association between the dietary fat intakes, whilst adjusting for potential confounders. Although apparent associations were observed in energy-adjusted models, multivariate adjustment attenuated results to null [e.g., EAC energy adjusted hazard ratio (HR) and 95% confidence interval (95% CI) 1.66 (1.27–2.18) p for trend <0.01; EAC multivariate adjusted HR (95% CI) 1.17 (0.84–1.64) p for trend 5 0.58]. Similar patterns were also observed for fat subtypes [e.g., EAC saturated fat, energy adjusted HR (95% CI) 1.79 (1.37–2.33) p for trend <0.01; EAC saturated fat, multivariate adjusted HR (95% CI) 1.27 (0.91–1.78) p for trend 5 0.28]. However, in multivariate models an inverse association for polyunsaturated fat (continuous) was seen for EAC in subjects with a body mass index (BMI) in the normal range (18.5–<25 kg/m2) [HR (95% CI) 0.76 (0.63–0.92)], that was not present in overweight subjects [HR (95% CI) 1.04 (0.96–1.14)], or in unstratified analysis [HR (95% CI) 0.97 (0.90–1.05)]. p for interaction 5 0.02. Overall, we found null associations between the dietary fat intakes with esophageal or gastric cancer risk; although a protective effect of polyunsaturated fat intake was seen for EAC in subjects with a normal BMI.

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Objective
To investigate the effect of fast food consumption on mean population body mass index (BMI) and explore the possible influence of market deregulation on fast food consumption and BMI.

Methods
The within-country association between fast food consumption and BMI in 25 high-income member countries of the Organisation for Economic Co-operation and Development between 1999 and 2008 was explored through multivariate panel regression models, after adjustment for per capita gross domestic product, urbanization, trade openness, lifestyle indicators and other covariates. The possible mediating effect of annual per capita intake of soft drinks, animal fats and total calories on the association between fast food consumption and BMI was also analysed. Two-stage least squares regression models were conducted, using economic freedom as an instrumental variable, to study the causal effect of fast food consumption on BMI.

Findings
After adjustment for covariates, each 1-unit increase in annual fast food transactions per capita was associated with an increase of 0.033 kg/m2 in age-standardized BMI (95% confidence interval, CI: 0.013–0.052). Only the intake of soft drinks – not animal fat or total calories – mediated the observed association (β: 0.030; 95% CI: 0.010–0.050). Economic freedom was an independent predictor of fast food consumption (β: 0.27; 95% CI: 0.16–0.37). When economic freedom was used as an instrumental variable, the association between fast food and BMI weakened but remained significant (β: 0.023; 95% CI: 0.001–0.045).

Conclusion
Fast food consumption is an independent predictor of mean BMI in high-income countries. Market deregulation policies may contribute to the obesity epidemic by facilitating the spread of fast food.

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Body fat distribution is a heritable trait and a well-established predictor of adverse metabolic outcomes, independent of overall adiposity. To increase our understanding of the genetic basis of body fat distribution and its molecular links to cardiometabolic traits, here we conduct genome-wide association meta-analyses of traits related to waist and hip circumferences in up to 224,459 individuals. We identify 49 loci (33 new) associated with waist-to-hip ratio adjusted for body mass index (BMI), and an additional 19 loci newly associated with related waist and hip circumference measures (P < 5 × 10(-8)). In total, 20 of the 49 waist-to-hip ratio adjusted for BMI loci show significant sexual dimorphism, 19 of which display a stronger effect in women. The identified loci were enriched for genes expressed in adipose tissue and for putative regulatory elements in adipocytes. Pathway analyses implicated adipogenesis, angiogenesis, transcriptional regulation and insulin resistance as processes affecting fat distribution, providing insight into potential pathophysiological mechanisms.

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OBJECTIVE: To determine whether exposure to diabetes in utero affects resting energy expenditure (REE) and fuel oxidation in infants.

STUDY DESIGN: At 35 ± 5 days after birth, body composition and REE were measured in full-term offspring of Native American and Hispanic women with either well-controlled diabetes (13 girls, 11 boys) or normal healthy pregnancies (18 girls, 17 boys).

RESULTS: Control of dysglycemia during gestation in the women with diabetes mellitus met current clinical standards, shown by average glycated hemoglobin (5.9 ± 0.2%; 40.6 ± 2.3 mmol/mol). Infant body mass (offspring of women with diabetes: 4.78 ± 0.13, control offspring: 4.56 ± 0.08 kg) and body fatness (offspring of women with diabetes: 25.2 ± 0.6, control offspring: 24.2 ± 0.5 %) did not differ between groups. REE, adjusted for lean body mass, was 14% lower in offspring of women with diabetes (41.7 ± 2.3 kJ/h) than control offspring (48.6 ± 2.0, P = .025). Fat oxidation was 26% lower in offspring of women with diabetes (0.54 ± 0.05 g/h) than control offspring (0.76 ± 0.04, P < .01) but carbohydrate oxidation did not differ. Thus, fat oxidation accounted for a lower fraction of REE in the offspring of women with diabetes (49 ± 4%) than control offspring (60 ± 3%, P = .022). Mothers with diabetes were older and had higher prepregnancy body mass index than control mothers.

CONCLUSIONS: Well-controlled maternal diabetes did not significantly affect body mass or composition of offspring at 1-month old. However, infants with mothers with diabetes had reduced REE and fat oxidation, which could contribute to adiposity and future disease risk. Further studies are needed to assess the impact differences in age and higher prepregnancy body mass index.

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OBJECTIVE: Abdominal obesity is associated with increased risk of type 2 diabetes (T2D) and cardiovascular disease. The aim of this study was to assess whether metabolomic markers of T2D and blood pressure (BP) act on these traits via visceral fat (VF) mass.

METHODS: Metabolomic profiling of 280 fasting plasma metabolites was conducted on 2,401 women from TwinsUK. The overlap was assessed between published metabolites associated with T2D, insulin resistance, or BP and those that were identified to be associated with VF (after adjustment for covariates) measured by dual-energy X-ray absorptiometry.

RESULTS: In addition to glucose, six metabolites were strongly associated with both VF mass and T2D: lactate and branched-chain amino acids, all of them related to metabolism and the tricarboxylic acid cycle; on average, 38.5% of their association with insulin resistance was mediated by their association with VF mass. Five metabolites were associated with BP and VF mass including the inflammation-associated peptide HWESASXX, the steroid hormone androstenedione, lactate, and palmitate. On average, 29% of their effect on BP was mediated by their association with VF mass.

CONCLUSIONS: Little overlap was found between the metabolites associated with BP and those associated with insulin resistance via VF mass.