206 resultados para metabolic weight
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Background Environmental factors can influence obesity by epigenetic mechanisms. Adipose tissue plays a key role in obesity-related metabolic dysfunction, and gastric bypass provides a model to investigate obesity and weight loss in humans. Results Here, we investigate DNA methylation in adipose tissue from obese women before and after gastric bypass and significant weight loss. In total, 485,577 CpG sites were profiled in matched, before and after weight loss, subcutaneous and omental adipose tissue. A paired analysis revealed significant differential methylation in omental and subcutaneous adipose tissue. A greater proportion of CpGs are hypermethylated before weight loss and increased methylation is observed in the 3′ untranslated region and gene bodies relative to promoter regions. Differential methylation is found within genes associated with obesity, epigenetic regulation and development, such as CETP, FOXP2, HDAC4, DNMT3B, KCNQ1 and HOX clusters. We identify robust correlations between changes in methylation and clinical trait, including associations between fasting glucose and HDAC4, SLC37A3 and DENND1C in subcutaneous adipose. Genes investigated with differential promoter methylation all show significantly different levels of mRNA before and after gastric bypass. Conclusions This is the first study reporting global DNA methylation profiling of adipose tissue before and after gastric bypass and associated weight loss. It provides a strong basis for future work and offers additional evidence for the role of DNA methylation of adipose tissue in obesity.
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Background: Body mass index (BMI) is widely used as a measure of adiposity. However, currently used cut-off values are not sensitive in diagnosing obesity in South Asian populations. Aim: To define BMI and waist circumference (WC), cut-off values representing percentage fat mass (%FM) associated with adverse health outcomes. Subjects and methods: A cross-sectional descriptive study of 285 5–14 year old Sri Lankan children (56% boys) was carried out. Fat mass (FM) was assessed using the isotope (D2O) dilution technique based on 2C body composition model. BMI and WC cut-off values were defined based on %FM associated with adverse health outcomes. Results: Sri Lankan children had a low fat free mass index (FFMI) and a high fat mass index (FMI). Individuals with the same BMI had %FM distributed over a wide range. Lean body tissue grew very little with advancing age and weight gain was mainly due to increases in body fat. BMI corresponding to 25% in males and 35% in females at 18 years was 19.2 kg/m2 and 19.7 kg/m2, respectively. WC cut-off values for males and females were 68.4 cm and 70.4 cm, respectively. Conclusion: This chart analysis clearly confirms that Sri Lankan children have a high %FM from a young age. With age, more changes occur in FM than in fat free mass (FFM). Although the newly defined BMI and WC cut-off values appear to be quite low, they are comparable to some recent data obtained in similar populations.
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The concept of energy gap(s) is useful for understanding the consequence of a small daily, weekly, or monthly positive energy balance and the inconspicuous shift in weight gain ultimately leading to overweight and obesity. Energy gap is a dynamic concept: an initial positive energy gap incurred via an increase in energy intake (or a decrease in physical activity) is not constant, may fade out with time if the initial conditions are maintained, and depends on the 'efficiency' with which the readjustment of the energy imbalance gap occurs with time. The metabolic response to an energy imbalance gap and the magnitude of the energy gap(s) can be estimated by at least two methods, i.e. i) assessment by longitudinal overfeeding studies, imposing (by design) an initial positive energy imbalance gap; ii) retrospective assessment based on epidemiological surveys, whereby the accumulated endogenous energy storage per unit of time is calculated from the change in body weight and body composition. In order to illustrate the difficulty of accurately assessing an energy gap we have used, as an illustrative example, a recent epidemiological study which tracked changes in total energy intake (estimated by gross food availability) and body weight over 3 decades in the US, combined with total energy expenditure prediction from body weight using doubly labelled water data. At the population level, the study attempted to assess the cause of the energy gap purported to be entirely due to increased food intake. Based on an estimate of change in energy intake judged to be more reliable (i.e. in the same study population) and together with calculations of simple energetic indices, our analysis suggests that conclusions about the fundamental causes of obesity development in a population (excess intake vs. low physical activity or both) is clouded by a high level of uncertainty.
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OBJECTIVE: To evaluate the effectiveness of a telephone-delivered behavioral weight loss and physical activity intervention targeting Australian primary care patients with type 2 diabetes. RESEARCH DESIGN AND METHODS: Pragmatic randomized controlled trial of telephone counseling (n = 151) versus usual care (n = 151). Reported here are 18-month (end-of-intervention) and 24-month (maintenance) primary outcomes of weight, moderate-to-vigorous-intensity physical activity (MVPA; via accelerometer), and HbA1c level. Secondary outcomes include dietary energy intake and diet quality, waist circumference, lipid levels, and blood pressure. Data were analyzed via adjusted linear mixed models with multiple imputation of missing data. RESULTS: Relative to usual-care participants, telephone counseling participants achieved modest, but significant, improvements in weight loss (relative rate [RR] -1.42% of baseline body weight [95% CI -2.54 to -0.30% of baseline body weight]), MVPA (RR 1.42 [95% CI 1.06-1.90]), diet quality (2.72 [95% CI 0.55-4.89]), and waist circumference (-1.84 cm [95% CI -3.16 to -0.51 cm]), but not in HbA1c level (RR 0.99 [95% CI 0.96-1.02]), or other cardio-metabolic markers. None of the outcomes showed a significant change/deterioration over the maintenance period. However, only the intervention effect for MVPA remained statistically significant at 24 months. CONCLUSIONS: The modest improvements in weight loss and behavior change, but the lack of changes in cardio-metabolic markers, may limit the utility, scalability, and sustainability of such an approach.
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Objective: To compare measurements of sleeping metabolic rate (SMR) in infancy with predicted basal metabolic rate (BMR) estimated by the equations of Schofield. Methods: Some 104 serial measurements of SMR by indirect calorimetry were performed in 43 healthy infants at 1.5, 3, 6, 9 and 12 months of age. Predicted BMR was calculated using the weight only (BMR-wo) and weight and height (BMR-wh) equations of Schofield for 0-3-y-olds. Measured SMR values were compared with both predictive values by means of the Bland-Altman statistical test. Results: The mean measured SMR was 1.48 MJ/day. The mean predicted BMR values were 1.66 and 1.47 MJ/day for the weight only and weight and height equations, respectively. The Bland-Altman analysis showed that BMR-wo equation on average overestimated SMR by 0.18 MJ/day (11%) and the BMR-wh equation underestimated SMR by 0.01 MJ/day (1%). However the 95% limits of agreement were wide: -0.64 to + 0.28 MJ/day (28%) for the former equation and -0.39 to + 0.41 MJ/day (27%) for the latter equation. Moreover there was a significant correlation between the mean of the measured and predicted metabolic rate and the difference between them. Conclusions: The wide variation seen in the difference between measured and predicted metabolic rate and the bias probably with age indicates there is a need to measure actual metabolic rate for individual clinical care in this age group.
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The common brown leafhopper, Orosius orientalis (Matsumura) (Homoptera: Cicadellidae), previously described as Orosius argentatus (Evans), is an important vector of several viruses and phytoplasmas worldwide. In Australia, phytoplasmas vectored by O. orientalis cause a range of economically important diseases, including legume little leaf (Hutton & Grylls, 1956), tomato big bud (Osmelak, 1986), lucerne witches broom (Helson, 1951), potato purple top wilt (Harding & Teakle, 1985), and Australian lucerne yellows (Pilkington et al., 2004). Orosius orientalis also transmits Tobacco yellow dwarf virus (TYDV; genus Mastrevirus, family Geminiviridae) to beans, causing bean summer death disease (Ballantyne, 1968), and to tobacco, causing tobacco yellow dwarf disease (Hill, 1937, 1941). TYDV has only been recorded in Australia to date. Both diseases result in significant production and quality losses (Ballantyne, 1968; Thomas, 1979; Moran & Rodoni, 1999). Although direct damage caused by leafhopper feeding has been observed, it is relatively minor compared to the losses resulting from disease (P Tr E bicki, unpubl.).
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In two experiments, we show that the beliefs women have about the controllability of their weight (i.e., weight locus of control) influences their responses to advertisements featuring a larger-sized female model or a slim female model. Further, we examine self-referencing as a mechanism for these effects. Specifically, people who believe they can control their weight (“internals”), respond most favorably to slim models in advertising, and this favorable response is mediated by self-referencing. In contrast, people who feel powerless about their weight (“externals”), self-reference larger-sized models, but only prefer larger-sized models when the advertisement is for a non-fattening product. For fattening products, they exhibit a similar preference for larger-sized models and slim models. Together, these experiments shed light on the effect of model body size and the role of weight locus of control in influencing consumer attitudes.
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Introduction: Weight gain is a common concern following breast cancer and has been associated with negative health outcomes. As such, prevention of weight gain is of clinical interest. This work describes weight change between 6- and 18-months following a breast cancer diagnosis and explores the personal, treatment and behavioural characteristics associated with gains in weight. Methods: Body mass index was objectively assessed, at three-monthly intervals, on a population-based sample of women newly diagnosed with unilateral breast cancer (n=185). Changes in BMI between 6- and 18-months post-diagnosis were calculated, with gains of one or more being considered clinically detrimental to future health. Results: Approximately 60% of participants were overweight or obese at 6-months post-diagnosis. While BMI remained relatively stable across the testing period (range=27.3-27.8), 24% of participants experienced clinically relevant gains in BMI (median gains=1.9). Following adjustment for potential confounders, younger age (<45 years; Odds ratio, OR=9.8), being morbidly obese at baseline (OR=4.6) and receiving hormone therapy (OR=4.8) were characteristics associated with an increased odds (p<0.05) of gaining BMI. Other characteristics associated with gains in BMI were more extensive surgery and having a history of smoking, although these relationships were not supported statistically. In contrast, caring for younger children was associated with reduced risk of gaining BMI (OR=0.3, p=0.20). Conclusions: Clinically relevant weight gain between 6- and 18-months post-breast cancer diagnosis is an issue for one in four women, with certain subgroups being particularly susceptible. However, the majority of women diagnosed with breast cancer are overweight or obese and gains in body weight are common. Thus, interventions that address the importance of achieving and sustaining a healthy body weight, delivered to all women with breast cancer, may have greater public health impact than interventions targeting any specific breast cancer subgroup.
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Background: Exercise is widely promoted as a method of weight management, while the other health benefits are often ignored. The purpose of this study was to examine whether exercise-induced improvements in health are influenced by changes in body weight. Methods: Fifty-eight sedentary overweight/obese men and women (BMI 31.8 (SD 4.5) kg/m2) participated in a 12-week supervised aerobic exercise intervention (70% heart rate max, five times a week, 500 kcal per session). Body composition, anthropometric parameters, aerobic capacity, blood pressure and acute psychological response to exercise were measured at weeks 0 and 12. Results: The mean reduction in body weight was −3.3 (3.63) kg (p<0.01). However, 26 of the 58 participants failed to attain the predicted weight loss estimated from individuals’ exercise-induced energy expenditure. Their mean weight loss was only −0.9 (1.8) kg (p<0.01). Despite attaining a lower-than-predicted weight reduction, these individuals experienced significant increases in aerobic capacity (6.3 (6.0) ml/kg/min; p<0.01), and a decreased systolic (−6.00 (11.5) mm Hg; p<0.05) and diastolic blood pressure (−3.9 (5.8) mm Hg; p<0.01), waist circumference (−3.7 (2.7) cm; p<0.01) and resting heart rate (−4.8 (8.9) bpm, p<0.001). In addition, these individuals experienced an acute exercise-induced increase in positive mood. Conclusions: These data demonstrate that significant and meaningful health benefits can be achieved even in the presence of lower-than-expected exercise-induced weight loss. A less successful reduction in body weight does not undermine the beneficial effects of aerobic exercise. From a public health perspective, exercise should be encouraged and the emphasis on weight loss reduced.
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Objective: In the majority of exercise intervention studies, the aggregate reported weight loss is often small. The efficacy of exercise as a weight loss tool remains in question. The aim of the present study was to investigate the variability in appetite and body weight when participants engaged in a supervised and monitored exercise programme. ---------- Design: Fifty-eight obese men and women (BMI = 31·8 ± 4·5 kg/m2) were prescribed exercise to expend approximately 2092 kJ (500 kcal) per session, five times a week at an intensity of 70 % maximum heart rate for 12 weeks under supervised conditions in the research unit. Body weight and composition, total daily energy intake and various health markers were measured at weeks 0, 4, 8 and 12. ---------- Results: Mean reduction in body weight (3·2 ± 1·98 kg) was significant (P < 0·001); however, there was large individual variability (−14·7 to +2·7 kg). This large variability could be largely attributed to the differences in energy intake over the 12-week intervention. Those participants who failed to lose meaningful weight increased their food intake and reduced intake of fruits and vegetables. ---------- Conclusion: These data have demonstrated that even when exercise energy expenditure is high, a healthy diet is still required for weight loss to occur in many people.
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Purpose: Television viewing time, independent of leisure-time physical activity, has cross-sectional relationships with the metabolic syndrome and its individual components. We examined whether baseline and five-year changes in self-reported television viewing time are associated with changes in continuous biomarkers of cardio-metabolic risk (waist circumference, triglycerides, high density lipoprotein cholesterol, systolic and diastolic blood pressure, fasting plasma glucose; and a clustered cardio-metabolic risk score) in Australian adults. Methods: AusDiab is a prospective, population-based cohort study with biological, behavioral, and demographic measures collected in 1999–2000 and 2004–2005. Non-institutionalized adults aged ≥ 25 years were measured at baseline (11,247; 55% of those completing an initial household interview); 6,400 took part in the five-year follow-up biomedical examination, and 3,846 met the inclusion criteria for this analysis. Multiple linear regression analysis was used and unstandardized B coefficients (95% CI) are provided. Results: Baseline television viewing time (10 hours/week unit) was not significantly associated with change in any of the biomarkers of cardio-metabolic risk. Increases in television viewing time over five years (10 hours/week unit) were associated with increases in: waist circumference (cm) (men: 0.43 (0.08, 0.78), P = 0.02; women: 0.68 (0.30, 1.05), P <0.001), diastolic blood pressure (mmHg) (women: 0.47 (0.02, 0.92), P = 0.04), and the clustered cardio-metabolic risk score (women: 0.03 (0.01, 0.05), P = 0.007). These associations were independent of baseline television viewing time and baseline and change in physical activity and other potential confounders. Conclusion: These findings indicate that an increase in television viewing time is associated with adverse cardio-metabolic biomarker changes. Further prospective studies using objective measures of several sedentary behaviors are required to confirm causality of the associations found.
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Background: The incidence of obesity is increasing; this is of major concern, as obesity is associated with cardiovascular disease, stroke, type 2 diabetes, respiratory tract disease, and cancer. Objectives/methods: This evaluation is of a Phase II clinical trial with tesofensine in obese subjects. Results: After 26 weeks, tesofensine caused a significant weight loss, and may have a higher maximal ability to reduce weight than the presently available anti-obesity agents. However, tesofensine also increased blood pressure and heart rate, and may increase psychiatric disorders. Conclusions: It is encouraging that tesofensine 0.5 mg may cause almost double the weight loss observed with sibutramine or rimonabant. As tesofensine and sibutramine have similar pharmacological profiles, it would be of interest to compare the weight loss with tesofensine in a head-to-head clinical trial with sibutramine, to properly assess their comparative potency. Also, as teso fensine 0.5 mg increases heart rate, as well as increasing the incidence of adverse effects such as nausea, drug mouth, flatulence, insomnia, and depressed mode, its tolerability needs to be further evaluated in large Phase III clinical trials.
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Objective: Obesity associated with atypical antipsychotic medications is an important clinical issue for people with schizophrenia. The purpose of this project was to determine whether there were any differences in resting energy expenditure (REE) and respiratory quotient (RQ) between men with schizophrenia and controls. Method: Thirty-one men with schizophrenia were individually matched for age and relative body weight with healthy, sedentary controls. Deuterium dilution was used to determine total body water and subsequently fat-free mass (FFM). Indirect calorimetry using a Deltatrac metabolic cart was used to determine REE and RQ. Results: When corrected for FFM, there was no significant difference in REE between the groups. However, fasting RQ was significantly higher in the men with schizophrenia than the controls. Conclusion: Men with schizophrenia oxidised proportionally less fat and more carbohydrate under resting conditions than healthy controls. These differences in substrate utilisation at rest may be an important consideration in obesity in this clinical group.
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In both developed and developing countries, increased prevalence of obesity has been strongly associated with increased incidence of type 2 diabetes mellitus (T2DM) in the adult population. Previous research has emphasized the importance of physical activity in the prevention and management of obesity and T2DM, and generic exercise guidelines originally developed for the wider population have been adapted for these specific populations. However, the guidelines traditionally focus on aerobic training without due consideration to other exercise modalities. Recent reviews on resistance training in the T2DM population have not compared this modality with others including aerobic training, or considered the implications of resistance training for individuals suffering from both obesity and T2DM. In short, the optimal mix of exercise modalities in the prescription of exercise has not been identified for it benefits to the metabolic, body composition and muscular health markers common in obesity and T2DM. Similarly, the underlying physical, social and psychological barriers to adopting and maintaining exercise, with the potential to undermine the efficacy of exercise interventions, have not been addressed in earlier reviews. Because it is well established that aerobic exercise has profound effects on obesity and T2DM risk, the purpose of this review was to address the importance of resistance training to obese adults with T2DM.