152 resultados para BODY WEIGHT CHANGE

em Queensland University of Technology - ePrints Archive


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BACKGROUND AND OBJECTIVES: College students and young adults are experiencing the greatest increases in rates of obesity, and 20% of college students are classified as obese. The objective of this study was to compare changes and rates of change in body weight and body composition between the freshman academic year and the summer after the freshman year among female college students. METHODS: Participants were recruited early in their freshman year of college to participate in a prospective longitudinal study examining changes in body weight and composition over the college years. Height and weight were measured, and body composition was assessed using dual energy x-ray absorptiometry (DEXA) at the beginning and end of the freshman year. Upon return from the summer for their sophomore year, participants returned to have all measurements repeated. Sixty-nine female participants completed all three visits. RESULTS: Body weight increased 1.3 kg during the academic period and an additional 0.1 kg during the summer period. Body mass index (BMI) increased between the first two visits but did not change between the last two visits. However, percent fat increased at each visit. Fat-free mass significantly increased 0.5 kg over the academic year but decreased by 1.1 kg over the summer (p<0.05). Greater rates of change were detected in percent fat, fat-free mass, and BMI during the summer compared with the academic year (p<0.05). CONCLUSIONS: Differences in body composition between the academic and summer periods may reflect changes in living situations between these periods. Unfavorable changes during the summer suggest the need to promote healthy lifestyles to freshman women before they leave campus for the summer

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Objective. To estimate the burden of disease attributable to excess body weight using the body mass index (BMI), by age and sex, in South Africa in 2000. Design. World Health Organization comparative risk assessment (CRA) methodology was followed. Re-analysis of the 1998 South Africa Demographic and Health Survey data provided mean BMI estimates by age and sex. Populationattributable fractions were calculated and applied to revised burden of disease estimates. Monte Carlo simulation-modelling techniques were used for the uncertainty analysis. Setting. South Africa. Subjects. Adults 30 years of age. Outcome measures. Deaths and disability-adjusted life years (DALYs) from ischaemic heart disease, ischaemic stroke, hypertensive disease, osteoarthritis, type 2 diabetes mellitus, and selected cancers. Results. Overall, 87% of type 2 diabetes, 68% of hypertensive disease, 61% of endometrial cancer, 45% of ischaemic stroke, 38% of ischaemic heart disease, 31% of kidney cancer, 24% of osteoarthritis, 17% of colon cancer, and 13% of postmenopausal breast cancer were attributable to a BMI 21 kg/m2. Excess body weight is estimated to have caused 36 504 deaths (95% uncertainty interval 31 018 - 38 637) or 7% (95% uncertainty interval 6.0 - 7.4%) of all deaths in 2000, and 462 338 DALYs (95% uncertainty interval 396 512 - 478 847) or 2.9% of all DALYs (95% uncertainty interval 2.4 - 3.0%). The burden in females was approximately double that in males. Conclusions. This study shows the importance of recognising excess body weight as a major risk to health, particularly among females, highlighting the need to develop, implement and evaluate comprehensive interventions to achieve lasting change in the determinants and impact of excess body weight.

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Background: While weight gain following breast cancer is considered common, results supporting these findings are dated. This work describes changes in body weight following breast cancer over 72 months, compares weight with normative data and explores whether weight changes over time are associated with personal, diagnostic, treatment or behavioral characteristics. Methods: A population-based sample of 287 Australian women diagnosed with early-stage invasive breast cancer was assessed prospectively at six, 12, 18 and 72 months post-surgery. Weight was clinically measured and linear mixed models were used to explore associations between weight and participant characteristics (collected via self-administered questionnaire). Those with BMI changes of one or more units were considered to have experienced clinically significant changes in weight. Results: More than half (57%) of participants were overweight or obese at 6 months post-surgery, and by 72 months post-surgery 68% of women were overweight or obese. Among those who gained more weight than age-matched norms, clinically significant weight gain between 6 and 18 months and 6 and 72 months post-surgery was observed in 24% and 39% of participants, respectively (median [range] weight gain: 3.9kg [2.0-11.3kg] and 5.2kg [0.6-28.7], respectively). Clinically-significant weight losses were observed in up to 24% of the sample (median [range] weight loss between 6 and 72 months post-surgery: -6.4kg [-1.9--24.6kg]). More extensive lymph node removal, being treated on the non-dominant side, receiving radiation therapy and lower physical activity levels at 6 months was associated with higher body weights post-breast cancer (group differences >3kg; all p<0.05). Conclusions: While average weight gain among breast cancer survivors in the long-term is small, subgroups of women experience greater gains linked with adverse health and above that experienced by age-matched counterparts. Weight change post-breast cancer is a contemporary public health issue and the integration of healthy weight education and support into standard breast cancer care has potential to significantly improve the length and quality of cancer survivorship.

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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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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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An increase in obesity is usually accompanied by an increase in eating disturbances. Susceptibility to these states may arise from different combinations of underlying traits: Three Factor Eating Questionnaire (TFEQ) Restraint and Disinhibition. Two studies were conducted to examine the interaction between these traits; one on-line study (n=351) and one laboratory-based study (n=120). Participants completed a battery of questionnaires and provided self-report measures of body weight and physical activity. A combination of high Disinhibition and high Restraint was associated with a problematic eating behaviour profile (EAT-26), and a higher rate of smoking and alcohol consumption. A combination of high Disinhibition and low Restraint was associated with a higher susceptibility to weight gain and a higher sedentary behaviour. These data show that different combinations of Disinhibition and Restraint are associated with distinct weight and behaviour outcomes.

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This thesis undertakes an empirical investigation to identify factors that influence the decision to undertake weight loss behaviour using the nationally representative HILDA dataset. Although many factors influenced the decision, the findings suggested that body weight satisfaction was the greatest determinant of weight loss dieting. This thesis therefore conducted a further empirical study to analyse the determinants of body weight satisfaction. A rank-hypothesis was found to better predict variation in body weight satisfaction levels than the absolute value of the individual's Body Mass Index (BMI) or the relative-norm hypothesis, which are commonly reported in the literature.

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Exercise has many health benefits and should be an effective weight loss strategy because it increases energy expenditure. However, the success of exercise in producing and sustaining weight loss is influenced by compensatory changes in energy intake and non-exercise activity, among other factors (see King et al. Obesity 15(6):1373–1383, 2007 for a detailed review). The aim of this chapter is to discuss the evidence describing the relationship between exercise and body weight regulation, with a particular focus on appetite control. Evidence is discussed which demonstrates that weight loss responses to exercise are highly variable between individuals. The mechanisms underlying the relationship between exercise, appetite and energy intake, and hence body weight are also discussed. Some people experience an increase in fasting hunger in response to 12 weeks of supervised exercise. However, this is offset by an increase in meal-related satiety in overweight and obese individuals. It is worth noting that weight loss should not be considered as the only successful outcome of an exercise program. Indeed, exercise, even in the absence of weight loss, is associated with numerous health benefits. Nevertheless, an improved understanding of compensatory responses to exercise is vital so that exercise can be more effectively used in weight management; such an understanding may assist us to devise strategies to sustain greater long-term participation in physical activity.

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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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Context: The magnitude of exercise-induced weight loss depends on the extent of compensatory responses. An increase in energy intake is likely to result from changes in the appetite control system toward an orexigenic environment; however, few studies have measured how exercise impacts on both orexigenic and anorexigenic peptides. ---------- Objective: The aim of the study was to investigate the effects of medium-term exercise on fasting/postprandial levels of appetite-related hormones and subjective appetite sensations in overweight/obese individuals. ---------- Design and Setting: We conducted a longitudinal study in a university research center. ---------- Participants and Intervention: Twenty-two sedentary overweight/obese individuals (age, 36.9 ± 8.3 yr; body mass index, 31.3 ± 3.3 kg/m2) took part in a 12-wk supervised exercise programme (five times per week, 75% maximal heart rate) and were requested not to change their food intake during the study. ---------- Main Outcome Measures: We measured changes in body weight and fasting/postprandial plasma levels of glucose, insulin, total ghrelin, acylated ghrelin (AG), peptide YY, and glucagon-like peptide-1 and feelings of appetite. ---------- Results: Exercise resulted in a significant reduction in body weight and fasting insulin and an increase in AG plasma levels and fasting hunger sensations. A significant reduction in postprandial insulin plasma levels and a tendency toward an increase in the delayed release of glucagon-like peptide-1 (90–180 min) were also observed after exercise, as well as a significant increase (127%) in the suppression of AG postprandially. ---------- Conclusions: Exercise-induced weight loss is associated with physiological and biopsychological changes toward an increased drive to eat in the fasting state. However, this seems to be balanced by an improved satiety response to a meal and improved sensitivity of the appetite control system.

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Purpose of review: To examine the relationship between energy intake, appetite control and exercise, with particular reference to longer term exercise studies. This approach is necessary when exploring the benefits of exercise for weight control, as changes in body weight and energy intake are variable and reflect diversity in weight loss. Recent findings: Recent evidence indicates that longer term exercise is characterized by a highly variable response in eating behaviour. Individuals display susceptibility or resistance to exercise-induced weight loss, with changes in energy intake playing a key role in determining the degree of weight loss achieved. Marked differences in hunger and energy intake exist between those who are capable of tolerating periods of exercise-induced energy deficit, and those who are not. Exercise-induced weight loss can increase the orexigenic drive in the fasted state, but for some this is offset by improved postprandial satiety signalling. Summary: The biological and behavioural responses to acute and long-term exercise are highly variable, and these responses interact to determine the propensity for weight change. For some people, long-term exercise stimulates compensatory increases in energy intake that attenuate weight loss. However, favourable changes in body composition and health markers still exist in the absence of weight loss. The physiological mechanisms that confer susceptibility to compensatory overconsumption still need to be determined.

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Understanding the relationship between diet, physical activity and health in humans requires accurate measurement of body composition and daily energy expenditure. Stable isotopes provide a means of measuring total body water and daily energy expenditure under free-living conditions. While the use of isotope ratio mass spectrometry (IRMS) for the analysis of 2H (Deuterium) and 18O (Oxygen-18) is well established in the field of human energy metabolism research, numerous questions remain regarding the factors which influence analytical and measurement error using this methodology. This thesis was comprised of four studies with the following emphases. The aim of Study 1 was to determine the analytical and measurement error of the IRMS with regard to sample handling under certain conditions. Study 2 involved the comparison of TEE (Total daily energy expenditure) using two commonly employed equations. Further, saliva and urine samples, collected at different times, were used to determine if clinically significant differences would occur. Study 3 was undertaken to determine the appropriate collection times for TBW estimates and derived body composition values. Finally, Study 4, a single case study to investigate if TEE measures are affected when the human condition changes due to altered exercise and water intake. The aim of Study 1 was to validate laboratory approaches to measure isotopic enrichment to ensure accurate (to international standards), precise (reproducibility of three replicate samples) and linear (isotope ratio was constant over the expected concentration range) results. This established the machine variability for the IRMS equipment in use at Queensland University for both TBW and TEE. Using either 0.4mL or 0.5mL sample volumes for both oxygen-18 and deuterium were statistically acceptable (p>0.05) and showed a within analytical variance of 5.8 Delta VSOW units for deuterium, 0.41 Delta VSOW units for oxygen-18. This variance was used as “within analytical noise” to determine sample deviations. It was also found that there was no influence of equilibration time on oxygen-18 or deuterium values when comparing the minimum (oxygen-18: 24hr; deuterium: 3 days) and maximum (oxygen-18: and deuterium: 14 days) equilibration times. With regard to preparation using the vacuum line, any order of preparation is suitable as the TEE values fall within 8% of each other regardless of preparation order. An 8% variation is acceptable for the TEE values due to biological and technical errors (Schoeller, 1988). However, for the automated line, deuterium must be assessed first followed by oxygen-18 as the automated machine line does not evacuate tubes but merely refills them with an injection of gas for a predetermined time. Any fractionation (which may occur for both isotopes), would cause a slight elevation in the values and hence a lower TEE. The purpose of the second and third study was to investigate the use of IRMS to measure the TEE and TBW of and to validate the current IRMS practices in use with regard to sample collection times of urine and saliva, the use of two TEE equations from different research centers and the body composition values derived from these TEE and TBW values. Following the collection of a fasting baseline urine and saliva sample, 10 people (8 women, 2 men) were dosed with a doubly labeled water does comprised of 1.25g 10% oxygen-18 and 0.1 g 100% deuterium/kg body weight. The samples were collected hourly for 12 hrs on the first day and then morning, midday, and evening samples were collected for the next 14 days. The samples were analyzed using an isotope ratio mass spectrometer. For the TBW, time to equilibration was determined using three commonly employed data analysis approaches. Isotopic equilibration was reached in 90% of the sample by hour 6, and in 100% of the sample by hour 7. With regard to the TBW estimations, the optimal time for urine collection was found to be between hours 4 and 10 as to where there was no significant difference between values. In contrast, statistically significant differences in TBW estimations were found between hours 1-3 and from 11-12 when compared with hours 4-10. Most of the individuals in this study were in equilibrium after 7 hours. The TEE equations of Prof Dale Scholler (Chicago, USA, IAEA) and Prof K.Westerterp were compared with that of Prof. Andrew Coward (Dunn Nutrition Centre). When comparing values derived from samples collected in the morning and evening there was no effect of time or equation on resulting TEE values. The fourth study was a pilot study (n=1) to test the variability in TEE as a result of manipulations in fluid consumption and level of physical activity; the magnitude of change which may be expected in a sedentary adult. Physical activity levels were manipulated by increasing the number of steps per day to mimic the increases that may result when a sedentary individual commences an activity program. The study was comprised of three sub-studies completed on the same individual over a period of 8 months. There were no significant changes in TBW across all studies, even though the elimination rates changed with the supplemented water intake and additional physical activity. The extra activity may not have sufficiently strenuous enough and the water intake high enough to cause a significant change in the TBW and hence the CO2 production and TEE values. The TEE values measured show good agreement based on the estimated values calculated on an RMR of 1455 kcal/day, a DIT of 10% of TEE and activity based on measured steps. The covariance values tracked when plotting the residuals were found to be representative of “well-behaved” data and are indicative of the analytical accuracy. The ratio and product plots were found to reflect the water turnover and CO2 production and thus could, with further investigation, be employed to identify the changes in physical activity.