97 resultados para Body weight change and diet
em Queensland University of Technology - ePrints Archive
Resumo:
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.
Resumo:
European American (EA) women report greater body dissatisfaction and less dietary control than do African American (AA) women. This study investigated whether ethnic differences in dieting history contributed to differences in body dissatisfaction and dietary control, or to differential changes that may occur during weight loss and regain. Eighty-nine EA and AA women underwent dual-energy X-ray absorptiometry to measure body composition and completed questionnaires to assess body dissatisfaction and dietary control before, after, and one year following, a controlled weight-loss intervention. While EA women reported a more extensive dieting history than AA women, this difference did not contribute to ethnic differences in body dissatisfaction and perceived dietary control. During weight loss, body satisfaction improved more for AA women, and during weight regain, dietary self-efficacy worsened to a greater degree for EA women. Ethnic differences in dieting history did not contribute significantly to these differential changes. Although ethnic differences in body image and dietary control are evident prior to weight loss, and some change differentially by ethnic group during weight loss and regain, differences in dieting history do not contribute significantly to ethnic differences in body image and dietary control.
Resumo:
In many countries, governments and health agencies are strongly promoting physical activity as a means to prevent the accumulation of fatness that leads to weight gain and obesity. However, there is often a resistance to respond to health promotion initiatives. For example, in the UK, the Chief Medical Officer has recently reported that 71% of women and 61% of men fail to carry out even the minimal amount of physical activity recommended in the government’s guidelines. Similarly, the Food safety Agency has promoted reductions in the intake of fat, sugar and salt but with very little impact on the pattern of consumption. Why is it that recommendations to improve health are so difficult to implement, and produce the desired outcome?
Resumo:
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
Resumo:
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.
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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.
Resumo:
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.
Interaction between disinhibition and restraint: Implications for body weight and eating disturbance
Resumo:
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.
Resumo:
Aim: Maternal obesity is associated with increased risk of adverse outcomes for mothers and offspring. Strategies to better manage maternal obesity are urgently needed; however, there is little evidence to assist the development of nutrition interventions during antenatal care. The present study aimed to assess maternal weight gain and dietary intakes of overweight and obese women participating in an exercise trial. Results will assist the development of interventions for the management of maternal overweight and obesity. Methods: Fifty overweight and obese pregnant women receiving antenatal care were recruited and provided dietary and weight data at baseline (12 weeks), 28 weeks, 36 weeks gestation and 6 weeks post-partum. Data collected were compared with current nutritional and weight gain recommendations. Associations used Pearson's correlation coefficient, and ANOVA assessed dietary changes over time, P < 0.05. Results: Mean prepregnancy body mass index was 34.4 ± 6.6 kg/m2. Gestational weight gain was 10.6 ± 6 kg with a wide range (−4.1 to 23.0 kg). 52% of women gained excessive weight (>11.5 kg for overweight and >9 kg for obese women). Gestational weight gain correlated with post-partum weight retention (P < 0.001). Dietary intakes did not change significantly during pregnancy. No women achieved dietary fat or dietary iron recommendations, only 11% achieved adequate dietary folate, and 38% achieved adequate dietary calcium. Very few women achieved recommended food group servings for pregnancy, with 83% consuming excess servings of non-core foods. Conclusion: Results provide evidence that early intervention and personalised support for obese pregnant women may help achieve individualised goals for maternal weight gain and dietary adequacy, but this needs to be tested in a clinical setting.
Resumo:
Background It is evident from previous research that the role of dietary composition in relation to the development of childhood obesity remains inconclusive. Several studies investigating the relationship between body mass index (BMI), waist circumference (WC) and/or skin fold measurements with energy intake have suggested that the macronutrient composition of the diet (protein, carbohydrate, fat) may play an important contributing role to obesity in childhood as it does in adults. This study investigated the possible relationship between BMI and WC with energy intake and percentage energy intake from macronutrients in Australian children and adolescents. Methods Height, weight and WC measurements, along with 24 h food and drink records (FDR) intake data were collected from 2460 boys and girls aged 5-17 years living in the state of Queensland, Australia. Results Statistically significant, yet weak correlations between BMI z-score and WC with total energy intake were observed in grades 1, 5 and 10, with only 55% of subjects having a physiologically plausible 24 hr FDR. Using Pearson correlations to examine the relationship between BMI and WC with energy intake and percentage macronutrient intake, no significant correlations were observed between BMI z-score or WC and percentage energy intake from protein, carbohydrate or fat. One way ANOVAs showed that although those with a higher BMI z-score or WC consumed significantly more energy than their lean counterparts. Conclusion No evidence of an association between percentage macronutrient intake and BMI or WC was found. Evidently, more robust longitudinal studies are needed to elucidate the relationship linking obesity and dietary intake.
Resumo:
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.