136 resultados para Lean Sigma
Resumo:
The term "Social and Emotional Wellbeing" (SEWB) was coined through the noted inability of conventional psychiatric terminology when addressing Indigenous holistic connections and opposes the Anglo-Saxon terminology that often boxes "mental health" as a diagnosis, disease or illness into separate origins from that of other personal holistic existence, which in turn directly objects to Indigenous thinking and perceptions of wellbeing. Purpose: This study's aim was to explore what Indigenous Women's Social and Emotional Wellbeing is, through Indigenous perceptions, beliefs and knowledge of Indigenous women's wellbeing experiences. Methods: Data was derived from semi-structured focus groups incorporating Indigenous specific Yarning, where Aboriginal and Torres Strait Islander women who have experienced or were at risk of developing social and emotional wellness problems came together. Results: The women identified many factors underpinning social and emotional wellness and what it means for Aboriginal and Torres Strait Islander women. The major themes centred around wellness and health, autonomy, Indigenous women being heard, historical factors, support and Indigenous women's group development and continuation. Conclusion: These issues where then explored and compared to the National Aboriginal and Torres Strait Islander Women's Health Strategy Action Areas.
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Objectives In non-alcoholic fatty liver disease (NAFLD), hepatic steatosis is intricately linked with a number of metabolic alterations. We studied substrate utilisation in NAFLD during basal, insulin-stimulated and exercise conditions, and correlated these outcomes with disease severity. Methods 20 patients with NAFLD (mean±SD body mass index (BMI) 34.1±6.7 kg/m2) and 15 healthy controls (BMI 23.4±2.7 kg/m2) were assessed. Respiratory quotient (RQ), whole-body fat (Fatox) and carbohydrate (CHOox) oxidation rates were determined by indirect calorimetry in three conditions: basal (resting and fasted), insulin-stimulated (hyperinsulinaemic–euglycaemic clamp) and exercise (cycling at an intensity to elicit maximal Fatox). Severity of disease and steatosis were determined by liver histology, hepatic Fatox from plasma β-hydroxybutyrate concentrations, aerobic fitness expressed as , and visceral adipose tissue (VAT) measured by computed tomography. Results Within the overweight/obese NAFLD cohort, basal RQ correlated positively with steatosis (r=0.57, p=0.01) and was higher (indicating smaller contribution of Fatox to energy expenditure) in patients with NAFLD activity score (NAS) ≥5 vs <5 (p=0.008). Both results were independent of VAT, % body fat and BMI. Compared with the lean control group, patients with NAFLD had lower basal whole-body Fatox (1.2±0.3 vs 1.5±0.4 mg/kgFFM/min, p=0.024) and lower basal hepatic Fatox (ie, β-hydroxybutyrate, p=0.004). During exercise, they achieved lower maximal Fatox (2.5±1.4 vs. 5.8±3.7 mg/kgFFM/min, p=0.002) and lower (p<0.001) than controls. Fatox during exercise was not associated with disease severity (p=0.79). Conclusions Overweight/obese patients with NAFLD had reduced hepatic Fatox and reduced whole-body Fatox under basal and exercise conditions. There was an inverse relationship between ability to oxidise fat in basal conditions and histological features of NAFLD including severity of steatosis and NAS
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Context: Postprandial dysmetabolism is emerging as an important cardiovascular risk factor. Augmentation index (AIx) is a measure of systemic arterial stiffness and independently predicts cardiovascular outcome. Objective: The objective of this study was to assess the effect of a standardized high-fat meal on metabolic parameters and AIx in 1) lean, 2) obese nondiabetic, and 3) subjects with type 2 diabetes mellitus (T2DM). Design and Setting: Male subjects (lean, n = 8; obese, n = 10; and T2DM, n = 10) were studied for 6 h after a high-fat meal and water control. Glucose, insulin, triglycerides, and AIx (radial applanation tonometry) were measured serially to determine the incremental area under the curve (iAUC). Results: AIx decreased in all three groups after a high-fat meal. A greater overall postprandial reduction in AIx was seen in lean and T2DM compared with obese subjects (iAUC, 2251 +/- 1204, 2764 +/- 1102, and 1187 +/- 429% . min, respectively; P < 0.05). The time to return to baseline AIx was significantly delayed in subjects with T2DM (297 +/- 68 min) compared with lean subjects (161 +/- 88 min; P < 0.05). There was a significant correlation between iAUC AIx and iAUC triglycerides (r = 0.50; P < 0.05). Conclusions: Obesity is associated with an attenuated overall postprandial decrease in AIx. Subjects with T2DM have a preserved, but significantly prolonged, reduction in AIx after a high-fat meal. The correlation between AIx and triglycerides suggests that postprandial dysmetabolism may impact on vascular dynamics. The markedly different response observed in the obese subjects compared with those with T2DM was unexpected and warrants additional evaluation.
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Combating unhealthy weight gain is a major public health and clinical management issue. The extent of research into the etiology and pathophysiology of obesity has produced a wealth of evidence regarding the contributing factors. While aspects of the environment are ‘obesogenic’, weight gain is not inevitable for every individual. What then explains potentially unhealthy weight gain in individuals living within an environment where others remain lean? In this paper we explore the biological compensation that acts in response to a reduced energy intake by reducing energy needs, in order to defend against weight loss. We then examine the evidence that there is only a weak biological compensation to surplus energy supply, and that this allows behavior to drive weight gain. The extent to which biology impacts behavior is also considered.
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Purpose: Type 2 diabetes is a leading cause of morbidity and mortality in midlife and older Australian women with known modifiable risk factors for type 2 diabetes including smoking, nutrition, physical activity and obesity. In Australia little research has been done to investigate the perceived barriers to healthy lifestyle activities in midlife and older women with type 2 diabetes. The primary aim of this study was to explore the level and type of perceived barriers to health promotion activities. The secondary aim was to explore the relationship of perceived barriers to smoking behaviour, fruit and vegetable intake, physical activity, and body mass index. Methods: The study was a cross sectional survey of women, aged over 45 with type 2 diabetes, attending metropolitan community health clinics (N = 41). Data was collected from self-report questionnaire and analysed using descriptive and inferential statistics. Results: Women in the study had average total barriers scores similar to those reported in the literature for women with a range of physical disabilities and illnesses. The leading barriers for this group of women were: lack of interest, concern about safety, too tired, lack of money and feeling what they do does not help. There was no association between total barriers scores and body mass index, physical activity, fruit and vegetable intake or socio-demographic variables. Conclusion: This study contributes to understanding the perceptions of midlife and older women with type 2 diabetes about the level and type of barriers to healthy lifestyle activities that they experience. Evidence from this study can be applied to inform health promotion for lifestyle risk factor reduction in women with type 2 diabetes.
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Diet Induced Thermogenesis (DIT) is the energy expended consequent to meal consumption, and reflects the energy required for the processing and digestion of food consumed throughout each day. Although DIT is the total energy expended across a day in digestive processes to a number of meals, most studies measure thermogenesis in response to a single meal (Meal Induced Thermogenesis: MIT) as a representation of an individual’s thermogenic response to acute food ingestion. As a component of energy expenditure, DIT may have a contributing role in weight gain and weight loss. While the evidence is inconsistent, research has tended to reveal a suppressed MIT response in obese compared to lean individuals, which identifies individuals with an efficient storage of food energy, hence a greater tendency for weight gain. Appetite is another factor regulating body weight through its influence on energy intake. Preliminary research has shown a potential link between MIT and postprandial appetite as both are responses to food ingestion and have a similar response dependent upon the macronutrient content of food. There is a growing interest in understanding how both MIT and appetite are modified with changes in diet, activity levels and body size. However, the findings from MIT research have been highly inconsistent, potentially due to the vastly divergent protocols used for its measurement. Therefore, the main theme of this thesis was firstly, to address some of the methodological issues associated with measuring MIT. Additionally this thesis aimed to measure postprandial appetite simultaneously to MIT to test for any relationships between these meal-induced variables and to assess changes that occur in MIT and postprandial appetite during periods of energy restriction (ER) and following weight loss. Two separate studies were conducted to achieve these aims. Based on the increasing prevalence of obesity, it is important to develop accurate methodologies for measuring the components potentially contributing to its development and to understand the variability within these variables. Therefore, the aim of Study One was to establish a protocol for measuring the thermogenic response to a single test meal (MIT), as a representation of DIT across a day. This was done by determining the reproducibility of MIT with a continuous measurement protocol and determining the effect of measurement duration. The benefit of a fixed resting metabolic rate (RMR), which is a single measure of RMR used to calculate each subsequent measure of MIT, compared to separate baseline RMRs, which are separate measures of RMR measured immediately prior to each MIT test meal to calculate each measure of MIT, was also assessed to determine the method with greater reproducibility. Subsidiary aims were to measure postprandial appetite simultaneously to MIT, to determine its reproducibility between days and to assess potential relationships between these two variables. Ten healthy individuals (5 males, 5 females, age = 30.2 ± 7.6 years, BMI = 22.3 ± 1.9 kg/m2, %Fat Mass = 27.6 ± 5.9%) undertook three testing sessions within a 1-4 week time period. During the first visit, participants had their body composition measured using DXA for descriptive purposes, then had an initial 30-minute measure of RMR to familiarise them with the testing and to be used as a fixed baseline for calculating MIT. During the second and third testing sessions, MIT was measured. Measures of RMR and MIT were undertaken using a metabolic cart with a ventilated hood to measure energy expenditure via indirect calorimetry with participants in a semi-reclined position. The procedure on each MIT test day was: 1) a baseline RMR measured for 30 minutes, 2) a 15-minute break in the measure to consume a standard 576 kcal breakfast (54.3% CHO, 14.3% PRO, 31.4% FAT), comprising muesli, milk toast, butter, jam and juice, and 3) six hours of measuring MIT with two, ten-minute breaks at 3 and 4.5 hours for participants to visit the bathroom. On the MIT test days, pre and post breakfast then at 45-minute intervals, participants rated their subjective appetite, alertness and comfort on visual analogue scales (VAS). Prior to each test, participants were required to be fasted for 12 hours, and have undertaken no high intensity physical activity for the previous 48 hours. Despite no significant group changes in the MIT response between days, individual variability was high with an average between-day CV of 33%, which was not significantly improved by the use of a fixed RMR to 31%. The 95% limits of agreements which ranged from 9.9% of energy intake (%EI) to -10.7%EI with the baseline RMRs and between 9.6%EI to -12.4%EI with the fixed RMR, indicated very large changes relative to the size of the average MIT response (MIT 1: 8.4%EI, 13.3%EI; MIT 2: 8.8%EI, 14.7%EI; baseline and fixed RMRs respectively). After just three hours, the between-day CV with the baseline RMR was 26%, which may indicate an enhanced MIT reproducibility with shorter measurement durations. On average, 76, 89, and 96% of the six-hour MIT response was completed within three, four and five hours, respectively. Strong correlations were found between MIT at each of these time points and the total six-hour MIT (range for correlations r = 0.990 to 0.998; P < 0.01). The reproducibility of the proportion of the six-hour MIT completed at 3, 4 and 5 hours was reproducible (between-day CVs ≤ 8.5%). This indicated the suitability to use shorter durations on repeated occasions and a similar percent of the total response to be completed. There was a lack of strong evidence of any relationship between the magnitude of the MIT response and subjective postprandial appetite. Given a six-hour protocol places a considerable burden on participants, these results suggests that a post-meal measurement period of only three hours is sufficient to produce valid information on the metabolic response to a meal. However while there was no mean change in MIT between test days, individual variability was large. Further research is required to better understand which factors best explain the between-day variability in this physiological measure. With such a high prevalence of obesity, dieting has become a necessity to reduce body weight. However, during periods of ER, metabolic and appetite adaptations can occur which may impede weight loss. Understanding how metabolic and appetite factors change during ER and weight loss is important for designing optimal weight loss protocols. The purpose of Study Two was to measure the changes in the MIT response and subjective postprandial appetite during either continuous (CONT) or intermittent (INT) ER and following post diet energy balance (post-diet EB). Thirty-six obese male participants were randomly assigned to either the CONT (Age = 38.6 ± 7.0 years, weight = 109.8 ± 9.2 kg, % fat mass = 38.2 ± 5.2%) or INT diet groups (Age = 39.1 ± 9.1 years, weight = 107.1 ± 12.5 kg, % fat mass = 39.6 ± 6.8%). The study was divided into three phases: a four-week baseline (BL) phase where participants were provided with a diet to maintain body weight, an ER phase lasting either 16 (CONT) or 30 (INT) weeks, where participants were provided with a diet which supplied 67% of their energy balance requirements to induce weight loss and an eight-week post-diet EB phase, providing a diet to maintain body weight post weight loss. The INT ER phase was delivered as eight, two-week blocks of ER interspersed with two-week blocks designed to achieve weight maintenance. Energy requirements for each phase were predicted based on measured RMR, and adjusted throughout the study to account for changes in RMR. All participants completed MIT and appetite tests during BL and the ER phase. Nine CONT and 15 INT participants completed the post-diet EB MIT and 14 INT and 15 CONT participants completed the post-diet EB appetite tests. The MIT test day protocol was as follows: 1) a baseline RMR measured for 30 minutes, 2) a 15-minute break in the measure to consume a standard breakfast meal (874 kcal, 53.3% CHO, 14.5% PRO, 32.2% FAT), and 3) three hours of measuring MIT. MIT was calculated as the energy expenditure above the pre-meal RMR. Appetite test days were undertaken on a separate day using the same 576 kcal breakfast used in Study One. VAS were used to assess appetite pre and post breakfast, at one hour post breakfast then a further three times at 45-minute intervals. Appetite ratings were calculated for hunger and fullness as both the intra-meal change in appetite and the AUC. The three-hour MIT response at BL, ER and post-diet EB respectively were 5.4 ± 1.4%EI, 5.1 ± 1.3%EI and 5.0 ± 0.8%EI for the CONT group and 4.4 ± 1.0%EI, 4.7 ± 1.0%EI and 4.8 ± 0.8%EI for the INT group. Compared to BL, neither group had significant changes in their MIT response during ER or post-diet EB. There were no significant time by group interactions (p = 0.17) indicating a similar response to ER and post-diet EB in both groups. Contrary to what was hypothesised, there was a significant increase in postprandial AUC fullness in response to ER in both groups (p < 0.05). However, there were no significant changes in any of the other postprandial hunger or fullness variables. Despite no changes in MIT in both the CONT or INT group in response to ER or post-diet EB and only a minor increase in postprandial AUC fullness, the individual changes in MIT and postprandial appetite in response to ER were large. However those with the greatest MIT changes did not have the greatest changes in postprandial appetite. This study shows that postprandial appetite and MIT are unlikely to be altered during ER and are unlikely to hinder weight loss. Additionally, there were no changes in MIT in response to weight loss, indicating that body weight did not influence the magnitude of the MIT response. There were large individual changes in both variables, however further research is required to determine whether these changes were real compensatory changes to ER or simply between-day variation. Overall, the results of this thesis add to the current literature by showing the large variability of continuous MIT measurements, which make it difficult to compare MIT between groups and in response to diet interventions. This thesis was able to provide evidence to suggest that shorter measures may provide equally valid information about the total MIT response and can therefore be utilised in future research in order to reduce the burden of long measurements durations. This thesis indicates that MIT and postprandial subjective appetite are most likely independent of each other. This thesis also shows that, on average, energy restriction was not associated with compensatory changes in MIT and postprandial appetite that would have impeded weight loss. However, the large inter-individual variability supports the need to examine individual responses in more detail.
Resumo:
Purpose: To present the results of a mixed-method study comparing the level of agreement of a two-phased, nurse-administered Comprehensive Geriatric Assessment (CGA) with current methods that assess the fitness for chemotherapy of older cancer patients. A nurse-led model of multidisciplinary cancer care based on the results is also described. Methods: The two phases comprised initial screening by a nurse with the Vulnerable Elders Survey-13 [VES-13], followed by nurse administration of a detailed CGA. Both phases were linked to a computerised algorithm categorising the patient as ‘fit’, ‘vulnerable’ or ‘frail’. The study determined the level of agreement between VES-13- and CGA-determined categories; and between the CGA and the physicians’ assessments. It also compared the CGA’s predictive abilities in terms of subsequent treatment toxicity; while interviews determined the acceptability of the nurse-led procedure from key stakeholders' perspectives. Results: Data collection was completed in December 2011. The results will be presented at the conference. A consecutive-series n=170 will be enrolled, 33% of whom are ‘fit’; 33% ‘vulnerable’; and 33% ‘too frail’ for treatment. This sample can detect, with 90% power, kappa coefficients of agreement of ≥ 0.70 or higher (“substantial agreement”). Fitness sub-group comparisons of agreement between the medical oncologist and the nurse assessments can detect kappa estimates of Κ ≥ 0.80 with the same power. Conclusion: The results have informed a nurse-led model of cancer care. It meets a clear need to develop, implement and test a nurse-led, robust, evidence-based, clinically-justifiable and economically-feasible CGA process that has relevance in national and international contexts.
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The focus of nutrition is often on healthy diets and exercise to minimise the risk of developing lifestyle diseases such as cancer, diabetes and cardiovascular disease. However, during the shift into older years often the nutrition priorities change towards meeting increased nutrient needs with less energy requirements and minimising lean muscle loss. There are several causes of general malnutrition in the elderly that lead to depletion of muscle including starvation (protein-energy malnutrition), sarcopenia and cachexia. The prevalence of protein-energy malnutrition increases with age and the number of comorbidities. A range of simple and validated screening tools can be used to identify malnutrition in older adults e.g. MST, MNA-SF and ‘MUST’. Older adults should be screened for nutritional issues at diagnosis, on admission to hospitals or care homes and during follow up at outpatient or General Practitioner clinics, at regular intervals depending on clinical status. Early identification and treatment of nutrition problems can lead to improved outcomes and better quality of life.
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RFLPs at the low density lipoprotein receptor locus (LDLR) display marked linkage disequilibrium between each other. Cross-sectional analysis of a bi-alleleic ApaLI RFLP of LDLR showed that the 9.4- and 6.6-kb alleles were present in similar frequency between a group of 84 Caucasian essential hypertensive (HT) and a group of 96 normotensive subjects whose parents each had a similar blood pressure status at age > or = 50. After subdividing HTs into lean and obese, however, the frequency of the 6.6-kb allele in the 27 HTs with BMI > or = 26 kg/m2 was 0.63, compared with 0.39 for HTs with BMI < 26 (chi 2 = 8.8; P = 0.004). The difference in genotype frequencies was even more striking (chi 2 = 23; P = 0.00008), with a virtual absence of 9.4-kb homozygotes in the obese HT group (1 vs 22). Genetic variation at LDLR (19p13.2) is thus associated with obesity in HT.
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1. The low density lipoprotein receptor is an important regulator of serum cholesterol which may have implications for the development of both hypertension and obesity. In this study, genotypes for a low density lipoprotein receptor gene (LDLR) dinucleotide polymorphism were determined in both lean and obese normotensive populations. 2. In previous cross-sectional association studies an ApaLI and a HincII polymorphism for LDLR were shown to be associated with obesity in essential hypertensives. However, these polymorphisms did not show an association with obesity in normotensives. 3. In contrast, this study reports that preliminary results for an LDLR microsatellite marker, located more towards the 3' end of the gene, show a significant association with obesity in the normotensive population studied. These results indicate that LDLR could play an important role in the development of obesity, which might be independent of hypertension.
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1. Previous glucagon receptor gene (GCGR) studies have shown a Gly40Ser mutation to be more prevalent in essential hypertension and to affect glucagon binding affinity to its receptor. An Alu-repeat poly(A) polymorphism colocalized to GCGR was used in the present study to test for association and linkage in hypertension as well as association in obesity development. 2. Using a cross-sectional approach, 85 hypertensives and 95 normotensives were genotyped using polymerase chain reaction primers flanking the Alu-repeat. Both hypertensive and normotensive populations were subdivided into lean and obese categories based on body mass index (BMI) to determine involvement of this variant in obesity. For the linkage study, 89 Australian Caucasian hypertension affected sibships (174 sibpairs) were genotyped and the results were analysed using GENE-HUNTER, Mapmaker Sibs, ERPA and SPLINK (all freely available from http://linlkage.rockefeller. edu/soft/list.html). 3. Cross-sectional results for both hypertension and obesity were analysed using Chi-squared and Monte Carlo analyses. Results did not show an association of this variant with either hypertension (χ2 = 6.9, P = 0.14; Monte Carlo χ2 = 7.0, P = 0.11; n = 5000) or obesity (χ2 = 3.3, P = 0.35; Monte Carlo χ2 = 3.26, P = 0.34; n = 5000). In addition, results from the linkage study using hypertensive sib-pairs did not indicate linkage of the poly(A) repent with hypertension. Hence, results did not indicate a role far the Alu-repeat in either hypertension or obesity. However, as the heterozygosity of this poly(A) repeat is low (35%), a larger number of hypertensive sib-pairs may be required to draw definitive conclusions.