998 resultados para portfolio adjustment weight


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O objetivo deste trabalho é compreender a etapa de ajuste no contexto da gestão do portfólio de projetos, destacando sua relação com os processos de categorização e balanceamento. A pesquisa realizada tem caráter qualitativo, sendo a abordagem adotada o estudo de caso longitudinal. A pesquisa foi desenvolvida em uma empresa do setor químico brasileiro. As evidências, de várias fontes, foram coletadas através de entrevistas, documentos e dados dos sistemas corporativos. Para a compreensão do portfólio de projetos da empresa foram coletados e analisados dados de mil projetos realizados entre 2001 e 2005. Os resultados indicam que maior atenção é dada à etapa de seleção, negligenciando a etapa de ajuste. A adoção de ferramentas de balanceamento permitiu evidenciar lacunas e fontes de desbalanceamento no portfólio de projetos, promovendo o debate entre os tomadores de decisão no que concerne ao viés introduzido pelos critérios adotados na etapa de seleção e levantando a necessidade de introdução de uma sistemática de ajuste e balanceamento. Observou-se que sem uma adequada categorização dos projetos da empresa seria difícil promover a análise de balanceamento.

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Objective: To develop a standard weight descriptor that can be used for estimation of patient size for obese patients. Patients and methods: Data were available from 3849 patients: 2839 from oncology patients (index data set) and 1010 from general medical patients (validation data set). The patients had a wide range of age (16-100 years), weight (25-165kg) and body mass index (BMI) [12-52 kg/m(2)] in both data sets. From the normal-weight patients in the oncology data set, an equation for male and female patients was developed to predict their normal weight as the sum of the lean body mass and normal fat body mass. The equations were evaluated by predicting the weight of patients in the general medical data set who had a normal BMI (30 kg/m(2)).

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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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Objective: We investigated to what extent changes in metabolic rate and composition of weight loss explained the less-than-expected weight loss in obese men and women during a diet-plus-exercise intervention. Design: 16 obese men and women (41 ± 9 years; BMI 39 ± 6 kg/m2) were investigated in energy balance before, after and twice during a 12-week VLED (565–650 kcal/day) plus exercise (aerobic plus resistance training) intervention. The relative energy deficit (EDef) from baseline requirements was severe (74-87%). Body composition was measured by deuterium dilution and DXA and resting metabolic rate (RMR) by indirect calorimetry. Fat mass (FM) and fat-free mass (FFM) were converted into energy equivalents using constants: 9.45 kcal/gFM and 1.13 kcal/gFFM. Predicted weight loss was calculated from the energy deficit using the '7700 kcal/kg rule'. Results: Changes in weight (-18.6 ± 5.0 kg), FM (-15.5 ± 4.3 kg), and FFM (-3.1 ± 1.9 kg) did not differ between genders. Measured weight loss was on average 67% of the predicted value, but ranged from 39 to 94%. Relative EDef was correlated with the decrease in RMR (R=0.70, P<0.01) and the decrease in RMR correlated with the difference between actual and expected weight loss (R=0.51, P<0.01). Changes in metabolic rate explained on average 67% of the less-than-expected weight loss, and variability in the proportion of weight lost as FM accounted for a further 5%. On average, after adjustment for changes in metabolic rate and body composition of weight lost, actual weight loss reached 90% of predicted values. Conclusion: Although weight loss was 33% lower than predicted at baseline from standard energy equivalents, the majority of this differential was explained by physiological variables. While lower-than-expected weight loss is often attributed to incomplete adherence to prescribed interventions, the influence of baseline calculation errors and metabolic down-regulation should not be discounted.

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The importance of modelling correlation has long been recognised in the field of portfolio management, with largedimensional multivariate problems increasingly becoming the focus of research. This paper provides a straightforward and commonsense approach toward investigating a number of models used to generate forecasts of the correlation matrix for large-dimensional problems.We find evidence in favour of assuming equicorrelation across various portfolio sizes, particularly during times of crisis. During periods of market calm, however, the suitability of the constant conditional correlation model cannot be discounted, especially for large portfolios. A portfolio allocation problem is used to compare forecasting methods. The global minimum variance portfolio and Model Confidence Set are used to compare methods, while portfolio weight stability and relative economic value are also considered.

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Objectives: To identify demographic and socioeconomic determinants of need for acute hospital treatment at small area level. To establish whether there is a relation between poverty and use of inpatient services. To devise a risk adjustment formula for distributing public funds for hospital services using, as far as possible, variables that can be updated between censuses. Design: Cross sectional analysis. Spatial interactive modelling was used to quantify the proximity of the population to health service facilities. Two stage weighted least squares regression was used to model use against supply of hospital and community services and a wide range of potential needs drivers including health, socioeconomic census variables, uptake of income support and family credit, and religious denomination. Setting: Northern Ireland. Main outcome measure: Intensity of use of inpatient services. Results: After endogeneity of supply and use was taken into account, a statistical model was produced that predicted use based on five variables: income support, family credit, elderly people living alone, all ages standardised mortality ratio, and low birth weight. The main effect of the formula produced is to move resources from urban to rural areas. Conclusions: This work has produced a population risk adjustment formula for acute hospital treatment in which four of the five variables can be updated annually rather than relying on census derived data. Inclusion of the social security data makes a substantial difference to the model and to the results produced by the formula.

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This article explores the literature concerning responses to pain of both premature and term-born newborn infants, the evidence for short-term and long-term effects of pain, and behavioral sequelae in individuals who have experienced repeated early pain in neonatal life as they mature. There is no doubt that pain causes stress in babies and this in turn may adversely affect long-term neurodevelopmental outcome. Although there are methods for assessing dimensions of acute reactivity to pain in an experimental setting, there are no very good measures available at the present time that can be used clinically. In the clinical setting repeated or chronic pain is more likely the norm rather than infrequent discrete noxious stimuli of the sort that can be readily studied. The wind-up phenomenon suggests that, exposed to a cascade of procedures as happens with clustering of care in the clinical setting in an attempt to provide periods of rest for stressed babies, an infant may in fact perceive procedures that are not normally viewed as noxious, as pain. Pain exposure during lifesaving intensive medical care of ELBW neonates may also affect subsequent reactivity to pain in the neonatal period, but behavioral differences are probably not likely to be clinically significant in the long term. Prolonged and repeated untreated pain in the newborn period, however, may produce a relatively permanent shift in basal autonomic arousal related to prior NICU pain experience, which may have long-term sequelae. In the long run, the most significant clinical effects of early pain exposure may be on neurodevelopment, contributing to later attention, learning, and behavior problems in these vulnerable children. Although there is considerable evidence to support a variety of adverse effects of early pain, there is less information about the long-term effects of opiates and benzodiazepines on the developing central nervous system. Current evidence reviewed suggests that judicious use of morphine for adjustment to mechanical ventilation may ameliorate the altered autonomic response. It may be very important, however, to distinguish stress from pain. Animal evidence suggests that the neonatal brain is affected differently when exposed to morphine administered in the absence of pain than in the presence of pain. Pain control may be important for many reasons but overuse of morphine or benzodiazepines may have undesirable long-term effects. This is a rapidly evolving area of knowledge of clear relevance to clinical management likely to affect long-term outcomes of high-risk children.

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Double Degree. A Work Project presented as part of the requirements for the Award of a Masters Degree in Management from the NOVA – School of Business and Economics and a Masters Degree in Finance from Louvain School of Management

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As a background document for Bruegel Policy Contribution 2012/11 ‘Compositional effects on productivity, labour cost and export adjustment’, this working paper presents detailed results for 24 EU countries on: • The sectoral changes in the economy; • The unit labour costs (ULC) based real effective exchange rate (REER) and its main components; • Export performance. • The ULC-REERs are calculated: • For the total economy, the business sector (excluding agriculture, construction and real estate activities), and some main sectors; • Using both actual aggregates and fixed-weight aggregates, as the latter are free from the impacts of compositional changes; • Against 30 trading partners and against three subsets of trading partners: euro-area, non-euro area EU, non-EU.

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In estimating the inputs into the Modern Portfolio Theory (MPT) portfolio optimisation problem, it is usual to use equal weighted historic data. Equal weighting of the data, however, does not take account of the current state of the market. Consequently this approach is unlikely to perform well in any subsequent period as the data is still reflecting market conditions that are no longer valid. The need for some return-weighting scheme that gives greater weight to the most recent data would seem desirable. Therefore, this study uses returns data which are weighted to give greater weight to the most recent observations to see if such a weighting scheme can offer improved ex-ante performance over that based on un-weighted data.

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It has been proposed that low birth weight is associated with high levels of blood pressure in later life. The aim of this study was to assess the relationship of blood pressure to birth weight and current body size during growth and adulthood. A total of 711 female multiple births, with one group of 244 in their growth phase mean age 12.0 (2.3)(SD) years and the other of 467 adults (mean age 35.2 (12.6) years), had height, weight and both systolic (SBP) and diastolic (DBP) blood pressures measured, and self-reported their birth weight. Regression analyses were performed to assess the cross-sectional and within-pair associations of blood pressure to birth weight, with and without adjustments for current body size. Within-pair analysis was based on 296 twin pairs. Cross-sectionally, a reduction in birth weight of 1 kg was associated with 2 to 3 mm Hg higher age-adjusted SBP, which was of marginal significance and explained about 2% of the population variance. Adjustment for body mass index did not significantly change this association. Within-pair analyses found no association between birth weight and SBP or DBP,even after adjusting for current body size. After age, current body size was the strongest predictor of systolic BP. The weak association of blood pressure to birth weight cross-sectionally is of interest, but any within-pair effect of birth weight on blood pressure must be minimal compared with the effect of current body size.

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OBJECTIVES: (1) To study the relationship between quality of life (QoL) and measured and perceived weight and dieting history in Dutch men and women; (2) to assess the effect of weight loss over a 5 y period on QoL.

DESIGN: A cross-sectional study, in a sub-sample longitudinal over 5 y.

SUBJECTS:
A total of 2155 men and 2446 women, aged 20-59 and recruited from the general population from three towns in The Netherlands.

MEASUREMENTS: Body weight, height, self-administered questionnaire including questions concerning demographic variables and weight loss practices as part of the Dutch Monitoring project on Risk Factors for Chronic Disease (MORGEN). The Rand-36 questionnaire was used as the QoL measure.

RESULTS: In men, measured overweight (body mass index, BMI>25 kg=m2) was not associated with any dimension of QoL after adjustment for age, educational level and perceived overweight. Perceived overweight was related to reduced scores for general health and vitality. This relationship was independent of measured obesity. A history of repeated weight loss was associated with reduced scores for role functioning due to both physical and emotional problems. In women, measured overweight was significantly associated with lower scores for five out of eight QoL dimensions and perceived overweight with three: general health, vitality and physical functioning. A history of frequent weight loss was related to significantly reduced scores in six dimensions. However, only with history of frequent weight loss, and uniquely in women, was there a significant reduction in
scores on mental health and limited emotional role functioning. Measured and perceived overweight and frequent weight loss were all related to reduced scores for physical functioning. Longitudinal data indicate that in older women weight gain of 10% body weight or more was associated with a significant deterioration in QoL.

CONCLUSIONS: When looking at measures of QoL in relation to overweight it is important to separate the effects of perception of weight status and history of weight loss. We observed that the latter two factors were associated with reduced scores on several dimensions of QoL, particularly in women. These associations were observed to be independent of body weight. International Journal of Obesity (2001) 25, 1386 – 1392

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Objective: The aims of this study were to estimate average yearly weight gain in midage women and to identify the determinants of weight gain and gaining weight at double the average rate.
Research Methods and Procedures: The study sample comprised 8071 participants (45 to 55 years old) in the Australian Longitudinal Study on Women's Health who completed mailed surveys in 1996, 1998, and 2001.
Results: On average, the women gained almost 0.5 kg per year [average 2.42 kg (95% confidence interval, 2.29 to 2.54) over 5 years]. In multivariate analyses, variables associated with energy balance (physical activity, sitting time, and energy intake), as well as quitting smoking, menopause/hysterectomy, and baseline BMI category were significantly associated with weight gain, but other behavioral and demographic characteristics were not. After adjustment for all of the other biological and behavioral variables, the odds of gaining weight at about twice the average rate (>5 kg over 5 years) were highest for women who quit smoking (odds ratio = 2.94; 95% confidence interval, 2.17, 3.96). There were also independent relationships between the odds of gaining >5 kg and lower levels of habitual physical activity, more time spent sitting, energy intake (but only in women with BMI > 25 at baseline), menopause transition, and hysterectomy.
Discussion: The average weight gain equates with an energy imbalance of only about 10 kcal or 40 kJ per day, which suggests that small sustained changes in the modifiable behavioral variables could prevent further weight gain.


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Objective: To estimate variation between small areas in adult body mass index (BMI), and assess the importance of area level socioeconomic disadvantage in predicting BMI.

Methods: We identified all census collector districts (CCDs) in the 20 innermost Local Government Areas in metropolitan Melbourne, Australia, and ranked them by the percentage of low income households (<$400/week). In all, 50 CCDs were randomly selected from the least, middle and most disadvantaged septiles of the ranked list and 4913 residents (61.4% participation rate) completed one of two surveys. Multilevel linear regression was used to estimate area level variance in BMI and the importance of area level socioeconomic disadvantage in predicting BMI.

Results: There were significant variations in BMI between CCDs for women, even after adjustment for individual and area SES (P=0.012); significant area variation was not found for men. Living in the most versus least disadvantaged areas was associated with an average difference in BMI of 1.08 kg/m2 (95% CI: 0.48–1.68 kg/m2) for women, and of 0.93 kg/m2 (95% CI: 0.32–1.55 kg/m2) for men. Living in the mid versus least disadvantaged areas were associated with an average difference in BMI of 0.67 kg/m2 (95% CI: 0.09–1.26 kg/m2) for women, and 0.43 kg/m2 for men (95% CI: -0.16–1.01).

Conclusion:
These findings suggest that area disadvantage is an important predictor of adult BMI, and support the need to focus on improving local environments to reduce socioeconomic inequalities in overweight and obesity.