985 resultados para reduced quality of life


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The epidemiology and sequelae of morphometric vertebral fracture (MVF) are poorly documented. We found that MVFs of the lower thoracic and lumbar spine were associated with poor quality of life and impaired physical function in men. We recommend that morphometric X-ray absorptiometry be included in routine requests for bone densitometry.

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Objective . To determine longitudinal relationships between body mass index (BMI) and health-related quality of life (HRQoL) in an adolescent population sample.
Design. Data collected in 2000 and 2005 within the Health of Young Victorians longitudinal cohort study.
Setting. Originally a community sample of elementary school students in Victoria, Australia. Follow-up occurred in either secondary schools or individuals homes.
Participants. Cohort recruited in 1997 via a random sampling design from Victorian elementary schools. Originally comprising 1 943 children, 1 569 (80.8%) participated in 2000 (wave 2, 8 – 13 years) and 851 (54%) in 2005 (wave 3, 13 – 19 years).
Main outcome measures. In both waves participants and their parents completed the PedsQL, a 23-item child HRQoL measure, and BMI z-scores and status (non-overweight, overweight or obese) were calculated from measured height and weight. Associations were tested cross-sectionally and longitudinally (linear regression, adjusted for baseline values)
Results. A total of 81.6% remained in the same BMI category, while 11.4% and 7.0% moved to higher and lower categories, respectively. Cross-sectional inverse associations between lower PedsQL and higher BMI categories were similar to those for elementary school children. Wave 2 BMI strongly predicted wave 3 BMI and wave 2 PedsQL strongly predicted wave 3 PedsQL. Only parent-reported Total PedsQL score predicted higher subsequent BMI, though this effect was small. Wave 2 BMI did not predict wave 3 PedsQL.
Conclusions. This novel study confi rmed previous cross-sectional associations, but did not provide convincing evidence that
BMI is causally associated with falling HRQoL or vice versa across the transition from childhood to adolescence.

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Older Australians are confronted by dramatic changes in their physical, social, financial, and psychological well-being. There are social costs to these changes related to their productivity and increased costs associated with caring for older Australians. Greater community engagement through voluntary work practice may minimize these costs, as well as positively influence volunteers' subjective quality of life (QOL). This study investigates the motivations for older Australians to engage in formal voluntary work. It seeks to identify whether the motivational factors to volunteer are associated with individuals' subjective QOL. The results indicate a positive relationship between older people's motivations to volunteer and their subjective QOL. This association is strengthened by respondents' community orientation, positive perception of voluntary work, positive personal attitudes toward volunteering, and their self-esteem. The role of policy makers in motivating larger participation by the older groups is discussed.

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Objective: To assess the prospective relationship between obesity and health-related quality of life, including a novel assessment of the impact of health-related quality of life on weight gain.

Design and setting:
Longitudinal, national, population-based Australian Diabetes, Obesity and Lifestyle (AusDiab) study, with surveys conducted in 1999/2000 and 2004/2005.

Participants:
A total of 5985 men and women aged 25 years at study entry.

Main outcome measure(s):
At both time points, height, weight and waist circumference were measured and self-report data on health-related quality of life from the SF-36 questionnaire were obtained. Cross-sectional and bi-directional, prospective associations between obesity categories and health-related quality of life were assessed.

Results:
Higher body mass index (BMI) at baseline was associated with deterioration in health-related quality of life over 5 years for seven of the eight health-related quality of life domains in women (all P0.01, with the exception of mental health, P>0.05), and six out of eight in men (all P<0.05, with the exception of role-emotional, P=0.055, and mental health, P>0.05). Each of the quality-of-life domains related to mental health as well as the mental component summary were inversely associated with BMI change (all P<0.0001 for women and P0.01 for men), with the exception of vitality, which was significant in women only (P=0.008). For the physical domains, change in BMI was inversely associated with baseline general health in women only (P=0.023).

Conclusions:
Obesity was associated with a deterioration in health-related quality of life (including both physical and mental health domains) in this cohort of Australian adults followed over 5 years. Health-related quality of life was also a predictor of weight gain over 5 years, indicating a bi-directional association between obesity and health-related quality of life. The identification of those with poor health-related quality of life may be important in assessing the risk of future weight gain, and a focus on health-related quality of life may be beneficial in weight management strategies.

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This study aimed to estimate utility-based quality of life (UQoL) differences between healthy body weight and excess body weight categories. Cross-sectional analysis of 10,959 adults, participating in baseline data collection of the nationally representative Australian Diabetes, Obesity, and Lifestyle (AusDiab) Study was undertaken. Height and weight were measured by trained personnel. Body weight categories were assigned as healthy weight, overweight, and obesity subclasses I, II and III. UQoL was assessed using the SF-6D, which captures physical functioning, role limitation, social functioning, pain, mental health, and vitality on a score of 0.00–1.00 (worst-best). The relationship between body weight categories and UQoL was assessed using linear regression, adjusting for age, sex, education, and smoking. Relative to the healthy weight group (mean UQoL score 0.77), mean adjusted UQoL differences (95% confidence intervals) were 0.001 (−0.008, 0.010) for overweight, −0.012 (−0.022, −0.001) for class-I obese, −0.020 (−0.041, 0.001) for class-II obese, and −0.069 (−0.099, −0.039) for class-III obese groups. Adding metabolic syndrome markers to the covariates had little impact on these differences. Results confirmed an inverse dose–response relationship between body weight and UQoL in this study of Australian adults. This highlights the need to incorporate UQoL measures which are sensitive to the subclasses of obesity when evaluating obesity interventions.

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Various trials have been conducted evaluating depression management programs for patients with Coronary Heart Disease (CHD). However, to date, the most effective way to manage this co-morbidity in the real world setting remains unclear. To better understand the past successes and failures of previous trials and subsequently develop suitable interventions that target key components of health related quality of life (HRQOL) such as mental, physical and vocational functioning, we first need to understand the mechanisms underpinning the relationship between the two conditions. This paper will draw on the key literature in this field as identified by psychiatric, medical and social sciences databases (Cochrane Central Register of Controlled Trials, PubMed, OVID, Medline) available up to January 2012, with the aim to conduct a narrative review which explores: the aetiological relationship between depression and CHD; its association with HRQOL; the relationship between CHD, depression and vocational functioning; and the impact of depression treatment on these outcomes. Key recommendations are made regarding the management of this prevalent co-morbidity in clinical settings.

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Background Participation in coronary heart disease secondary prevention programs is low. Innovative programs to meet this treatment gap are required.

Purpose To aim of this study is to describe the effectiveness of a telephone-delivered secondary prevention program for myocardial infarction patients.

Methods Four hundred and thirty adult myocardial infarction patients in Brisbane, Australia were randomised to a 6-month secondary prevention program or usual care. Primary outcomes were health-related quality of life (Short Form-36) and physical activity (Active Australia Survey).

Results Significant intervention effects were observed for health-related quality of life on the mental component summary score (p = 0.02), and the social functioning (p = 0.04) and role-emotional (p = 0.03) subscales, compared with usual care. Intervention participants were also more likely to meet recommended levels of physical activity (p = 0.02), body mass index (p = 0.05), vegetable intake (p = 0.04) and alcohol consumption (p = 0.05).

Conclusions Telephone-delivered secondary prevention programs can significantly improve health outcomes and could meet the treatment gap for myocardial infarction patients.

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PURPOSE: To conduct a meta-analysis evaluating the effectiveness of depression treatment on mental and physical health-related quality of life (HRQOL) of cardiac patients.

METHODS: Studies were identified using medical, health, psychiatry, psychology, and social sciences databases. Inclusion criteria were (1) 1 or more control conditions, (2) random assignment to condition after admission for myocardial infarction (MI)/acute coronary syndrome, after recording positive results on a depression screener, (3) documentation of depression symptoms at baseline, (4) depression management as a component of the rehabilitation/intervention, (5) validated measure of HRQOL as an outcome, at minimum 6-month followup. For meta-analysis, mental and physical HRQOL were the end points studied, using standardized mean differences for continuous outcome measures, with 95% confidence intervals. Heterogeneity was explored by calculating I2 statistic.

RESULTS: Five randomized controlled trials included in the analysis represented 2105 participants (1058 intervention vs 1047 comparator). Compared with a comparator group at 6 months, a test for overall effect demonstrated statistically significant improvements in mental HRQOL in favor of the intervention (standardized mean differences = −0.29 [−0.38 to −0.20], [P < .00001]; I2 = 0%). Depression treatment had a modest yet significant impact on physical HRQOL (standardized mean differences = −0.14 [−0.24 to −0.04] [P = .009]; I2 = 15%).

CONCLUSION: While the impact of post-MI depression interventions on physical HRQOL is modest, treatment can improve mental HRQOL in a significant way. Future research is required to develop and evaluate a program that can achieve vital improvements in overall HRQOL, and potentially cardiovascular outcomes, of cardiac patients.

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This chapter describes some aspects of life quality in Australia. The data for the initial overview have come from various sources. Following this general introduction, the chapter concentrates on two areas of Australian life that are key to subjective wellbeing. Using the combined data base from 24 surveys using the Australian Unity Wellbeing Index, we identified the happiest and the saddest groups in Australia as defined by their demographic profile. The highest wellbeing groups comprise people who have both a partner and a decent level of wealth. The lowest wellbeing groups are people with no partner, who have a low income and who are unemployed. The chapter then concentrates on the two common, defining elements of the highest and lowest groups as money and relationships. The results are interpreted in terms of data norms, homeostasis theory and possible causal agents. It is concluded that the results generally conform to the predictions of homeostasis and offer signposts as to the kinds of structural changes that influence population wellbeing.

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Background : Nutrition and physical activity are major determinants of health and quality of life; however, there exists little research focusing on determinants of these behaviours in older adults. This is important, since just as these behaviours vary according to subpopulation, it is likely that the determinants also vary. An understanding of the modifiable determinants of nutrition and physical activity behaviours among older adults to take into account the specific life-stage context is required in order to develop effective interventions to promote health and well-being and prevent chronic disease and improve quality of life.

Methods : The aim of this work is to identify how intrapersonal, social and environmental factors influence nutrition and physical activity behaviours among older adults living in urban and rural areas. This study is a cohort study of adults aged 55-65 years across urban and rural Victoria, Australia. Participants completed questionnaires at baseline in 2010 and will complete follow-up questionnaires in 2012 and 2014. Self-report questionnaires will be used to assess outcomes such as food intake, physical activity and sedentary behaviours, anthropometry and quality of life. Explanatory variables include socioeconomic position, and measures of the three levels of influence on older adults' nutrition and physical activity behaviours (intrapersonal, social and perceived environmental influences).

Discussion : Obesity and its determinant behaviours, physical inactivity and poor diet are major public health concerns and are significant determinants of the quality of life among the ageing population. There is a critical need for a better understanding of the determinants of nutrition and physical activity in this important target group. This research will provide evidence for the development of effective policies and programs to promote and support increased physical activity and healthy eating behaviours among older adults.