847 resultados para interactional determinants


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The paper examines the decision by Australian Real Estate Trusts (A-REITs) to issue seasoned equity offerings from 2000 - 2008 and stock market reaction to the offerings. The findings reveal that highly leveraged A-REITs with variable earnings are less likely to issue seasoned equity offerings. Inconsistent results for structure and type of properties held by the A-REIT do not allow for inference to be drawn. Similar to previous studies of seasoned equity offerings, we find a significant negative abnormal return associated with their announcement and no evidence of excessive leakage of information. Furthermore, market reaction differences to announcements of SEOs for the pre-global financial crisis (GFC) (2000-2006) and GFC eras (2007-2008) are noted with GFC era shareholders incurring larger abnormal return losses at 1.13% in comparison to the pre-GFC era shareholder loss of 0.34% on the SEO announcement day. Cross-sectional regressions show that the issued amount, leverage and profitability are significant factors affecting abnormal returns. Growth opportunities, tangibility, operating risk, size of A-REIT and other variables capturing A-REIT structure and property types held do not have an impact on abnormal returns

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This paper investigates the patterns and determinants of life satisfaction in Germany following reunification. We implement a new fixed-effect estimator for ordinal life satisfaction in the German Socio-Economic Panel and find negative effects on life satisfaction from being recently fired, losing a spouse through either death or separation, and time spent in hospital, while we find strong positive effects from income and marriage. Using a new causal decomposition technique, we find that East Germans experienced a continued improvement in life satisfaction to which increased household incomes contributed around 12 percent. Most of the improvement is explained by better average circumstances, such as greater political freedom. For West Germans, we find little change in average life satisfaction over this period.

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A growing literature seeks to explain differences in individuals' self-reported satisfaction with their jobs. The evidence so far has mainly been based on cross-sectional data and when panel data have been used, individual unobserved heterogeneity has been modelled as an ordered probit model with random effects. This article makes use of longitudinal data for Denmark, taken from the waves 1995-1999 of the European Community Household Panel, and estimates fixed effects ordered logit models using the estimation methods proposed by Ferrer-i-Carbonel and Frijters (2004) and Das and van Soest (1999). For comparison and testing purposes a random effects ordered probit is also estimated. Estimations are carried out separately on the samples of men and women for individuals' overall satisfaction with the jobs they hold. We find that using the fixed effects approach (that clearly rejects the random effects specification), considerably reduces the number of key explanatory variables. The impact of central economic factors is the same as in previous studies, though. Moreover, the determinants of job satisfaction differ considerably between the genders, in particular once individual fixed effects are allowed for.

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Background: Apart from promoting physical recovery and assisting in activities of daily living, a major challenge in stroke rehabilitation is to minimize psychosocial morbidity and to promote the reintegration of stroke survivors into their family and community. The identification of key factors influencing long-term outcome are essential in developing more effective rehabilitation measures for reducing stroke-related morbidity. The aim of this study was to test a theoretical model of predictors of participation restriction which included the direct and indirect effects between psychosocial outcomes, physical outcome, and socio-demographic variables at 12 months after stroke.--------- Methods: Data were collected from 188 stroke survivors at 12 months following their discharge from one of the two rehabilitation hospitals in Hong Kong. The settings included patients' homes and residential care facilities. Path analysis was used to test a hypothesized model of participation restriction at 12 months.---------- Results: The path coefficients show functional ability having the largest direct effect on participation restriction (β = 0.51). The results also show that more depressive symptoms (β = -0.27), low state self-esteem (β = 0.20), female gender (β = 0.13), older age (β = -0.11) and living in a residential care facility (β = -0.12) have a direct effect on participation restriction. The explanatory variables accounted for 71% of the variance in explaining participation restriction at 12 months.---------- Conclusion: Identification of stroke survivors at risk of high levels of participation restriction, depressive symptoms and low self-esteem will assist health professionals to devise appropriate rehabilitation interventions that target improving both physical and psychosocial functioning.

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The sinking of the Titanic in April 1912 took the lives of 68 percent of the people aboard. Who survived? It was women and children who had a higher probability of being saved, not men. Likewise, people traveling in first class had a better chance of survival than those in second and third class. British passengers were more likely to perish than members of other nations. This extreme event represents a rare case of a well-documented life and death situation where social norms were enforced. This paper shows that economic analysis can account for human behavior in such situations.

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This report presents the outcomes of a project undertaken by the VACCHO Public Health Research Unit to explore ways to build capacity in Aboriginal and Torres Strait Islander social determinants research. The project was funded by the Cooperative Research Centre for Aboriginal Health.----- The project involved a series of four social determinants research workshops conducted in July and August 2009 and a collaborative forum conducted in September 2009. Invitations to participate were extended to the VACCHO membership and the nine universities in Victoria. Three workshops were held with ACCHOs (in Bendigo, Melbourne and Gippsland), and one workshop with universities (in Melbourne).----- The workshops aimed to build VACCHO’s social determinants research capacity and provide direction for VACCHO on ways to more effectively engage in Aboriginal health research. Through the workshops, VACCHO aimed to work with ACCHOs to identify research processes and issues that are equitable and sustainable, and which address the social determinants of health.----- At the workshops, participants explored questions around the priorities for the social determinants of Aboriginal health and considered the key partnerships that might be important to social determinants research.----- At the workshops with ACCHOs, participants identified key research priorities and questions in Aboriginal social determinants and health. This focus reflects the need for Aboriginal and Torres Strait Islander community representatives to identify the priorities in health and social determinants research. Identifying these priorities is important if researchers are to respond in a meaningful way and undertake relevant research in the most urgent areas of need. At the university workshop, participants focused on identifying research process and implementation issues in social determinants research.----- The final forum brought together ACCHOs, university representatives, invited presenters and participants from justice, education and housing departments, and representatives from non-government funding organisations. The forum aimed to provide an insight into how priorities and funding decisions are made, and how research can help to ensure they are influenced by the priorities of the community. The findings from the workshops were presented at the forum and used to develop pathways for future research.

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This chapter describes physical and environmental determinants of the health of Australians, providing a background to the development of successful public health activity. Health determinants are the biomedical, genetic, behavioural, socio-economic and environmental factors that impact on health and wellbeing. These determinants can be influenced by interventions and by resources and systems (AIHW 2006). Many factors combine to affect the health of individuals and communities. People’s circumstances and the environment determine whether the population is healthy or not. Factors such as where people live, the state of their environment, genetics, their education level and income, and their relationships with friends and family, all are likely to impact on their health. The determinants of population health reflect the context of people’s lives; however, people are very unlikely to be able to control many of these determinants (WHO 2007). This chapter and Chapter 6 illustrate how various determinants can relate to, and influence other determinants, as well as health and wellbeing. We believe it is particularly important to provide an understanding of determinants and their relationship to health and illness in order to provide a structure in which a broader conceptualisation of health can be placed. Determinants of health do not exist in isolation from one another. More frequently they work together in a complex system. What is clear to anyone who works in public health is that many factors impact on the health and wellbeing of people. For example, in the next chapter we discuss factors such as living and working conditions, social support, ethnicity and class, income, housing, work stress and the impact of education on the length and quality of people’s lives. In 1974, the influential ‘Lalonde Report’ (Lalonde 1974) described key factors that impact on health status. These factors included lifestyle, environment, human biology and health services. Taking a population health approach builds on the Lalonde Report, and recognises that a range of factors, such as living and working conditions and the distribution of wealth in society, interact to determine the health status of a population. Tackling health determinants has great potential to reduce the burden of disease and promote the health of the general population. In summary, we understand very clearly now that health is determined by the complex interactions between individual characteristics, social and economic factors and physical environments; the entire range of factors that impact on health must be addressed if we are to make significant gains in population health, and focussing interventions on the health of the population or significant sub-populations can achieve important health gains. In 2007, the Australian Government included in the list of National Health Priority Areas the following health issues: cancer control, injury prevention and control, cardiovascular health, diabetes mellitus, mental health, asthma, and arthritis and musculoskeletal conditions. The National Health Priority Areas set the agenda for the Commonwealth, States and Territories, Local Governments and not-for-profit organisations to place attention on those areas considered to be the major foci for action. Many of these health issues are discussed in this chapter and the following chapter.

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It is now well known that pesticide spraying by farmers has an adverse impact on their health. This is especially so in developing countries where pesticide spraying is undertaken manually. The estimated health costs are large. Studies to date have examined farmers’ exposure to pesticides, the costs of ill-health and their determinants based on information provided by farmers. Hence, some doubt has been cast on the reliability of such studies. In this study, we rectify this situation by conducting surveys among two groups of farmers. Farmers who perceive that their ill-health is due to exposure to pesticides and obtained treatment and farmers whose ill-health have been diagnosed by doctors and who have been treated in hospital for exposure to pesticides. In the paper, cost comparisons between the two groups of farmers are made. Furthermore, regression analysis of the determinants of health costs show that the quantity of pesticides used per acre per month, frequency of pesticide use and number of pesticides used per hour per day are the most important determinants of medical costs for both samples. The results have important policy implications.