945 resultados para Population health


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BACKGROUND: Health-related quality of life (HRQL) assessment is an important measure of the impact of a wide range of disease process on an individual. To date, no HRQL tool has been evaluated in an Iranian population with cardiovascular disorders, specifically myocardial infarction, a major cause of mortality and morbidity. The MacNew Heart Disease Health-related Quality of Life instrument is a disease-specific HRQL questionnaire with satisfactory validity and reliability when applied cross-culturally. METHOD: A Persian version of MacNew was prepared by both forward and backward translation by bilinguals after which a feasibility test was performed. Consecutive patients (n = 51) admitted to a coronary care unit with acute myocardial infarction were recruited for measurement of their HRQL with retest one month after discharge in the follow-up clinic. Principal components analysis, intra-class correlation reliability, internal consistency, and test-retest reliability were assessed. RESULTS: Trivial rates of missing data confirmed the acceptability of the tool. Principal component analysis revealed that the three domains, emotional, social and physical, performed as well as in the original studies. Internal consistency was high and comparable to other studies, ranging from 0.92 for the emotional and physical domains, to 0.94 for the social domain, and to 0.95 for the Global score. Domain means of 5, 5.3 and 4.9 for emotional, physical and social respectively indicate that our Iranian population has similar emotional and physical but worse social HRQL scores. Test-retest analysis showed significant correlation in emotional and physical domains (P < 0.05). CONCLUSION: The Persian version of the MacNew questionnaire is comparable to the English version. It has high internal consistency and reasonable reproducibility, making it an appropriate specific quality of life tool for population-based studies and clinical practice in Iran in patients who have survived an acute myocardial infraction. Further studies are needed to confirm its validity in larger populations with cardiovascular disease

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Background: Body composition is affected by diseases, and affects responses to medical treatments, dosage of medicines, etc., while an abnormal body composition contributes to the causation of many chronic diseases. While we have reliable biochemical tests for certain nutritional parameters of body composition, such as iron or iodine status, and we have harnessed nuclear physics to estimate the body’s content of trace elements, the very basic quantification of body fat content and muscle mass remains highly problematic. Both body fat and muscle mass are vitally important, as they have opposing influences on chronic disease, but they have seldom been estimated as part of population health surveillance. Instead, most national surveys have merely reported BMI and waist, or sometimes the waist/hip ratio; these indices are convenient but do not have any specific biological meaning. Anthropometry offers a practical and inexpensive method for muscle and fat estimation in clinical and epidemiological settings; however, its use is imperfect due to many limitations, such as a shortage of reference data, misuse of terminology, unclear assumptions, and the absence of properly validated anthropometric equations. To date, anthropometric methods are not sensitive enough to detect muscle and fat loss. Aims: The aim of this thesis is to estimate Adipose/fat and muscle mass in health disease and during weight loss through; 1. evaluating and critiquing the literature, to identify the best-published prediction equations for adipose/fat and muscle mass estimation; 2. to derive and validate adipose tissue and muscle mass prediction equations; and 3.to evaluate the prediction equations along with anthropometric indices and the best equations retrieved from the literature in health, metabolic illness and during weight loss. Methods: a Systematic review using Cochrane Review method was used for reviewing muscle mass estimation papers that used MRI as the reference method. Fat mass estimation papers were critically reviewed. Mixed ethnic, age and body mass data that underwent whole body magnetic resonance imaging to quantify adipose tissue and muscle mass (dependent variable) and anthropometry (independent variable) were used in the derivation/validation analysis. Multiple regression and Bland-Altman plot were applied to evaluate the prediction equations. To determine how well the equations identify metabolic illness, English and Scottish health surveys were studied. Statistical analysis using multiple regression and binary logistic regression were applied to assess model fit and associations. Also, populations were divided into quintiles and relative risk was analysed. Finally, the prediction equations were evaluated by applying them to a pilot study of 10 subjects who underwent whole-body MRI, anthropometric measurements and muscle strength before and after weight loss to determine how well the equations identify adipose/fat mass and muscle mass change. Results: The estimation of fat mass has serious problems. Despite advances in technology and science, prediction equations for the estimation of fat mass depend on limited historical reference data and remain dependent upon assumptions that have not yet been properly validated for different population groups. Muscle mass does not have the same conceptual problems; however, its measurement is still problematic and reference data are scarce. The derivation and validation analysis in this thesis was satisfactory, compared to prediction equations in the literature they were similar or even better. Applying the prediction equations in metabolic illness and during weight loss presented an understanding on how well the equations identify metabolic illness showing significant associations with diabetes, hypertension, HbA1c and blood pressure. And moderate to high correlations with MRI-measured adipose tissue and muscle mass before and after weight loss. Conclusion: Adipose tissue mass and to an extent muscle mass can now be estimated for many purposes as population or groups means. However, these equations must not be used for assessing fatness and categorising individuals. Further exploration in different populations and health surveys would be valuable.

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In Scotland, life expectancy and health outcomes are strongly tied to socioeconomic status. Specifically, socioeconomically deprived areas suffer disproportionately from high levels of premature multimorbidity and mortality. To tackle these inequalities in health, challenges in the most deprived areas must be addressed. One avenue that merits attention is the potential role of general medical practitioners (GPs) in helping to address health inequalities, particularly due to their long-term presence in deprived communities, their role in improving patient and population health, and their potential advocacy role on behalf of their patients. GPs can be seen as what Lipsky calls ‘street-level bureaucrats’ due to their considerable autonomy in the decisions they make surrounding individual patient needs, yet practising under the bureaucratic structure of the NHS. While previous research has examined the applicability of Lipsky’s framework to the role of GPs, there has been very little research exploring how GPs negotiate between the multiple identities in their work, how GPs ‘socially construct’ their patients, how GPs view their potential role as ‘advocate’, and what this means in terms of the contribution of GPs to addressing existing inequalities in health. Using semi-structured interviews, this study explored the experience and views of 24 GPs working in some of Scotland’s most deprived practices to understand how they might combat this growing health divide via the mitigation (and potential prevention) of existing health inequalities. Participants were selected based on several criteria including practice deprivation level and their individual involvement in the Deep End project, which is an informal network comprising the 100 most deprived general practices in Scotland. The research focused on understanding GPs’ perceptions of their work including its broader implications, within their practice, the communities within which they practise, and the health system as a whole. The concept of street-level bureaucracy proved to be useful in understanding GPs’ frontline work and how they negotiate dilemmas. However, this research demonstrated the need to look beyond Lipsky’s framework in order to understand how GPs reconcile their multiple identities, including advocate and manager. As a result, the term ‘street-level professional’ is offered to capture more fully the multiple identities which GPs inhabit and to explain how GPs’ elite status positions them to engage in political and policy advocacy. This study also provides evidence that GPs’ social constructions of patients are linked not only to how GPs conceptualise the causes of health inequalities, but also to how they view their role in tackling them. In line with this, the interviews established that many GPs felt they could make a difference through advocacy efforts at individual, community and policy/political levels. Furthermore, the study draws attention to the importance of practitioner-led groups—such as the Deep End project—in supporting GPs’ efforts and providing a platform for their advocacy. Within this study, a range of GPs’ views have been explored based on the sample. While it is unclear how common these views are amongst GPs in general, the study revealed that there is considerable scope for ‘political GPs’ who choose to exercise discretion in their communities and beyond. Consequently, GPs working in deprived areas should be encouraged to use their professional status and political clout not only to strengthen local communities, but also to advocate for policy change that might potentially affect the degree of disadvantage of their patients, and levels of social and health inequalities more generally.

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Introduction: Nonagenarian population, clearly increasing, shows different characteristics from the rest of elderly people. Health-related quality of life is a way to study population health in physical, psychological and social dimensions. Objectives: To examine the relationship between nutritional status and health-related quality of life in a group of free-living nonagenarians. Differences with octogenarians were also studied. Methods: Within Villanueva Older Health Study, 20 non-institutionalised people (92.5±3.5 years; 80% women) make the nonagenarian subsample. Nutritional risk was assessed by Mininutritional Assessment questionnaire, dietary intake by a 24-hour dietary recall and health-related quality of life by EuroQoL-5D questionnaire. SPSS was used for statistical analysis. Results: 40% nonagenarians were at risk of malnutrition. Dietary assessment showed magnesium, zinc, potassium, folic acid, vitamin D and vitamin E deficiencies. Problems in mobility were more frequently reported (80%). EQ-5Dindex was associated with MNA (p<0.05). Self-care dimension was associated with calcium and niacin (p<0.05), retinol and cholesterol (p<0.01) intake. Usual activities dimension was associated with niacin (p<0.01) and cholesterol(p<0.05) intake. Pain/discomfort dimension was associated with protein (p<0.01), energy, selenium and niacin (p<0.05) intake. Anxiety/depression was associated with protein(p<0.01) and selenium (p<0.05) intake. Conclusions: Risk of malnutrition is a factor associated to health-related quality of life. Results suggest that energy and some nutrient intakes could be possibly associated to health-related quality of life but further research on this influence is required.

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Transition to diets that are high in saturated fat and sugar has caused a global public health concern as the pattern of food consumption is a mayor modifiable risk factor for chronic non-communicable diseases Although agri food systems are intimately associated with this transition, agriculture and health sectors are largely disconnected in their priorities policy, and analysis with neither side considering the complex inter relation between agri trade patterns of food consumption health, and development We show the importance of connection of these perspectives through estimation of the effect of adopting a healthy diet on population health, agricultural production trade the economy and livelihoods, with a computable general equilibrium approach on the basis of case studies from the UK and Brazil we suggest that benefits of a healthy diet policy will vary substantially between different populations, not only because of population dietary intake but also because of agricultural production trade and other economic factors

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AIMS/HYPOTHESIS: With incidence rates for diabetes increasing rapidly worldwide, estimates of the magnitude of the impact on population health are required. We aimed to estimate the lifetime risk of diabetes, the number of years lived free of, and the number of years lived with diabetes for the Australian adult population from the year 2000, and to project prevalence of diabetes to the year 2025. METHODS: Multi-state life-tables were constructed to simulate the progress of a cohort of 25-year-old Australians. National mortality rates were combined with incidence rates of diabetes and the RR of mortality in people with diabetes derived from the Australian Diabetes, Obesity and Lifestyle study (a national, population-based study of 11,247 adults aged >or=25 years). RESULTS: If the rates of mortality and diabetes incidence observed over the period 2000-2005 continue, 38.0% (95% uncertainty interval 36.6-38.9) of 25-year-olds would be expected to develop diabetes at some time throughout their life. On average, a 25-year-old Australian will live a further 56 years, 48 of these free of diabetes. On average, a 45-year-old person with diabetes can expect to live 6 years less than a person free of diabetes. The prevalence of diabetes is projected to rise from 7.6% in 2000 to 11.4% by 2025. CONCLUSIONS/INTERPRETATION: If we maintain current diabetes incidence rates, more than a third of individuals will develop diabetes within their lifetime and in Australia there will an additional 1 million cases of diabetes by the year 2025.

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Professionals who provide nutrition education and consulting to the public are encouraged to take into account the health, environmental and social contexts that influence health-related attitudes and behaviours in the population. This paper examined the awareness of shifts in population health outcomes associated with the nutrition transition in Vietnam among university nutrition lecturers, health professionals and school education professionals. Most of these professionals held accurate views of the current population health issues in Vietnam. However, they differed in their awareness of the seriousness of overweight and obesity. Although the majority indicated that the prevalence of obesity and non-communicable diseases (NCDs) had increased, nearly half believed that the government should complete its attempts to control undernutrition before trying to control obesity. More health professionals believed that food marketing was responsible for the growing prevalence of children's obesity, and more of them disapproved of the marketing of less healthy food to children. In contrast, the university nutrition lecturers were least aware of food marketing and the seriousness of obesity. Of the three groups, the university nutrition lecturers held less accurate perceptions of nutrition transition problems and their likely drivers. There is an urgent need for greater provision of public nutrition education for all three groups of professionals.

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This paper explores some of the lessons of the coordinated care trials in Australia in the context of managed care in America and asks how do we best manage our finite health care dollars for the most equitable and effective outcomes for whole populations? The COAG trial in Australia tested a more structured process for managing the care of patients with chronic illness and postulated that currently fragmented health system funding could be pooled around individual patient need, and managed for improved economic outcomes and patient wellbeing. There is little doubt, following this initiative and much work in other countries, that as health care costs rise, for a range of reasons, improvements are needed in the management of our resources if we are to control rising health care costs. We also know that chronic illness, much of which is preventable and avoidable, is the major component in the rising health care cost equation and a factor likely to consume around 75% of our health dollars in the future. Much chronic illness can be prevented through social and population health strategies and we know that even if chronic illness can?t be prevented, it can be managed better through community-based chronic illness management programs. These programs rely on information, education, patient lifestyle and behaviour change, and on patients developing improved self-management skills. But, what is the best way to manage population health in Australia and ensure equity and fairness in the health care market as we evolve new approaches, especially to the management of chronic illness?

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Whilst health science, epidemiology and public health developments have forged enormous progress in understanding, prevention and cure in the health care area we still appear to lack the motivation to tackle the fundamental antecedents of many of our emerging population-based community health problems; the prevention of chronic illness being a prime example.

In spite of much progress in the area of health science, the social, economic and evolutionary forces that cast our physical being in the world still remain poorly understood or accepted in the health care arena. However, if our health care systems are to be manageable and sustainable in the future, these wider antecedents of our health status and wellbeing must be factored more fundamentally in to our management models with more effort being put into preventing lifestyle related chronic illnesses than is currently the case.

As in the past where public health infrastructure innovations such as running water and efficient waste disposal systems served to add greatly to the wellbeing of individuals and communities, we now need to make similar efforts to control preventable illnesses such as metabolic syndrome, type 2 diabetes and lifestyle related cardio-vascular disease at their source rather than waiting until the manifestation of these conditions require major medical and chemical intervention and management before we act. Our young people are at risk of early onset chronic conditions as a result of their emerging sedentary lifestyles, un-healthy dietary habits and health related behaviours, yet we continue to concentrate our health management effort on managing those with existing chronic conditions while leaving younger generations with lifestyle practices and behaviours that pre-dispose individuals to developing chronic illness earlier and earlier in their lives.

It is time we took notice of these emerging trends and began expending more effort to prevent what are essentially lifestyle related illnesses that can be eliminated before they become endemic. By concentrating more upon the social and environmental factors affecting our illness profiles as well as upon dealing more effectively with those who are already suffering from chronic illness we will reduce the need for major end-stage interventions and alleviate the impact and cost of early onset chronic disease. To achieve this new population health vision in Australia at least, we will not only need to utilize the new government funding structures more effectively; those structures that support coordination and more effective management of care, but also take a much broader, environmental and social view of cause and effect in relation to the health of populations.

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This book is especially apt for those interested in implementing the practices and strategies that support programmes of health maintenance, preventive health and strategies for bringing about a change in personal and population health ...

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Health literacy is an important construct in population health and healthcare requiring rigorous measurement. The Health Literacy Questionnaire (HLQ), with nine scales, measures a broad perception of health literacy. This study aimed to adapt the HLQ to the Danish setting, and to examine the factor structure, homogeneity, reliability and discriminant validity. The HLQ was adapted using forward-backward translation, consensus conference and cognitive interviews (n = 15). Psychometric properties were examined based on data collected by face-to-face interview (n = 481). Tests included difficulty level, composite scale reliability and confirmatory factor analysis (CFA). Cognitive testing revealed that only minor re-wording was required. The easiest scale to respond to positively was 'Social support for health', and the hardest were 'Navigating the healthcare system' and 'Appraisal of health information'. CFA of the individual scales showed acceptably high loadings (range 0.49-0.93). CFA fit statistics after including correlated residuals were good for seven scales, acceptable for one. Composite reliability and Cronbach's α were >0.8 for all but one scale. A nine-factor CFA model was fitted to items with no cross-loadings or correlated residuals allowed. Given this restricted model, the fit was satisfactory. The HLQ appears robust for its intended application of assessing health literacy in a range of settings. Further work is required to demonstrate sensitivity to measure changes.

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Food security is a global and regional concern of rapidly increasing consequence. It is at risk of inattention because of competing crises, because of its theoretical amenability to previously effective, if temporary measures, most impressively with the so-called Green Revolution and because of the recourse to the global trade paradigm as a putative solution. We identify some missing or under-emphasised dimensions in this analysis, with particular reference to Asia, which in spite of recent growth-or in some cases because of it-faces particularly daunting food problems. Greater emphasis needs to be given to population size and distribution through more concerted family planning and enlightened migration policy; public policy to retain or encourage plant-based diets; integration of food, health and environmental approaches to create resilient regional food systems; and the incorporation of food into the broader human security agenda. While regional organisations, along with their NGO counterparts and nation states, have an over-arching role to strategise in this way, substantial progress could still be made at the community and household levels, especially with current technologies which can marshal their collective and coherent action.

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Suicide has drawn much attention from both the scientific community and the public. Examining the impact of socio-environmental factors on suicide is essential in developing suicide prevention strategies and interventions, because it will provide health authorities with important information for their decision-making. However, previous studies did not examine the impact of socio-environmental factors on suicide using a spatial analysis approach. The purpose of this study was to identify the patterns of suicide and to examine how socio-environmental factors impact on suicide over time and space at the Local Governmental Area (LGA) level in Queensland. The suicide data between 1999 and 2003 were collected from the Australian Bureau of Statistics (ABS). Socio-environmental variables at the LGA level included climate (rainfall, maximum and minimum temperature), Socioeconomic Indexes for Areas (SEIFA) and demographic variables (proportion of Indigenous population, unemployment rate, proportion of population with low income and low education level). Climate data were obtained from Australian Bureau of Meteorology. SEIFA and demographic variables were acquired from ABS. A series of statistical and geographical information system (GIS) approaches were applied in the analysis. This study included two stages. The first stage used average annual data to view the spatial pattern of suicide and to examine the association between socio-environmental factors and suicide over space. The second stage examined the spatiotemporal pattern of suicide and assessed the socio-environmental determinants of suicide, using more detailed seasonal data. In this research, 2,445 suicide cases were included, with 1,957 males (80.0%) and 488 females (20.0%). In the first stage, we examined the spatial pattern and the determinants of suicide using 5-year aggregated data. Spearman correlations were used to assess associations between variables. Then a Poisson regression model was applied in the multivariable analysis, as the occurrence of suicide is a small probability event and this model fitted the data quite well. Suicide mortality varied across LGAs and was associated with a range of socio-environmental factors. The multivariable analysis showed that maximum temperature was significantly and positively associated with male suicide (relative risk [RR] = 1.03, 95% CI: 1.00 to 1.07). Higher proportion of Indigenous population was accompanied with more suicide in male population (male: RR = 1.02, 95% CI: 1.01 to 1.03). There was a positive association between unemployment rate and suicide in both genders (male: RR = 1.04, 95% CI: 1.02 to 1.06; female: RR = 1.07, 95% CI: 1.00 to 1.16). No significant association was observed for rainfall, minimum temperature, SEIFA, proportion of population with low individual income and low educational attainment. In the second stage of this study, we undertook a preliminary spatiotemporal analysis of suicide using seasonal data. Firstly, we assessed the interrelations between variables. Secondly, a generalised estimating equations (GEE) model was used to examine the socio-environmental impact on suicide over time and space, as this model is well suited to analyze repeated longitudinal data (e.g., seasonal suicide mortality in a certain LGA) and it fitted the data better than other models (e.g., Poisson model). The suicide pattern varied with season and LGA. The north of Queensland had the highest suicide mortality rate in all the seasons, while there was no suicide case occurred in the southwest. Northwest had consistently higher suicide mortality in spring, autumn and winter. In other areas, suicide mortality varied between seasons. This analysis showed that maximum temperature was positively associated with suicide among male population (RR = 1.24, 95% CI: 1.04 to 1.47) and total population (RR = 1.15, 95% CI: 1.00 to 1.32). Higher proportion of Indigenous population was accompanied with more suicide among total population (RR = 1.16, 95% CI: 1.13 to 1.19) and by gender (male: RR = 1.07, 95% CI: 1.01 to 1.13; female: RR = 1.23, 95% CI: 1.03 to 1.48). Unemployment rate was positively associated with total (RR = 1.40, 95% CI: 1.24 to 1.59) and female (RR=1.09, 95% CI: 1.01 to 1.18) suicide. There was also a positive association between proportion of population with low individual income and suicide in total (RR = 1.28, 95% CI: 1.10 to 1.48) and male (RR = 1.45, 95% CI: 1.23 to 1.72) population. Rainfall was only positively associated with suicide in total population (RR = 1.11, 95% CI: 1.04 to 1.19). There was no significant association for rainfall, minimum temperature, SEIFA, proportion of population with low educational attainment. The second stage is the extension of the first stage. Different spatial scales of dataset were used between the two stages (i.e., mean yearly data in the first stage, and seasonal data in the second stage), but the results are generally consistent with each other. Compared with other studies, this research explored the variety of the impact of a wide range of socio-environmental factors on suicide in different geographical units. Maximum temperature, proportion of Indigenous population, unemployment rate and proportion of population with low individual income were among the major determinants of suicide in Queensland. However, the influence from other factors (e.g. socio-culture background, alcohol and drug use) influencing suicide cannot be ignored. An in-depth understanding of these factors is vital in planning and implementing suicide prevention strategies. Five recommendations for future research are derived from this study: (1) It is vital to acquire detailed personal information on each suicide case and relevant information among the population in assessing the key socio-environmental determinants of suicide; (2) Bayesian model could be applied to compare mortality rates and their socio-environmental determinants across LGAs in future research; (3) In the LGAs with warm weather, high proportion of Indigenous population and/or unemployment rate, concerted efforts need to be made to control and prevent suicide and other mental health problems; (4) The current surveillance, forecasting and early warning system needs to be strengthened, to trace the climate and socioeconomic change over time and space and its impact on population health; (5) It is necessary to evaluate and improve the facilities of mental health care, psychological consultation, suicide prevention and control programs; especially in the areas with low socio-economic status, high unemployment rate, extreme weather events and natural disasters.

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Introduction: The core business of public health is to protect and promote health in the population. Public health planning is the means to maximise these aspirations. Health professionals develop plans to address contemporary health priorities as the evidence about changing patterns of mortality and morbidity is presented. Officials are also alert to international trends in patterns of disease that have the potential to affect the health of Australians. Integrated planning and preparation is currently underway involving all emergency health services, hospitals and population health units to ensure Australia's quick and efficient response to any major infectious disease outbreak, such as avian influenza (bird flu). Public health planning for the preparations for the Sydney Olympics and Paralympic Games in 2000 took almost three years. ‘Its major components included increased surveillance of communicable disease; presentations to sentinel emergency departments; medical encounters at Olympic venues; cruise ship surveillance; environmental and food safety inspections; bioterrorism surveillance and global epidemic intelligence’ (Jorm et al 2003, 102). In other words, the public health plan was developed to ensure food safety, hospital capacity, safe crowd control, protection against infectious diseases, and an integrated emergency and disaster plan. We have national and state plans for vaccinating children against infectious diseases in childhood; plans to promote dental health for children in schools; and screening programs for cervical, breast and prostate cancer. An effective public health response to a change in the distribution of morbidity and mortality requires planning. All levels of government plan for the public’s health. Local governments (councils) ensure healthy local environments to protect the public’s health. They plan parks for recreation, construct traffic-calming devices near schools to prevent childhood accidents, build shade structures and walking paths, and even embed drafts/chess squares in tables for people to sit and play. Environmental Health officers ensure food safety in restaurants and measure water quality. These public health measures attempt to promote the quality of life of residents. Australian and state governments produce plans that protect and promote health through various policy and program initiatives and innovations. To be effective, program plans need to be evaluated. However, building an integrated evaluation plan into a program plan is often forgotten, as planning and evaluation are seen as two distinct entities. Consequently, it is virtually impossible to measure, with any confidence, the extent to which a program has achieved its goals and objectives. This chapter introduces you to the concepts of public health program planning and evaluation. Case studies and reflection questions are presented to illustrate key points. As various authors use different terminology to describe the same concepts/actions of planning and evaluation, the glossary at the back of this book will help you to clarify the terms used in this chapter.

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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.