993 resultados para Mortality, Premature


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The estimated one million Australians with type 2 diabetes face significant risks of morbidity and premature mortality. Inadequate diabetes self-management is associated with poor glycaemic control, which is further impaired by comorbid dysphoria. Regular access to ongoing self-management and psychological support is limited, especially in rural and regional locations. Web-based interventions can provide complementary support to patients’ usual care. Semi-structured interviews were undertaken with two samples that comprised (a) 13 people with type 2 diabetes and (b) 12 general practitioners (GPs). Interviews explored enablers and barriers to self-care, emotional challenges, needs for support, and potential web-based programme components. Patients were asked about the potential utility of a web-based support programme, and GPs were asked about likely circumstances of patient referral to it. Thematic analysis was used to summarise responses. Most perceived facilitators and barriers to self-management were similar across the groups. Both groups highlighted the centrality of dietary self-management, valued shared decision-making with health professionals, and endorsed the idea of web-based support. Some emotional issues commonly identified by patients varied to those perceived by GPs, resulting in different attributions for impaired self-care. A web-based programme that supported self-management and psychological/emotional needs appears likely to hold promise in yielding high acceptability and perceived utility.

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Background: It is important to identify patients who are at risk of malnutrition upon hospital admission as malnutrition results in poor outcomes such as longer length of hospital stay, readmission, hospitalisation cost and mortality. The aim of this study was to determine the prognostic validity of 3-Minute Nutrition Screening (3-MinNS) in predicting hospital outcomes in patients admitted to an acute tertiary hospital through a list of diagnosis-related groups (DRG). Methods: In this study, 818 adult patients were screened for risk of malnutrition using 3-MinNS within 24 hours of admission. Mortality data was collected from the National Registry with other hospitalisation outcomes retrieved from electronic hospital records. The results were adjusted for age, gender and ethnicity, and matched for DRG. Results: Patients identified to be at risk of malnutrition (37%) using 3-MinNS had significant positive association with longer length of hospital stay (6.6 ± 7.1 days vs. 4.5 ± 5.5 days, p<0.001), higher hospitalisation cost (S$4540 ± 7190 vs. S$3630 ± 4961, p<0.001) and increased mortality rate at 1 year (27.8% vs. 3.9%), 2 years (33.8% vs. 7.2%) and 3 years (39.1% vs. 10.5%); p<0.001 for all. Conclusions: The 3-MinNS is able to predict clinical outcomes and can be used to screen newly admitted patients for nutrition risk so that appropriate nutrition assessment and early nutritional intervention can be initiated.

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Seasonal patterns in mortality have been recognised for decades, with a marked excess of deaths in winter, yet our understanding of the causes of this phenomenon is not yet complete. Research has shown that low and high temperatures are associated with increased mortality independently of season; however, the impact of unseasonal weather on mortality has been less studied. In this study, we aimed to determine if unseasonal patterns in weather were associated with unseasonal patterns in mortality. We obtained daily temperature, humidity and mortality data from 1988 to 2009 for five major Australian cities with a range of climates. We split the seasonal patterns in temperature, humidity and mortality into their stationary and non-stationary parts. A stationary seasonal pattern is consistent from year-to-year, and a non-stationary pattern varies from year-to-year. We used Poisson regression to investigate associations between unseasonal weather and an unusual number of deaths. We found that deaths rates in Australia were 20–30% higher in winter than summer. The seasonal pattern of mortality was non-stationary, with much larger peaks in some winters. Winters that were colder or drier than a typical winter had significantly increased death risks in most cities. Conversely summers that were warmer or more humid than average showed no increase in death risks. Better understanding the occurrence and cause of seasonal variations in mortality will help with disease prevention and save lives.

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BACKGROUND This paper describes the first national burden of disease study for South Africa. The main focus is the burden due to premature mortality, i.e. years of life lost (YLLs). In addition, estimates of the burden contributed by morbidity, i.e. the years lived with disability (YLDs), are obtained to calculate disability-adjusted life years (DALYs); and the impact of AIDS on premature mortality in the year 2010 is assessed. METHOD Owing to the rapid mortality transition and the lack of timely data, a modelling approach has been adopted. The total mortality for the year 2000 is estimated using a demographic and AIDS model. The non-AIDS cause-of-death profile is estimated using three sources of data: Statistics South Africa, the National Department of Home Affairs, and the National Injury Mortality Surveillance System. A ratio method is used to estimate the YLDs from the YLL estimates. RESULTS The top single cause of mortality burden was HIV/AIDS followed by homicide, tuberculosis, road traffic accidents and diarrhoea. HIV/AIDS accounted for 38% of total YLLs, which is proportionately higher for females (47%) than for males (33%). Pre-transitional diseases, usually associated with poverty and underdevelopment, accounted for 25%, non-communicable diseases 21% and injuries 16% of YLLs. The DALY estimates highlight the fact that mortality alone underestimates the burden of disease, especially with regard to unintentional injuries, respiratory disease, and nervous system, mental and sense organ disorders. The impact of HIV/AIDS is expected to more than double the burden of premature mortality by the year 2010. CONCLUSION This study has drawn together data from a range of sources to develop coherent estimates of premature mortality by cause. South Africa is experiencing a quadruple burden of disease comprising the pre-transitional diseases, the emerging chronic diseases, injuries, and HIV/AIDS. Unless interventions that reduce morbidity and delay morbidity become widely available, the burden due to HIV/AIDS can be expected to grow very rapidly in the next few years. An improved base of information is needed to assess the morbidity impact more accurately.

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BACKGROUND Measuring disease and injury burden in populations requires a composite metric that captures both premature mortality and the prevalence and severity of ill-health. The 1990 Global Burden of Disease study proposed disability-adjusted life years (DALYs) to measure disease burden. No comprehensive update of disease burden worldwide incorporating a systematic reassessment of disease and injury-specific epidemiology has been done since the 1990 study. We aimed to calculate disease burden worldwide and for 21 regions for 1990, 2005, and 2010 with methods to enable meaningful comparisons over time. METHODS We calculated DALYs as the sum of years of life lost (YLLs) and years lived with disability (YLDs). DALYs were calculated for 291 causes, 20 age groups, both sexes, and for 187 countries, and aggregated to regional and global estimates of disease burden for three points in time with strictly comparable definitions and methods. YLLs were calculated from age-sex-country-time-specific estimates of mortality by cause, with death by standardised lost life expectancy at each age. YLDs were calculated as prevalence of 1160 disabling sequelae, by age, sex, and cause, and weighted by new disability weights for each health state. Neither YLLs nor YLDs were age-weighted or discounted. Uncertainty around cause-specific DALYs was calculated incorporating uncertainty in levels of all-cause mortality, cause-specific mortality, prevalence, and disability weights. FINDINGS Global DALYs remained stable from 1990 (2·503 billion) to 2010 (2·490 billion). Crude DALYs per 1000 decreased by 23% (472 per 1000 to 361 per 1000). An important shift has occurred in DALY composition with the contribution of deaths and disability among children (younger than 5 years of age) declining from 41% of global DALYs in 1990 to 25% in 2010. YLLs typically account for about half of disease burden in more developed regions (high-income Asia Pacific, western Europe, high-income North America, and Australasia), rising to over 80% of DALYs in sub-Saharan Africa. In 1990, 47% of DALYs worldwide were from communicable, maternal, neonatal, and nutritional disorders, 43% from non-communicable diseases, and 10% from injuries. By 2010, this had shifted to 35%, 54%, and 11%, respectively. Ischaemic heart disease was the leading cause of DALYs worldwide in 2010 (up from fourth rank in 1990, increasing by 29%), followed by lower respiratory infections (top rank in 1990; 44% decline in DALYs), stroke (fifth in 1990; 19% increase), diarrhoeal diseases (second in 1990; 51% decrease), and HIV/AIDS (33rd in 1990; 351% increase). Major depressive disorder increased from 15th to 11th rank (37% increase) and road injury from 12th to 10th rank (34% increase). Substantial heterogeneity exists in rankings of leading causes of disease burden among regions. INTERPRETATION Global disease burden has continued to shift away from communicable to non-communicable diseases and from premature death to years lived with disability. In sub-Saharan Africa, however, many communicable, maternal, neonatal, and nutritional disorders remain the dominant causes of disease burden. The rising burden from mental and behavioural disorders, musculoskeletal disorders, and diabetes will impose new challenges on health systems. Regional heterogeneity highlights the importance of understanding local burden of disease and setting goals and targets for the post-2015 agenda taking such patterns into account. Because of improved definitions, methods, and data, these results for 1990 and 2010 supersede all previously published Global Burden of Disease results.

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INTRODUCTION: The first South African National Burden of Disease study quantified the underlying causes of premature mortality and morbidity experienced in South Africa in the year 2000. This was followed by a Comparative Risk Assessment to estimate the contributions of 17 selected risk factors to burden of disease in South Africa. This paper describes the health impact of exposure to four selected environmental risk factors: unsafe water, sanitation and hygiene; indoor air pollution from household use of solid fuels; urban outdoor air pollution and lead exposure. METHODS: The study followed World Health Organization comparative risk assessment methodology. Population-attributable fractions were calculated and applied to revised burden of disease estimates (deaths and disability adjusted life years, [DALYs]) from the South African Burden of Disease study to obtain the attributable burden for each selected risk factor. The burden attributable to the joint effect of the four environmental risk factors was also estimated taking into account competing risks and common pathways. Monte Carlo simulation-modeling techniques were used to quantify sampling, uncertainty. RESULTS: Almost 24 000 deaths were attributable to the joint effect of these four environmental risk factors, accounting for 4.6% (95% uncertainty interval 3.8-5.3%) of all deaths in South Africa in 2000. Overall the burden due to these environmental risks was equivalent to 3.7% (95% uncertainty interval 3.4-4.0%) of the total disease burden for South Africa, with unsafe water sanitation and hygiene the main contributor to joint burden. The joint attributable burden was especially high in children under 5 years of age, accounting for 10.8% of total deaths in this age group and 9.7% of burden of disease. CONCLUSION: This study highlights the public health impact of exposure to environmental risks and the significant burden of preventable disease attributable to exposure to these four major environmental risk factors in South Africa. Evidence-based policies and programs must be developed and implemented to address these risk factors at individual, household, and community levels.

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Objective Smoking prevalence among Vietnamese men is among the highest in the world. Our aim was to provide estimates of tobacco attributable mortality to support tobacco control policies. Method We used the Peto–Lopez method using lung cancer mortality to derive a Smoking Impact Ratio (SIR) as a marker of cumulative exposure to smoking. SIRs were applied to relative risks from the Cancer Prevention Study, Phase II. Prevalence-based and hybrid methods, using the SIR for cancers and chronic obstructive pulmonary disease and smoking prevalence for all other outcomes, were used in sensitivity analyses. Results When lung cancer was used to measure cumulative smoking exposure, 28% (95% uncertainty interval 24–31%) of all adult male deaths (> 35 years) in Vietnam in 2008 were attributable to smoking. Lower estimates resulted from prevalence-based methods [24% (95% uncertainty interval 21–26%)] with the hybrid method yielding intermediate estimates [26% (95% uncertainty interval 23–28%)]. Conclusion Despite uncertainty in these estimates of attributable mortality, tobacco smoking is already a major risk factor for death in Vietnamese men. Given the high current prevalence of smoking, this has important implications not only for preventing the uptake of tobacco but also for immediate action to adopt and enforce stronger tobacco control measures.

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Background: High levels of wealth inequality with improved health statistics in South Africa (SA) provide an important opportunity to investigate non-communicable diseases (NCDs) among the poor. Aims: This paper uses two distinct national data sets to contrast patterns of mortality in rich and poor areas and explore the associations between poverty, risk factors, health care and selected NCDs diseases in South African adults. Methods: Causes of premature mortality in 1996 experienced in the poorest magisterial districts are compared with those in the richest, using average household wealth to classify districts. Logistic and multinomial regression are used to investigate the association of a household asset index and selected chronic conditions, related risk factors and healthcare indicators using data from the 1998 South African Demographic and Health Survey. Results: NCDs accounted for 39% and 33% of premature mortality in rich and poor districts respectively. The household survey data showed that the risk factors hypertension and obesity increased with increasing wealth, while most of the lifestyle factors, such as light smoking, domestic exposure to ``smoky'' fuels and alcohol dependence were associated with poverty. Treatment status for hypertension and asthma was worse for poor people than for rich people. Conclusions: The study suggests that NCDs and lifestyle-related risk factors are prevalent among the poor in SA and treatment for chronic diseases is lacking for poor people. The observed increase in hypertension and obesity with wealth suggests that unless comprehensive health promotion strategies are implemented, there will be an unmanageable chronic disease epidemic with future socioeconomic development in SA.

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Background We used data from the Global Burden of Diseases, Injuries, and Risk Factors Study 2010 (GBD 2010) to estimate the burden of disease attributable to mental and substance use disorders in terms of disability-adjusted life years (DALYs), years of life lost to premature mortality (YLLs), and years lived with disability (YLDs). Methods For each of the 20 mental and substance use disorders included in GBD 2010, we systematically reviewed epidemiological data and used a Bayesian meta-regression tool, DisMod-MR, to model prevalence by age, sex, country, region, and year. We obtained disability weights from representative community surveys and an internet-based survey to calculate YLDs. We calculated premature mortality as YLLs from cause of death estimates for 1980–2010 for 20 age groups, both sexes, and 187 countries. We derived DALYs from the sum of YLDs and YLLs. We adjusted burden estimates for comorbidity and present them with 95% uncertainty intervals. Findings In 2010, mental and substance use disorders accounted for 183·9 million DALYs (95% UI 153·5 million–216·7 million), or 7·4% (6·2–8·6) of all DALYs worldwide. Such disorders accounted for 8·6 million YLLs (6·5 million–12·1 million; 0·5% [0·4–0·7] of all YLLs) and 175·3 million YLDs (144·5 million–207·8 million; 22·9% [18·6–27·2] of all YLDs). Mental and substance use disorders were the leading cause of YLDs worldwide. Depressive disorders accounted for 40·5% (31·7–49·2) of DALYs caused by mental and substance use disorders, with anxiety disorders accounting for 14·6% (11·2–18·4), illicit drug use disorders for 10·9% (8·9–13·2), alcohol use disorders for 9·6% (7·7–11·8), schizophrenia for 7·4% (5·0–9·8), bipolar disorder for 7·0% (4·4–10·3), pervasive developmental disorders for 4·2% (3·2–5·3), childhood behavioural disorders for 3·4% (2·2–4·7), and eating disorders for 1·2% (0·9–1·5). DALYs varied by age and sex, with the highest proportion of total DALYs occurring in people aged 10–29 years. The burden of mental and substance use disorders increased by 37·6% between 1990 and 2010, which for most disorders was driven by population growth and ageing. Interpretation Despite the apparently small contribution of YLLs—with deaths in people with mental disorders coded to the physical cause of death and suicide coded to the category of injuries under self-harm—our findings show the striking and growing challenge that these disorders pose for health systems in developed and developing regions. In view of the magnitude of their contribution, improvement in population health is only possible if countries make the prevention and treatment of mental and substance use disorders a public health priority.

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Background Up-to-date evidence on levels and trends for age-sex-specific all-cause and cause-specific mortality is essential for the formation of global, regional, and national health policies. In the Global Burden of Disease Study 2013 (GBD 2013) we estimated yearly deaths for 188 countries between 1990, and 2013. We used the results to assess whether there is epidemiological convergence across countries. Methods We estimated age-sex-specific all-cause mortality using the GBD 2010 methods with some refinements to improve accuracy applied to an updated database of vital registration, survey, and census data. We generally estimated cause of death as in the GBD 2010. Key improvements included the addition of more recent vital registration data for 72 countries, an updated verbal autopsy literature review, two new and detailed data systems for China, and more detail for Mexico, UK, Turkey, and Russia. We improved statistical models for garbage code redistribution. We used six different modelling strategies across the 240 causes; cause of death ensemble modelling (CODEm) was the dominant strategy for causes with sufficient information. Trends for Alzheimer's disease and other dementias were informed by meta-regression of prevalence studies. For pathogen-specific causes of diarrhoea and lower respiratory infections we used a counterfactual approach. We computed two measures of convergence (inequality) across countries: the average relative difference across all pairs of countries (Gini coefficient) and the average absolute difference across countries. To summarise broad findings, we used multiple decrement life-tables to decompose probabilities of death from birth to exact age 15 years, from exact age 15 years to exact age 50 years, and from exact age 50 years to exact age 75 years, and life expectancy at birth into major causes. For all quantities reported, we computed 95% uncertainty intervals (UIs). We constrained cause-specific fractions within each age-sex-country-year group to sum to all-cause mortality based on draws from the uncertainty distributions. Findings Global life expectancy for both sexes increased from 65·3 years (UI 65·0–65·6) in 1990, to 71·5 years (UI 71·0–71·9) in 2013, while the number of deaths increased from 47·5 million (UI 46·8–48·2) to 54·9 million (UI 53·6–56·3) over the same interval. Global progress masked variation by age and sex: for children, average absolute differences between countries decreased but relative differences increased. For women aged 25–39 years and older than 75 years and for men aged 20–49 years and 65 years and older, both absolute and relative differences increased. Decomposition of global and regional life expectancy showed the prominent role of reductions in age-standardised death rates for cardiovascular diseases and cancers in high-income regions, and reductions in child deaths from diarrhoea, lower respiratory infections, and neonatal causes in low-income regions. HIV/AIDS reduced life expectancy in southern sub-Saharan Africa. For most communicable causes of death both numbers of deaths and age-standardised death rates fell whereas for most non-communicable causes, demographic shifts have increased numbers of deaths but decreased age-standardised death rates. Global deaths from injury increased by 10·7%, from 4·3 million deaths in 1990 to 4·8 million in 2013; but age-standardised rates declined over the same period by 21%. For some causes of more than 100 000 deaths per year in 2013, age-standardised death rates increased between 1990 and 2013, including HIV/AIDS, pancreatic cancer, atrial fibrillation and flutter, drug use disorders, diabetes, chronic kidney disease, and sickle-cell anaemias. Diarrhoeal diseases, lower respiratory infections, neonatal causes, and malaria are still in the top five causes of death in children younger than 5 years. The most important pathogens are rotavirus for diarrhoea and pneumococcus for lower respiratory infections. Country-specific probabilities of death over three phases of life were substantially varied between and within regions. Interpretation For most countries, the general pattern of reductions in age-sex specific mortality has been associated with a progressive shift towards a larger share of the remaining deaths caused by non-communicable disease and injuries. Assessing epidemiological convergence across countries depends on whether an absolute or relative measure of inequality is used. Nevertheless, age-standardised death rates for seven substantial causes are increasing, suggesting the potential for reversals in some countries. Important gaps exist in the empirical data for cause of death estimates for some countries; for example, no national data for India are available for the past decade.

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Background Climate change may affect mortality associated with air pollutants, especially for fine particulate matter (PM2.5) and ozone (O3). Projection studies of such kind involve complicated modelling approaches with uncertainties. Objectives We conducted a systematic review of researches and methods for projecting future PM2.5-/O3-related mortality to identify the uncertainties and optimal approaches for handling uncertainty. Methods A literature search was conducted in October 2013, using the electronic databases: PubMed, Scopus, ScienceDirect, ProQuest, and Web of Science. The search was limited to peer-reviewed journal articles published in English from January 1980 to September 2013. Discussion Fifteen studies fulfilled the inclusion criteria. Most studies reported that an increase of climate change-induced PM2.5 and O3 may result in an increase in mortality. However, little research has been conducted in developing countries with high emissions and dense populations. Additionally, health effects induced by PM2.5 may dominate compared to those caused by O3, but projection studies of PM2.5-related mortality are fewer than those of O3-related mortality. There is a considerable variation in approaches of scenario-based projection researches, which makes it difficult to compare results. Multiple scenarios, models and downscaling methods have been used to reduce uncertainties. However, few studies have discussed what the main source of uncertainties is and which uncertainty could be most effectively reduced. Conclusions Projecting air pollution-related mortality requires a systematic consideration of assumptions and uncertainties, which will significantly aid policymakers in efforts to manage potential impacts of PM2.5 and O3 on mortality in the context of climate change.