20 resultados para Mortality data

em University of Queensland eSpace - Australia


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Objective To assess whether trends in mortality from heart failure(HF) in Australia are due to a change in awareness of the condition or real changes in its epidemiology. Methods We carried out a retrospective analysis of official data on national mortality data between 1997 and 2003. A death was attributed to HF if the death certificate mentioned HF as either the underlying cause of death (UCD) or among the contributory factors. Findings From a total of 907 242 deaths, heart failure was coded as the UCD for 29 341 (3.2%) and was mentioned anywhere on the death certificate in 135 268 (14.9%). Between 1997 and 2003, there were decreases in the absolute numbers of deaths and in the age-specific and age-standardized mortality rates for HF either as UCD or mentioned anywhere for both sexes. HF was mentioned for 24.6% and 17.8% of deaths attributed to ischaemic heart disease and circulatory disease, respectively, and these proportions remained unchanged over the period of study. In addition, HF as UCD accounted for 8.3% of deaths attributed to circulatory disease and this did not change materially from 1997 to 2003. Conclusion The decline in mortality from HF measured as either number of deaths or rate probably reflects a real change in the epidemiology of HF. Population-based studies are required to determine accurately the contributions of changes in incidence, survival and demographic factors to the evolving epidemiology of HF.

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Objective: To examine the frequency distribution of co-existing conditions for deaths where the underlying cause was infectious and parasitic diseases. Materials and methods: Besides the underlying cause of death, the distributions of co-existing conditions for deaths from infectious and parasitic diseases were examined in total and by various age and sex groups, at individual and chapter levels, using 1998 Australian mortality data. Results: In addition to the underlying cause of death, the average number of reported co-existing conditions for a single infectious and parasitic death was 1.62. The most common co-existing conditions were respiratory failure, acute renal failure non-specific causes, ischaemic heart disease, pneumonia and diabetes. When studying the distribution of co-existing conditions at the ICD-9 chapter level, it was found that the circulatory system diseases were the most important. There was an increasing trend in the number of reported co-existing conditions from 60 years of age upwards. Gender differences existed in the frequency of some reported co-existing conditions. The most common organism types of co-existing conditions were other bacterial infection and other viruses. Conclusions: The study indicated that the quality of death certificates is less than satisfactory for the 1998 Australian mortality data. The findings may be helpful in clarifying the ICD coding rules and the development of disease prevention strategies. (C) 2003 International Society for Infectious Diseases. Published by Elsevier Ltd. All rights reserved.

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Registration of births, recording deaths by age, sex and cause, and calculating mortality levels and differentials are fundamental to evidence-based health policy, monitoring and evaluation. Yet few of the countries with the greatest need for these data have functioning systems to produce them despite legislation providing for the establishment and maintenance of vital registration. Sample vital registration (SVR), when applied in conjunction with validated verbal autopsy, procedures and implemented in a nationally representative sample of population clusters represents an affordable, cost-effective, and sustainable short- and medium-term solution to this problem. SVR complements other information sources by producing age-, sex-, and cause-specific mortality data that are more complete and continuous than those currently available. The tools and methods employed in an SVR system, however, are imperfect and require rigorous validation and continuous quality assurance; sampling strategies for SVR are also still evolving. Nonetheless, interest in establishing SVR is rapidly growing in Africa and Asia. Better systems for reporting and recording data on vital events will be sustainable only if developed hand-in-hand with existing health information strategies at the national and district levels; governance structures; and agendas for social research and development monitoring. If the global community wishes to have mortality measurements 5 or 10 years hence, the foundation stones of SVR must be laid today.

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Objectives: To validate verbal autopsy (VA) procedures for use in sample vital registration. Verbal autopsy is an important method for deriving cause-specific mortality estimates where disease burdens are greatest and routine cause-specific mortality data do not exist. Methods: Verbal autopsies and medical records (MR) were collected for 3123 deaths in the perinatal/neonatal period, post-neonatal < 5 age group, and for ages of 5 years and over in Tanzania. Causes of death were assigned by physician panels using the International Classification of Disease, revision 10. Validity was measured by: cause-specific mortality fractions (CSMF); sensitivity; specificity and positive predictive value. Medical record diagnoses were scored for degree of uncertainty, and sensitivity and specificity adjusted. Criteria for evaluating VA performance in generating true proportional mortality were applied. Results: Verbal autopsy produced accurate CSMFs for nine causes in different age groups: birth asphyxia; intrauterine complications; pneumonia; HIV/AIDS; malaria (adults); tuberculosis; cerebrovascular diseases; injuries and direct maternal causes. Results for 20 other causes approached the threshold for good performance. Conclusions: Verbal autopsy reliably estimated CSMFs for diseases of public health importance in all age groups. Further validation is needed to assess reasons for lack of positive results for some conditions.

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Objective To compare mortality burden estimates based on direct measurement of levels and causes in communities with indirect estimates based on combining health facility cause-specific mortality structures with community measurement of mortality levels. Methods. Data from sentinel vital registration (SVR) with verbal autopsy (VA) were used to determine the cause-specific mortality burden at the community level in two areas of the United Republic of Tanzania. Proportional cause-specific mortality structures from health facilities were applied to counts of deaths obtained by SVR to produce modelled estimates. The burden was expressed in years of life lost. Findings. A total of 2884 deaths were recorded from health facilities and 2167 recorded from SVR/VAs. In the perinatal and neonatal age group cause-specific mortality rates were dominated by perinatal conditions and stillbirths in both the community and the facility data. The modelled estimates for chronic causes were very similar to those from SVR/VA. Acute febrile illnesses were coded more specifically in the facility data than in the VA. Injuries were more prevalent in the SVR/VA data than in that from the facilities. Conclusion. In this setting, improved International classification of diseases and health related problems, tenth revision (ICD-10) coding practices and applying facility-based cause structures to counts of deaths from communities, derived from SVR, appears to produce reasonable estimates of the cause-specific mortality burden in those aged 5 years and older determined directly from VA. For the perinatal and neonatal age group, VA appears to be required. Use of this approach in a nationally representative sample of facilities may produce reliable national estimates of the cause-specific mortality burden for leading causes of death in adults.

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Background: Hospital performance reports based on administrative data should distinguish differences in quality of care between hospitals from case mix related variation and random error effects. A study was undertaken to determine which of 12 diagnosis-outcome indicators measured across all hospitals in one state had significant risk adjusted systematic ( or special cause) variation (SV) suggesting differences in quality of care. For those that did, we determined whether SV persists within hospital peer groups, whether indicator results correlate at the individual hospital level, and how many adverse outcomes would be avoided if all hospitals achieved indicator values equal to the best performing 20% of hospitals. Methods: All patients admitted during a 12 month period to 180 acute care hospitals in Queensland, Australia with heart failure (n = 5745), acute myocardial infarction ( AMI) ( n = 3427), or stroke ( n = 2955) were entered into the study. Outcomes comprised in-hospital deaths, long hospital stays, and 30 day readmissions. Regression models produced standardised, risk adjusted diagnosis specific outcome event ratios for each hospital. Systematic and random variation in ratio distributions for each indicator were then apportioned using hierarchical statistical models. Results: Only five of 12 (42%) diagnosis-outcome indicators showed significant SV across all hospitals ( long stays and same diagnosis readmissions for heart failure; in-hospital deaths and same diagnosis readmissions for AMI; and in-hospital deaths for stroke). Significant SV was only seen for two indicators within hospital peer groups ( same diagnosis readmissions for heart failure in tertiary hospitals and inhospital mortality for AMI in community hospitals). Only two pairs of indicators showed significant correlation. If all hospitals emulated the best performers, at least 20% of AMI and stroke deaths, heart failure long stays, and heart failure and AMI readmissions could be avoided. Conclusions: Diagnosis-outcome indicators based on administrative data require validation as markers of significant risk adjusted SV. Validated indicators allow quantification of realisable outcome benefits if all hospitals achieved best performer levels. The overall level of quality of care within single institutions cannot be inferred from the results of one or a few indicators.

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PURPOSE: To determine the efficacy of exercise training and its effects on outcomes in patients with heart failure. METHODS: MEDLINE, Medscape, and the Cochrane Controlled Trials Registry were searched for trials of exercise training in heart failure patients. Data relating to training protocol, exercise capacity, and outcome measures were extracted and reviewed. RESULTS: A total of 81 studies were identified: 30 randomized controlled trials, five nonrandomized controlled trials, nine randomized crossover trials, and 37 longitudinal cohort studies. Exercise training was performed in 2387 patients. The average increment in peak oxygen consumption was 17% in 57 studies that measured oxygen consumption directly, 17% in 40 studies of aerobic training, 9% in three studies that only used strength training, 15% in 13 studies of combined aerobic and strength training, and 16% in the one study on inspiratory training. There were no reports of deaths that were directly related to exercise during more than 60,000 patient-hours of exercise training. During the training and follow-up periods of the randomized controlled trials, there were 56 combined (deaths or adverse events) events in the exercise groups and 75 combined events in the control groups (odds ratio [OR] = 0.98; 95% confidence interval [Cl]: 0.61 to 1.32; P = 0.60). During this same period, 26 exercising and 41 nonexercising subjects died (OR = 0.71; 95% CT: 0.37 to 1.02; P = 0.06). CONCLUSION: Exercise training is safe and effective in patients with heart failure. The risk of adverse events may be reduced, but further studies are required to determine whether there is any mortality benefit. (C) 2004 by Excerpta Medica Inc.

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The purpose of this work was to model lung cancer mortality as a function of past exposure to tobacco and to forecast age-sex-specific lung cancer mortality rates. A 3-factor age-period-cohort (APC) model, in which the period variable is replaced by the product of average tar content and adult tobacco consumption per capita, was estimated for the US, UK, Canada and Australia by the maximum likelihood method. Age- and sex-specific tobacco consumption was estimated from historical data on smoking prevalence and total tobacco consumption. Lung cancer mortality was derived from vital registration records. Future tobacco consumption, tar content and the cohort parameter were projected by autoregressive moving average (ARIMA) estimation. The optimal exposure variable was found to be the product of average tar content and adult cigarette consumption per capita, lagged for 2530 years for both males and females in all 4 countries. The coefficient of the product of average tar content and tobacco consumption per capita differs by age and sex. In all models, there was a statistically significant difference in the coefficient of the period variable by sex. In all countries, male age-standardized lung cancer mortality rates peaked in the 1980s and declined thereafter. Female mortality rates are projected to peak in the first decade of this century. The multiplicative models of age, tobacco exposure and cohort fit the observed data between 1950 and 1999 reasonably well, and time-series models yield plausible past trends of relevant variables. Despite a significant reduction in tobacco consumption and average tar content of cigarettes sold over the past few decades, the effect on lung cancer mortality is affected by the time lag between exposure and established disease. As a result, the burden of lung cancer among females is only just reaching, or soon will reach, its peak but has been declining for I to 2 decades in men. Future sex differences in lung cancer mortality are likely to be greater in North America than Australia and the UK due to differences in exposure patterns between the sexes. (c) 2005 Wiley-Liss, Inc.

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Background Reliable information on causes of death is a fundamental component of health development strategies, yet globally only about one-third of countries have access to such information. For countries currently without adequate mortality reporting systems there are useful models other than resource-intensive population-wide medical certification. Sample-based mortality surveillance is one such approach. This paper provides methods for addressing appropriate sample size considerations in relation to mortality surveillance, with particular reference to situations in which prior information on mortality is lacking. Methods The feasibility of model-based approaches for predicting the expected mortality structure and cause composition is demonstrated for populations in which only limited empirical data is available. An algorithm approach is then provided to derive the minimum person-years of observation needed to generate robust estimates for the rarest cause of interest in three hypothetical populations, each representing different levels of health development. Results Modelled life expectancies at birth and cause of death structures were within expected ranges based on published estimates for countries at comparable levels of health development. Total person-years of observation required in each population could be more than halved by limiting the set of age, sex, and cause groups regarded as 'of interest'. Discussion The methods proposed are consistent with the philosophy of establishing priorities across broad clusters of causes for which the public health response implications are similar. The examples provided illustrate the options available when considering the design of mortality surveillance for population health monitoring purposes.

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Although smoking is widely recognized as a major cause of cancer, there is little information on how it contributes to the global and regional burden of cancers in combination with other risk factors that affect background cancer mortality patterns. We used data from the American Cancer Society's Cancer Prevention Study II (CPS-II) and the WHO and IARC cancer mortality databases to estimate deaths from 8 clusters of site-specific cancers caused by smoking, for 14 epidemiologic subregions of the world, by age and sex. We used lung cancer mortality as an indirect marker for accumulated smoking hazard. CPS-II hazards were adjusted for important covariates. In the year 2000, an estimated 1.42 (95% CI 1.27-1.57) million cancer deaths in the world, 21% of total global cancer deaths, were caused by smoking. Of these, 1.18 million deaths were among men and 0.24 million among women; 625,000 (95% CI 485,000-749,000) smoking-caused cancer deaths occurred in the developing world and 794,000 (95% CI 749,000-840,000) in industrialized regions. Lung cancer accounted for 60% of smoking-attributable cancer mortality, followed by cancers of the upper aerodigestive tract (20%). Based on available data, more than one in every 5 cancer deaths in the world in the year 2000 were caused by smoking, making it possibly the single largest preventable cause of cancer mortality. There was significant variability across regions in the role of smoking as a cause of the different site-specific cancers. This variability illustrates the importance of coupling research and surveillance of smoking with that for other risk factors for more effective cancer prevention. (C) 2005 Wiley-Liss, Inc.

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In the granitic Seychelles, many shores and beaches are fringed by coral reef flats which provide protection to shores from erosion by waves. The surfaces of these reef flats support a complex ecology. About 10 years ago their seaward zones were extensively covered by a rich coral growth, which reached approximately to mean low water level, but in 1998 this was largely killed by seawater warming. The resulting large expanses of dead coral skeletons in these locations are now disintegrating, and much of the subsequent modest recovery by new coral recruitment was set back by further mortalities. A mathematical model of wave energy reaching shorelines protected by coral reef flats has been applied to 14 Seychelles reefs. It is derived from equations which predict: (1) the raised water level, or wave set-up, on reef flats resulting from wave breaking, which depends upon offshore wave height and period, depth of still water over the reef flat and the reef crest profile, and (2) the decay of energy from reef edge to shoreline that is affected by width of reef flat, surface roughness, sea level rise and 'pseudo-sea level rise' created by increased depth resulting from disintegration of coral colonies. The model treats each reef as one entity, but because biota and zonation on reef flats are not homogenous, all reefs are divided into four zones. In each, cover by both living and dead biota was estimated for calculation of parameters, and then averaged to obtain input data for the model. All possible biological factors were taken into account, such as the ability of seagrass beds to grow upwards to match expected sea level rise, reduction in height of the reef flat in relation to sea level as zones of dead corals decay, and the observed 'rounding' of reef crests as erosion removes corals from those areas. Estimates were also made of all these factors for a time approximately a decade ago, representing a time before the mass coral mortality, and for approximately a decade in the future when the observed rapid state of dead coral colony disintegration is assumed to have reached an end point. Results of increased energy over the past decade explain observations of erosion in some sites in the Seychelles. Most importantly, it is estimated that the rise in energy reaching shores protected by fringing reefs will now accelerate more rapidly, such that the increase expected over the next decade will be approximately double than that seen over the past decade. (c) 2005 Elsevier Ltd. All rights reserved.

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Background-Elevated serum inflammatory marker levels are associated with a greater long-term risk of cardiovascular events. Because 3-hydroxy-3-methylglutaryl coenzyme-A reductase inhibitors (statins) may have an antiinflammatory action, it has been suggested that patients with elevated inflammatory marker levels may have a greater reduction in cardiovascular risk with statin treatment. Methods and Results-We evaluated the association between the white blood cell count (WBC) and coronary heart disease mortality during a mean follow-up of 6.0 years in the Long-Term Intervention With Pravastatin in Ischemic Disease (LIPID) Study, a clinical trial comparing pravastatin (40 mg/d) with a placebo in 9014 stable patients with previous myocardial infarction or unstable angina. An increase in baseline WBC was associated with greater coronary heart disease mortality in patients randomized to placebo (hazard ratio for 1 X 10(9)/L increase in WBC, 1.18; 95% CI, 1.12 to 1.25; P<0.001) but not pravastatin (hazard ratio, 1.02; 95% CI, 0.96 to 1.09; P=0.56; P for interaction=0.004). The numbers of coronary heart disease deaths prevented per 1000 patients treated with pravastatin were 0, 9, 30, and 38 for baseline WBC quartiles of <5.9, 6.0 to 6.9, 7.0 to 8.1, and >8.2X10(9)/L, respectively. WBC was a stronger predictor of this treatment benefit than the ratio of total to high-density lipoprotein cholesterol and a global measure of cardiac risk. There was also a greater reduction (P=0.052) in the combined incidence of cardiovascular mortality, nonfatal myocardial infarction, and stroke with pravastatin as baseline WBC increased ( by quartile: 3, 41, 61, and 60 events prevented per 1000 patients treated, respectively). Conclusions-These data support the hypothesis that individuals with evidence of inflammation may obtain a greater benefit from statin therapy.

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Background - Smoking is a major cause of cardiovascular disease mortality. There is little information on how it contributes to global and regional cause-specific mortality from cardiovascular diseases for which background risk varies because of other risks. Method and Results - We used data from the American Cancer Society's Cancer Prevention Study II (CPS II) and the World Health Organization Global Burden of Disease mortality database to estimate smoking-attributable deaths from ischemic heart disease, cerebrovascular disease, and a cluster of other cardiovascular diseases for 14 epidemiological subregions of the world by age and sex. We used lung cancer mortality as an indirect marker for accumulated smoking hazard. CPS-II hazards were adjusted for important covariates. In the year 2000, an estimated 1.62 (95% CI, 1.27 to 2.04) million cardiovascular deaths in the world, 11% of total global cardiovascular deaths, were due to smoking. Of these, 1.17 million deaths were among men and 450 000 among women. There were 670 000 (95% CI, 440 000 to 920 000) smoking-attributable cardiovascular deaths in the developing world and 960 000 (95% CI, 770 000 to 1 200 000) in industrialized regions. Ischemic heart disease accounted for 54% of smoking-attributable cardiovascular mortality, followed by cerebrovascular disease (25%). There was variability across regions in the role of smoking as a cause of various cardiovascular diseases. Conclusions - More than 1 in every 10 cardiovascular deaths in the world in the year 2000 were attributable to smoking, demonstrating that it is an important preventable cause of cardiovascular mortality.

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Objective Comparisons of the changing patterns of inequalities in occupational mortality provide one way to monitor the achievement of equity goals. However, previous comparisons have not corrected for numerator/denominator bias, which is a consequence of the different ways in which occupational details are recorded on death certificates and on census forms. The objective of this study was to measure the impact of this bias on mortality rates and ratios over time. Methods Using data provided by the Australian Bureau of Statistics, we examined the evidence for bias over the period 1981-2002, and used imputation methods to adjust for this bias. We compared unadjusted with imputed rates of mortality for manual/non-manual workers. Findings Unadjusted data indicate increasing inequality in the age-adjusted rates of mortality for manual/non-manual workers during 1981-2002, Imputed data suggest that there have been modest fluctuations in the ratios of mortality for manual/non-manual workers during this time, but with evidence that inequalities have increased only in recent years and are now at historic highs. Conclusion We found that imputation for missing data leads to changes in estimates of inequalities related to social class in mortality for some years but not for others. Occupational class comparisons should be imputed or otherwise adjusted for missing data on census or death certificates.