4 resultados para Adult Deaths

em University of Queensland eSpace - Australia


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Background: Smoking has been causally associated with increased mortality from several diseases, and has increased considerably in many developing countries in the past few decades. Mortality attributable to smoking in the year 2000 was estimated for adult males and females, including estimates by age and for specific diseases in 14 epidemiological subregions of the world. Methods: Lung cancer mortality was used as an indirect marker of the accumulated hazard of smoking. Never-smoker lung cancer mortality was estimated based on the household use of coal with poor ventilation. Estimates of mortality caused by smoking were made for lung cancer, upper aerodigestive cancer, all other cancers, chronic obstructive pulmonary disease ( COPD), other respiratory diseases, cardiovascular diseases, and selected other medical causes. Estimates were limited to ages 30 years and above. Results: In 2000, an estimated 4.83 million premature deaths in the world were attributable to smoking, 2.41 million in developing countries and 2.43 million in industrialised countries. There were 3.84 million male deaths and 1.00 million female deaths attributable to smoking. 2.69 million smoking attributable deaths were between the ages of 30 - 69 years, and 2.14 million were 70 years of age and above. The leading causes of death from smoking in industrialised regions were cardiovascular diseases ( 1.02 million deaths), lung cancer (0.52 million deaths), and COPD (0.31 million deaths), and in the developing world cardiovascular diseases (0.67 million deaths), COPD (0.65 million deaths), and lung cancer (0.33 million deaths). The share of male and female deaths and younger and older adult deaths, and of various diseases in total smoking attributable deaths exhibited large inter-regional heterogeneity, especially in the developing world. Conclusions: Smoking was an important cause of global mortality in 2000, affecting a large number of diseases. Age, sex, and disease patterns of smoking-caused mortality varied greatly across regions, due to both historical and current smoking patterns, and the presence of other risk factors that affect background mortality from specific diseases.

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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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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.