994 resultados para Occupational mortality


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Background: To compare the likely costs and benefits of a range of potential policy interventions in Fiji and Tonga targeted at diet-related noncommunicable diseases (NCDs), in order to support more evidence-based decision-making.

Method: A relatively simple and quick macro-simulation methodology was developed. Logic models were developed by local stakeholders and used to identify costs and dietary impacts of policy changes. Costs were confined to government costs, and excluded cost offsets. The best available evidence was combined with local data to model impacts on deaths from noncommunicable diseases over the lifetime of the target population. Given that the modelling necessarily entailed assumptions to compensate for gaps in data and evidence, use was made of probabilistic uncertainty analysis.

Results:
Costs of implementing policy changes were generally low, with the exception of some requiring additional long-term staffing or construction activities. The most effective policy options in Fiji and Tonga targeted access to local produce and high-fat meats respectively, and were estimated to avert approximately 3% of diet-related NCD deaths in each population. Many policies had substantially lower benefits. Cost-effectiveness was higher for the low-cost policies. Similar policies produced markedly different results in the two countries.

Conclusion:
Despite the crudeness of the method, the consistent modelling approach used across all the options, allowed reasonable comparisons to be made between the potential policy costs and impacts. This type of modelling can be used to support more evidence-based and informed decision-making about policy interventions and facilitate greater use of policy to achieve a reduction in NCDs.

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In-hospital mortality rates associated with an ICU stay are high and vary widely among units. This variation may be related to organizational factors such as staffing patterns, ICU structure, and care processes. We aimed to identify organizational factors associated with variation in in-hospital mortality for patients with an ICU stay. This was a retrospective observational cross-sectional study using administrative data from 34 093 patients from 171 ICUs in 119 Veterans Health Administration hospitals. Staffing and patient data came from Veterans Health Administration national databases. ICU characteristics came from a survey in 2004 of ICUs within the Veterans Health Administration. We conducted multilevel multivariable estimation with patient-, unit-, and hospital-level data. The primary outcome was in-hospital mortality. Of 34 093 patients, 2141 (6.3%)died in the hospital. At the patient level, risk of complications and having a medical diagnosis were significantly associated with a higher risk of mortality. At the unit level, having an interface with the electronic medical record was significantly associated with a lower risk of mortality. The finding that electronic medical records integrated with ICU information systems are associated with lower in-hospital mortality adds support to existing evidence on organizational characteristics associated with in-hospital mortality among ICU patients.

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There are substantial geographic variations in coronary heart disease (CHD) mortality rates in England that may in part be due to differences in climate and air pollution. An ecological cross-sectional multi-level analysis of male and female CHD mortality rates in all wards in England (1999–2004) was conducted to estimate the relative strength of the association between CHD mortality rates and three aspects of the physical environment - temperature, hours of sunshine and air quality. Models were adjusted for deprivation, an index measuring the healthiness of the lifestyle of populations, and urbanicity. In the fully adjusted model, air quality was not significantly associated with CHD mortality rates, but temperature and sunshine were both significantly negatively associated (p<0.05), suggesting that CHD mortality rates were higher in areas with lower average temperature and hours of sunshine. After adjustment for the unhealthy lifestyle of populations and deprivation, the climate variables explained at least 15% of large scale variation in CHD mortality rates. The results suggest that the climate has a small but significant independent association with CHD mortality rates in England.

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Background Higher waist circumference and lower hip circumference are both associated with increased cardiovascular disease (CVD) risk, despite being directly correlated. The real effects of visceral obesity may therefore be underestimated when hip circumference is not fully taken into account. We hypothesized that adding waist and hip circumference to traditional risk factors would significantly improve CVD risk prediction.

Methods
In a population-based survey among South Asian and African Mauritians (n = 7978), 1241 deaths occurred during 15 years of follow-up. In a model that included variables used in previous CVD risk calculations (a Framingham-type model), the association between waist circumference and mortality was examined before and after adjustment for hip circumference. The percentage with an increase in estimated 10-year cumulative mortality of >25% and a decrease of >20% after waist and hip circumference were added to the model was calculated.

Results Waist circumference was strongly related to mortality only after adjustment for hip circumference and vice versa. Adding waist and hip circumference to a Framingham-type model increased estimated 10-year cumulative CVD mortality by >25% for 23.7% of those who died and 15.7% of those censored. Cumulative mortality decreased by >20% for 4.5% of those who died and 14.8% of those censored.

Conclusions
The effect of central obesity on mortality risk is seriously underestimated without adjustment for hip circumference. Adding waist and hip circumference to a Framingham-type model for CVD mortality substantially increased predictive power. Both may be important inclusions in CVD risk prediction models.

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Objective: This study investigated the sensitivity and specificity of the national mortality codes in identifying cardiovascular disease (CVD) deaths and documents methods of verification.

Methods: A 12-year retrospective case ascertainment of all ICD-coded CVD deaths was performed for deaths between 1990 and 2002 in the Melbourne Collaborative Cohort Study, comprising 41,528 subjects. Categories of non-CVD codes were also examined. Stratified samples of 750 deaths were adjudicated from a total of 2,230 deaths. Expert panels of cardiologists and neurologists adjudicated deaths.

Results: Of the 750 deaths adjudicated, 582 were verified as CVD [392 coronary heart disease (CHD) and 92 stroke] and 168 non-CVD. Estimated sensitivity and specificity of national mortality codes for identifying specific causes of death were: CHD 74.2% (95% CI: 69.8–78.5%) and 97.6% (96.0–99.2%), respectively; myocardial infarction 59.9% (50.9–69.0%) and 94.2% (92.4–96.0%), respectively; haemorrhagic stroke 58.9% (46.0–71.7%) and 99.8% (99.4–100.0%), respectively and; ischaemic stroke 38.7% (20.5–56.9%) and 99.9% (99.6–100.0%), respectively. Misclassification was most common for deaths with primary ICD codes for endocrine-metabolic and genito-urinary diseases.

Conclusions: National mortality coding under-estimated the true proportion of CHD and stroke deaths in the cohort by 13.6% and 50.8%, respectively.

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Background While the relationship between socio-economic disadvantage and cardiovascular disease (CVD) is well established, the role that traditional cardiovascular risk factors play in this association remains unclear. The authors examined the association between education attainment and CVD mortality and the extent to which behavioural, social and physiological factors explained this relationship.

Methods Adults (n=38 355) aged 40–69 years living in Melbourne, Australia were recruited in 1990–1994. Subjects with baseline CVD risk factor data ascertained through questionnaire and physical measurement were followed for an average of 9.4 years with CVD deaths verified by review of medical records and autopsy reports.

Results CVD mortality was higher for those with primary education only, compared with those who had completed tertiary education, with an HR of 1.66 (95% CI 1.10 to 2.49) after adjustment for age, country of birth and gender. Those from the lowest educated group had a more adverse cardiovascular risk factor profile compared with the highest educated group, and adjustment for these risk factors reduced the HR to 1.18 (95% CI 0.78 to 1.77). In analysis of individual risk factors, smoking and waist circumference explained most of the difference in CVD mortality between the highest and lowest education groups.

Conclusions Most of the excess CVD mortality in lower socio-economic groups can be explained by known risk factors, particularly smoking and overweight. While targeting cardiovascular risk factors should not divert efforts from addressing the underlying determinants of health inequalities, it is essential that known risk factors are addressed effectively among lower socio-economic groups.

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