Approximations for Estimating Change in Life Expectancy Attributable to Air Pollution in Relation to Multiple Causes of Death Using a Cause Modified Life Table

Risk Analysis ◽  
2015 ◽  
Vol 35 (8) ◽  
pp. 1468-1478 ◽  
Author(s):  
David M. Stieb ◽  
Stan Judek ◽  
Kevin Brand ◽  
Richard T. Burnett ◽  
Hwashin H. Shin
Author(s):  
Eliane Miranda da Silva ◽  
Gulnar Azevedo e Silva ◽  
Norma de Paula Motta Rubini ◽  
Carlos Alberto Morais de Sá

2009 ◽  
Vol 39 (2) ◽  
pp. 253-265
Author(s):  
Kamel Alsaleh ◽  
Mesa Al-Saleh ◽  
Saadoun Al-Azmi ◽  
Ibtesam Alfares ◽  
Bader Alnashi ◽  
...  

2005 ◽  
Vol 5 (1) ◽  
Author(s):  
Melanie M Wall ◽  
Jinzhou Huang ◽  
John Oswald ◽  
Diane McCullen

2019 ◽  
Vol 35 (5) ◽  
Author(s):  
Ana Luiza Bierrenbach ◽  
Gizelton Pereira Alencar ◽  
Cátia Martinez ◽  
Maria de Fátima Marinho de Souza ◽  
Gabriela Moreira Policena ◽  
...  

Heart failure is considered a garbage code when assigned as the underlying cause of death. Reassigning garbage codes to plausible causes reduces bias and increases comparability of mortality data. Two redistribution methods were applied to Brazilian data, from 2008 to 2012, for decedents aged 55 years and older. In the multiple causes of death method, heart failure deaths were redistributed based on the proportion of underlying causes found in matched deaths that had heart failure listed as an intermediate cause. In the hospitalization data method, heart failure deaths were redistributed based on data from the decedents’ corresponding hospitalization record. There were 123,269 (3.7%) heart failure deaths. The method with multiple causes of death redistributed 25.3% to hypertensive heart and kidney diseases, 22.6% to coronary heart diseases and 9.6% to diabetes. The total of 41,324 heart failure deaths were linked to hospitalization records. Heart failure was listed as the principal diagnosis in 45.8% of the corresponding hospitalization records. For those, no redistribution occurred. For the remaining ones, the hospitalization data method redistributed 21.2% to a group with other (non-cardiac) diseases, 6.5% to lower respiratory infections and 9.3% to other garbage codes. Heart failure is a frequently used garbage code in Brazil. We used two redistribution methods, which were straightforwardly applied but led to different results. These methods need to be validated, which can be done in the wake of a recent national study that will investigate a big sample of hospital deaths with garbage codes listed as underlying causes.


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