Why choice of metric matters in public health analyses: a case study of the attribution of credit for the decline in coronary heart disease mortality in the US and other populations

<p>Abstract</p> <p>Background</p> <p>Reasons for the widespread declines in coronary heart disease (CHD) mortality in high income countries are controversial. Here we explore how the type of metric chosen for the analyses of these declines affects the answer obtained.&l...

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Main Authors: Gouda Hebe N (Author), Critchley Julia (Author), Powles John (Author), Capewell Simon (Author)
Format: Book
Published: BMC, 2012-01-01T00:00:00Z.
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042 |a dc 
100 1 0 |a Gouda Hebe N  |e author 
700 1 0 |a Critchley Julia  |e author 
700 1 0 |a Powles John  |e author 
700 1 0 |a Capewell Simon  |e author 
245 0 0 |a Why choice of metric matters in public health analyses: a case study of the attribution of credit for the decline in coronary heart disease mortality in the US and other populations 
260 |b BMC,   |c 2012-01-01T00:00:00Z. 
500 |a 10.1186/1471-2458-12-88 
500 |a 1471-2458 
520 |a <p>Abstract</p> <p>Background</p> <p>Reasons for the widespread declines in coronary heart disease (CHD) mortality in high income countries are controversial. Here we explore how the type of metric chosen for the analyses of these declines affects the answer obtained.</p> <p>Methods</p> <p>The analyses we reviewed were performed using IMPACT, a large Excel based model of the determinants of temporal change in mortality from CHD. Assessments of the decline in CHD mortality in the USA between 1980 and 2000 served as the central case study.</p> <p>Results</p> <p>Analyses based in the metric of number of deaths prevented attributed about half the decline to treatments (including preventive medications) and half to favourable shifts in risk factors. However, when mortality change was expressed in the metric of life-years-gained, the share attributed to risk factor change rose to 65%. This happened because risk factor changes were modelled as slowing disease progression, such that the hypothetical deaths averted resulted in longer average remaining lifetimes gained than the deaths averted by better treatments. This result was robust to a range of plausible assumptions on the relative effect sizes of changes in treatments and risk factors.</p> <p>Conclusions</p> <p>Time-based metrics (such as life years) are generally preferable because they direct attention to the changes in the natural history of disease that are produced by changes in key health determinants. The life-years attached to each death averted will also weight deaths in a way that better reflects social preferences.</p> 
546 |a EN 
690 |a Comparative Effectiveness Research 
690 |a Policy analysis 
690 |a Determinants of Mortality 
690 |a Epidemiologic Methods 
690 |a Coronary Heart Disease 
690 |a Public aspects of medicine 
690 |a RA1-1270 
655 7 |a article  |2 local 
786 0 |n BMC Public Health, Vol 12, Iss 1, p 88 (2012) 
787 0 |n http://www.biomedcentral.com/1471-2458/12/88 
787 0 |n https://doaj.org/toc/1471-2458 
856 4 1 |u https://doaj.org/article/1b9f0d7c41444a07b2f17e65f0b2bc90  |z Connect to this object online.