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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.

Gouda, HN; Critchley, J; Powles, J; Capewell, S (2012) 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. BMC PUBLIC HEALTH, 12 (88). ISSN 1471-2458 https://doi.org/10.1186/1471-2458-12-88
SGUL Authors: Critchley, Julia

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Abstract

BACKGROUND: 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. METHODS: 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. RESULTS: 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. CONCLUSIONS: 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.

Item Type: Article
Additional Information: PubMed ID: 22284813 © 2012 Gouda et al; BioMed Central Ltd. This is an Open Access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/2.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
Keywords: Adult, Aged, Aged, 80 and over, Bias (Epidemiology), Coronary Disease, Data Interpretation, Statistical, Female, Humans, Male, Middle Aged, Models, Statistical, Public Health, United States, Science & Technology, Life Sciences & Biomedicine, Public, Environmental & Occupational Health, Comparative Effectiveness Research, Policy analysis, Determinants of Mortality, Epidemiologic Methods, Coronary Heart Disease, RISK-FACTOR CHANGES, MYOCARDIAL-INFARCTION, BLOOD-PRESSURE, DECREASE, SCOTLAND, IRELAND, ENGLAND, WALES, RATES
SGUL Research Institute / Research Centre: Academic Structure > Population Health Research Institute (INPH)
Journal or Publication Title: BMC PUBLIC HEALTH
ISSN: 1471-2458
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Dates:
DateEvent
28 January 2012Published
Web of Science ID: WOS:000301527200001
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URI: http://sgultest.da.ulcc.ac.uk/id/eprint/1672
Publisher's version: https://doi.org/10.1186/1471-2458-12-88

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