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Lies, Damned Lies, and Health Inequality Measurements: Understanding the Value Judgments.

Kjellsson, Gustav; Gerdtham, Ulf LU and Petrie, Dennis (2015) In Epidemiology 26(5). p.673-680
Abstract
Measuring and monitoring socioeconomic health inequalities are critical for understanding the impact of policy decisions. However, the measurement of health inequality is far from value neutral, and one can easily present the measure that best supports one's chosen conclusion or selectively exclude measures. Improving people's understanding of the often implicit value judgments is therefore important to reduce the risk that researchers mislead or policy makers are misled. While the choice between relative and absolute inequality is already value laden, further complexities arise when, as is often the case, health variables have both a lower and upper bound, and thus can be expressed in terms of either attainments or shortfalls, such as for... (More)
Measuring and monitoring socioeconomic health inequalities are critical for understanding the impact of policy decisions. However, the measurement of health inequality is far from value neutral, and one can easily present the measure that best supports one's chosen conclusion or selectively exclude measures. Improving people's understanding of the often implicit value judgments is therefore important to reduce the risk that researchers mislead or policy makers are misled. While the choice between relative and absolute inequality is already value laden, further complexities arise when, as is often the case, health variables have both a lower and upper bound, and thus can be expressed in terms of either attainments or shortfalls, such as for mortality/survival.We bring together the recent parallel discussions from epidemiology and health economics regarding health inequality measurement and provide a deeper understanding of the different value judgments within absolute and relative measures expressed both in attainments and shortfalls, by graphically illustrating both hypothetical and real examples. We show that relative measures in terms of attainments and shortfalls have distinct value judgments, highlighting that for health variables with two bounds the choice is no longer only between an absolute and a relative measure but between an absolute, an attainment-relative and a shortfall-relative one. We illustrate how these three value judgments can be combined onto a single graph which shows the rankings according to all three measures, and illustrates how the three measures provide ethical benchmarks against which to judge the difference in inequality between populations.This is an open access article distributed under the Creative Commons Attribution License 4.0 (CCBY), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. (Less)
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author
organization
publishing date
type
Contribution to journal
publication status
published
subject
in
Epidemiology
volume
26
issue
5
pages
673 - 680
publisher
Wolters Kluwer Health/LWW
external identifiers
  • pmid:26133019
  • wos:000359726800009
  • scopus:84940049081
ISSN
1531-5487
DOI
10.1097/EDE.0000000000000319
language
English
LU publication?
yes
id
d6156176-695b-456f-8dbc-875b370fc1ce (old id 7751136)
alternative location
http://www.ncbi.nlm.nih.gov/pubmed/26133019?dopt=Abstract
date added to LUP
2015-08-01 21:25:29
date last changed
2017-09-10 03:00:57
@article{d6156176-695b-456f-8dbc-875b370fc1ce,
  abstract     = {Measuring and monitoring socioeconomic health inequalities are critical for understanding the impact of policy decisions. However, the measurement of health inequality is far from value neutral, and one can easily present the measure that best supports one's chosen conclusion or selectively exclude measures. Improving people's understanding of the often implicit value judgments is therefore important to reduce the risk that researchers mislead or policy makers are misled. While the choice between relative and absolute inequality is already value laden, further complexities arise when, as is often the case, health variables have both a lower and upper bound, and thus can be expressed in terms of either attainments or shortfalls, such as for mortality/survival.We bring together the recent parallel discussions from epidemiology and health economics regarding health inequality measurement and provide a deeper understanding of the different value judgments within absolute and relative measures expressed both in attainments and shortfalls, by graphically illustrating both hypothetical and real examples. We show that relative measures in terms of attainments and shortfalls have distinct value judgments, highlighting that for health variables with two bounds the choice is no longer only between an absolute and a relative measure but between an absolute, an attainment-relative and a shortfall-relative one. We illustrate how these three value judgments can be combined onto a single graph which shows the rankings according to all three measures, and illustrates how the three measures provide ethical benchmarks against which to judge the difference in inequality between populations.This is an open access article distributed under the Creative Commons Attribution License 4.0 (CCBY), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.},
  author       = {Kjellsson, Gustav and Gerdtham, Ulf and Petrie, Dennis},
  issn         = {1531-5487},
  language     = {eng},
  number       = {5},
  pages        = {673--680},
  publisher    = {Wolters Kluwer Health/LWW},
  series       = {Epidemiology},
  title        = {Lies, Damned Lies, and Health Inequality Measurements: Understanding the Value Judgments.},
  url          = {http://dx.doi.org/10.1097/EDE.0000000000000319},
  volume       = {26},
  year         = {2015},
}