Evidence map›Paper›PMID 26133019›Full record

ArticleEpidemiology (Cambridge, Mass.)2015

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

Gustav Kjellsson, Ulf-G Gerdtham, Dennis Petrie

Abstract read
In one paragraph

Article in Epidemiology (Cambridge, Mass.), 2015. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 35 papers.

0numbers the graph read from it
0cells of the map it votes in
35citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

35 citing papers in PubMed.

  1. Measuring and decomposing income inequalities in child and adolescent mental health in the UK.The European journal of health economics : HEPAC : health economics in prevention and care · 2026
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  6. Evaluating Effects of Multilevel Interventions on Disparity in Health and Healthcare Decisions.Prevention science : the official journal of the Society for Prevention Research · 2024
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4 · The record

Corrections and comments

5 · Who and what money

Authors and funding

3 authors.

Gustav KjellssonFrom the aDepartment of Economics, University of Gothenburg, Gothenburg, Sweden; bDepartment of Economics, cHealth Economics & Management, Institute of Economic Research, Lund University, Lund, Sweden; dCenter for Primary Health Care Research, Lund University/Region Skåne, Lund, Sweden; and eCentre for Health Policy, School of Population and Global Health, The University of Melbourne, Melbourne, VIC, Australia.
Ulf-G Gerdtham
Dennis Petrie

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

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 policymakers 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.

Indexed as

Health Status DisparitiesJudgmentSocial ValuesAdultAgedAged, 80 and overBiasEpidemiologic Research DesignHealth PolicyHumansMiddle AgedPrejudiceSocioeconomic Factors

Identifiers

PMID26133019
PMCPMC4521896

What OpenQuestion holds

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Registered trials

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.