Evidence map›Paper›PMID 30255428›Full record

ArticleDemography2018

Poor Health Reporting? Using Anchoring Vignettes to Uncover Health Disparities by Wealth and Race.

Laura Rossouw, Teresa Bago d'Uva, Eddy van Doorslaer

Abstract read
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In one paragraph

Article in Demography, 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 6 papers.

0numbers the graph read from it
0cells of the map it votes in
6citing 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

6 citing papers in PubMed.

  1. Article
  2. Article
  3. Differences in rating of health related quality of life on the EQ-5D-5 L between ethnic groups.Quality of life research : an international journal of quality of life aspects of treatment, care and rehabilitation · 2025
    Article
  4. Article
  5. Educational Inequalities in Self-Rated Health in Europe and South Korea.International journal of environmental research and public health · 2020
    Article
  6. Article
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

3 authors.

Laura RossouwResearch on Socio-Economic Policy, Economics Department, Stellenbosch University, Stellenbosch, South Africa.
Teresa Bago d'UvaErasmus School of Economics, Erasmus University Rotterdam and Tinbergen Institute, Rotterdam, The Netherlands.
Eddy van DoorslaerResearch on Socio-Economic Policy, Economics Department, Stellenbosch University, Stellenbosch, South Africa. vandoorslaer@ese.eur.nl.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

In spite of the wide disparities in wealth and in objective health measures like mortality, observed inequality by wealth in self-reported health appears to be nearly nonexistent in low- to middle-income settings. To determine the extent to which this is driven by reporting tendencies, we use anchoring vignettes to test and correct for reporting heterogeneity in health among elderly South Africans. Significant reporting differences across wealth groups are detected. Poorer individuals rate the same health state description more positively than richer individuals. Only after we correct for these differences does a significant and substantial health disadvantage of the poor emerge. We also find that health inequality and reporting heterogeneity are confounded by race. Within race groups-especially among black Africans and to a lesser degree among whites-heterogeneous reporting leads to an underestimation of health inequalities between richest and poorest. More surprisingly, we also show that the correction may go in the opposite direction: the apparent black African (vs. white) health disadvantage within the top wealth quintile almost disappears after we correct for reporting tendencies. Such large shifts and even reversals of health gradients have not been documented in previous studies on reporting bias in health inequalities. The evidence for South Africa, with its history of racial segregation and socioeconomic inequality, highlights that correction for reporting matters greatly when using self-reported health measures in countries with such wide disparities.

Indexed as

Health Status DisparitiesAgedAged, 80 and overAge FactorsBlack PeopleData CollectionFemaleHumansIncomeMaleMental HealthMiddle AgedRacial GroupsSelf ReportSex FactorsSocioeconomic FactorsHealth measurementInequalitySelf-assessed healthSouth AfricaVignettes

Identifiers

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Registered trials

None linked

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.