Evidence map›Paper›PMID 30063540›Full record

ArticleEpidemiology (Cambridge, Mass.)2018

Decomposition Analysis to Identify Intervention Targets for Reducing Disparities.

John W Jackson, Tyler J VanderWeele

Abstract read
In one paragraph

Article in Epidemiology (Cambridge, Mass.), 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 73 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
73citing papers in PubMed, 1 pooled it
–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

73 citing papers in PubMed, 1 synthesis or guideline pooled it.

  1. Pooled it
  2. Trial
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  8. Article
  9. Causal Inference in Health Disparities Research.Annual review of public health · 2026
    Review
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  16. The toll of caregiving: life-course family care and disparities in physical functioning.The journals of gerontology. Series B, Psychological sciences and social sciences · 2026
    Article
  17. Article
  18. Article
  19. Three-Way Decomposition for Applied Health Equity Research: A Practical Tutorial to Understand and Address Inequalities.Prevention science : the official journal of the Society for Prevention Research · 2025
    Article
  20. Article

13 more citing papers are in PubMed but not listed here.

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

2 authors.

John W JacksonFrom the Department of Epidemiology, Johns Hopkins Bloomberg School of Public Health, Baltimore, MD.
Tyler J VanderWeeleDepartment of Epidemiology, Harvard T.H. Chan School of Public Health, Boston, MA.

Funding

Theory and methods for mediation and interactionR01CA222147 · NCI · HARVARD SCHOOL OF PUBLIC HEALTH · PI TCHETGEN TCHETGEN, ERIC JOEL, VANDERWEELE, TYLER · 2018 to 2022
$2.1M
Theory and methods for sufficient cause interactionsR01ES017876 · NIEHS · HARVARD SCHOOL OF PUBLIC HEALTH · PI VANDERWEELE, TYLER · 2010 to 2014
$1.2M
Theory and methods for interactionR56ES017876 · NIEHS · HARVARD SCHOOL OF PUBLIC HEALTH · PI TCHETGEN TCHETGEN, ERIC JOEL, VANDERWEELE, TYLER · 2016 to 2016
$150k
NCI NIH HHS R01 CA222147NIEHS NIH HHS R01 ES017876NIEHS NIH HHS R56 ES017876NIMH NIH HHS L30 MH111012
6 · The paper itself

Abstract

There has been considerable interest in using decomposition methods in epidemiology (mediation analysis) and economics (Oaxaca-Blinder decomposition) to understand how health disparities arise and how they might change upon intervention. It has not been clear when estimates from the Oaxaca-Blinder decomposition can be interpreted causally because its implementation does not explicitly address potential confounding of target variables. While mediation analysis does explicitly adjust for confounders of target variables, it typically does so in a way that effectively entails equalizing confounders across racial groups, which may not reflect the intended intervention. Revisiting prior analyses in the National Longitudinal Survey of Youth on disparities in wages, unemployment, incarceration, and overall health with test scores, taken as a proxy for educational attainment, as a target intervention, we propose and demonstrate a novel decomposition that controls for confounders of test scores (e.g., measures of childhood socioeconomic status [SES]) while leaving their association with race intact. We compare this decomposition with others that use standardization (to equalize childhood SES [the confounders] alone), mediation analysis (to equalize test scores within levels of childhood SES), and one that equalizes both childhood SES and test scores. We also show how these decompositions, including our novel proposals, are equivalent to implementations of the Oaxaca-Blinder decomposition but provide a more formal causal interpretation for these decompositions.

Indexed as

Health Status DisparitiesAdolescentAdultHumansMaleModels, StatisticalRacial GroupsSocial ClassSocioeconomic FactorsStatistics as TopicUnited StatesYoung Adult

Identifiers

PMID30063540
PMCPMC6218173

What OpenQuestion holds

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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.