Evidence map›Paper›PMID 33394809›Full record

ArticleEpidemiology (Cambridge, Mass.)2021

Meaningful Causal Decompositions in Health Equity Research: Definition, Identification, and Estimation Through a Weighting Framework.

John W Jackson

Erratum issuedAbstract read
In one paragraph

Article in Epidemiology (Cambridge, Mass.), 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. An erratum has been issued. Cited by 56 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
56citing 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

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

  1. Pooled it
  2. Article
  3. Observational
  4. Review
  5. Article
  6. Article
  7. Causal Inference in Health Disparities Research.Annual review of public health · 2026
    Review
  8. Straining Under Contradiction? Contradictory Class Locations and Job Strain in the United States.International journal of social determinants of health and health services · 2026
    Article
  9. Article
  10. Article
  11. Article
  12. Article
  13. Article
  14. Article
  15. Article
  16. 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
  17. Observational
  18. Article
  19. Article
  20. Article
4 · The record

Corrections and comments

5 · Who and what money

Authors and funding

1 author.

John W JacksonFrom the Department of Epidemiology, Johns Hopkins Bloomberg School of Public Health, Baltimore, MD.

Funding

Systems Science for Translational Health Disparities ResearchK01HL145320 · NHLBI · JOHNS HOPKINS UNIVERSITY · PI JACKSON, JOHN WILLIAM · 2019 to 2023
$832k
NHLBI NIH HHS K01 HL145320
6 · The paper itself

Abstract

Causal decomposition analyses can help build the evidence base for interventions that address health disparities (inequities). They ask how disparities in outcomes may change under hypothetical intervention. Through study design and assumptions, they can rule out alternate explanations such as confounding, selection bias, and measurement error, thereby identifying potential targets for intervention. Unfortunately, the literature on causal decomposition analysis and related methods have largely ignored equity concerns that actual interventionists would respect, limiting their relevance and practical value. This article addresses these concerns by explicitly considering what covariates the outcome disparity and hypothetical intervention adjust for (so-called allowable covariates) and the equity value judgments these choices convey, drawing from the bioethics, biostatistics, epidemiology, and health services research literatures. From this discussion, we generalize decomposition estimands and formulae to incorporate allowable covariate sets (and thereby reflect equity choices) while still allowing for adjustment of non-allowable covariates needed to satisfy causal assumptions. For these general formulae, we provide weighting-based estimators based on adaptations of ratio-of-mediator-probability and inverse-odds-ratio weighting. We discuss when these estimators reduce to already used estimators under certain equity value judgments, and a novel adaptation under other judgments.

Indexed as

Health EquityCausalityHumansModels, StatisticalProbabilityResearch Design

Identifiers

PMID33394809
PMCPMC8478117

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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.