Evidence mapPaperPMID 41222083Full record

SynthesisInternational journal of stroke : official journal of the International Stroke Society2026

A systematic review of causal pathways of socioeconomic inequalities in stroke.

Camila Pantoja-Ruiz, Lu Liu, Evelyn Lim, Marina Soley-Bori, Wasana Kalansooriya, Eva Emmett, Abdel Douiri, Yanzhong Wang, Ajay Bhalla, Amal R Khanolkar and 5 more

Abstract readSystematic Review
In one paragraph

Synthesis in International journal of stroke : official journal of the International Stroke Society, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing 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

1 citing paper in PubMed.

  1. 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

15 authors.

Camila Pantoja-RuizDepartment of Population Health Sciences, School of Life Course & Population Sciences, King's College London, London, UK.ORCID 0000-0003-4411-466X
Lu LiuDepartment of Population Health Sciences, School of Life Course & Population Sciences, King's College London, London, UK.
Evelyn LimDepartment of Population Health Sciences, School of Life Course & Population Sciences, King's College London, London, UK.
Marina Soley-BoriDepartment of Population Health Sciences, School of Life Course & Population Sciences, King's College London, London, UK.
Wasana KalansooriyaDepartment of Population Health Sciences, School of Life Course & Population Sciences, King's College London, London, UK.
Eva EmmettDepartment of Population Health Sciences, School of Life Course & Population Sciences, King's College London, London, UK.
Abdel DouiriDepartment of Population Health Sciences, School of Life Course & Population Sciences, King's College London, London, UK.ORCID 0000-0002-4354-4433
Yanzhong WangDepartment of Population Health Sciences, School of Life Course & Population Sciences, King's College London, London, UK.ORCID 0000-0002-0768-1676
Ajay BhallaDepartment of Population Health Sciences, School of Life Course & Population Sciences, King's College London, London, UK.
Amal R KhanolkarDepartment of Population Health Sciences, School of Life Course & Population Sciences, King's College London, London, UK.ORCID 0000-0002-6327-2463
Divya ParmarDepartment of Population Health Sciences, School of Life Course & Population Sciences, King's College London, London, UK.
Sabine LandauInstitute of Psychiatry, Psychology & Neuroscience, King's College London, London, UK.
Matthew Dl O'ConnellDepartment of Population Health Sciences, School of Life Course & Population Sciences, King's College London, London, UK.ORCID 0000-0002-9565-487X
C D A WolfeDepartment of Population Health Sciences, School of Life Course & Population Sciences, King's College London, London, UK.
Iain J MarshallDepartment of Population Health Sciences, School of Life Course & Population Sciences, King's College London, London, UK.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundSocioeconomic status (SES), often measured by education, income, occupation, or area-level deprivation, impacts stroke incidence and outcomes, yet the underlying mechanisms remain unclear. This review synthesizes causal analyses quantifying drivers of these inequalities.

methodsWe conducted a systematic review (PROSPERO CRD42024554285) and reported following the PRISMA-2020 guidelines. Observational studies applying causal mediation analysis between SES and stroke risk, disability, or mortality were included from PubMed, Embase, Scopus, and Google Scholar. SES indicators, outcomes, mediators, and decompositions into natural direct effect (NDE) and natural indirect effect (NIE) were extracted. Risk of bias and certainty of evidence were assessed using ROBINS-E and GRADE. A narrative synthesis was undertaken, and findings were illustrated in causal diagrams.

resultsOf 12,034 records, 19 studies (15 in high-income countries) were included. Lower SES increased stroke incidence through hypertension (NIE 14-21% of the total effect, moderate certainty), although one study restricted to women reported smaller effects (2-4%). Smoking (6-19.9%, very low certainty). At 3 months post-stroke, the combined outcome of death or disability was higher due to severe strokes (38.5% for ischemic, 57-94% for hemorrhagic, moderate certainty). One study found that hypertension, atrial fibrillation, and smoking together mediated 28.5% of the SES effect on stroke severity (low certainty). Reduced access to thrombolysis and stroke units mediated 2.7% of 3-month disability/mortality (very low certainty), while greater distance to specialized centers explained 48% of inequalities in thrombectomy access (low certainty). Long-term mortality (⩾6 months) was mediated by comorbidities (18%) and healthcare coverage (24-55%), both with low certainty.

conclusionsHypertension, smoking, and differential stroke severity at presentation are the main pathways through which low SES increases stroke risk and causes worse outcomes. Targeting these may reduce inequalities, though evidence from low-income settings and emerging mediators (e.g. early-life SES, environmental exposures, care quality) is lacking.

Indexed as

Low Socioeconomic StatusStrokeHumansRisk FactorsSocioeconomic Disparities in Healthhypertensioninequalitiespublic healthrehabilitationSocioeconomic statusstroke risk

Identifiers

PMID41222083
PMCPMC13291443

What Socratic holds

Textmetadata
LicenceCC BY
Read underepoch 390

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 Socratic graph.