ReviewInternational journal for equity in health2025
Writing about health inequality: recommendations for accurate and impactful presentation of evidence.
Review in International journal for equity in health, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers, 1 of them a synthesis that pooled 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.
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.
Who cites it
4 citing papers in PubMed, 1 synthesis or guideline pooled it.
- Osmotic and stimulant laxatives for the management of childhood constipation.The Cochrane database of systematic reviews · 2026Pooled it
- Baby Boomers in Germany: a secondary data analysis of demographics, regional disparities, healthcare utilization, and mortality.BMC public health · 2026Article
- Health inequalities among people with disabilities: an umbrella review and evidence synthesis.EClinicalMedicine · 2026Review
- Visualizing health inequality data: guidance for selecting and designing graphs and maps.International journal for equity in health · 2025Review
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
12 authors.
Funding
Abstract
Health and development agendas and programmes often prioritize the reduction of unfair and remediable health inequalities. There is a growing amount of data pertaining to health inequalities. Written outputs, including academic research papers, are key tools for describing health inequalities. Epidemiologists, data analysts, policy advisors and health equity scholars can have greater impact through accurate, concise and compelling presentation of this evidence and so assist those advocating for action to close health gaps. We make recommendations to improve the accuracy and impact of written evidence on health inequality. Focusing on the micro, macro and meta aspects of developing written reports, we drew from our varied experiences promoting health inequality monitoring to identify key strategies specific to this field, which were further expanded and explored through literature searches and consultation with experts. We recommend four general strategies: (i) using terminology deliberately and consistently; (ii) presenting statistical content accurately and with sufficient detail; (iii) adhering to guidelines and best practices for reporting; and (iv) respecting and upholding the interests of affected communities. Specifically, we address the use of terminology related to health inequality and health inequity, dimensions of inequality and determinants of health, economic inequality and economic-related inequality, sex and gender, and race and ethnicity. We present common pitfalls related to reporting statistical content, underscoring the importance of clarity when reporting association and causation. We advocate for engaged and inclusive writing processes that use affirming language and adopt strength-based messaging. This guidance is intended to increase the impact of written evidence on efforts to tackle avoidable health inequalities.
Indexed as
Identifiers
What OpenQuestion holds
Registered trials
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.