STROBE-Equity (STROBE Extension for Health Equity)

What it is

— STROBE-Equity (Strengthening the Reporting of Observational Studies in Epidemiology — extension for health equity) is a reporting-guideline extension that supplements the base STROBE checklist with equity-specific reporting items for observational studies in which health equity is part of the research question. It was developed by an international consensus group (Dewidar, Shamseer, Welch, Tugwell and colleagues) using EQUATOR/Cochrane methodology and published in 2025 as a combined extension checklist and elaboration in JAMA Network Open; it is maintained as a project of Cochrane Equity within the EQUATOR Network. Its purpose is to make the equity dimensions of an observational study transparent and auditable: who the disadvantaged and comparison groups are, how equity-relevant characteristics were defined and measured, what stratified/effect- modification analyses were planned and conducted, and how findings bear on avoidable, unjust health differences. Crucially, STROBE-Equity is an add-on, not a replacement — authors complete base STROBE and then report the additional equity items on top of it. The equity dimensions it operationalizes are framed by PROGRESS-Plus (Place of residence, Race/ethnicity/culture/language, Occupation, Gender/sex, Religion, Education, Socioeconomic status, Social capital, plus context-specific factors such as age, disability, and other vulnerabilities).

When to use

— Apply STROBE-Equity when you are reporting an observational study (cohort, case-control, cross-sectional, including claims/EHR/registry real-world evidence) in which equity is an explicit aim — e.g., the study examines health differences across socioeconomic, racial/ethnic, geographic, sex/gender, or other PROGRESS-Plus strata, or intends its results to inform policy affecting disadvantaged populations. It is the appropriate extension for a peer-reviewed observational manuscript with an equity objective, and increasingly for the observational evidence underpinning an HTA/payer dossier where equity impact is a deliberative criterion (e.g., NICE/ICER distributional and health-inequality considerations). Decision rule for the right family member: observational study with an equity question → base STROBE + STROBE-Equity; randomized trial with an equity question → CONSORT-Equity; systematic review with an equity question → PRISMA-Equity / equity-focused PRISMA extension; observational study with no equity question → base STROBE alone. STROBE-Equity sits on an orthogonal axis to RECORD / RECORD-PE (routinely-collected-data and pharmacoepidemiologic extensions): an equity-focused study built on claims or EHR data can and should apply RECORD/RECORD-PE and STROBE-Equity together — they govern different facets of the same report.

What it requires

— Layered on the base STROBE items, STROBE-Equity compels explicit reporting of the equity architecture of the study. The added items require, in substance: (1) an equity-framed rationale and objectives, stating which populations or PROGRESS-Plus dimensions are of interest and why the differences studied are considered avoidable and unjust; (2) explicit definition and measurement of equity-relevant characteristics — how race/ethnicity, socioeconomic position, sex/gender, geography, etc. were operationalized, the data source and classification scheme, and the limits of those measures (a real-world-data crux, since claims and EHR capture these variably and often by proxy); (3) clear specification of the disadvantaged group(s) and the comparison group(s), and the reference category chosen; (4) pre-specified stratified analyses and equity-relevant effect modification / subgroup analyses, distinguishing planned from post-hoc, with appropriate handling of multiplicity and sparse strata; (5) reporting of differential attrition, missingness, and selection across equity strata — not just overall — because loss to follow-up and unobserved person-time are rarely equity-neutral; (6) honest discussion of transportability and generalizability to the disadvantaged populations the study aims to inform; and (7) interpretation framed against existing inequities, including potential for the analysis itself to entrench or mask them. For claims/EHR/registry RWE, these generic items carry specific operational weight: phenotype and outcome algorithms may perform differently across subgroups, time-zero and enrollment requirements can differentially exclude disadvantaged patients, and confounding control must not absorb the very equity-relevant exposures of interest.

When NOT to use — limitations and common misapplications

— STROBE-Equity is a reporting checklist, not a risk-of-bias instrument, not a quality score, and not an analysis method. Concrete failure modes: (1) Treating it as a replacement for base STROBE — it is an extension; the base 22 items still apply and STROBE-Equity adds on top. (2) Wrong design — using STROBE-Equity for a randomized trial (use CONSORT-Equity) or a systematic review (use a PRISMA equity extension). (3) Confusing the checklist with the framework — PROGRESS-Plus is the conceptual framework of equity dimensions; STROBE-Equity is the reporting checklist that operationalizes it. The two are complementary, not interchangeable. (4) Equity-as-theater — bolting equity items onto a study that has no genuine equity question, or ticking the items while reporting only a single overall effect, defeats the purpose; the value is transparent equity analysis, not box-count. (5) Reporting ≠ doing — completing the equity items does not make the study causally valid or its subgroup contrasts unconfounded; a fully STROBE-Equity- compliant paper can still rest on a biased design, mismeasured race/SES variables, or an underpowered, data-dredged subgroup. (6) Mismeasured equity variables passed off as analyzed — naming a PROGRESS-Plus dimension in the checklist while it is captured only by a crude or missing-laden proxy (e.g., area-level income as individual SES) reports the intent without the substance.

How it maps to this catalog

— In this repo, STROBE-Equity's requirements are implemented (or appraised) by these concepts: - Equity-relevant effect modification / subgroup analysis (added items on stratified analysis): implemented by causal-mediation-effect-modification-rwe, which supplies the estimand-aware machinery for analyzing and reporting heterogeneity across PROGRESS-Plus strata rather than a single average effect. - Estimand and intercurrent-event clarity for subgroup contrasts: estimands-ate-att-intercurrent-events-rwe — the equity contrast must specify a target population and estimand, not an undefined "subgroup effect." - Differential attrition and selection across strata (the equity attrition item): attrition-and-loss-to- follow-up-rwe and database-feasibility-attrition-funnel-rwe, reported by equity stratum, not only overall. - Measurement validity of equity-relevant and outcome variables in RWE: algorithm-validation, diagnosis-phenotype-algorithm-1ip-2op-time-window-rwe, and claims-outcome-algorithm-ppv-sensitivity-rwe — because phenotype/outcome algorithms can have subgroup-specific performance that distorts equity conclusions. - Transportability/external validity to disadvantaged populations: generalizability-transportability- external-validity-rwe. - Design and confounding spine the equity analysis sits on: target-trial-emulation, active-comparator-new-user, high-dimensional-propensity-score-hdps-rwe, and the structured-question discipline of picots-framework-rwe (which forces the population and comparator to be named before equity strata are examined). These design/measurement concepts are not STROBE-Equity items in themselves; they are the substantive analyses whose results the equity items demand you report transparently.

Applied note (claims/EHR/registry RWE)

An equity-focused comparative claims study should report how each PROGRESS-Plus dimension was captured (e.g., race/ethnicity from enrollment files of variable completeness, individual vs area-level SES, Medicare-vs-Medicaid-vs-commercial coverage as a confounded marker of access — see medicare-ffs-ma-commercial-claims-differences-rwe and claims-analysis), present the attrition funnel and loss to follow-up split by equity stratum, validate that outcome/phenotype algorithms perform comparably across subgroups, pre-specify the equity-relevant effect modification it will test, and state plainly how findings transport to the disadvantaged populations they are meant to inform — all on top of, not instead of, the base STROBE checklist.