{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,4,9]],"date-time":"2026-04-09T20:39:18Z","timestamp":1775767158713,"version":"3.50.1"},"reference-count":37,"publisher":"BMJ","issue":"5","funder":[{"DOI":"10.13039\/100002129","name":"Heart Foundation","doi-asserted-by":"publisher","award":["R122-A8403"],"award-info":[{"award-number":["R122-A8403"]}],"id":[{"id":"10.13039\/100002129","id-type":"DOI","asserted-by":"publisher"}]}],"content-domain":{"domain":["bmj.com"],"crossmark-restriction":true},"short-container-title":["J Epidemiol Community Health"],"accepted":{"date-parts":[[2025,11,27]]},"published-print":{"date-parts":[[2026,5]]},"abstract":"<jats:p>Disadvantaged groups are often defined by characteristics such as income or ethnicity. Reducing health disparities by directly manipulating such exposures may be infeasible. Instead, interventions can target mediators between these exposures and health outcomes. Indirect effects estimated using mediation analysis, interventional effects or the interventional disparity measure can quantify the expected impact of such disparity-reducing interventions. They capture the impact of changing the mediator distribution evaluated among the total population. This means keeping individuals in their exposure group but hypothetically assigning them the mediator distribution of another group. However, when indirect effects are intended to inform about disparity-reducing interventions implemented among disadvantaged groups, estimating effects in the total population does not quantify the effect among those targeted. Instead, we propose evaluating the interventional disparity indirect effect directly among the disadvantaged individuals. We introduce the estimand and illustrate it using a register-based study examining a potential intervention improving medication initiation in low-income heart failure patients. We compare the expected change in 1-year mortality in a hypothetical world where low-income patients were as likely to initiate medication as high-income patients. We included 1700 patients and assessed intervention effects in low-income patients and the total population, respectively. Under the intervention, the 1-year mortality declined from 10.3% to 9.3% (95% CI 8.6% to 10.1%) among low-income patients but 6.6% to 6.2% (95% CI 6.0% to 6.5%) in the total population. In disparity research, evaluating intervention effects in the total population, rather than among disadvantaged groups, may impact the effect size. Therefore, when guiding future disparity-targeted interventions, measuring effects within disadvantaged groups is important.<\/jats:p>","DOI":"10.1136\/jech-2025-224627","type":"journal-article","created":{"date-parts":[[2026,1,8]],"date-time":"2026-01-08T18:20:25Z","timestamp":1767896425000},"page":"309-315","update-policy":"https:\/\/doi.org\/10.1136\/crossmarkpolicy","source":"Crossref","is-referenced-by-count":1,"title":["Estimating effects of targeted public health interventions using the interventional disparity indirect effect among the exposed"],"prefix":"10.1136","volume":"80","author":[{"ORCID":"https:\/\/orcid.org\/0000-0003-2952-2809","authenticated-orcid":false,"given":"Amalie Lykkemark","family":"M\u00f8ller","sequence":"first","affiliation":[{"name":"Cancer and Medicine, Danish Cancer Institute, Copenhagen, Denmark"},{"name":"Section of Biostatistics, Department of Public Health, University of Copenhagen, Copenhagen, Denmark"},{"name":"Copenhagen Health Complexity Center, Department of Public Health, University of Copenhagen, Copenhagen, Denmark"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Kathrine Kold","family":"S\u00f8rensen","sequence":"additional","affiliation":[{"name":"Department for Clinical and Translational Research, Copenhagen University Hospital, Steno Diabetes Center Copenhagen, Herlev, Denmark"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Nerissa","family":"Nance","sequence":"additional","affiliation":[{"name":"Novo Nordisk A\/S, S\u00f8borg, Denmark"},{"name":"University of California, Berkeley, Berkeley, California, USA"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Julie Thietje","family":"Mortensen","sequence":"additional","affiliation":[{"name":"Novo Nordisk A\/S, S\u00f8borg, Denmark"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Thomas Alexander","family":"Gerds","sequence":"additional","affiliation":[{"name":"Section of Biostatistics, Department of Public Health, University of Copenhagen, Copenhagen, Denmark"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Christian","family":"Torp-Pedersen","sequence":"additional","affiliation":[{"name":"Section of Biostatistics, Department of Public Health, University of Copenhagen, Copenhagen, Denmark"},{"name":"Department for Clinical and Translational Research, Copenhagen University Hospital, Steno Diabetes Center Copenhagen, Herlev, Denmark"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Helene Charlotte Wiese","family":"Rytgaard","sequence":"additional","affiliation":[{"name":"Section of Biostatistics, Department of Public Health, University of Copenhagen, Copenhagen, Denmark"}],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"239","published-online":{"date-parts":[[2026,1,8]]},"reference":[{"key":"2026040902101212000_80.5.309.1","doi-asserted-by":"crossref","first-page":"52","DOI":"10.1007\/s40471-014-0030-4","article-title":"Counterfactual Theory in Social Epidemiology: Reconciling Analysis and Action for the Social Determinants of Health","volume":"2","author":"Naimi","year":"2015","journal-title":"Curr Epidemiol Rep"},{"key":"2026040902101212000_80.5.309.2","doi-asserted-by":"crossref","first-page":"1409","DOI":"10.1016\/S0140-6736(03)14639-9","article-title":"Tackling socioeconomic inequalities in health: analysis of European experiences","volume":"362","author":"Mackenbach","year":"2003","journal-title":"The Lancet"},{"key":"2026040902101212000_80.5.309.3","doi-asserted-by":"crossref","first-page":"598","DOI":"10.1093\/aje\/kwy248","article-title":"Causal Mediation Analysis With Observational Data: Considerations and Illustration Examining Mechanisms Linking Neighborhood Poverty to Adolescent Substance Use","volume":"188","author":"Rudolph","year":"2019","journal-title":"Am J Epidemiol"},{"key":"2026040902101212000_80.5.309.4","doi-asserted-by":"crossref","first-page":"143","DOI":"10.1097\/00001648-199203000-00013","article-title":"Identifiability and Exchangeability for Direct and Indirect Effects","volume":"3","author":"Robins","year":"1992","journal-title":"Epidemiology (Sunnyvale)"},{"key":"2026040902101212000_80.5.309.5","unstructured":"Pearl J . 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