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2020-08-10Zeitschriftenartikel DOI: 10.1371/journal.pone.0237349
Non-response in a national health survey in Germany: An intersectionality-informed multilevel analysis of individual heterogenity and discriminatory accuracy
dc.contributor.authorJaehn, Philipp
dc.contributor.authorMena, Emily
dc.contributor.authorMerz, Sibille
dc.contributor.authorHoffmann, Robert
dc.contributor.authorGößwald, Antje
dc.contributor.authorRommel, Alexander
dc.contributor.authorHolmberg, Christine
dc.date.accessioned2026-09-28T11:53:27Z
dc.date.available2026-09-28T11:53:27Z
dc.date.issued2020-08-10none
dc.identifier.urihttp://edoc.rki.de/176904/13963
dc.description.abstractBackground Dimensions of social location such as socioeconomic position or sex/gender are often associated with low response rates in epidemiological studies. We applied an intersectionality-informed approach to analyze non-response among population strata defined by combinations of multiple dimensions of social location and subjective health in a health survey in Germany. Methods We used data from the cross-sectional sample of the German Health Interview and Examination Survey for Adults (DEGS1) conducted between 2008 and 2011. Information about non-responders was available from a mailed non-responder questionnaire. Intersectional strata were constructed by combining all categories of age, sex/gender, marital status, and level of education in scenario 1. Subjective health was additionally used to construct intersectional strata in scenario 2. We applied multilevel analysis of individual heterogeneity and discriminatory accuracy (MAIHDA) to calculate measures of discriminatory accuracy, proportions of non-responders among intersectional strata, as well as stratum-specific total interaction effects (intersectional effects). Markov chain Monte Carlo methods were used to estimate multilevel logistic regression models. Results Data was available for 6,534 individuals of whom 36% were non-responders. In scenario 2, we found weak discriminatory accuracy (variance partition coefficient = 3.6%) of intersectional strata, while predicted proportions of non-response ranged from 20.6% (95% credible interval (CI) 17.0%-24.9%) to 57.5% (95% CI 48.8%-66.5%) among intersectional strata. No evidence for intersectional effects was found. These results did not differ substantially between scenarios 1 and 2. Conclusions MAIHDA revealed that proportions of non-response varied widely between intersectional strata. However, poor discriminatory accuracy of intersectional strata and no evidence for intersectional effects indicate that there is no justification to exclusively target specific intersectional strata in order to increase response, but that a combination of targeted and population-based measures might be appropriate to achieve more equal representation.eng
dc.language.isoengnone
dc.publisherRobert Koch-Institut
dc.rights(CC BY 3.0 DE) Namensnennung 3.0 Deutschlandger
dc.rights.urihttp://creativecommons.org/licenses/by/3.0/de/
dc.subject.ddc610 Medizin und Gesundheitnone
dc.titleNon-response in a national health survey in Germany: An intersectionality-informed multilevel analysis of individual heterogenity and discriminatory accuracynone
dc.typearticle
dc.identifier.urnurn:nbn:de:0257-176904/13963-0
dc.identifier.doi10.1371/journal.pone.0237349
dc.type.versionpublishedVersionnone
local.edoc.container-titlePLOS Onenone
local.edoc.container-issn1932-6203none
local.edoc.pages17none
local.edoc.type-nameZeitschriftenartikel
local.edoc.container-typeperiodical
local.edoc.container-type-nameZeitschrift
local.edoc.container-urlhttps://journals.plos.org/plosone/none
local.edoc.container-publisher-namePLOSnone
local.edoc.container-volume15none
local.edoc.container-issue8none
local.edoc.container-reportyear2020none
dc.description.versionPeer Reviewednone

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