000304287 001__ 304287
000304287 005__ 20250903114815.0
000304287 0247_ $$2doi$$a10.1038/s41598-025-17859-5
000304287 0247_ $$2pmid$$apmid:40890381
000304287 037__ $$aDKFZ-2025-01827
000304287 041__ $$aEnglish
000304287 082__ $$a600
000304287 1001_ $$aTetzlaff, Fabian$$b0
000304287 245__ $$aWidening socioeconomic inequalities in cancer incidence and related potential to reduce cancer between 2008 and 2019 in Germany.
000304287 260__ $$a[London]$$bSpringer Nature$$c2025
000304287 3367_ $$2DRIVER$$aarticle
000304287 3367_ $$2DataCite$$aOutput Types/Journal article
000304287 3367_ $$0PUB:(DE-HGF)16$$2PUB:(DE-HGF)$$aJournal Article$$bjournal$$mjournal$$s1756818981_26695
000304287 3367_ $$2BibTeX$$aARTICLE
000304287 3367_ $$2ORCID$$aJOURNAL_ARTICLE
000304287 3367_ $$00$$2EndNote$$aJournal Article
000304287 520__ $$aBackground Cancer is one of the main causes of a high burden of disease and one of the strongest contributors to earlier mortality among lower socioeconomic groups in Germany. Therefore, studying socio-economic inequalities in cancer incidence is of high relevance from a public-health and health-equity lens. The aim of this study was to examine in more depth time trends in socioeconomic inequalities in cancer incidence and the related potential for reducing the incidence of specific cancers across Germany. Methods We used epidemiologic data from the Centre for Cancer Registry Data at the Robert Koch Institute and official population statistics for Germany from 2008 to 2019. To analyse trends in socioeconomic inequalities in cancer incidence, we used an ecological study design and linked the cancer registry and population data with the German Index of Socioeconomic Deprivation at district level. We calculated standardised cancer incidence rates for the most common cancers by area-level socioeconomic deprivation and estimated the Slope and Relative Index of Inequality (SII, RII) to determine the extent of area-level socioeconomic inequalities in the risk of cancer. In a what-if analysis, counterfactual scenarios were used to calculate how much lower cancer incidence could be if socioeconomic inequalities in incidence were reduced or eliminated. Results Due to less favourable trends of cancer incidence in more deprived areas, socioeconomic inequalities in cancer incidence has widened to the detriment of residents in highly deprived areas. This was observed for all cancers combined and for several common cancers such as stomach, colorectal and lung cancer among both women and men. In 2017-19, total cancer incidence was 18% (women: RII 1,18) and 49% (men: RII 1,49) higher in the most than in the least deprived area. Reverse inequalities were observed for skin melanoma in both sexes and female breast cancer, the lowest incidence being among residents of highly deprived districts. For 2017-19, the what-if analysis showed that the annual number of newly diagnosed cancers cases would be 9,100-76,000 cases fewer if the socioeconomic gap in cancer incidence between districts could be narrowed or eliminated. Conclusions In Germany, socioeconomic inequalities in cancer incidence have widened in recent decades. Tackling cancer risks in deprived areas could reduce those inequalities and the burden of cancer overall. Our study emphasises the growing importance of structural approaches in cancer prevention for reducing health inequalities in Germany.
000304287 536__ $$0G:(DE-HGF)POF4-319H$$a319H - Addenda (POF4-319H)$$cPOF4-319H$$fPOF IV$$x0
000304287 588__ $$aDataset connected to CrossRef, PubMed, , Journals: inrepo02.dkfz.de
000304287 650_7 $$2Other$$aArea-level socioeconomic inequalities
000304287 650_7 $$2Other$$aDeprivation
000304287 650_7 $$2Other$$aGISD
000304287 650_7 $$2Other$$aGermany
000304287 650_7 $$2Other$$aSocial determinants
000304287 650_7 $$2Other$$aTrends cancer incidence
000304287 650_2 $$2MeSH$$aHumans
000304287 650_2 $$2MeSH$$aGermany: epidemiology
000304287 650_2 $$2MeSH$$aNeoplasms: epidemiology
000304287 650_2 $$2MeSH$$aIncidence
000304287 650_2 $$2MeSH$$aFemale
000304287 650_2 $$2MeSH$$aMale
000304287 650_2 $$2MeSH$$aSocioeconomic Factors
000304287 650_2 $$2MeSH$$aRegistries
000304287 650_2 $$2MeSH$$aMiddle Aged
000304287 650_2 $$2MeSH$$aAged
000304287 650_2 $$2MeSH$$aAdult
000304287 650_2 $$2MeSH$$aHealth Status Disparities
000304287 7001_ $$aBarnes, Benjamin$$b1
000304287 7001_ $$0P:(DE-He78)bbfe0ebad1e3b608bca2b49d4f86bd09$$aJansen, Lina$$b2$$udkfz
000304287 7001_ $$aPeters, Frederik$$b3
000304287 7001_ $$aSchultz, Annemarie$$b4
000304287 7001_ $$aKatalinic, Alexander$$b5
000304287 7001_ $$aKraywinkel, Klaus$$b6
000304287 7001_ $$aMichalski, Niels$$b7
000304287 7001_ $$aNowossadeck, Enno$$b8
000304287 7001_ $$aHoebel, Jens$$b9
000304287 773__ $$0PERI:(DE-600)2615211-3$$a10.1038/s41598-025-17859-5$$gVol. 15, no. 1, p. 32232$$n1$$p32232$$tScientific reports$$v15$$x2045-2322$$y2025
000304287 909CO $$ooai:inrepo02.dkfz.de:304287$$pVDB
000304287 9101_ $$0I:(DE-588b)2036810-0$$6P:(DE-He78)bbfe0ebad1e3b608bca2b49d4f86bd09$$aDeutsches Krebsforschungszentrum$$b2$$kDKFZ
000304287 9131_ $$0G:(DE-HGF)POF4-319H$$1G:(DE-HGF)POF4-310$$2G:(DE-HGF)POF4-300$$3G:(DE-HGF)POF4$$4G:(DE-HGF)POF$$aDE-HGF$$bGesundheit$$lKrebsforschung$$vAddenda$$x0
000304287 9141_ $$y2025
000304287 915__ $$0StatID:(DE-HGF)0100$$2StatID$$aJCR$$bSCI REP-UK : 2022$$d2024-12-18
000304287 915__ $$0StatID:(DE-HGF)0200$$2StatID$$aDBCoverage$$bSCOPUS$$d2024-12-18
000304287 915__ $$0StatID:(DE-HGF)0300$$2StatID$$aDBCoverage$$bMedline$$d2024-12-18
000304287 915__ $$0StatID:(DE-HGF)0501$$2StatID$$aDBCoverage$$bDOAJ Seal$$d2024-07-29T15:28:26Z
000304287 915__ $$0StatID:(DE-HGF)0500$$2StatID$$aDBCoverage$$bDOAJ$$d2024-07-29T15:28:26Z
000304287 915__ $$0StatID:(DE-HGF)0030$$2StatID$$aPeer Review$$bDOAJ : Anonymous peer review$$d2024-07-29T15:28:26Z
000304287 915__ $$0StatID:(DE-HGF)0600$$2StatID$$aDBCoverage$$bEbsco Academic Search$$d2024-12-18
000304287 915__ $$0StatID:(DE-HGF)0030$$2StatID$$aPeer Review$$bASC$$d2024-12-18
000304287 915__ $$0StatID:(DE-HGF)0199$$2StatID$$aDBCoverage$$bClarivate Analytics Master Journal List$$d2024-12-18
000304287 915__ $$0StatID:(DE-HGF)1040$$2StatID$$aDBCoverage$$bZoological Record$$d2024-12-18
000304287 915__ $$0StatID:(DE-HGF)1150$$2StatID$$aDBCoverage$$bCurrent Contents - Physical, Chemical and Earth Sciences$$d2024-12-18
000304287 915__ $$0StatID:(DE-HGF)1050$$2StatID$$aDBCoverage$$bBIOSIS Previews$$d2024-12-18
000304287 915__ $$0StatID:(DE-HGF)0160$$2StatID$$aDBCoverage$$bEssential Science Indicators$$d2024-12-18
000304287 915__ $$0StatID:(DE-HGF)1190$$2StatID$$aDBCoverage$$bBiological Abstracts$$d2024-12-18
000304287 915__ $$0StatID:(DE-HGF)0113$$2StatID$$aWoS$$bScience Citation Index Expanded$$d2024-12-18
000304287 915__ $$0StatID:(DE-HGF)0150$$2StatID$$aDBCoverage$$bWeb of Science Core Collection$$d2024-12-18
000304287 915__ $$0StatID:(DE-HGF)9900$$2StatID$$aIF < 5$$d2024-12-18
000304287 915__ $$0StatID:(DE-HGF)0561$$2StatID$$aArticle Processing Charges$$d2024-12-18
000304287 915__ $$0StatID:(DE-HGF)0700$$2StatID$$aFees$$d2024-12-18
000304287 9201_ $$0I:(DE-He78)M110-20160331$$kM110$$lM110 Epidemiologisches Krebsregister BW$$x0
000304287 980__ $$ajournal
000304287 980__ $$aVDB
000304287 980__ $$aI:(DE-He78)M110-20160331
000304287 980__ $$aUNRESTRICTED