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| Home > Publications database > Widening socioeconomic inequalities in cancer incidence and related potential to reduce cancer between 2008 and 2019 in Germany. > print |
| 001 | 304287 | ||
| 005 | 20250903114815.0 | ||
| 024 | 7 | _ | |a 10.1038/s41598-025-17859-5 |2 doi |
| 024 | 7 | _ | |a pmid:40890381 |2 pmid |
| 037 | _ | _ | |a DKFZ-2025-01827 |
| 041 | _ | _ | |a English |
| 082 | _ | _ | |a 600 |
| 100 | 1 | _ | |a Tetzlaff, Fabian |b 0 |
| 245 | _ | _ | |a Widening socioeconomic inequalities in cancer incidence and related potential to reduce cancer between 2008 and 2019 in Germany. |
| 260 | _ | _ | |a [London] |c 2025 |b Springer Nature |
| 336 | 7 | _ | |a article |2 DRIVER |
| 336 | 7 | _ | |a Output Types/Journal article |2 DataCite |
| 336 | 7 | _ | |a Journal Article |b journal |m journal |0 PUB:(DE-HGF)16 |s 1756818981_26695 |2 PUB:(DE-HGF) |
| 336 | 7 | _ | |a ARTICLE |2 BibTeX |
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| 336 | 7 | _ | |a Journal Article |0 0 |2 EndNote |
| 520 | _ | _ | |a Background 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. |
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| 650 | _ | 7 | |a Area-level socioeconomic inequalities |2 Other |
| 650 | _ | 7 | |a Deprivation |2 Other |
| 650 | _ | 7 | |a GISD |2 Other |
| 650 | _ | 7 | |a Germany |2 Other |
| 650 | _ | 7 | |a Social determinants |2 Other |
| 650 | _ | 7 | |a Trends cancer incidence |2 Other |
| 650 | _ | 2 | |a Humans |2 MeSH |
| 650 | _ | 2 | |a Germany: epidemiology |2 MeSH |
| 650 | _ | 2 | |a Neoplasms: epidemiology |2 MeSH |
| 650 | _ | 2 | |a Incidence |2 MeSH |
| 650 | _ | 2 | |a Female |2 MeSH |
| 650 | _ | 2 | |a Male |2 MeSH |
| 650 | _ | 2 | |a Socioeconomic Factors |2 MeSH |
| 650 | _ | 2 | |a Registries |2 MeSH |
| 650 | _ | 2 | |a Middle Aged |2 MeSH |
| 650 | _ | 2 | |a Aged |2 MeSH |
| 650 | _ | 2 | |a Adult |2 MeSH |
| 650 | _ | 2 | |a Health Status Disparities |2 MeSH |
| 700 | 1 | _ | |a Barnes, Benjamin |b 1 |
| 700 | 1 | _ | |a Jansen, Lina |0 P:(DE-He78)bbfe0ebad1e3b608bca2b49d4f86bd09 |b 2 |u dkfz |
| 700 | 1 | _ | |a Peters, Frederik |b 3 |
| 700 | 1 | _ | |a Schultz, Annemarie |b 4 |
| 700 | 1 | _ | |a Katalinic, Alexander |b 5 |
| 700 | 1 | _ | |a Kraywinkel, Klaus |b 6 |
| 700 | 1 | _ | |a Michalski, Niels |b 7 |
| 700 | 1 | _ | |a Nowossadeck, Enno |b 8 |
| 700 | 1 | _ | |a Hoebel, Jens |b 9 |
| 773 | _ | _ | |a 10.1038/s41598-025-17859-5 |g Vol. 15, no. 1, p. 32232 |0 PERI:(DE-600)2615211-3 |n 1 |p 32232 |t Scientific reports |v 15 |y 2025 |x 2045-2322 |
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