Bibliographic Details
| Title: |
Intersectional analysis of social disparities in type 2 diabetes risk among adults in Germany: results from a nationwide population-based survey |
| Authors: |
Francesca Färber, Enrique Alonso-Perez, Christin Heidemann, Yong Du, Gertraud Stadler, Paul Gellert, Julie Lorraine O’Sullivan |
| Source: |
BMC Public Health, Vol 24, Iss 1, Pp 1-12 (2024) |
| Publisher Information: |
BMC, 2024. |
| Publication Year: |
2024 |
| Collection: |
LCC:Public aspects of medicine |
| Subject Terms: |
Diabetes mellitus, Diabetes risk, Prevention, Intersectionality, Social determinants, Population-based survey, Public aspects of medicine, RA1-1270 |
| More Details: |
Abstract Background Differences in type 2 diabetes risk have been reported for several sociodemographic determinants including sex/gender or socioeconomic status. From an intersectional perspective, it is important to not only consider the role of social dimensions individually, but also their intersections. This allows for a deeper understanding of diabetes risk and preventive needs among diverse population groups. Methods As an intersectionality-informed approach, multilevel analysis of individual heterogeneity and discriminatory accuracy (MAIHDA) was used in a population-based sample of adults without known diabetes in Germany from the cross-sectional survey “Disease knowledge and information needs– Diabetes mellitus (2017)”. Diabetes risk was assessed by the German Diabetes Risk Score (GDRS, range 0-122 points), estimating the individual risk of developing type 2 diabetes within the next 5 years based on established self-reported risk factors. Nesting individuals in 12 intersectional strata defined by combining sex/gender, educational level, and history of migration, we calculated measures to quantify the extent to which individual differences in diabetes risk were explained at strata level, and how much this was due to additive or multiplicative intersectional effects of social determinants. Results Drawing on data of 2,253 participants, we found good discriminatory accuracy of intersectional strata (variance partition coefficient = 14.00% in the simple intersectional model). Model-predicted GDRS means varied between 29.97 (corresponding to a “low risk” of |
| Document Type: |
article |
| File Description: |
electronic resource |
| Language: |
English |
| ISSN: |
1471-2458 |
| Relation: |
https://doaj.org/toc/1471-2458 |
| DOI: |
10.1186/s12889-024-17903-5 |
| Access URL: |
https://doaj.org/article/12fca36cae1042fda0601dd2ad793939 |
| Accession Number: |
edsdoj.12fca36cae1042fda0601dd2ad793939 |
| Database: |
Directory of Open Access Journals |
|
Full text is not displayed to guests. |
Login for full access.
|
