Bibliographic Details
| Title: |
Validation of prevalent diabetes risk scores based on non-invasively measured predictors in Ghanaian migrant and non-migrant populations – The RODAM study |
| Authors: |
James Osei-Yeboah, Andre-Pascal Kengne, Ellis Owusu-Dabo, Matthias B. Schulze, Karlijn A.C. Meeks, Kerstin Klipstein-Grobusch, Liam Smeeth, Silver Bahendeka, Erik Beune, Eric P. Moll van Charante, Charles Agyemang |
| Source: |
Public Health in Practice, Vol 6, Iss , Pp 100453- (2023) |
| Publisher Information: |
Elsevier, 2023. |
| Publication Year: |
2023 |
| Collection: |
LCC:Public aspects of medicine |
| Subject Terms: |
Diabetes risk prediction, External validation, Sub-Saharan Africa population, Migrant population, Public aspects of medicine, RA1-1270 |
| More Details: |
Background: Non-invasive diabetes risk models are a cost-effective tool in large-scale population screening to identify those who need confirmation tests, especially in resource-limited settings. Aims: This study aimed to evaluate the ability of six non-invasive risk models (Cambridge, FINDRISC, Kuwaiti, Omani, Rotterdam, and SUNSET model) to identify screen-detected diabetes (defined by HbA1c) among Ghanaian migrants and non-migrants. Study design: A multicentered cross-sectional study. Methods: This analysis included 4843 Ghanaian migrants and non-migrants from the Research on Obesity and Diabetes among African Migrants (RODAM) Study. Model performance was assessed using the area under the receiver operating characteristic curves (AUC), Hosmer-Lemeshow statistics, and calibration plots. Results: All six models had acceptable discrimination (0.70 ≤ AUC |
| Document Type: |
article |
| File Description: |
electronic resource |
| Language: |
English |
| ISSN: |
2666-5352 |
| Relation: |
http://www.sciencedirect.com/science/article/pii/S266653522300099X; https://doaj.org/toc/2666-5352 |
| DOI: |
10.1016/j.puhip.2023.100453 |
| Access URL: |
https://doaj.org/article/98edbb0dc943497babdab71b19a1b60e |
| Accession Number: |
edsdoj.98edbb0dc943497babdab71b19a1b60e |
| Database: |
Directory of Open Access Journals |
