Validation of prevalent diabetes risk scores based on non-invasively measured predictors in Ghanaian migrant and non-migrant populations – The RODAM study

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dc.contributor.authorOsei-Yeboah James
dc.contributor.authorKengne Andre-Pascal
dc.contributor.authorSchulze B. Matthias
dc.contributor.authorOwusu-Dabo Ellis
dc.contributor.authorBahendeka Silver
dc.contributor.authorAgyemang Charles....et al
dc.date.accessioned2023-12-06T09:38:28Z
dc.date.available2023-12-06T09:38:28Z
dc.date.issued2023
dc.descriptionThis article is published by Elsevier and is also available at www.sciencedirect.com/journal/public-health-in-practice
dc.description.abstractBackground: 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 Gha naian 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 <0.80) for screen-detected diabetes in the overall/combined population. Model performance did not significantly differ except for the Cambridge model, which outperformed Rotterdam and Omani models. Calibration was poor, with a consistent trend toward risk overestimation for screen-detected diabetes, but this was substantially attenuated by recalibration through adjustment of the original model intercept. Conclusion: Though acceptable discrimination was observed, the original models were poorly calibrated among populations of African ancestry. Recalibration of these models among populations of African ancestry is needed before use.
dc.description.sponsorshipKNUST
dc.identifier.citationPublic Health in Practice 6 (2023) 100453
dc.identifier.uri10.1016/j.puhip.2023.100453
dc.identifier.urihttps://ir.knust.edu.gh/handle/123456789/14634
dc.language.isoen
dc.publisherELSEVIER
dc.titleValidation of prevalent diabetes risk scores based on non-invasively measured predictors in Ghanaian migrant and non-migrant populations – The RODAM study
dc.typeArticle
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