Screening for diabetes and impaired glucose metabolism in Qatar: Models' development and validation. Issue 1 (February 2022)

• Record Type: Journal Article
• Authors: Sadek, Khaled; Abdelhafez, Ibrahim; Al-Hashimi, Israa; Al-Shafi, Wadha; Tarmizi, Fatihah; Al-Marri, Hissa; Alzohari, Nada; Balideh, Mohammad; Carr, Alison
• Is Part Of: Primary care diabetes. Volume 16:Issue 1(2022)
• Page Start: 69
• Page End: 77
• Publication Date: 2022-02
• Subjects: Diabetes -- Impaired glucose metabolism -- Risk score -- Epidemiology -- Public health; Diabetes -- Periodicals; 616.462
• DOI: 10.1016/j.pcd.2021.10.002
• Languages: English
• ISSNs: 1751-9918

Abstract

Highlights: The prevalence of diabetes in Qatar (15.6%) is one of highest worldwide. We propose models screening for diabetes and impaired glucose metabolism in Qatar. The models performed well with area under the curve ranging from .774 to .870. The models are based on demographics, past history and anthropometric measurements. The proposed models can be used for primary prevention of diabetes in Qatar. Abstract: Aim: To establish two scoring models for identifying individuals at risk of developing Impaired Glucose Metabolism (IGM) or Type two Diabetes Mellitus (T2DM) in Qatari. Materials and methods: A sample of 2000 individuals, from Qatar BioBank, was evaluated to determine features predictive of T2DM and IGM. Another sample of 1000 participants was obtained for external validation of the models. Several scoring models screening for T2DM were evaluated and compared to the model proposed by this study. Results: Age, gender, waist-to-hip-ratio, history of hypertension and hyperlipidemia, and levels of educational were statistically associated with the risk of T2DM and constituted the Qatar diabetes mellitus risk score (QDMRISK). Along with, the 6 aforementioned variables, the IGM model showed that BMI was statistically significant. The QDMRISK performed well with area under the curve (AUC) 0.870 and .815 in the development and external validation cohorts, respectively. The QDMRISK showed overall better accuracy and calibration compared to other evaluated scores. The IGM model showed good accuracy and calibration, with AUCs .796 and .774 in the development and external validation cohorts, respectively. Conclusions: This study developed Qatari-specific diabetes and IGM risk scores to identify high risk individuals and can guide the development of a nationwide primary prevention program.