Characterizing epidemiology of prediabetes, diabetes, and hypertension in Qataris: A cross-sectional study.

OBJECTIVES: To characterize the epidemiologic profiles of prediabetes mellitus (preDM), diabetes mellitus (DM), and hypertension (HTN) in Qataris using the nationally representative 2012 Qatar STEPwise Survey. METHODS: A secondary data analysis of a cross-sectional survey that included 2,497 Qatari nationals aged 18-64 years. Descriptive and analytical statistical analyses were conducted. RESULTS: Prevalence of preDM, DM, and HTN in Qataris aged 18-64 years was 11.9% (95% confidence interval [CI] 9.6%-14.7%), 10.4% (95% CI 8.4%-12.9%), and 32.9% (95% CI 30.4%-35.6%), respectively. Age was the common factor associated with the three conditions. Adjusted analyses showed that unhealthy diet (adjusted odds ratio (aOR) = 1.84, 95% CI 1.01-3.36) was significantly associated with preDM; that physical inactivity (aOR = 1.66, 95% CI 1.12-2.46), central obesity (aOR = 2.08, 95% CI 1.02-4.26), and HTN (aOR = 2.18, 95% CI 1.40-3.38) were significantly associated with DM; and that DM (aOR = 2.07, 95% CI 1.34-3.22) was significantly associated with HTN. Population attributable fraction of preDM associated with unhealthy diet was 7.7%; of DM associated with physical inactivity, central obesity, and HTN, respectively, was 14.9%, 39.8%, and 17.5%; and of HTN associated with DM was 3.0%. CONCLUSIONS: One in five Qataris is living with either preDM or DM, and one in three is living with HTN, conditions that were found to be primarily driven by lifestyle factors. Prevention, control, and management of these conditions should be a national priority to reduce their disease burden and associated disease sequelae.

A diabetes risk score for Qatar utilizing a novel mathematical modeling approach to identify individuals at high risk for diabetes.

We developed a diabetes risk score using a novel analytical approach and tested its diagnostic performance to detect individuals at high risk of diabetes, by applying it to the Qatari population. A representative random sample of 5,000 Qataris selected at different time points was simulated using a diabetes mathematical model. Logistic regression was used to derive the score using age, sex, obesity, smoking, and physical inactivity as predictive variables. Performance diagnostics, validity, and potential yields of a diabetes testing program were evaluated. In 2020, the area under the curve (AUC) was 0.79 and sensitivity and specificity were 79.0% and 66.8%, respectively. Positive and negative predictive values (PPV and NPV) were 36.1% and 93.0%, with 42.0% of Qataris being at high diabetes risk. In 2030, projected AUC was 0.78 and sensitivity and specificity were 77.5% and 65.8%. PPV and NPV were 36.8% and 92.0%, with 43.0% of Qataris being at high diabetes risk. In 2050, AUC was 0.76 and sensitivity and specificity were 74.4% and 64.5%. PPV and NPV were 40.4% and 88.7%, with 45.0% of Qataris being at high diabetes risk. This model-based score demonstrated comparable performance to a data-derived score. The derived self-complete risk score provides an effective tool for initial diabetes screening, and for targeted lifestyle counselling and prevention programs.