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.Peer reviewe

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.This publication was made possible by NPRP grant number 10-1208-160017 from the Qatar National Research Fund (a member of Qatar Foundation)

Type 2 diabetes epidemic and key risk factors in Qatar: A mathematical modeling analysis

Introduction We aimed to characterize and forecast type 2 diabetes mellitus (T2DM) disease burden between 2021 and 2050 in Qatar where 89% of the population comprises expatriates from over 150 countries. Research design and methods An age-structured mathematical model was used to forecast T2DM burden and the impact of key risk factors (obesity, smoking, and physical inactivity). The model was parametrized using data from T2DM natural history studies, Qatar's 2012 STEPwise survey, the Global Health Observatory, and the International Diabetes Federation Diabetes Atlas, among other data sources. Results Between 2021 and 2050, T2DM prevalence increased from 7.0% to 14.0%, the number of people living with T2DM increased from 170 057 to 596 862, and the annual number of new T2DM cases increased from 25 007 to 45 155 among those 20-79 years of age living in Qatar. Obesity prevalence increased from 8.2% to 12.5%, smoking declined from 28.3% to 26.9%, and physical inactivity increased from 23.1% to 26.8%. The proportion of incident T2DM cases attributed to obesity increased from 21.9% to 29.9%, while the contribution of smoking and physical inactivity decreased from 7.1% to 6.0% and from 7.3% to 7.2%, respectively. The results showed substantial variability across various nationality groups residing in Qatar - for example, in Qataris and Egyptians, the T2DM burden was mainly due to obesity, while in other nationality groups, it appeared to be multifactorial. Conclusions T2DM prevalence and incidence in Qatar were forecasted to increase sharply by 2050, highlighting the rapidly growing need of healthcare resources to address the disease burden. T2DM epidemiology varied between nationality groups, stressing the need for prevention and treatment intervention strategies tailored to each nationality

Temporal Dynamics and Impact of Climate Factors on the Incidence of Zoonotic Cutaneous Leishmaniasis in Central Tunisia

Old world cutaneous leishmaniasis is a vector-borne disease occurring in rural areas of developing countries. The main reservoirs are the rodents Psammomys obesus and Meriones shawi. Zoonotic Leishmania transmission cycle is maintained in the burrows of rodents where the sand fly Phlebotomus papatasi finds the ideal environment and source of blood meals. In the present study we showed seasonality of the incidence of disease during the same cycle with an inter-epidemic period ranging from 4 to 7 years. We evaluated the impact of climate variables (rainfall, humidity and temperature) on the incidence of zoonotic cutaneous leishmaniais in central Tunisia. We confirmed that the risk of disease is mainly influenced by the humidity related to the months of July to September during the same season and mean rainfall lagged by 12 to 14 months

School children growth monitoring program in the state of Qatar: Observations from two survey rounds in 2016–17 and 2019–20

Abstract Introduction Growth monitoring surveys provide critical anthropometric data to monitor physical growth and various forms of malnutrition among school age children. In the beginning, growth monitoring programs were introduced to identify the extent of undernutrition among children, which were later considered equally useful in the identification of overweight and obesity among school age children. Observing the shifts in weight categories among school age children provides an important insight to design targeted interventions for improving growth and development of children. Methodology The study used growth monitoring survey data among 5–19‐year school children of two academic years (2016–17 and 2019–20) in Qatar where 2016–17 survey included 186,986 students, whereas 2019–20 survey included 215,279 students. A total of 7514 unique records of students aged 5–14 years available in both survey rounds were included in the final analysis. This study documented shift in BMI‐z‐scores to ascertain the movement of students among obese, overweight, normal, thinness, and severe thinness categories. Python version 3.9.5 was used for data analysis along with a pairwise comparison between each of BMI‐z‐score shift to evaluate the effects of specific shifts in BMI‐z‐score category. Results Overall, the proportion of overweight and obese category of students increased from 44% in 2016–17 to 49.3% in 2019–20 with a decrease in the proportion of students in normal BMI‐z‐score category (from 48.8% to 47.8%) and severe thinness and thinness category (from 7.3% to 3%) between two rounds of growth monitoring survey. Statistically significant shifts in BMI‐z‐score categories were noted for students of different age groups, gender, and nationality. Conclusions Shift from normal BMI‐z‐score to obese and overweight category is a cause of concern and an opportunity to develop appropriate interventions. The significant shift among different categories needs to be investigated further to identify associated reasons to effectively develop interventions