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

Preventing type 2 diabetes mellitus in Qatar by reducing obesity, smoking, and physical inactivity: mathematical modeling analyses.

BACKGROUND: The aim of this study was to estimate the impact of reducing the prevalence of obesity, smoking, and physical inactivity, and introducing physical activity as an explicit intervention, on the burden of type 2 diabetes mellitus (T2DM), using Qatar as an example. METHODS: A population-level mathematical model was adapted and expanded. The model was stratified by sex, age group, risk factor status, T2DM status, and intervention status, and parameterized by nationally representative data. Modeled interventions were introduced in 2016, reached targeted level by 2031, and then maintained up to 2050. Diverse intervention scenarios were assessed and compared with a counter-factual no intervention baseline scenario. RESULTS: T2DM prevalence increased from 16.7% in 2016 to 24.0% in 2050 in the baseline scenario. By 2050, through halting the rise or reducing obesity prevalence by 10-50%, T2DM prevalence was reduced by 7.8-33.7%, incidence by 8.4-38.9%, and related deaths by 2.1-13.2%. For smoking, through halting the rise or reducing smoking prevalence by 10-50%, T2DM prevalence was reduced by 0.5-2.8%, incidence by 0.5-3.2%, and related deaths by 0.1-0.7%. For physical inactivity, through halting the rise or reducing physical inactivity prevalence by 10-50%, T2DM prevalence was reduced by 0.5-6.9%, incidence by 0.5-7.9%, and related deaths by 0.2-2.8%. Introduction of physical activity with varying intensity at 25% coverage reduced T2DM prevalence by 3.3-9.2%, incidence by 4.2-11.5%, and related deaths by 1.9-5.2%. CONCLUSIONS: Major reductions in T2DM incidence could be accomplished by reducing obesity, while modest reductions could be accomplished by reducing smoking and physical inactivity, or by introducing physical activity as an intervention

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

Epidemiological impact of public health interventions against diabetes in Qatar: mathematical modeling analyses

AimsTo predict the epidemiological impact of specific, and primarily structural public health interventions that address lifestyle, dietary, and commuting behaviors of Qataris as well as subsidies and legislation to reduce type 2 diabetes mellitus (T2DM) burden among Qataris.MethodsA deterministic population-based mathematical model was used to investigate the impact of public health interventions on the epidemiology of T2DM among Qataris aged 20–79 years, which is the age range typically used by the International Diabetes Federation for adults. The study evaluated the impact of interventions up to 2050, a three-decade time horizon, to allow for the long-term effects of different types of interventions to materialize. The impact of each intervention was evaluated by comparing the predicted T2DM incidence and prevalence with the intervention to a counterfactual scenario without intervention. The model was parameterized using representative data and stratified by sex, age, T2DM risk factors, T2DM status, and intervention status.ResultsAll intervention scenarios had an appreciable impact on reducing T2DM incidence and prevalence. A lifestyle management intervention approach, specifically applied to those who are categorized as obese and ≥35 years old, averted 9.5% of new T2DM cases by 2050. An active commuting intervention approach, specifically increasing cycling and walking, averted 8.5% of new T2DM cases by 2050. Enhancing consumption of healthy diets including fruits and vegetables, specifically a workplace intervention involving dietary modifications and an educational intervention, averted 23.2% of new T2DM cases by 2050. A subsidy and legislative intervention approach, implementing subsidies on fruits and vegetables and taxation on sugar-sweetened beverages, averted 7.4% of new T2DM cases by 2050. A least to most optimistic combination of interventions averted 22.8–46.9% of new T2DM cases by 2050, respectively.ConclusionsImplementing a combination of individual-level and structural public health interventions is critical to prevent T2DM onset and to slow the growing T2DM epidemic in Qatar

Sleep quality and excessive daytime sleepiness in a Arab diabetic population

The aim of this cross-sectional study was to examine the sleep quality, excessive daytime sleepiness (EDS) and its patterns in a Diabetic population sample. The survey was carried out at the outpatient diabetic clinics of the Hamad General Hospital and Primary Health Care (PHC) centres. A total number of 1050 T2DM patients aged above 20 years of age were selected by a systematic sampling procedure from diabetic clinics of the hospitals and PHC centres and 847 cases agreed to participate in the study with a response rate of 80.7%. The study included information about socio-demographic characteristics including age, sex, marital status, education level, occupation, height, weight and parental consanguinity, medical history, smoking habit, physical activity and sleeping habits during the past month. We have used both instruments Epworth sleepiness scale (ESS) score and the Pittsburgh sleep quality index (PSQI). Of the studied diabetic patients, 46.9% were males and 53.1% females. Majority of the diabetic patients were in the age group (40 - 59) years old (59.3%). More than half of the diabetic women were housewives (56.9%) and most of the men were in sedentary and professional jobs (38.1%). ESS score revealed that diabetic women (64.4%) were significantly more sleepier than men (55.2%) during the daytime (p= 0.034). Overall, 60.1% of the diabetic patients were very sleepy during the daytime with 43% men and 57% women and a significant difference was observed between both the genders (p< 0.001). There was a significant association observed between both the genders in all the situations of the Epworth Sleepiness Scale, especially while watching TV (18.4% vs 23.8%, p= 0.024), sitting in the public place (4% vs 10.4%; p= 0.003) and sitting talking to someone (1.5% vs 6.4%, p< 0.001) and sitting in a car in the traffic (3.8% vs 7.1%; p< 0.001). Obesity was significantly higher in diabetic women who had high chances of EDS (51.7%) than men (39.3%) (p= 0.007). Physical activity was significantly lower in diabetic women with poor sleep (38.6%) compared to men (50.2%) (p= 0.012). The present study findings observed that sleep quality was very poor in diabetic population. Also, Excessive day time sleepiness was observed more in diabetic population

Is male fertility associated with type 2 diabetes mellitus?

The aim of this study was to determine the prevalence of infertility in Qatari men with Diabetes Mellitus (T2DM) and to examine the association between T2DM and infertility

The prevalence of restless legs syndrome and comorbid condition among patient with type 2 diabetic mellitus visiting primary healthcare

AIM: The aim of this study was to determine the prevalence of restless legs syndrome (RLS) and Pittsburgh Sleep Quality Index (PSQI) in patients with type 2 diabetes mellitus (T2DM) attending primary healthcare. SUBJECTS AND METHODS: This is a cross-sectional study and participants were between 25 and 70 years old who visited the diabetes and endocrinology department of Mega Medipol University Teaching Hospital, Istanbul. The diagnosis of RLS was performed according to the International Restless Legs Syndrome Study Group consensus criteria. The RLS and PSQI instruments were conducted on 871 patients with T2DM. Good sleep quality was defined as PSQI score <5. RLS severity was assessed by the Restless Legs Syndrome-6 Scales (RLS-6). The scale development and validation was carried out using Rasch measurement model. RESULTS: The prevalence of RLS was 22.8% including 60.3% of females and 39.7% of males. This study showed significant differences between RLS and no RLS patients with respect to their age (years), body mass index (BMI) (kg/m2), physical activity, smoking habit, sheesha smoking, income, and sleeping quality with PSQI. Also, the analysis presented that statistically significant differences between both RLS and no RLS reported sleep complaints including difficulty falling asleep, inadequate sleep, anytime fatigue, and leg discomfort. There were statistically significant differences between RLS and no RLS patients regarding hypoglycemia, numbness in legs, retinopathy, neuropathy, nephropathy high blood pressure, depression, stroke, anemia, diabetic foot, ulcer, arthritis, respiratory disease, metabolic syndrome, and coronary heart disease. Furthermore, there were statistically significant differences between RLS and no RLS concerning the number of sleeping hours, wake-up time (AM), sleeping time (PM), BMI (kg/m2), HbA1c, vitamin D, calcium, creatinine, fasting blood glucose, low-density lipoprotein, triglyceride, uric acid, and systolic and diastolic blood pressure (mmHg). CONCLUSION: This study confirms positive relation and high prevalence of RLS among patients with T2DM visiting primary healthcare. The results suggest that physical activity is associated with a better perception of functional capacity and pain in diabetic patients with RLS, and thus a more active lifestyle should be encouraged

Low vitamin D deficiency associated with thyroid disease among type 2 diabetic mellitus patients

Background: The aim of this study was to investigate the relationship between vitamin D deficiency and thyroid diseases among type 2 diabetes mellitus (T2DM) patients.Methods: This was a cohort case and control study, 546 T2DM patients and 546 control study participants were enrolled, aged between 25 and 65 years. The subjects were also investigated for fasting blood glucose levels (FBG), post prandial glucose (PPG,) glycosylated hemoglobin (HbA1c), thyroid stimulating hormone (TSH), T3, T4, and presence of other comorbid conditions. Thyroid fine needle aspiration biopsy was suggested to patients whose thyroid nodules were greater than 1.00 cm.Results: There were significant differences between T2DM patients and control subjects regarding BMI (kg/m2), physical activity, cigarette smoking, sheesha smoking, family history of diabetes, hypertension and family history of thyroid nodules. The clinical biochemistry values among T2DM for vitamin D, calcium, magnesium, potassium, phosphorous, fasting blood glucose, cholesterol, HbA1c, HLDL, LDL, triglyceride, systolic blood pressure (SBP) and diastolic blood pressure (DBP) were lower than control subjects, but higher in creatinine, albumin, TSH, T3, and T4 which appeared statistically significant differences (P < 0.001). Also, the study revealed statistically significant differences between subjects vitamin D deficiency and with thyroid nodules for calcium, magnesium, phosphorous, HbA1c, high density lipoprotein (HDL), SBP and DBP, TSH, T3, and T4 among T2DM patients and control subjects (P < 0.001). Multivariable stepwise logistic regression analysis showed that TSH, HbA1c, vitamin D deficiency, SBP (mm Hg), BMI, family history of DM, serum calcium level and family history of thyroid were considered at higher risk as predictors of thyroid among T2DM patients.Conclusions: This study suggests that obesity, HbA1c, the environment, and genetic susceptibility among T2DM, may increase the risk of thyroid disease and cancer. Although evidence has shown that thyroid cancer incidence has been rising more rapidly over time than the occurrence of cancers of other sites, due to an increase of obesity, diabetes and lack of physical activity, this study lacks of direct evidence supporting this conclusion

Prevalence of erectile dysfunction in male stroke patients, and associated co-morbidities and risk factors

Background Sexual problems have been a common finding in chronically ill and physically disabled patients such as those with cerebrovascular accidents. Previous studies have supported the association between stroke and erectile dysfunction (ED)

Does Ramadan fasting have effects on sleep, fatigue and blood pressure among patients with hypertension?

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