scholarly journals Mathematical Regression Models for Analyzing and Forecasting Diabetes prevalence in Oman

2021 ◽  
Author(s):  
Jabar Yousif
Keyword(s):  
Mathematical Model ◽  
Mathematical Models ◽  
Regression Models ◽  
Diabetes Type 2 ◽  
Diabetes Type ◽  
Actual Data ◽  
Sultanate Of Oman ◽  
Proposed Model ◽  
Future Data

<p>This work is concerned with proposing mathematical models characterized by accuracy and ease in predicting the number of diabetics type 2 in the Sultanate of Oman. By analyzing the proposed mathematical models of the current work (1, 2, and 3), it was found that the proposed mathematical model in Equation 6 can accurately predict the number of diabetics in Oman up to 2050. In order to test the model's accuracy and validity, we revised it with actual data. The results prove the accuracy of the proposed model in predicting future data of 99%. Lastly, several recommendations were recorded that could help to reduce the prevalence of diabetes type 2 in Oman.</p>

scholarly journals Mathematical Regression Models for Analyzing and Forecasting Diabetes prevalence in Oman

2021 ◽  
Author(s):  
Jabar Yousif
Keyword(s):  
Mathematical Model ◽  
Mathematical Models ◽  
Regression Models ◽  
Diabetes Type 2 ◽  
Diabetes Type ◽  
Actual Data ◽  
Sultanate Of Oman ◽  
Proposed Model ◽  
Future Data

<p>This work is concerned with proposing mathematical models characterized by accuracy and ease in predicting the number of diabetics type 2 in the Sultanate of Oman. By analyzing the proposed mathematical models of the current work (1, 2, and 3), it was found that the proposed mathematical model in Equation 6 can accurately predict the number of diabetics in Oman up to 2050. In order to test the model's accuracy and validity, we revised it with actual data. The results prove the accuracy of the proposed model in predicting future data of 99%. Lastly, several recommendations were recorded that could help to reduce the prevalence of diabetes type 2 in Oman.</p>

Mathematical Regression Models for Analyzing and Forecasting Diabetes prevalence in Oman

2021 ◽  
pp. 91-102
Author(s):  
Jabar H. Yousif
Keyword(s):  
Mathematical Models ◽  
Financial Burden ◽  
Diabetes Type 2 ◽  
Economic Effects ◽  
Sultanate Of Oman ◽  
Proposed Model ◽  
Future Data ◽  
Use Of Health Services

Diabetes mellitus has a significant impact on people's lives and drugs financial burden. On the other hand, diabetes also has substantial economic effects on countries and national health systems. Most countries spend between 5% and 20% of their total health expenditures on diabetes. This is due to the increased use of health services, lack of productivity, and the long-term demand for complications associated with diabetes, such as kidney failure, blindness, and heart problems. This is why diabetes poses a significant challenge to healthcare systems and hinders sustainable economic development. This work is concerned with proposing mathematical models characterized by accuracy and ease in predicting the number of diabetics type 2 in the Sultanate of Oman. By analyzing the proposed mathematical models of the current work (1, 2, and 3), it was found that the proposed mathematical model in Equation 6 can accurately predict the number of diabetics in Oman up to 2050. In order to test the model's accuracy and validity, we revised it with actual data. The results prove the accuracy of the proposed model in predicting future data of 99%. Lastly, several recommendations were recorded that could help to reduce the prevalence of diabetes type 2 in Oman.

Eksplorasi Kesadaran Diri, Persepsi Dan Sikap Pada Individu Yang Memiliki Riwayat Keluarga Diabetes Melitus Tipe 2

2019 ◽  
Vol 1 (1) ◽  
pp. 52-62
Author(s):  
Mulia Mayangsari
Keyword(s):  
Diabetes Mellitus ◽  
Type 2 Diabetes ◽  
Family History ◽  
Diabetes Type 2 ◽  
Diabetes Type ◽  
Self Awareness ◽  
Perceptions And Attitudes ◽  
History Of ◽  
Diabetes Melitus

 Individuals who have a family history oftype 2 diabetes mellitus (DM) have a highrisk for type 2 diabetes. Type 2 diabetescan be prevented by improving modifiablerisk factors, supported by self-awareness,perceptions and attitudes of individualswho have a high family history of DM. Thisstudy used a qualitative phenomenologicaldesign. A Purposive Sampling techiniquewas applied to determine individuals whohad parents with type 2 diabetes. Nineindividuals participated in this study. AQualitative content analysis with Collaiziapproach used as a data analysis method.The main themes depicted individuals selfawareness,perceptions, & attitudes were:denials that diabetes caused by heredityfactors; misperception about diabetes;“traditional modalities” as a preventionmeasurement toward type 2 diabetes; andDM is perceived as a “threatening disease”.Further study is needed to examine indepth the themes that have been identifiedon the number of participants are morenumerous and varied.

Risk Factors Associated With Hyperuricemia in Patients with Diabetes Type 2: About 190 Cases

2020 ◽  
Vol 2 (1) ◽  
pp. 12-16
Author(s):  
Fennoun H ◽  
Haraj NE ◽  
El Aziz S ◽  
Bensbaa S ◽  
Chadli A
Keyword(s):  
Type 2 Diabetes ◽  
Heart Disease ◽  
Glycemic Control ◽  
Ischemic Heart Disease ◽  
Diabetes Type 2 ◽  
Diabetes Type ◽  
Ischemic Heart ◽  
Factors Associated ◽  
Patients With Diabetes

Introduction: Hyperuricemia is common Type 2 diabetes at very high cardiovascular risk. Objective: Evaluate the relationship between hyperuricemia and diabetes type 2, and determine its predictive factors in this population. Patients and Methods: Retrospective study cross including 190 patients with diabetes type 2 hospitalized Service of Endocrinology of CHU Ibn Rushd Casablanca from January 2015 to December 2017. Hyperuricemia was defined as a serum uric acid concentration> 70 mg/L (men) and> 60 mg/L (women). The variables studied were the anthropometric measurements), cardiovascular factors (tobacco, hypertension, dyslipidemia), and degenerative complications (retinopathy, neuropathy, kidney failure, ischemic heart disease). The analyzes were performed by SPSS software. Results: Hyperuricemia was found in 26.5% of patients with a female predominance (76%), an average age of 55.9 years, and an average age of 12.4ans diabetes. The glycemic control was found in 84.6% of cases with mean glycated hemoglobin 8.6%. Factors associated al hyperuricemia were the blood pressure in 86% (p <0.05), dyslipidemia in 76.3% of cases (p <0.001) with hypertriglyceridemia in 48.3% of cases (p <0.02), and a hypoHDLémie 28% (p <0.001). The age, obesity, smoking, and glycemic control were associated significantly n al hyperuricemia. The research of degenerative complications of hyperuricemia has objectified renal impairment (GFR between 15 and 60ml / min) chez47% (p <0.001), it was kind of moderate in 35.8% (p <0.01) and severe in 5.1% (p <0.02), ischemic heart disease was found in 34% of cases (p <0.01). Conclusion: In our study, hyperuricemia in type 2 diabetes is common in female patients, especially with hypertension, dyslipidemia, and renal failure. Other factors such as age, obesity, smoking is not associated with hyperuricemia in type 2 diabetics.

scholarly journals Investigating GSTT1 and GSTM1 null genotype as the risk factor of diabetes type 2 retinopathy

2013 ◽  
Vol 12 (1) ◽  
Author(s):  
Alamdar Dadbinpour ◽  
Mohammad Hasan Sheikhha ◽  
Mojtaba Darbouy ◽  
Mohammad Afkhami-Ardekani
Keyword(s):  
Risk Factor ◽  
Diabetes Type 2 ◽  
Diabetes Type ◽  
Gstm1 Null Genotype

Dementie bij diabetes type 2 onvermijdelijk

2011 ◽  
Vol 54 (12) ◽  
pp. 635-635
Author(s):  
Ymte Groeneveld
Keyword(s):  
Diabetes Type 2 ◽  
Diabetes Type

scholarly journals Neuroinflammation as a Common Denominator of Complex Diseases (Cancer, Diabetes Type 2, and Neuropsychiatric Disorders)

2021 ◽  
Vol 22 (11) ◽  
pp. 6138
Author(s):  
Serena Asslih ◽  
Odeya Damri ◽  
Galila Agam
Keyword(s):  
Cell Activation ◽  
Neuronal Degeneration ◽  
Complex Diseases ◽  
Diabetes Type 2 ◽  
Neuropsychiatric Disorders ◽  
Diabetes Type ◽  
Common Denominator ◽  
Cancer Type ◽  
Complex Disorders

The term neuroinflammation refers to inflammation of the nervous tissue, in general, and in the central nervous system (CNS), in particular. It is a driver of neurotoxicity, it is detrimental, and implies that glial cell activation happens prior to neuronal degeneration and, possibly, even causes it. The inflammation-like glial responses may be initiated in response to a variety of cues such as infection, traumatic brain injury, toxic metabolites, or autoimmunity. The inflammatory response of activated microglia engages the immune system and initiates tissue repair. Through translational research the role played by neuroinflammation has been acknowledged in different disease entities. Intriguingly, these entities include both those directly related to the CNS (commonly designated neuropsychiatric disorders) and those not directly related to the CNS (e.g., cancer and diabetes type 2). Interestingly, all the above-mentioned entities belong to the same group of “complex disorders”. This review aims to summarize cumulated data supporting the hypothesis that neuroinflammation is a common denominator of a wide variety of complex diseases. We will concentrate on cancer, type 2 diabetes (T2DM), and neuropsychiatric disorders (focusing on mood disorders).

Sign in / Sign up

Export Citation Format

Share Document