scholarly journals Statin use and Type 2 Diabetes Incidence

2021 ◽  
Vol 4 (1) ◽  
pp. 1139-1145
Author(s):  
Musa Basheer Mansour ◽  
Sara Elsheikh Ahmedana
Keyword(s):  
Type 2 Diabetes ◽  
Diabetes Incidence ◽  
Statin Use

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1460-P: Type 2 Diabetes Polygenic Score in Addition to Clinical Factors for Prediction of Diabetes Incidence in an Indigenous American Population

Diabetes ◽  
2020 ◽  
Vol 69 (Supplement 1) ◽  
pp. 1460-P
Author(s):  
LAUREN E. WEDEKIND ◽  
SAYUKO KOBES ◽  
WEN-CHI HSUEH ◽  
LESLIE BAIER ◽  
WILLIAM C. KNOWLER ◽  
...  
Keyword(s):  
Type 2 Diabetes ◽  
Diabetes Incidence ◽  
American Population ◽  
Clinical Factors ◽  
Polygenic Score ◽  
Prediction Of Diabetes ◽  
P Type

Statin use in Type 2 diabetes mellitus is associated with a delay in starting insulin

2004 ◽  
Vol 21 (9) ◽  
pp. 962-967 ◽  
Author(s):  
A. Yee ◽  
S. R. Majumdar ◽  
S. H. Simpson ◽  
F. A. McAlister ◽  
R. T. Tsuyuki ◽  
...  
Keyword(s):  
Diabetes Mellitus ◽  
Type 2 Diabetes ◽  
Type 2 Diabetes Mellitus ◽  
Statin Use

scholarly journals The Active Role of Leguminous Plant Components in Type 2 Diabetes

2014 ◽  
Vol 2014 ◽  
pp. 1-12 ◽  
Author(s):  
Monika Gętek ◽  
Natalia Czech ◽  
Małgorzata Muc-Wierzgoń ◽  
Elżbieta Grochowska-Niedworok ◽  
Teresa Kokot ◽  
...  
Keyword(s):  
Type 2 Diabetes ◽  
Bioactive Compounds ◽  
International Diabetes Federation ◽  
Noncommunicable Diseases ◽  
Antidiabetic Activity ◽  
Leguminous Plant ◽  
Morbidity Rate ◽  
Diabetes Incidence ◽  
Leguminous Plants

Diabetes appears to be one of the most frequent noncommunicable diseases in the world. A permanent growth in the incidence of diabetes can be observed and according to the International Diabetes Federation (IDF) the year 2030 will mark the increase in the number of diabetics to 439 mln worldwide. Type 2 diabetes accounts for about 90% of all diabetes incidence. Nutrition model modification not only features the basic element in type 2 diabetes treatment but also constitutes the fundamental factor influencing a morbidity rate decrease. Leguminous plants are a key factor in the diabetic diet; plants such as pulses or soybeans are nutritious products valued highly in nutrition. These legumes are high in the content of wholesome protein and contain large amounts of soluble alimentary fiber fractions, polyunsaturated fatty acids, vitamins and minerals, and bioactive substances with antioxidant, anti-inflammatory, and anticancer activity. They are distinguished by the high amount of bioactive compounds that may interfere with the metabolism of glucose. The most significant bioactive compounds displaying antidiabetic activity in leguminous plants are as follows: genistein and daidzein, alpha-amylase inhibitors, and alpha-glucosidase inhibitors.In vitroresearch using leguminous plant extracts has confirmed their antidiabetic properties. Leguminous plants should be employed in the promotion of healthy lifestyles in terms of functional food.

scholarly journals Serum Selenium Status in Patients with Type 2 Diabetes and Control Group

2016 ◽  
Vol 9 (5) ◽  
pp. 234
Author(s):  
Zahra Heidari ◽  
Zahra Sepehri ◽  
Aleme Doostdar
Keyword(s):  
Type 2 Diabetes ◽  
Serum Level ◽  
Control Group ◽  
Diabetic Patients ◽  
Diabetes Incidence ◽  
Serum Selenium ◽  
Type 2 Diabetic Patients ◽  
Significant Difference ◽  
The Mean

<p>In addition to known risk factors, the role of different micronutrients such as selenium in diabetes incidence has been proposed. Some previous studies have shown an association of selenium deficiency and type 2 diabetes mellitus, while other studies have not confirmed such a relationship. The aim of this study was to evaluate serum level of selenium in patients with Type 2 diabetes compared with the control group. This cross-sectional study was carried out on patients with type 2 diabetes in Zahedan, southeastern Iran. One hundred newly diagnosed type 2 diabetic patients were evaluated for serum selenium level. One hundred subjects from the general population who had normal fasting blood sugar levels were selected as the control group. The control group subjects were matched in pairs with each of patients on the basis of sex, age (± one year), and body mass index (±1). Serum level of selenium was determined by spectrometry method. Results were compared using t-test. The mean serum level of selenium in patients was 94.47±18.07 µg/L whereas in control group was 142.79±23.67 µg/L. The mean serum level of selenium was significantly different between the two groups (P&lt;0.001). Serum levels of selenium in diabetic patients with significant difference statistically were lower than the control group. In order to evaluate serum level of selenium in patients with diabetes, studies with larger sample size are required. Likewise, prospective studies along with selenium supplementation and investigating its effect on incidence of diabetes are accordingly needed.</p>

scholarly journals Predicting the Development of Type 2 Diabetes in a Large Australian Cohort Using Machine-Learning Techniques: Longitudinal Survey Study (Preprint)

2019 ◽  
Author(s):  
Lei Zhang ◽  
Xianwen Shang ◽  
Subhashaan Sreedharan ◽  
Xixi Yan ◽  
Jianbin Liu ◽  
...  
Keyword(s):  
Machine Learning ◽  
Type 2 Diabetes ◽  
Risk Prediction ◽  
Machine Learning Algorithms ◽  
Survey Study ◽  
Gradient Boosting ◽  
Diabetes Incidence ◽  
Diabetes Onset ◽  
Prediction Of Diabetes

BACKGROUND Previous conventional models for the prediction of diabetes could be updated by incorporating the increasing amount of health data available and new risk prediction methodology. OBJECTIVE We aimed to develop a substantially improved diabetes risk prediction model using sophisticated machine-learning algorithms based on a large retrospective population cohort of over 230,000 people who were enrolled in the study during 2006-2017. METHODS We collected demographic, medical, behavioral, and incidence data for type 2 diabetes mellitus (T2DM) in over 236,684 diabetes-free participants recruited from the 45 and Up Study. We predicted and compared the risk of diabetes onset in these participants at 3, 5, 7, and 10 years based on three machine-learning approaches and the conventional regression model. RESULTS Overall, 6.05% (14,313/236,684) of the participants developed T2DM during an average 8.8-year follow-up period. The 10-year diabetes incidence in men was 8.30% (8.08%-8.49%), which was significantly higher (odds ratio 1.37, 95% CI 1.32-1.41) than that in women at 6.20% (6.00%-6.40%). The incidence of T2DM was doubled in individuals with obesity (men: 17.78% [17.05%-18.43%]; women: 14.59% [13.99%-15.17%]) compared with that of nonobese individuals. The gradient boosting machine model showed the best performance among the four models (area under the curve of 79% in 3-year prediction and 75% in 10-year prediction). All machine-learning models predicted BMI as the most significant factor contributing to diabetes onset, which explained 12%-50% of the variance in the prediction of diabetes. The model predicted that if BMI in obese and overweight participants could be hypothetically reduced to a healthy range, the 10-year probability of diabetes onset would be significantly reduced from 8.3% to 2.8% (<i>P</i>&lt;.001). CONCLUSIONS A one-time self-reported survey can accurately predict the risk of diabetes using a machine-learning approach. Achieving a healthy BMI can significantly reduce the risk of developing T2DM.

scholarly journals A high-fat, high-glycaemic index, low-fibre dietary pattern is prospectively associated with type 2 diabetes in a British birth cohort

2016 ◽  
Vol 115 (9) ◽  
pp. 1632-1642 ◽  
Author(s):  
Silvia Pastorino ◽  
Marcus Richards ◽  
Mary Pierce ◽  
Gina L. Ambrosini
Keyword(s):  
Type 2 Diabetes ◽  
Waist Circumference ◽  
Dietary Pattern ◽  
Repeated Measures ◽  
Glycaemic Index ◽  
Diabetes Risk ◽  
Processed Meat ◽  
Diabetes Incidence ◽  
High Fat

AbstractThe combined association of dietary fat, glycaemic index (GI) and fibre with type 2 diabetes has rarely been investigated. The objective was to examine the relationship between a high-fat, high-GI, low-fibre dietary pattern across adult life and type 2 diabetes risk using reduced rank regression. Data were from the MRC National Survey of Health and Development. Repeated measures of dietary intake estimated using 5-d diet diaries were available at the age of 36, 43 and 53 years for 1180 study members. Associations between dietary pattern scores at each age, as well as longitudinal changes in dietary pattern z-scores, and type 2 diabetes incidence (n 106) from 53 to 60–64 years were analysed. The high-fat, high-GI, low-fibre dietary pattern was characterised by low intakes of fruit, vegetables, low-fat dairy products and whole-grain cereals, and high intakes of white bread, fried potatoes, processed meat and animal fats. There was an increasing trend in OR for type 2 diabetes with increasing quintile of dietary pattern z-scores at the age of 43 years among women but not among men. Women in the highest z-score quintile at the age of 43 years had an OR for type 2 diabetes of 5·45 (95 % CI 2·01, 14·79). Long-term increases in this dietary pattern, independently of BMI and waist circumference, were also detrimental among women: for each 1 sd unit increase in dietary pattern z-score between 36 and 53 years, the OR for type 2 diabetes was 1·67 (95 % CI 1·20, 2·43) independently of changes in BMI and waist circumference in the same periods. A high-fat, high-GI, low-fibre dietary pattern was associated with increased type 2 diabetes risk in middle-aged British women but not in men.

Association between Statin Use and Physical Function among Older Chinese Inpatients with Type 2 Diabetes

2019 ◽  
Vol 24 (2) ◽  
pp. 194-197
Author(s):  
Y. Li ◽  
X. Yang ◽  
Y. Zou ◽  
J. Li ◽  
Q. Sun ◽  
...  
Keyword(s):  
Type 2 Diabetes ◽  
Physical Function ◽  
Older Chinese ◽  
Statin Use

scholarly journals An Evaluation of Statin Use Among Patients with Type 2 Diabetes at High Risk of Cardiovascular Events Across Multiple Health Care Systems

2020 ◽  
Vol 26 (9) ◽  
pp. 1090-1098
Author(s):  
Ralph Ward ◽  
Erin R. Weeda ◽  
Kinfe G. Bishu ◽  
R. Neal Axon ◽  
David J. Taber ◽  
...  
Keyword(s):  
Type 2 Diabetes ◽  
Health Care ◽  
High Risk ◽  
Cardiovascular Events ◽  
Health Care Systems ◽  
Care Systems ◽  
Multiple Health ◽  
Statin Use

scholarly journals Adolescent Nonalcoholic Fatty Liver Disease and Type 2 Diabetes in Young Adulthood

2020 ◽  
Vol 106 (1) ◽  
pp. e34-e44
Author(s):  
Aya Bardugo ◽  
Cole D Bendor ◽  
Inbar Zucker ◽  
Miri Lutski ◽  
Tali Cukierman-Yaffe ◽  
...  
Keyword(s):  
Type 2 Diabetes ◽  
Liver Disease ◽  
Fatty Liver ◽  
Nonalcoholic Fatty Liver Disease ◽  
Fatty Liver Disease ◽  
Sensitivity Analyses ◽  
Control Group ◽  
Diabetes Incidence ◽  
Nonalcoholic Fatty Liver

Abstract Context The long-term risk of type 2 diabetes in adolescents with nonalcoholic fatty liver disease (NAFLD) is unclear. Objective To assess type 2 diabetes risk among adolescents with NAFLD. Design and Setting A nationwide, population-based study of Israeli adolescents who were examined before military service during 1997–2011 and were followed until December 31, 2016. Participants A total of 1 025 796 normoglycemic adolescents were included. Interventions Biopsy or radiographic tests were prerequisite for NAFLD diagnosis. Data were linked to the Israeli National Diabetes Registry. Main Outcome Measures Type 2 diabetes incidence. Results During a mean follow-up of 13.3 years, 12 of 633 adolescents with NAFLD (1.9%; all with high body mass index [BMI] at baseline) were diagnosed with type 2 diabetes compared with 2917 (0.3%) adolescents without NAFLD. The hazard ratio (HR) for type 2 diabetes was 2.59 (95% confidence interval [CI], 1.47–4.58) for the NAFLD vs. the non-NAFLD group after adjustment for BMI and sociodemographic confounders. The elevated risk persisted in several sensitivity analyses. These included an analysis of persons without other metabolic comorbidities (adjusted HR, 2.75 [95% CI, 1.48-5.14]) and of persons with high BMI; and an analysis whose outcome was type 2 diabetes by age 30 years (adjusted HR, 2.14 [95% CI, 1.02-4.52]). The results remained significant when a sex-, birth year-, and BMI-matched control group was the reference (adjusted HR, 2.98 [95% CI, 1.54-5.74]). Conclusions Among normoglycemic adolescents, NAFLD was associated with an increased adjusted risk for type 2 diabetes, which may be apparent before age 30 years.

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