Prevalence and screening for risk factors of type 2 diabetes in Rize, Nourtheast Turkey: findings from a population-based study

2016 ◽  
Vol 10 (1) ◽  
pp. 10-18 ◽  
Author(s):  
A. Bayındır Çevik ◽  
M. Metin Karaaslan ◽  
S. Koçan ◽  
H. Pekmezci ◽  
S. Baydur Şahin ◽  
...  
Keyword(s):  
Risk Factors ◽  
Type 2 Diabetes ◽  
Population Based ◽  
Population Based Study

scholarly journals APPLYING DECISION TREE FOR DETECTION OF A RISK FACTORS FOR TYPE 2 DIABETES: A POPULATION BASED STUDY

2017 ◽  
Vol 2 (1) ◽  
pp. 138-138
Author(s):  
Maryam Tayefi ◽  
Habibollah Esmaeily ◽  
Majid Ghayour-Mobarhan ◽  
Ali Reza Amirabadi zadeh
Keyword(s):  
Risk Factors ◽  
Type 2 Diabetes ◽  
Decision Tree ◽  
Population Based ◽  
Population Based Study

Abstract P057: Clusters of Cardiovascular Risk Factors Predict Incidence of Type 2 Diabetes in Men and Women: A Swedish Population-based Study

Circulation ◽  
2016 ◽  
Vol 133 (suppl_1) ◽  
Author(s):  
Charlotte A Larsson ◽  
Bledar Daka ◽  
Margareta I Hellgren ◽  
Maria C Eriksson ◽  
Lennart Råstam ◽  
...  
Keyword(s):  
Physical Activity ◽  
Risk Factors ◽  
Type 2 Diabetes ◽  
Cardiovascular Risk ◽  
Cardiovascular Risk Factors ◽  
Population Based ◽  
Population Based Study ◽  
Men And Women ◽  
Self Rated Health

Introduction: Clusters of metabolic variables and their effects on incidence of type 2 diabetes have been studied previously; however, little is known about the effects on diabetes from risk factor clusters including lifestyle and self-rated health. Hypothesis: We assessed the hypothesis that clusters of common cardiovascular risk factors, including lifestyle and self-rated health, can predict development of type 2 diabetes in men and women, respectively. Methods: In 2002-2005, 2816 men and women, 30-74 years, were randomly selected from two municipalities in southwestern Sweden and assessed with regard to cardiovascular/metabolic risk factors within the Skaraborg Project (76% participation). Participants performed an OGTT, had blood samples drawn, had anthropometric measurements and blood pressure taken, and answered validated questionnaires about e.g. leisure-time physical activity (with four answer alternatives from intensive to sedentary) and self-rated health (with five alternatives from excellent to very poor). Using the same protocol, 1332 participants from the baseline survey where re-examined in 2011-2014. After excluding those with diabetes at baseline, 1268 participants were included in this prospective population-based study. Results: Factor analysis (using varimax rotation) identified significant loadings (≥0.40) on the following three identical factors in men and women: the metabolic factor , comprising HOMA-ir, WHR, systolic blood pressure, and apolipoprotein B-to-A1 ratio; the vitality factor , comprising physical activity and self-rated health; and the addiction factor , comprising smoking and alcohol consumption. After a mean follow-up of 9.7±1.4 years, 76 cases of diabetes were identified; 46 in men and 30 in women. In a logistic regression analysis adjusted for all principal components, age, and educational level, the metabolic factor significantly predicted type 2 diabetes in both men (OR: 3.3, CI: 2.3-5.0) and women (OR: 3.5, CI: 2.2-5.6). Furthermore, a predictive effect of the vitality factor was also seen in women (OR: 1.8, CI: 1.2-2.9), but not in men (OR: 1.1, CI: 0.8-1.6), whereas the addiction factor had no effect in either men or women. Conclusions: This is to our knowledge the first time principle components of cardiovascular risk factors, including both metabolic and lifestyle variables, have been used to predict incidence of type 2 diabetes. The gender difference observed with regard to the combined impact of self-rated health and physical activity are novel and indicates a mechanism beside the metabolic syndrome that warrants further gender-specific exploration in future studies.

scholarly journals Incidence and Risk Factors for Dementia in Type 2 Diabetes Mellitus: A Nationwide Population-Based Study in Korea

2020 ◽  
Vol 44 (1) ◽  
pp. 113 ◽  
Author(s):  
Ji Hee Yu ◽  
Kyungdo Han ◽  
Sanghyun Park ◽  
Hanna Cho ◽  
Da Young Lee ◽  
...  
Keyword(s):  
Diabetes Mellitus ◽  
Risk Factors ◽  
Type 2 Diabetes ◽  
Type 2 Diabetes Mellitus ◽  
Population Based ◽  
Population Based Study

Abstract 31: Patterns Of Healthcare Resource Utilization Among Adults With Type 2 Diabetes Mellitus At Risk Of Cardiovascular Events In The Large Population-based Study To Help Improve Early Evaluation And Management Of Risk Factors Leading To Diabetes (SHIELD)

2013 ◽  
Vol 6 (suppl_1) ◽  
Author(s):  
Kathleen M Fox ◽  
Ying Wu ◽  
Jennifer Kim ◽  
Susan Grandy
Keyword(s):  
Diabetes Mellitus ◽  
Risk Factors ◽  
Type 2 Diabetes ◽  
Healthcare Resource ◽  
Population Based ◽  
Healthcare Resource Utilization ◽  
Population Based Study ◽  
Very High

Objectives: Patterns of healthcare resource utilization (HRU) among patients with type 2 diabetes mellitus (T2DM) and cardiovascular disease (CVD) are not well studied in large epidemiological studies. Using a large US population-based study, SHIELD, this study quantified the HRU over 3 and 5 years among adults with T2DM at high risk for CVD. Methods: SHIELD is a 5-year (2004-2009) prospective survey-based study of adults with and without T2DM. Respondents with T2DM were stratified into 2 cohorts: (1) established CVD with age ≥40 years, prior MI, prior stroke, atherosclerosis, or peripheral vascular disease, and (2) multiple risk factors (men ≥55 years and women ≥60 years and ≥1 risk factors of hyperlipidemia, hypertension, currently smoking, without prior history of CVD). Number of hospitalizations, emergency room (ER) visits, and physician office visits were tabulated for respondents who did and did not report a new CVD event (MI, stroke, angioplasty, or heart bypass surgery) in each cohort for up to 3 and 5 years of follow-up. Results: Frequencies of hospitalization, ER visit, and physician visit within 3 and 5 years of follow-up were significantly higher among those who reported a new CVD event over 3 and 5 years for both cohorts compared with respondents without a new CVD event, p <0.05 (Table). Median number of hospitalizations, ER visits, and physician visits were significantly higher for respondents reporting a new CVD event compared with respondents with no new CVD events for both cohorts, p <0.01 (Table). Conclusions: CVD events among T2DM patients continue to represent a very high economic burden on the healthcare system. HRU is very high among adults with T2DM at-risk of CVD events and significantly higher among those who had a new CVD event within 3 and 5 years compared with those who did not have a new CVD event.

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