an application of association rule mining to extract risk pattern for type 2 diabetes using tehran lipid and glucose study database

نویسندگان

azra ramezankhani prevention of metabolic disorders research center, research institute for endocrine sciences, shahid beheshti university of medical sciences, tehran, ir iran

omid pournik department of community medicine, school of medicine, iran university of medical sciences, tehran, ir iran

jamal shahrabi department of industrial engineering, amirkabir university of technology, tehran, ir iran

fereidoun azizi endocrine research center, research institute for endocrine sciences, shahid beheshti university of medical sciences, tehran, ir iran

چکیده

conclusions our study showed that arm is a useful approach in determining which combinations of variables or predictors occur together frequently, in people who will develop diabetes. the arm focuses on joint exposure to different combinations of risk factors, and not the predictors alone. background type 2 diabetes, common and serious global health concern, had an estimated worldwide prevalence of 366 million in 2011, which is expected to rise to 552 million people, by 2030, unless urgent action is taken. objectives the aim of this study was to identify risk patterns for type 2 diabetes incidence using association rule mining (arm). patients and methods a population of 6647 individuals without diabetes, aged ≥ 20 years at inclusion, was followed for 10-12 years, to analyze risk patterns for diabetes occurrence. study variables included demographic and anthropometric characteristics, smoking status, medical and drug history and laboratory measures. results in the case of women, the results showed that impaired fasting glucose (ifg) and impaired glucose tolerance (igt), in combination with body mass index (bmi) ≥ 30 kg/m2, family history of diabetes, wrist circumference > 16.5 cm and waist to height ≥ 0.5 can increase the risk for developing diabetes. for men, a combination of igt, ifg, length of stay in the city (> 40 years), central obesity, total cholesterol to high density lipoprotein ratio ≥ 5.3, low physical activity, chronic kidney disease and wrist circumference > 18.5 cm were identified as risk patterns for diabetes occurrence.

برای دانلود باید عضویت طلایی داشته باشید

برای دانلود متن کامل این مقاله و بیش از 32 میلیون مقاله دیگر ابتدا ثبت نام کنید

اگر عضو سایت هستید لطفا وارد حساب کاربری خود شوید

منابع مشابه

An Application of Association Rule Mining to Extract Risk Pattern for Type 2 Diabetes Using Tehran Lipid and Glucose Study Database

BACKGROUND Type 2 diabetes, common and serious global health concern, had an estimated worldwide prevalence of 366 million in 2011, which is expected to rise to 552 million people, by 2030, unless urgent action is taken. OBJECTIVES The aim of this study was to identify risk patterns for type 2 diabetes incidence using association rule mining (ARM). PATIENTS AND METHODS A population of 6647 ...

متن کامل

Association of the Type and Amount of Dietary Proteins with Microalbuminuria: Tehran Lipid and Glucose Study

Introduction: Microalbuminuria is an independent risk factor for cardiovascular disease and is associated with all-cause mortality. The present study aimed to investigate the possible association between different types and amounts of dietary protein and microalbuminuria among Iranian adults participating in the Tehran Lipid and Glucose Study (TLGS). Materials and Methods: Adults (1192 men and ...

متن کامل

Association of Dietary Fat Pattern and Incidence of Cardiovascular Disease, Hypertension and Chronic Kidney Disease: Tehran Lipid and Glucose Study

Introduction: Cardiovascular disease (CVD), hypertension (HTN) and chronic kidney disease (CKD) are chronic conditions of recent decades, and dietary intakes play an important role in their prevention. The purpose of this study was to examine the association between dietary fat pattern and incidence of these conditions. Materials and Methods: Participants of the third phase (2006-2008) of the T...

متن کامل

Designing an intelligent system for diagnosing type 2 diabetes using the data mining approach: brief report

Background: Diabetes mellitus has several complications. The Late diagnosis of diabetes in people leads to the spread of complications. Therefore, this study has been done to determine the possibility of predicting diabetes type 2 by using data mining techniques. Methods: This is a descriptive-analytic study that was conducted as a cross-sectional study. The study population included people re...

متن کامل

Comparing Three Data Mining Algorithms for Identifying the Associated Risk Factors of Type 2 Diabetes

Background: Increasing the prevalence of type 2 diabetes has given rise to a global health burden and a concern among health service providers and health administrators. The current study aimed at developing and comparing some statistical models to identify the risk factors associated with type 2 diabetes. In this light, artificial neural network (ANN), support vector machines (SVMs), and multi...

متن کامل

an application of fuzzy logic for car insurance underwriting

در ایران بیمه خودرو سهم بزرگی در صنعت بیمه دارد. تعیین حق بیمه مناسب و عادلانه نیازمند طبقه بندی خریداران بیمه نامه براساس خطرات احتمالی آنها است. عوامل ریسکی فراوانی می تواند بر این قیمت گذاری تاثیر بگذارد. طبقه بندی و تعیین میزان تاثیر گذاری هر عامل ریسکی بر قیمت گذاری بیمه خودرو پیچیدگی خاصی دارد. در این پایان نامه سعی در ارائه راهی جدید برای طبقه بندی عوامل ریسکی با استفاده از اصول و روش ها...

منابع من

با ذخیره ی این منبع در منابع من، دسترسی به آن را برای استفاده های بعدی آسان تر کنید


عنوان ژورنال:
international journal of endocrinology and metabolism

جلد ۱۳، شماره ۲، صفحات ۰-۰

میزبانی شده توسط پلتفرم ابری doprax.com

copyright © 2015-2023