Assessment of the Metabolic Syndrome Data in Children and Adolescence in Birjand city of Iran: A data mining based approach

Computer and Knowledge Engineering

مقالات آماده انتشار، پذیرفته شده، انتشار آنلاین از تاریخ 04 اسفند 1399  

نوع مقاله: Machine learning-Sadoghi

شناسه دیجیتال (DOI): 10.22067/cke.2021.63297.0

نویسندگان

Fatemeh Taheri¹؛ Vahide Babaiyan ²؛ Mohsen Saffarian ³؛ Seyed Mahmood Kazemi ³؛ Kokab Namakin ¹؛ Toba Kazemi ⁴؛ Azra Ramezankhani⁵

¹Cardiovascular Diseases Research Centre, Department of Pediatric, Birjand University of Medical Sciences, Birjand, Iran.

²Department of Computer Engineering, Birjand University of Technology, Birjand, Iran

³Department of Industrial Engineering, Birjand University of Technology, Birjand, Iran

⁴Cardiovascular Diseases Research Centre, Department of Cardiology, Birjand University of Medical Sciences, Birjand, Iran.

⁵Prevention of Metabolic Disorders Research Center, Research Institute for Endocrine Sciences, Shahid Beheshti University of Medical Sciences, Tehran, Iran

چکیده

Metabolic Syndrome (MS) is the collection of risk factors for coronary artery disease (CAD). It is responsible for cardiovascular disease (CVD), type 2 diabetes, cancer, renal and mental diseases with the transition from childhood to adulthood. The MS is increasing in recent decades in different societies, especially in Iran. This study is conducted to determine the predictive factors of MS in children and adolescents in Birjand city (Capital of South Khorasan province in Iran) using a data mining approach. The four different analyses for females, males, 6-11 and 12-18 year-old group were carried out using three popular decision tree models. The most important prognostic factors for MS were high level of TG and low level of DBP and HDL in 6-11-year-old group, and high level of waist circumference (WC) and low level of TG for 12-18-year-old group. The most important factors were TG and HDL in females and WC and TG in males. Apprise teens and families to the risk factors and screening for children and teens, Monitor and control the risk factors through life style correction including more physical activity and healthy eating is recommended.

کلیدواژه‌ها

Metabolic Syndrome؛ Data Mining؛ Decision Tree؛ School-Age Population