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:: Volume 23, Issue 3 (خرداد و تیر 1400) ::
Koomesh 1400, 23(3): 402-408 Back to browse issues page
Predictive factors of glycosylated hemoglobin using additive regression model
Hamzeh Zangeneh , Mehdi Omidi , Marzieh Hadavi , Hossein Seidekhani , Kourosh Sayehmiri
Abstract:   (1991 Views)
Introduction: Diabetes is a chronic disease, non-epidemic disease that costs a lot of money in each year. One of the diagnostic criteria for diabetes is Glycosylated Hemoglobin (HBA1C), which in this study the effective factors on it examined by additive regression model. Materials and Methods: In this cross-sectional study, 130 patients with diabetes type-2 were selected based on simple random sampling in Ilam city (Iran). Several variables were examined such as gender, age, weight, height, systolic and diastolic blood pressure, hypertension, smoking, family history of diabetes, daily walking for at least 30 minutes, waist and hip circumferences, HbA1c, fasting blood sugar (FBS), RBC mean corpuscular volume (MCV) and BMI. The data were collected based on Canadian diabetes checklist questionnaire. Results: In simple linear regression, waist and hip circumferences and in multiple regression, hip circumference and BMI had a significant effect on HBA1C (P
Keywords: Diabetes Mellitus, Glycated Hemoglobin A, Body Mass Index, Waist Circumference, Regression Analysis
Full-Text [PDF 761 kb]   (624 Downloads)    
Type of Study: Research | Subject: General
Received: 2020/08/12 | Accepted: 2020/11/25 | Published: 2021/05/9
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Zangeneh H, Omidi M, Hadavi M, Seidekhani H, Sayehmiri K. Predictive factors of glycosylated hemoglobin using additive regression model. Koomesh 1400; 23 (3) :402-408
URL: http://koomeshjournal.semums.ac.ir/article-1-6545-en.html


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Volume 23, Issue 3 (خرداد و تیر 1400) Back to browse issues page
کومش Koomesh
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