استفاده از مدل رگرسیون لجستیک در مدل بندی داده های چاقی و اضافه وزنی

عنوان انگليسی

Using Multinomial Logistic Regression for modeling obesity and overweight among people in urban area of Ardabil city, Ardabil, Iran

خلاصه انگلیسی

Introduction: Overweight and obesity are defined as abnormal or excessive fat accumulation that may impair health and increase the risk of more diseases in future. Body mass index (BMI) is a good method for measure the overweight and obesity and waist to hip ration is a good index for measure the abdominal obesity. Methods: This cross-sectional study was done on 1316 people who selected randomly from Ardabil city. Demographic data and anthropometric parameters such as age, sex, height, weight, waist circumference and hip circumference were measured by interviewers. Data were analyzed by statistical methods such as t-test, chi-square test, Pearson correlation and multinomial logistic regression model in SPSS version 21. Results: The mean age of the people was 28.5±7.4 years of them, 63.1% were in age group 20-30 years. The mean height of the samples was 162.7±8.6 cm in range 110-194 and the mean weight of them was 68.9±11.7 kg in range 43-111. The mean BMI of patients was 25.7. According to BMI, 35.6% of all samples had overweight and 18.6% had obesity. According to the WHR, 28.1% of male and 22.1% of female had high WHR (abdominal obesity). The prevalence of abdominal obesity based WHR was 25.2%. Conclusions: By using Multinomial Logistic Regression we showed that the relation between BMI and Age was positive and significant and by increasing one year at age of people, the rate of overweight increased 13% and the rate of obesity increased 17% in compare with normal patients.

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