Application of artificial neural network (ANN) in estimation of body mass index (BMI) based on the connection between environmental factors and physical activity
Date
2012
Authors
Hoseini, S.H.
Soltani, A.
Pourahmadi Nakhli, M.
Editors
Advisors
Journal Title
Journal ISSN
Volume Title
Type:
Journal article
Citation
International Journal of Artificial Intelligence & Applications, 2012; 3(4):107-115
Statement of Responsibility
Conference Name
Abstract
One of the main concerns of people in modern societies is increasing the Body Mass Index (BMI) level. BMI, in fact, can be considered as an indicator of overall health condition. Genetic aspects aside, the BMI level is affected by different factors, such as socio-economic, environmental, and physical activity level.This study investigated the effect of different factors on the BMI level of a sample population of 470 adults of three residential neighbourhoods in Shiraz, Iran. The Pearson correlation test, independent sample Ttestand One Way ANOVA were used to extract the variables which significantly influenced the BMI. The statistical analysis showed that despite the apparent association of BMI with physical activity level, it is influenced by several factors such as age, residence record, number of children, distance to bus or taxi stop, indoor or sport exercise. Then, an Artificial Neural Network (ANN) was applied to predict the level of personal BMI. The results of this analysis showed that the generalized estimating ANN model was satisfactory in estimating the BMI based on the introduced pattern
School/Discipline
Dissertation Note
Provenance
Description
Access Status
Rights
Copyright 2012 A I R C C Publishing Corporation
Access Condition Notes: This is an open access article