Abstract
One of the main concerns of people inmodern 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 physicalactivity 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 Ttest and One Way ANOVA we re 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 ofchildren, 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 BMIbased on the introduced pattern.
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More From: International Journal of Artificial Intelligence & Applications
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