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IJSTR >> Volume 8 - Issue 8, August 2019 Edition



International Journal of Scientific & Technology Research  
International Journal of Scientific & Technology Research

Website: http://www.ijstr.org

ISSN 2277-8616



A Multivariate Binary Logistic Regression Modeling for Assessing Various Risk Factors that affect Diabetes

[Full Text]

 

AUTHOR(S)

Pallavi Rastogi, B.K. Singh

 

KEYWORDS

Goodness-of-Fit, Hosmer-Lemeshow test, Logistic regression, odds ratio, ROC curve

 

ABSTRACT

This study is based on the development of multivariate logistic regression model to assess the effect of various risk factors like age, BMI, meal-regularity and fast-food consumption on the prevalence of diabetes spatially in urban and rural areas of India. The existence of non-multicollinearity, non-normality and non-linearity between the variables was studied. The test-of-association showed that age, BMI and fast-food were significantly associated with diabetes in rural(p<0.05). While, age and BMI were found to be associated with diabetes in urban area. The Wald test and Odds ratio (OR>1)showed that age and BMI were significant predictors of diabetes. The intake of fast-food has 4.08 times more effect on diabetes than those who do not take. Similarly, the persons with regular nutritional diet were at low risk of getting diabetic. The area under the ROC curve showed the better performance of the model. Hence, the developed logistic regression model can be a powerful statistical technique for identifying the association of most prominent risk factor to diabetes and thus timely notify to take needful actions to reduce the risk of getting diabetes.

 

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