On the Study of Clear Causal Risk Factors of Diabetes Mellitus Using Multiple Regression

Ibrahim Abubakar Sadiq *

Department of Statistics, Ahmadu Bello University, Zaria, Nigeria. and Department of Mathematics and Statistics, Mewar University, Rajasthan, India.

Kode Komali

Department of Mathematics and Statistics, Mewar University, Rajasthan, India.

*Author to whom correspondence should be addressed.


Abstract

The incurable lingering metabolic syndrome of diabetes mellitus is an up-surging global tricky with tremendous physical, social, mental, economics and health undesired ramifications. Three hundred and ninety four diabetic patients were measured on 4 baseline variable age (years), sex (Male=1 and Female=2), body mass index (kg/m2) and blood pressure (mmHg). Blood sugar concentration (mg/dl) represented the response variable. The basic objective of this study is to verify the clear causal risk factors of diabetes. Both Multiple Linear Regression and Stepwise Regression techniques were applied on the data and the analysis showed that Body Mass Index (kg/m2) and Blood Pressure (mmHg) are the clearest risk factors of diabetes. This justification served the same purpose in the procedure of variables selection used.

Keywords: Multiple linear regression, stepwise regression techniques, diabetes, baseline variable, risk factor, SPSS.


How to Cite

Sadiq, Ibrahim Abubakar, and Kode Komali. 2020. “On the Study of Clear Causal Risk Factors of Diabetes Mellitus Using Multiple Regression”. Asian Journal of Probability and Statistics 9 (4):29-47. https://doi.org/10.9734/ajpas/2020/v9i430233.

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