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Type 2 diabetes mellitus represents a prevalent and widespread global healthconcern, necessitating a comprehensive assessment of its risk factors. Thisstudy aimed towards learning whether there is any differential impact of age,Lifestyle, BMI and Waist to height ratio on the risk of Type 2 diabetesmellitus in males and females in Kolkata, West Bengal, India based on a sampleobserved from the out-patient consultation department of Belle Vue Clinic inKolkata. Various machine learning models like Logistic Regression, RandomForest, and Support Vector Classifier, were used to predict the risk ofdiabetes, and performance was compared based on different predictors. Ourfindings indicate a significant age-related increase in risk of diabetes forboth males and females. Although exercising and BMI was found to havesignificant impact on the risk of Type 2 diabetes in males, in females bothturned out to be statistically insignificant. For both males and females,predictive models based on WhtR demonstrated superior performance in riskassessment compared to those based on BMI. This study sheds light on thegender-specific differences in the risk factors for Type 2 diabetes, offeringvaluable insights that can be used towards more targeted healthcareinterventions and public health strategies.

Gender-Based Comparative Study of Type 2 Diabetes Risk Factors in Kolkata, India: A Machine Learning Approach