Authors - SMT. DIVYASHREE D V, D RAMESH Abstract - In India, obesity has become a serious public health concern, especially in urban and semi-urban areas that are seeing fast changes in diet and lifestyle. Predictive modelling has advanced globally, but there are still very few techniques tailored to a given region that take into consideration Indi's distinct socioeconomic, environmental, and cultural context. The study is conducted from the local population in Tumkur city by creating an ANN model that predicts the obesity risk from diverse age groups. The model is built with the physiological, behavioural and environmental parameters that make deeper study to analyse the risk through multi-faceted dataset. A mobile application is developed to close the gap and monitor the obesity risk through recommendation given by interactive monitoring tool. This tool will provide the real time risk evaluations to the individuals by giving warnings and progress updates that supports health tracking for timely behavioural and physiological changes. The research mainly focusses on predicting the obesity risk, designing a mobile health monitoring tool and assessing the obesity risk by validating the hypothesis risk framework by one-way ANOVA statistical analysis on primary data on region specific.
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