HWBI: Health and Well-Being Index: A neural network based index which quantifies the cumulative impact of lifestyle habits on personal health and well-being and demonstration of its application in managing the risk of diabetes

摘要

In this era of epidemiological transition, effective maintenance of personal lifestyle is touted as a sustainable strategy to minimize the risk of contracting lifestyle related diseases. Understanding of the cumulative impact of multiple lifestyle habits on overall health can be cognitively challenging for an individual. Therefore, to simplify this conundrum, we present a neural network based HWBI, which helps the person understand the impact of lifestyle interventions/habits upon his overall health and well-being. We argue that a neural network based approach captures the inter-relationship between the various lifestyle factors better than a multivariate regression model and outputs a holistic health and well-being index. We further validate the utility of HWBI in estimating the risk of diabetes for different age groups. Based on the results of the inter-relationship between HWBI and risk of diabetes, we assert that such an approach could be investigated for other lifestyle related diseases in which a lifestyle index can be explored to model disease risks. This provides a future prospect to quantitatively measure, monitor and manage the health of the individual based on his lifestyle and hence, of the community.