This project aims to segment a sample population based on demographic info and health metrics. This is then used to determine which segments of the population are more susceptible to diabetes and pre-diabetes. The key finding is that irrespective of the clustering algorithm, we always find a cluster of individuals that are younger and healthier than the other clusters, and with higher income and education. This is the cluster that has the lowest occurrence of pre-diabetes or diabetes.
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Cluster analysis of population based on demographic and health data. Clusters then used to determine which have a higher instance of diabetes.
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