Mining Medical Data Toward a More Equitable Health System for the Public

The aim of this study is to identify predictors of different sleep disorders which are less studied within the field. With sleep disorders affecting the overall well being of millions of individuals worldwide this is an important examination of potential factors which can lead to the development of such disorders. A relational database was constructed using MySql and Python in order to perform multiple different statistical analyses on data provided by the National Health and Nutrition Examination Survey (NHANES) dataset. Correlations and predictions between described sleep disorders and different physiological factors described within the dataset were found to establish conclusions as to which lesser explored factors are the most related in an individual developing such disorders. The contribution this work has on the field is identifying potential pitfalls of research being conducted in order to potentially provide better care for patients. Such patients can either be those who already hold a sleep disorder diagnosis or those who hold the factors identified within this study that were proven to have strong relations to the development of a sleep disorder.