Mexican socio-demographic risk factors analysis in type 2 diabetes mellitus through data science

Abstract

Diabetes mellitus is an alarming problem worldwide with various negative impacts inherent to the multidimensional complexity of its nature. In particular, although it is preventable, type 2 diabetes mellitus afflicts 90% of the total diabetic population. The speed with which this preventable disease is deteriorating society, overloading health systems, draining health budgets and finally slowing economic growth, has led to its being considered one of the main health emergencies of the 21st century, and to it becoming an area of significant research attention. In Mexico, efforts to address the alarming calls launched worldwide to prevent type 2 diabetes mellitus are still underway. In particular, national studies have not yet integrated multidisciplinary techniques of data science into their analysis methodology, leaving an opportunity gap open for the process of knowledge extraction. This work addresses this gap by presenting a multidisciplinary study that integrates data science tools for the national study of type 2 diabetes mellitus. The study reveals implicit, non-trivial, unknown and potentially useful patterns of information in the national study of type 2 diabetes mellitus, its main associated health variables and its socio-demographic profile. The results obtained present quality information that could be used to manage and support effective strategies to combat the prevalence of type 2 diabetes mellitus in Mexico.