AUTHOR=Cruces-Salguero Sara , Larrañaga Igor , Mar Javier , Matheu Ander 

TITLE=Descriptive and predictive analysis identify centenarians' characteristics from the Basque population

JOURNAL=Frontiers in Public Health

VOLUME=Volume 10 - 2022

YEAR=2023

URL=https://www.frontiersin.org/journals/public-health/articles/10.3389/fpubh.2022.1096837

DOI=10.3389/fpubh.2022.1096837

ISSN=2296-2565

ABSTRACT=Centenarians exhibit extreme longevity and have been postulated, in some circumstances, as a model for healthy aging. The identification of the characteristics of centenarians might be useful to understand the process of human aging. In this retrospective study, we took advantage of demographic, clinical, biological and functional data of deceased individuals between 2014 and 2020 in Guipúzcoa (Basque Country, Spain) taken from Basque Health Service electronic health records data lake. 50 characteristics derived from demographic, clinical, pharmaceutical, biological and functional were studied in the descriptive analysis and compared through difference in means tests. 27 of them were used to build machine learning models in the predictive analysis and their relevance for classifying centenarians was assessed. Most centenarians were women and lived in nursing home. Importantly, they developed fewer diseases, took fewer drugs, and required fewer medical attendances. They also showed better biological profiles, exhibiting lower levels of glucose, hemoglobin, glycosylated hemoglobin, and triglycerides in blood analysis. Additionally, machine learning analyses revealed the profiles associated to centenarian´s status being woman, having fewer consultations, fewer diagnoses of neoplasms, and lower levels of hemoglobin the main characteristics. Our results identified the main characteristics associated to centenarian population in the Basque Country using Computational Biology programs. These results expand the knowledge on the characterization of centenarian population and hence of human longevity.