Machine learning analysis of emerging risk factors for early-onset hypertension in the Tlalpan 2020 cohort.

Journal: Frontiers in cardiovascular medicine
Published Date: Jan 17, 2025

Abstract

INTRODUCTION: Hypertension is a significant public health concern. Several relevant risk factors have been identified. However, since it is a complex condition with broad variability and strong dependence on environmental and lifestyle factors, current risk factors only account for a fraction of the observed prevalence. This study aims to investigate the emerging early-onset hypertension risk factors using a data-driven approach by implementing machine learning models within a well-established cohort in Mexico City, comprising initially 2,500 healthy adults aged 18 to 50 years.

Authors

  • Mireya Martínez-García
    Department of Immunology, Instituto Nacional de Cardiología Ignacio Chávez, México City, México.
  • Guadalupe O Gutiérrez-Esparza
    Investigadora por México CONAHCYT Consejo Nacional de Humanidades, Ciencias y Tecnologías, México City, México.
  • Manlio F Márquez
    Diagnostic and Treatment Division, Instituto Nacional de Cardiología Ignacio Chávez, México City, México.
  • Luis M Amezcua-Guerra
    Department of Immunology, Instituto Nacional de Cardiología Ignacio Chávez, México City, México.
  • Enrique Hernández-Lemus
    Computational Genomics Division, Instituto Nacional de Medicina Genómica, México City, México.

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