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

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.

Methods

Hypertensive individuals were newly diagnosed during 6,000 person-years, and normotensive individuals were those who, during the same time, remained without exceeding 140 mm Hg in systolic bloo

SUBMITTER: Martinez-Garcia M 

PROVIDER: S-EPMC11782138 | biostudies-literature | 2024

REPOSITORIES: biostudies-literature