Latest research unveils five key patterns in cardiometabolic disease progression

A new study from the University of Barcelona identifies five key patterns of cardiometabolic disease progression, across the UK and Brazil. The research reveals significant sex and country differences in disease onset and prevalence, underscoring the impact of education and lifestyle on disease progression. The findings highlight the need for targeted public health interventions, particularly for women, to address the varied impacts of cardiometabolic diseases across different populations. 

Understanding how diseases progress

Cardiometabolic diseases, such as diabetes, hypertension, and heart disease, are major global health challenges affecting millions of people. These conditions often develop over time and can lead to serious health complications or premature death. Understanding how these diseases progress, occur together and impact different groups of people is crucial for developing effective prevention and treatment strategies.

The study, part of the LongITools project, used a machine learning approach to study sex and population differences in the cardiometabolic continuum (CMC), The aim was to uncover distinct patterns of cardiometabolic diseases between men and women across different populations, which could help tailor public health efforts to better address the specific needs of various groups.

Exploring two extensive health datasets

The global study, which included around 25,000 participants, leveraged two extensive health datasets to explore patterns of cardiometabolic disease progression in the UK and Brazil. Both datasets used comprehensive health data, including clinical measures and self-reports to track the progression of hypertension, diabetes, heart diseases, angina, myocardial infarction, or heart failure, and stroke over time. Using a clustering algorithm, people were classified as healthy or by the diseases they developed and how early or late they developed them. Key findings included:

• Five distinct patterns of cardiometabolic disease progression were uncovered: Early Hypertension, First Diabetes, First Heart Disease, Healthy, and Late Hypertension. These patterns were consistent across the UK Biobank and the Brazilian Longitudinal Study of Adult Health (ELSA-Brasil).
• Significant differences were observed between men and women in the progression of cardiometabolic diseases.Women in the UK Biobank showed a higher likelihood of being healthy, while men were more likely to have cardiometabolic diseases.
• Women in Brazil experienced earlier onset of diabetes and hypertension compared to their UK counterparts, highlighting regional variations in disease progression and the need for localised health interventions.
• Education, smoking, and ethnicity played significant roles in disease patterns. Higher education levels were associated with better health outcomes in both cohorts, particularly in Brazil.

 Evidence to strengthen public health policies

“The research found clear sex differences in the cardiometabolic diseases that varied across the UK and Brazilian cohorts. Disadvantages regarding incidence and the time to onset of diseases were more pronounced for women in Brazil. The results show the need to strengthen public health prevention policies and control the time course of cardiometabolic disease, with an emphasis on women.”

said Marina Camacho, Researcher at the Artificial Intelligence in Medicine Lab, University of Barcelona. Marina added,

“Further research is needed to validate the findings across different populations and settings. This includes exploring additional factors that might influence disease trajectories and examining the impact of interventions based on these patterns.  Further research would also enable us to improve the accuracy of models used to predict disease trajectories, which will help better understand the complexities of cardiometabolic disease progression and refine preventive strategies.” 

This study was published in the BMC Public Health journal.

Notes to editors

Marina Camacho, Researcher at Artificial Intelligence in Medicine Lab, University of Barcelona is available for interview on request. For more information, please contact marinacamachosanz@ub.edu.

Paper

Paula, D.P., Camacho, M., Barbosa, O. et al. Sex and population differences in the cardiometabolic continuum: a machine learning study using the UK Biobank and ELSA-Brasil cohorts. BMC Public Health 24, 2131 (2024).