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Sex and population differences in the cardiometabolic continuum: a machine learning study using the UK Biobank and
Daniela Polessa Paula1,2, Marina Camacho3, Odaleia Barbosa4
1National School of Statistical Sciences, Brazilian Institute of Geography and Statistics, Rio de Janeiro, Brazil. danielapopaula@gmail.com.
Insights
This study reveals significant sex differences in the cardiometabolic continuum (CMC), highlighting varied disease progression patterns between men and women across UK and Brazilian populations. Public health strategies should prioritize women
Area of Science:
- Cardiology
- Endocrinology
- Public Health
- Data Science
Background:
- The cardiometabolic continuum (CMC) describes the temporal sequence of cardiometabolic diseases (CMDs) arising from complex gene-environmental interactions and lifestyle factors.
- While physiological links between metabolic and cardiovascular diseases are known, sex and population-specific differences in the CMC remain understudied.
Purpose of the Study:
- To develop a machine learning model for the CMC.
- To investigate sex and population-specific differences in CMC patterns using UK Biobank and ELSA-Brasil cohorts.
Main Methods:
- Utilized k-means clustering to identify CMC patterns based on disease occurrence timing.
- Employed random forest classifiers and SHAP methodology to analyze clinical, sociodemographic, and lifestyle predictors.
- Analyzed data from 17,700 UK Biobank participants and 7,162 ELSA-Brasil participants.
Main Results:
- Identified five CMC patterns: Early Hypertension, First Diabetes, First Heart Disease, Healthy, and Late Hypertension.
- Observed distinct sex distributions within CMC patterns across cohorts, with UK women more often in the 'Healthy' cluster and men in others.
- Found earlier onset of isolated hypertension in women (UK Biobank) and a shorter time from diabetes to hypertension in women (ELSA-Brasil).
- Identified key predictors like smoking and education for both sexes, with ethnicity and coffee/alcohol consumption showing sex-specific importance.
Conclusions:
- Significant sex differences exist in the CMC, varying between UK and Brazilian populations.
- Women, particularly in Brazil, face greater disadvantages in disease incidence and onset time.
- Results underscore the need for tailored public health policies to address CMD progression, with a focus on women's health.
Background:
The temporal relationships across cardiometabolic diseases (CMDs) were recently conceptualized as the cardiometabolic continuum (CMC), sequence of cardiovascular events that stem from gene-environmental interactions, unhealthy lifestyle influences, and metabolic diseases such as diabetes, and hypertension. While the physiological pathways linking metabolic and cardiovascular diseases have been investigated, the study of the sex and population differences in the CMC have still not been described.
Methods:
We present a machine learning approach to model the CMC and investigate sex and population differences in two distinct cohorts: the UK Biobank (17,700 participants) and the Brazilian Longitudinal Study of Adult Health (ELSA-Brasil) (7162 participants). We consider the following CMDs: hypertension (Hyp), diabetes (DM), heart diseases (HD: angina, myocardial infarction, or heart failure), and stroke (STK). For the identification of the CMC patterns, individual trajectories with the time of disease occurrence were clustered using k-means. Based on clinical, sociodemographic, and lifestyle characteristics, we built multiclass random forest classifiers and used the SHAP methodology to evaluate feature importance.
Results:
Five CMC patterns were identified across both sexes and cohorts: EarlyHyp, FirstDM, FirstHD, Healthy, and LateHyp, named according to prevalence and disease occurrence time that depicted around 95%, 78%, 75%, 88% and 99% of individuals, respectively. Within the UK Biobank, more women were classified in the Healthy cluster and more men in all others. In the EarlyHyp and LateHyp clusters, isolated hypertension occurred earlier among women. Smoking habits and education had high importance and clear directionality for both sexes. For ELSA-Brasil, more men were classified in the Healthy cluster and more women in the FirstDM. The diabetes occurrence time when followed by hypertension was lower among women. Education and ethnicity had high importance and clear directionality for women, while for men these features were smoking, alcohol, and coffee consumption.
Conclusions:
There are clear sex differences in the CMC that varied across the UK and Brazilian cohorts. In particular, disadvantages regarding incidence and the time to onset of diseases were more pronounced in Brazil, against woman. The results show the need to strengthen public health policies to prevent and control the time course of CMD, with an emphasis on women.
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