Evidence map›Paper›PMID 39107721›Full record

ArticleBMC public health2024

Sex and population differences in the cardiometabolic continuum: a machine learning study using the UK Biobank and ELSA-Brasil cohorts.

Daniela Polessa Paula, Marina Camacho, Odaleia Barbosa, Larissa Marques, Rosane Harter Griep, Maria Jesus Mendes da Fonseca, Sandhi Barreto, Karim Lekadir

Abstract read
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Article in BMC public health, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.

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2citing papers in PubMed
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1 · What the graph read from it

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3 · Its place in the literature

Who cites it

2 citing papers in PubMed.

  1. Article
  2. Position Statement on Cardiometabolic Health Across the Woman's Life Course - 2025.Revista brasileira de ginecologia e obstetricia : revista da Federacao Brasileira das Sociedades de Ginecologia e Obstetricia · 2025
    Article
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5 · Who and what money

Authors and funding

8 authors.

Daniela Polessa PaulaNational School of Statistical Sciences, Brazilian Institute of Geography and Statistics, Rio de Janeiro, Brazil. danielapopaula@gmail.com.
Marina CamachoDepartament de Matemàtiques i Informàtica, Universitat de Barcelona, Barcelona, Spain.
Odaleia BarbosaInstitute of Nutrition, University of the Rio de Janeiro State, Rio de Janeiro, Brazil.
Larissa MarquesCoordination of Information and Communication (CINCO - PEIC), Oswaldo Cruz Foundation, Rio de Janeiro, Rio de Janeiro, Brazil.
Rosane Harter GriepHealth and Environmental Education Laboratory, Oswaldo Cruz Institute (IOC), Rio de Janeiro, RJ, Brazil.
Maria Jesus Mendes da FonsecaNational School of Public Health, Oswaldo Cruz Foundation, Rio de Janeiro, Brazil.
Sandhi BarretoPostgraduate Program in Public Health, School of Medicine & Clinical Hospital, Federal University of Minas Gerais, Belo Horizonte, Brazil.
Karim LekadirDepartament de Matemàtiques i Informàtica, Universitat de Barcelona, Barcelona, Spain.

Funding

European Union's Horizon 2020 research and innovation program 874739
6 · The paper itself

Abstract

backgroundThe 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.

methodsWe 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.

resultsFive 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.

conclusionsThere 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.

Indexed as

Cardiovascular DiseasesMachine LearningAdultAgedBrazilCardiometabolic Risk FactorsCohort StudiesFemaleHumansLongitudinal StudiesMaleMiddle AgedSex FactorsUK BiobankUnited KingdomCardiometabolic continuumCardiometabolic trajectoriesELSA-BrasilMachine learningSHAPUK Biobank

Identifiers

PMID39107721
PMCPMC11304673

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.