Diversity and Representation in Cardiovascular Research
Evidence Gaps, Emerging Models, and Policy Implications
Bibliographic Data
| ID | 15466927 |
|---|---|
| Authors | Simran Grewal (0000-0002-7377-8740, OLVG), James E Wildish (Glasgow School of Art), James Wildish (0009-0007-2475-4391, Department of Research, The Original Fit Factory, Glasgow G62 7LW, UK), Catherine Chalmers (Glasgow School of Art), Christine Dedding (0000-0003-3296-4245, Vrije Universiteit Amsterdam), Jeanine Suurmond (0000-0001-6872-2067, Radboud University Nijmegen), Charles Agyemang (0000-0002-3882-7295, Johns Hopkins University), Nimrat Grewal (0000-0001-9981-8336, Yale New Haven Hospital, corresponding author) |
| Year | 2026 |
| Volume | 23 |
| Issue | 2 |
| Pages | 241-241 |
| Publication date | 2026-02-14 |
| Open Access | Yes |
| Type | ARTICLE |
| Venue | International Journal of Environmental Research and Public Health (JOURNAL) |
| Journal identifiers | ISSN: 1661-7827 • E-ISSN: 1660-4601 |
| Publisher | Multidisciplinary Digital Publishing Institute (PUBLISHER • CH) |
| DOI | 10.3390/ijerph23020241 |
| PMID | 41752323 |
| OpenAlex | W7128925253 |
| Language | EN |
| References cited | 115 |
Although cardiovascular disease (CVD) is the leading cause of mortality globally, it remains insufficiently understood in large parts of the world. The scientific foundations underpinning CVD risk prediction, diagnostics, and treatment are extensively derived from homogenous datasets, primarily including White, male participants from high-income countries. This lack of diversity and inclusion can lead to biased evidence, which in turn contributes to reduced diagnostic accuracy and the under-representation of key populations, and ultimately limits the generalizability of trial results and guidelines. In this paper, we discuss that diversity in cardiovascular data is a scientific necessity for valid and globally applicable knowledge and not just a matter of fairness. Drawing from emerging initiatives in genomics, digital health, and participatory research, we propose a global roadmap to reshape how cardiovascular research is conducted. This includes strategies such as data donation frameworks, inclusive biobanking, equitable AI development, and international policy change. Only by integrating diversity into scientific methodologies can we ensure that cardiovascular guidelines are effective, inclusive, and just
Citizen journalism · Disease · Diversity (politics · Generalizability theory · Generalization · Inclusion (mineral · Representation (politics · Underpinning · Acute Myocardial Infarction Research · Cardiovascular Health and Risk Factors · Sex and Gender in Healthcare
Barriers to recruiting underrepresented populations to cancer clinical trials
Comparison of Sociodemographic and Health-Related Characteristics of UK Biobank Participants With Those of the General Population
Grand Challenges in Global Health
Cohort Profile
Human Demographic History Impacts Genetic Risk Prediction across Diverse Populations
Prediction of Coronary Heart Disease Using Risk Factor Categories
The Care Principles for Indigenous Data Governance
Estimating the burden of cardiovascular risk in community dwellers over 40 years old in South Africa, Kenya, Burkina Faso and Ghana
Fostering better science by releasing biomedical research and innovation from the grip of rich nations
Racial differences in laboratory testing as a potential mechanism for bias in AI
Learning from the Brazilian Community Health Worker Model in North Wales
Development of the Jackson Heart Study Coordinating Center
Feasibility of community-based screening for cardiovascular disease risk in an ethnic community
What types of interventions generate inequalities? Evidence from systematic reviews
Cardiovascular risk prediction tools for populations in Asia
Collaboration for transformation
Addressing Global Data Sharing Challenges
Narratives of research collaboration for sustainability at the global science-policy interface
Building a systems-thinking community workforce to scale action on determinants of health in New Zealand
Hypertension in a Brazilian Urban Slum Population
When Science Became Western
| Highly cited | No |
|---|