Data Science & Evidence Synthesis Hub
Cardiovascular diseases (CVD), such as strokes and heart attacks, cause millions of deaths every year across the world. Timely screening for CVD risk, including identification of behavioural and clinical risk factors, such as poor diet, sedentary lifestyle, smoking and high blood pressure, for example, can contribute to reducing CVD onset and deaths.
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Diet plays a major role on CVD prevention but the complexity of foods and their components and the several pathways linking diets to CVD risk factors make disentangling the relative contribution of preventative dietary interventions a challenging task, hindering the development of more targeted approaches to promoting metabolic and cardiovascular health across the life course.
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Information from millions of research participants is collected every year, which could be used to develop and test more accurate risk estimation models to better predict and prevent CVD. The introduction of electronic health records (EHR) has created new opportunities for exploring the generalisability of risk estimates generated in research studies to real-world settings.
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Curated evidence exploring the links between diet, CVD risk factors and outcomes combined with research and real-world data can pave the way for new discoveries on CVD identification, prevention, and management.
OUR CURRENT PROJECTS
One stream of the NNEdPro Data Science Hub on Nutrition aims to harness the power of data sharing and research partnerships to support more timely and effective CVD risk identification and prevention. Aligned with NNEdPro mission to deliver education and empower professionals and policy makers, we also aim to further develop data literacy and capacity for action among relevant stakeholders in the public and private health systems.
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Research collaborators: Prof Sumantra Ray, Dr Rajna Golubic, Dr Christine Delon, Dr Federica Amati, Dr Claudia Tramontt, Dr Marjorie Lima do Vale, Sarah Armes, Xunhan Liu, Mayara de Paula, Ravi Mohan Lal, Ramya Rajaram, Dr Saad Mouti, Dr Jeffrey Bohn, Nate Jansen, Dr Adam Strange, Dr Christoph Nabholz, Doug Rix, Daniel Meyer, Dr John Schoonbee, Dr Elango Vijaykumar, Dr Vipan Bhardwaj
Objectives
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Use traditional regression models as well as innovative tools from causal inference to interrogate research and clinical datasets to disentangle the relative importance of behavioural and clinical risk factors and markers for CVD risk and total mortality and inform innovations in public and private health policies.
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Provide bespoke training and collaboration opportunities to strengthen data and research literacy and capacity amongst health professionals and decision makers to support surveillance, service innovation and research.
Research outputs
2022
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​8th International Summit on Empowering Global Nutrition with Digital Technology
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Pre-Summit Satellite Event: Cardiometabolic Health: From Digital Data Science to Human Interventions
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Building a holistic view of health: a deep-dive into diabetes in Asia (webinar delivered by Dr Adam Strange)
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Investigating cardiometabolic risk factors in the Biobank data: Preliminary baseline models on total mortality and CVD mortality (webinar delivered by Dr Christine Delon)
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Peer-reviewed publication
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Tramontt, C.R. et al., (2022). The mediated effects of adiposity and glycaemia on low carbohydrate diets and markers of CVD risk: findings from the UK National Diet and Nutrition Survey (NDNS) 2008–2016. (Under review)
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2021
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7th International Summit on Nutrition and Health
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Pre-Summit Satellite Event: A holistic view on health resilience, from the environment to nutrition (webinar delivered by Dr Jeffrey Bohn and Dr Christoph Nabholz)
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Peer-reviewed publications
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Lima do Vale, M. R. et al., (2021). A synthesis of pathways linking diet, metabolic risk and cardiovascular disease: a framework to guide further research and approaches to evidence-based practice. Nutrition research reviews, 1–27. Advanced online publication. https://doi.org/10.1017/S0954422421000378
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Buckner, L. et al., (2021). The Association between Dietary Quality and Behaviours with Novel Cardiovascular Risk Biomarkers in the NSHD cohort (in preparation).
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2020
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6th International Summit on Medical Nutrition Education and Research.
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Pre-Summit Satellite Event: Causal Inference – Results and Next Steps (webinar delivered by Dr Jeffrey Bohn)
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Causal Inference Workshop - When should we change our minds? (webinar delivered by Dr Jeffrey Bohn)
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Diet and Cardiometabolic Risk (webinar delivered by Prof Sumantra Ray, Dr Marjorie Vale, Nate Jensen, Dr Xiaowu Dai, and Dr Saad Mouti)
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Diet and cardiovascular disease risk: New insights for research and practice (Webinar delivered to SRI).
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5th International Summit on Medical Nutrition Education and Research.
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Causal inference: Unravelling the nutrition, longevity, & type-2 diabetes tangle (workshop by Dr Jeffrey Bohn)
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Swiss Re Institute Workshop on Causal Inference (workshop by Prof Lis Goldberg)​​​​​​
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DATA SECURITY
As part of the Data Science & Evidence Synthesis Hub procedures, we abide by any data protection regulations in the countries we work. Advanced security mechanisms that authenticate users and prevent unauthorised access to sensitive data are part of our IT safety standards. This includes a 2-step authentication process to access the data. Data integrity is maintained by optimising access to data and shareability as well as trackability of changes made.
Project Team
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Christine Delon
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Claudia Tramontt
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Federica Amati
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Marjorie Lima do Vale
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Mayara de Paula
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Rajna Golubic
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Ramya Rajaram
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Ravi Mohan Lal
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Saad Mouti
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Sarah Armes
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Sumantra Ray