University of Leeds

Academic Institute

OFHS240166

This study aims to evaluate the impact of lifestyle choices that affect the cardiovascular health of a person across their lifetime. It aims to report: (i) How common cardiovascular disease (including heart disease, stroke and other diseases of the arteries) and risk factors for cardiovascular disease are in Our Future Health (OFH) participants, both at the start and during the study. (ii) What proportion heart attacks and strokes may be due to lifestyle factors (such as cholesterol problems, smoking and obesity), allowing calculation of the proportion of cardiovascular events that may be prevented. (iii) The impact of cardiovascular risk factors on the the risk of developing cardiovascular disease by age, sex and other important characteristics. (iv) The presence of different patterns of cardiovascular risk factors present in OFH participants over time. It will also study different approaches to constructing mathematical models to predict an individual’s lifetime risk (LTR) of cardiovascular disease, and will evaluate the effects of different strategies of lowering cardiovascular risk (e.g. stopping smoking, cholesterol and blood pressure medication, weight loss) using reduction estimates available from pre-existing clinical trials. Cardiovascular disease (CVD, including coronary artery disease and stroke) remains the leading cause of death globally. Over the last century, greater understanding of the pathophysiology of CVD has led to the identification of causal cardiovascular risk factors. The wealth of linked data available for Our Future Health enables ascertainment of a wide spectrum of these risk factors, including demographic, psychosocial, behavioural, metabolic and genetic factors (inferable from family history and genotype data). Some risk factors (including smoking, dyslipidaemia and hypertension) are modifiable through lifestyle changes and medication, whereas others (including age and genotype) are not. It is critical that finite public health resources are targeted at modifiable risk factors that lead to the greatest burden of cardiovascular disease. At present, clinical guidelines advocate a uniform approach to risk factor management for those at greatest risk. Recommendations centre around 10-year risk assessment and assume a homogenous effect of risk factors across age and sex, which is unlikely: the factors driving CVD in a 30-year-old man likely differ markedly to those in a 90-year-old woman. Targeted lifetime primary prevention approaches remain incompletely explored. This study will explore the benefits of a stratified, whole life-course strategy for the primary prevention of cardiovascular disease.

Cardiovascular disease leads to a reduced quality of life, more doctor appointments and hospital stays, and increases the risk of death at a younger age. New approaches to prevent (or delay the development of) cardiovascular disease may lead to individuals living longer, free of cardiovascular disease. We hope that the findings of this study will enable policy makers to target public health resources to risk factors in proportion with the amount of cardiovascular disease that is caused by that risk factor. Our lifetime risk models will enable clinicians to help patients make lifestyle choices that reduce their risk of cardiovascular disease that are most impactful (and appropriate) for their stage of life. This may benefit the public in a number of key ways, including: (i) reducing the number of people that develop cardiovascular disease, (ii) increasing the personalisation of cardiovascular disease prevention, minimising unnecessary treatments in those unlikely to benefit and avoiding unnecessary medication side effects, (iii) reducing healthcare costs, due to fewer cardiovascular disease-related hospital admissions, and (iv) reducing healthcare inequality (through the inclusion of socioeconomic status and ethnicity in the above models). Overall, the findings of this study will enable the optimisation of cardiovascular disease prevention-at-both-the-individual-level (by-improved-lifetime-risk-prediction)-and-population-level (by-targeting-resources-to-the-most-important-risk-factors).

Public Health Research

23/05/2025

29/01/2025

TRE