Abstract

IntroductionCardiovascular diseases (CVD) are the leading cause of death globally and share determinants with other major non-communicable diseases. Risk factors for CVD are routinely measured in population surveys and thus provide an opportunity to study health transitions. Understanding the drivers of health transitions in countries that have not followed expected paths compared with those that exemplified models of ‘epidemiologic transition’, such as England, can generate knowledge on where resources may best be directed to reduce the burden of disease. This study aims to examine the notions of epidemiological transition by identifying and quantifying the drivers of change in CVD risk in a middle-income African setting compared with a high-income European setting.Methods and analysisThis is a secondary joint analysis of data collected within the scope of multiple population surveys conducted in South Africa and England between 1998 and 2017 on nationally representative samples of the adult population. The study will use a validated, non-laboratory risk score to estimate and compare the distribution of and trends in total CVD risk in the population. Statistical modelling techniques (fixed-effects and random-effects multilevel regression models and structural equation models) will be used to examine how various factors explain the variation in CVD risk over time in the two countries.Ethics and disseminationThis study has obtained approval from the University of Greenwich (20.5.6.8) and Stellenbosch University (X21/09/027) Research Ethics Committees. It uses anonymised microdata originating from population surveys which received ethical approval from the relevant bodies, with no additional primary data collection. Results of the study will be disseminated through (1) peer-reviewed articles in open access journals; (2) policy briefs; (3) conferences and meetings; and (4) public engagement activities designed to reach health professionals, governmental bodies, civil society and the lay public. A harmonised data set will be made publicly available through online repositories.

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