Skip navigation

Estimating trends in cardiovascular disease risk for the EXPOSE (Explaining Population Trends in Cardiovascular Risk: a comparative analysis of health transitions in South Africa and England) study: repeated cross-sectional study

Estimating trends in cardiovascular disease risk for the EXPOSE (Explaining Population Trends in Cardiovascular Risk: a comparative analysis of health transitions in South Africa and England) study: repeated cross-sectional study

Scholes, Shaun, Mindell, Jennifer S, Toomse-Smith, Mari, Cois, Annibale and Adjaye-Gbewonyo, Kafui ORCID logoORCID: https://orcid.org/0000-0002-8919-6518 (2025) Estimating trends in cardiovascular disease risk for the EXPOSE (Explaining Population Trends in Cardiovascular Risk: a comparative analysis of health transitions in South Africa and England) study: repeated cross-sectional study. JMIR Cardio, 9:e64893. ISSN 2561-1011 (Online) (doi:10.2196/64893)

[thumbnail of Open Access Article]
Preview
PDF (Open Access Article)
49486 ADJAYE-GBEWONYO_Estimating_Trends_In_Cardiovascular_Disease_Risk_For_The_EXPOSE_(OA)_2025.pdf - Published Version
Available under License Creative Commons Attribution.

Download (841kB) | Preview

Abstract

Background: Cardiovascular diseases (CVDs) are the leading cause of death globally. Demographic, behavioral, socioeconomic, health care, and psychosocial variables considered risk factors for CVD are routinely measured in population health surveys, providing opportunities to examine health transitions. Studying the drivers of health transitions in countries where multiple burdens of disease persist (eg, South Africa), compared with countries regarded as models of “epidemiologic transition” (eg, England), can provide knowledge on where best to intervene and direct resources to reduce the disease burden.
Objective: The EXPOSE (Explaining Population Trends in Cardiovascular Risk: A Comparative Analysis of Health Transitions in South Africa and England) study analyzes microlevel data collected from multiple nationally representative population health surveys conducted in these 2 countries between 1998 and 2017. Creating a harmonized dataset by pooling repeated cross-sectional surveys to model trends in CVD risk is challenging due to changes in aspects such as survey content, question wording, inclusion of boost samples, weighting, measuring equipment, and guidelines for data protection. This study aimed to create a harmonized dataset based on the annual Health Surveys for England to estimate trends in mean predicted 10-year CVD risk (primary outcome) and its individual risk components (secondary outcome).
Methods: We compiled a harmonized dataset to estimate trends between 1998 and 2017 in the English adult population, including the primary and secondary outcomes, and potential drivers of those trends. Laboratory- and non–laboratory-based World Health Organization (WHO) and Globorisk algorithms were used to calculate the predicted 10-year total (fatal and nonfatal) CVD risk. Sex-specific estimates of the mean 10-year CVD risk and its components by survey year were calculated, accounting for the complex survey design.
Results: Laboratory- and non–laboratory-based 10-year CVD risk scores were calculated for 33,628 and 61,629 participants aged 40 to 74 years, respectively. The absolute predicted 10-year risk of CVD declined significantly on average over the last 2 decades in both sexes (for linear trend; all P<.001). In men, the mean of the laboratory-based WHO risk score was 10.1% (SE 0.2%) and 8.4% (SE 0.2%) in 1998 and 2017, respectively; corresponding figures in women were 5.6% (SE 0.1%) and 4.5% (SE 0.1%). In men, the mean of the non–laboratory-based WHO risk score was 9.6% (SE 0.1%) and 8.9% (SE 0.2%) in 1998 and 2017, respectively; corresponding figures in women were 5.8% (SE 0.1%) and 4.8% (SE 0.1%). Predicted CVD risk using the Globorisk algorithms was lower on average in absolute terms, but the pattern of change was very similar. Trends in the individual risk components showed a complex pattern.
Conclusions: Harmonized data from repeated cross-sectional health surveys can be used to quantify the drivers of recent changes in CVD risk at the population level.

Item Type: Article
Additional Information: Preprints (earlier versions) of this paper are available at https://preprints.jmir.org/preprint/64893, first published August 01, 2024.
Uncontrolled Keywords: data harmonization, cardiovascular disease, CVD, CVD risk scores, trends, cross-country comparisons, public health, England, South Africa
Subjects: Q Science > Q Science (General)
R Medicine > R Medicine (General)
Faculty / School / Research Centre / Research Group: Faculty of Education, Health & Human Sciences
Faculty of Education, Health & Human Sciences > Institute for Lifecourse Development
Faculty of Education, Health & Human Sciences > Institute for Lifecourse Development > Centre for Chronic Illness and Ageing
Related URLs:
Last Modified: 21 Jan 2025 15:07
URI: http://gala.gre.ac.uk/id/eprint/49486

Actions (login required)

View Item View Item

Downloads

Downloads per month over past year

View more statistics