Using primary and routinely collected data to determine the prevalence of cardiovascular-kidney-metabolic syndrome in rural China

Abstract Background Cardiovascular-Kidney-Metabolic (CKM) syndrome is a complex health condition caused by the interactions between cardiovascular diseases, kidney diseases, and metabolic disorders. These interactions result in multi-organ dysfunction and significantly increase the risk of adverse cardiovascular events. Despite its health-related consequences, studies using robust data to understand CKM syndrome in resource-limited rural areas in China are lacking. Purpose This study aims to comprehensively determine the prevalence of CKM syndrome in a representative rural population in China, using multiple data sources, including primary data (questionnaire, physical examination and blood collection) and routinely collected data. Methods This cross-section study was conducted across three provinces in China, with two counties per province and 40 villages per county, totaling 240 villages. Twenty-five participants were randomly selected and stratified by sex and age. CKM syndrome was defined as the co-occurrence of cardiovascular diseases (including high blood pressure, high cholesterol, stroke, and heart disease), chronic kidney disease, and metabolic disorders (including diabetes, overweight and high triglyceride). Data were collected through face-to-face questionnaire, physical examinations, fasting blood samples and routinely collected data (health insurance claims and hospital electronic records). The study compared the prevalence of multiple CKM patterns based on either (1) self-reported history of diseases from face-to-face questionnaire and disease diagnosis from routinely collected data (data source 1), or (2) supplemented by physical examinations and fasting blood tests (data source 2). Results A total of 6474 participants were included (50.9% female, mean age 57.1 years, Table). The inclusion of physical examinations and fasting blood tests significantly increased the prevalence of CKM triad patterns and all associated dyad patterns, including cardiovascular and kidney diseases (CK), kidney and metabolic disorders (KM) and cardiovascular and metabolic disorders (CM). The prevalence of CKM rose from 0.88% with data source 1 to 8.77% with data source 2 (Figure). Among the dyad patterns, CM showed the greatest increase in prevalence (from 7.29% to 57.72%), followed by CK from 3.21% to 12.57% and KM from 0.99% to 9.44%. In addition, blood pressure measurements identified that over 40% of the participants had elevated blood pressure, while blood tests found 23.06% with high cholesterol, 21.04% with high triglyceride and 9.22% with increased risk of chronic kidney disease. Conclusion The prevalence of CKM syndrome in rural China is substantial. But gaps in early screening and diagnosis persist, particularly high blood pressure, chronic kidney disease, high cholesterol and high triglyceride. Future studies should focus on improving early screening and diagnosis for CKM syndrome in resource-constrained rural areas, to minimize health equity gaps.Table.Prevalence in subgroups  Figure.Prevalence in each combinations