The Rationale/Design of the Guimarães/Vizela Study: A Multimodal Population-Based Cohort Study to Determine Global Cardiovascular Risk and Disease

BACKGROUND: Cardiovascular disease and dementia are growing medical and social problems in aging societies. Appropriate knowledge of cardiovascular disease and cognitive decline risk factors (RFs) are critical for global CVR health preventive intervention. Many epidemiological studies use case definition based on data collected/measured in a single visit, a fact that can overestimate prevalence rates and distant from clinical practice demanding criteria. Portugal displays an elevated stroke mortality rate. However, population's global CV risk characterization is limited, namely, considering traditional/nontraditional RF and new intermediate phenotypes of CV and renal disease. Association of hemodynamic variables (pulse wave velocity and central blood pressure) with global CVR stratification, cognitive performance, and kidney disease are practically inexistent at a dwelling population level. STUDY DESIGN AND METHODS: After reviewing published data, we designed a population-based cohort study to analyze the prevalence of these cardiovascular RFs and intermediate phenotypes, using random sampling of adult dwellers living in 2 adjacent cities. Strict definition of phenotypes was planned: subjects were observed twice, and several hemodynamic and other biological variables measured at least 3 months apart. RESULTS: Three thousand thirty-eight subjects were enrolled, and extensive data collection (including central and peripheral blood pressure, pulse wave velocity), sample processing, and biobank edification were carried out. One thousand forty-seven cognitive evaluations were performed. CONCLUSIONS: Seeking for CV risk reclassification, early identification of subjects at risk, and evidence of early vascular aging and cognitive and renal function decline, using the strict daily clinical practice criteria, will lead to better resource allocation in preventive measures at a population level.