Causes and consequences of cardiovascular health variation across the lifecourse

Cardiovascular diseases (CVDs) are the leading cause of worldwide mortality. Epidemiological studies have provided evidence for relationships between an adverse cardiovascular profile throughout the lifecourse and mortality from all causes, CVDs, diabetes and many cancers. Furthermore, cardiovascula...

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Bibliographic Details
Main Author: Wade, Kaitlin Hazel
Published: University of Bristol 2015
Subjects:
Online Access:http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.690898
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Summary:Cardiovascular diseases (CVDs) are the leading cause of worldwide mortality. Epidemiological studies have provided evidence for relationships between an adverse cardiovascular profile throughout the lifecourse and mortality from all causes, CVDs, diabetes and many cancers. Furthermore, cardiovascular health can be altered by both genetic and environmental factors at different stages of the lifecourse, where early life may be of particular importance for reducing the risk of adverse cardiovascular outcomes in later life. Within this thesis, I aimed to characterise cardiovascular health as a complex phenotype, distinguishing between BP (often measured within large cohort studies) and more detailed measures of peripheral and central vascular function and structure, with the aim of determining if BP is a good proxy for overall cardiovascular health. I aimed to assess the associations of genetic variation and selected environmental factors throughout childhood and adolescence (specifically parental lifestyle, feeding behaviour, dietary components, cardiometabolic traits and adiposity) with later cardiovascular health. I used a variety of resources and methods to improve causal inference including large-scale prospective study designs in the Avon Longitudinal Study of Parents and Children (ALSPAC) and the Promotion of Breast feeding Intervention Trial (PRO BIT) based in Belarus and Mendelian randomisation (MR), a method utilising genetic variation to overcome limitations in observational studies, such as confounding, bias and reverse causation.