Scientific rationale:
Chronic metabolic diseases constitute a group of conditions primarily characterised by metabolic abnormalities, including hypertension, diabetes, hyperlipidaemia, metabolic syndrome, gout, polycystic ovary syndrome (PCOS) and other associated complications. Nowadays, chronic metabolic diseases have become a major challenge to global health.
Chronic metabolic diseases are influenced by multiple factors. Although existing research has indicated that traditional factors such as age, environment, and lifestyle exert significant influence on the occurrence and progression of chronic metabolic diseases, the combined role of multiple factors in their development and prognosis remains insufficiently elucidated.
Objectives:
To investigate the impact of individual physiological factors, psychological factors, genetic factors, dietary data, and lifestyle on chronic metabolic diseases and their prognosis.
Research questions:
In this study, we will use data from the UK Biobank, including baseline questionnaire data (e.g., lifestyle, dietary data and sociodemographic information), genomic data, physical measurements, blood biochemical indicators, metabolic biomarkers and clinical data (e.g., records of medical history, cardiovascular and cerebrovascular complications, and mental disorders). We propose employing multiple statistical methodologies to investigate risk factors for chronic metabolic diseases and their association with prognosis using complex multi-modal data, as well as trying to develop predictive models for personalised management.
This study will provide a basis for relevant health management and policy formulation, and can be applied to comprehensive clinical management, such as through lifestyle management, nutritional dietary management, etc. to prevent disease progression and reduce the occurrence of complications.
