Nutrition and body composition as risk factors of non-communicable diseases in Saudi Arabia

Background: Saudi Arabia is an affluent nation faced with steep population increase (~75% in just over 10 years) and a young population (63% aged under 30) in the context of globalized dietary habits and food supply leading to increase the trend of consumption junk food use. However, there are no national dietary surveys to give more accurate details. With existing high prevalence of obesity, it is foreseeable that Saudi Arabia (SA) will face a significant increase in the burden of non-communicable diseases (NCDs) in a short space of time. Reducing the behavioural and environmental risk factors associated with NCDs (physical activity, alcohol overuse, exposure to tobacco smoke, and low nutritionally balanced diet including high salt and energy intake and low intake of fruit and vegetables) requires cross-community sectors, including health, education, agriculture, and planning. Early detection and intervention also require reliable and cost effective tools. The relationship between chronic high salt intake and CVDs has already been established. This thesis examines the relationship between body composition and nutrition, and NCDs using techniques from the full breadth of Human Nutrition Research. Methods: The first cross-sectional study focused on developing and validating a culture-specific FFQ for salt intake against 24-h urinary outputs and repeated 24-h dietary recall, to identify relationships between salt intake, socio-economic factors and blood pressure (BP); and explore dietary sources of salt intake. In the second study, a secondary analysis of integrated data from five Saudi National Surveys assessed the performance of different anthropometric measures (body mass index (BMI), waist circumference (WC), waist to hip ratio (WHR) and waist to height ratio (WHtR)) and body composition indices (estimated skeletal muscle mass (SMM), the percentage of skeletal muscle mass to body weight (%SMM) and Skeletal Muscle Mass Index (SMI)) in predicting metabolic diseases.