The development of a food-group, tree classification method and its use in exploring dietary associations with metabolic dysfunction-associated Steatotic liver disease (MASLD) and other health-related outcomes in a UK population
Amina A. Alawadi , Amrita Vijay , Jane I. Grove , Moira A. Taylor , Guruprasad P. Aithal
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引用次数: 0
Abstract
Background
Metabolic dysfunction-Associated Steatotic Liver Disease (MASLD) affects up to one in five people in the UK, with persistent overeating and a sedentary lifestyle being significant risk factors. Exploring dietary patterns at a food level is a novel approach to understand associations between diet and disease.
Methods
This cross-sectional case-control study included 168 MASLD patients and 34 healthy controls from Nottingham (UK). Dietary data were collected using the EPIC-food frequency questionnaire. A food-group, tree classification method was developed which categorized 923 ingredients into three levels (main food group, sub-types, and cooking methods) and intakes were associated with clinical outcomes using logistic regression and degree of liver fibrosis using linear regression.
Results
Significant associations were found for red meat intake with MASLD (OR [CI]: 1.013 [1.001–1.025]) and fibrosis (Beta [SE]: +0.048 [0.013]); intakes of nuts (OR [CI]: 0.951 [0.905–0.999]); and fish (OR [CI]: 0.985 [0.971–0.999]) with MASLD; “Cereals and cereals products”, “salt and gravy” and baked foods with fibrosis (Beta [SE]: +0.018 to +0.057 [0.005–0.23]); white and organ meat (Beta [SE]: −0.04 to −0.61 [0.015–0.249]); diet soda (OR [CI]: +0.01 [1–1.003]) and red meat intakes (OR [CI]:+0.002 [1.002–1.016]) with T2DM; wholegrain wheat, red meat, and semi-skimmed dairy intakes with hypercholesterolemia (ORs [CI]: −0.003 to −0.023 [1–1.043]); “herbs and spices” and wholegrain rice with hypercholesterolaemia (ORs [CI]: −0.08 to −0.98 [0.159–0.989); fresh herbs and boiled foods intakes with hypertension (ORs [CI]: −0.001 to −2.21 [0.013–1]).
Conclusion
The study introduces a new food-group, tree classification method to characterise UK diet data and identify risk factors for MASLD, potentially informing the development of culturally applicable dietary guidelines designed to improve public health.