Non-alcoholic fatty liver disease affects approximately 30% of the global population, and liver fibrosis while liver fibrosis stage is considered the strongest predictor of disease-related mortality in NAFLD. Since 2023, new terminology has been implemented – metabolic dysfunction-associated steatotic liver disease (MASLD). The growing global incidence of MASLD coexists with the worldwide increase in the prevalence of overweight and obesity, which underscores the relevance of this dissertation.
The study was conducted from 2021 to 2024 and involved patients from the clinical sites of Bogomolets National Medical University: private medical centre «Universal Clinic «Oberig», Medical Laboratory “DILA” and also KNE «Kyiv Municipal Consultative and Diagnostic Center». Nutrition assessment, clinical, anthropometric, instrumental, laboratory, and statistical methods were utilized in the research. MASLD diagnosis was established according to criteria defined by the American Association for the Study of Liver Diseases (AASLD).
The aim of the study was to improve the management algorithm for patients with MASLD by assessing nutrition, body composition parameters, comorbidities, laboratory markers of nutritional status, and their relationship with liver fibrosis.
The first stage of the research involved the adaptation and validation of the EPIC-Norfolk Food Frequency Questionnaire (FFQ). The FFQ validation was conducted against the 24-hour dietary recall method (24HR). The validation process included 140 adults aged 18 years or older who provided informed consent to participate in the study. Data from 90 individuals who fully completed the FFQ and provided detailed information in the 24HR were included in the final analysis. Using Wilcoxon signed test we found a significant difference between results obtained by FFQ and 24HRs for less than 50% of nutrients. Correlations ranged from 0.0738 (retinol equivalents) to 0.458 (total energy and phosphorus), with an average correlation of 0.339. Energy-adjusted correlations ranged from 0.0733 (vitamin C) to 0.409 (carbohydrates), with an average correlation of 0.26.
The percentage of participants classified into the same quartiles ranged from 22.22% (vitamin A, as retinol equivalents) to 43.33 % (sodium), with an average of 32.5%. The percentage of participants classified into the same and adjacent quartiles ranged from 61.11% (vitamin A as retinol equivalents) to 81.11% (vitamin D), with an average of 74.2%. Gross misclassification into the opposite quartile ranged from 3.33% (magnesium) to 10% (cholesterol, vitamin A as retinol and retinol equivalents) with an average of 6.1%. After adjustment for energy intake, the percentage of participants classified into the same quartiles ranged from 17.78 % (total folate) to 40% (iron), with an average of 32.2%. The percentage of participants classified into the same and adjacent quartiles ranged from 63.32% (vitamin A, as retinol) to 81.1% (total sugars), with an average of 71.6%. Gross misclassification of more than 10% was recorded only for dietary intake of vitamin C (14.44%) and total folate (12.22%). Using the weighted kappa (ĸ), most nutrients had a fair agreement (ĸ = 0.21 – 0.40). However, the values of the weighted kappa (ĸ) for total PUFA, niacin, vitamin C, cholesterol, total folate, vitamin A as retinol and retinol equivalents, and iron were defined as poor, even after energy adjustment. We used the Bland-Altman analysis for all nutrients to assess the presence, direction, and extent of bias at the group level. The lowest values of the “bias” between the FFQ and 24HRs were observed for energy, carbohydrates, fat, vitamin B2, vitamin D, iron, and magnesium – the mean difference did not exceed 5%.
