Standardised and Objective Dietary Intake Assessment Tool (SODIAT) : Protocol of a dual-site dietary intervention study to integrate dietary assessment methods

INTRODUCTION: Current dietary assessment methods struggle to accurately capture individuals' dietary habits. The 'Standardised and Objective Dietary Intake Assessment Tool' (SODIAT)-1 study aims to assess the effectiveness of three emerging technologies (urine and capillary blood biomarkers, wearable camera technology) and two online self-reporting dietary assessment tools to monitor dietary intake.METHODS: This randomised controlled crossover trial was conducted at two sites (Hammersmith Hospital and the University of Reading) and aimed to recruit 30 UK participants (aged 18-70 years, BMI 20-30 kg/m 2). Exclusion criteria included recent weight change, food allergies/intolerances, restrictive diets, certain health conditions and medication use. Volunteers completed an online screening questionnaire via REDCap and eligible participants attended a pre-study visit. Participants consumed, in a random order, two highly-controlled diets (compliant/non-compliant with UK guidelines) for four consecutive days, separated by at least one-week. Dietary intake was monitored daily using wearable cameras and self-recorded using Intake24 (24HR). Two versions of the online eNutri FFQ were completed: at baseline to assess habitual diet and on day 4 of each test period to record food intake. Urine and capillary blood samples were collected for biomarker analysis. Data analysis will assess dietary reporting accuracy across these methods using Lin's concordance correlation coefficient. DISCUSSION AND ETHICAL CONSIDERATIONS: The SODIAT project introduced a novel approach to dietary assessment, aiming to address the limitations like misreporting and inclusivity. However, challenges persist, such as variability in biomarker data due to failure to follow sample storage requirements and the practicalities of wearing cameras throughout the day. To protect privacy, participants removed cameras at inappropriate times, and AI removed non-food related images and blurred faces/device screens captured on the images. The accuracy of the tools in a highly-controlled setting will be evaluated in this study. Future studies are planned to validate these tools further in free-living and minority populations.