Advancing Dietary Assessment Methodology for Nigeria: Validation of a Web-Based Dietary Recall System Against Biomarker Reference Methods

Accurate dietary assessment in population-based nutrition research is foundational to producing reliable evidence, yet dietary assessment methods used in Nigeria have been inconsistently validated, limiting the quality and comparability of national nutrition data. This study validates a newly developed Nigerian web-based dietary recall system, NutriRecallNG, against recovery and concentration biomarkers, representing the most rigorous methodological validation standard available. The study recruited 300 adults aged 20 to 55 years from Abuja, Enugu, and Ibadan through stratified sampling. Participants completed three web-based 24-hour dietary recalls administered on non-consecutive days across a three-week period, supplemented by food photographic documentation. Recovery biomarkers used for validation included doubly labelled water for total energy intake, 24-hour urinary nitrogen for protein intake, and 24-hour urinary potassium for potassium intake. Concentration biomarkers for vitamin C, serum carotenoids, and plasma long-chain polyunsaturated fatty acids were also measured. Measurement error modelling using the National Cancer Institute method estimated usual intake distributions and adjusted for within-person variability. Systematic and random error components were quantified, and energy-adjustment and attenuation correction approaches were evaluated. Cognitive interviewing with 40 participants assessed comprehension, cultural appropriateness, and usability of the web platform. The calibration equations generated from biomarker validation will enable correction of error-prone dietary estimates in future Nigerian epidemiological studies. Findings will produce the first rigorously validated digital dietary assessment tool for Nigeria, delivering a significant methodological advance to the national nutrition science infrastructure. Keywords: dietary assessment validation, web-based recall, doubly labelled water, biomarkers, measurement error.