Background: The joint distribution of ultra-processed food (UPF) consumption, sleep behaviour and cardiometabolic risk is poorly characterised in comparable young-adult samples across the United Kingdom and Ghana. 
Objective: To develop a harmonised cross-country epidemiological protocol and a technically explicit analytical strategy for estimating nonlinear exposure–outcome associations, between-setting heterogeneity and measurement uncertainty. 
Methods: The proposed cross-sectional field design targets adults aged 18–35 years and integrates repeated NOVA-coded dietary recall, sleep timing and Pittsburgh Sleep Quality Index assessment, anthropometry, blood pressure and glycaemic measurements. An existing synthetic dataset of 2,400 records, divided evenly between country-labelled scenarios, is retained strictly to demonstrate the analysis workflow. The revised framework introduces latent usual-intake models, spline-based and hierarchical generalised models, flexible sleep interaction structures, multiple imputation, measurement invariance checks and quantitative bias analysis. Results: Six existing simulation figures illustrate predetermined scenario differences and correlations; none constitute observed UK or Ghana estimates. The expanded models are specified for future application but have not been empirically fitted to participant data. 
Conclusions: A harmonised, pre-registered design can test whether UPF–cardiometabolic associations vary across sleep profiles and food environments. Representative recruitment, ethics approvals and independent model validation are prerequisites for population claims.