Meal Architecture: An Implementation Framework for Reconfiguring Evidence-Based Dietary Interventions for Time-Constrained Working Adults

Evidence-based dietary patterns are effective for preventing and managing metabolic syndrome (MetS). However, they often assume that individuals have sufficient time, cognitive resources, and stable daily routines to prepare healthy meals, monitor dietary intake, and make repeated food-related decisions. For many business professionals, these assumptions are unrealistic, creating an implementation gap between nutritional evidence and everyday practice. To address this gap, this paper proposes Meal Architecture, a conceptual implementation framework that reconfigures evidence-based dietary interventions into forms that remain feasible under real-world time constraints. Rather than introducing another dietary pattern, Meal Architecture distinguishes the core metabolic functions that should be preserved from the implementation forms that can be adapted to different food environments while maintaining their intended physiological effects. The framework preserves four core metabolic functions: attenuation of postprandial glycemic excursions, prevention of excessive energy intake, provision of dietary fiber and high-quality carbohydrates, and provision of appropriate protein sources. Implementation components such as detailed calorie counting, routine home cooking, complex meal planning, continuous food logging, and sustained reliance on motivation are treated as adaptable rather than indispensable. These functions are operationalized through context-sensitive implementation strategies, including substitution, addition, sequencing, portion adjustment, and routine selection. Meal Architecture emphasizes repeated effective exposure to core metabolic functions through feasible, sustainable behaviors rather than perfect adherence to ideal meal plans. Meal Architecture reframes unhealthy dietary behavior among business professionals not as a consequence of inadequate knowledge or poor self-control, but as a design mismatch between evidence-based dietary interventions and the realities of everyday life. By integrating nutrition science with implementation science, the framework provides a theoretical foundation for designing low-burden dietary interventions applicable to health promotion, occupational health, workplace wellness, and AI-assisted personalized health support.