Abstract

Ultra-processed food consumption represents a complex behavioral phenomenon shaped by individual preferences, commercial influences, product accessibility, nutritional information, and socioeconomic conditions. This study proposes a structural equation model to examine the relationships among consumption motivations, advertising influence, perceived accessibility, warning-label responsiveness, and ultra-processed food consumption in Ahome, Sinaloa, Mexico. Consumption motivations comprise taste preference, convenience, and time availability. Advertising influence includes advertising exposure, promotional appeal, and purchase intention after exposure. Perceived accessibility incorporates product availability, ease of purchase, and price accessibility. Warning-label responsiveness encompasses purchase moderation, purchase discontinuation, and reduced purchase intention. Ultra-processed food consumption is represented through consumption frequency, purchase frequency, and weekly expenditure. Household income, educational attainment, and household-head age are incorporated as observed socioeconomic predictors. The proposed structural framework examines the expected positive relationships between consumption motivations, perceived accessibility, and food consumption, while considering the anticipated negative association between warning-label responsiveness and consumption. Advertising influence is included to assess the relationship between commercial exposure and purchasing behavior. The model also considers socioeconomic differences that may shape consumer choices and household food expenditure. The measurement framework specifies reflective latent constructs, subject to empirical assessment of indicator reliability, internal consistency, convergent validity, and discriminant validity. Structural relationships are intended to be evaluated through path coefficients, explanatory power, predictive relevance, and effect sizes. This framework offers an integrated analytical approach to understanding consumer behavior and identifying potential intervention points for nutritional education, food labeling policies, and healthier purchasing environments. Empirical conclusions require estimation using the original respondent-level records.