Multi-indicator comparative analysis of health food regulations in various countries using a large-scale language model (LLM)

Health foods are subject to diverse regulatory frameworks worldwide, reflecting differences in legal systems, food cultures, and consumer protection approaches. This study compared major regulations in Japan, the United States, the European Union, Australia, and China by focusing on four aspects: definitions, labeling rules, safety evaluations, and enforcement measures. We used the Gemini API, a large-scale language model, to perform a text-based analysis of official regulatory documents obtained from government databases and websites. Our results showed substantial variation in the definitions of “health foods,” with some countries lacking an explicit legal category for these products, whereas others treat them as intermediate products between regular foods and medicines. Labeling rules in all jurisdictions aim to prevent misleading claims and ensure provision of accurate information, although specific labeling requirements differ considerably. Safety evaluations are typically grounded in scientific evidence; however, administrative organizations, review scope, and approval procedures can vary between regions. Enforcement measures for violations also share common elements—such as administrative penalties and product recalls—but differ in severity and legal procedures. These findings demonstrate that health food regulation is shaped by each country’s policy priorities and consumer expectations. The approach used in this study, which integrates large-scale language modeling with comparative legal analysis, can help researchers and policymakers track evolving regulatory trends. The proposed approach can be extended to other regions and incorporate market data and consumer perspectives for a more comprehensive understanding of international regulatory practices.