Before AI tells patients what to eat, it needs to know where they live: a cross-sectional ecological study of diabetes and food access in California and Michigan census tracts, with a spotlight on Metro Detroit and Metro Los Angeles

Background: AI chatbots now give people with diabetes diet advice, but whether those foods can be bought near home is rarely checked. Methods: In a cross-sectional ecological study of 11,974 California and Michigan census tracts, I linked diabetes prevalence (CDC PLACES 2025) with two USDA food-access maps: all SNAP-authorized stores (2025) and large grocery stores only (2019). I identified double-burden tracts (high diabetes and low income/low access) and hidden food deserts (low access to large grocery stores, but not to any SNAP store). In a pilot, ChatGPT, Gemini, and Claude generated meal

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