We present a parsimonious demand modeling approach developed for the annual USDA-ERS International Food Security Assessment. The assessment focuses on chronic food insecurity. The approach incorporates price effects, food quality variation across income deciles, and consistent aggregation over income deciles and food qualities. The approach is based on a simple demand approach for four food categories. It relies on the existing sparse data available for the Assessment, complemented by own-price and income elasticities and available price data. Beyond consistent aggregation, the framework exhibits desirable characteristics: food quality is increasing with income; price and income responses become less sensitive with increasing income; and increasing income inequality decreases average per capita food consumption. The proposed approach is illustrated for Tanzania. We then use the calibrated model to decompose the impact of income, prices, and exchange rates on food consumption. Next, we assess future food insecurity in Tanzania using the calibrated model and two alternative characterizations of the income distribution (decile based and continuous). Food-insecure population is estimated as well as the implied distributional gap in calorie per day per food insecure person and in total annual food volume in grain equivalent. The latter gauges the depth of the chronic food insecurity.