Abstract Background: The conventional formula for calculating food self-sufficiency cannot cover all the food we eat on a daily basis, and the food self-sufficiency ratios (FSSR) of each country cannot be calculated. The conventional food self-sufficiency ratio (CFSSR) can only calculate the FSSRs of each country for grains. To determine the actual state of food insecurity worldwide as accurately as possible, a method for calculating the FSSR of each country for all the foods we eat on a daily basis is needed. To address this situation, this study proposes the supply-side food self-sufficiency ratio (SSFSSR), which can systematically calculate the self-sufficiency ratio of all foods in all countries/regions. Results: We compared the results of both calculations under the same conditions and used the same data to determine whether the CFSSR or the SSFSSR is a more suitable method for obtaining basic information and formulating measures of global food security. The results showed that the SSFSSR has advantages and practicality over the CFSSR. The SSFSSR can calculate self-sufficiency ratios for all foods in all countries/regions of the world, and the figures for various statistical tests are better. The food that is the subject of the calculation in the SSFSSR formula is the entire supply from production, distribution, storage, and consumption, excluding duplication in the calculation, and includes primary products required to produce secondary products, such as livestock products and edible oils. The study also highlighted the value of reducing the amount of primary products used to produce secondary products such as livestock and edible oils, thereby lowering the primary product conversion rate (PPCR). Conclusion: This study used actual data to estimate the SSFSSR for each country/region to demonstrate the applicability of this method and that lowering the PPCR would lead to an increase in the food self-sufficiency ratio. To further refine this methodology, we find that the most important tasks for the future are to collect more reliable data on calories per weight for a large number of foods, expand the number of types covered by more reliable PPCRs, and analyze those data.