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Background: The aim of this study is to monitor the concept of 'leaving no one behind' in the Sustainable Development Goals (SDGs) to track the implications of the mobilization of health care resources by the National Health Insurance Fund (NHIF) of Sudan. Methods: A cross-sectional study was used to monitor 'leaving no one behind' in NHIF by analyzing the secondary data of the information system for the year 2016. The study categorized the catchment areas of health care centers (HCCS) according to district administrative divisions, which are neighborhood, subdistrict, district, and zero. The District Division Administrative Disaggregation Data (DDADD) framework was developed and investigated with the use of descriptive statistics, maps of Sudan, the Mann-Whitney test, the Kruskal-Wallis test and health equity catchment indicators. SPSS ver. 18 and EndNote X8 were also used. Results: The findings show that the NHIF has mobilized HCCs according to coverage of the insured population. This mobilization protected the insured poor in high-coverage insured population districts and left those living in very low-coverage districts behind. The Mann-Whitney test presented a significant median difference in the utilization rate between catchment areas (P value < 0.001). The results showed that the utilization rate of the insured poor who accessed health care centers by neighborhood was higher than that of the insured poor who accessed by more than neighborhood in each state. The Kruskal-Wallis test of the cost of health care services per capita in each catchment area showed a difference (P value < 0.001) in the median between neighborhoods. The cost of health care services in low-coverage insured population districts was higher than that in high-coverage insured population districts. Conclusion: The DDADD framework identified the inequitable distribution of health care services in low-density population districts leaves insured poor behind. Policymakers should restructure the equation of health insurance schemes based on equity and probability of illness, to distribute health care services according to needs and equity, and to remobilize resources towards districts left behind. [ABSTRACT FROM AUTHOR]