The Chinese urbanization ratio has increased as the economy has developed over the past 30 years. The rapid urbanization has caused increasingly unprecedented environmental problems, such as air pollution, water pollution, water resource shortages, encroachment of cultivated fields, and erratic regional climates. All these factors suggest that there are deeper interactions between the regional eco-environment and urbanization. Currently, most studies have focused on the total relationship between urbanization and the eco-environment through synthetic assessments. Although strong interactions have been determined, the key factors affecting urbanization and their interactions have not been identified and explored. Based on Beijing-Tianjin-Hebei urban agglomeration, which is a large-scale urban agglomeration and important economic zone in China, this study identified key factors and assessed their interactions affecting urbanization and the eco-environment. We used the urbanization ratio to describe urban development; and used land use, water resources, and environmental, ecological, and energy parameters to describe the eco-environment. This study assessed the impacts of eco-environmental factors on urbanization through a (1) correlation analysis to show the preliminary relationships and grey relation analysis (GRA) to rank the relations of each factor affected by urbanization, (2) significance analysis to merge homogeneous factors and determine the effect of interactions between cities and factors using a one-way ANOVA method. The results revealed that (1) total and household water consumption showed the lowest R²; socio-economic parameters showed the best correlations; land use parameters showed a lower R² than socio-economic parameters; energy parameters showed the same level of accuracy as land use counterparts, and both were considerably more correlated than NDVI, which showed a higher R² than water consumption parameters; (2) GRA results were heterogeneous among both the 13 cities and factors of the Beijing-Tianjin-Hebei urban agglomeration. Furthermore, the GRA results were different for the same factors in different categories, such as for land use and socio-economic parameters. Together, the max GRA results showed the citizen electricity usage ranked the highest, and household water consumption ranked the lowest. The variance of GRA results showed that built-up area was the most stable and population was the least stable factor; (3) pairwise GRA value comparisons among the factors were conducted to determine homogeneous factors. The fisher-LSD results showed significance to be weak within a category and strong among categories. Based on the significant properties, the total factors were compressed from 10 to 6, which represented the original selected categories whilst maintaining the assessment accuracy; (4) an interaction assessment module was used in a one-way ANOVA to evaluate the interaction effect of factors. We found that the factors significantly represented the different aspects of the ecological-environment, and the cities also significantly represented the differences between each city caused by various industrial structures and different natural environments. The interactive effect between cities and factors was significant, which provided solid evidence to further explore the interactive mode and environmental effect of the factors with increasing urbanization. This work provides a foundation to determine the supportive and suppressive effects between the eco-environment and urbanization.