Following the preceding descriptive analyses, this chapter empirically investigates the linkages between the Objective Built Environment (OBE) and residents’ Life Satisfaction (LS) within Guangzhou’s high-density urban context. Its primary aim is to examine both the geographic and statistical relationships between OBE elements—conceptualized through the “5D” framework (Density, Diversity, Design, Distance to transit, and Destination accessibility)—and LS, testing direct effects via multiple linear regression. Section 8.1 employs geographic information visualization and correlation matrices to explore bivariate relationships between each OBE factor (e.g., Population Density, Building Density, Functional Mix Diversity, Road Intersection Density, Bus Line Density, Bus Stop Density, POI Density) and community-level average LS. These preliminary analyses reveal mixed spatial patterns and weak-to-moderate correlations. Section 8.2 specifies a multivariate regression model controlling for individual socioeconomic attributes to test hypotheses on OBE effects. Results show significant negative effects of Building Density (β = −0.106, p < 0.05), Road Intersection Density (β = −0.164, p < 0.01), and Bus Stop Density (β = −0.135, p < 0.1), and a positive effect of Bus Line Density (β = 0.146, p < 0.05). Functional mix diversity was marginally negative (β = −0.075, p < 0.1), while population and POI Density were non-significant. By regression analysis, this chapter provides strong evidence to reveal whether specific OBE factors affect LS, highlighting their nuanced and sometimes countervailing roles. These findings establish a foundation for subsequent mechanistic analyses via structural equation modeling.