## 4 Discussion
This viewpoint again questions the reliability of per capita measures. For instance, the per capita number for Figure 10-2 might be higher than Figure 10-1, but it cannot address the inequity issue. However, it should be noted that although the findings reveal spatial patterns, a detailed spatial relationship analysis is beyond the scope of this research, as the current methodology primarily aimed at identifying general associations. In terms of methodology, the Network Analysis tool provides the walking distance to certain destinations using the existing roads, as well as the distance from the UGS boundary rather than centroids. The analysis using this tool shows that higher SES SA2s in Melbourne have shorter access to UGSs. One reason behind the improved access score could be the existing road network. For instance, in the central SA2s, which are mainly among higher quintiles, there is a 400 m access to at least one UGS from almost every spot. It shows there are more access alternatives to green spaces, which is probably a result of the compact urban form in central Melbourne. This finding is particularly consistent with [PERSON] et al. 's [9] study on livability in Australian cities, showing inner suburbs are more livable in various terms, namely walkability and open spaces. There has been a limitation to this approach due to the large-scale case study. The Network Analysis tool requires point features as the destination; therefore, we used the 'feature to point' tool to convert the UGS feature boundaries into points. The tool draws a point at each vertex, which demonstrates the precise shape of the feature for irregularly shaped UGS. So, if there is a straight line without a fraction, the tool draws a single point for it regardless of the length. This may cause some levels of inaccuracy in the analysis. Therefore, future studies can develop a method for more accurate accessibility assessment or a smaller scale case study. On the other side of the analysis, assessments of the correlation between UGS availability measures and the CVD rates show a lower proportion of the affected population in areas with higher UGS density and accessibility. The CVD rates among people living in areas with higher-than-average UGS density and accessibility are minimal (about 4.1 percent of the population) compared to other areas. Furthermore, in areas with lower UGS accessibility, regardless of changes in density, this percentage reaches near 4.6. So, future studies may include more specific indicators like physical activity, hypertension, obesity, etc. [48], as contributors to CVD. Also, studies with more subjective approaches like surveys among residents in addition to UGS qualities, like existing facilities, green coverage, etc., in different SES areas can deepen the understanding of the impacts of UGS on decreasing CVD chances. Beyond the limitations of the analytical method, it is important to acknowledge that 400 m access to UGS is just one of many factors that may contribute to variations in CVD risk. Additionally, certain areas in Melbourne, similar to any other city, may be predominantly populated by younger adults, potentially affecting the health indicators at the area level. These limitations highlight the need for a careful interpretation of findings in studies of this nature, as the results are not definitive.