Urban Management: Learning from Green Infrastructure, Socioeconomics and Health Indicators in the Municipalities of the State of Paraná, Brazil, Towards Sustainable Cities and Communities

Abstract

The 2030 Agenda for Sustainable Development included universal access to health care and well-being. However, the massive growth of cities and the reduction of vegetated areas induced imbalances in the environment. Green spaces reduce environmental stressors such as heat waves, air and noise pollution. Nonetheless, late-year Reports by WHO-Europe demonstrated that there is some controversy about the benefits of green spaces. This paper discusses results of a pilot study involving socioeconomic data and built environment indicators, including green infrastructure, as well as morbidities of respiratory and circulatory diseases for the 399 municipalities of the State of Paraná, as well as a data mining approach to extract rules to associate morbidities with said indicators. Results showed high variability in the values of such indicators. Hierarchical tree analysis and non-hierarchical k-means technique grouped the same variables into two clusters, one of which formed only by the morbidities. Main component analysis resulted in four factors that explain about 70% of the variance of the original variables. The mining of associative rules was encouraging but further research is necessary, probably looking into other data extracts such as geography, age and gender. These outcomes may support urban planning and policies to enhance urban quality of life.