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Sustainability, Health and Environmental Metrics: Impact on Ranking and Associations with Socioeconomic Measures for 50 U.S. Cities
Citation:
Gallagher, J., E. Hubal, L. Jackson, Jeff Inmon, E. Hudgens, A. Williams, D. Lobdell, J. Rogers, AND Tim Wade. Sustainability, Health and Environmental Metrics: Impact on Ranking and Associations with Socioeconomic Measures for 50 U.S. Cities. Sustainability. MDPI, Basel, Switzerland, 5:789-804, (2013).
Impact/Purpose:
The integrated data analysis presented here combines data across three broad domains; Environment and Health and Sustainability and includes over 70 measures. We have demonstrated how performance rankings of 50 populous cities are highly dependent on the metrics used in the assessment. Our study sheds light on a number of important socioeconomic inequalities associated with poorer performing cites though viewing the indices in the context of socioeconomic data. Our study draws attention to the significant interconnections between environmental, health, sustainability and sociodemographic factors, using individual and aggregated extant data and furthers the understanding of the potential positive or negative impact that infrastructure and land use planning decisions have on these metrics.
Description:
Abstract: Waste and materials manage¬ment, land use planning, transportation and infrastructure, including water and energy can have indirect or direct beneficial impact on the environment and public health. The potential for impact however, is rarely viewed in an integrated fashion. Here, we catalogue common, publically available Environmental (e), Health (h) and, Sustainability (s) metrics along with sociodemographic measurements to facilitate such an integrated view and to support community-based policy decision making. 84 extant (e), (h) (s) measurements for 50 US cities were extracted from three sources; SustainLane, Earth Day Network’s 2008 urban environment report (UER) and the 2010 U.S. census data. We ranked the best performing cities based on individual (e),(h), (s) metrics and derived aggregated (E), (H) and (S) indices and a composite (EHS) Index. Interconnections between and amongst the metrics and socioeconomic data for these cities were evaluated using Pearson correlation analyses, and assessed between city variability based on the (E), (H), and (S) indices. A higher (better) composite (EHS) Index was significantly associated with measures related to race, income, poverty level, education attainment level and access to health insurance. The order of the top ten best ranked cities changes when the assessment excludes (s) metrics. Understanding the interconnections between sustainability, environment, socioeconomics, and human health allow for more holistic community assessment.