Metropolitan Geographic Definitions and Code for "Urban Inequality, the Housing Crisis and Deteriorating Water Access in US Cities"

Safe, reliable, and equitable water access is critical to human health and livelihoods. In this study, we present the first longitudinal analysis of household access to running water—a vital social infrastructure—in the 50 largest US cities since 1970. In the accompanying paper published in Nature Cities, results of the analysis indicate that water access has worsened in an increasing number and typology of US cities since the 2008 global financial crash, disproportionately affecting households of color. We provide evidence to suggest that a ‘reproductive squeeze’—systemic, compounding pressures on households’ capacity to reproduce themselves on a daily and societal basis—is forcing urban households into more precarious living arrangements, including housing without running water, with few signs of abating.

This file—which is the supplementary data that underpins the paper—contains the microdata dataset for the manuscript "Urban Inequality, the Housing Crisis and Deteriorating Water Access in US Cities" (Nature Cities). Here, we present customized and improved Public Use Microdata Sample (PUMS) definitions used in our study that enable researchers to compare US Metropolitan Statistical Area (MSA) over time, while minimizing spatial error. The dataset also includes accompanying R code for statistical analysis of census microdata and the creation of static and dynamic spatial visualizations.

Parties interested in collaborating on use of the full script may contact the corresponding author (K. Meehan).

If you use this dataset or code, please cite as follows: Meehan, Katie, Jason R. Jurjevich, Lucy Everitt, Nicholas M.J.W. Chun, and Justin Sherrill. (2024). Metropolitan Geographic Definitions and Code for "Urban Inequality, the Housing Crisis and Deteriorating Water Access in US Cities.” Tucson, AZ: University of Arizona Research Data Repository. DOI: 10.25422/azu.data.25724286

FUNDING
This research and dataset were supported by a grant selected by the European Research Council and funded by UKRI Horizon Europe Guarantee (Grant No. EP/Y024265/1)

For inquiries regarding the contents of this dataset, please contact the Corresponding Author listed in the README.txt file. Administrative inquiries (e.g., removal requests, trouble downloading, etc.) can be directed to data-management@arizona.edu