Survey topics included: Household Composition, Residence and Housing Status; Health, Social Determinants of Health, Long COVID, Mental Health; Disability; Perceptions of Neighborhood; Transportation mode; Financial Precarity; Perception of Control; Voting; Employment; Demographics. This data file contains 673 Ypsilanti residents' close-ended responses. The full dataset will be published on ICPSR.
Survey topics included: Household Composition, Residence and Housing Status; Health, Social Determinants of Health, Long COVID, Mental Health; Disability; Perceptions of Neighborhood; Transportation mode; Financial Precarity; Perception of Control; Voting; Employment; Demographics. This data file contains 704 Flint residents' close-ended responses. The full dataset will be published on ICPSR.
Survey topics included: Household Composition, Residence and Housing Status; Perceptions of Neighborhood; Neighborhood Blight; Social Connection, Social Isolation, Loneliness; Election; Employment; Crime, Violence, Safety & Violence Reduction Programs; Municipal Services and Democratic Values. This data file contains 2,450 Detroit residents' close-ended responses. The full dataset will be published on ICPSR.
This collection was produced as part of the project, “A ‘Big Data’ Approach to Understanding Neighborhood Effects in Chronic Illness Disparities.” The Investigators for the project are Tiffany Veinot, Veronica Berrocal, Phillipa Clarke, Robert Goodspeed, Daniel Romero, and VG Vinod Vydiswaran from the University of Michigan. The study took place from 2015-2016, with funding from the University of Michigan’s Social Sciences Annual Institute, MCubed, and the Sloan and Moore Foundations.
Contact: Tiffany Veinot, MLS, PhD
Office: 3443 North Quad
Phone: 734/615-8281
Email: tveinot@umich.edu
MCubed project page:
https://mcubed.umich.edu/projects/%E2%80%9Cbig-data%E2%80%9D-approach-understanding-neighborhood-effects-chronic-illness-disparities
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