332919
Quantifying Spatial Polygamy Among Low-Income Housing Residents in NYC: A GPS Study
Methods:Data come from the NYC Low-Income Housing, Neighborhoods and Health Study, where participants wore a GPS device (on their person; e.g. in their pocket) for one week. We completed an analysis with GPS and survey data to quantify spatial polygamy for participants enrolled with complete GPS data and valid geocoded home addresses (analytic n=102; 85.8%). Five participants travelled extensively outside the city of New York during the duration of the study and were omitted from further analysis. Self-report of spatial polygamy was also assessed with five questions, including “Would you consider the neighborhood where you live to be different from the one you work or go to school in?” Response options were “Yes” and “No”.
Results:Over 70% said Yes to “Would you consider the neighborhood where you live to be different from the one you work or go to school in?” Our GPS analyses suggest that participants spend a large portion of their time outside of traditionally defined “home buffers”. In analysis of these data, the total area covered by half mile “home buffers” was 22.72 square miles, whereas total activity space buffers for the study population as a whole covered 239.1 square miles, indicating a high degree of mobility and thus wide ranging exposures to the broader environment. In addition, participant GPS data was found to be in 199 of 263 (75.7%) ZIP codes in NYC, and were found in 1192 of 2618 (45.5%) census tract areas as defined by the 2010 decennial census. This shows the general mobility as the participants only come from 26 ZIP codes or 37 tracts, but cover a much broader area of NYC.
Conclusion: Our findings highlight significant spatial polygamy among low-income housing residents in NYC, suggesting spatial entrapment is not particularly salient for this population. Thus, when conducting neighborhoods and health research among low-income populations, researchers must study beyond the residential neighborhood context—which may eventually mitigate health disparities.
Learning Areas:
Environmental health sciencesEpidemiology
Learning Objectives:
Identify and articulate different methods of examining neighborhood boundaries
Differentiate methods for studying spatial polygamy and that it can exist
Keyword(s): Geographic Information Systems (GIS), Urban Health
Qualified on the content I am responsible for because: I am a spatial epidemiologist and am PI of the study described in this abstract. I have nearly 40 publications and book chapters.
Any relevant financial relationships? No
I agree to comply with the American Public Health Association Conflict of Interest and Commercial Support Guidelines, and to disclose to the participants any off-label or experimental uses of a commercial product or service discussed in my presentation.