Nonlinear relationship between health factors and health outcomes

Russell S. Gonnering, Mirsad Hadzikadic, William Riley, Kailey Love, Joseph Whitmeyer

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Abstract

The relationship between Health Factors and Health Outcomes is a topic of great practical importance in the understanding of the genesis of and solution to the problem of health disparities. We have investigated the data compiled by the Population Health Institute of the University of Wisconsin and contained within the Robert Wood Johnson Foundation's “County Health Rankings and Roadmaps” with special reference to Arizona. We found that the relationships are complex, non-linear and in many instances counterintuitive. There exists a nonlinear model “signature” specific to each state as well as the counties within each state. The surprisingly better Health Outcomes in Yuma County than what would normally be expected from the Health Factors indicate that the transformational function that converts Health Factors into Health Outcomes may be more important than the Health Factors themselves. This transformational function approach allows new understanding for such anomalies in Health Outcomes.

Original languageEnglish (US)
Title of host publicationProceedings of the 2017 International Conference of the Computational Social Science Society of the Americas, CSS 2017
PublisherAssociation for Computing Machinery
VolumePart F137133
ISBN (Electronic)9781450352697
DOIs
StatePublished - Oct 19 2017
Event2017 International Conference of the Computational Social Science Society of the Americas, CSS 2017 - Santa Fe, United States
Duration: Oct 19 2017Oct 22 2017

Other

Other2017 International Conference of the Computational Social Science Society of the Americas, CSS 2017
CountryUnited States
CitySanta Fe
Period10/19/1710/22/17

Keywords

  • Arizona
  • Emergence
  • Health Disparity
  • Health Factors
  • Health Outcomes
  • Population Health

ASJC Scopus subject areas

  • Human-Computer Interaction
  • Computer Networks and Communications
  • Computer Vision and Pattern Recognition
  • Software

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  • Cite this

    Gonnering, R. S., Hadzikadic, M., Riley, W., Love, K., & Whitmeyer, J. (2017). Nonlinear relationship between health factors and health outcomes. In Proceedings of the 2017 International Conference of the Computational Social Science Society of the Americas, CSS 2017 (Vol. Part F137133). [a2] Association for Computing Machinery. https://doi.org/10.1145/3145574.3145576