@inproceedings{76712eba3cc347dfb75768779430c195,
title = "Nonlinear relationship between health factors and health outcomes",
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.",
keywords = "Arizona, Emergence, Health Disparity, Health Factors, Health Outcomes, Population Health",
author = "Gonnering, {Russell S.} and Mirsad Hadzikadic and William Riley and Kailey Love and Joseph Whitmeyer",
note = "Publisher Copyright: Copyright {\textcopyright} 2017 held by the owner/author(s).; 2017 International Conference of the Computational Social Science Society of the Americas, CSS 2017 ; Conference date: 19-10-2017 Through 22-10-2017",
year = "2017",
month = oct,
day = "19",
doi = "10.1145/3145574.3145576",
language = "English (US)",
series = "ACM International Conference Proceeding Series",
publisher = "Association for Computing Machinery",
booktitle = "Proceedings of the 2017 International Conference of the Computational Social Science Society of the Americas, CSS 2017",
}