Background: Health space (HS) is a statistical way of visualizing individual’s health status in multi-dimensional space. In this study, we propose a novel HS in two-dimensional space based on scores of metabolic stress and of oxidative stress. Methods: These scores were derived from three statistical models: logistic regression model, logistic mixed effect model, and proportional odds model. HSs were developed using Korea National Health And Nutrition Examination Survey data with 32,140 samples. To evaluate and compare the performance of the HSs, we also developed the Health Space Index (HSI) which is a quantitative performance measure based on the approximate 95% confidence ellipses of HS. Results: Through simulation studies, we confirmed that HS from the proportional odds model showed highest power in discriminating health status of individual (subject). Further validation studies were conducted using two independent cohort datasets: a health examination dataset from Ewha-Boramae cohort with 862 samples and a population-based cohort from the Korea association resource project with 3,199 samples. Conclusions: These validation studies using two independent datasets successfully demonstrated the usefulness of the proposed HS.
Bibliographical noteFunding Information:
This research was supported by the Bio-Synergy Research Project (2013M3A9C4078158) of the Ministryof Science, ICT and Future Planning through the National Research Foundation and by a grant of the KoreaHealth Technology R&D Project through the Korea Health Industry Development Institute (KHIDI), funded bythe Ministry of Health & Welfare, Republic of Korea (grant number: HI16C2037). The funders had no role in thedesign of the study; in the collection, analyses, or interpretation of data; in the writing of the manuscript, or in thedecision to publish the results.
© 2022, The Author(s).
- Health space
- Metabolic stress
- Oxidative stress