Department of Statistics, Seoul National University, Seoul, Republic of Korea.
Department of Nutritional Science and Food Management, Ewha Womans University, Seoul, Republic of Korea.
BMC Public Health. 2022 Sep 8;22(1):1701. doi: 10.1186/s12889-022-14081-0.
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.
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.
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.
These validation studies using two independent datasets successfully demonstrated the usefulness of the proposed HS.
健康空间（HS）是一种在多维空间中可视化个体健康状况的统计方法。本研究提出了一种基于代谢应激和氧化应激得分的二维 HS。
这些分数是从三个统计模型中得出的：逻辑回归模型、逻辑混合效应模型和比例优势模型。HS 使用韩国国家健康和营养检查调查数据中的 32140 个样本开发。为了评估和比较 HS 的性能，我们还开发了健康空间指数（HSI），这是一种基于 HS 的近似 95%置信椭圆的定量性能度量。
通过模拟研究，我们证实了比例优势模型的 HS 在区分个体（受试者）的健康状况方面具有最高的能力。使用两个独立的队列数据集进行了进一步的验证研究：一个来自 Ewha-Boramae 队列的健康检查数据集，包含 862 个样本，另一个来自韩国关联资源项目的基于人群的队列，包含 3199 个样本。
使用两个独立数据集的这些验证研究成功地证明了所提出的 HS 的有用性。
