Statistical modeling of health space based on metabolic stress and oxidative stress scores.
BMC Public Health
; 22(1): 1701, 2022 09 08.
Article
en En
| MEDLINE
| ID: mdl-36076235
ABSTRACT
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.Palabras clave
Texto completo:
1
Bases de datos:
MEDLINE
Asunto principal:
Estrés Oxidativo
Tipo de estudio:
Prognostic_studies
/
Risk_factors_studies
Límite:
Humans
País/Región como asunto:
Asia
Idioma:
En
Revista:
BMC Public Health
Asunto de la revista:
SAUDE PUBLICA
Año:
2022
Tipo del documento:
Article