Assessment of Multidimensional Health Care Parameters Among Adults in Japan for Developing a Virtual Human Generative...

Area of Science:

• Multidisciplinary health sciences
• Biostatistics
• Personalized medicine

Background:

• Human health status is assessed using diverse parameters.
• Understanding statistical relationships among health parameters enables personalized and preventive healthcare.
• Identifying modifiable risk factors (lifestyle, diet, physical activity) is crucial for optimal treatment design.

Purpose of the Study:

• To compile a high-dimensional, cross-sectional dataset of comprehensive health information.
• To construct a joint probability distribution model for analyzing multidimensional health data.
• To facilitate further research into individual relationships among various health variables.

Main Methods:

• Cross-sectional observational study involving 997 adult participants (aged ≥20 years).
• Data collection included biochemical, metabolic, bacterial, genetic (mRNA), proteomic, metabolomic, lifestyle, functional, and olfactory profiles.
• Statistical analyses involved training a joint probability distribution model and investigating individual variable relationships.

Main Results:

• Data from 997 participants were collected between October 2021 and February 2022.
• The collected data will be utilized to develop a Virtual Human Generative Model.
• The model and data are anticipated to elucidate relationships between diverse health statuses.

Conclusions:

• Correlations between health statuses are expected to influence individual health outcomes.
• This study will support the development of evidence-based, population-specific interventions.
• Findings will advance personalized and preventive healthcare strategies.