Modeling the impact of socioeconomic disparity, biological markers and environmental exposures on phenotypic age using mediation analysis and structural equation models.

Introduction: Average age is increasing worldwide, raising the public health burden of age-related diseases, as more resources will be required to manage treatments. Phenotypic Age is a score that can be useful to provide an estimate of the probability of developing aging-related conditions, and prevention of such conditions could be performed efficiently studying the mechanisms leading to an increased phenotypic age. The objective of this study is to characterize the mechanisms that lead to aging acceleration from the interactions among socio-demographic factors, health predispositions and biological phenotypes.

Identifying biological markers and sociodemographic factors that influence the gap between phenotypic and chronological ages.

Introduction: The world's population is aging rapidly, leading to increased public health and economic burdens due to age-related cardiovascular and neurodegenerative diseases. Early risk detection is essential for prevention and to improve the quality of life in elderly individuals. Plus, health risks associated with aging are not directly tied to chronological age, but are also influenced by a combination of environmental exposures.