Pathways leading to atherosclerosis: a structural equation modeling approach in young adults

Area of Science:

• Cardiovascular disease research
• Metabolic health studies
• Advanced statistical modeling

Background:

• Rising incidence of obesity and cardiovascular diseases necessitates improved risk factor modeling.
• Complex interrelationships between risk factors have challenged traditional statistical methods.
• Structural Equation Modeling (SEM) offers a powerful approach to analyze intricate associations.

Purpose of the Study:

• To investigate SEM's capability in unraveling and visualizing pathways contributing to cardiovascular diseases.
• To model the direct and indirect effects of risk factors on atherosclerosis.
• To explore sex-specific differences in these pathways.

Main Methods:

• Utilized Structural Equation Modeling (SEM) on data from 322 healthy participants (ages 18-24) in the PROGRAM study.
• Explored pathways leading to atherosclerosis, measured by carotid intima-media thickness.
• Incorporated body fat percentage, serum lipid levels, and blood pressure into the SEM models for males and females.

Main Results:

• Developed SEM models with excellent fit for both male and female participants.
• Fat mass significantly impacts carotid intima-media thickness, primarily through blood pressure.
• Identified distinct pathways between sexes, with serum lipids having a greater effect in males.

Conclusions:

• SEM is a suitable technique for identifying models that elucidate complex disease origins.
• Presented a novel SEM model demonstrating fat mass's influence on atherosclerosis risk factors in young adults.
• Highlighted the importance of considering sex-specific pathways in cardiovascular disease development.