The Association of Elevated Depression Levels and Life's Essential 8 on Cardiovascular Health With Predicted Machine...

Area of Science:

• Cardiology
• Psychiatry
• Data Science

Background:

• Cardiovascular health (CVH) is crucial for overall well-being.
• Depression is a significant public health concern.
• Understanding the link between CVH and depression is vital for targeted interventions.

Purpose of the Study:

• To analyze the association between depression severity and cardiovascular health (CVH) using Life's Essential 8 (LE8).
• To investigate age-specific differences in this association.
• To employ machine learning (ML) for predictive modeling and clinical recommendations.

Main Methods:

• Utilized data from 21,279 participants in the National Health and Nutrition Examination Survey (NHANES) (2007-2018).
• Employed weighted ordinal logistic regression (LR) with sensitivity and dose-response analyses.
• Applied eight ML algorithms with SHapley Additive exPlanations (SHAP) for interpretability.

Main Results:

• Demonstrated a robust inverse relationship between LE8 scores and elevated depressive levels.
• Identified higher depression severity in middle-aged and older adults (40-60 and >60 years).
• Developed interpretable ML models for predicting the association.

Conclusions:

• Confirmed a negative association between LE8 and depression severity.
• Highlighted the need for age-specific interventions for cardiovascular health and depression.
• Provided ML-driven recommendations for clinical practice and public health awareness.