Time-Varying Effect Models for Examining Age-Dynamic Associations in Gerontological Research

Area of Science:

• Gerontology
• Biostatistics
• Public Health

Background:

• Dynamic processes in later adulthood are crucial for gerontological research.
• Time-varying effect modeling (TVEM) can analyze dynamic change trajectories but is underutilized in gerontology.
• The National Health and Aging Trends Study (NHATS) provides data for such analyses.

Purpose of the Study:

• To introduce and demonstrate the application of TVEM in gerontological research.
• To examine age-varying prevalence of depression and anxiety symptoms in older adults.
• To investigate age-varying associations between mental health symptoms and functional/educational factors.

Main Methods:

• Utilized TVEM to analyze data from the National Health and Aging Trends Study (NHATS).
• Assessed prevalence of past-month elevated depression and anxiety symptoms across different age groups.
• Examined the relationship between these symptoms and activities of daily living (ADLs) and educational attainment, considering age variations.

Main Results:

• Past-month elevated depression and anxiety symptoms increased gradually from ages 70-92 (23-29%).
• Needing help with ADLs was associated with higher odds of elevated symptoms, with the association strongest in the 60s compared to the 80s.
• Lower educational attainment correlated with higher odds of elevated symptoms across all ages, with age-dependent variations.

Conclusions:

• TVEM is valuable for studying dynamic, age-varying associations in older adults.
• The availability of user-friendly software facilitates TVEM adoption in gerontology.
• TVEM offers a new tool for gerontological researchers to explore complex developmental changes in later life.