Self-rated health trajectories: A dynamic time warp analysis

Area of Science:

• Health outcomes research
• Biostatistics
• Longitudinal studies

Background:

• Self-rated health (SRH) is a significant predictor of future health events and mortality.
• Understanding the developmental trajectories of SRH is crucial for effective disease prevention.
• Previous research has not fully characterized the typical patterns of SRH change over time.

Purpose of the Study:

• To identify prototypic trajectories of self-rated health (SRH) over time.
• To apply dynamic time warping (DTW) for uncovering distinct SRH developmental paths.
• To inform disease prevention by identifying SRH trajectories associated with adverse health outcomes.

Main Methods:

• Utilized dynamic time warping (DTW), a time series analysis technique, to compare individual SRH data.
• Analyzed longitudinal data from a representative Dutch sample of 2,154 individuals.
• Identified distinct clusters of SRH trajectories based on temporal patterns.

Main Results:

• Dutch individuals generally do not exhibit steady growth or decline in SRH.
• Four relatively stable SRH trajectories were identified, varying in average SRH levels.
• A significant trajectory characterized by consistently low self-rated health was observed.

Conclusions:

• SRH development is characterized by stable trajectories rather than linear changes.
• The identification of a persistent low SRH trajectory highlights a population subgroup requiring targeted health interventions.
• Findings support the use of DTW in public health research for understanding health perception dynamics.