Associations between personality traits and depressive symptoms transitions in middle-aged and older adults: a markov model approach

OBJECTIVES: Given the growing population health impact of depressive symptoms (DS), mapping DS state transitions and their associated factors, particularly personal traits, may offer critical insights for designing targeted prevention measures. METHOD: We employed three waves (2018, 2020, and 2022) of China Family Panel Studies (CFPS) data to operationalize DS into three categorical states (non-DS, mild-DS, severe-DS) and implemented multi-state Markov modeling to quantify transition probabilities and assess personality traits associations. RESULTS: A total of 6410 participants aged 45 years or older were included in this cohort analysis. DS state transitions were observed between adjacent and non-adjacent states, with higher transition intensities occurring between adjacent states. Extraversion, openness, conscientiousness, and agreeableness were associated with a lower likelihood of DS progression and showed positive correlations with symptom remission. Neuroticism was linked to an increased probability of DS progression and appeared to be associated with an increased likelihood of DS reversal. CONCLUSION: Personality traits show persistent but differential associations with DS dynamic transitions, highlighting the relevance of personality trait assessments, which may support the development of tailored strategies to maintain mental health among middle-aged and older adults.