Peer-reviewed article
Estimating severity and rate of change of depressive symptoms in adolescence: a comparison of functional principal component analysis and mixed effects models
Hernandez MA, Kwong AS, Li C, Simpkin AJ, Wootton RE et al. ·
Summary
Written by AI, not yet AICS's view · claude-haiku-4-5-20251001This study tracked depressive symptoms in over 8,000 young people from childhood to age 25 using two statistical methods to map how their mental health changed over time. It found that girls experienced higher and earlier peaks in depression symptoms compared to boys. Early-life stressors such as abuse, bullying, domestic violence, and parental depression were all linked to more severe and faster-developing depressive symptoms in adolescence.
Key points
- Peak depressive symptoms and rate of change were higher and occurred over 1 year earlier in females than males
- All early-life factors examined (maternal education, maternal perinatal depression, domestic violence, abuse, bullying, psychiatric disorder) associated with higher peak symptoms
- Abuse and bullying specifically associated with earlier age of peak symptoms
- Functional principal component analysis proved effective for characterising depressive symptom trajectories
- Early-life stressors may accelerate both the timeline and intensity of symptom escalation during adolescence
Limitations
The study population was mostly White European, limiting generalisability to other ethnic and cultural groups. The research is observational and establishes associations rather than causal links between early-life factors and depressive symptom trajectories.
Abstract
ABSTRACT Understanding depressive symptoms dynamics and their determinants is crucial for designing effective mental health support initiatives. This study compared two methods for describing youth depressive symptoms trajectories and investigated associations of early-life factors (maternal education, maternal perinatal depression, domestic violence, physical, emotional, or sexual abuse, bullying victimisation, psychiatric disorder) with trajectory features. Prospective data from 8,264 mostly White European participants (54% female), including self-reported Short Moods and Feelings Questionnaires on ten occasions between 10-25 years, were used. Trajectories were summarised using functional principal component analysis (FPCA) and P-splines linear mixed-effect (PLME) models. Estimated derivatives were used to obtain magnitude and age of peak symptoms and peak symptoms velocity. Both methods performed comparably, but PLME models tended to over-smooth trajectories. Peak symptoms and peak velocity were higher and occurred >1 year earlier in females than males. All early-life factors were associated with higher peak symptoms, and most associated with higher and earlier peak velocity. Abuse and bullying additionally associated with earlier age of peak symptoms. FPCA is a useful alternative for characterising depressive symptoms trajectories and informing time-sensitive preventative measures to reduce impact of depression before symptoms reach their peak. Early-life stressors may accelerate timeline and intensity of symptoms escalation during adolescence. Lay summary Understanding development of depressive symptoms and factors shaping them is crucial for designing effective mental health support initiatives. This study used data from over 8,000 young people regularly followed up from before birth to compare two cutting-edge methods for describing depressive symptoms trajectories and examined how known risk factors for adulthood depression relate to the severity and rate of change of depressive symptoms in adolescence. We found that both methods performed well and that the peaks in depressive symptoms and their rate of change were, on average, higher and occurred over a year earlier in females than males. Our findings additionally suggest that early-life stressors (e.g., abuse, bullying) may accelerate the development of depression, highlighting the importance of early prevention.