BACKGROUND: The network perspective on psychopathology views depression as a system of interacting symptoms. Research shows that mental health problems change with age. Children with parental absence are at risk for depression, but it's unclear how their depressive symptom networks evolve across developmental stages. METHOD: Network analysis was conducted on data from 179,519 children with parental absence who completed the depression scale CESD. The Graphical LASSO algorithm was used to construct depressive symptom networks for each age group. Global network metrics and centrality measures were then calculated and compared across age groups. RESULTS: Depressive symptoms increased with age, with mean CES-D scores rising from 3.44 at age nine to 10.8 at age 17. Network density showed a general increase from age nine (0.045) to age 17 (0.047), while average path length decreased from age nine (18.380) to age 18 (15.338) and clustering coefficient decreased from age 9 (0.879) to age 18 (0.706). Closeness centrality demonstrated the most substantial age-related effect (F = 1445.111, p <
0.001, η CONCLUSION: As children with parental absence age, their depressive symptom networks become more severe, interconnected, and efficiently structured. This suggests a need for age-specific interventions addressing both core symptoms and emerging adolescent self-evaluative concerns, advancing our understanding of developmental psychopathology in this vulnerable group.