Identifying Critical Points of Trajectories of Depressive Symptoms From Childhood to Young Adulthood: Evidence of Sex Differences from the Avon Longitudinal Study of Parents and Children (ALSPAC)
Alex S. F. Kwong,
Nicholas J. Timpson,
Rebecca M Pearson,
Hannah M Sallis,
Oliver S.P. Davis,
Posted 07 Feb 2018
bioRxiv DOI: 10.1101/193680
Posted 07 Feb 2018
Depression is a common mental illness associated with increased substance misuse and risk of suicide. Potential risk factors for depression include sex and depressive symptoms in early life, however the mechanisms responsible are not yet understood. Research has focused on late childhood and adolescence as this developmental period may be a modifiable risk factor that prevents or reduces depression at a later stage. It is also important to establish at what ages the level of depression is changing as this will help identify critical points to intervene with treatment. We used multilevel growth-curve models to explore adolescent trajectories of depressive symptoms in the Avon Longitudinal Study of Parents and Children, a UK based pregnancy cohort. Using data from 9301 individuals, trajectories of depressive symptoms were constructed for males and females between 10.6 and 22.8 years old. We calculated the age of peak velocity for depressive symptoms (the age at which depressive symptoms increases most rapidly) and the age of maximum depressive symptoms. Adjusted results suggested that being female was associated with a steeper trajectory compared to being male (per 1 year increase in relation to depressive symptoms: 0.128, SE = 0.035, [95% CI: 0.059, 0.198]; p <0.001). We found evidence suggesting that females had an earlier age of peak velocity of depressive symptoms (females 13.7 years old, SE = 0.321, [95% CI: 12.9, 14.4] and males 16.4 years old, SE = 0.096, [95% CI: 16.2, 16.6]; p <0.001), but weak evidence of an earlier age of maximum depressive symptoms (p = 0.125). Possible mechanisms that underlie this sex difference include the roles of pubertal development and timing. Using multilevel growth curve models to estimate the age of peak velocity and maximum depressive symptoms for different population subgroups may provide useful knowledge for treating and preventing later depression.
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