Abstract
Increased sensitivity to ovarian hormone changes is implicated in the etiology of reproductive mood disorders across the female lifespan, including menstrually-related mood disorders, perinatal mood disorders, and perimenopausal depression. Developing a method to accurately quantify sensitivity to endogenous hormone fluctuations may therefore facilitate the prediction and prevention of these mental health conditions. Here, we propose one such method applying a synchrony analysis to compute time-lagged cross-correlations between repeated assessments of endogenous hormone levels and self-reported affect. We apply this method to a dataset containing frequent repeated assessments of affective symptoms and the urinary metabolites of estradiol (E2) and progesterone (P4) in 94 perimenopausal females. These preliminary findings suggest that, with further refinement and validation, the proposed method holds promise as a diagnostic tool to be used in clinical practice and to advance research investigating the etiology of reproductive mood disorders.