Patterns of premenstrual syndrome and depression symptoms in Chinese female university students: Results of a latent profile analysis

Abstract

BackgroundPremenstrual syndrome (PMS) and depression co-occur frequently; however, their relationship remains controversial. This study was conducted primarily to discern heterogeneous patterns of such co-occurring symptoms in Chinese female university students, using a latent profile analysis (LPA), a person-centered statistical approach. MethodsThe PMS Scale and Beck Depression Inventory were used to examine self-reported PMS and depression symptoms in 701 Chinese female university students. LPA, multinomial logistical regression, and analyses of variance were adopted to investigate latent profiles and their validity. ResultsThe LPA results indicated that a four-class solution characterized by low symptoms (57.2%), predominantly PMS (11.3%), predominantly depression (23.7%), and combined PMS–depression (7.8%) patterns fitted the data best. Age, first menstrual experience, and personality factors were associated with differences in nonparallel profiles characteristic of menstrual attitude. LimitationsUse of self-report measures can lead to response biases; the cross-sectional design at a single time point limits the examination of changes in symptom characteristics and members within the category over time; and the specific age group limits the generalizability of results. ConclusionThese results confirm that PMS is independent from depression, rather than a variant of depression, and can be used to resolve the controversy regarding the relationship between PMS and depression. The current findings highlight the need for identifying women at high risk for PMS and depression, and promoting interventions individually tailored to their symptom presentations.