Literature DB >> 23036262

Mood and the menstrual cycle: a review of prospective data studies.

Sarah Romans1, Rose Clarkson, Gillian Einstein, Michele Petrovic, Donna Stewart.   

Abstract

BACKGROUND: The human menstrual cycle (MC) has historically been the focus of myth and misinformation, leading to ideas that constrain women's activities.
OBJECTIVES: We wished to examine one pervasive idea, that the MC is a cause of negative mood, by studying the scientific literature as a whole. We briefly reviewed the history of the idea of premenstrual syndrome and undertook a systematic review of quality studies.
METHODS: We searched PubMed, PsycINFO, and article bibliographies for published studies using non-help-seeking samples with daily mood data collected prospectively for a minimum of 1 complete MC. We critiqued their methodologies and tabulated the key findings.
RESULTS: Of 47 English language studies identified, 18 (38.3%) found no association of mood with any MC phase; 18 found an association of negative mood in the premenstrual phase combined with another MC phase; and only 7 (14.9%) found an association of negative mood and the premenstrual phase. Finally, the remaining 4 studies (8.5%) showed an association between negative mood and a non-premenstrual phase. Considering the only 41 adequately powered studies, the same phase links were reported by 36.6%, 41.5%, and 13.5% of studies, respectively. Their diversity of methods (sampling, instruments, and cycle phase definitions) precluded a meta-analysis.
CONCLUSIONS: Taken together, these studies failed to provide clear evidence in support of the existence of a specific premenstrual negative mood syndrome in the general population. This puzzlingly widespread belief needs challenging, as it perpetuates negative concepts linking female reproduction with negative emotionality.
Copyright © 2012 Elsevier HS Journals, Inc. All rights reserved.

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Year:  2012        PMID: 23036262     DOI: 10.1016/j.genm.2012.07.003

Source DB:  PubMed          Journal:  Gend Med        ISSN: 1550-8579


  19 in total

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