Document Type

Open Access Thesis

Embargo Period

4-6-2015

Degree Program

Public Health

Degree Type

Master of Science (M.S.)

Year Degree Awarded

2015

Month Degree Awarded

May

Advisor Name

Elizabeth

Advisor Middle Initial

R.

Advisor Last Name

Bertone-Johnson

Co-advisor Name

Brian

Co-advisor Middle Initial

W.

Co-advisor Last Name

Whitcomb

Third Advisor Name

Carol

Third Advisor Last Name

Bigelow

Abstract

Approximately 80% of reproductive age women experience physical or emotional symptoms prior to onset of menses. Of these women, approximately 20% experience symptoms severe enough to interfere with social functioning and life activities and meet criteria for premenstrual syndrome (PMS). More than 100 different symptoms are associated with PMS, the most common of which include breast tenderness, headache, anger, and depression. Symptom groupings tend to be stable within an individual but can vary distinctly between women. Potential differences in the etiology of symptoms suggest that PMS should not be considered a single condition in research or clinical studies, but rather may represent distinct entities that group by symptom patterns. The primary goal of this study was to identify symptom patterns using factor and cluster analysis. Analysis included: 1) a cohort of healthy women aged 18-30 (n =414); and 2) the subgroup of women meeting established criteria for PMS (n=80). All participants provided information on the occurrence and severity of 26 menstrual symptoms by validated questionnaire. Four distinct symptom patterns emerged: Emotional,

Psychological, Physical, and Consumption. Cronbach’s alpha levels demonstrating reliability were high in both the total population (0.71 – 0.90) and in the PMS subset (0.69-0.80). Additionally, cluster analysis identified 4 clusters in both the total population and PMS subset. These symptom patterns were consistent with those identified in prior studies in diverse populations. These observations suggest that distinct subtypes of PMS may exist, and should be considered when recommending treatments and evaluating risk factors.

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