Uterine leiomyoma and menstrual cycle characteristics in a population-based cohort study.
BACKGROUND
We examined the association of uterine leiomyoma with menstrual cycle characteristics in a population of non-care-seeking women.


METHODS
This cross-sectional study uses data from the Seveso Women's Health Study (SWHS), a population-based cohort in Italy. Participants included 341 premenopausal women, 30-60 years old, who had an intact uterus and were not pregnant, lactating, or using oral contraception or intra-uterine devices. We examined the presence of any ultrasound-detected uterine leiomyoma in relation to self-reported menstrual cycle length, flow length and heaviness of flow. The association of leiomyoma number, volume, tissue layer location and axial position with menstrual cycle characteristics was also examined.


RESULTS
Uterine leiomyomata were detected in 73 women (21.4%). After adjustment for covariates, the presence of a leiomyoma was not significantly related to menstrual cycle length, flow length or heaviness of flow [odds ratio (OR) for scanty flow =1.9, 95% confidence interval (CI) 0.8-4.3; OR for heavy flow =1.3, 95% CI 0.7-2.5; relative to moderate flow]. Number, volume, tissue layer location (subserosal or intramural) and axial position (anterior or posterior) of the leiomyoma were also not related to menstrual cycle characteristics.


CONCLUSIONS
In this Italian population of women not seeking gynaecological care, menstrual characteristics are not related to leiomyoma.
Marino
J L
JL
School of Public Health, University of California, Berkeley, California 94720-7360, USA.
Eskenazi
B
B
Warner
M
M
Samuels
S
S
Vercellini
P
P
Gavoni
N
N
Olive
D
D
D000328:Adult; D015331:Cohort Studies; D003430:Cross-Sectional Studies; D005260:Female; D006801:Humans; D015994:Incidence; D007558:Italy / Q000453:epidemiology; D007889:Leiomyoma / Q000000981:diagnostic imaging / Q000453:epidemiology / Q000503:physiopathology*; D008597:Menstrual Cycle; D008875:Middle Aged; D017697:Premenopause; D014463:Ultrasonography; D014594:Uterine Neoplasms / Q000000981:diagnostic imaging / Q000453:epidemiology / Q000503:physiopathology*