Objective

Previous studies describing menses duration and heaviness of flow during the menopausal transition (MT) have been short in duration and limited to white women. We estimated the frequency of and risk factors for prolonged bleeding, spotting and heavy bleeding during the MT in an ethnically diverse population.

Design

Prospective community-based cohort study.

Setting usa

southeastern Michigan, northern California and Los Angeles, California.

Population

A total of 1320 midlife women who participated in the Study of Women's Health Across the Nation (SWAN) Menstrual Calendar Substudy. Participants included African-American, white, Chinese, and Japanese women.

Methods

Women completed daily menstrual calendars from 1996 to 2006, and provided information on hormone therapy, smoking and physical activity. Annual measures included height and weight. Kaplan-Meier survival analysis and multivariable regression were used to analyse the data.

Main outcome measures

Menses of 10+ days, spotting of 6+ days, heavy bleeding of 3+ days.

Results

At least three occurrences of menses 10+ days was reported by 77.7% (95% confidence interval [95% CI] 56.7-93.2), of 6+ days of spotting by 66.8% (95% CI 55.2-78.0) and of 3+ days of heavy bleeding by 34.5% (95% CI 30.2-39.2) of women. Menses of 10+ days, 6+ days of spotting, and 3+ days of heavy bleeding were associated with MT stage, uterine fibroids, hormone use and ethnicity. Body mass index was associated with 3+ days of heavy bleeding.

Conclusions

These data provide clinicians and women with important information about the expected frequency of prolonged and heavy bleeding and spotting during the menopausal transition that may facilitate clinical decision making.

The sensitivity and specificity of a urinary pregnanediol-3-glucuronide (PdG) ratio algorithm to identify anovulatory cycles was studied prospectively in two independent populations of women. Urinary hormone data from the first group was used to develop the algorithm, and data from the second group was used for its validation. PdG ratios were calculated by a cycles method in which daily PdG concentrations indexed by creatinine (CR) from cycle day 11 onward were divided by a baseline PdG (average PdG/Cr concentration for cycle days 6-10). In the interval method, daily PdG/CR concentrations from day 1 onward were divided by baseline PdG (lowest 5-day average of PdG/CR values throughout the collection period). Evaluation of the first study population (n = 6) resulted in cycles with PdG ratios > or = 3 for > or = 3 consecutive days being classified as ovulatory; otherwise they were anovulatory. The sensitivity and specificity of the PdG ratio algorithm to identify anovulatory cycles in the second population were 75% and 89.5%, respectively, for all cycles (n = 88); 50% and 88.3% for first cycles (n = 40) using the cycles method; 75% and 92.2%, respectively, for all cycles (n = 89); and 50% and 94.1% for first cycles (n = 40) using the interval method. The "gold standard" for anovulation was weekly serum samples < or = 2 ng/ml progesterone. The sensitivity values for all cycles and for the first cycle using both methods were underestimated because of apparent misclassification of cycles using serum progesterone due to infrequent blood collection. Blood collection more than once a week would have greatly improved the sensitivity and modestly improved the specificity of the algorithm. The PdG ratio algorithm provides an efficient approach for screening urine samples collected in epidemiologic studies of reproductive health in women.

Introduction: We examined the association between mammographic density and single-nucleotide polymorphisms (SNPs) in genes encoding CYP1A1, CYP1B1, aromatase, 17β-HSD, ESR1, and ESR2 in pre- and early perimenopausal white, African-American, Chinese, and Japanese women.Methods: The Study of Women's Health Across the Nation is a longitudinal community-based cohort study. We analyzed data from 451 pre- and early perimenopausal participants of the ancillary SWAN Mammographic Density study for whom we had complete information regarding mammographic density, genotypes, and covariates. With multivariate linear regression, we examined the relation between percentage mammographic breast density (outcome) and each SNP (primary predictor), adjusting for age, race/ethnicity, parity, cigarette smoking, and body mass index (BMI).Results: After multivariate adjustment, the CYP1B1 rs162555 CC genotype was associated with a 9.4% higher mammographic density than the TC/TT genotype (P = 0.04). The CYP19A1 rs936306 TT genotype was associated with 6.2% lower mammographic density than the TC/CC genotype (P = 0.02). The positive association between CYP1A1 rs2606345 and mammographic density was significantly stronger among participants with BMI greater than 30 kg/m2than among those with BMI less than 25 kg/m2(Pinteraction= 0.05). Among white participants, the ESR1 rs2234693 CC genotype was associated with a 7.0% higher mammographic density than the CT/TT genotype (P = 0.01).Conclusions: SNPs in certain genes encoding sex steroid metabolism enzymes and ESRs were associated with mammographic density. Because the encoded enzymes and ESR1 are expressed in breast tissue, these SNPs may influence breast cancer risk by altering mammographic density. © 2009 Crandall; licensee BioMed Central Ltd.