Home > Publications . Search All . Browse All . Country . Browse PSC Pubs . PSC Report Series

PSC In The News

RSS Feed icon

Axinn says data show incidents of sexual assault start at 'very young age'

Miech on 'generational forgetting' about drug-use dangers

Impacts of H-1B visas: Lower prices and higher production - or lower wages and higher profits?

More News

Highlights

Call for papers: Conference on computational social science, April 2017, U-M

Sioban Harlow honored with 2017 Sarah Goddard Power Award for commitment to women's health

Post-doc fellowship in computational social science for summer or fall 2017, U-Penn

ICPSR Summer Program scholarships to support training in statistics, quantitative methods, research design, and data analysis

More Highlights

Next Brown Bag

Mon, Feb 13, 2017, noon:
Daniel Almirall, "Getting SMART about adaptive interventions"

Classifying menopause stage by menstrual calendars and annual interviews: need for improved questionnaires

Publication Abstract

Paramsothy, P., Sioban D. Harlow, Michael R. Elliott, L. Lisabeth, S. Crawford, and J.F. Randolph. 2013. "Classifying menopause stage by menstrual calendars and annual interviews: need for improved questionnaires." Menopause, 20(7): 727-35.

OBJECTIVE: This study aims to assess the agreement between the menopausal transition stages defined by annual interviews or annual follicle-stimulating hormone levels and the menopausal transition stages defined by monthly menstrual calendars, as well as factors associated with discordance. METHODS: These analyses used daily self-recorded menstrual calendar data from 1996 to 2006, annual interviews, and annual follicle-stimulating hormone levels. Participants were recruited from four study sites of the Study of Women's Health Across the Nation (Boston, southeastern Michigan, Oakland, and Los Angeles) and four racial/ethnic groups (African American, white, Chinese, and Japanese). Women who had a defined final menstrual period and who never had hormone therapy were included (n = 379). Cohen's kappa statistics for 2 * 2 tables were calculated for two definitions of agreement. Logistic regression was used to identify factors associated with discordance. RESULTS: Poor agreement between annual interview and menstrual calendar data was found for early menopausal transition (kappa = -0.13; 95% CI, -0.25 to -0.02) and late menopausal transition (kappa = -0.18; 95% CI, -0.26 to -0.11). For late stage, Chinese women (odds ratio [OR], 2.16; 95% CI, 1.08 to 4.30), African-American women (OR, 2.39; 95% CI, 1.00 to 5.71), and women with high school education or less (OR, 2.16; 95% CI, 1.08 to 4.30) were more likely to be discordant. Poor agreement between annual follicle-stimulating hormone levels and menstrual calendars was also found for early menopausal transition (kappa = -0.44; 95% CI, -0.57 to -0.30) and late menopausal transition (kappa = -0.32; 95% CI, -0.42 to -0.23). CONCLUSIONS: New questions need to be developed to accurately identify the start of the menopausal transition and should be evaluated in a multiethnic population with varying educational backgrounds.

DOI:10.1097/GME.0b013e3182825ff2 (Full Text)

PMCID: PMC3686995. (Pub Med Central)

Browse | Search : All Pubs | Next