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American Journal of Epidemiology Advance Access originally published online on January 30, 2007
American Journal of Epidemiology 2007 165(8):936-945; doi:10.1093/aje/kwk090
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American Journal of Epidemiology Copyright © 2007 by the Johns Hopkins Bloomberg School of Public Health All rights reserved; printed in U.S.A.

ORIGINAL CONTRIBUTIONS

Characterizing Daily Urinary Hormone Profiles for Women at Midlife Using Functional Data Analysis

Peter M. Meyer1, Scott L. Zeger2, Siobán D. Harlow3, MaryFran Sowers3, Sybil Crawford4, Judith L. Luborsky5, Imke Janssen1, Daniel S. McConnell3, John F. Randolph6 and Gerson Weiss7

1 Department of Preventive Medicine, Rush University Medical Center, Chicago, IL
2 Department of Biostatistics, Johns Hopkins Bloomberg School of Public Health, Baltimore, MD
3 Department of Epidemiology, University of Michigan School of Public Health, Ann Arbor, MI
4 Division of Preventive and Behavioral Medicine, University of Massachusetts Medical School, Worcester, MA
5 Department of Pharmacology, Rush University Medical Center, Chicago, IL
6 Department of Obstetrics and Gynecology, University of Michigan Medical School, Ann Arbor, MI
7 Department of Obstetrics and Gynecology, New Jersey Medical School, Newark, NJ

Reprint requests to Dr. Peter M. Meyer, Department of Preventive Medicine, 1700 W Van Buren, Suite 470, Chicago, IL 60612-3244 (e-mail: pmeyer{at}rush.edu).

Received for publication January 14, 2005. Accepted for publication October 9, 2006.

The availability of daily hormone values for entire menstrual cycles offers an opportunity to apply new analytic techniques that confirm current knowledge and provide new insights into patterns of changing hormone profiles in women as they transition to the menopause. The Study of Women's Health Across the Nation (SWAN) collected urine samples during 1997–1999 from one menstrual cycle or up to 50 days from 848 women who live in seven cities across the United States. These samples were assayed for the urinary forms of estrogen, progesterone, follicle-stimulating hormone, and luteinizing hormone. The authors used functional data analysis to study variability in the hormone patterns of 572 of the 848 pre- and early-perimenopausal women with evidence of a luteal transition. Functional data analysis enabled the authors to identify asymmetries in women's hormone patterns related to cycle length that are not captured with single hormone value comparisons. Longer cycles were characterized by increasing dyssynchrony between follicle-stimulating hormone and luteinizing hormone in the luteal phase.

hormones; menopause; menstrual cycle; principal component analysis

Abbreviations: FSH, follicle-stimulating hormone; PdG, pregnanediol-glucuronide; SWAN, Study of Women's Health Across the Nation


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