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Predictors of Bone Mass in Perimenopausal Women: A Prospective Study of Clinical Data Using Photon Absorptiometry

Charles W. Slemenda, DrPH; Siu L. Hui, PhD; Christopher Longcope, MD; Henry Wellman, MD; and C. Conrad Johnston Jr, MD
[+] Article and Author Information

Grant Support: By NIH grants AG02927, P01AG05793, and RR00750, and a grant from the Ancient and Accepted Scottish Rite, Valley of Indianapolis.

Requests for Reprints: Charles W. Slemenda, Dr PH, Regenstrief Health Center, Fifth Floor, 1001 West Tenth Street, Indianapolis, IN 46202-2859.

Current Author Addresses: Drs. Slemenda and Hui: Regenstrief Institute, RG/5th floor, 1001 W. 10th St., Indianapolis, IN 46202-2859.

Dr. Longcope: University of Massachusetts Medical School, 55 Lake Avenue North, Worcester, MA 01655.

Dr. Wellman: Indiana University School of Medicine, UH P 018, 926 W. Michigan St., Indianapolis, IN 46202-5253.

Dr. Johnston: Indiana University School of Medicine, EM 421, 545 Barnhill Dr. , Indianapolis, IN 46202-5124.


©1990 American College of PhysiciansAmerican College of Physicians


Ann Intern Med. 1990;112(2):96-101. doi:10.7326/0003-4819-112-2-96
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Study Objective: To determine whether clinically available data on risk factors are adequate to identify perimenopausal women with either low or high bone mass.

Design: Cross-sectional observational study of a cohort of perimenopausal women (mean age, 50. 8 years).

Setting: Community volunteers in a university hospital.

Subjects: One hundred twenty-four white volunteers established as perimenopausal by history and serum concentrations of estrogens and follicle-stimulating hormone.

Measurements and Main Results: Models were constructed to predict bone mass in the radius, lumbar spine, and hip using risk factors (age, height, weight, calcium and caffeine intake, alcohol and tobacco use, and urinary markers of bone turnover). Although highly significant predictive models were developed for all skeletal sites, none of the models correctly identified more than 70% of women with low bone mass at any site. However, for the radius, a model was constructed that never overestimated bone mass by more than 0.10 g/cm. A small subgroup (7%) with short stature, low body weight, low calcium intake, and who were heavy smokers always had low radial bone mass. Using these models, about 30% of our population could be assessed without bone mass measurements. Predictions for the spine and femur were less efficient, suggesting that direct measurements are required if therapy decisions are to be based on bone mass at these sites.

Conclusions: Risk factors for osteoporosis are of limited use in identifying women with low bone mass around the time of menopause. Measurements of bone mass are probably necessary if the risk for osteoporosis is to be the basis for deciding on estrogen replacement therapy.

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