The DOI matches its Crossref record; 13 of the 13 references it cites were found in a registry or an index.
Predictors of Bone Mass in Perimenopausal Women: A Prospective Study of Clinical Data Using Photon Absorptiometry
Abstract
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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Cites
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EPIDEMIOLOGY OF OSTEOPOROSIS AND OSTEOPOROTIC FRACTURES
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Age and bone mass as predictors of fracture in a prospective study.
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Self-citationModifications of a specific assay for hydroxyproline in urine
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Baseline Measurement of Bone Mass Predicts Fracture in White Women
Hui, S. L., Slemenda, C. W., & Johnston, C. C. (1989) · Annals of Internal Medicine · doi:10.7326/0003-4819-111-5-355 · Cited by 580
Self-citationNUTRIENT SOURCES IN THE AMERICAN DIET: QUANTITATIVE DATA FROM THE NHANES II SURVEY
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Cited by
Garvey, W. T., Mechanick, J. I., Brett, E. M., Garber, A. J., Hurley, D. L., Jastreboff, A. M., Nadolsky, K., Pessah-Pollack, R., & Plodkowski, R. (2016) · Endocrine Practice · doi:10.4158/ep161365.gl · Cited by 1,914
Effects of caffeine on human health
Nawrot, P., Jordan, S., Eastwood, J., Rotstein, J., Hugenholtz, A., & Feeley, M. (2003) · Food Additives and Contaminants · doi:10.1080/0265203021000007840 · Cited by 1,199
Pre-Existing Fractures and Bone Mass Predict Vertebral Fracture Incidence in Women
Ross, P. D., Davis, J. W., Epstein, R. S., & Wasnich, R. D. (1991) · Annals of Internal Medicine · doi:10.7326/0003-4819-114-11-919 · Cited by 1,107
Effects of weight and body mass index on bone mineral density in men and women: The framingham study
Felson, D. T., Zhang, Y., Hannan, M. T., & Anderson, J. J. (1993) · Journal of Bone and Mineral Research · doi:10.1002/jbmr.5650080507 · Cited by 987
Villareal, D. T., Apovian, C. M., Kushner, R. F., & Klein, S. (2005) · The American Journal of Clinical Nutrition · doi:10.1093/ajcn/82.5.923 · Cited by 880
Metadata
- Authors
- Slemenda, C. W., Hui, S. L., Longcope, C., Wellman, H., & Johnston, C. C.
- Venue
- Annals of Internal Medicine
- Publisher
- American College of Physicians
- Published
- 1990-01-15
- Volume
- 112
- Issue
- 2
- Pages
- 96-101
- ISSN
- 0003-4819 (ISSN-L)
- 1539-3704
- OpenAlex
- W1982376401
- Cited by
- 276
- References
- 13
- FWCI
- 24.64
- Type
- journal article
- Language
- en
- Open access
- closed
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- Slemenda, C. W., Hui, S. L., Longcope, C., Wellman, H., & Johnston, C. C. (1990). Predictors of Bone Mass in Perimenopausal Women: A Prospective Study of Clinical Data Using Photon Absorptiometry. Annals of Internal Medicine. https://doi.org/10.7326/0003-4819-112-2-96
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