Predictors for lumbar bone mineral density in premenopausal and postmenopausal women in Korea.
- Author:
Yun Seok YANG
1
;
Heung Tae NOH
Author Information
1. Department of Obstetrics & Gynecology, College of Medicine, Eulji University, Daejeon, Korea.
- Publication Type:Original Article
- Keywords:
Bone mineral density;
Pre-and postmenopause;
Predictor
- MeSH:
Bone Density;
Densitometry;
Female;
Humans;
Korea;
Mass Screening;
Prescriptions;
Risk Factors
- From:Korean Journal of Obstetrics and Gynecology
2008;51(4):429-440
- CountryRepublic of Korea
- Language:English
-
Abstract:
OBJECTIVE: The need for early and correct prescription for bone densitometry led to the research for decision model useful for clinicians to address women to bone densitometry. there are few studies that have focused on both pre- and postmenopausal groups simultaneously in healthy pre-and postmenopausal Korean women. METHODS: The authors analyzed the easily obtained biometrical variables such as factors used at clinical decision rules for BMD testing and evaluated predictive values and robustness of a decision model for prediction of lumbar BMD in total , pre-and postmenopausal Korean women. RESULTS: After stepwise multiple regression analysis, Lumbar BMD in total population is 1.083-0.153 (status of menopause)-0.007 (age of menopause)+0.0039 (body weight) (R2=0.52). Postmenopausal women is 0.563-0.0077 (duration after menopause)+0.0054 (body weight) (R2=0.30) and premenopausal women is 0.23+0.0048 (height) (R2=0.05). Although its validity (52%) in total population was sufficiently high for the prediction of lumbar BMD in clinical settings, In postmenopausal women only 30% of the decision model can be explained by the predictors of bone demineralization which is not completely satisfactory in determining lumbar BMD and in premenopausal women 5% is the very low explanatory value which is necessary for identifying possible factors influencing BMD. CONCLUSIONS: Because of difference in underlying risk, as well as differences in the distribution of different risk factors according to menopausal status, this study present different robustness of prediction models according to menopausal status and suggest that it be need to design prediction models divided by menopausal status. More research is needed for computer-based screening aids useful to clinician which overcome some limitation of our study.
