Prediction Model for Reduced Bone mass in Women using Individual Characteristics & Life Style Factors

여성의 개인적 특성과 생활양식요인을 이용한 골량감소 예측모형

This study was carried out to identify the Important modifiable risk factors for reduced bone mass and to construct prediction model which can classify women with either low or high bone mass. Through the literature review, individual characteristics such as age, body weight, height, education level, family history, age of menarche, postmenopausal period, gravity, parity, menopausal status, and breast feeding period were identified and factors of life style such as past milk consumption, past physical activity, present daily activity, present calcium intake, alcohol intake, cigarette smoking, coffee consumption were identified as influencing factors of reduced bone mass in women. Four hundred and eighty women aged between 28 and 76 who had given measurement bone mineral density by dual energy x-ray absortiometry in lumbar vertebrae and femur from July to October, 1997 at 4 general hospitals in Seoul and Pusan were selected for this study. Women were excluded if they had a history of any chronic illness such as rheumatoid arthritis, diabetes mellitus, hyperthroidism, & gastrointestinal disorder and any medication such as calcium supplements, calcitonin, estrogen, thyroxine, antacids, & corticosteroids known affect bone. As a result of these exclusion criteria, four hundred and seventeen women were used for analysis. Multiple logistic regression model was developed for estimating the likelihood of the presence or absence of reduced bone mass. A SAS procedure was used to estimate risk factor coefficient. The results are as follows For lumbar spine, the variables significant were age, body weight, menopause status, daily activity, past milk consumption, and past physical activity(p<0.01), while for femoral Ward's triangle, age, body weight, level of education, past milk consumption, past physical activity(p<0.001). Past physical activity, present daily activity and past milk consumption are the most powerful modifiable predictors in vertebrae and femur among the predictors. When the model performance was evaluated by comparing the observed outcome with predicted outcome, the model correctly identified 74.1% of persons with reduced bone mass and 84.5% of persons with normal bone mass in the lumbar vertebrae and 82.9% of persons with reduced bone mass and 75.0% of persons with normal bone mass in the femoral Ward's triangle. On the basis of these results, a number of recommendations for the management of reduced bone mass may be made : First, those woman who are classified as high risk group of the reduced bone mass in the prediction model should examine the bone mineral density to further examine the usefulness of this model. Second, the optimal amount of milk consumption and a regular weight bearing exercise in childhood, adolescence, and early adult should be ensured.