Screening for osteoporosis by bone densitometry: A stratified intervention approach

Abstract

We have performed computer modelling of the relationship between bone mass, age and hip fracture in a conditional probability model using a notional population of 100 000 postmenopausal women aged 50 who have their bone density measured once. The computer model very closely reproduced the actual number of fractures in a Western Australian population. Intervention to bone loss completely in subjects with the lowest bone density (below 1 SD below the mean) would prevent 0.42 of a hip fracture per patient treated if the whole population were treated. Halving the rate of bone loss in the whole population would reduce hip fracture by two-thirds. These data suggest that hormone replacement therapy, which is the most effective therapy for preventing bone loss but which has the most side effects, should be focused on subjects with bone mass below 1 SD below the mean. The remainder of the population could be targeted with a public health campaign based on the lifestyle factors of increased dietary calcium and exercise which have been shown to slow but not stop bone loss.