Predictor Of Bone Mass Research Articles

Effect of ethnicity and sex on the growth of the axial and appendicular skeleton of children living in a developing country

Bones in the axial and appendicular skeletons exhibit heterogeneous growth patterns between different ethnic and sex groups. However, the influence of this differential growth on the expression of bone mineral content is not yet established. The aims of the present study were to investigate: 1) whether there are ethnic and sex differences in axial and appendicular dimensions of South African children; and 2) whether regional segment length is a better predictor of bone mass than stature. Anthropometric measurements of stature, weight, sitting height, and limb lengths were taken on 368 black and white, male and female 9-year-old children. DXA (dual-energy x-ray absorptiometry) scans of the distal ulna, distal radius, and hip and lumbar spine were also obtained. Analyses of covariance were performed to assess differences in limb lengths, adjusted for differences in stature. Multiple regression analyses were used to assess significant predictors of site-specific bone mass. Stature-adjusted means of limb lengths show that black boys have longer legs and humeri but shorter trunks than white boys. In addition, black children have longer forearms than white children, and girls have longer thighs than boys. The regression analysis demonstrated that site-specific bone mass was more strongly associated with regional segment length than stature, but this had little effect on the overall pattern of ethnic and sex differences. In conclusion, there is a differential effect of ethnicity and sex on the growth of the axial and appendicular skeletons, and regional segment length is a better predictor of site-specific bone mass than stature.

LRP5 gene polymorphisms predict bone mass and incident fractures in elderly Australian women

Postmenopausal osteoporosis and bone mass are influenced by multiple factors including genetic variation. The importance of LDL receptor-related protein 5 (LRP5) for the regulation of bone mass has recently been established, where loss of function mutations is followed by severe osteoporosis and gain of function is related to increased bone mass. The aim of this study was to evaluate the role of polymorphisms in the LRP5 gene in regulating bone mass and influencing prospective fracture frequency in a well-described, large cohort of normal, ambulatory Australian women. A total of 1301 women were genotyped for seven different single nucleotide polymorphisms (SNPs) within the LRP5 gene of which five were potentially informative. The effects of these gene polymorphisms on calcaneal quantitative ultrasound measurements (QUS), osteodensitometry of the hip and bone-related biochemistry was examined. One SNP located in exon 15 was found to be associated with fracture rate and bone mineral density. Homozygosity for the less frequent allele of c.3357A > G was associated with significant reduction in bone mass at most femoral sites. The subjects with the GG genotype, compared to the AA/AG genotypes showed a significant reduction in BUA and total hip, femoral neck and trochanter BMD (1.5% P = 0.032; 2.7% P = 0.047; 3.6% P = 0.008; 3.1% P = 0.050, respectively). In the 5-year follow-up period, 227 subjects experienced a total of 290 radiologically confirmed fractures. The incident fracture rate was significantly increased in subjects homozygous for the GG polymorphism (RR of fracture = 1.61, 95% CI [1.06–2.45], P = 0.027). After adjusting for total hip BMD, the fracture rate was still increased (RR = 1.67 [1.02–2.78], P = 0.045), indicating factors other than bone mass are of importance for bone strength. In conclusion, genetic variation in LRP5 seems to be of importance for regulation of bone mass and osteoporotic fractures.

A two‐year prospective controlled study of bone mass and bone turnover in children with early juvenile idiopathic arthritis

To explore early changes and predictors of bone mass in children with juvenile idiopathic arthritis (JIA) in order to identify patients who will develop bone mass reductions. We conducted a prospective cohort study of 108 children with early JIA (ages 6-18 years; mean disease duration 19.3 months) who were individually matched with 108 healthy children for age, sex, race, and county of residence. Bone mass and changes in total body, spine, femur, and forearm bone mineral density and bone mineral content (BMC), body composition, growth, and biochemical parameters of bone turnover were examined at baseline and at followup a mean of 24 months later. Low bone mass was defined as a Z score >1 SD below the reference population. Of the 200 children evaluated at followup, the 100 healthy children had greater gains in total body BMC (P = 0.035), distal radius BMC (P < 0.001), and total body lean mass (P < 0.001) than did the 100 JIA patients. Low or very low total body BMC was observed in 24% of the patients and 12% of the healthy children. Bone formation, bone resorption, and weight-bearing activities were reduced in the patients compared with the healthy children. Multiple regression analysis showed that in patients with JIA, serum bone-specific alkaline phosphatase, serum C-telopeptide of type I collagen, and weight-bearing activities were independent predictors of changes in total body BMC. Total body BMC was lower in patients with polyarticular onset than in those with oligoarticular disease onset. Patients with JIA have moderate reductions in bone mass gains, bone turnover, and total body lean mass early in the disease course.

Osteoporosis for the home care physician. Part 1: etiology and current diagnostic strategies.

Osteoporosis affects over 20 million individuals in North America and is responsible for over 1.5 million fractures in the US. Although most cases of osteoporosis are primary, in 20% of older women and 40% of older men presenting with vertebral fractures, a secondary cause can be identified. The WHO based the diagnosis of postmenopausal osteoporosis on the presence of BMD T-score that is 2.5 standard deviations or greater below the mean for young women. The International Society of Clinical Densitometry defined male osteoporosis as BMD T-score of 2.5 or greater below the mean for young men. BMD assessment at the hip and spine by DXA is the standard procedure to assess bone density. Laboratory testing in patients with low BMD is performed to exclude other conditions that could cause low BMD such as multiple myeloma, endocrinopathies and osteomalacia. Bone turnover marker levels currently do not predict bone mass or fracture risk and are only weakly associated with changes in bone mass. Subsequently, they are of limited use in the clinical evaluation of bone density changes.

Osteoporosis for the Home Care Physician, Part 1: Etiology and Current Diagnostic Strategies

Osteoporosis affects over 20 million individuals in North America and is responsible for over 1.5 million fractures in the US. Although most cases of osteoporosis are primary, in 20% of older women and 40% of older men presenting with vertebral fractures, a secondary cause can be identified. The WHO based the diagnosis of postmenopausal osteoporosis on the presence of BMD T-score that is 2.5 standard deviations or greater below the mean for young women. The International Society of Clinical Densitometry defined male osteoporosis as BMD T-score of 2.5 or greater below the mean for young men. BMD assessment at the hip and spine by DXA is the standard procedure to assess bone density. Laboratory testing in patients with low BMD is performed to exclude other conditions that could cause low BMD such as multiple myeloma, endocrinopathies and osteomalacia. Bone turnover marker levels currently do not predict bone mass or fracture risk and are only weakly associated with changes in bone mass. Subsequently, they are of limited use in the clinical evaluation of bone density changes.

The effect of physical activity and its interaction with nutrition on bone health.

Physical activity (PA) is a popular therapy for the prevention and treatment of bone loss and osteoporosis because it has no adverse side effects, it is low cost, and it confers additional benefits such as postural stability and fall prevention. Bone mass is regulated by mechanical loading, and is limited but not controlled by diet. The mechanism by which strain thresholds turn bone remodelling 'on' and 'off' is known as the mechanostat theory. Research in animals has shown that optimal strains are dynamic, with a high change rate, an unusual distribution and a high magnitude of strain, but the results of randomized controlled trials in human subjects have been somewhat equivocal. In the absence of weight-bearing activity nutritional or endocrine interventions cannot maintain bone mass. Biochemical markers of bone turnover predict bone mass changes, and findings from our research group and others have shown that both acute and chronic exercise can reduce bone resorption. Similarly, Ca intervention studies have shown that supplementation can reduce bone resorption. Several recent meta-analytical reviews concur that changes in bone mass with exercise are typically 2-3%. Some of these studies suggest that Ca intake may influence the impact of PA on bone, with greater effects in Ca-replete subjects. Comparative studies between Asian (high PA, low Ca intake) and US populations (low PA, high Ca intake) suggest that PA may permit an adaptation to low Ca intakes. Whether Ca and PA interact synergistically is one of the most important questions unanswered in the area of lifestyle-related bone health research.

A Clinical Prediction Rule to Identify Premenopausal Women with Low Bone Mass

Identifying premenopausal women at risk for osteoporosis and related fractures is a potentially important way to reduce the burden of illness from this disease as low peak bone mass is a risk factor for postmenopausal osteoporosis. We examined predictors of 'low' peak bone mass in 668 healthy, pre-menopausal, Caucasian women ages 18-35 years. Predictors of bone mass were assessed using a detailed, standardized interview. Bone mass was assessed using two measures: dual-energy X-ray absorptiometry (DXA) at the femoral neck and lumbar spine, and quantitative ultrasound (QUS) of the heel, which evaluates stiffness, speed of sound (SOS) and broadband ultrasound attenuation (BUA). Bone mass was considered 'low' if the corresponding Z-score was <-1.00 (DXA values, stiffness) or if values were in the lowest quintile (BUA, SOS). Using multivariate logistic regression modeling, predictors of low bone mass based on QUS, DXA or both were determined. The mean age of the cohort was 27.3 years. Independent predictors of low bone mass by both DXA and QUS were: low body weight, menarche at age 15 years or later and physical inactivity as an adolescent. Individuals with all three risk factors had a 92% chance of having low bone mass using both techniques. This suggests that a simple risk factor assessment can identify most young women with low peak bone mass. Early intervention in this group of women may reduce the risk for osteoporosis in later life.

Predictors of bone mass by peripheral quantitative computed tomography in early adolescent girls.

This cross-sectional study used peripheral quantitative computed tomography (pQCT) to evaluate the influences of age, body size, puberty, calcium intake, and physical activity on bone acquisition in healthy early adolescent girls. The pQCT technique provides analyses of volumetric bone mineral density (vBMD) (mg/cm(3)) for total as well as cortical and trabecular bone compartments and bone strength expressed as polar strength strain index (mm(2)). Bone mass of the nondominant distal and midshaft tibia by pQCT and lumbar spine and hip by dual X-ray absorptiometry (DXA) were measured in 84 girls ages 11-14 yr. Pubertal stage, menarche status, anthropometrics, and 3-d food intake and physical activity records were collected. Total and cortical bone mineral content and vBMD measurements by pQCT were significantly related to lumbar spine and femoral neck BMD measurements by DXA. We did not note any significant determinants or predictors for trabecular bone mass. Body weight was the most important predictor and determinant of total and cortical bone density and strength in healthy adolescent girls. Menarche, calcium intake, height, body mass index, and weight-bearing physical activity level age were also identified as minor but significant predictors and determinants of bone density and strength. Bone measurements by the pQCT technique provide information on bone acquisition, architecture, and strength during rapid periods of growth and development. Broader cross-sectional studies using the pQCT technique to evaluate the influence of age, gender, ethnicity, puberty, body size, and lifestyle factors on bone acquisition and strength are needed.

Early response in biochemical markers predicts long-term response in bone mass during hormone replacement therapy in early postmenopausal women

Based on data from 153 early postmenopausal women who completed a double-blind, randomized 3 year study of graded hormone replacement therapy (HRT) doses or placebo, we investigated the value of bone markers to predict prevention of bone loss. Absolute values of serum and urinary CrossLaps (S-CTX and U-CTX) after 2 weeks of treatment were significantly correlated to 3 year bone mass response ( r = −0.28/−0.35; p < 0.001). These associations were fully expressed at 6 months ( r = −0.61/−0.64; p < 0.001). Receiver operating characteristic analyses revealed that the predictive capacity of one measurement of a resorption marker after 6 months’ treatment performed similarly as assessment of hip bone mass over 3 years in predicting preservation of spinal bone mass over 3 years. Comparable results were obtained using percent change from baseline in resorption markers at both 6 and 12 months, whereas for formation markers percent change was superior to absolute value at 6 months but not at 12 months. Values of accuracy for S-CTX for a cutoff of 1881 pmol/L at 6 months were 85.2% (sensitivity), 74.3% (specificity), 90.5% (positive predictive value), and 63.4% (negative predictive value); U-CTX performed similarly, whereas the values for the formation markers were slightly lower. A cutoff for S-CTX of 1245 pmol/L eliminated false-positive individuals (those who had a decrease below the cutoff but lost bone). In the false-negative group, which was composed of individuals whose S-CTX did not decrease below the cutoff but had preserved bone mass, S-CTX was significantly associated with spinal bone mass response ( r = −0.41; p < 0.01), indicating these women had been treated with a dose that was not at its optimum for their individual bone turnover. For this cutoff, the values were 49.5% (sensitivity), 97.1% (specificity), 98% (positive predictive value), and 40% (negative predictive value). In conclusion, early bone marker measurements predict long-term preservation of bone mass during HRT. Resorption markers seem superior to formation markers, which reflects that the primary effect of HRT is on bone resorption. A strategy with two cutoff levels may optimize the use of bone markers to predict bone mass response. Whether resorption markers can be used to guide individualized treatment remains to be investigated.

A Noninvasive Measure of Physical Maturity as a Predictor of Bone Mass in Children

Objective: The purpose of this study was to describe the accumulation of whole body bone mass in a longitudinal study of prepubertal boys and girls using Rochersquo;s physical maturity index as a measure of developmental age.Methods: We measured 561 children (39% white, 61% African-American) from a suburban school district, representing an ethnically mixed, middle-class community adjacent to Detroit. Anthropometric measures taken for the present study included recumbent length (cm), stature (cm), weight (kg), whole body bone mineral content (WBBMC in g) and a noninvasive measure of physical maturity (PM%). PM% was calculated from published formulae derived from data from the Fels Longitudinal Study, using recumbent length, weight, midparental stature, age, and age- and gender-specific regression coefficients.Results: At average age 9.9 (±0.6) years, there were no significant gender differences in stature, recumbent length, weight, or WBBMC in either ethnic group. Average PM for girls was significantly greater than that for boys within each ethnic group. There were no significant ethnic differences in PM in either gender. Stature and WBBMC were significantly different in the two ethnic groups for both boys and girls. Regressions of WBBMC on PM and chronological age indicated that PM explained more of the variance in WBBMC than did age (r2 ranging from 0.28 to 0.75 for PM versus 0.01 to 0.06 for age). In the case of African-American boys, r2 was similar (0.09 for PM and 0.06 for age).Conclusions: PM is a useful, noninvasive measure of developmental age that is significantly correlated with bone mass in children. Our study also indicates that PM is a better predictor of WBBMC than chronological age. Because PM can be calculated without using invasive and potentially expensive methods, PM may be useful in some clinical as well as research settings.

Bone mineral density, collagen type 1 alpha 1 genotypes and bone turnover in premenopausal women with diabetes mellitus.

Osteopenia is a recognised complication of diabetes mellitus which could be due to abnormal bone turnover or disturbances in the calcium/parathyroid hormone/vitamin D axis or both. Genetic factors also play an important part in determining bone mass although this has not been studied in diabetes. Recently a polymorphism of the collagen type 1 alpha 1 (COL1A1) gene has been shown to be associated with low bone mass in British women. To identify subjects with diabetes who may be at risk of developing osteoporosis and fractures, we analysed bone mineral density in relation to the biochemical markers of bone turnover, calcium homeostasis and the COL1A1 genotype in a group of premenopausal women with Type I (insulin-dependent) diabetes mellitus (n = 31), Type II (non-insulin dependent) diabetes mellitus (n = 21) and control subjects (n = 20). Bone mineral density was lower at the femoral neck in the subjects with Type I diabetes (p = 0.08) as were serum 25-hydroxyvitamin D compared with control subjects (p = 0.023) and this was negatively correlated with serum collagen type 1 C-terminal propeptide (r = -0.56, p < 0.001). Bone mineral density in Type II diabetes was not different from control subjects, after correction for body mass index. Bone resorption was, however, raised in the Type II diabetic subjects as reflected by the higher urinary deoxypyridinoline values (p = 0.016) and lower collagen type 1 C-terminal propeptide:deoxypyridinoline ratio (p = 0.04). In the whole group studied, subjects with the COL1A1 's' genotype had lower bone mineral density at the femoral neck (p = 0.01) which was partly attributable to a lower body mass index. Following multiple regression analysis body mass index and collagen type 1 C-terminal propeptide concentrations remained determinants of bone mass at all three sites, whereas genotype appeared to be a predictor of bone mass at the femoral neck only. We conclude that measurement of these variables could prove useful in firstly identifying those diabetic women at risk of osteoporosis and secondly guiding therapeutic intervention.

Dietary calcium, protein, and phosphorus are related to bone mineral density and content in young women

Dietary factors have been implicated in modifying bone health, although the results remain controversial, particularly in young women. The objective of the study was to determine relations of selected dietary factors and anthropometric measurements to bone mineral density (BMD) of the spine, femoral neck, trochanter, Ward's triangle, radius, and total body and the bone mineral content (BMC) of the spine, radius, and total body. The study was a cross-sectional analysis of 215 women aged 18-31 y. Weight, height, and lean mass were correlated with bone mineral measures at every site (r = 0.17-0.78). Postmenarcheal age (years since onset of menses) was positively correlated with total-body BMD and BMC, radius BMD and BMC, and spine BMC, and negatively correlated with Ward's triangle BMD. Radius BMD was correlated with protein, calcium, and phosphorus intakes, and spine BMD and BMC were correlated with energy, protein, calcium, and phosphorus intakes. These correlations remained significant when postmenarcheal age, lean mass, and fat mass were controlled. A pattern emerged in multiple regression analyses that showed a complex relation among calcium, protein or phosphorus, and the calcium-protein or calcium-phosphorus ratio and spine or total-body BMC and BMD. All 3 variables (calcium, protein or phosphorus, and calcium-protein or calcium-phosphorus ratio) were required in the model for significance. Anthropometric measures were predictors of bone mass. A single ratio of calcium to phosphorus or protein did not optimize bone mass across the range of calcium intakes.

Relation of Nutrition, Body Composition and Physical Activity to Skeletal Development: A Cross-Sectional Study in Preadolescent Females

Objective: To examine the relation of anthropometric and growth parameters (weight, stature, body composition, age, and skeletal age), nutritional factors, and physical activity to the total body and radius bone mineral density and content and radiogrammetry parameters of the second metacarpal.Study design: The study was a cross-sectional evaluation of 456 healthy, Caucasian girls, ages 8 to 13 years. Multiple regression models were created based on Cp statistics to determine the association between bone parameters and various independent variables.Results: Mean calcium intake was 956±381 mg/day, about 20% below the RDA of 1200 mg/day and about 36% below the threshold intake of approximately 1500 mg/day. The most significant predictors for total body and radius bone mineral density were corresponding bone areas, lean body mass, body fat, skeletal age, dietary calcium, and stature (only for total body) with corresponding R2(adjusted) of 48% and 36%. The total body and radius bone mineral content was positively associated with corresponding bone areas, lean body mass, body fat, calcium intake, and skeletal age with corresponding R2(adjusted) of 86% and 72%. Energy expenditure (corrected for BMI) was stratified into quartiles and bone mass parameters were distributed accordingly. A statistically significant difference in total body and radius bone mineral density and content was noted between the fourth and lower quartiles (ANOVA, p<0.05 to p<0.0001).Conclusion: The most significant predictors of bone mass in preadolescent females evaluated in this study are bone area, lean body mass, body fat, skeletal age and dietary calcium.

Epidemiology and predictors of fractures associated with osteoporosis

Approximately 40 in 100 women will experience one or more fractures after the age of 50 years. At 50 years for women the lifetime risk is 17.5% for hip fracture, 16% for vertebral fracture, and 16% for Colles' fracture; for men, the respective lifetime risks are 6%, 5%, and 2.5%. The incidence of hip fractures has increased in recent years in most but not all European countries, partly as a result of the aging of the population. However, the age-adjusted incidence has also increased in several countries. The age-adjusted incidence of hip fractures varies greatly between European countries; in women incidence varies from about 50 per 10,000 women in Malta and Poland to 500 per 10,000 in Sweden. In addition, the sex ratio (female: male) varies from 1.6 in Poland to 4.2 in Iceland. A proportion of this large variation may be the result of underreporting of cases, although most European countries now have an adequate hospital registration. The prevalence of vertebral deformities also shows geographic variation. In the multinational European Vertebral Osteoporosis Study, a population-based study, the prevalence of vertebral deformities was similar among men and women at ages 65–69 years (12–13%); at younger ages the prevalence was higher in men than women, whereas the reverse was true at older ages. Incidence data on vertebral fractures are scarce because a large proportion of vertebral fractures are not clinically diagnosed. Prospective epidemiologic studies indicate that bone mineral density (BMD) is the single best predictor of fractures in perimenopausal women. Historic risk factors do not predict bone mass (or fractures) with sufficient precision to be useful in assessment of fracture risk or BMD. However, the presence of one vertebral fracture doubles the risk of future vertebral fracture as assessed by a BMD measurement. At advanced ages, other risk factors may be more important, such as the risk of falling, and combinations of risk factors for falls and low BMD may predict hip fractures. Risk factor assessment is currently of less value for the prediction of other fractures, such as vertebral or Colles' fracture. Determining the causes of the large geographic differences in hip fracture incidence and the large differences in sex ratios for hip fractures in European countries could lead to identification of hitherto unknown risk factors and provide clues for prevention of fractures. Many risk factors cannot be prevented or modified; however, these risk factors (for example, family history, past fracture, and visual loss) can identify risk groups amenable to drug treatment or to preventive measures such as protective hip pads or environmental changes. Assessment of risk factors and definition of risk profiles are important steps toward the prevention of fractures in the elderly.

MAXIMUM LEG POWER BEST PREDICTS FEMORAL NECK AND LUMBAR SPINE BMD IN 14-YEAR OLD GIRLS 878

Research has demonstrated that body weight best predicts bone mineral density and content in adolescents. Little is known about the associations between bone mass of the appendicular and axial skeleton and measures of body composition, muscle strength and muscular power and in adolescent girls. This cross-sectional study examined these relationships in 39 high school girls(age=14.6±0.5 y; 61.2±14.3 kg; 164.4±5.9 cm; 24.7±6.7% fat) who averaged 1.8±1.2 years past menarche. Bone mineral content (BMC) and bone mineral density (BMD) were assessed at the whole body, lumbar spine, femoral neck, and femoral mid-shaft by dual energy x-ray absorptiometry (Hologic QDR-1000/W). Strength of the left knee extensors was measured by isokinetic dynamometry (Kin-Com 500H) and maximum leg power was assessed using the Wingate Anaerobic Power Test with the workload set at 7.5% of body weight. Stepwise multiple regression, which included whole body lean mass, whole body fat mass, maximum knee extensor force, maximum leg power, and years past menarche revealed that lean mass and fat mass independently predicted whole body BMC (R2=0.87, p<0.0001), but that lean mass was the strongest predictor (β=0.73 vs. 0.29). At the femoral midshaft, whole body lean mass was the only independent predictor of BMD(R2=0.36, p<0.0001). Using the same regression model, maximum power was the single independent predictor of femoral neck BMD (R2=0.39, p<0.0001) and lumbar spine BMD (R2=0.13, p<0.026). In conclusion, results from this preliminary study indicate that whole body lean mass best predicts bone mass of the appendicular skeleton in 14-year old girls, whereas bone of the axial skeleton in this population is best predicted by maximum leg power. Further, these results suggest that the most important component of weight and its relationship to bone is lean, not fat mass.

Not all postmenopausal women on chronic steroid treatment are osteoporotic: Predictors of bone mass

Not all postmenopausal women on chronic steroid treatment are osteoporotic: Predictors of bone mass

Lean body mass and muscle strength as predictors of bone mass in young women

Lean body mass and muscle strength as predictors of bone mass in young women

Black-White Differences in Serum Sex Hormones and Bone Mineral Density

To determine if differences in serum sex hormones contribute to racial differences in bone mass, independent of obesity, the authors compared bone mass and sex steroid hormone levels in 273 white women and 86 black women aged 65 years or older. This study was ancillary to the Study of Osteoporotic Fractures. Black women were recruited at two clinical centers in Baltimore, Maryland, and the Monongahela Valley, near Pittsburgh, Pennsylvania. An age-stratified random sample of white women was chosen from the Pittsburgh clinic. Demographic and historical information and anthropometric measurements were obtained from a clinic questionnaire, interview, and examination. Single photon absorptiometry was obtained at three sites: the distal radius, the proximal radius, and the calcaneus. Serum estrone, androstenedione, and testosterone were measured using extraction, column chromatography, and radioimmunoassay. Serum estrone concentrations were significantly higher and androstenedione levels were significantly lower in black women compared with white women. Racial differences in estrone could be explained largely by differences in the degree of obesity. Bone mass was greater in black women compared with white women within age, body mass index, (kg/m2), and estrone strata. Androgens were not related to bone mass. Within each race, bone mass increased linearly with increasing concentration of serum estrone. There was no interaction between race and serum estrone on bone mass. Each factor contributed independently and significantly to the regression model predicting bone mass. There was no attenuation of the effect of race if estrone was included in the model. In conclusion, race and serum estrone were independent determinants of bone mass.

Can urinary pyridinium crosslinks and urinary oestrogens predict bone mass and rate of bone loss after the menopause?

We measured urinary pyridinoline and deoxy-pyridinoline by high performance liquid chromatography, and urinary oestrogens by radioimmunoassay, in 68 healthy postmenopausal women to evaluate these assays for the prediction soon after the menopause of the risk of developing osteoporotic fractures in later life. Change in forearm bone mineral content was assessed by single photon absorptiometry over 4 years. Although there was no significant correlation between the pyridinium crosslinks and urinary oestrogens, we found that up to 58% of the variation in the rate of loss of bone mineral content in women soon after the menopause could be explained by pyridinoline and oestradiol glucuronide assays together with body mass index. Measurement of the urinary pyridinium crosslinks and oestradiol glucuronide may make a significant contribution to a biochemical screening procedure for future osteoporotic fracture.

A method for estimating the uncertainty of future bone mass

The development of statistical models for estimating fracture probability is a promising method for quantitating and optimizing the clinical utility of bone mass measurements. Earlier models have assumed that future bone mass could be predicted exactly and were, therefore, limited to analyses that assume the loss rate is known in advance. Since bone loss rates may vary over time and cannot be predicted accurately, we have developed a new model, based on empirical data, that estimates the degree of uncertainty associated with predicted bone mass. Without a bone mass measurement, the population mean must be assumed for an individual. For the calcaneus, the standard deviation of the population distribution is about 60 mg/cm 2. By measuring bone mass, one can determine how close or far from the mean an individual's true bone mass is, with a standard deviation (SD) of about 3 mg/cm 2. Without a subsequent bone mass measurement, our model predicts that the uncertainty (standard deviation) in calcaneal bone mass will increase approximately sixfold (relative to the reproducibility at the initial measurement) over a period of five years for women under age 60, from 3 mg/cm 2 to 19 mg/cm 2. The five-year increase in uncertainty is approximately fourfold for women over age 60, from 3 to 13 mg/cm 2. However, the uncertainty in bone mass for an individual five years after the initial measurement is still only one third to one fifth that of the entire population, and can be reduced to the initial level by obtaining another measurement. Furthermore, the predicted (or measured) values are usually much better estimates of an individual's true bone mass than simply assuming the population average. This model can be adapted to other types of bone mass measurements, and will find application in cost-effectiveness analyses of osteoporosis treatment and prophylaxis, including estimation of the optimal time interval between bone mass measurements.