Male osteoporosis has been increasingly recognized as a major global health problem over the last decade. Demographically, its incidence is increasing and expected to keep rising given prolonged life span. Specifically, the prevalence of osteoporosis in Korean men aged 50 years or older was 7.5% according to national health survey data [
We enrolled subjects who had attended a health promotion center in a Jeju university hospital for diverse health examinations from July 2009 to January 2012. They were generally healthy and interested enough in their health to pay for the exams. The variables taken into consideration at the initial stage of designing of the study were as follows based on a review article by Robert [
The BMD was measured at the lumbar spine (L1~L4) and hip (femoral neck, trochanter, ward) and defined as grams per square centimeter. The BMD measurement was made using a densitometry, GE lunar DPX Bravo (USA). T-score was automatically calculated based on manufacturer’s reference data and classified as normal, osteopenia, or osteoporosis according to WHO BMD criteria.
The OST was calculated as follows according to the formula of the Osteoporosis Self-Assessment Tool for Asians (OSTA) [
All statistical analyses were performed using SPSS for window version 17.0 (SPSS Inc., Chicago, IL, USA). Continuous variables were expressed as means and standard deviation using a Student’s
Descriptive characteristics were summarized in Table
Summary of descriptive characteristics of 359 men.
Variables | Mean ± SD or number (%) |
---|---|
Age (years) |
|
Weight (kg) |
|
Height (cm) |
|
BMI (kg/m2) |
|
Current smoker | 139 (38.7) |
Heavy alcohol consumption* | 206 (57.4) |
Exercise† | 256 (71.3) |
|
|
Number of subjects with osteoporosis | 32 (8.9) |
|
|
SD: standard deviation; BMI: body mass index.
Characteristics of subjects according to bone density status.
Normal and osteopenia* |
Osteoporosis* |
|
|
---|---|---|---|
Age (years) |
|
|
0.028 |
Weight (kg) |
|
|
0.002 |
Height (cm) |
|
|
0.565 |
BMI (kg/m2) |
|
|
0.002 |
Current smoker | 120 (36.7) | 19 (59.4) | 0.012 |
Heavy alcohol consumption† | 189 (57.8) | 17 (53.1) | 0.610 |
Exercise‡ | 233 (71.3) | 23 (71.9) | 0.941 |
|
|
|
0.001 |
Data are mean ± standard deviation or number (percent).
BMI: body mass index.
Logistic regression analysis revealed age, weight, and current smoker to be significant variables to predict the presence of osteoporosis in study population both before and after controlling for all five variables: age, weight, current smoker, heavy alcohol consumption, and exercise status (Table
Results of logistic regression: crude and multivariate-adjusted OR of osteoporosis for risk factors in men under 70 years of age.
Unadjusted |
|
Adjusted |
|
|
---|---|---|---|---|
Age | 1.06 (1.01–1.11) | 0.030 | 1.05 (1.00–1.11) | 0.044 |
Weight | 0.93 (0.90–0.98) | 0.002 | 0.95 (0.91–0.99) | 0.019 |
Current smoker | 2.52 (1.20–5.29) | 0.014 | 3.04 (1.35–6.82) | 0.007 |
Heavy alcohol consumption† | 0.83 (0.40–1.71) | 0.610 | 0.80 (0.36–1.76) | 0.570 |
Exercise‡ | 1.03 (0.46–2.31) | 0.941 | 1.00 (0.43–2.31) | 0.999 |
OR: odds ratio; CI: confidence interval.
The discriminatory abilities of weight, BMI, OST, and PIO for osteoporosis in men under 70 years of age were evaluated by ROC analysis (Table
Area under the ROC curve, sensitivity, specificity, and the optimal cut-off value (only of predictive index) of variables to predict osteoporosis in men under 70 years of age.
AUC (95% CI) |
|
Sensitivity (%) | Specificity (%) | Cut-off value | |
---|---|---|---|---|---|
Weight | 0.69 (0.60–0.77) | 0.001 | 75.0 | 57.8 | 70.5 |
BMI | 0.66 (0.56–0.77) | 0.002 | 50.0 | 69.4 | 24.0 |
OST* | 0.69 (0.61–0.78) | <0.001 | 78.1 | 58.4 | 2.5 |
PIO† | 0.74 (0.66–0.81) | <0.001 | 71.9 | 70.0 | 0.87 |
ROC: receiver operating characteristics; AUC: area under the curve; CI: confidence interval; BMI: body mass index.
ROC curves of weight, BMI, OST, and PIO to identify osteoporosis in men under 70 years of age. ROC: receiver operating characteristics; BMI: body mass index. *Osteoporosis self-assessment tool [weight (kg) − age (years)] × 0.2, decimal dropped. †Predictive index for osteoporosis [age (years) + 10 (for current smoker)]/weight (kg).
However, when it comes to comparing the AUC values of those indices, it turned out that there was no statistical significance of differences between them. On the other hand, according to the traditional academic point system where AUC values lower than 0.7 are considered “poor or worthless,” only PIO appeared to be a fair index for the prediction of osteoporosis in men under 70 years of age [
Our study developed a new predictive index based on age, weight, and current smoking status to identify Korean men under 70 years of age who are at high risk of having osteoporosis and thus should undergo BMD screening. The PIO appeared to be an easy and simple assessment tool requiring less than 30 seconds to calculate for clinicians to identify men who need BMD screening for osteoporosis. In our study population, a PIO score of 0.87 seemed to serve as the optimal cutoff value which yielded a sensitivity, specificity, positive predictive, and negative predictive values of 71.9%, 70.0%, 17.2%, and 96%, respectively. Given that guidelines about who should be candidates for BMD testing in men vary according to expert groups and appeared not to have reached a consensus, the PIO seems to provide another practical and reliable guide for identifying such candidates. Interestingly, it was noted that the PIO tends to show greater diagnostic performance for osteoporosis in younger adult men. When the utility of the PIO was analyzed according to age groups, the index showed higher discriminatory accuracy for men under 50 years of age (AUC 0.78, 95% CI (0.60–0.96)) than that for men aged 50 to 69 years (AUC 0.70, 95% CI (0.62–0.79)) while the OST did not show any significant performance for men under 50 years of age (AUC 0.65, 95% CI (0.38–0.91)). In other words, the PIO in contrast to the OST appears to show greater diagnostic performance in younger men indicating that such relative superiority of the PIO may decrease in elderly men. Thus, this finding indicates that the PIO may serve as a promising index to identify osteoporosis in young adults although low BMD alone does not necessarily determine the diagnosis of the osteoporosis in young people [
The OST has been validated in Asian and Western population as a useful tool in identifying men who need to undergo BMD measurement. Lee et al. assessed the utility of the OST in predicting osteoporosis in Korean men above 50 years of age yielding an AUC of 0.77, sensitivity of 85%, and specificity of 62% [
Compared to the OST, better performance of the PIO may be attributable to containing an additional variable, current smoking status, in the formula of PIO. The link between smoking and osteoporosis has long been recognized and a recent study by Tamaki et al. addressed the association of smoking (current or previous) with male osteoporosis [
Our results must be interpreted within the context of some limitations. Firstly, we did not count all risk factors for osteoporosis in selecting variables to devise a new predictive index. For instance, history of decrease in height or eating habit was not taken into consideration in the modeling process. Ideally, a predictive model should consist of as many independent variables as possible to better predict the outcome. However, it was almost impossible to collect data containing information about all risk factors and also not practical to implement a clinical assessment index consisting of complicated factors. Secondly, this was a single-center study located in an island with a small sample size which limits the generalization of the result to whole population. Nevertheless, we still believe that the new index has a potential for use in the general population. One way to prove its utility is to use it in actual practice and see how well it predicts osteoporosis in men.
In summary, the purpose of this new predictive index was not only to diagnose osteoporosis but also to identify men aged under 70 years who are more likely to have osteoporosis and should, therefore, undergo BMD screening.
To that end, we validated the PIO by comparing the diagnostic performance between the PIO, the OST, weight, and BMI proving that the new index appeared a little bit superior to the OST and other variables in this particular age group. A larger and multi-ethnic population-based study assessing our new predictive index will be needed to validate its utility in population outside Korea.
The authors declare that there is no conflict of interests regarding the publication of this paper.
This work was supported by the research grant from Jeju National University Hospital.