Abstract
The objective of this cross‐sectional analysis was to examine the correlates of trabecular and cortical volumetric bone mineral density (vBMD) in 3670 community‐dwelling men, mean age 73.6 ± 5.9 years. vBMD was measured by quantitative computed tomography (QCT) and areal BMD by dual‐energy X‐ray absorptiometry (DXA). Demographic, historical, and lifestyle information was obtained by interview, and height, weight, and neuromuscular function were determined by examination. To express the strength of the associations, percent differences (95% confidence interval) were calculated from multivariable linear regression models using the formula 100 (β × unit/mean BMD). Units for continuous variables were chosen to approximate 1 standard deviation (SD). The multivariable linear regression models predicted 15%, 21%, and 20% of the overall variance in trabecular and cortical vBMD of the femoral neck and vBMD of the lumbar spine, respectively. Diabetes was associated with a 16.5% greater trabecular vBMD at the femoral neck and 11% at the lumbar spine but less than 2% for cortical vBMD. For femoral neck trabecular vBMD, the strongest negative correlates were past smoking (−9%), fracture history (−15%), kidney stones (−7%), corticosteroids (−11%), and insulin therapy (−26%). For cortical vBMD, the strongest negative correlate was use of thyroid medication (−2.8%). The strongest negative correlates for lumbar spine trabecular vBMD were fracture history (−5%), antiandrogen use (−19%), height (−8%), and thiazoliainedione use (−22%). Bioavailable estradiol and testosterone levels were positively related and sex hormone–binding globulin was negatively related to trabecular vBMD of the spine. There was no relationship between sex hormones and femoral neck trabecular vBMD. Our conclusion is that correlates of trabecular vBMD and cortical vBMD appear to differ in older men. © 2010 American Society for Bone and Mineral Research
Keywords: male osteoporosis, volumetric bone mineral density, areal bone mineral density, trabecular bone, cortical bone
Osteoporotic fractures are considered a major public health problem among older men. The lifetime risk of shoulder, forearm, hip, or spine fractures is estimated at 23.8%; in fact, one‐third of all hip fractures occur in men.1, 2, 3, 4, 5 The etiology of osteoporotic fractures in men is complex, with low areal bone mineral density (aBMD), reflecting an integration of both cortical and trabecular bone, considered a primary determinant.6, 7, 8
Although dual‐energy X‐ray absorptiometry (DXA) assessments are invaluable in measuring BMD and fracture risk, they provide no insight into the structural characteristics of bone or other elements of bone that might contribute to bone strength. Such factors include the size, shape, geometry, and relative amounts of bone in the cortical and trabecular compartments. Areal measurements are confounded by bone size such that individuals with larger bones have greater aBMD simply because of their larger bones.9 In addition, lumbar spine aBMD might be overestimated in older men because of degenerative, artifactual, and age‐related changes.
Computed tomographic scans provide measures of volumetric or 3D BMD and also can separate the cortical and trabecular compartments. At present, there is limited information on the correlates of trabecular or cortical volumetric BMD (vBMD) in older men. These correlates could differ from aBMD and for trabecular and cortical vBMD.
In a previous analysis by Marshall and colleagues, race and ethnic variation in proximal femur structure and vBMD were examined among older men participating in the Osteoporotic Fractures in Men (MrOS) Study. African‐American and Asian men had greater cortical thickness and higher trabecular vBMD compared with white men.10
Building on our initial analysis of race and vBMD, the objectives of this analysis were to comprehensively determine the demographic, anthropometric, historical (medical and family), lifestyle, and neuromuscular factors associated with trabecular and cortical vBMD of the proximal femur and lumbar spine in ethnically diverse, community‐dwelling older men enrolled in the MrOS Study. A secondary objective was to compare the correlates of vBMD with those of aBMD.
Material and Methods
Study participants
The MrOS Study is a prospective cohort study designed to examine the extent to which fracture risk is related to skeletal characteristics, lifestyle factors, anthropometric and physical performance measures, fall propensity, and other factors. Design and recruitment have been described previously.11, 12 The MrOS population consisted of 5995 community‐dwelling men aged 65 years and older. From March 2000 to April 2002, participants were recruited from six US clinical sites. Most clinics used population‐based sources to identify potential participants for this study. Exclusion criteria for MrOS were an inability to walk without assistance from another person or a history of bilateral hip replacement. Institutional review boards at all participating clinical sites approved the study, and written informed consent was obtained from all participants.
Measurement of bone status: DXA
Areal BMD (g/cm2) of the lumbar spine, total hip, and hip subregions was measured using DXA (QDR 4500W, Hologic, Inc., Bedford, MA, USA) in all MrOS participants. Lumbar spine BMD for each subject was measured in the anteroposterior projection and calculated as the mean of the BMD from the first through fourth lumbar vertebrae. All hip DXA BMD measurements were made on the right hip unless the subject reported a right hip replacement or metal objects in the right leg, in which case the left hip was measured.
All DXA operators were centrally certified on the basis of an evaluation of scanning and analysis techniques. Densitometry technicians at the coordinating center (University of California, San Francisco) reviewed a random sample of all the scans, scans with exceptionally high or low BMD, and potentially problematic scans flagged at the clinic to ensure adherence to standardized techniques. Cross‐calibration studies found no linear differences across scanners, and the maximum percent difference in mean total spine BMD between scanners was 1.4%. Longitudinal quality control using daily scan data for standardized phantoms indicated no shifts or drifts in scanner performance.
Quantitative computed tomography
The first 650 men and all nonwhite men enrolled at each site were referred for quantitative computed tomographic (QCT) scans of the hip and lumbar spine as part of their baseline visit for a total of 3786 men (63% of the MrOS cohort). Some men were not eligible for the scans (eg, hip replacement), or there were problems with the image processing. Volumetric BMD (g/cm3) of the lumbar spine, total hip, and hip region was measured using QCT.13, 14 Images were acquired using a GE Prospeed (Birmingham), GE Hispeed Advantage (Minneapolis), Philips MX‐8000 (Palo Alto), Siemans Somatom +4 (Pittsburgh), Philips CT‐Twin (Portland), Toshiba Acquilion (Portland), or Picker PQ‐5000 (San Diego). All QCT scans were transferred to the University of California at San Francisco for processing and central review. Image processing was performed using published methods.13, 15 Each participant's scan included a calibration standard of three hydroxyapatite concentrations (150, 75, and 0 mg/cm3; Image Analysis, Columbia, KY, USA). Images were converted from the native scanner Hounsfield units (HU) to equivalent concentration (g/cm3) of calcium hydroxyapatite contained in the calibrations standard.
Femoral neck vBMD
Of the 3427 hip scans processed, data were available for analysis on 3425 men for measurement of cortical bone and 3423 men for measurement of trabecular bone. To measure vBMD at the femoral neck, a QCT scan of the pelvic region (from the femoral head to 3.5 cm below the lesser trochanter) was acquired at settings of 80 kVp, 280 mA, 3‐mm slice thickness, and 512 × 512 matrix in spiral reconstruction mode.
Regions of interest (ROIs) in the left proximal femur were identified in QCT images re‐formatted along the neutral axis of the femoral neck. The periosteal boundary of the femur was determined with a threshold‐based region‐growing algorithm. Using this boundary, the cross‐sectional area of each slice along the neutral axis of the femoral neck between the proximal femoral neck and the lateral edge of the trochanter was calculated, and the minimum and maximum areas were determined. The femoral neck ROI was defined as the portions of the neck extending from the slice with minimum cross‐sectional area (medial boundary) to a point 25% of the distance to the maximal cross‐sectional area. Integral volume of the ROI was computed as the total volume within the periosteal boundary. A trabecular volume of the ROI was obtained by applying an erosion process to the integral volume to retain the same shape in a region fully contained within the medullary space. The cortical volume then was defined by applying a threshold of 0.35 g/cm3 to all voxels between the periosteal boundary and the outer boundary of the trabecular volume. vBMD for trabecular and cortical compartments was computed over all voxels in the respective volumes. In a group of postmenopausal women, coefficients of variation for vBMD ranged from 0.6% to 3%.15
Lumbar spine vBMD
Of the 3683 spine scans, data were available for analysis on 3556 for measurement of trabecular vBMD. Lumbar spine scans were obtained from 5 mm above the L1 superior endplate to 5 mm below the L2 inferior endplate at settings of 120kVp, 150 mA, 1‐mm slice thickness, and 512 × 512 matrix in spiral reconstruction mode. The lumbar spine ROI was defined as the 10‐mm slice in the midvertebral section for each vertebra. Integral volume of the ROI was computed as the total volume within the periosteal boundary. vBMD for the trabecular compartment was computed over all voxels within this region.
Correlate measurements
Participants completed a self‐administered baseline questionnaire and were interviewed and examined. Demographic characteristics included age, education, and race. Lifestyle factors included diet (modified Block Food Frequency Questionnaire), alcohol consumption, smoking history, and physical activity [walking for exercise and the Physical Activity Scale for the Elderly (PASE) score].16 Medical history included weight and height at age 25, self‐reported comorbid conditions, history of fracture after age 50, and family history of fracture. Current prescription medication use was ascertained through an in‐clinic review of participants' medication bottles. All prescription medications recorded by the clinics were stored in an electronic medications inventory database (San Francisco Coordinating Center, San Francisco, CA, USA). Each medication then was matched to its ingredient(s) based on the Iowa Drug Information Service Drug Vocabulary (College of Pharmacy, University of Iowa, Iowa City, IA, USA).17 For diabetes medication, we looked at all hypoglycemic medications, and then insulin and thiazoliainediones (TZDs) were analyzed separately. Quality‐of‐life measures included self‐rated health and back pain.
Physical measures performed at clinical sites included height (stadiometer) and weight (balance‐beam or digital scale). Grip strength was assessed using a Jamar dynamometer (Sammons Preston Rolyan, Bolingbrook, IL, USA) and scored as the maximum of two attempts for the stronger hand.18 Participants were timed while walking 6 m at their normal pace and then as they completed the walk while taking no more than two deviations outside a 20‐cm‐wide path.19 Leg extension power was measured using the Nottingham Power Rig (Nottingham University, Nottingham, UK).20 Participants also were asked to rise from a chair without using their arms and complete five chair stands. Time to complete the five chair stands was recorded.
Sex steroid hormone measurements
At baseline, fasting morning blood was collected; serum was prepared immediately and stored at −70°C. All samples remained frozen until assay. A combined gas chromatographic–negative ionization–tandem mass spectrometric (GC/NCI/MS/MS) and liquid chromatographic–electrospray–tandem mass spectrometric (LC/ESI/MS/MS) bioanalytical method was used to measure testosterone, estradiol, and estrone (Taylor Technology, Princeton, NJ, USA). The ranges of detection for estradiol were 0.625 to 80 pg/mL; estrone, 1.56 to 200 pg/mL; and testosterone, 2.5 to 320 ng/dL. Duplicate aliquots from each participant's serum were assayed, and the two results were averaged. The intra‐ and interassay coefficients of variation (CVs), respectively, for testosterone were 2.5% and 6%; for estradiol, 6.4% and 10.1%; and for estrone, 5.2% and 12.9%. Sex hormone–binding globulin concentration was determined on an Immulite Analyzer with chemiluminescent substrate (Diagnostic Products Corp., Los Angeles, CA, USA). The standard curve ranged from 0.2 to 180 nm/L; intraassay CV was 4.6%, and interassay CV was 5.8%. Calculation of the free and bioavailable fractions of testosterone and estradiol used the methods described by Sodegard.21
Statistical analysis
Our analytical cohort consists of the 3670 men with data on either cortical or trabecular vBMD at the femoral neck or trabecular vBMD at the lumbar spine. Differences between the analytical cohort and the rest of the MrOS population were examined using t tests for normally distributed continuous covariates, Wilcoxon rank‐sum tests for skewed continuous covariates, and chi‐square tests for categorical data.
Linear regression models were used to detect potential associations with vBMD. All models were adjusted for clinic site. To express the relative strength of the associations, units of percent difference in vBMD for continuous variables were chosen to approximate 1 SD in the distribution of a given variable. For age, body weight, and height, we used standard units—5 years for age, 10 kg for weight, and 10 cm for height. Percent differences in BMD were calculated from the regression coefficients using the formula 100 × (β × unit/mean BMD). Although aBMD is not the focus of the analysis, parallel modeling was performed on aBMD of the lumbar spine and femoral neck on this subset of 3670 men for comparison with vBMD results.
We first analyzed the data using clinic‐ and age‐adjusted linear regression models. Variables with clinic‐ and age‐adjusted associations in which the p values were less than .10 for the outcomes of femoral neck aBMD, trabecular vBMD, or cortical vBMD were included for consideration in stepwise multiple regression models for femoral neck BMD. We used a forward stepwise selection process with variables significant at the p = .15 entry and exit criteria to determine the final multivariable models. If a covariate was selected for any of the three femoral neck outcomes, it was included in the final multivariate model for all three femoral neck BMD outcomes. Similar modeling was performed for the outcomes of lumbar spine aBMD and trabecular vBMD. Age, weight, clinic, and race were forced into all stepwise regression models. The data collected included sets of variables related to broad areas of interest such as measures of obesity and muscle strength and estimates of physical activity. Within each set, several variables were associated with vBMD in clinic‐ and age‐adjusted analyses. We chose to include the variable within each set that had the lowest amount of missing data and showed the strongest relationship to vBMD.
The variables entered into the femoral neck multivariable stepwise models included age, clinic site, race, education, weight, weight change since age 25, height, height change since age 25, past smoking, daily caffeine intake, average number of alcohol drinks per week, PASE score, daily calcium intake, nontrauma fracture after age 50, maternal and paternal history of fracture, diabetes, hypertension, hypothyroidism, chronic obstructive pulmonary disease (COPD), Parkinson's disease, kidney stones, select medications [use of cyclooxygenase type 2 (COX‐2) inhibitors, nonsteroidal anti‐inflammatory drugs (NSAIDS), thiazide diuretics, nonthiazide diuretics, beta blockers, statins, selective serotonin reuptake inhibitors (SSRIs), thyroid, oral, or inhaled steroid use, and insulin], walking speed, time to complete five chair stands, and grip strength.
The variables entered into the lumbar spine multivariable stepwise models included age, clinic site, race, weight, weight change since age 25, height, height change since age 25, current and past smoking, daily caffeine intake, average number of alcohol drinks per week, daily calcium intake, nontrauma fracture after age 50, maternal and paternal history of fracture, diabetes, hypertension, osteoarthritis, COPD, Parkinson's disease, prostate cancer, kidney stones, select medications (use of antiandrogen, COX‐2 inhibitors, NSAIDs, thiazide diuretics, nonthiazide diuretics, beta blockers, SSRIs, oral or inhaled steroid use, and TZDs), back pain, walking speed, time to complete five chair stands, and grip strength.
To avoid bias from specific therapies for osteoporosis or a history of osteoporosis, we excluded men from the multivariable model screening process and final multivariate models who reported ever taking an osteoporosis medication (n = 101) and men who self‐reported osteoporosis (n = 138), two categories that were not mutually exclusive. In addition, because of the cumulative effect of missing values, the sample size in the multivariable regression were n = 2842 fot trabecular vBMD, n = 2841 for cortical vBMD of the femoral neck, and n = 2935 for the lumbar spine trabecular vBMD.
Sex steroid hormones were measured in a subset of 978 men (29%) with QCT data. We examined the clinic‐ and age‐adjusted percentage difference in trabecular and cortical vBMD per 1 SD increase in bioavailable estradiol, bioavailable testosterone, and sex hormone–binding globulin. For the multivariable model, we added the sex hormones to the final multivariable model developed on the entire QCT cohort to test whether sex steroids were independently associated with vBMD. Separate models were run for each sex hormone.
Results
By study design, data were obtained for lumbar spine and femoral neck by QCT in 3670 of the 5995 older men in MrOS. Except for the higher proportion of minorities (13% versus 7%), the characteristics of men in the QCT subset were similar to the overall population of men in MrOS. There were no significant differences in age, body mass index (BMI), current smoking status, walking for exercise, or fracture history; femoral neck aBMD also was similar between groups, but average spine aBMD was significantly different (QCT subset mean 1.08 versus overall population mean 1.07 g/cm2, p = .009). The mean ± SD trabecular vBMD of the femoral neck was 0.072 ± 0.044 g/cm3; femoral neck cortical vBMD, 0.526 ± 0.062 g/cm3; and lumbar spine trabecular vBMD, 0.110 ± 0.039 g/cm3.
Age‐ and clinic‐adjusted models (Table 1)
Demographics
A 5‐year increase in age was associated with a 7% to 9% lower trabecular vBMD and less than 1% lower cortical vBMD. Education was unrelated to either trabecular or cortical vBMD. African‐American, Asian, and Hispanic men had significantly higher femoral neck and lumbar spine trabecular vBMD than white men. Cortical vBMD was higher in African‐American men only in comparison with white men. 1
Table 1.
Correlates of Volumetric BMD in Clinic‐ and Age‐Adjusted Models
| Variable | Unit | Mean ± SD or Prevalence (%) | Percentage difference in bone mass per unit (95% confidence interval) | ||
|---|---|---|---|---|---|
| Femoral neck cortical vBMD | Femoral neck trabecular vBMD | Lumbar spine trabecular vBMD | |||
| Demographics | |||||
| Age (years) | 5 | 73.6 ± 5.9 | −0.55 (−0.86, −0.24) | −9.17 (−10.88, −7.47) | −6.73 (−7.69, −5.78) |
| Race | |||||
| White | 87.0% | ||||
| African‐American | 5.5% | 4.04 (2.40, 5.67) | 34.78 (25.84, 43.72) | 33.58 (28.72, 38.44) | |
| Asian | 3.6% | −1.75 (−3.72, 0.21) | 29.11 (18.36, 39.86) | 10.37 (4.54, 16.21) | |
| Hispanic | 2.6% | 1.49 (−0.77, 3.74) | 13.31 (0.98, 25.64) | 6.97 (0.18, 13.77) | |
| Other | 1.3% | −0.9 (−4.09, 2.30) | −5.96 (−23.40, 11.48) | −4.28 (−13.99, 5.43) | |
| >High school education | Yes | 76.4% | −0.47 (−1.37, 0.43) | 0.46 (−4.51, 5.43) | −0.11 (−2.86, 2.64) |
| Anthropometry | |||||
| Weight (kg) | 10 | 83.2 ± 13.5 | 0.98 (0.71, 1.25) | 4.55 (3.03, 6.07) | 3.54 (2.69, 4.39) |
| Weight change since age 25 (kg) | 11.6 | 10.4 ± 11.6 | 0.46 (0.09, 0.82) | 4.54 (2.53, 6.55) | 2.99 (1.87, 4.11) |
| Height (cm) | 10 | 174.0 ± 6.9 | 0.72 (0.19, 1.26) | −1.92 (−4.88, 1.04) | −4.5 (−6.13, −2.87) |
| Height change since age 25 (cm) | 3.0 | 3.7 ± 3.0 | −0.27 (−0.64, 0.11) | −4.99 (−7.04, −2.94) | −1.6 (−2.74, −0.47) |
| BMI (kg/m2) | 3.9 | 27.4 ± 3.9 | 1.14 (0.76, 1.51) | 4.92 (2.86, 6.98) | 5.22 (4.09, 6.34) |
| Lifestyle | |||||
| Current smoking | Yes | 3.5% | −0.18 (−2.16, 1.81) | 1.17 (−9.80, 12.14) | −6.69 (−12.65, −0.73) |
| Past smoking | Yes | 61.1% | 1.07 (0.32, 1.82) | −6.82 (−10.97, −2.68) | −4.21 (−6.50, −1.93) |
| Caffeine intake (mg/day) | 232.5 | 211.8 ± 232.5 | 0.14 (−0.23, 0.50) | −2.98 (−4.99, −0.98) | −1.44 (−2.56, −0.33) |
| Alcohol (drinks/week) | 6.6 | 4.2 ± 6.6 | 0.63 (0.27, 0.99) | −1.2 (−3.21, 0.81) | −0.44 (−1.55, 0.67) |
| Physical activity (PASE) | 67.5 | 145.8 ± 67.5 | 0.21 (−0.16, 0.58) | 1.11 (−0.93, 3.15) | −0.03 (−1.16, 1.10) |
| Walk for exercise | Yes | 49.4% | 0.02 (−0.70, 0.74) | −2.24 (−6.19, 1.72) | −0.29 (−2.49, 1.91) |
| Diet | |||||
| Dietary calcium intake (mg/day) | 393.0 | 807.9 ± 393.0 | −0.31 (−0.67, 0.05) | 2.6 (0.60, 4.59) | 0.6 (−0.50, 1.70) |
| Supplemental calcium intake (mg/day) | 435.0 | 346.2 ± 435.0 | −0.39 (−0.75, −0.03) | −1.46 (−3.46, 0.55) | −1.41 (−2.53, −0.30) |
| Total calcium (mg/day) | 595.8 | 1154.1 ± 595.8 | −0.48 (−0.84, −0.12) | 0.65 (−1.33, 2.64) | −0.62 (−1.72, 0.48) |
| Total vitamin D (IU) | 245.9 | 395.1 ± 245.9 | −0.06 (−0.42, 0.30) | −0.87 (−2.87, 1.12) | −0.58 (−1.68, 0.53) |
| Fracture history (since age 50) | |||||
| Nontrauma fracture (any) | Yes | 17.0% | −1.99 (−2.96, −1.03) | −17.64 (−22.95, −12.32) | −9.08 (−11.99, −6.18) |
| Hip fracture | Yes | 1.3% | −3.67 (−8.27, 0.93) | −21.16 (−46.51, 4.18) | −11.08 (−20.81, −1.36) |
| Wrist fracture | Yes | 4.0% | −1.63 (−3.50, 0.23) | −20.24 (−30.50, −9.98) | −7.49 (−13.04, −1.94) |
| Spine fracture | Yes | 2.0% | −3.63 (−6.22, −1.04) | −12.35 (−26.64, 1.95) | −10.8 (−18.60, −2.99) |
| Family history | |||||
| Mother fracture (any) | Yes | 22.1% | −0.83 (−1.71, 0.04) | −10.46 (−15.28, −5.65) | −4.34 (−6.99, −1.69) |
| Mother hip fracture | Yes | 11.0% | −0.01 (−1.18, 1.16) | −8.44 (−14.87, −2.02) | −5.66 (−9.16, −2.16) |
| Father fracture (any) | Yes | 14.7% | −0.98 (−2.00, 0.03) | −4 (−9.60, 1.60) | −2.38 (−5.49, 0.73) |
| Father hip fracture | Yes | 3.1% | −0.61 (−2.67, 1.44) | −5.53 (−16.90, 5.83) | −0.79 (−7.10, 5.53) |
| Medical history | |||||
| Diabetes | Yes | 11.1% | 2.34 (1.20, 3.47) | 15.45 (9.19, 21.72) | 10.71 (7.22, 14.21) |
| Hypertension | Yes | 41.9% | 1.35 (0.62, 2.08) | 8.82 (4.81, 12.83) | 5.06 (2.84, 7.29) |
| Myocardial infarction | Yes | 13.8% | −0.04 (−1.08, 1.00) | −4.21 (−9.96, 1.54) | −1.22 (−4.45, 2.01) |
| Stroke | Yes | 5.6% | 0.2 (−1.39, 1.79) | 2.3 (−6.47, 11.08) | −0.19 (−5.03, 4.65) |
| Osteoporosis | Yes | 3.8% | −3.54 (−5.50, −1.59) | −28.41 (−39.21, −17.61) | −23.7 (−29.50, −17.91) |
| Rheumatoid arthritis | Yes | 5.1% | 0.32 (−1.36, 2.00) | 2.96 (−6.28, 12.21) | −1.25 (−6.27, 3.76) |
| Osteoarthritis | Yes | 19.9% | 0.63 (−0.29, 1.55) | −0.06 (−5.11, 4.99) | 1.14 (−1.64, 3.92) |
| Hyperthyroid | Yes | 1.6% | −1.69 (−4.63, 1.24) | −8.29 (−24.45, 7.88) | −1.53 (−10.20, 7.13) |
| Hypothyroid | Yes | 7.5% | −2.14 (−3.52, −0.77) | −1.7 (−9.29, 5.89) | −2.21 (−6.41, 1.98) |
| COPD | Yes | 10.8% | 1.03 (−0.14, 2.21) | 0.17 (−6.28, 6.62) | −4.3 (−7.86, −0.75) |
| Parkinson's | Yes | 0.8% | −3.91 (−8.12, 0.31) | 7.84 (−15.41, 31.09) | −6.61 (−19.27, 6.05) |
| Prostate cancer | Yes | 11.3% | 0 (−1.15, 1.14) | −1.86 (−8.17, 4.45) | −1.48 (−4.97, 2.02) |
| Gastrectomy | Yes | 7.5% | −0.19 (−1.56, 1.18) | −3.76 (−11.33, 3.81) | −2.16 (−6.36, 2.04) |
| Kidney stones | Yes | 12.5% | −0.09 (−1.17, 0.99) | −6.74 (−12.71, −0.78) | −3.31 (−6.64, 0.01) |
| Medications | |||||
| Androgens | Yes | 1.1% | −2.74 (−6.21, 0.73) | 0.75 (−18.41, 19.92) | 4.43 (−6.64, 15.51) |
| Testosterone injection | Yes | 1.0% | −1.95 (−5.57, 1.66) | 10.15 (−9.79, 30.09) | 6.95 (−4.16, 18.07) |
| Antiandrogen | Yes | 0.5% | −1.98 (−7.09, 3.13) | 6.92 (−21.30, 35.14) | −8.48 (−24.34, 7.38) |
| Cox‐2 inhibitor | Yes | 6.0% | 0.78 (−0.80, 2.37) | 6.61 (−2.12, 15.34) | 3.67 (−1.13, 8.47) |
| NSAID | Yes | 64.0% | 0.64 (−0.11, 1.39) | −2.79 (−6.91, 1.34) | 0 (−2.29, 2.28) |
| Thiazide diuretic | Yes | 12.8% | 0.63 (−0.47, 1.72) | 9.19 (3.16, 15.21) | 6.37 (3.03, 9.71) |
| Nonthiazide diuretic | Yes | 9.5% | 0.86 (−0.42, 2.14) | 9.35 (2.27, 16.43) | 4.92 (1.05, 8.80) |
| Statin | Yes | 25.6% | 0.52 (−0.33, 1.36) | 2.18 (−2.47, 6.83) | 0.07 (−2.51, 2.65) |
| Nitrate | Yes | 4.5% | −0.46 (−2.24, 1.32) | 5.8 (−4.01, 15.61) | 0.47 (−5.01, 5.94) |
| Beta blocker | Yes | 18.1% | 0.17 (−0.79, 1.13) | 4.69 (−0.60, 9.98) | 1.87 (−1.06, 4.80) |
| Non‐BZ anticonvulsant | Yes | 2.1% | −0.18 (−2.78, 2.42) | −5.96 (−20.39, 8.46) | −3.96 (−11.68, 3.76) |
| SSRI | Yes | 2.9% | −0.86 (−3.02, 1.31) | −7.22 (−19.16, 4.72) | −6.67 (−13.45, 0.10) |
| Tricyclic antidepressants | Yes | 2.0% | 1.88 (−0.69, 4.45) | −0.81 (−15.01, 13.39) | −4.89 (−12.93, 3.15) |
| Thyroid | Yes | 7.0% | −2.49 (−3.95, −1.03) | −4.09 (−12.17, 3.99) | −1.64 (−6.08, 2.80) |
| Corticosteroid (any) | Yes | 8.5% | 0.35 (−0.97, 1.67) | −9.97 (−17.28, −2.67) | −6.81 (−10.83, −2.78) |
| Inhaled corticosteroid | Yes | 6.9% | 0.92 (−0.54, 2.37) | −8.85 (−16.88, −0.83) | −4.86 (−9.31, −0.41) |
| Oral corticosteroid | Yes | 2.2% | −1.48 (−4.02, 1.06) | −16.52 (−30.51, −2.53) | −15.8 (−23.50, −8.11) |
| Bisphosphonate | Yes | 2.0% | −4.41 (−7.17, −1.66) | −20.11 (−35.23, −4.99) | −20.36 (−28.59, −12.12) |
| Calcitonin | Yes | 0.5% | −0.3 (−5.57, 4.98) | −40.99 (−70.96, −11.01) | −32.94 (−47.62, −18.26) |
| Any osteoporosis medication (ever) | Yes | 2.8% | −4.07 (−6.37, −1.77) | −28.54 (−41.27, −15.81) | −23 (−29.69, −16.30) |
| Hypoglycemic | Yes | 8.3% | 2.87 (1.54, 4.20) | 16.04 (8.71, 23.37) | 12.77 (8.71, 16.84) |
| Insulin | Yes | 1.1% | 2.68 (−0.23, 5.59) | −5.36 (−21.40, 10.69) | 9.81 (1.03, 18.58) |
| TZD | Yes | 1.2% | 1.36 (−2.06, 4.79) | −5.77 (24.66, 13.13) | −11.99 (−22.22, −1.76) |
| General health | |||||
| Health (good/excellent) | Yes | 85.0% | 0.24 (−0.79, 1.26) | 0.24 (−5.40, 5.89) | 1.97 (−1.13, 5.06) |
| Back pain (last 12 months) | Yes | 67.8% | −0.06 (−0.83, 0.71) | −0.92 (−5.15, 3.32) | 0.55 (−1.80, 2.89) |
| Neuromuscular | |||||
| Gait speed (m/s) | 0.2 | 1.2 ± 0.2 | −0.09 (−0.49, 0.30) | −2.42 (−4.59, −0.25) | −1.12 (−2.32, 0.08) |
| Chair stands (seconds) | 3.3 | 11.1 ±3.3 | −0.22 (−0.60, 0.17) | −1.71 (−3.84, 0.42) | −2.21 (−3.36, −1.06) |
| Stand without using arms | Yes | 97.1% | −2.03 (−4.32, 0.25) | −6.26 (−18.91, 6.39) | 1.32 (−5.40, 8.03) |
| Grip strength (kg) | 8.2 | 38.5 ± 8.2 | 0.23 (−0.18, 0.64) | 2.59 (0.34, 4.85) | 1.03 (−0.21, 2.27) |
| Leg extension power (W) | 63.4 | 205.8 ± 63.4 | 0.48 (0.04, 0.92) | 3.48 (1.06, 5.89) | 1.39 (0.07, 2.71) |
| Sex steroid hormonesa | |||||
| Bioavailable estradiol (pg/mL) | 5.5 | 14.3 ± 5.5 | 0.87 (0.15, 1.59) | 6.87 (2.79, 10.94) | 6.57 (4.44, 8.70) |
| Bioavailable testosterone (ng/dL) | 79.4 | 206.8 ± 79.4 | −0.19 (−0.93, 0.54) | −0.78 (−4.97, 3.41) | 2.62 (0.41, 4.82) |
| Sex hormone–binding globulin (nM) | 19.7 | 49.3 ± 19.7 | −0.54 (−1.28, 0.20) | −8.48 (−12.62, −4.33) | −5.22 (−7.36, −3.07) |
Sex steroids measured on a subset of 978 subjects.
Bold = significant at p < .05.
Anthropometry
Weight was more strongly associated with trabecular vBMD (4% to 5% per 10‐kg increase) than with cortical vBMD (1% per 10‐kg increase). Similar results were observed for weight change since age 25 and BMI. A 10‐cm increase in height was associated with a 4.5% lower lumbar spine vBMD but was unrelated to trabecular vBMD of the hip. Height was weakly positively correlated with cortical vBMD. A 1 SD increase in loss in height since age 25 was associated with a 5% lower femoral neck trabecular vBMD and a 1.6% lower lumbar spine trabecular vBMD but was unrelated to cortical vBMD.
Lifestyle
Past smoking had a strong negative association with trabecular vBMD of the femoral neck. A modest positive association was observed for past smoking and cortical vBMD. A 1 SD increase in caffeine intake was associated with 3.0% and 1.4% lower trabecular vBMD at the femoral neck and lumbar spine, respectively. A 1 SD increase in alcohol consumption (6.6 drinks per week) was associated with a 0.6% higher cortical vBMD. Physical activity was unrelated to vBMD.
Diet
Dietary calcium was positively associated with femoral neck vBMD, but supplemental calcium was negatively associated, probably reflecting an indication bias; that is, men may have been advised to take calcium supplements because their BMD was low. There was no association between dietary vitamin D intake and vBMD, but dietary vitamin D is a poor indicator of total vitamin D status.
Fracture
History of fracture was associated with 18% and 9% lower trabecular vBMD at the hip and spine, respectively, with weaker, albeit significant, associations with cortical vBMD. Examination of the history of specific fracture locations revealed generally similar results.
Family history
Maternal history of any fracture or specifically hip fracture was associated with 4% to 10% lower trabecular vBMD at the hip and spine respectively, but was unrelated to cortical vBMD. Paternal history of fracture was unrelated to vBMD.
Medical history
Self‐reported diabetes and hypertension were each associated with greater vBMD at both trabecular and cortical sites, but the association was much stronger for trabecular vBMD. A history of osteoporosis was reported by 3.8% of men and was associated with lower vBMD, especially trabecular vBMD. History of hypothyroid disease was negatively associated with vBMD, but the association was statistically significant for cortical vBMD only. A history of COPD was associated with 4% lower spine trabecular vBMD, and kidney stones were associated with 6.7% lower femoral neck trabecular vBMD. There was no association between self‐report of myocardial infarction, stroke, rheumatoid arthritis, osteoarthritis, hyperthyroid disease, Parkinson's disease, prostate cancer, or gastrectomy and either cortical or trabecular vBMD.
Medications
Both thiazide and nonthiazide diuretics were associated with 5% to 9% higher trabecular vBMD but were unrelated to cortical vBMD. Thyroid medication was associated with lower cortical vBMD but was not significantly associated with trabecular vBMD. Men who reported taking a bisphosphonate, calcitonin, or any osteoporosis medication had significantly lower vBMD, especially at trabecular bone sites. Use of any hypoglycemic medication was associated with 12% to 16% higher trabecular vBMD, with smaller effects on cortical vBMD. Use of insulin was associated with significantly higher vBMD, whereas TZDs were associated with significantly lower lumbar spine trabecular vBMD, and TZDs were not associated with femoral neck vBMD. Corticosteroids, both inhaled and oral, were associated with lower trabecular but not cortical vBMD.
Neuromuscular
There were no consistent associations between our neuromuscular measures and vBMD except for leg extension power. A 1 SD increase in leg extension power was associated with 0.5%, 3.5%, and 1.4% higher proximal femoral cortical, trabecular, and lumbar spine trabecular vBMD, respectively.
Sex steroid hormones
In age‐ and clinic‐adjusted models, a 1 SD increase in bioavailable estradiol was associated with 6% higher trabecular vBMD of both the hip and spine. Weaker, albeit statistically significant, associations were observed between bioavailable estradiol and cortical vBMD of the femoral neck. Bioavailable testosterone was associated with greater lumbar spine trabecular vBMD but was unrelated to vBMD at the femoral neck. There were strong negative associations between sex hormone–binding globulin and trabecular vBMD of the hip and spine and no association with cortical vBMD.
Multivariable correlates of femoral neck trabecular vBMD, cortical vBMD, and aBMD (Tables 2 and 5)
Multivariable models explained 15%, 21%, and 21% of the overall variance in trabecular vBMD, cortical vBMD, and aBMD at the femoral neck, respectively. In general, the associations were stronger for trabecular than cortical vBMD. For trabecular vBMD, African‐American and Asian race, diabetes, and use of Cox‐2 inhibitors were positively associated (≥5%), whereas age, past smoking, history of nontrauma fracture, maternal history of fracture, history of kidney stones, and use of NSAIDs, corticosteroids, or insulin were independent negatively associated (≥–5%). Height change since age 25 was a moderate negative correlate and calcium intake and hypertension were moderate positive correlates of trabecular vBMD (3% to <5%).
Table 2.
Multivariate Correlates of Femoral Neck BMD: Areal BMD, Trabecular vBMD, Cortical vBMD
| Variable | Percentage difference in bone mass per unit (95% confidence interval) | |||
|---|---|---|---|---|
| Unit | aBMD | Trabecular vBMD | Cortical vBMD | |
| Demographics | ||||
| Age (years) | 5 | −0.42 (−0.96, 0.12) | −5.79 (−7.97, −3.60) | −0.21 (−0.61, 0.20) |
| Race | ||||
| White (Ref) | ||||
| African‐American | Yes | 11.87 (9.33, 14.41) | 33.34 (23.02, 43.66) | 3.99 (2.07, 5.92) |
| Asian | Yes | 1.54 (−1.41, 4.50) | 26.03 (14.23, 37.84) | −0.88 (−3.08, 1.32) |
| Hispanic/other | Yes | 0.11 (−2.59, 2.81) | 6.70 (−4.07, 17.48) | 0.01 (−2.00, 2.02) |
| >High school education | Yes | −0.01 (−1.37, 1.34) | 4.04 (−1.45, 9.53) | −0.47 (−1.49, 0.56) |
| Anthropometry | ||||
| Weight (kg) | 10 | 4.87 (4.22, 5.52) | 2.45 (−0.18, 5.09) | 1.02 (0.53, 1.51) |
| Weight change since age 25 (kg) | 11.6 | −1.09 (−1.84, −0.35) | 2.37 (−0.63, 5.37) | −0.51 (−1.07, 0.05) |
| Height (cm) | 10 | −1.33 (−2.35, −0.32) | −2.54 (−6.66, 1.58) | 0.09 (−0.67, 0.86) |
| Height change since age 25 (cm) | 3.0 | −0.92 (−1.48, −0.36) | −4.00 (−6.26, −1.75) | −0.11 (−0.53, 0.31) |
| Lifestyle | ||||
| Past smoking | Yes | −1.29 (−2.37, −0.20) | −8.50 (−12.87, −4.12) | 0.67 (−0.15, 1.48) |
| Alcohol (drinks/week) | 6.6 | 1.36 (0.82, 1.91) | 0.97 (−1.25, 3.18) | 0.56 (0.15, 0.98) |
| Physical activity (PASE) | 67.5 | 0.78 (0.24, 1.32) | 1.73 (−0.47, 3.92) | 0.26 (−0.15, 0.67) |
| Diet | ||||
| Total calcium (mg/day) | 595.8 | 0.46 (−0.07, 0.99) | 3.22 (1.07, 5.37) | −0.23 (−0.63, 0.17) |
| Fracture history (any) | ||||
| Nontrauma fracture | Yes | −3.70 (−5.15, −2.25) | −15.36 (−21.28, −9.45) | −1.5 (−2.60, −0.40) |
| Family history | ||||
| Mother fracture (any) | Yes | −1.44 (−2.70, −0.17) | −5.36 (−10.51, −0.21) | −0.63 (−1.59, 0.33) |
| Father fracture (any) | Yes | −1.15 (−2.62, 0.33) | −1.59 (−7.53, 4.36) | −1.04 (−2.15, 0.07) |
| Medical history | ||||
| Diabetes | Yes | 3.37 (1.51, 5.24) | 16.54 (9.07, 24.01) | 1.90 (0.51, 3.29) |
| Hypertension | Yes | 0.86 (−0.25, 1.97) | 4.63 (0.17, 9.10) | 0.67 (−0.16, 1.50) |
| Hypothyroid | Yes | 2.98 (−0.34, 6.29) | 9.97 (−3.51, 23.46) | 0.12 (−2.40, 2.63) |
| Parkinson's | Yes | −5.91 (−12.49, 0.67) | 1.10 (−26.91, 29.10) | −4.67 (−9.89, 0.55) |
| Kidney stones | Yes | −2.31 (−3.89, −0.73) | −7.42 (−13.72, −1.11) | −0.14 (−1.31, 1.04) |
| Medications | ||||
| Cox‐2 inhibitor | Yes | 3.22 (0.86, 5.57) | 11.01 (1.45, 20.57) | 0.94 (−0.84, 2.72) |
| NSAID | Yes | −0.95 (−2.07, 0.17) | −5.78 (−10.30, −1.26) | 0.15 (−0.69, 0.99) |
| Nonthiazide diuretic | Yes | 1.95 (0.03, 3.87) | 5.31 (−2.45, 13.07) | 0.35 (−1.09, 1.80) |
| Statin | Yes | 1.56 (0.33, 2.78) | 1.47 (−3.44, 6.38) | 0.49 (−0.42, 1.41) |
| SSRI | Yes | −3.25 (−6.51, 0.01) | −8.44 (−21.45, 4.57) | −1.29 (−3.72, 1.13) |
| Thyroid | Yes | −4.69 (−8.13, −1.24) | −13.36 (−27.33, 0.60) | −2.82 (−5.42, −0.22) |
| Corticosteroid (any, inhaled or oral) | Yes | −1.90 (−3.85, 0.05) | −10.78 (−18.59, −2.96) | 0.29 (−1.17, 1.75) |
| Insulin | Yes | −4.25 (−8.87, 0.37) | −26.12 (−44.59, −7.65) | 0.56 (−2.88, 4.00) |
| Neuromuscular | ||||
| Chair stands (seconds) | 3.29 | −0.52 (−1.10, 0.06) | −0.69 (−3.10, 1.72) | −0.53 (−0.98, −0.08) |
| Grip strength (kg) | 8.21 | 0.34 (−0.31, 0.99) | 1.33 (−1.31, 3.98) | −0.41 (−0.90, 0.09) |
Bold = significant at p < .05.
Table 3.
Multivariate Correlates of Lumbar Spine BMD: Areal BMD, Trabecular vBMD
| Variable | Percentage difference in bone mass per unit (95% confidence interval) | ||
|---|---|---|---|
| Unit | aBMD | Trabecular vBMD | |
| Demographics | |||
| Age (years) | 5 | 2.03 (1.41, 2.64) | −5.01 (−6.18, −3.85) |
| Race | |||
| White (Ref) | |||
| African‐American | Yes | 5.71 (2.85, 8.56) | 33.09 (27.65, 38.52) |
| Asian | Yes | 0.32 (−3.03, 3.66) | 5.95 (−0.35, 12.26) |
| Hispanic/other | Yes | −3.15 (−6.18, −0.11) | −0.90 (−6.67, 4.86) |
| Anthropometry | |||
| Weight (kg) | 10 | 3.89 (3.16, 4.62) | 3.98 (2.59, 5.38) |
| Weight change since age 25 (kg) | 11.6 | −3.46 (−4.30, −2.63) | −0.06 (−1.65, 1.54) |
| Height (cm) | 10 | 0.50 (−0.66, 1.65) | −7.94 (−10.13, −5.75) |
| Height change since age 25 (cm) | 3.0 | 0.38 (−0.25, 1.01) | −1.09 (−2.28, 0.11) |
| Lifestyle | |||
| Past smoking | Yes | −0.80 (−2.03, 0.43) | −4.89 (−7.22, −2.56) |
| Alcohol (drinks/week) | 6.6 | 0.89 (0.27, 1.51) | 1.04 (−0.13, 2.21) |
| Diet | |||
| Total calcium (mg/day) | 595.8 | 0.31 (−0.29, 0.91) | 1.52 (0.38, 2.66) |
| Fracture history (any) | |||
| Nontrauma fracture | Yes | −4.31 (−5.95, −2.68) | −5.23 (−8.33, −2.13) |
| Family history | |||
| Mother fracture (any) | Yes | −1.63 (−3.05, −0.21) | −0.97 (−3.67, 1.73) |
| Medical history | |||
| Diabetes | Yes | 5.01 (2.95, 7.07) | 10.73 (6.80, 14.66) |
| Hypertension | Yes | 1.67 (0.41, 2.92) | 1.04 (−1.34, 3.43) |
| Osteoarthritis | Yes | 2.84 (1.26, 4.42) | 2.56 (−0.44, 5.56) |
| COPD | Yes | −1.85 (−3.92, 0.22) | −4.06 (−8.02, −0.11) |
| Parkinson's | Yes | −8.56 (−15.95, −1.16) | −11.44 (−25.30, 2.42) |
| Kidney stones | Yes | −2.33 (−4.11, −0.56) | −3.09 (−6.47, 0.30) |
| Medications | |||
| Antiandrogen | Yes | −13.64 (−22.93, −4.35) | −19.29 (−37.48, −1.11) |
| Cox‐2 inhibitor | Yes | 2.96 (0.30, 5.63) | 4.33 (−0.72, 9.39) |
| Beta blocker | Yes | 1.40 (−0.16, 2.96) | −0.52 (−3.50, 2.45) |
| Corticosteroid (any, inhaled or oral) | −3.79 (−6.10, −1.47) | −4.08 (−8.49, 0.33) | |
| TZD | Yes | −7.95 (−13.82, −2.08) | −21.84 (−32.86, −10.83) |
| General health | |||
| Back pain last 12 months | Yes | 1.71 (0.46, 2.96) | 1.48 (−0.89, 3.86) |
| Neuromuscular | |||
| Gait speed (m/s) | 0.23 | −1.06 (−1.81, −0.32) | −0.56 (−1.97, 0.85) |
| Chair stands (seconds) | 3.29 | −0.41 (−0.63, −0.19) | −0.72 (−1.13, −0.31) |
| Grip strength (kg) | 8.21 | 0.52 (−0.22, 1.25) | 1.16 (−0.24, 2.56) |
Bold = significant at p < .05.
In the multivariable model for cortical vBMD, Asian race was no longer significant. African‐American race, body weight, alcohol consumption, and diabetes were associated with higher cortical vBMD, whereas fracture history, use of thyroid medication, and longer time to complete chair stands were associated with lower cortical vBMD.
For the most part, the directions for the associations with femoral neck aBMD were similar to those for vBMD. African‐American race, body weight, alcohol comsumption, physical activity, diabetes, and use of Cox‐2 inhibitors, nonthiazide diuretics, or statins were positively associated with aBMD, whereas greater weight change, height, height change, past smoking, fracture history, maternal history of fracture, kidney stones, and use of thyroid medication were negatively associated with aBMD. The magnitude of the relationship tended to be stronger for vBMD than for aBMD, especially for race, smoking, diabetes, and corticosteroid use. Of interest, the association between body weight and BMD was much stronger for aBMD than for vBMD, where there was no association between weight and trabecular vBMD but a weak positive association with cortical vBMD.
Multivariable correlates of lumbar spine trabecular vBMD and aBMD (Tables 3 and 6)
Multivariate models explained 20% and 13% of the variance in the lumbar spine trabecular vBMD and aBMD, respectively. African‐Americans had the greatest lumbar spine trabecular vBMD: 33.1% higher than white men compared with only a 5.7% difference for lumbar spine aBMD. Men with diabetes had 10.7% higher vBMD compared with 5.0% higher aBMD relative to those without diabetes. Use of antiandrogens and TZDs was associated with 19% and 22%, respectively, lower trabecular vBMD. Antiandrogens similarly were associated with lower aBMD, but the negative impact of TZDs on BMD was much stronger for trabecular vBMD versus aBMD. Five‐year increase in age was associated with lower trabecular vBMD but higher aBMD. Body weight similarly was associated with higher aBMD and vBMD, whereas weight change was associated with lower aBMD and height with lower vBMD. Smoking was associated with 5% lower trabecular vBMD but was unrelated to aBMD. Similar results were observed for COPD. Finally, longer time to complete five chair stands was negatively associated with aBMD.
Multivariable models with sex steroid hormones
In multivariable models, bioavailable estradiol was significantly associated with higher aBMD and cortical vBMD in the femoral neck (Table 4). A 1 SD increase in bioavailable estradiol was associated with about a 4.5% higher femoral neck trabecular vBMD, but the association was only borderline significant (p = .06). A stronger and statistically significant association was found between bioavailable estradiol and both lumbar spine aBMD and trabecular vBMD. There was no association between bioavailable testosterone and femoral neck aBMD or vBMD. However, a 1 SD increase in bioavailable testosterone was associated with a 2.76% higher spine trabecular vBMD. Finally, sex hormone–binding globulin was negatively related to both aBMD and trabecular vBMD of the spine but was unrelated to femoral neck vBMD.
Table 4.
Multivariable Association Between Sex Steroid Hormones and Femoral Neck and Lumbar Spine BMD
| Variable | Unit | Percentage change in bone mass percent (95% confidence interval) | ||||
|---|---|---|---|---|---|---|
| Femoral Neck | Lumbar Spine | |||||
| aBMD | Trabecular vBMD | Cortical vBMD | aBMD | Trabecular vBMD | ||
| Bioavailable estradiol (pg/mL) | 5.4 | 1.5 (0.4, 2.7) | 4.5 (−0.2, 9.2) | 1.02 (0.2, 1.9) | 2.44 (1.2, 3.7) | 4.98 (2.6, 7.4) |
| Bioavailable testosterone (ng/dL) | 79.8 | −0.75 (−0.4, 1.8) | −0.59 (−4.0, 5.2) | 0.01 (−0.8, 0.8) | −0.74 (−0.5, 2.0) | 2.76 (0.4, 5.1) |
| Sex hormone–binding globulin (nM) | 19.6 | −0.77 (−1.9, 0.4) | −4.4 (−0.9, 0.4) | −0.55 (−1.4, 0.3) | −1.56 (−2.8, −0.3) | −3.69 (−6.1, −1.2) |
Note: Femoral neck multivariable models were adjusted for age, race, weight, weight change since age 25, height, height change since age 25, past smoking, alcohol, physical activity, total calcium intake, history of nontrauma fracture after age 50, maternal and paternal history of fracture, medical history (diabetes, hypertension, hypothyroid, Parkinson's disease, kidney stones), medications (Cox‐2 inhibitor, NSAID, nonthiazide diuretic; statin, SSRI, thyroid, corticosteroid, insulin), neuromuscular function (chair stands, grip strength). Lumber spine multivariable models were adjusted for age, race, weight, weight change since age 25, height, height change since age 25, past smoking, alcohol, calcium intake, history of nontrauma fracture after age 50, maternal history of fracture, medical history (diabetes, hypertension, osteoarthritis, COPD, Parkinson's disease, kidney stones), medications (Cox‐2 inhibitor, beta blocker, corticosteroid,TZD), back pain, neuromuscular function (gait speed, chair stands, and grip strength).
Bold = significant at p < .05.
Discussion
In this population of community‐dwelling older men, the associations among demographic, anthropometric, lifestyle, historical (medical and family), and neuromuscular factors were stronger for trabecular than cortical vBMD (Tables 5 and 6). Overall, race and diabetes were the strongest consistent positive correlates, whereas history of nontraumatic fractures was the strongest consistent negative correlate. The strong negative association between maternal family history of fracture and trabecular vBMD underscores the importance of identifying the specific genes that contribute to the heritability of trabecular versus cortical vBMD in men. Indeed, a recent paper by Yerges and colleagues22 showed that genetic associations differed for cortical and trabecular vBMD. There was no association between paternal history of fracture, perhaps reflecting a shorter life span in men and less “opportunity” for fracture in this generation. Awareness of lifestyle, behavioral, medical, and historical factors correlated with vBMD may improve our ability to identify men at greatest risk of osteoporosis and related fractures.
Table 5.
Multivariate Correlates of Femoral Neck BMD: Areal BMD, Trabecular vBMD, Cortical vBMD
| Variable | aBMD | Trabecular vBMD | Cortical vBMD |
|---|---|---|---|
| Demographics | |||
| Age | 0 | − − − − | 0 |
| Race | |||
| White (Ref) | |||
| African‐American | ++ + ++ | ++ + ++ | +++ |
| Asian | 0 | ++ + ++ | 0 |
| Hispanic/Other | 0 | 0 | 0 |
| >High school education | 0 | 0 | 0 |
| Anthropometry | |||
| Weight | +++ | 0 | ++ |
| Weight change since age 25 | − − | 0 | 0 |
| Height | − − | 0 | 0 |
| Height change since age 25 | − | − − − | 0 |
| Lifestyle | |||
| Past smoking | − − | − − − − | 0 |
| Alcohol | ++ | 0 | + |
| Physical activity (PASE) | + | 0 | 0 |
| Diet | |||
| Total calcium | 0 | +++ | 0 |
| Fracture history | |||
| Nontrauma fracture (any) | − − − | − − − − − | − − |
| Mother fracture (any) | − − | − − − − | 0 |
| Father fracture (any) | 0 | 0 | 0 |
| Medical history | |||
| Diabetes | +++ | ++ + ++ | ++ |
| Hypertension | 0 | +++ | 0 |
| Hypothyroid | 0 | 0 | 0 |
| Parkinson's | 0 | 0 | 0 |
| Kidney stones | − − | − − − − | 0 |
| Medications | |||
| Cox‐2 inhibitor | +++ | ++ + ++ | 0 |
| NSAID | 0 | − − − − | 0 |
| Nonthiazide diuretic | ++ | 0 | 0 |
| Statin | ++ | 0 | 0 |
| SSRI | 0 | 0 | 0 |
| Thyroid | − − − | 0 | − − |
| Corticosteroid (any, inhaled or oral) | 0 | − − − − − | 0 |
| Insulin | 0 | − − − − − | 0 |
| Neuromuscular | |||
| Chair stands | 0 | 0 | − |
| Grip strength | 0 | 0 | 0 |
| Sex steroid hormones | |||
| Bioavailable estradiol | ++ | 0 | + |
| Bioavailable testosterone | 0 | 0 | 0 |
| Sex hormone–binding globulin | 0 | 0 | 0 |
Note: Five symbols indicate ≥ 10% change in BMD per unit change in variable; four symbols indicate 5% to <10% change; three symbols, a 3% to 5% change in BMD per unit change in variable; two symbols, a 1% to 3% change, and one symbol, a change of less than 1%. 0 means that the variable was not related. See Tables 2 and 3 for definitions of unit change.
Table 6.
Multivariate Correlates of Lumbar Spine BMD: Areal BMD, Trabecular vBMD
| Variable | aBMD | Trabecular vBMD |
|---|---|---|
| Demographics | ||
| Age | ++ | − − − − |
| Race | ||
| White (Ref) | ||
| African‐American | ++ + + | ++ + ++ |
| Asian | 0 | 0 |
| Hispanic/other | − − − | 0 |
| Anthropometry | ||
| Weight | +++ | +++ |
| Weight change since age 25 | − − − | 0 |
| Height | 0 | − − − − |
| Height change since age 25 | 0 | 0 |
| Lifestyle | ||
| Past smoking | 0 | − − − |
| Alcohol | + | 0 |
| Diet | ||
| Total calcium | 0 | ++ |
| Fracture history | ||
| Nontrauma fracture (any) | − − − | − − − − |
| Mother fracture (any) | − − | 0 |
| Medical history | ||
| Diabetes | ++ + + | ++ + ++ |
| Hypertension | ++ | 0 |
| Osteoarthritis | ++ | 0 |
| COPD | 0 | − − − |
| Parkinson's | − − − − | 0 |
| Kidney stones | − − | 0 |
| Medications | ||
| Antiandrogen | − − − − − | − − − − − |
| Cox‐2 inhibitor | ++ | 0 |
| Beta blocker | 0 | 0 |
| Corticosteroid (any, inhaled or oral) | − − − | 0 |
| TZD | − − − − | − − − − − |
| General health | ||
| Back pain last 12 months | ++ | 0 |
| Neuromuscular | ||
| Gait speed | − − | 0 |
| Chair stands | − | − |
| Grip strength | 0 | 0 |
| Sex steroid hormones | ||
| Bioavailable estradiol | ++ | +++ |
| Bioavailable testosterone | 0 | ++ |
| Sex hormone–binding globulin | − − | − − − |
Note: Five symbols indicate ≥ 10% change in BMD per unit change in variable; four symbols indicate 5% to <10% change; three symbols, a 3% to 5% change in BMD per unit change in variable; two symbols, a 1% to 3% change, and one symbol, a change of less than 1%.
Diabetes mellitus was associated with higher aBMD and vBMD at both the femoral neck and lumbar spine, with the association strongest for trabecular vBMD. The observation that diabetes was associated with greater BMD is consistent with findings from other studies of aBMD in older men.23, 24, 25, 26 Most previous studies were limited to aBMD, but our results are consistent with the results from the Health ABC Study, in which men with diabetes had significantly higher lumbar spine trabecular vBMD.25 Diabetes also was strongly associated with higher trabecular but not cortical vBMD in the peripheral skeleton.27, 28 Since most men in this study had type 2 diabetes, it is possible that hyperinsulinemia may contribute to greater bone density. This finding also may reflect the impact of greater body weight on skeletal loading, although after adjustments for body weight this association still existed, suggesting that additional osteogenic factors may play a role selectively on trabecular but not cortical vBMD. Recent experiments have shown a reciprocal relationship between bone remodeling and energy metabolism.29 In animal experiments, leptin inhibits insulin secretion, and this inhibition appears to be under neuronal control. A component of this neuronal regulation is sympathetic innervation to the osteoblast. Thus the osteoblast itself may be a specific endocrine cell type.
Use of insulin was negatively correlated with trabecular vBMD of the femoral neck. TZDs were negatively associated with trabecular vBMD and aBMD of the lumbar spine but were unrelated to femoral neck trabecular or cortical vBMD. The association with trabecular spine vBMD but not trabecular femoral neck vBMD is somewhat surprising but may reflect the overall lower proportion of trabecular vBMD at the hip. Use of insulin may be a marker of more severe disease and may explain why it is associated with lower vBMD. The negative association between TZDs and lower spine BMD is consistent with the higher fracture rates observed among TZD users.30 Previous reports have shown greater spine and hip aBMD loss in women but not men using TZDs,31 whereas others have shown greater spine and hip aBMD loss in men treated with TZDs.32 It has been suggested that the divergent skeletal responses to TZDs may reflect different genetic backgrounds.33
A number of other medical conditions were correlated with vBMD. Hypertension was associated with greater femoral neck trabecular vBMD but not spine trabecular vBMD in multivariable models. Hypertension also was linked with higher trabecular vBMD at the radius but not tibia using peripheral QCT.27 Hypertension has been associated with abnormalities in calcium metabolism, leading to increased calcium losses and secondary activation of the parathyroid gland.34 The positive association between hypertension and BMD was independent of body weight and may result from confounding by the use of medications that may increase BMD such as thiazide diuretics, a common medication used to treat hypertension.
Previous studies have shown that SSRI use was associated with lower hip aBMD and more rapid bone loss in both sexes.35 We found no association between SSRIs and either aBMD or vBMD, perhaps reflecting lower power in this smaller population of MrOS men.
Several differences between the correlates of aBMD and vBMD are noteworthy. In particular, it is well established that body weight is strongly positively associated with aBMD, but at least for the hip, we found much weaker associations with vBMD. This suggests that body weight facilitates at least some of its positive effects on aBMD through effects on bone size. While past smoking was weakly related to lower aBMD of the femoral neck and unrelated to lumbar spine aBMD, smoking had a strong negative impact on trabecular vBMD at both the spine and hip. A study of Afro‐Caribbean men also reported a negative association between smoking and trabecular but not cortical vBMD in the peripheral skeleton.36 The Gothenburg Osteoporosis and Obesity Determinants (GOOD) Study also found no association with cortical vBMD.37 Because trabecular bone is more metabolically active, trabecular bone may be more sensitive to the influences of smoking. Cigarette smoking also has been shown to enhance metabolic clearance of estrogen, which may lead to lower vBMD.38 Another possible mechanism for direct effects of smoking on bone includes a direct effect of nicotine on bone metabolism and BMD by inhibiting the proliferation of osteoprogenitor cells in a concentration‐dependent manner.39, 40
Parkinson's disease was strongly associated with lower aBMD of the spine but was not related to spine trabecular vBMD, perhaps reflecting low power owing to the low prevalence of Parkinson' s disease and the increased variability and reduced precision of QCT. We have shown previously that MrOS men with Parkinson's disease experienced faster areal bone loss and had an increased risk of fracture.41
A history of kidney stones was associated with lower femoral neck trabecular vBMD but not cortical vBMD, consistent with observations that individuals who are calcium stone formers have increased bone resorption, lower BMD,42 and higher cytokine activity,43 which would preferentially influence the more metabolically active trabecular bone.
Alcohol consumption was positively related to aBMD at both the spine and hip and cortical vBMD at the femoral neck but was unrelated to trabecular vBMD. The associations, however, were quite modest. Previous studies have shown that moderate alcohol consumption (fewer than 2 drinks per day) has a positive association with aBMD in men but no association with cortical or trabecular vBMD of the peripheral skeleton.36, 44, 45 The mechanism for this association is unclear, but it could reflect a “healthy user” effect because moderate alcohol consumption is associated with a lower total mortality.46 Alcohol also may increase BMD by raising sex steroid hormone levels47 or by direct effects on the aromatase gene.48 More research is needed to further our understanding of why alcohol's beneficial effects may be limited to cortical vBMD.
A 5‐year increase in age was associated with a 5% to 10% lower trabecular vBMD at the spine and hip but was not significantly related to cortical vBMD. The lack of association with cortical vBMD is somewhat surprising because most studies have shown age‐related losses in both trabecular and cortical vBMD.49 For example, Riggs and colleagues observed a substantial loss in cortical vBMD in men after the average age of 75. However, our results are limited to cross‐sectional comparisons across age groups and may mask individual changes in BMD in specific age groups over the long term. The stronger association with trabecular vBMD likely reflects the higher rate of bone turnover in trabecular bone and age‐associated increases in bone remodeling.
In multivariate models, higher calcium intake was positively associated with trabecular vBMD at both the hip and spine but was not related to cortical vBMD. This may reflect a beneficial effect of calcium on bone turnover that may be more evident in the more metabolically active trabecular bone.
Corticosteroids were strongly negatively correlated with trabecular vBMD at the hip but not cortical vBMD, likely reflecting the negative effects of glucocorticoids on osteoblasts, osteocytes, and osteoclasts leading to decreased bone formation and excessive bone resorption.50 The major effect on trabecular vBMD is consistent with the observation that fractures in patients receiving chronic glucocorticoid therapy occur more frequently at sites enriched with trabecular bone.51
Men who reported taking thyroid supplements had lower cortical vBMD of the femoral neck but not trabecular vBMD. Biochemical hyperthyroidism has been associated with lower BMD at the trabecular‐rich ultradistal (both sexes) and distal (women) forearm.52 This is in contrast to our finding that thyroid hormone supplements have major effects in cortical vBMD. More research is needed on the skeletal effects of thyroid hormones in both men and women.
Use of NSAIDS was associated with lower femoral neck trabecular vBMD but was unrelated to aBMD or cortical vBMD. On the other hand, Cox‐2 inhibitors were strong positive correlates of especially femoral neck trabecular vBMD. Examination of the relationships of NSAIDs with BMD by Cox selectivity showed that users of NSAIDs who had higher Cox‐2 selectivity had higher BMD values at multiple sites.53 Previous studies that showed positive correlations between NSAIDs and BMD may be spurious because they did not account for Cox‐2 selectivity.
In the subset of men with sex steroid hormone data, we found the strongest relationship between sex steroid hormone levels and lumbar spine trabecular vBMD: All three sex hormones were significantly related to trabecular vBMD in the multivariate model, with the strongest association with bioavailable estradiol. This observation is generally consistent with previous studies that demonstrated positive and consistent associations with bioavailable estradiol.54 The stronger association with trabecular vBMD may reflect a direct effect of sex hormones on rates of bone turnover. The magnitude of the association between bioavailable estradiol and lumbar spine vBMD was similar to a 1 SD increase in body weight. Previous studies have not consistently reported an association between testosterone and BMD.55, 56 Most of these studies, however, have been confined to aBMD. We found a positive association between testosterone and trabecular vBMD of the spine, highlighting the need to further explore the influence of sex hormones on trabecular versus cortical bone compartments. Sex hormone–binding globulin was negatively correlated with both aBMD and vBMD of the spine, consistent with the observation that high sex hormone–binding globulin has been linked to an increased risk of fracture.57 In general, the sex steroid hormones were not related to femoral neck vBMD except for a relatively weak association with cortical vBMD. The observation that the sex steroids hormones were more strongly associated with lumbar spine trabecular vBMD than femoral neck vBMD may reflect the relatively small proportion of trabecular vBMD at the femoral neck.
Several associations likely reflected an indication bias, which exists when a drug is prescribed for a condition that itself is associated with the outcome of interest. For example, men reporting use of osteoporosis medications or calcium supplements had lower vBMD values, likely reflecting their diagnosis and treatment of osteoporosis.
This study has several potential limitations. The MrOS cohort is limited to generally healthy community‐dwelling men and may not be generalizable to other groups. Some analyses, such as steroid use or smoking, were limited in power because of low numbers; for example, only 3.5% of our cohort were current smokers. Habits and history, which were assessed by questionnaire or through interviews, may be compromised by inaccurate recall. Although we examined a large number of potential correlates, the aggregate effect of all these factors on BMD, however, was modest, which highlights the need to identify new risk factors for variations in vBMD and aBMD. Sex steroid hormones were available on fewer than a third of the sample of men with QCT data. Finally, this study was a cross‐sectional design, and therefore, causality cannot be assessed.
On the other hand, this study has several strengths. The MrOS cohort is a large population‐based study of ethnically diverse older men. The large number of covariates examined helps to provide greater insight into correlates of vBMD. Given this study design, we were able to directly compare DXA‐ and QCT‐derived measures and to separately examine trabecular and cortical compartments.
In conclusion, in this study of older, ethnically diverse men, a number of important associations that may help to identify men at risk for osteoporosis and related fractures were identified. Correlates of trabecular vBMD and cortical vBMD appear to differ among older men.
Disclosures
JAC has received research support from Merck & Co, Inc., Pfizer Pharmaceuticals, and Novartis Pharmaceuticals. She also has received consulting fees from Novartis Pharmaceuticals. KLS is a consultant for Sepracor, Inc., and paid speaker for Sanofi‐Aventis. EB‐C has received grant support and/or consulting fees from Amgen, Eli Lilly and Co., Merck & Co., Inc., and Pfizer Pharmaceuticals. TB receives partial salary support from Eli Lilly and Co. All the other authors state that they have no conflicts of interest.
Acknowledgements
The Osteoporotic Fractures in Men (MrOS) Study is supported by NIH funding. The following institutes provide support: the National Institute of Arthritis and Musculoskeletal and Skin Diseases (NIAMS), the National Institute on Aging (NIA), the National Center for Research Resources (NCRR), and the NIH Roadmap for Medical Research under the following grant numbers: U01 AR45580, U01 AR45614, U01 AR45632, U01 AR45647, U01 AR45654, U01 AR45583, U01 AG18197, U01‐AG027810, and UL1 RR024140.
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