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Abstract

  1. Top of page
  2. Abstract
  3. INTRODUCTION
  4. SUBJECTS AND METHODS
  5. RESULTS
  6. DISCUSSION
  7. AUTHOR CONTRIBUTIONS
  8. Acknowledgements
  9. REFERENCES

Objective

To determine the effect of 6 years of routine management on body composition, physical functioning, and quality of life, and their interrelationships, in men with idiopathic vertebral fracture.

Methods

Twenty men with idiopathic vertebral fracture (patients: mean ± SD age 58 ± 6 years) were age and height matched to 28 healthy controls with no known disease. The primary outcome was skeletal muscle mass (appendicular lean mass by dual x-ray absorptiometry) assessed at 2 visits (0 and 6 years). Physical functioning and quality of life domains were assessed by the Senior Fitness Test and Short Form 36 (SF-36) questionnaire at visit 2 only. Data were analyzed by repeated-measures analysis of variance, independent t-tests, and correlation.

Results

At visit 1, appendicular lean mass was 9% lower in patients than controls. Although patients better maintained appendicular lean mass between visits (interaction P = 0.016), at visit 2 appendicular lean mass remained 5% lower in patients than controls. Furthermore, patients' appendicular lean mass change was correlated with femoral neck bone density change (r = 0.507, P = 0.023). Physical function tests were 13–27% lower in patients compared with controls (P = 0.056 to 0.003), as were SF-36 quality of life physical domains (13–26% lower; P = 0.028 to <0.001).

Conclusion

Despite an association between changes in muscle mass and bone density, routine management of men with idiopathic vertebral fracture does not address muscle loss. Combined with the observation of reduced physical functioning and quality of life, this study identifies novel targets for intervention in men with idiopathic vertebral fracture.


INTRODUCTION

  1. Top of page
  2. Abstract
  3. INTRODUCTION
  4. SUBJECTS AND METHODS
  5. RESULTS
  6. DISCUSSION
  7. AUTHOR CONTRIBUTIONS
  8. Acknowledgements
  9. REFERENCES

At age 50 years, the lifetime risk of osteoporotic fractures in men is substantial (1). Although osteoporosis is generally more common in women, morphometrically assessed vertebral fracture occurs in men with a similarly high incidence (2). In men, osteoporotic fractures typically occur later in life, and consequently mortality after fracture is higher (3, 4). As a result, osteoporotic fractures in men have a considerable impact on the burden of health care costs and diminish quality of life (1, 5).

Treatment of men with idiopathic osteoporosis focuses on reducing bone loss and preventing fractures. Very rarely does treatment specifically address comorbidities associated with osteoporosis that also impact outcome and quality of life. Previously, we have shown that at diagnosis, skeletal muscle mass is lower in men with idiopathic vertebral fracture (6, 7). Such differences in body composition are of potential importance. First, it is well established that muscle loss is generally associated with poor outcomes, including disability, decreased quality of life, and increased morbidity and mortality (8–11). Second, loss of muscle may predispose to fracture in states of low bone mass due to increased fall risk and loss of protective tissue cushioning (12–14). Third, muscle tension on bone may be important for maintaining bone mineral density (BMD) (15), and muscle may act as a source of hormones that maintain bone density (16, 17).

Despite the potential importance of altered body composition and a link between bone and muscle identified in healthy men (13, 18), muscle loss remains poorly recognized in men with idiopathic vertebral fracture, and relationships between body composition and bone have not been adequately determined. Furthermore, whether muscle loss decreases physical functioning and impacts quality of life in men with idiopathic vertebral fracture has not been well investigated, and whether current clinical practice addresses these additional outcomes remains uncertain. Therefore, the first objective of this study was to determine the impact of 6 years of routine management of men with idiopathic vertebral fracture on body composition, physical function, and quality of life. The second objective was to investigate the relationships between these variables and, specifically, to determine whether soft tissue body composition influences BMD and quality of life. To achieve these objectives, a matched-cohort 6-year longitudinal study of men with idiopathic vertebral fracture receiving routine management was completed. Our hypotheses were that men with idiopathic vertebral fracture would have low muscle mass, low muscle strength, and impaired physical function compared with an age- and height-matched healthy control group without any known disease. Furthermore, after initial diagnosis, muscle mass would decline over time due to aging and/or the disease process. Finally, we hypothesized that correlations would be present between changes in muscle mass and changes in BMD, and between muscle mass, physical functioning, and quality of life.

Significance & Innovations

  • This study identified reduced muscle mass, physical functioning, and quality of life in men with idiopathic vertebral fracture.

  • Longitudinal data provided strong evidence of relationships between muscle mass and bone mineral density.

  • Cross-sectional relationships also suggested associations between muscle strength, physical functioning, and quality of life.

  • In men with idiopathic vertebral fracture, muscle mass and muscle strength are novel targets for intervention to increase bone strength and improve physical functioning, respectively, and addressing these targets may reduce fracture risk and increase quality of life.

SUBJECTS AND METHODS

  1. Top of page
  2. Abstract
  3. INTRODUCTION
  4. SUBJECTS AND METHODS
  5. RESULTS
  6. DISCUSSION
  7. AUTHOR CONTRIBUTIONS
  8. Acknowledgements
  9. REFERENCES

Study design.

A matched-cohort 6-year longitudinal study was completed. Men presenting with idiopathic vertebral fracture were followed up 6 years from the point of the initial diagnosis to investigate body composition, physical function, and quality of life. It was considered essential to control for changes in body composition that occur with healthy aging, but unethical to use a randomized design where patients with vertebral fracture received either treatment or no treatment. Alternatively, healthy controls matched for age and height were recruited and followed up for the same time period. Body composition was assessed at 2 visits, baseline and 6 years, and physical functioning and quality of life were determined at visit 2 only.

Setting and participants.

Patients with vertebral fracture were recruited (by SFE, CAS, and MWJD) using a convenience sampling method at metabolic bone clinics held at a specialist orthopedic hospital between May 2002 and September 2004. The main inclusion criteria were age <75 years and presence of idiopathic vertebral fracture. Fractures were ascertained from lateral radiographs of the spine (thoracic and lumbar region) and deformities were graded using the method of Black et al (19). At recruitment, the median number of fractures was 1.5 (range 1–7) (Table 1).

Table 1. Baseline demographic, anthropometric, and clinical data of men with idiopathic vertebral fracture and matched healthy controls*
 Vertebral fracture patients (n = 20)Controls (n = 28)P
  • *

    Values are the mean ± SD unless otherwise indicated. N/A = not applicable, as no statistical test was completed; IV = intravenous.

  • P values were determined by independent t-test or by Mann-Whitney U test, as appropriate.

  • Vertebral fractures were graded using the method of Black et al (19).

  • §

    Body mass was determined from balance scales.

  • P < 0.05.

Patients with graded vertebral fractures, no.  N/A
 Grade 110 
 Grade 2120 
 Grade 370 
Followup time, years5.5 ± 0.75.9 ± 0.70.081
Age, years58.4 ± 6.058.7 ± 6.80.905
Height, meters1.74 ± 0.081.73 ± 0.070.890
Body mass, kg§75.3 ± 11.881.8 ± 14.00.101
Body mass index, kg/m225.0 ± 3.727.1 ± 3.60.052
Alcohol intake, units/week11.2 ± 12.613.7 ± 11.70.481
Osteoporosis treatment, no. NoneN/A
 Ibandronate1  
 Risedronate5  
 Alendronate8  
 Pamidronate IV4  
 No treatment2  
Comorbid conditions, no.  N/A
 Hypertension35 
 Irritable bowel syndrome12 
 Arthritis32 
 Asthma31 
 Other   
  Diverticulitis1  
  Prostatic hyperplasia 1 
  Depression 1 
Smoker, no.14150.207
Requires mobility aid, no.620.038

At recruitment, secondary causes of osteoporosis were excluded, such as corticosteroid treatment, epilepsy, anticonvulsant medication, abnormal liver function tests, malabsorption disorders, eating disorders, alcohol abuse (>28 units/week), hypogonadism, hyperparathyroidism, hypo- or hypercalcemia, hypovitaminosis D, thyrotoxicosis, and endogenous hypersecretion of cortisol. Absence of secondary causes was confirmed by clinical examination, combined with biochemical tests undertaken by an NHS chemical pathology service. At recruitment, no patient had received treatment for osteoporosis. Patients were also excluded if their vertebral fracture was caused by trauma, if coincident fractures were present at other skeletal sites, if there was a neoplasm at any site, or if they had diabetes mellitus.

Healthy controls were recruited locally. The main exclusion criteria were as for idiopathic vertebral fracture patients, plus a vertebral deformity grade of 1 or greater (≥20%), ascertained by assessment of lateral dual x-ray absorptiometry (DXA) scans of the spine using the instant vertebral assessment protocol. Medical conditions or medication known to influence musculoskeletal health and history of any unexplained fracture also excluded controls. Participants were followed up during the period of June 2008 to May 2009. All of the participants gave written informed consent and the studies were approved by the North Wales (East) and North Staffordshire research ethics committees.

Outcome measures.

Whole body and regional areal BMD at the lumbar spine (L2–L4) and the femoral neck were assessed by a blinded operator (HLD) using DXA (QDR 4500A; Hologic), as described previously (7), with an operator precision of 1.45% (20). Areal BMD was expressed as gm/cm2. Coefficients of variation (CVs) relating to bone mineral content and BMD, performed on a spine phantom scanned daily during the followup period of the study, were 0.40% and 0.64%, respectively.

Using DXA, whole body lean, fat, and trunk fat mass were also determined (7). Appendicular lean mass was further defined as the sum of the lean mass of the 4 arms and legs and was the main outcome measure in this study, being a proxy measure of skeletal muscle mass (7, 13, 21). Appendicular lean mass was not normalized by height or body mass due to longitudinal changes in height and fat mass expected in participants. Operator precision of appendicular lean mass is reported to be 2.6% (22), and a step phantom was scanned before each scan (CV data not available).

Physical functioning was assessed by the Senior Fitness Test Battery (23). After a warm up, the participants completed the following physical tests: 1) upper extremity function was assessed by the 30-second arm curl test with a dumbbell (3.6 kg) and recording the number of repetitions completed; 2) lower body physical function was assessed using the 30-second sit-to-stand test and recording the number of repetitions completed; 3) lower body physical function and agility were assessed by 8-foot get up and go and recording the time taken; and 4) an estimate of aerobic endurance was determined using the 2-minute step test, the score being the number of full steps completed in 2 minutes.

Then, bilateral knee extension strength was assessed using an isometric chair (Bodycare Products) equipped with a load cell (Tedea Huntleigh 615 S Type; Vishay), resolved and converted to force in newtons by a data acquisition and analysis system (PowerLab 16SP; AD Instruments PTY). Finally, hand grip strength (dominant side) was measured using a hydraulic dynamometer (Saehan). The best of 3 maximal efforts was recorded. Adequate reliability of these physical function and strength tests has been shown previously by our group in patients with chronic kidney disease (24), and standard verbal instructions were provided by the unblinded assessors to motivate participants equally in each group.

Quality of life was measured using version 1 of the Medical Outcomes Study Short Form 36 (SF-36) (25). The SF-36 is a validated generic instrument that comprises 36 questions that relate to 8 different domains: physical health, role limitations due to physical and emotional health, bodily pain, general health, vitality, social functioning, and mental health. Using appropriate scoring algorithms (26), the raw scores were mapped to the 8 different domain scores and were transformed into a 0–100 score, with a low score indicating a poorer quality of life. To further aid interpretation, scores were presented using a norm-based method, and the 8 domains were also summarized into a physical and mental component summary score (27).

Statistical methods.

All data are presented as the mean ± SD and were analyzed using SPSS, version 18, with statistical significance set at P values less than or equal to 0.05 (2-tailed). After checking relevant assumptions, comparisons of baseline demographic characteristics and confounding variables were performed by using Student's t-tests or the Mann-Whitney U test, as appropriate. Longitudinal body composition data were analyzed by 2-factor repeated-measures analysis of variance with a within factor of time (visit 1 or visit 2) and a between factor of group (vertebral fracture patients or controls). Significant interactions were followed up with post hoc Tukey's tests. To provide an estimate of the sample size independent magnitude of the analysis of variance interaction and main effects, effect sizes were calculated by eta squared (η2) and can be interpreted as small (0.01), medium (0.06), or large (0.14) (28). Cross-sectional physical functioning and quality of life data were analyzed by Student's t-tests. To provide an estimate of the sample size independent magnitude of the cross-sectional difference between groups, effect sizes were calculated as Cohen's d and can be interpreted as small (0.2), medium (0.5), or large (0.8). Following visual inspection for outliers, relationships between variables were determined by Pearson's correlation coefficient (r).

Using Hopkins's method of estimating sample size for magnitude-based inferences (29), a minimum sample size of 12 vertebral fracture patients and 18 controls was calculated as follows: the smallest important difference in change in means for appendicular lean mass was assumed to be 1 kg, the within-subject SD (typical error) was calculated as 1.1 kg (using a between-subject SD of 3.5 and a test–retest correlation of 0.9, calculated from unpublished data collected by our group), the maximum chances of making Type I and II clinical errors were 0.5% and 25%, respectively, and the proportion in the vertebral fracture patient group was planned to be 40%.

RESULTS

  1. Top of page
  2. Abstract
  3. INTRODUCTION
  4. SUBJECTS AND METHODS
  5. RESULTS
  6. DISCUSSION
  7. AUTHOR CONTRIBUTIONS
  8. Acknowledgements
  9. REFERENCES

Of approximately 1,200 male patients referred to the clinic and of 195 healthy men (controls) who responded to advertisements to take part in the study, 31 vertebral fracture patients and 38 controls (all white) were initially included in the study. Reasons for exclusion were unable to determine eligibility (∼10%), did not consent (∼15%), and did not meet inclusion or matching criteria (∼75%). Eventually, 20 patients and 28 controls attended both visits and their data are included herein. Reasons for loss to followup were dropout between the first and second visits; reasons for vertebral fracture patients included loss of interest (n = 2), death (n = 4), and unable to be contacted (n = 5); and reasons for controls were loss of interest (n = 3), death (n = 3), unable to be contacted (n = 3), and metal implant precluding the DXA scan (n = 1).

Followup time and demographic and clinical variables of participants upon entering the longitudinal study are shown in Table 1. Reasons for referral of idiopathic vertebral fracture patients to the clinic included back pain (n = 16), unexplained fractures (n = 2), and family history of osteoporosis (n = 2). Age and height matching was successful, with no statistical differences between the groups at baseline. No other demographic or clinical variables were significantly different between the groups, except that the number of vertebral fracture patients using mobility aids was higher than controls. Eighteen of 20 vertebral fracture patients were prescribed a bisphosphonate for management of osteoporosis (2 patients did not receive a bisphosphonate due to not meeting the criteria for treatment).

Objective 1.

For lumbar spine BMD, there was a significant interaction by analysis of variance (Table 2). Significant post hoc tests suggested that at visit 1, BMD at the lumbar spine was 26% lower in vertebral fracture patients than in controls. Over the 6-year followup, BMD at the lumbar spine increased in vertebral fracture patients by 11% but did not change in controls. Nevertheless, at visit 2, BMD was still 19% lower in vertebral fracture patients. In contrast, for BMD at the femoral neck there were no significant interactions or main effects of time (Table 2), suggesting that femoral neck BMD did not change between visits 1 and 2 in either group. However, a significant main effect of group revealed that BMD at the femoral neck was 17% lower in the vertebral fracture patients at both visits 1 and 2.

Table 2. Longitudinal body composition of men with idiopathic vertebral fracture and matched healthy controls*
 Group, mean ± SDP (effect size [η2])Main effect of time
Vertebral fracture patients (n = 20)Controls (n = 28)InteractionMain effect of group
  • *

    aBMD = areal bone mineral density; BMC = bone mineral content.

  • P values were determined by repeated-measures analysis of variance. A significant interaction suggests that over time, vertebral fracture patients responded differently than controls; a significant main effect of group suggests that vertebral fracture patients were always different than controls; and a significant main effect of time suggests both groups changed over time. Effect size was calculated as eta squared (η2), where 0.01 = small, 0.06 = medium, and 0.14 = large effects.

  • P < 0.05.

Mean lumbar spine aBMD, gm/cm2  0.003 (0.11)< 0.001 (0.41)< 0.001 (0.37)
 Visit 10.81 ± 0.141.09 ± 0.15   
 Visit 20.91 ± 0.151.12 ± 0.16   
Femoral neck aBMD, gm/cm2  0.203 (0.03)< 0.001 (0.30)0.788 (0.00)
 Visit 10.70 ± 0.110.84 ± 0.11   
 Visit 20.69 ± 0.110.83 ± 0.11   
Whole body BMC, kg  0.057 (0.07)< 0.001 (0.33)0.354 (0.02)
 Visit 12.2 ± 0.42.7 ± 0.4   
 Visit 22.2 ± 0.42.7 ± 0.4   
Lean mass, kg  0.732 (0.00)0.100 (0.06)0.152 (0.04)
 Visit 155.1 ± 7.559.1 ± 7.0   
 Visit 255.7 ± 8.459.5 ± 8.1   
Fat mass, kg  0.352 (0.02)0.435 (0.01)0.022 (0.11)
 Visit 117.9 ± 6.019.0 ± 6.8   
 Visit 218.5 ± 7.020.5 ± 7.9   
Trunk fat mass, kg  0.495 (0.01)0.330 (0.01)< 0.001 (0.25)
 Visit 19.8 ± 3.610.8 ± 4.0   
 Visit 210.9 ± 4.412.3 ± 5.0   
Total body mass, kg  0.704 (0.01)0.137 (0.05)0.028 (0.49)
 Visit 175.1 ± 12.380.8 ± 13.3   
 Visit 276.5 ± 14.482.7 ± 14.5   

Body composition data are also shown in Table 2. As shown by a significant main effect of group, whole body bone mineral content was 19% lower in vertebral fracture patients compared with controls at both visits 1 and 2. As shown by significant main effects of time, total body mass and fat mass increased between visits 1 and 2 in both groups. The increase in fat mass of 6% is equivalent to a +2 kg increase per decade. Trunk fat mass also significantly increased over the followup period by 11% (equivalent to +1.8 kg per decade). Although no interactions were shown for whole body composition parameters, there was a significant interaction between time and group for appendicular lean mass (Figure 1). Appendicular lean mass decreased in the control group (by 2%, equivalent to −1.1 kg per decade) but did not change in the vertebral fracture patient group (nonsignificant increase of 1%, equivalent to +0.5 kg per decade). Nevertheless, appendicular lean mass was lower in vertebral fracture patients compared with controls throughout the study, being 9% lower at visit 1 and 5% lower at visit 2, with both differences attaining significance in post hoc tests.

thumbnail image

Figure 1. Longitudinal appendicular lean mass in 20 men with idiopathic vertebral fracture and 28 matched healthy controls. Data are the mean ± SD. The broken line shows the vertebral fracture patients and the solid line shows the healthy controls. Tukey's post hoc tests suggested that the controls lost appendicular lean mass between the 2 visits (mean ± SD 26.8 ± 4.0 versus 26.2 ± 3.8; P < 0.05). In contrast, the vertebral fracture patients' appendicular lean mass did not change (mean ± SD 24.5 ± 3.6 versus 24.8 ± 4.0; P > 0.05). * = significant interaction by repeated-measures analysis of variance (P = 0.016, η2 = 0.12 [medium to strong effect size]).

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Physical functioning data, collected during visit 2 at the end of the followup period, are shown in Table 3. Measures of muscle strength were lower in vertebral fracture patients compared with controls by 13% and 19%, respectively, for hand grip and bilateral knee extension strength, although the latter result narrowly failed to attain statistical significance. All of the measures of functional capacity were significantly lower in vertebral fracture patients: arm curl by 19%, sit-to-stand by 27%, get up and go by 26%, and the step test by 20%.

Table 3. Physical functioning of men with idiopathic vertebral fracture and matched healthy controls
 Vertebral fracture patients (n = 20), mean ± SDControls (n = 28), mean ± SDP (effect size [d])*
  • *

    P values were determined by independent t-test. Effect size was calculated as Cohen's d, where 0.2 = small, 0.5 = medium, and 0.8 = large effects.

  • P < 0.05.

Hand grip strength, newtons375 ± 100429 ± 830.049 (0.58)
Bilateral leg extension strength, newtons299 ± 124371 ± 1260.056 (0.56)
Arm curl test, reps in 30 seconds13 ± 516 ± 60.040 (0.55)
Sit-to-stand test, reps in 30 seconds8 ± 411 ± 30.003 (0.77)
Get up and go test, seconds7.3 ± 3.25.4 ± 1.10.021 (0.79)
Step test, reps in 2 minutes80 ± 23100 ± 240.005 (0.78)

Quality of life collected during visit 2 is shown in Table 4. The physical summary score was significantly lower in vertebral fracture patients compared with controls by 25%. Also, the individual domain scores for physical function (26%), role physical (21%), bodily pain (15%), general health (17%), vitality (13%), and social functioning (18%) were significantly lower in the vertebral fracture patients compared with the controls. In contrast, the mental summary score and the role emotional and mental health domain scores were not significantly different between the vertebral fracture patients and controls.

Table 4. Quality of life in men with idiopathic vertebral fracture and matched healthy controls*
 Vertebral fracture patients (n = 20)Controls (n = 28)P (effect size [d])
  • *

    Values are the mean normative-based scores ± SD.

  • P values were determined by independent t-test. Effect size was calculated as Cohen's d, where 0.2 = small, 0.5 = medium, and 0.8 = large effects.

  • P < 0.05.

Physical component summary38 ± 1150 ± 8< 0.001 (1.29)
Mental component summary53 ± 956 ± 60.293 (0.34)
Physical function38 ± 1352 ± 6< 0.001 (1.45)
Role-physical41 ± 1351 ± 100.004 (0.93)
Bodily pain45 ± 1153 ± 100.013 (0.75)
General health42 ± 951 ± 70.001 (1.07)
Vitality47 ± 1254 ± 100.028 (0.66)
Social functioning45 ± 1354 ± 60.005 (1.03)
Role-emotional48 ± 1253 ± 60.099 (0.56)
Mental health53 ± 756 ± 70.142 (0.44)

Objective 2.

Longitudinal correlation analyses revealed that the change in appendicular lean mass was significantly correlated with the change in BMD at the femoral neck in the vertebral fracture patient group (Pearson's r = 0.507, P = 0.023) but not in the control group (r = 0.267, P = 0.169). No such correlations were present between appendicular lean mass and lumbar spine BMD, or between fat mass and BMD at any site (data not shown).

Cross-sectional correlation analyses revealed that muscle mass was significantly correlated with hand grip and leg extension strength measures, but only in control participants (Table 5). Muscle mass was not correlated with any physical function test in either group (Pearson's r ranged from 0.041 to 0.300, P ranged from 0.865 to 0.199). Muscle mass was also not correlated with quality of life in either group (selected correlations shown in Table 5).

Table 5. Relationships between strength, physical functioning, and body composition variables in 20 men with idiopathic vertebral fracture and 28 matched healthy controls*
Variable and groupMuscle massArm curlSit-to-stand testGet up and go test2-minute step test
  • *

    Values are the Pearson's correlation coefficient (P). N/A = not applicable.

  • P < 0.05.

Strength: hand grip  N/AN/AN/A
 Controls0.437 (0.020)0.520 (0.005)   
 Vertebral fracture patients0.385 (0.094)0.392 (0.087)   
Strength: bilateral leg extensor N/A   
 Controls0.402 (0.034) 0.476 (0.010)−0.476 (0.011)0.406 (0.032)
 Vertebral fracture patients0.360 (0.119) 0.564 (0.010)−0.612 (0.004)0.651 (0.002)
Quality of life: physical summary score     
 Controls−0.068 (0.729)0.382 (0.045)0.515 (0.005)−0.518 (0.005)0.552 (0.002)
 Vertebral fracture patients−0.006 (0.909)0.721 (< 0.001)0.709 (< 0.001)−0.653 (0.002)0.741 (< 0.001)
Quality of life: body pain     
 Controls−0.014 (0.945)0.362 (0.059)0.515 (0.005)−0.487 (0.009)0.526 (0.004)
 Vertebral fracture patients−0.198 (0.402)0.608 (0.004)0.807 (< 0.001)−0.714 (< 0.001)0.703 (0.001)

In contrast, hand grip strength and bilateral leg extension strength were generally correlated with upper and lower body physical functioning, respectively, in both groups (Table 5). Furthermore, leg extension strength was significantly correlated with quality of life domains (vertebral fracture patients: r ranged from 0.567 to 0.608, P ranged from 0.004 to 0.002); in contrast, hand grip strength was not related to quality of life (vertebral fracture patients: r ranged from 0.307 to 0.233, P ranged from 0.188 to 0.324). There were no significant correlations between muscle strength and BMD at any site (vertebral fracture patients and controls: r ranged from 0.082 to 0.356, P ranged from 0.824 to 0.063).

For physical functioning, function tests were positively and strongly associated with quality of life. Relationships were strongest in the vertebral fracture patient group, especially for the physical component summary and the bodily pain domains (selected correlations shown in Table 5).

DISCUSSION

  1. Top of page
  2. Abstract
  3. INTRODUCTION
  4. SUBJECTS AND METHODS
  5. RESULTS
  6. DISCUSSION
  7. AUTHOR CONTRIBUTIONS
  8. Acknowledgements
  9. REFERENCES

To our knowledge, this is the first longitudinal study of body composition–related outcomes in men undergoing routine management of idiopathic vertebral fracture. Consistent with our hypotheses and our previous work (6, 7), at diagnosis (visit 1) muscle mass was reduced in patients with idiopathic vertebral fracture. However, a novel and unexpected finding was that muscle mass did not decline any further in the vertebral fracture patients over the 6-year followup period, despite an aging-associated decline of muscle mass in controls. Nevertheless, muscle mass remained significantly reduced in idiopathic vertebral fracture patients at visit 2, as were physical function and quality of life. Determination of relationships between variables also revealed novel and important findings. A longitudinal analysis provided strong evidence of a relationship between muscle mass and bone strength: loss of appendicular lean mass was correlated with loss of bone density at the femoral neck. Cross-sectional analyses further suggested that physical functioning was correlated with quality of life.

For soft tissue body composition, at the whole body level both groups responded as would be expected from previous studies on normal aging. For example, fat mass typically increases at a rate of 0.4 kg per year (30) until age 60 years, very similar to that observed here in both groups. Although lean mass is generally assumed to decline with age, this becomes most apparent after age 60 years (31), eventually attaining a 1.5 kg per decade loss in old age (32). Therefore, in our study's participants, whose mean age was only 58 years, we found that lean mass did not decline. Furthermore, total body mass was gained in the present study, indicative of improved nutritional status that would be expected to moderate lean mass loss (33).

However, of particular note in this study are the regional body composition changes. Despite no changes in total lean mass, appendicular lean mass was lost in the control group. This is highly indicative of skeletal muscle mass loss (21), which has been shown previously with aging (31, 34), and is likely to increase risk of disability (35). However, such a loss of appendicular lean mass was not present in the vertebral fracture patient group, which is surprising since muscle mass is not currently targeted by clinical interventions. The majority of our patients (18 of 20) were receiving bisphosphonates to manage fracture risk. While bisphosphonates are not recognized as having muscle anabolic actions, potential reduction in (musculoskeletal) pain (36) may have increased physical functioning and indirectly influenced muscle mass. Other lifestyle changes implemented at the time of diagnosis, or some other factor not investigated, also may have acted to preserve muscle mass. Nevertheless, it should be recognized that appendicular lean mass in the vertebral fracture patients did not attain control group values, and could consequently still influence outcome (8–11), including risk of further fracture (37).

The regional changes are also particularly important, since appendicular lean mass change was correlated with femoral neck BMD change. Therefore, these findings provide the first longitudinal evidence for an association between muscle mass and bone density in men with idiopathic vertebral fracture, extending previous cross-sectional data (6, 7) and confirming the few longitudinal studies completed in healthy men (38). The exact mechanism underlying this relationship is still unknown. Muscular pull may cause bone strain and growth (39). Muscle may also act as a source of anabolic hormones on bone (16), or a common factor may influence both tissues (13). In contrast to the femoral neck, at the lumbar spine there were no correlations between change in muscle mass and change in BMD. Therefore, the observed 11% increase in mean BMD at the lumbar spine in vertebral fracture patients must be due to some factor other than muscle mass.

Although it was hypothesized that low muscle mass would also impact strength, physical function, and consequently quality of life, the present data suggest this model may be oversimplified. Muscle mass, strength, physical function, and quality of life were indeed lower in vertebral fracture patients, strength measures were correlated with physical function tests, and physical function tests were correlated with quality of life (as shown previously [8]). However, the correlations between muscle mass and strength, physical function, and quality of life did not obtain significance in patients with vertebral fracture. Possibly poor muscle quality, poor neural recruitment, or reduced effort may influence poor physical functioning in these patients (40, 41). Consistent with the latter explanation was the finding that self-reported pain, one of the domains of the SF-36 quality of life questionnaire, was correlated with both muscle strength and physical functioning in patients with vertebral fracture.

Strengths of this study include use of a longitudinal cohort design for body composition outcome variables. A strict definition of the patient cohort reduced the possibility of using a loosely defined population with different etiologies. Use of both a subjective self-reported quality of life questionnaire and objectively assessed physical functioning tests allowed an accurate and relevant assessment of physical functioning. Weaknesses of the study include a lack of longitudinal data on physical functioning and quality of life outcomes, a lack of power to detect small differences in the mental health domains of quality of life, measurement of bone density rather than bone quality (an important determinant of fracture susceptibility [42]), and possible confounding by a number of lifestyle factors, including the level of physical activity. However, the study's objective was to determine body composition changes and not their cause.

Future studies should obtain longitudinal data on physical functioning and self-reported quality of life and confirm why quality of life is reduced in men with idiopathic vertebral fracture. To address the reduced physical functioning of vertebral fracture patients identified herein, potential targets for intervention may include reducing pain and increasing muscle strength by both medical and lifestyle interventions. Finally, the present study supports a link between muscle and bone in men with idiopathic vertebral fracture. Since the predisposition to idiopathic vertebral fracture remains elusive, the influence of muscle mass on bone strength should be recognized and investigated further.

AUTHOR CONTRIBUTIONS

  1. Top of page
  2. Abstract
  3. INTRODUCTION
  4. SUBJECTS AND METHODS
  5. RESULTS
  6. DISCUSSION
  7. AUTHOR CONTRIBUTIONS
  8. Acknowledgements
  9. REFERENCES

All authors were involved in drafting the article or revising it critically for important intellectual content, and all authors approved the final version to be published. Dr. Macdonald had full access to all of the data in the study and takes responsibility for the integrity of the data and the accuracy of the data analysis.

Study conception and design. Macdonald, Evans, Davie, Sharp.

Acquisition of data. Macdonald, Evans, Davies, Sharp.

Analysis and interpretation of data. Macdonald, Evans, Davies, Wilson, Davie, Sharp.

Acknowledgements

  1. Top of page
  2. Abstract
  3. INTRODUCTION
  4. SUBJECTS AND METHODS
  5. RESULTS
  6. DISCUSSION
  7. AUTHOR CONTRIBUTIONS
  8. Acknowledgements
  9. REFERENCES

The authors would like to thank Michael Haddaway (Medical Physicist, Robert Jones & Agnes Hunt Orthopaedic Hospital) for his help throughout the study and the anonymous reviewers for suggesting useful revisions to the submitted manuscript.

REFERENCES

  1. Top of page
  2. Abstract
  3. INTRODUCTION
  4. SUBJECTS AND METHODS
  5. RESULTS
  6. DISCUSSION
  7. AUTHOR CONTRIBUTIONS
  8. Acknowledgements
  9. REFERENCES
  • 1
    Geusens P, Dinant G. Integrating a gender dimension into osteoporosis and fracture risk research. Gend Med 2007; 4 Suppl: S14761.
  • 2
    Jackson SA, Tenenhouse A, Robertson L. Vertebral fracture definition from population-based data: preliminary results from the Canadian Multicenter Osteoporosis Study (CaMos). Osteoporos Int 2000; 11: 6807.
  • 3
    Jiang HX, Majumdar SR, Dick DA, Moreau M, Raso J, Otto DD, et al. Development and initial validation of a risk score for predicting in-hospital and 1-year mortality in patients with hip fractures. J Bone Miner Res 2005; 20: 494500.
  • 4
    Geusens P, Sambrook P, Lems W. Fracture prevention in men. Nat Rev Rheumatol 2009; 5: 497504.
  • 5
    Seeman E, Bianchi G, Khosla S, Kanis JA, Orwoll E. Bone fragility in men: where are we? Osteoporos Int 2006; 17: 157783.
  • 6
    Evans SF, Davie MW. Low body size and elevated sex-hormone binding globulin distinguish men with idiopathic vertebral fracture. Calcif Tissue Int 2002; 70: 915.
  • 7
    Macdonald JH, Evans SF, Davie MW, Sharp CA. Muscle mass deficits are associated with bone mineral density in men with idiopathic vertebral fracture. Osteoporos Int 2007; 18: 13718.
  • 8
    Shin H, Panton LB, Dutton GR, Ilich JZ. Relationship of physical performance with body composition and bone mineral density in individuals over 60 years of age: a systematic review. J Aging Res 2011; 2011: 191896.
  • 9
    Kotler DP. Cachexia. Ann Intern Med 2000; 133: 62234.
  • 10
    Janssen I, Heymsfield SB, Ross R. Low relative skeletal muscle mass (sarcopenia) in older persons is associated with functional impairment and physical disability. J Am Geriatr Soc 2002; 50: 88996.
  • 11
    Roubenoff R. Sarcopenia: effects on body composition and function. J Gerontol A Biol Sci Med Sci 2003; 58: 10127.
  • 12
    Chan BK, Marshall LM, Winters KM, Faulkner KA, Schwartz AV, Orwoll ES. Incident fall risk and physical activity and physical performance among older men: the Osteoporotic Fractures in Men study. Am J Epidemiol 2007; 165: 696703.
  • 13
    Szulc P, Beck TJ, Marchand F, Delmas PD. Low skeletal muscle mass is associated with poor structural parameters of bone and impaired balance in elderly men: the MINOS study. J Bone Miner Res 2005; 20: 7219.
  • 14
    Crepaldi G, Maggi S. Sarcopenia and osteoporosis: a hazardous duet. J Endocrinol Invest 2005; 28: 668.
  • 15
    Frost HM. Why do marathon runners have less bone than weight lifters? A vital-biomechanical view and explanation. Bone 1997; 20: 1839.
  • 16
    Lemmey AB, Glassford J, Flick-Smith HC, Holly JM, Pell JM. Differential regulation of tissue insulin-like growth factor-binding protein (IGFBP)-3, IGF-I and IGF type 1 receptor mRNA levels, and serum IGF-I and IGFBP concentrations by growth hormone and IGF-I. J Endocrinol 1997; 154: 31928.
  • 17
    Sharp CA, Brown SJ, Davie MW, Magnusson P, Mohan S. Increased matrix concentrations of IGFBP-5 in cancellous bone in osteoarthritis. Ann Rheum Dis 2004; 63: 11625.
  • 18
    Pluijm SM, Visser M, Smit JH, Popp-Snijders C, Roos JC, Lips P. Determinants of bone mineral density in older men and women: body composition as mediator. J Bone Miner Res 2001; 16: 214251.
  • 19
    Black DM, Palermo L, Nevitt MC, Genant HK, Epstein R, San Valentin R, et al. Comparison of methods for defining prevalent vertebral deformities: the Study of Osteoporotic Fractures. J Bone Miner Res 1995; 10: 890902.
  • 20
    Haddaway MJ, Davie MW, McCall IW. Bone mineral density in healthy normal women and reproducibility of measurements in spine and hip using dual-energy x-ray absorptiometry. Br J Radiol 1992; 65: 2137.
  • 21
    Kim J, Wang Z, Heymsfield SB, Baumgartner RN, Gallagher D. Total-body skeletal muscle mass: estimation by a new dual-energy x-ray absorptiometry method. Am J Clin Nutr 2002; 76: 37883.
  • 22
    Gallagher D, Ruts E, Visser M, Heshka S, Baumgartner RN, Wang J, et al. Weight stability masks sarcopenia in elderly men and women. Am J Physiol Endocrinol Metab 2000; 279: E36675.
  • 23
    Rikli R, Jones C. Senior fitness test manual. Champaign (IL): Human Kinetics; 2001.
  • 24
    Macdonald JH, Marcora SM, Jibani MM, Kumwenda MJ, Ahmed W, Lemmey AB. Nandrolone decanoate as anabolic therapy in chronic kidney disease: a randomized phase II dose-finding study. Nephron Clin Pract 2007; 106: c12535.
  • 25
    Ware JE Jr, Sherbourne CD. The MOS 36-item Short-Form health survey (SF-36). I. Conceptual framework and item selection. Med Care 1992; 30: 47383.
  • 26
    Ware JE Jr, Snow KK, Kosinski M, Gandek B. SF-36 health survey: manual and interpretation guide. 2nd ed. Lincoln (RI): Quality Metric; 2000.
  • 27
    Ware JE, Kosinski M, Bjorner JB, Turner-Bowker DM, Gandek B, Maruish ME. User's manual for the SF-36v2 health survey. 2nd ed. Lincoln (RI): QualityMetric; 2007.
  • 28
    Cohen J. Statistical power analysis for the behavioral sciences. 2nd ed. Hillsdale (NJ): Lawrence Erlbaum Associates; 1988.
  • 29
    Hopkins WG. A new view of statistics. Sportscience 2006; 10: 6370.
  • 30
    Zafon C. Oscillations in total body fat content through life: an evolutionary perspective. Obes Rev 2007; 8: 52530.
  • 31
    Kyle UG, Genton L, Hans D, Karsegard VL, Michel JP, Slosman DO, et al. Total body mass, fat mass, fat-free mass, and skeletal muscle in older people: cross-sectional differences in 60-year-old persons. J Am Geriatr Soc 2001; 49: 163340.
  • 32
    Forbes G. Human body composition. New York: Springer-Verlag; 1987.
  • 33
    Forbes GB. Longitudinal changes in adult fat-free mass: influence of body weight. Am J Clin Nutr 1999; 70: 102531.
  • 34
    Gallagher D, Visser M, De Meersman RE, Sepulveda D, Baumgartner RN, Pierson RN, et al. Appendicular skeletal muscle mass: effects of age, gender, and ethnicity. J Appl Physiol 1997; 83: 22939.
  • 35
    Fantin F, Di Francesco V, Fontana G, Zivelonghi A, Bissoli L, Zoico E, et al. Longitudinal body composition changes in old men and women: interrelationships with worsening disability. J Gerontol A Biol Sci Med Sci 2007; 62: 137581.
  • 36
    Francis RM, Aspray TJ, Hide G, Sutcliffe AM, Wilkinson P. Back pain in osteoporotic vertebral fractures. Osteoporos Int 2008; 19: 895903.
  • 37
    Lang T, Koyama A, Li C, Li J, Lu Y, Saeed I, et al. Pelvic body composition measurements by quantitative computed tomography: association with recent hip fracture. Bone 2008; 42: 798805.
  • 38
    Bakker I, Twisk JW, Van Mechelen W, Kemper HC. Fat-free body mass is the most important body composition determinant of 10-yr longitudinal development of lumbar bone in adult men and women. J Clin Endocrinol Metab 2003; 88: 260713.
  • 39
    Schwarz P. Physical activity and bone strength [editorial]. Scand J Med Sci Sports 2004; 14: 1.
  • 40
    Hughes VA, Frontera WR, Wood M, Evans WJ, Dallal GE, Roubenoff R, et al. Longitudinal muscle strength changes in older adults: influence of muscle mass, physical activity, and health. J Gerontol A Biol Sci Med Sci 2001; 56: B20917.
  • 41
    Thom JM, Morse CI, Birch KM, Narici MV. Influence of muscle architecture on the torque and power-velocity characteristics of young and elderly men. Eur J Appl Physiol 2007; 100: 6139.
  • 42
    Jarvinen TL, Kannus P, Sievanen H. Bone quality: emperor's new clothes. J Musculoskelet Neuronal Interact 2008; 8: 29.