age, sex, and grip strength determine architectural bone parameters assessed by peripheral...

Journal of Biomechanics 34 (2001) 497–503

Age, sex, and grip strength determine architectural bone parametersassessed by peripheral quantitative computed tomography (pQCT)

at the human radius

Yusuke Hasegawa, Peter Schneider*, Christoph Reiners

Clinic for Nuclear Medicine, University of Wurzburg, Josef-Schneider-Str. 2, 97080 Wurzburg, Germany

Accepted 25 October 2000

Abstract

The purpose of this study was to estimate the relation of some noninvasively derived mechanical characteristics of radial bone

including architectural parameters for bone strength to grip strength and muscle cross-section. Sixty-three males between 21 and78 yr of age and 101 females between 18 and 80 yr of age were measured at the nondominant forearm using peripheral quantitativecomputed tomography (pQCT). We assessed the integral bone mineral density (BMDI) and content (BMCI) by pQCT at the distaland at the mid-shaft radius. Integral bone area (AreaI), cortical thickness (C-th), and a newly proposed index for bone strength; the

stress–strain index (SSI) were also calculated. The dynamometrically measured maximum grip strength was taken as a mechanicalloading parameter and muscle cross-section as a substitute for it. Sex, grip strength, BMCI and BMDI (distal radius) were identifiedin a multiple regression analysis to significantly predict bone strength as expressed by SSI, after adjusting for all other independent

variables, including age and sex ( p50.0001). Grip strength was closest related to age, sex, BMDI and SSIp of the distal radius. Thecross-sectional area of muscle was not significantly determining the grip strength within the analysis model. In conclusion, ourresults suggested that architectural parameters at the distal radius were better related to grip strength than to cross-sectional muscle

area in both males and females. Maximum muscle strength as estimated by grip strength might be a stronger determinant ofmechanical characteristics of bones as compared with cross-sectional muscle area. # 2001 Elsevier Science Ltd. All rightsreserved.

Keywords: Bone architecture; Bone mineral density; Bone strength; Grip strength; Peripheral quantitative computed tomography

1. Introduction

Research in osteoporosis has lead to the growingawareness of the influence of physical activities on bonemass, strength, and architecture (Hasegawa et al., 2000;Kritz-Silverstein and Barrett-Connor, 1994). The pri-mary mechanical function of bones is to provide rigidlevers for muscles to pull against, and to remain as lowin weight as possible to allow efficient locomotion. A100 yr ago, Wolff suggested that this was achieved byadaptation of shape and architecture as a result ofstresses on bone to make efficient use of the material(Wolff, 1892, 1986). Several authors expanded this viewin that the adaptation of bones in later life isdynamically controlled by a feedback mechanism that

adapts bone’s structural strength, further referred to as‘‘architecture’’, to its physical loading. The resultingproposals comprised a dynamical approach based on theassumption of minimum effective strains (Turner, 1998;Frost, 1987; Frost, 1990).Decline in muscle strength due to aging usually

accompanies a decline in muscle mass. This observationgives reason to investigate the effects of muscle strengthon bone strength and ‘‘mass’’. Moreover, it wassuggested that measurements of BMC alone did notadequately reflect the mechanical integrity of the radiusas compared with torsional rigidity (Burr and Martin,1983, 1997).Peripheral QCT can provide useful accurate non-

invasive measures of cross-sectional bone features thatshould affect bone (Hasegawa et al., 2000; Faulkner etal., 1993; Ferretti et al., 1992; Harrington et al., 1993;Myburgh et al., 1992; Augat et al., 1996). It includes

*Corresponding author. Tel.: +49-931-2015868; fax: +49-931-

2012247.

0021-9290/01/$ - see front matter # 2001 Elsevier Science Ltd. All rights reserved.

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separate determinations of volumetric cortical, trabecu-lar and total bone tissue material content and density;cross-sectional cortical bone area, and the cross-sectional cartesian and polar moments of inertia. In aspecial mode, muscle cross-section can be determined.The objective of this study was to investigate the

association of grip strength and muscle cross-sectionwith these bone-related parameters (Table 1) at tworadial sites using pQCT.

2. Materials and methods

We studied 63 males between 21 and 78 yr of age(median: 53) and 101 females between 18 and 80 yr ofage (median: 54). The patients were subjected to bonedensitometry to estimate the fracture risk. Exclusioncriteria were the presence of any history of generalizeddisease of nerve and muscle. Informed consent wasgiven.

2.1. Bone measurements

All subjects were measured at the nondominantforearm by pQCT (XCT2000, Stratec GmbH Pforz-heim, Germany). After recording a scout scan, cross-sectional images were taken at the standard measure-ment sites 4 and 66% of the ulnar length proximal to thedistal radius end using an automated computer routine.The volumetric bone mineral density (BMD) of the mid-shaft and the distal radius was calculated from thesingle-slice cross-sections (Schneider and Borner, 1991;Louis et al., 1995). Calibration was based on the newEuropean standard COMAC forearm phantom that hasfour different bone density compartments (Pearsonet al., 1994).Parameters related to bone mass, density and

architectural status were determined (Table 1). Thecortical bone area was defined using the outer contourof the bone at a threshold of 0.48 cm�1 (linearattenuation coefficient at the X-ray energy of thesystem). The threshold level was kept constant for allpatients. Cortical thickness (C-th) was estimated usingthe endosteal and periosteal circumferences. The inte-gral bone area (areaI) was calculated as the total area

encompassed by the periosteal circumference, includingthe marrow. The area moments of inertia (CSMI) werecalculated along the radioulnar and dorsopalmar axes.Following Hsu et al. (1993), it was assumed that theyrepresented approximately the principal moments ofinertia. These moments of inertia and the polar momentof inertia (CSMIp) were based on the cortical bone seenin the CT image at the specified threshold. A newlyintroduced index was proposed to reflect bone strengthmore generally than the CSMI’s, dubbed stress–strainindex (SSI) by the manufacturer of the pQCT device.Their software calculated the section modulus followingan approach to describe bending stresses in beams(Rumpel and Sonderhausen, 1995). Then a correctionfor the apparent bone density of each voxel (partialvolume effect) was applied, assuming that a voxelcontaining only cortical bone would have a normalbone mineral density of 1200mg/cm3

SSI ¼X

i¼l;n

r2i aCD

NDrmax

;

where rmax is the distance of voxel from center, CD theapparent cortical density, ND the normal corticaldensity, ri the pixel position from center, a the area ofa pixel (STRATEC manual). Radioulnar, dorsopalmarand polar SSIs were calculated.The CSMI has been reported to be closely correlated

with failure load (Augat et al., 1996). At very low BMDvalues the CSMI and SSI tended to result in extremelylow values due to inaccuracy (3 female cases). At thethreshold set, trabecular bone at the distal radius wasexcluded from the calculation of CSMI and SSI. Thepolar moment of inertia (an estimator for torsionrigidity) appeared to be numerically between the areamoments of inertia (estimators for bending rigidity).They were studied separately and revealed no significantdifferences. The same was true for the three kinds of SSI.To avoid similarity and ill-conditioning of the matricesin the regression analysis, only the polar SSIp was finallyconsidered to sufficiently represent bone strength. AllCSMIs were left out.The architectural parameters at the mid-shaft were

determined using a threshold of 0.70 cm�1. The in vivoprecision errors were 1.0–1.9% for vBMD, 3.4% for C-th, and 6.8% for CSMIp and SSIp (Hasegawa et al.,1997).

2.2. Muscle measurement

Muscle cross-sectional area was estimated at the 66%measurement site, using a threshold below waterequivalent linear attenuation set at 0.22 cm�1. Thisthreshold eliminated skin and fat mass with lower linearattenuation (50.22 cm�1) in the cross-sectional slice.From the remaining area bone area was subtracted,

Table 1

Estimators used in the study to describe bone mass, density, and

architectural properties at the distal radius and at the midshaft

Description Abbreviation

Integral bone mineral density (mg/cm3) BMDI

Integral bone mineral mass/content (mg) BMCI

Integral bone area (mm2) AreaICortical thickness (mm) C-th

Polar cross-sectional moment of inertia (mm4) CSMIpPolar stress–strain index (mm3) SSIp

Y. Hasegawa et al. / Journal of Biomechanics 34 (2001) 497–503498

revealing the muscle at its maximum cross-sectionalarea. Precision error of this procedure was 3%.

2.3. Grip strength measurements

In all 164 patients grip strength was determined as amechanical loading factor at the nondominant forearmby a hand-held dynamometer (Grip-D, Takei ScientificInstruments CO., LTD, Tokyo, Japan). The subjectswere tested without prior training. Their maximum gripstrength was thus assumed to best reflect the currentstatus and the history of their musculoskeletal adapta-tion of the forearm. The test was done after theadjustment of the device handle to the patient’s gripwith him or her sitting and the forearm flexed. Themeasurements were repeated five times within 3min andan average value was calculated. The intraindividualreproducibility was 5.5% (coefficient of variation). Theaccuracy of the device was 2 digits or 1 newton (N).

3. Statistical analysis

Stepwise multiple regression analysis was employed toshow the dependence of the data on age, sex (entered as0=female, 1=male), and bone-related parameters.Partial correlations were calculated to analyze thecontributions of the independent variables. The differ-ence between two Pearson correlations was computedusing the quick probability calculator and the two-sidedtest. The StatisticaTM software package was used.Significance level was set at p50.05.

4. Results

In the first step SSIp at the distal radius, a clinicallyrelevant site, was chosen as the dependent variable topredict the contribution of age, sex, muscle cross-section, and the remaining bone mineral and architectu-rally related parameters. Four parameters remained inthis model, covering a predictive capability of 81.7%(p50.0001, Table 2). Besides two bone-related para-meters of the distal radius and sex, grip contributedsignificantly to predict SSIp (p50.0003). Fig. 1 showsthe correlation of grip with SSIp for males and females.Surprisingly, muscle cross section did not remain in theregression equation of this model. Some outliers in theresidual analysis (Fig. 2) were identified as inaccuratecalculation of SSIp values due to low BMD. However,they had no significant influence on the reasonable fit ofthe model and were therefore not removed.In order to reversely look at determinants of grip, in

the next step the analysis was designed using grip asdependent variable to identify the parameters mostclosely related. This approach resulted in an overall

explanatory power of the regression analysis of 64.7%,with age and sex contributing best to this model asindicated by the partial correlations. SSIp and BMD atthe distal radius ranked second, whereas muscle cross-section was least significant (Table 3).Fig. 3 shows the association of the distal SSIp to

muscle cross-section. A partial influence of sex on theregression of muscle cross-section and grip strength may

Table 2

Multiple regression results of a forward stepwise regression (6 steps)

with SSIp of the distal radius as dependent variable. The set of

parameters shown in Table 1 plus age and sex were entered, variables

remaining in the analysis are listed in the order of their significance, sex

was entered as 0=female, 1=male. Multiple R=0.910, p50.0001,

adjusted R-square=0.817

Beta St. error

of beta

Partial

correlation

p-level

BMCI (distal radius) 0.693 0.068 0.488 50.0001

BMDI (distal radius) 0.281 0.052 0.378 50.0001

Grip strength 0.199 0.055 0.262 0.0003

Sex 0.134 0.058 0.177 0.02

Fig. 1. Association of grip strength to polar stress–strain index (SSIp)

of the distal radius in males (n=63) and females (n=101). Regression

lines are not significantly different.

Fig. 2. Normal probability plot of the residuals in the multiple

regression model using SSIp as the dependent variable (adjusted

r2=0.82).

Y. Hasegawa et al. / Journal of Biomechanics 34 (2001) 497–503 499

be concluded from Fig. 4. However, the regression linesfor males and females were not significantly different(p=0.59).Lastly, muscle cross-section was taken as dependent

variable to characterize its association with the othervariables used in this study. The result revealed SSIp andBMD of the midshaft, BMD at the distal radius, and sexwith significant association (Table 4). BMD at themidshaft showed a negative partial correlation, which

may be explained as statistical artifact because differ-ences in BMD in predominantly cortical bone are verysmall, thus resulting in a large standard error of Beta.The overall explanatory power was comparatively low(58.9%).In summary, the bone architectural parameter SSIp of

the distal radius was the best predictor for maximumgrip strength, but not for muscle cross-section. SinceSSIp and CSMIp were highly associated parameter, onlySSIp was considered in the analyses presented. Furtheranalysis of the determinants of grip strength revealed apredominant association with age and sex.

5. Discussion

Grip strength, as a standardized measure, is a widelyaccepted estimator of the load on the radius (Desrosierset al., 1999; Hanten et al., 1999; Dvir, 1999; Suzuki etal., 1999; Greeves et al., 1999). Results of the previousstudies (Nordstrom et al., 1998; Frost et al., 1998) andthis investigation suggested that mechanical loading bythe appropriate muscle group could have partiallydetermined the bone architecture.All measures and surrogate parameters used in this

study (except age and sex) were functionally directlyrelated to each other. Indirectly related parameters suchas height or body mass index were not considered.To further elucidate the involvement of the para-

meters in our study which were identified to besignificant, some background should be given. Changesin bone mass may be described by two complementaryassumptions. Modeling and remodeling should adapt abone’s strength to its largest strains, originating frommuscle forces (Jee, 1989). The underlying mechanismmay be viewed as the master control of bone strengthand mass (Frost, 1996). Moreover, it has been reportedthat the bone area values were strongly related to musclestrength (Nordstrom et al., 1998) or to muscle cross-section (Tysarczik-Niemeyer et al., 1999).Muscle strength and cross-sectional muscle area were

associated with bone parameters both at the midshaft

Table 3


with grip strength as dependent variable. The set of parameters shown

in Table 1 plus age and sex (0=female, 1=male) were entered,

variables remaining in the analysis are listed in the order of their

significance. Multiple R=0.811, p50.0001, adjusted R-square=0.647

Beta St. error

of beta

Partial

correlation

p-level

Sex �0.472 0.064 �0.506 50.0001

Age �0.358 0.052 �0.479 50.0001

SSIp (distal radius) 0.309 0.084 0.278 0.0002

BMD (distal radius) �0.204 0.074 �0.215 0.006

Muscle cross-section 0.112 0.065 0.137 0.08

Fig. 3. Association of muscle cross-section to polar stress–strain index

(SSIp) of the distal radius in males (n=63) and females (n=101).

Regression lines are not significantly different.

Fig. 4. Association of grip strength to muscle cross-section of the

distal radius in males (n=63) and females (n=101). Regression lines

are not significantly different.

Table 4


with muscle cross-section as dependent variable. The set of parameters

shown in Table 1 plus age and sex (0=female, 1=male) were entered,

variables remaining in the analysis are listed in the order of their

significance. Multiple R=0.777, p50.0001, adjusted R-square=0.589

Beta St. error

of beta

Partial

correlation

p-level

SSIp (midshaft) 0.367 0.070 0.383 50.0001

BMD (midshaft) �0.276 0.545 �0.374 50.0001

Sex �0.259 0.092 �0.243 0.002

BMD (distal radius) 0.188 0.060 0.242 0.002


and the distal radius in our study. Grip strength mayhave partially reflected bending stress, and the cross-sectional muscle area should be proportionally involved.The results of our linear regression model suggested thatmuscle cross-section was not a strong predictor of gripstrength or bone architectural parameters. Perhaps, theefficiency and the composition of muscle fibers aresubject to changes with age. Such factors could not beassessed in this study. Although we found no signifi-cantly different regression between muscle cross-sectionand grip strength in males and females, this findingshould be further investigated regarding a proposedinfluence of hormone status on muscles (Greeves et al.,1999; Osei-Hyiaman et al., 1998).In vivo strain gauge measurements showed that the

maximum strains occurring during different types ofactivities resulted from engineering shear (Burr et al.,1996). They appeared to be over 50% higher thancompression and tensile strains. Grip force in our testsetting should have provided a moment equilibrium inthe joint, favorably involving compression strains. Ifsuch strains would cause adaptation of bone rigidityover long periods, these considerations could help toexplain that SSIp was significantly associated with gripstrength. Our results would support the observation ofAugat et al. (1996), who found geometrical and strengthparameters of the cortical shell, combined with BMD orBMC values to be the best predictors of (ultimate) load.Studies were beginning to identify genes that may be

responsible for acquisition of adult bone or lean massand muscle strength (Seeman et al., 1996; Pocock et al.,1987). However, in such studies the particular statisticalapproach may be misleading. The study of Seeman et al.showed that even in monocygotic twins the within-pairtrait differences ranged from 45 to 75% concerning bonedensity, lean mass or muscle strength. Moreover, suchstudies neglected analysis of the influence of individuallong-term adaptive processes that sufficiently might haveexplained these differences by environmental factorssuch as training (Frost, 1987, 1990, 1996, 1998).Although remarkable associations were shown, thestudy of Seeman et al. particularly lacked threeinteresting answers: (a) explanation of the striking traitdifferences between individual twin pairs, (b) substantia-tion of the functional association of total body leanmass with BMD of specific skeletal sites (lumbar spine,hip), and, (c) could the results of their study be adoptedin a heterogenetic population?Our study showed an overall explanatory capacity of

82% within the specified model not involving geneticfactors. Thus, only the remaining 18% could accom-odate some involvement of such factors. This clearlycontrasted with conclusions drawn from twin studies,claiming that genetic factors may explain up to 80%of the variance in bone density or lean mass (Seemanet al., 1996).

Morrison et al. have reported that vitamin D receptorallels can be associated with genetic variations in bonedensity. The influence explained roughly one standarddeviation difference in bone density in mono- anddizygotic twins. These finding have been reproduced insome patient populations (Morrison et al., 1994; Gunzeret al., 1995) but not in others (Gallagher et al., 1994;Looney et al., 1995; Arden and Spector, 1997). Whetheror not this was associated with differences in fractureincidence was not investigated. These conflicting resultsare the likely consequences of genetic heterogeneity ofthe human population coupled with important environ-mental differences, especially in the aged. Otherwisegenetic factors could normalize bone and joint archi-tecture in congenitally or neonatally paralyzed limbs(Frost, 1990). Newer studies, looking at the geneticassociation of other factors like BMP-4 polymorphism,and COLIA1 Sp1 polymorphism revealed the samecontroversial situation (Semprini et al., 2000; McLellanet al., 1997; Uitterlinden et al., 1997). This controversysuggests that future studies related to bone and geneticsshould also consider more appropriate models for theassessment of bone architecture/muscle and bonedensity/fracture incidence interrelations.In conclusion, our results suggested that age and sex

were strongly associated with grip strength and bone-related parameters. Maximum muscle strength asestimated by grip strength should be considered asstronger determinant of mechanical characteristics ofbones as compared with cross-sectional muscle area.

Acknowledgements

The Lilly fellowship program for bone and mineralresearch supported this work.

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