Archives of Oral Biology 46 (2000) 641648

Determinants of masticatory performance in dentate adults

J.P. Hatch a,b,*, R.S.A. Shinkai a,e, S. Sakai a, J.D. Rugh a, E.D. Paunovich c,d

a Department of Orthodontics, The Uniersity of Texas Health Science Center at San Antonio, 7703 Floyd Curl Drie,San Antonio, TX 78229-3900, USA

b Department of Psychiatry, The Uniersity of Texas Health Science Center at San Antonio, 7703 Floyd Curl Drie,San Antonio, TX 78229-3900, USA

c Department of Dental Diagnostic Science, The Uniersity of Texas Health Science Center at San Antonio, 7703 Floyd Curl Drie,San Antonio, TX 78229-3900, USA

d South Texas Veterans Health Care System, Audie L. Murphy Diision, 7400 Merton Minter Bld.,San Antonio, TX 78229-3900, USA

e Department of Prosthodontics and Periodontics, Uniersity of Campinas, A. Limeira, 901, Piracicaba, SP 13414-900, Brazil

Accepted 24 January 2001

Abstract

Masticatory performance results from a complex interplay of direct and indirect effects, yet most studies employunivariate models. This study tested a multivariate model of masticatory performance for dentate subjects. Explana-tory variables included number of functional tooth units, bite force, sex, age, masseter cross-sectional area, presenceof temporomandibular disorders, and presence of diabetes mellitus. The population-based sample consisted of 631dentate subjects aged 3780 years. Covariance structure analysis showed that 68% of the variability in masticatoryperformance could be explained by the combined effects of the explanatory variables. Age and sex did not show astrong effect on masticatory performance, either directly or indirectly through masseter cross-sectional area,temporomandibular disorders, and bite force. Number of functional tooth units and bite force were confirmed as thekey determinants of masticatory performance, which suggests that their maintenance may be of major importance forpromoting healthful functional status. 2001 Elsevier Science Ltd. All rights reserved.

Keywords: Mastication; Masticatory performance; Dentate; Structural equation modeling

www.elsevier.com/locate/archoralbio

1. Introduction

Factors believed to affect masticatory performanceinclude loss and restoration of postcanine teeth(Helkimo et al., 1978; Akeel et al., 1992; Van der Bilt etal., 1993, 1994; Yamashita et al., 2000), bite force(Wilding, 1993; Boretti et al., 1995; Fontijn-Tekamp etal., 2000), severity of malocclusion (Omar et al., 1987),tactile sensitivity (Kapur et al., 1990), occlusal contact

area and body size (Julien et al., 1996), and oral motorfunction (Koshino et al., 1997). With a few exceptions,the factors affecting mastication have been studied oneat a time in a piecemeal fashion. This approach mayprovide only limited insight regarding the complex in-terplay of factors that jointly determine masticatoryperformance. While not every potentially relevant vari-able can be studied in any single investigation, key setsof variables can be identified and studied within amultivariate research design.

Our purpose now was to focus on two key variablesthought to be implicated in the aging-related loss ofmasticatory performance in adults loss of postca-nine functional tooth units and loss of bite force. Both

* Corresponding author. Tel.: +1-210-5674594; fax: +1-210-5676941.

E-mail address: hatch@uthscsa.edu (J.P. Hatch).

0003-9969/01/$ - see front matter 2001 Elsevier Science Ltd. All rights reserved.

PII: S0003-9969(01)00023-1

J.P. Hatch et al. / Archies of Oral Biology 46 (2001) 641648642

variables were selected as main factors because theyrepresent local measures of occlusion and oral strength,which have been consistently shown to influence chew-ing. Previous studies demonstrate that age per se is notnecessarily associated with a loss of masticatory perfor-mance (Wayler and Chauncey, 1983; Carlsson, 1984;Fontijn-Tekamp et al., 2000). Therefore, it is necessaryto look to other factors that may be linked to the agingprocess. We hypothesized that age-related local or sys-temic diseases, which lead to loss of tooth structure,masticatory muscle pathology, or pain, are largely re-sponsible for age-related decline of masticatory func-tion. In this study, signs and symptoms oftemporomandibular disorders represented a local dis-ease process, and a diagnosis of diabetes mellitus repre-sented a systemic disease process.

To test this hypothesis a cross-sectional, population-based study was conducted. A theoretical multivariatemodel of masticatory performance was constructed andtested using a statistical modeling procedure known ascovariance structure modeling, linear structural equa-tion modeling, or causal modeling (Blaylock, 1971).The name causal modeling does not imply that causalpathways are being proven. Rather the researcher de-velops a priori an explicit model based on hypothesizedcausal pathways. Data are then collected and analyzedto determine how consistent they are with the model.

2. Materials and methods

2.1. Participants

We studied 283 men and 348 women, MexicanAmerican and EuropeanAmerican, between the agesof 37 and 80 years (mean 58.5, S.D. 11.1), who hadbeen participants in the Oral Health, San AntonioLongitudinal Study on Aging conducted in San Anto-nio, TX, from 1994 to 1998. Those participants hadbeen selected by a stratified random selection procedurethat sampled three socioeconomically distinct neighbor-hoods in San Antonio, a low income barrio neighbor-hood, a middle income transitional neighborhood, andan upper income suburban neighborhood. Sociodemo-graphic and medical/dental characteristics are displayedin Tables 1 and 2, respectively. Exclusion criteria com-prised pregnancy, impossibility of classification as Mex-icanAmerican or EuropeanAmerican, and presenceof any removable full or partial denture. Subjects wereselected without regard to their dental treatment status.

2.2. Procedures

Data were collected during a medical and dentalexamination, which included a comprehensive dentaland periodontal assessment, evaluation of masticatory

performance, examination of the temporomandibularjoints and registration of bite force, number of func-tional tooth units, and masseter cross-sectional area. Inaddition, a complete review of medical history, medica-tions, and physical and functional assessments wereaccomplished. All subjects gave written informed con-sent for their participation, and the protocol was ap-proved by the Universitys Institutional Review Board.

2.2.1. Masticatory performanceThe modified Mastication Performance Index was

adopted (Manly and Braley, 1950; Yurkstas andManly, 1950). This index quantifies the percentage byweight of a masticated test food bolus that will passthrough a standard screen sieve after a set number ofmasticatory strokes. Peanuts served as the test food forunilateral chewing, with three 20-stroke trials per side.The mean of the six trials administered by a calibratedexaminer composed the bilateral Mastication Perfor-mance Index score. The interexaminer reliability of themasticatory performance test assessed using the intra-class correlation coefficient was equal to 0.78. Thissieving method has been used for many years by differ-ent research groups and is particularly suitable for largesamples studies (Demers et al., 1996; Kapur et al., 1997;Garrett et al., 1998; Krall et al., 1998).

2.2.2. Temporomandibular joint disordersThe number and severity of signs and symptoms of

temporomandibular joint disorders were assessed usingthe Craniomandibular Index administered by a cali-brated examiner with the subject seated in a dentalchair (Fricton and Schiffman, 1986, 1987). The overallaggregate score for the Craniomandibular Index wasused.

2.2.3. Bite forceBilateral maximum bite force was measured using a

cross-arch force transducer (Sensotec 13/2445-02,

Table 1Sociodemographic characteristics of subjects (n=631)

%Characteristic Count

Sex348 55.2Female283 44.8Male

Ethnic group58.3368MexicanAmerican

EuropeanAmerican 263 41.7

NeighborhoodBarrio 157 24.9Transitional 222 35.2Suburban 252 39.9

J.P. Hatch et al. / Archies of Oral Biology 46 (2001) 641648 643

Table 2Medicaldental characteristics of subjects (n=631)

S.D. CountCharacteristic %Mean

Functional tooth units (count) 8.37 3.76281.11583.49Bilateral bite force (N)

59.46Masticatory performance (%) 24.980.064Craniomandibular Index score 0.082

1.54.6Masseter cross-sectional area (cm2, n=216)Age (years) 11.158.5

Diabetes mellitusDiabetic 128 20.4

501 79.6Non-diabetic

Columbus, OH) placed in the region of the first molar.Vertical jaw opening at the point of bite pad insertionwas 14 mm. Force was digitized using an analog-to-dig-ital converter, registered in pounds, and converted toNewtons. The procedures were explained to subjects,and they then were allowed several test bites on the biteelement in order to build confidence in its stability. Themean of the three highest trials of ten recordings wasrecorded as the maximum bite force. Except for the useof a bilateral bite element the procedures were similarto those used in previous studies (Van Spronsen et al.,1989; Bakke et al., 1990).

2.2.4. Functional tooth unitsFunctional tooth units were defined as pairs of oc-

cluding natural, restored or fixed prosthetic postcanineteeth (molars=2 units; bicuspids=1 unit).

2.2.5. Diabetes mellitusClassification into the diabetic or non-diabetic group

was according to the American Diabetes Association(1999) criteria or occasionally according to self-re-ported diabetic status.

2.2.6. Masseter muscle cross-sectional areaThis was measured indirectly using high frequency

ultrasound (Bakke et al., 1992; Alanen et al., 1994).Real-time imaging of the masseter muscles was per-formed bilaterally using a fingertip probe connected toan ultrasound scanner (HDI 3000; Advanced Technol-ogy Laboratories). Three recordings on each side wereperformed, with the subjects in an upright position andgently biting on a custom-made occlusal plane. Mea-surements of masseter cross-sectional area were madeusing the scanners electronic cursors by tracing themuscle outline on the screen. Areas of both sides werecomputed for each subject and averaged.

2.2.7. Data analysisWe used the Reticular Action Model (McArdle and

McDonald, 1984) as implemented in Systat 8.0 (SPSS,

Inc., Chicago, IL). The outcome variable was mastica-tory performance. Explanatory variables included bilat-eral bite force, number of functional tooth units, sex(dummy coded 1=male; 2= female), age, Cranio-mandibular Index score, and diabetes mellitus (dummycoded 0=not diabetic; 1=diabetic). The Cran-iomandibular Index score was square root transformedto more closely approximate normality.

The hypothesized model is depicted in Fig. 1. Vari-ables represented by rectangles were considered mani-fest, i.e. they were assumed to be directly observableand measurable. The latent or unobservable variablesrepresent residual unexplained variance and measure-ment error (represented by circles in Figs. 1 and 2).Input data were in the form of a Pearson correlationmatrix estimated using a maximum likelihood expecta-tion maximization procedure. The variances of all la-tent variables were fixed at a value of 1.0. Goodness offit between the model and the data was assessed usingthe SteiglerLind root mean square error of approxi-mation statistic, a measure of significance that is ad-justed for model complexity.

3. Results

The matrix of bivariate correlations among the inputvariables is displayed in Table 3. Bartletts statistic(2=1102.4, P0.001) showed that the variables wereglobally associated. Results of the primary analysis aredisplayed in Fig. 1. Only direct path coefficients areshown next to arrows. Indirect effects can be calculatedby multiplying component path coefficients, and totaleffects by summing direct and indirect effects. Wehypothesized direct causal pathways from functionaltooth units, age, and bite force to masticatory perfor-mance. We predicted that the effect of age would besmall relative to the effects of functional tooth unitsand bite force. We further hypothesized that the im-pact, if any, of diabetes on masticatory performancewould be exerted through its effect on functional tooth

J.P. Hatch et al. / Archies of Oral Biology 46 (2001) 641648644

units, and that the effects of temporomandibular disor-ders on masticatory performance would be exertedthrough its effect on bite force. Standardized estimatesof path coefficients are displayed adjacent to arrowsrepresenting pathways. The multiple R2 for each struc-tural equation is displayed above the upper right-handcorner of rectangles representing endogenous variables.The double-headed curved arrows connecting diabeteswith age and diabetes with sex represent unanalyzedrelationships. The SteigerLind statistic was equal to0.030 (90% confidence interval 0.000, 0.060), indicatingan excellent fit between the model and the data. The R2

value of 0.71 (Fig. 1) demonstrates that the modelaccounts for a 71% of the variance observed in mastica-tory performance. The coefficient representing unex-plained residual variance in masticatory performance(represented by the circle labeled U in Figs. 1 and 2)demonstrates that variables not represented in themodel remain to be identified. The residual variancesassociated with bite force, temporomandibular disor-ders, and functional tooth units (represented by circleslabeled W, X, and Y, respectively) are relativelylarge because only a small number of their determinantswere included in the model. Explanation of more of thevariance in these variables would not necessarily yield amore complete explanation of masticatoryperformance.

As predicted, the direct effect of age on masticatoryperformance was slight. The direct effects of age onfunctional tooth units and bite force also were relativelysmall. In contrast, the direct effects of the identified keyvariables, i.e. postcanine functional tooth units and biteforce, were much larger. Bite force, in turn, was shownto be influenced primarily by sex and number of func-tional tooth units. The representative local disease pro-cess, temporomandibular disorders, appeared to exertonly a small influence on bite force. The representativesystemic disease, diabetes mellitus, did show the pre-dicted influence on the number of remaining functionaltooth units. In summary, the primary analysis demon-strated that the data were highly consistent with thehypothesized causal model.

The effects of masseter cross-sectional area were as-sessed by adding this variable to the model and testingon a sub-sample of 216 subjects for whom musclescanning data were available. The path diagram corre-sponding to this modified sub-model is shown in Fig. 2.This model yielded a SteigerLind statistic equal to0.041 (90% confidence interval 0.000, 0.093), once againindicating a very good fit of the data to the model. TheR2 value of 0.68 (Fig. 2) demonstrates that the modifiedmodel accounts for a 68% of the variance observed inmasticatory performance.

Fig. 1. Path diagram depicting the covariance structure model of masticatory performance (sample size n=631). Rectanglesrepresent manifest (measured) variables. Circles (labeled W, U, X, Y, and Z) represent latent (unobservable) variables, i.e.measurement error. Single-headed arrows represent proposed causal pathways. Double-headed curved arrows represent unanalyzedrelationships. Numbers adjacent to arrows are standardized path coefficients. Numbers immediately above the upper right-handcorner of rectangles represent the R2 associated with each structural equation. Variables on the left are assumed to be causally priorto those on the right. Indirect effects are computed by multiplying component path coefficients. Total effects are calculated bysumming direct and indirect effects. *, P0.05; **, P0.01; ***, P0.001.

J.P. Hatch et al. / Archies of Oral Biology 46 (2001) 641648 645

Fig. 2. Path diagram depicting the covariance structure model of masticatory performance involving masseter cross-sectional area(sample size n=216). * P0.05; **, P0.01; ***, P0.001.

As can be seen from Fig. 2, the path coefficientcorresponding to the pathway from diabetes to musclecross-sectional area was very small and statistically notsignificant. In this sample, age and sex were strongerdeterminants of muscle cross-sectional area than wasdiabetes. The coefficient linking muscle cross-sectionalarea to bite force was statistically significant.

4. Discussion

A conceptual model of mastication for dentate sub-jects was constructed with causal assumptions based onexisting literature, and tested in a large, stratified ran-dom sample derived from the San Antonio, TX popula-tion. The findings support the hypothesis thatmasticatory performance is the outcome of complexsimultaneous interrelationships among physiologicaland contextual variables. The proposed model showedthat the combined effects of the explanatory variablesexplain 68% of the variability in masticatory perfor-mance (see Fig. 2). Number of functional tooth unitsand bite force were confirmed as key predictors, whichsuggests that maintenance of these factors may be ofprimary importance for promoting healthy function.

The single best predictor of masticatory performancewas the number of postcanine functional tooth units.This finding corroborates that the capacity for com-minution depends on the number of occluding pairs ofteeth (Helkimo et al., 1978; Omar et al., 1987; Akeel et

al., 1992; Van der Bilt et al., 1993). Our community-based results add evidence that primary interventions tomaintain or improve masticatory performance in den-tate subjects should be aimed at the preservation and/orrestoration of posterior functional teeth. However, theincreased number of posterior occlusal units seems toimprove chewing performance only when the predomi-nant chewing side arch is restored (Van der Bilt et al.,1994). Thus the distribution of functional tooth units,and not only their number, might be a relevant factoraffecting masticatory performance. The influence ofocclusal contact area on chewing efficiency has alsobeen evaluated, but with contradictory results (Wilding,1993; Julien et al., 1996).

Diabetes and age were considered modifiers of thenumber of functional tooth units. Loss of teeth is theendpoint of many local oral diseases, such as caries andperiodontal disease, which can be influenced by sys-temic diseases and the aging process. However, in thisrandom sample, diabetes and age together accountedfor only 7% of the variability in the number of func-tional tooth units (see Fig. 2). Diabetic individuals hadfewer functional units than non-diabetic subjects, butthe clarification of diabetes as a cause of tooth lossshould be attempted in longitudinal studies.

Number of functional tooth units also showed animportant influence on bite force, which, in turn, affectsmasticatory performance. Considering the model de-picted in Fig. 2, the indirect impact of functional toothunits on mastication was approximately sevenfold

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lower than the direct effect1 and is explained by themoderate effects of functional tooth units on bite forceand of bite force on masticatory performance.

Bite force was the other key predictor in our model,but its impact on masticatory performance was not asstrong as that of number of functional units. Indeed,the effect of bite force was lower than expected fromthe literature. This probably occurred because otherstudies investigated this relationship in samples of sub-jects with more heterogeneous dental status, i.e. den-tate, edentulous, and prosthesis wearers (Heath, 1982;Fontijn-Tekamp et al., 2000).

In addition, we tested the hypothesis that bite forcemediates the effects of several other physiologic anddemographic variables. The combined effects of sex,number of functional postcanine tooth units, massetercross-sectional area, age, and presence of temporo-mandibular disorders explained 52% of the variance inbite force. However, 48% of the variation in bite forcemay be explained by variables not included in thismodel. For example, other factors believed to affectbite force are psychological factors (Orchardson andCadden, 1998), craniofacial morphology (Raadsheer etal., 1999), and body size (Julien et al., 1996). Currentdental treatment status also could have an effect on biteforce, but this variable was not explored here.

Sex was the most important factor influencing biteforce, basically through the direct path. Females tendedto have lower maximum bite force values comparedwith males, which could be explained by a difference ofmass in the masticatory muscles (Newton et al., 1993).Masseter muscle cross-sectional area and thickness isrelated to craniofacial morphology (Weijs and Hillen,1986; Bakke et al., 1992; Raadsheer et al., 1996, 1999),body size (Raadsheer et al., 1996; Shiau et al., 1999),

and bite force (Van Spronsen et al., 1989; Bakke et al.,1992; Raadsheer et al., 1999). Our data show a signifi-cant association between masseter cross-sectional areaand bite force (bivariate r=0.41). The strength of thisassociation, however, was attenuated in the multivari-ate analysis after controlling for other variables affect-ing bite force (compare Table 3 and Fig. 2). Althoughmasseter muscle thickness was shown to be the majorcontributing factor of bite force in adults (Raadsheer etal., 1999), the association between sex and massetercross-sectional area was not strong enough to explainthe sex differences in bite force in this study.

Another indirect effect of sex on bite force wasassessed through the temporomandibular disorderspath. The expected association of sex with temporo-mandibular disorders was confirmed, but a strong influ-ence of temporomandibular disorders as a local factorcausing restriction of jaw mobility and pain, and thuslimiting bite force (Svensson et al., 1998), could not bedemonstrated. One explanation for this result may bethe low prevalence of temporomandibular disorders(Carniomandibular Index mean=0.064, on a scale of01) in our non-clinical sample in contrast to studiesthat included patients with more severe temporo-mandibular disorders (Sato et al., 1999; Tortopidis etal., 1999).

Finally, as predicted, age did not exert a strong effecton masticatory performance, either directly or indi-rectly through maintenance of tooth structure or biteforce. In fact, the direct path from age to masticatoryperformance could not be sustained. This suggests thatmasticatory performance need not decline with age ifteeth are retained and masticatory muscle strength ismaintained. Age may affect oral function through thecumulative effect of a multitude of minor influences.The influence of age is currently viewed as the result ofan accumulation of insults to orofacial structures (Shipet al., 1996). This indirect effect of age on masticatoryperformance was assessed in the model via pathwaysinvolving dental and muscular tissues. However, thesepathways were shown to be relatively weak.

1 The direct effect of posterior functional tooth units onmasticatory performance is 0.68. The indirect effect is calcu-lated by multiplying the components beta path coefficients0.410.27=0.10.

Table 3Correlation coefficients among variables used in the model (n=631)a

1 2 3 4 5 6 7

Temporomandibular disorders10.29***Sex2

Functional tooth units 0.01 0.013Age 0.02 0.02 0.22***4Bite force 0.24*** 0.48*** 0.45***5 0.27***

0.12** 0.08* 0.27*** 0.13**6 0.06DiabetesMasticatory performance 0.06 0.08 0.82*** 0.19*** 0.55*** 0.19***7

0.25***0.13 0.25***0.040.41***0.22***Masseter cross-sectional area 0.15*8

a *, P0.05; **, P0.01; ***, P0.001. , Sample size for correlations involving masseter cross-sectional area is 216, anddisplayed P-values are correct for this sample size.

J.P. Hatch et al. / Archies of Oral Biology 46 (2001) 641648 647

Although ability to chew has sociopsychological as-pects, masticatory performance is considered an objec-tive indicator of masticatory function (Boretti et al.,1995; Yamashita et al., 1999). On the whole, a generalprediction about masticatory performance in dentatesubjects can be made using the proposed multivariatemodel. Nevertheless, moderate to high coefficients forthe residual variables indicate the presence of unknownfactors associated with the outcome measures. Thesemay include biological, behavioral, and/or social vari-ables not assessed here. Because of the population-based design of this study, we focused on selectedvariables and pathways to limit the complexity of theanalysis (Sheultz and Poulsen, 1999). In future studieswe will test if this model can be generalized to otherpopulations, such as edentulous individuals and wearersof removable prostheses. It also will be necessary toconduct longitudinal studies to confirm causal relation-ships and refine the model.

Acknowledgements

This study was supported by NIH/NIDCR GrantP50 DE 10756 and by CAPES/Brazil BEX 0807/99-0.

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