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American Journal of Epidemiology Advance Access originally published online on May 26, 2006
American Journal of Epidemiology 2006 164(3):246-256; doi:10.1093/aje/kwj188
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American Journal of Epidemiology Copyright © 2006 by the Johns Hopkins Bloomberg School of Public Health All rights reserved; printed in U.S.A.

Original Contribution

Genetic and Environmental Influences on Variation in Balance Performance among Female Twin Pairs Aged 21–82 Years

Natalie El Haber1,2,3, Keith D. Hill1,3, Anne-Marie T. Cassano2, Lynda M. Paton2, Robert J. MacInnis4, James S. Cui5,6, John L. Hopper5 and John D. Wark1,2

1 Department of Medicine, Faculty of Medicine, Dentistry and Health Sciences, The University of Melbourne, Melbourne, Victoria, Australia
2 Department of Medicine, Royal Melbourne Hospital, Melbourne, Victoria, Australia
3 National Ageing Research Institute, Melbourne, Victoria, Australia
4 Cancer Council Victoria, Melbourne, Victoria, Australia
5 Centre for Genetic Epidemiology, School of Population Health, The University of Melbourne, Melbourne, Victoria, Australia
6 Department of Epidemiology and Preventive Medicine, Monash University, Melbourne, Victoria, Australia

Correspondence to Prof. John D. Wark, Department of Medicine, Royal Melbourne Hospital, Parkville, Victoria 3050, Australia (e-mail: jdwark{at}unimelb.edu.au).

Received for publication August 9, 2005. Accepted for publication February 13, 2006.


   ABSTRACT
TOP
 ABSTRACT
INTRODUCTION
 MATERIALS AND METHODS
 RESULTS
 DISCUSSION
 References
 
Genetic and environmental influences on variation in balance performance were measured in 93 monozygous and 83 dizygous female twin pairs aged 21–82 years (mean age, 50.5 years) in Melbourne, Australia, between 1999 and 2003. The authors administered clinical (Lord's Balance Test and Step Test) and laboratory tests of static and dynamic balance from the Chattecx Balance System with and without distractor tasks. The authors conducted factor analysis and estimated genetic and environmental variance components and heritability (defined as additive genetic variance as a proportion of all variance, after adjustment for age) using a multivariate normal model with the statistical package FISHER. Three factors were identified and adjusted for age. Heritability was 46% (standard error (SE), 9) for the "sensory balance tests" factor and 30% (SE, 9) for the "static and dynamic perturbations" factor. For both factors, the remaining variance was attributed to unique environmental effects. There was no evidence that genetic factors influenced variation in the "dynamic weight shift tests" factor, with environmental effects shared by twins accounting for 38% (SE, 7) of variance. Neither genetic nor environmental proportions of variance differed significantly between twin subgroups by age (≤50/>50 years). An age-related decline in performance measures was found across the whole sample. These results imply that balance impairments may have a heritable element.

genetics; models, genetic; musculoskeletal equilibrium; posture; twins

Abbreviations: CBS, Chattecx Balance System; DZ, dizygous; LBT, Lord's Balance Test; MZ, monozygous


   INTRODUCTION
TOP
 ABSTRACT
 INTRODUCTION
MATERIALS AND METHODS
 RESULTS
 DISCUSSION
 References
 
Consequences of balance dysfunction include falls and fractures, which represent major public health and individual medical problems that affect health and independence. Falls are a common problem for women over 65 years of age (1Go), although a decline in balance function has been demonstrated in women starting from the age of 40 years (2Go). Overall, women at all ages experience more fall-related bruising, soft tissue injuries, and fractures than men (3Go).

Reduced balance function might be related to a genetic trait in some persons rather than due to a specific disease state. If such a heritable component of balance dysfunction exists, clinicians need to be aware of this cause of variation in order to identify its presence and consider approaches to the management of genetically determined fall risk.

Cummings et al. (4Go) have reported familial aggregation of hip fracture, where a woman's maternal history of hip fracture is predictive of future hip fractures. Heritability of bone mineral density and hip axis length can explain approximately 20 percent and 10 percent, respectively, of familial aggregation of hip fractures (less than half the risk associated with maternal hip fracture) (5Go). Therefore, there remains a substantial residual unexplained component of this familial risk, to which a familial risk of falls might contribute.

In the present study, a classical twin study, we examined whether there is a significant genetic influence on an important element of fall risk (balance) that might help to explain why hip fractures run in families. Previous studies have investigated the heritability of functional ability in male (6Go, 7Go) and female (6Go) twins over 68 years of age and the genetic contribution to measures of lower extremity function in older male twins. Estimated heritability was 34–47 percent for three functional ability scores among older females (6Go), and among the male twins, significant within-pair differences in correlations were reported between the two zygosities for measures of walking speed and functional measures of leg muscle but not for measures of standing balance (7Go). However, the former study (6Go) was based on self-reports, which may differ from actual performance measures (8Go). There is a need to undertake similar investigations among females, since the greatest impact of osteoporosis, falls, and fall-related fractures is evident among older women (9Go).

Recently, Pajala et al. (10Go) identified a moderate genetic influence on balance in a study containing 97 monozygous twin pairs and 102 dizygous twin pairs. However, that study was limited to women within a narrow age range (64–76 years) and used only static tests of balance. Dynamic balance measures may provide different and possibly more useful data than static tests (11Go). Other limitations associated with the testing protocol of Pajala et al. included a lack of practice trials prior to testing (10Go). These issues were addressed in the current study. Our aims in this study were to 1) test the hypothesis that additive genetic factors contribute significantly to variation in balance-related traits among adult female twins and 2) determine differences in these measures as a function of age.


   MATERIALS AND METHODS
TOP
 ABSTRACT
 INTRODUCTION
 MATERIALS AND METHODS
RESULTS
 DISCUSSION
 References
 
Participants
Participants were enrolled in the Australian Twin Registry and the Twin Research Program at the Royal Melbourne Hospital (Melbourne, Victoria, Australia) and had participated in bone research investigating genetic and environmental determinants of bone health. Participants were required to have a good understanding of English, and subjects with major musculoskeletal disorders were excluded. One hundred and eighty pairs of community-dwelling twins (94 monozygous pairs and 86 dizygous pairs) were recruited and completed the full evaluation. Twins' zygosity was determined through a self-report questionnaire designed by the Australian Twin Registry (12Go), which is accurate in identifying true zygosity in 95 percent of twin pairs (13Go).

The study was approved by both the institutional Human Research Ethics Committee and the Australian Twin Registry. All subjects gave informed written consent for participation.

Procedures
Demographic data and information on risk factors for falls and fractures were obtained from questionnaires completed prior to the testing session. The testing session, which lasted 1.5 hours per subject, was conducted at the National Ageing Research Institute and comprised screening tests and assessment of clinical and laboratory measures of balance.

Screening tests.
Subjects were excluded if they had clinically significant impairment or disease affecting their ability to perform test procedures. Screening tests, with cutoff scores for exclusion shown in square brackets, were as follows.

  1. Abbreviated Mental Test Score (14Go) [<7/10].
  2. Visual contrast sensitivity using the Melbourne Edge Test (15Go) [<16/24].
  3. Proprioception of both great toes. Three trials were given for each great toe with confounding movements of the toe interspersed [any incorrect response].
  4. Sharpened Romberg Test (16Go). Subjects were instructed to stand with one foot in front of the other, heel to toe (with whichever foot they preferred in front), and with their arms by their side and eyes closed for 5 seconds [being unable to maintain this position for 5 seconds].
  5. Postural blood pressure and pulse rate. Postural blood pressure and pulse rate were recorded in the supine position, after standing for 1 minute, and after standing for 3 minutes, using an automatic electronic blood pressure Sein-6000 device (Sein Electronics Company Ltd., Kyunki-do, South Korea) [>20-mmHg drop in systolic blood pressure or >10-mmHg drop in diastolic blood pressure upon standing] (17Go).

Three dizygous pairs of twins were excluded. One member of each of two pairs reported musculoskeletal problems that affected her test performance (Scheuermann's disease and poliomyelitis), and one member of the third pair failed to correctly identify left toe proprioception. One monozygous twin pair was excluded because one member reported a history of poliomyelitis and also scored less than 7 on the Abbreviated Mental Test Score. Therefore, 93 monozygous and 83 dizygous twin pairs were included in the study.

Balance performance measures.
Participants' heights and weights were recorded, and shoes were removed prior to testing. Because of the complex, multifaceted nature of balance performance, the following validated laboratory and clinical measures of balance were performed.

Posturography tests.
The Chattecx Balance System (CBS) (Chattanooga Group, Inc., Chattanooga, Tennessee) is a computerized force platform used to measure the body's center of pressure under several static and dynamic conditions (18Go). CBS testing was conducted while the participant stood with feet together and eyes open, using a six-test protocol (19Go). The order of the six tests was randomized to account for learning and fatigue effects. The six tests consisted of three platform conditions (stable, forward-backward tilting, and side-to-side tilting), each assessed as a single task as well as under dual-task conditions, where the subject performed a concurrent distractor task (counting backwards by threes from a randomly selected three-digit number as quickly and accurately as possible while keeping as steady as possible). Several indices were derived from the center-of-pressure data, including total sway (root mean square), symmetry, and amplitude of sway in the anteroposterior and mediolateral directions. On the basis of previous research, the mediolateral amplitude (cm) of center-of-pressure excursion was the primary measure selected from the CBS for each test condition (20Go). One acclimatization session was conducted to achieve consistent performance on the CBS (18Go).

Clinical balance tests.
1) Lord's Balance Test. Lord's Balance Test (LBT) is a series of dual-limb static stance tests (feet 10 cm apart) using a sway meter to record displacements of the body at the level of the waist (21Go). Four sensory conditions, each of 30 seconds' duration, were evaluated: standing on a firm surface with eyes open and eyes closed and standing on high-density foam with eyes open and eyes closed. Total sway for each test condition was calculated manually by counting the number of 1-mm squares traversed by a pen on graph paper during the 30-second period. Data from one dizygous twin pair were excluded from analysis of the eyes-closed-on-foam task, because one member of the twin pair was unable to balance for the full 30 seconds. 2) Step Test. The Step Test, a measure of dynamic single-limb stance, involves stepping one foot on and off a 7.5-cm-high block as fast as possible for 15 seconds (22Go). Performance was assessed separately for each leg.

Statistical analysis
Regression and factor analyses.
Significant differences between monozygous and dizygous twins with regard to demographic variables were evaluated using the {chi}2 statistic. Linear regression analyses were performed to standardize the CBS mediolateral amplitude of sway excursion (cm) by the subject's height (m).

Principal-component factor analysis (oblique rotation) was used to rationalize balance measures, to reduce measurement error and the replication and redundancy of testing/data (23Go). Factor scores obtained in factor analysis are arbitrary units with a mean value of 0 and a standard deviation of 1.

Twin analysis and modeling.
The following analyses were undertaken for the whole sample and separately for younger (age ≤50 years; 56 monozygous twin pairs, 37 dizygous twin pairs) and older (age >50 years; 37 monozygous twin pairs, 46 dizygous twin pairs) subgroups.

Correlation.
Within-pair correlations in monozygous and dizygous twin pairs with regard to age-adjusted outcome measures were evaluated using intraclass correlation coefficients. We used the classical twin model approach (24Go), comparing the strength of within-pair correlations of monozygous (rMZ) and dizygous (rDZ) twin pairs in measures of balance function. This comparison can be used to estimate the genetic contribution to variation in traits. This design is based on the assumption that monozygous twins are genetically identical (share 100 percent of their genes) and differences between them can be due only to environmental factors, whereas dizygous twins share on average half of their segregating genes and differences between them can be due to a combination of both environmental and genetic factors (25Go–27Go). The intraclass correlation coefficient was used to estimate within-pair similarity for monozygous and dizygous twin pairs. By comparing the within-pair correlations of the two zygosities, an estimate of the genetic component of a trait can be obtained. This model has been explained in detail previously (24Go).

Univariate analysis.
Genetic and environmental (shared and unique) variance component analyses were performed following the classical biometric model (25Go). Model parameters were estimated by maximum likelihood methods using FISHER software (24Go, 28Go). The total variance of each phenotype (Y) was decomposed into its variance components representing additive genetic Formula common- or shared-environment (shared within pairs) Formula and individual (unique to individuals within pairs) Formula effects. Univariate component analyses were performed for each performance measure separately. The mean values of all performance measures were adjusted for age concurrently with the estimation of variance components as quadratic functions (and are presented as decrement/increment per unit of balance measure per year). Graphic representations of quadratic relations between age-adjusted and non-age-adjusted performance measures were plotted.

Models of genetic and environmental determination of balance and related measures were devised, starting from the ACE model (25Go), which includes additive genetic effects (A), common environmental effects (C), and specific environmental factors (E). Following the assumptions of the classical twin model, three basic models were fitted: model 1, Formula (assumes that rMZ is twice rDZ); model 2, Formula (assumes that rMZ is equivalent to rDZ); and model 3, no variance component constrained (assumes that rMZ is greater than rDZ).

The most parsimonious model was selected by calculating differences between twice the log-likelihood for each model and comparing the differences with the {chi}2 distribution to conduct relative goodness-of-fit tests between observed covariances and expected covariances on the basis of fitted model parameters and the Akaike Information Criterion (29Go).

Fisher Z transformation of the correlations and variance components (obtained from FISHER analyses) was performed to test differences between the younger and older subgroups.

All statistical analyses other than the FISHER analyses were conducted using SPSS for Windows (release 11.0.1; SPSS, Inc., Chicago, Illinois). All p values were two-sided, and statistical significance was defined as p < 0.05.


   RESULTS
TOP
 ABSTRACT
 INTRODUCTION
 MATERIALS AND METHODS
 RESULTS
DISCUSSION
 References
 
Participants' health profile
The participants' demographic profile is presented in table 1. Monozygous and dizygous twins displayed similar characteristics regarding living arrangements, medical history, falls, and fracture history (p > 0.05). Thirty-four percent of both monozygous and dizygous twins had experienced fractures; 70 percent (monozygous twins) and 82 percent (dizygous twins) of these fractures were fall-related. Approximately 5 percent of monozygous twins and 11 percent of dizygous twins reported that their mother had broken her hip. Twenty percent of participants were aged 20–39 years, 58 percent were aged 40–59 years, and 22 percent were aged 60 years or more. One fifth of participants reported having had a fall in the past year (20 percent of monozygous twins and 21 percent of dizygous twins).


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  		TABLE 1. Demographic profiles of monozygous and dizygous twin pairs, Melbourne, Victoria, Australia, 1999–2003

 
Performance of twins on the balance measures
An important assumption in twin studies is that mean values and total variances in monozygous and dizygous twins are equal. Estimates of heritability may be biased if these values differ between zygosities. Mean values and total variances were similar between monozygous and dizygous twins for all performance measures in this study (p > 0.05) (table 2).


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  		TABLE 2. Age-adjusted mean scores for performance on balance measures between monozygous and dizygous twin pairs, Melbourne, Victoria, Australia, 1999–2003*

 
Principal-component factor analysis
Comprehensive assessment of a complex trait such as balance requires the selection of appropriate and multiple balance tests. However, complexity and difficulty in the precision of direct measurement of multiple balance tests may lead to overestimation of unique environmental effects and underestimation of heritability effects on balance measures. Using principal-component factor analysis, we reduced data obtained from multiple balance measures (the CBS, the LBT, and the Step Test) into three factors labeled as follows on the basis of tests loading most strongly on each factor. Factor 1, "static and dynamic perturbations" (accounting for 33.5 percent of variance), included the six CBS tests; the strongest-loading individual measure on this factor was side-to-side perturbation with distraction. Factor 2 was labeled "sensory balance tests." The four LBT measures loaded most strongly on this factor (accounting for 15.5 percent of variance); the strongest-loading individual measure was the test of standing with one's eyes closed on a firm surface. Factor 3 was labeled "dynamic weight shift tests" (accounting for 13.1 percent of variance); the strongest-loading measures on this factor were the right and left leg support Step Test scores. These factors accounted for 62.1 percent of the variance in global balance performance. Our findings demonstrated high reliability of these factor scores (intraclass correlation coefficients were 0.71 for "static and dynamic perturbations," 0.82 for "sensory balance tests," and 0.86 for "dynamic weight shift tests").

Association of age with measures of balance
Average scores for each balance test for the full sample (mean age = 50.5 years) are reported in table 3. Postural sway on the CBS tests increased with age by 0.01–0.07 units (mediolateral amplitude (cm)/height (m)) per year (0.47–0.85 percent difference per year of mean score measure), depending on the test. Increase in sway per year for LBT varied from 0.20 mm per year to 1.46 mm per year (0.32–1.39 percent/year), with the greatest age-related difference being evident for the most challenging condition (eyes closed on foam). Performance on the Step Test declined with age by 0.10–0.13 steps per year (0.53–0.67 percent/year) (table 3).


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  		TABLE 3. Association of age with balance measures in a sample of female twins (n = 352) with an average age of 50.5 years, Melbourne, Victoria, Australia, 1999–2003

 
Overall, for "static and dynamic perturbations" and "sensory balance tests" (factors 1 and 2), there were increases of 0.03 (figure 1, table 3) and 0.02 (figure 2, table 3) units per year of increasing age, respectively, and for "dynamic weight shift tests" (factor 3), there was a decrease of 0.03 units per year of increasing age (figure 3, table 3).


Figure 1
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  		FIGURE 1. Relation between age and the height (m)-adjusted "static and dynamic perturbations" factor in women aged 21–82 years, Melbourne, Victoria, Australia, 1999–2003.

 

Figure 2
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  		FIGURE 2. Relation between age and the "sensory balance tests" factor in women aged 21–82 years, Melbourne, Victoria, Australia, 1999–2003.

 

Figure 3
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  		FIGURE 3. Relation between age and the "dynamic weight shift tests" factor in women aged 21–82 years, Melbourne, Victoria, Australia, 1999–2003.

 
Within-pair correlations in monozygous and dizygous twin pairs
Age-adjusted intraclass correlation coefficients for monozygous and dizygous twin pairs are presented in table 4. Correlation coefficients were consistently greater for monozygous pairs than for dizygous pairs on a number of measures, including several that were significantly different or close to reaching nominal significance: the CBS tasks forwards-backwards perturbations with distraction (rMZ = 0.36, rDZ = 0.10; p = 0.07) and without distraction (rMZ = 0.26, rDZ = –0.07; p = 0.03) and the LBT task "eyes open on a firm surface" (rMZ = 0.35, rDZ = 0.09; p = 0.07).


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  		TABLE 4. Age-adjusted intraclass correlation coefficients for balance measures among monozygous (rMZ) and dizygous (rDZ) twin pairs, Melbourne, Victoria, Australia, 1999–2003

 
We identified significant differences in within-pair correlations between monozygous and dizygous twin pairs on balance measure factor scores for "static and dynamic perturbations" (rMZ = 0.41, rDZ = 0.001; p = 0.005) and "sensory balance tests" (rMZ = 0.51, rDZ = 0.16; p = 0.009). The difference in within-pair correlations was not significant for the "dynamic weight shift tests" factor score, where rDZ was greater than half of rMZ (rMZ = 0.46, rDZ = 0.38; p = 0.5).

The high rMZ relative to rDZ suggests involvement of genetic influences on the CBS and LBT measures. An rDZ greater than half of or equivalent to an rMZ is consistent with common environmental effects, as on the Step Test (table 4).

Intraclass correlation coefficients for rMZ for younger (≤50 years) and older (>50 years) twins were not significantly different for the balance performance measures and factor scores (p > 0.05; data not shown). Similarly, there was no significant difference in the same comparisons for rDZ.

Genetic and environmental univariate model-fitting analyses
When we compared the ACE, AE, and CE models for the factor scores obtained from the principal-component factor analysis, the AE submodel provided the best fit for the CBS and LBT measures. In this model, additive genetic effects explained 30 percent of variance in the "static and dynamic perturbations" factor and 46 percent for the "sensory balance tests" factor, with the remaining variance being attributed to unique environmental effects. The CE model was the most parsimonious model for the "dynamic weight shift tests" factor, where common environmental influences contributed 38 percent of the total variance, while the remainder was due to unique environmental effects and measurement error (table 5).


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  		TABLE 5. Models of balance measures for female twin pairs aged 21–82 years, Melbourne, Victoria, Australia, 1999–2003

 
The pattern of variance distribution with the FISHER analysis for the younger and older subgroups did not differ significantly from that for the overall sample (p > 0.05, table 5), although a trend was evident for the "static and dynamic perturbations" factor (p = 0.103).


   DISCUSSION
TOP
 ABSTRACT
 INTRODUCTION
 MATERIALS AND METHODS
 RESULTS
 DISCUSSION
References
 
Our study showed that genetic effects accounted for more than 30 percent of the total variance in factors relating to static and dynamic and sensory balance measures. Similar results were obtained when subjects were divided into subgroups above and below the median age of the whole sample (≤50/>50 years). This heritable contribution to balance function may indicate a familial risk of falls and may contribute to the familial risk of hip fractures. Common environmental effects on the "dynamic weight shift tests" factor suggest a familial, nongenetic component of risk. To our knowledge, there has been no previous application of factor analysis with a range of physical measures in determining heritability, as was done in this study.

These results are consistent in part with conclusions drawn by Pajala et al. (10Go) from their study of genetic and environmental influences on balance performance in a sample of female twins aged 64–76 years. They identified additive genetic and common environmental influences accounting for 35 percent and 24 percent, respectively, of the total variance in static balance performance. However, results from our study did not identify any common environmental influences on the static and dynamic and sensory balance test factors. In contrast, the moderate-to-high within-pair correlations in both monozygous and dizygous twins suggest shared environmental influences on the "dynamic weight shift tests" factor, with common environmental effects explaining 38 percent of the total variance. Several studies have reported moderate-to-high correlations for both monozygous and dizygous twin pairs on lower extremity muscle strength measures, ranging from 0.41 to 0.80 in monozygous twins (7Go, 30Go–32Go) and from 0.31 to 0.77 in dizygous twins (7Go, 33Go). These results suggest that performance of dynamic weight shift tasks such as the Step Test may require a substantial amount of lower limb strength compared with other balance tasks, and muscle strength appears to be explained to a moderate degree by common environmental effects. Such common environmental effects also contribute to the familial aggregation of traits.

A study of 185 male twin pairs aged 68–79 years (7Go) attempted to identify determinants of neuronal cellular loss by evaluating the contribution of genetic influences to measures of lower extremity function. Results indicated that there were genetic influences on gait and strength measures and that the heritability of a lower-extremity summary scale was 57 percent, of which 39 percent was due to additive genetic effects and 18 percent was due to a nonadditive dominance effect (7Go). In contrast to our study, that study did not identify a heritable component in the balance measures investigated, which may have been partly due to the narrow selection of static tests of balance used as outcome measures (7Go).

The results of our study add to previous research in terms of the range of static and dynamic balance measures utilized, as well as in targeting females, who represent the group most likely to experience falls and fractures (9Go). The testing protocol used by Pajala et al. (10Go) was limited to static single tasks on a force platform. It is clear that static and dynamic balance tasks reflect differing demands on the balance system (34Go, 35Go). Pajala et al. (10Go) acknowledged the need for future studies using more challenging tasks, such as altering sensory conditions or dynamic balance tasks, to explain genetic and environmental influences on balance. Our study also included use of dual task conditions for each balance task on the CBS, which have been shown to increase the difficulty and improve discrimination of balance ability (19Go).

The broad age range used in our study differs from the narrow age range (64–76 years) in the study by Pajala et al. (10Go). Given that balance performance has been shown to decline in women starting from 40 years of age (2Go), it is important to investigate heritability across a broader age range.

The maintenance of upright posture and balance becomes more challenging with increasing age. Our findings of increased postural sway with age (on all balance tests) in women extend the findings of Melzer et al. (36Go) and many others who have reported greater sway in older women than in younger women on both single- and dual-task tests, using other systems and measurement techniques (2Go, 34Go, 37Go, 38Go). In our study, force platform (CBS) measures declined 0.47–0.85 percent per year. Similar age-related declines were observed using the clinical balance measures.

The altered sensory conditions on the LBT resulted in a greater increase in sway with eyes closed compared with eyes open (0.32–1.39 percent/year). The Step Test demonstrated a clear negative association with age (0.53–0.67 percent/year). A recent study (39Go) evaluated normative scores in women aged 20–80 years on a number of clinical measures and found that the Step Test was the most sensitive test in showing differences by age in the sample studied.

There are several potential limitations to our study that need to be considered in interpreting the generalizability of the results. The twins in this study were community-dwelling volunteers registered with the Twin Bone Program. As with any volunteer program, there was potential for recruitment bias. Comparison of activity levels between women from the Twin Bone Program who were participants and nonparticipants in this study indicated no differences in hours of general sports or walking for the last 12 months. Moreover, the subset sample of women aged 65 years or more in our study was similar to a randomly generated sample of older people living in the community (40Go), where the majority lived at home with other persons, approximately one quarter were taking more than four medications, and most of the participants rated their general health as good. Therefore, the results of this study are likely to be generalizable to the wider female population.

It is possible that balance performance differs between the sample used in this study (twins) and the broader non-twin population. Performance achieved on outcome measures by the older twins in this study was similar to that reported for healthy older women (41Go). However, the estimation of the heritable component of balance is population-specific and may differ between age groups and genders (42Go), where in this case it applies to a wide age range. Based on the higher rates of low-trauma fractures and some evidence of gender differences in balance ability (43Go), we decided to include only female twins in this study. Evaluation of these outcomes in a similar sample of males is needed.

Finally, there remains a need for further studies to determine genetic and environmental effects of balance function in younger, older, and frailer populations. Although we found an age-related decline in performance measures across the whole sample, there was no difference between younger and older twins in the genetic and environmental proportions of variance or in the heritability of performance measures estimated using the intraclass correlation coefficients (rMZ, rDZ). We acknowledge the wide age range of participants in this study and the relatively small sample used for the subgroup analyses of genetic and environmental factors by age. In future studies with larger samples, genetic modeling should be repeated separately for younger and older women, to identify the life stages in which the genetic effect is expressed and where it is strongest.

The identification of a heritable or familial component of balance performance may be used to facilitate early identification of fall or fracture risk. Ultimately, the results of this study may improve our understanding and management of familial hip fracture risk.


   ACKNOWLEDGMENTS
 
This project was supported by grants from the Australasian Menopause Society and the University of Melbourne Research Grant Scheme and by two scholarships (to Natalie El Haber) from Osteoporosis Australia and the University of Melbourne.

The authors acknowledge the role of the Australian Twin Registry. The Australian Twin Registry is supported by an Enabling Grant (ID 310667) from the National Health and Medical Research Council, administered by the University of Melbourne.

Conflict of interest: none declared.


   References
TOP
 ABSTRACT
 INTRODUCTION
 MATERIALS AND METHODS
 RESULTS
 DISCUSSION
 References
 

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A. Viljanen, J. Kaprio, I. Pyykko, M. Sorri, S. Pajala, M. Kauppinen, M. Koskenvuo, and T. Rantanen
Hearing as a Predictor of Falls and Postural Balance in Older Female Twins
J Gerontol A Biol Sci Med Sci, February 1, 2009; 64A(2): 312 - 317.
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