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Maximum voluntary isometric pinch contraction andforce-matching from the fourth to the eighth decades of lifeTrenah L. Herring-Marler, Waneen W. Spirduso, Richard T. Eakinand Lawrence D. Abraham

Understanding the effects of age and gender on pinch

strength, variability, and accuracy and how ones hand

function changes with age better enables those in the

preventative and rehabilitative fields to combat these

losses. The present study examined fine motor maximum

pinch strength [maximum voluntary isometric contraction

(MVIC)] as well as the ability to maintain 5% MVIC

accurately and consistently in five decades. One hundred

adults in five groups, 20 in each decade of life from 30 to 79

years old, were nonrandomly recruited from the community.

A two-way analysis of variance applied to MVIC, and a

two-way multivariate analysis of variance applied to the

variability (coefficient of variability) and accuracy (root

mean square error), plus correlation and regression

analyses, were used to determine decade and gendereffects on pinch force. The task involved using isometric

pinch control of a computer cursor to match a 5% of MVICforce level represented by a horizontal line. MVIC and

force-matching steadiness and accuracy across all ageswere not significantly different until the eighth decade

(P< 0.01). Men were stronger (P< 0.001) but performedlow-level force-matching with greater error (P< 0.001) than

women. Strength was not correlated with steadiness but

was weakly correlated with accuracy (r=0.293, P 60 years) in the ability

to produce single-finger and multifinger force (13 and 48%

lower, respectively) as compared with their gender-

matched younger (mean 21.9 years) counterparts. De

Serres and Fang (2004) reported a mean maximal pinch

force of the dominant hand of 12 young adults (2228

years) at 60.2 N, compared with 44.2 N for 12 older adults

(6775 years), a 26.6% reduction. Similar results were

found with older participants (mean 70.5 years), showing

27.3% less pinch-grip strength than young adults (Ranga-

nathan et al., 2001). Sperling (1980) reported an averagedrop of 14% in maximal finger pinch force in 70-year-old

men and women when compared with young adults

(2030 years). Similarly, Puh (2010), the only researcher

to compare pinch-grip strength across four age groups

(2034; 3549; 5064; 6579 years), found the fingertip

pinch of the oldest group to be 19% less than that of theyoungest group. However, the strongest age group was the

3549-year-old group, not the 2034-year-old group.

Force variability

Age also affects force variability during gross motor

submaximal contractions (Tracy and Enoka, 2002) and

Original article 159

0342-5282 c 2014 Wolters Kluwer Health | Lippincott Williams & Wilkins DOI: 10.1097/M RR.0b013e32836061ee

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is associated with increases in force variability during fine

motor force-matching tasks among old adults (Galganskiet al., 1993;Laidlaw et al., 2000;Ranganathan et al., 2001;

Vaillancourt et al., 2003; De Serres and Fang, 2004). In a510% maximum voluntary isometric contraction (MVIC)

matching pinch task, force fluctuations were significantlygreater in amplitude among older participants (6579

years) than in younger participants (2035 years) (Ranga-nathan et al., 2001). Furthermore, healthy older adults

(Galganski et al., 1993) and women (Ranganathan et al.,

2001) showed a decreased ability to maintain steady

submaximal forces in the hand compared with that of

young adults (2035 years) and men, respectively.

Vaillancourt et al. (2003) found an increased coefficient

of variability (CV) of force with increased age at all

force levels [5, 10, 20, 40% maximum voluntary contrac-

tion (MVC)/MVIC]; however, the greatest age differential

in variability occurred at the 5 and 10% MVC force levels.

AccuracyIn addition to decreases in strength and increases in

variability, aging decreases fine motor finger force

regulation, especially at low forces (Shinohara et al.,

2003a) and more so for those in their 80s than those in

their 70s (Hackel et al., 1992). Other researchers have

substantiated these reports with findings of larger force-

matching errors at lower force levels for older adults

(Galganski et al., 1993; Visser et al., 2003; Sosnoff and

Newell, 2006). De Serres and Fang (2004) found near-

significant differences (P< 0.068) in relative force error

between young and elderly groups (mean age 25.3 and

71.5 years, respectively) in force-reproduction tasks

without visual feedback at 5% maximal pinch force(termed MVIC in the present study) but not at the 20

and 40% MVIC force-matching levels.

Gender and strength

Puh (2010) reported, along with seven other research

groups, that womens grip strength ranged from 57 to 65%

that of men and that womens fingertip-pinch strength

reached 73% that of men. Using single-finger and four-

finger tasks, Oliveira et al. (2008) and Shinohara et al.

(2003a)investigated how the gender of participants affects

MVIC. Elderly women showed greater force deficits

(51%; Oliveira et al., 2008: four-finger task and 35.7%;Shinohara et al., 2003b) when compared with young

females, whereas older men showed 45% Oliveira et al.,

2008 and 28.2% less force production (Shinohara

et al., 2003b) than younger men. Elderly womens proximal

phalangeal press (intrinsic musculature) produced the

largest age-related force deficit of 45.2%, and mens distal

phalangeal press (extrinsic musculature) recorded the least

amount of force deficit at 23.1%, emphasizing differences

between sexes as well as between tasks that involve

extrinsic and intrinsic musculature tasks (Shinohara et al.,

2003b). Ranganathan et al. (2001) found that the pinch

strength of 70-year-old men was 14.2% less than that of

20-year-old men, but the pinch strength of 70-year-old

women was 32.5% less than that of young women, which wasmore than double the pinch strength difference in men.

Gender in force variability and accuracy

Men and womens hand function decreases with age asmeasured by the Jebson Test of Hand Function (Hackel

et al., 1992;Peolssonet al., 2001;Ranganathanet al., 2001).However, gender effects in controlling submaximal forces

in fine motor tasks have been mixed. The ability of older

women to maintain a steady submaximal pinch force has

been reported to be less than that of men (Hackel et al.,

1992). However,Shimet al. (2004)did not find any gender

effects for a multifinger task at 10% MVIC.Shinoharaet al.

(2003b) investigated how the gender of a participant

influenced finger coordination in submaximal ramped

force-matching, finding among elderly (7095 years old)

participants significant differences in the ability to match

a target force, with men having greater variability than

women (P< 0.01).

Relationships among maximum voluntary isometric

contraction, force variability, and accuracy

Few researchers have correlated fine motor strength

measures to force variability or accuracy measures. In one

study, older womens peg-placing time significantly corre-

lated negatively with their index-thumb pinch strength

(r= 0.693; Ranganathan et al., 2001). Olafsdottir et al.

(2008) found high correlations between error measure-

ments and force. Accuracy of performance was associated

with increases in the force-stabilization synergies, which

the researchers attributed to the hypothesis that

synergies lead to more reproducible performance.

Understanding the effects of age and gender on pinch

strength, variability, and accuracy, and the manner in

which ones hand function changes with age better

enables those in the preventative and rehabilitative fields

to combat these losses. The present study examined fine

motor maximum pinch strength (MVIC) as well as theability to maintain 5% MVIC accurately and consistently

in five decades, from 30 to 80 years of age.

The researchers hypothesized that (a) 10-year age groups(decades) would differ in MVIC, variability, and accuracy;

(b) mens MVIC pinch strength would be higher thanwomens; (c) the interaction of decade and gender would

not be significant for MVIC pinch; and (d) genderdifferences would not be significant for variability and

accuracy. It was also hypothesized that MVIC would becorrelated with submaximal force variability (CV) and

accuracy [root mean square error (RMSE)].

MethodsParticipants

One hundred adults in five groups, 20 in each decade of

life from 30 to 79 years, participated voluntarily in the

160 International Journal of Rehabilitation Research 2014, Vol 37 No 2



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study. Each decade group contained 10 men and 10

women. On the basis of a P level of 0.05 or higher,and power levels equal to or greater than 0.950, we

used Cohens (1988) interpretation of effect sizes todetermine meaningful differences. Participant selection,

regardless of ethnic background or socioeconomic status,was based on the participants self-reported absence of

both neurological symptoms and past or current relatedmedical treatment. Participants were excluded if deemed

unable to comprehend or sufficiently perform practice

trials or if they presented with any other marked deficit

(e.g. vision impairments, orthopedic injury to tested

upper extremity) affecting their ability to complete the

task. Participants were allowed to use corrective lenses.

Participants taking medications that could interfere with

hand function, cognition, or visual acuity were also

excluded (e.g. lithium, baclofen).

DesignThis study used a quasi-experimental between-model

design in which the independent variables (between

factors) were age (decade) (3079 years) and gender

(male/female). The dependent variables (within factors)

were MVIC, pinch-force variability (CV), and accuracy

(RMSE). The MVIC was defined as the highest aggregate

preferred hand thumb and finger force level of three

MVIC trials expressed in N. The CV (force variability)

was calculated as the mean of the coefficient of thumb

finger aggregate force measurements for all of a

participants 10 individual trials. Those 10 trial-specific

values represented an average difference between a

measured force at each sampling and the mean forceacross all samplings scaled by that mean; that is, the SDs

away from the participants own mean divided by the

participants own mean. Thus, CV= sum (SD/m)/10.

The dependent variable used to indirectly assess accuracy

was a RMSE derived from the individual force error of

each sampling instance corresponding to the static target

level, which was scaled to 5% of the persons MVIC.Thus, for each sampling, the error e was determined by

e fcj j5 % MVIC;

where fc

is the force level of the cursor, determined

by the sum of the finger and thumb forces. Thedependent variables then were determined as the root

mean square of these error values, that is,

RMSE

ffiffiffiffiffiffiffiffiffiffiPNi1

e2i

N

vuuut ;

whose mean over a grouping is

RMSEM

XM

i1

RMSE i

and the CV of force, that is,

CV

ffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiPNi1

fcfc 2

i=N

s

fc;

whose mean over a grouping is

CVMXMi1

CV i:

In these expressionsNis the number of samplings within

the trial segment with the summation running overall

sampling instances in the interval being evaluated and

M is the number of trials or trial segments over which

the variable mean is taken.

Instrumentation and procedures

This study used the Manual Force Quantification System

(MFQS) (Fig. 1a and b), controlled by LabVIEW software

(LabVIEW 6.1; National Instruments, Austin, Texas,

USA), which quantifies low-level isometric force control

during a precision pinch task of the thumb and index

finger (Spirdusoet al., 2005a).Spirduso et al. (2005a)can

also be referenced for instrumentation, procedures, and

data acquisition.

After a demonstration, the participants provided three

maximum pinch forces for a duration of 6 s each with a

1-min rest between them. The participants performed 10

force-matching (Fig. 2) trials at 5% MVIC for a test time

duration scaled to their MVIC, between 12 and 18s.

These were the last 10 trials of a battery of three tests:

tracing (20 trials), tracking (20 trials) and force-matching

(10 trials). The protocol was similar to that described

bySpirduso et al. (2005b), and the details and outcomes

of these other results (tracing and tracking) are presented

in separate studies. No static force-matching elements

were included in the 40 prior task trials, thus the

participants gained no specific force-matching practiceby performing the prior tasks. Five of the 100 participants

used their left hand as their preferred hand (Fig. 2).

Analysis

Statistical analyses included descriptive statistics. A mod-ified z-score method of finding outliers (Shiffler, 1988) was

used. Trial data that were above an absolute value of 2.85

(maximumz-score for an Nof 10) were removed from the

data analysis but saved for reference. Means and SDs were

recalculated based on the remaining trials.

A simple analysis of variance (ANOVA) was used to analyze

MVIC, and two-way MANOVA (decade and gender) with

Bonferroni correction was carried out to analyze RMSEand

CVin force-matching. Main effects and interactions were

tested. Post-hoc, pair-wise comparisons were carried out for

decades in MVIC, RMSE, and CV. Levenes test of

MVIC pinch and force-matching Herring-Marleret al. 161



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homogeneity, Pearsons product-moment correlation, and

regression analyses were performed.

ResultsMaximum voluntary isometric contraction force

The main effect for decades MVIC was significant

[F(4,90) = 4.857, P< 0.001, Z2P= 0.178] for precision

pinch peak force (Fig. 3). Post-hoc, pair-wise comparisons

revealed that the maximum isometric pinch forces

of the participants in their 70s were significantly lower

than those of participants in their 40s (P< 0.01),

50s (P< 0.005), and 60s (P< 0.01). Although the 30s

had higher MVIC values than the 70s, the difference

between the groups was not statistically significant

(P= 0.09).

The main effect for gender was significant with a large

effect size for maximal pinch force [F(1,90) = 81.09,P< 0.001, Z2P= 0.474]. The MVIC of women was 29.9%less than that of men overall (Table 1). Gender did not

interact with decade in MVIC.

Force-matching

The force-matching test also resulted in age-related

effects for force variability and accuracy. The mean

within-participant force variability for each decade,

produced by averaging all the individual CV values of

the groups participants CV, revealed a main effect for

decade [F(4,90) = 7.318, P< 0.001, Z2P= 0.240]. Post-

hoc tests revealed that participants in their 70s were

more variable than participants in their 30s, 40s, 50s, and

60s (46, 48, 39, and 35% difference, respectively,P< 0.01; Fig. 4a). A main effect for accuracy (RMSE)

was found [F(4,90) = 4.773, P< 0.005, Z2P= 0.175].

Participants in their 70s produced significantly more

error than the participants in their 30s and 40s (43 and

36% at P< 0.01, respectively). Additionally, participants

in their 70s approached significance in error differences

from participants in their 50s (30% more error, P= 0.06);

whereas those in their 60s were not different from those

in their 70s (23% more error, P= 0.33;Fig. 4b).

No gender effects were found for force variability.However, there were gender effects for accuracy

[F(1,90) = 17.389, P< 0.001, Z2P= 0.162]. Men per-formed with higher error at RMSE = 0.073 N, whereas

the equivalent value for women was 32% lower(RMSE = 0.50 N). No interactions were found.

Correlation and homogeneity

Pearsons product-moment correlation with sexes com-

bined (N= 100) between MVIC and accuracy (RMSE)

wasr= 0.293,P< 0.01; whereas, for CVandRMSEit was

r= 0.783,P< 0.001. MVIC andCVwere not significantly

correlated with each other.

Fig. 1

(a) Manual Force Quantification System (MFQS) and (b) force transducers. The MFQS includes a force-matching template displayed on a computerscreen, a platform, and a console (a) that supports the adjustable force transducers (b) and arm and wrist supports. Matching task is displayed oncomputer monitor.

Fig. 2

Start

Stop

Target line

Visual cue lines

Analyzed data

Initial cursor position

Force-matching task. The participants dot cursor is red until his or hercombined thumb and finger force reaches his or her 5% maximumvoluntary isometric contraction (MVIC) force level, which is the start pointon the horizontal line. Time, not the participant, moves the cursor acrossthe target line. The participant simply attempts to match a constant 5%MVIC force level denoted by the target line for the time configured foreach participant, which is a time relative to his or her own MVIC.




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Levenes test for homogeneity of variance was applied

to determine how homogeneous each decades CV andRMSEwereCV (P< 0.009) andRMSE(P< 0.002). SDs

within each decade group tended to increase as thedecades increased with the greatest diversity (SD) being

in the 7079-year group (Table 2).

Regression

A regression analysis was performed to determine the

impact of MVIC, decade, and gender on force-variability

characteristics (CV and RMSE). The model revealed a

significant overall effect [F(3,99) = 11.296, P< 0.001,R = 0.511] for CV and [F(3,99) = 12.631, P< 0.001,R = 0.532] forRMSE.

MVIC, decade, and gender were all strong predictors ofCV (P< 0.05, b = 0.292; P< 0.01, b = 0.422; andP< 0.001, b = 0.317, respectively). A 4.7% of variance

in CV was uniquely accounted for by MVIC (partcorrelation = 0.217), 17% by decade (part correlation =

0.413), and 5.7% by gender (part correlation = 0.239).

Decade was a strong predictor (P< 0.001,b = 0.391) of

RMSE, whereas gender was a moderate predictor(P< 0.05, b = 0.229). Fifteen percent of RMSE var-

iance was uniquely accounted for by decade (partcorrelation = 0.383) and 3.0% by gender (part correla-

tion = 0.172). MVIC was not a significant predictor ofRMSE [Part correlation (otherwise known as semipartial

correlations), as opposed to partial correlation, takes intoaccount other variables contributions and eliminates those

contributions from the influence of the variable of interest.].

DiscussionMaximum voluntary isometric pinch force

The results suggest that fine motor pinch strengthdeclines with age. Declines were slightly less than

previously reported for gross motor strength after 5070years, 15% per decade (Grabiner and Enoka, 1995) or

11.5% per year (Spirduso et al., 2005b) with a 7%

decrease from the 50s to the 60s and 13% from the 60s tothe 70s. Furthermore, the strength differences between

the 70s and the 30s were similar (19% decrease; women

27%, men 13%) to losses previously recorded in various

fine motor strength studies involving older adults ranging

from 60 to 75 years and younger adults from 20 to 35 years

old, with 26% (Ranganathan et al., 2001), 30% (Oliveira

et al., 2008), 26.6% (De Serres and Fang, 2004), and 14%

(Sperling, 1980) strength losses.

Pinch-force strength did not decline linearly across the

decade groups, as has been seen with isometric grip

strength, which involves multiple larger muscle

masses. Rantanen et al. (1998) reported a clear lineardecline significantly different in every age group in a

sample of 3680 men ranging in age from 45 to 92 years in

grip strength, a manual isometric test requiring full force

from both intrinsic and extrinsic muscles controlling the

thumb and digits. Puh (2010) also found significant

differences in isometric grip and three different pinch

forces in four different age categories ranging from 2034

to 6579 years; however, these were not linear. Puhs

second age group (3549 years) and this studys second

age group (4049 years) showed higher strength levels

than the respective younger age groups.

While our 4069-year-olds were statistically stronger thanthe 70-year-olds, 30-year-olds had higher MVIC values

Fig. 3

MVIC

MVIC(

N)

120

100

80

60

40

20

030s 40s 50s 60s 70s

Men Women

Maximum voluntary isometric contraction (MVIC) force across decades.The 7079-year-olds were weaker than people in their 60s, 50s, and40s (P< 0.01), but, interestingly, not weaker than the 30s. Values are

the decade group meansSD.

Table 1 Maximal voluntary isometric contraction by decade and gender

MSD

Fourth decade(3039 years)

Fifth decade(4049 years)

Sixth decade(5059 years)

Seventh decade(6069 years)

Eighth decade(7079 years)

Average acrossdecades

MVIC force (N) 63.214 66.019 69.516 67.016 54.016 64.317Men MVIC (N) 73.507 78.317 78.815 80.110 63.313 74.814Women MVIC (N) 52.811 55.012 59.210 53.908 44.713 53.112

MVIC, maximum voluntary isometric contraction.




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than those in their 70s, but not so much so that it

resulted in significant differences. Upon closer examina-

tion, the 30-year-olds contained a wide distribution of

MVIC values with two substantially low MVICs, which

contributed toward the insignificant differences (P=

0.09) between the 30- and 70-year-olds.

Gender effects on maximum voluntary isometric contraction

The significant gender main effect indicated that

womens pinch-force averages were lower than mensthroughout the decades. Averaged over five decades, men

were 29% stronger than women. An analysis of within-gender age differences revealed that men in their 70s

were able to produce 87% of their MVIC compared with

men in their 30s, whereas women in their 70s produced

only 75% compared with women in their 30s.

The decade gender interaction was not significant. Theobservation of lower MVIC for women is consistent

with previous findings. This could be explained by the

findings that women have less muscle mass than men

(Puh, 2010), demonstrate smaller twitch forces (Doherty

and Brown, 1997), have a longer half-relaxation time, and

have a higher proportion of type I fibers (Hunter, 2009).

Force variability and accuracy

The ability of participants to sustain a steady force at a

target level was compromised with aging. Adults in their

70s exhibited higher force variability than those in all

other decades. The results were similar for accuracy;

however, the difference in the 60s and 70s approached

significance (P= 0.06). Group mean step differences

between decades for force variability (CV) were as

follows: fifthfourth decade = 0.000, sixthfifth decade =

0.001, seventhsixth decade= 0.001, and eighth

seventh decade = 0.008 (Fig. 4a). Group mean step

differences in force error (RMSE) were 0.006, 0.005,0.005, and 0.019 N, respectively (Fig. 4b). Therefore, the

age differences for force-matching were also nonlinear.

Accuracy, but not force variability, was weakly and

positively correlated with fine motor strength, which

suggests that the stronger the participant was the less

accurate his or her force-matching performance was (as

measured by RMSE). CV and RMSE were positively

correlated with each other. Finally, the older the age

group was the greater were the differences in MVIC,

accuracy, and force variability among members of that

decade.

Fig. 4

0.04

0.035

0.16

0.14

0.12

0.1

0.08

(a) (b)

0.06

0.04

0.02

0

CV

CV

RMSE

RMSE

0.03

0.02

0.015

0.01

0.005

030s 40s 50s 60s 70s 30s 40s 50s 60s 70s

0.025

Men Women

Force-matching. (a) Force variability [coefficient of variability (CV)] across decades, (b) accuracy [root mean square error (RMSE)] across decades.Arrows, significant difference; double hash intercepts, near differences. The 7079-year-olds were significantly different from the 30s, 40s, 50s, and60s (P< 0.001) for CV but the 70s were not different from the 50s (P= 0.06) or 60s (P= 0.32) for RMSE. Values are decade group meansSD.

Table 2 Force variability (coefficient of variation) and accuracy (root mean square error) by decade and gender

MSD

Fourth decade(3039 years)

Fifth decade(4049 years)

Sixth decade(5059 years)

Seventh decade(6069 years)

Eighth decade(7079 years)

Average acrossdecades

Force variability (CV) 0.0130.004 0.0130.005 0.0140.005 0.0150.006 0.0230.010 0.0160.006Men (CV) 0.0130.004 0.0120.003 0.0150.007 0.0160.007 0.0250.007 0.0160.006Women (CV) 0.0120.004 0.0130.006 0.0120.003 0.0140.006 0.0230.012 0.0130.005Accuracy (RMSE) 0.0480.015 0.0540.025 0.0590.034 0.0650.028 0.0840.042 0.0620.032Men (RMSE) 0.0550.015 0.0560.017 0.0740.042 0.0750.022 0.1070.042 0.0730.034Women (RMSE) 0.0410.012 0.0520.032 0.0450.015 0.0540.030 0.0600.028 0.0500.024

CV, coefficient of variability; RMSE, root mean square error.




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Several factors have been proposed as explanations for

greater force variability and lower accuracy in the forcecontrol of older adults: lower levels of maximum strength,

enhanced neural noise, and tactile and proprioceptiveeffects.

Low force levelsIt is well documented that controlling very low levels (5%

MVIC) of force is more difficult than controlling higher

levels (Slifkin and Newell, 1999; Varadhan et al., 2010).

Also, in older participants who have significantly lower

MVICs, the requirement of extremely low force levels

(5% MVIC) could account for the greater difficulty that

older adults have in the force-matching task. Producing

5% of a very low MVIC could possibly be more

challenging than producing 5% of a moderate MVIC

(Sosnoff and Newell, 2006).

Enhanced neural noise

Neuronal noise is a term commonly used to describe the

continuous and frequent random synaptic inputs within

complex neural networks that affect individual neurons,

creating a noisy synaptic input state for any given

neuron. The noisier the neural state is the higher the

signal (motor command) has to be to be detected.

Neuronal and synaptic noise has been shown to increase

with age, resulting in lower signal-to-noise ratios, which

in turn results in older adults greater error fluctuations

during voluntary force production (Jones et al.,

2002; Smits-Engelsman et al., 2003; Christou and Tracy,

2006;John et al., 2009).Pascoet al. (2011)suggested that

age-related changes in the integration of synaptic inputreduce the ability of older adults to modulate discharge

characteristics of motor units at low sustained isometric

force levels (5% MVC) of the biceps brachii.

Tactile and proprioceptive mechanisms

A third factor that may explain age differences in

variability and accuracy is the contribution of tactile and

proprioceptive mechanisms. Neurologists and physical

therapists often use weighted spoons, wrist or ankle cuffs,or vests to assist their patients in producing steadier and

smoother movements and hence prevent food and drink

spills. Weighting enhances sensory information fromreceptors for increased proprioception (muscle spindles

and Golgi tendon organs), thus assisting patients by

providing more feedback about their location in space

and allowing them to better feel the force they are

producing. In addition, pressure (force) is sensed through

pacinian corpuscles, which enhances the development of

motor memory for the task at hand (Fix, 2002). A similar

phenomenon could be occurring with the force-matching

task. Researchers suggest that 5% MVIC of a weaker

person could result in a more unloaded condition,

feasibly offering significantly reduced initial sensory feed-

forward proprioception information as well as providing

less proprioception and kinesthesia for the participant

(Robles-De-La-Torre and Hayward, 2001).

Gender effects on force variability and accuracy

Gender differences were not significant in force variability

(CV), but they were significant in accuracy as measured by

RMSE. Just as Shinohara et al. (2003b)found men to be

more variable, this study showed similar results: men

produced greater error, RMSE = 0.073 N, than women,RMSE = 0.050 N. The differences in mens and womens

body sizes have been attributed to more effective gross

motor performance in men (Thomaset al., 1991), but fine

motor tasks require different sensorimotor attributes than

strength and power. Women have been shown to perform

better in tasks requiring sensory discrimination (Noble,

1978). Women also have a greater number of type 1 fibers;

therefore, they would activate more motor units at lower

force levels than men and, hence, would be better able to

modify fine motor forces.

Conclusion

As expected, 7079-year-olds were weaker than 4069-

year-olds, and women were weaker than men. Unique

findings of this study were that (a) no differences were

found in strength, steadiness, or force variability among

the decades, up to the seventh decade (r 69 years of

age); (b) 7079-year-olds were weaker, less steady, and

less accurate in force-matching than their younger

counterparts; (c) although Hackel (1992) found women

more variable and Shim et al. (2004) reported no gender

difference, the results of this study were in agreement

with those ofShinoharaet al.(2003b)that men performedlow-level force-matching with greater error than women;

(d) strength was not correlated with steadiness but was

weakly correlated with accuracy, and steadiness and

accuracy were strongly correlated; and (e) decade and

gender were moderate and strong predictors of accuracy

and steadiness, respectively.

Clinical applications

Fine motor strength declines are significant and can cause

severe limitations in daily activities as adults age. Society

has been educated and trained to address age-related gross-muscle motor losses with research, rehabilitation, and

training, but it is clear that fine motor deficits can beseriously debilitating as well and should receive more

attention. The results suggest that additional research

should address the benefits of training programs designed

to increase finger strength and dexterity. Accordingly, these

programs should be initiated no later than a persons sixth

decade (age 5059 years), especially in women.

The increase in SD in MVIC, force variability, and accuracy

within decade groups as age progresses suggest that as

people age they become more diversified within their age

groups. This implies that some people retain function as

they grow old, and some do not. An important goal of aging




8/8

research is to determine how to increase the number of

individuals who maintain function in their later years.

Limitations

A potential limitation for this study is a possible order

effect of task administration that could have produced

cognitive and physical fatigue. Force-matching was the

last of three tasks the participants performed within thetest session and was the easiest, but all tasks required

high levels of attention and information processing. Each

test session was B3045 min long and could have

produced some cognitive fatigue. However, given that

the matching task included only 10 trials and required

only 5% MVIC and that the overall duration over which

the slowest participants were actively contracting isome-

trically during the entire protocol was no more than

B4 min, it is unlikely that physical fatigue, even in the

older groups, compromised the results.

AcknowledgementsThe authors acknowledge and express extended appre-

ciation for the excellent help of Diana Hunter for

consultation on design and written representation,

Michael Mahometa from the Division of Statistics and

Scientific Computation at The University of Texas at

Austin for statistical consultation, and Tess Roach for

editing services.

Conflicts of interest

There are no conflicts of interest.

ReferencesChristou EA, Tracy BL (2006). Aging and variability in motor output. In: Davids K,

Bennett S, Newell K, editors. Movement system variability. Champaign, IL:Human Kinetics; pp. 199215.

Cohen J (1988). Statistical power analysis for the behavioral sciences. 2nd ed.Hillsdale, NJ: Lawrence Erlbaum Associates, Inc.

De Serres SJ, Fang NZ (2004). The accuracy of perception of a pinch grip forcein older adults.Can J Physiol Pharmocol82:693701.

Doherty TJ, Brown WF (1997). Age-related changes in the twitch contractileproperties of human thenar motor units. J Appl Physicol82:93101.

Fix JD (2002). Neuroanatomy. Hagerstown, MD: Lippincott Williams & Wilkins.Francis KL, Spirduso WW (2000). Age differences in the expression of manual

asymmetry.Exp Aging Res26:169180.Galganski ME, Fuglevand AJ, Enoka RM (1993). Reduced control of motor

output in a human hand muscle of elderly subjects during submaximalcontractions. J Neurophysiol69:21082115.

Grabiner MD, Enoka RM (1995). Changes in movement capabilities with aging.Exerc Sports Sci Rev23:65104.Hackel ME, Wolfe GA, Bang SM, Canfield JS (1992). Changes in hand function

in the aging adult as determined by the Jebsen Test of Hand Function. PhysTher72:373377.

Hunter SK (2009). Sex differences and mechanisms of task-specific musclefatigue. Exerc Sport Sci Rev37:113122.

John EB, Liu W, Gregory RW (2009). Biomechanics of muscular effort:age-related changes. Med Sci Sports Exerc41:418425.

Jones KE, Hamilton AF, Wolpert DM (2002). Sources of signal-dependent noiseduring isometric force production. J Neurophysiol88:15331544.

Laidlaw DH, Bilodeau M, Enoka RM (2000). Steadiness is reduced and motorunit discharge is more variable in old adults. Muscle Nerve23:600612.

Noble CE (1978). Age, race, and sex in learning and performance of psychomotorskills. In: Osborne RT, Noble CE, Weyl N, editors. Human variation: the bio-psychology of age, race and sex. New York: Academy Press; pp. 287378.

Olafsdottir HB, Kim SW, Zatsiorsky VM, Latash ML (2008). Anticipatory synergyadjustments in preparation to self-triggered perturbations in elderly indivi-duals. J Appl Biomech 24:175179.

Oliveira MA, Hsu J, Park J, Clark JE, Kun Shim JK (2008). Age-related changes inmulti-finger interactions in adults during maximum voluntary finger forceproduction tasks. Hum Mov Sci27:714727.

Pasco MA, Holmes MR, Enoka RM (2011). Discharge characteristics of bicepsbrachii motor units at recruitment when older adults sustained an isometriccontraction. J Neurophysiol105 :571581.

Peolsson A, Hedlund R, Oberg B (2001). Intra- and inter-tester reliability andreference values for hand strength. J Rehabil Med33:3641.

Puh U (2010). Age-related and sex-related differences in hand and pinch gripstrength in adults. Int J Rehabil Res 33:411.

Ranganathan VK, Siemionow V, Sahgal V, Yue GH (2001). Effects of aging onhand function. J Am Geriatr Soc49:14781484.

Rantanen T, Masaki K, Foley D, Izmirlian G, White L, Guralnik JM (1998). Gripstrength changes over 27 yr in Japanese-American men. J Appl Physiol

85:20472053.Robles-De-La-Torre G, Hayward V (2001). Force can overcome object geometry

in the perception of shape through active touch.Nature412 :445448.Shiffler RE (1988). Maximum z scores and outliers. Am Stat42:7980.Shim JK, Lay BS, Zatsiorsky VM, Latash ML (2004). Age-related changes in

finger coordination in static prehension tests. J Appl Physiol97:213224.Shinohara M, Latash ML, Zatsiorsky VM (2003a). Age effects on force produced

by intrinsic and extrinsic hand muscles and finger interaction duringMVC tasks. J Appl Physiol95 :13611369.

Shinohara M, Li S, Kang N, Zatsiorsky VM, Latash ML (2003b). Effects of age andgender on finger coordination in MVC and submaximal force-matching tasks.J Appl Physiol94 :259270.

Slifkin AB, Newell KM (1999). Noise, information transmission, and forcevariability.J Exp Psych Hum Percept Perform 25:837851.

Smits-Engelsman BC, Gielen SC, Duysens J (2003). Effects of aging on motoroutput variability in uni- and bi-manual isometric tasks. 33rd Annual Meetingof the Society of Neuroscience; December 2003; New Orleans, LA;pp. 392393.

Sosnoff JJ, Newell KM (2006). Visual intermittency and variability in isometricforce output. J Gerontol B Psychol Sci Soc Sci61:117124.

Sperling L (1980). Evaluation of upper extremity function in 70 year old menand women. Scand J Rehabil Med12:139144.

Spirduso WW, Francis K, Eakin T, Stanford C (2005a). Quantification of manualforce control and tremor. J Mot Behav37:197210.

Spirduso WW, Francis K, MacRae P (2005b). Physical dimensions of aging.2nd ed. Champaign, IL: Human Kinetics.

Thomas JR, Nelson JK, Church G (1991). A developmental analysis of genderdifferences in health related physical fitness. Pediatr Exerc Sci3:2842.

Tracy BL, Enoka RM (2002). Older adults are less steady during submaximalisometric contractions with knee extensor muscles. J Appl Physiol92:10041012.

Vaillancourt DE, Larsson L, Newell KM (2003). Effects of aging on forcevariability, single motor unit discharge patterns, and the structure of 10, 20,

and 40 Hz EMG activity. Neurobiol Aging 24:2535.Varadhan SK, Zatsiorsky VM, Latash ML (2010). Variance components in discreteforce production tasks. Exp Brain Res 205 :335349.

Visser B, de Looze MP, Veeger DH, Douwes M, Groenesteijn L, de Korte E,van Dieen JH (2003). The effects of precision demands during a low intensitypinching task on muscle activation and load sharing of the fingers.J Electromyogr Kinesiol13:149157.



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