Performed the experiments: JAM. Provided the equipment for measurement: JR. In the scientific literature, there is much evidence of a relationship between age and dexterity, where increased age is related to slower, less nimble and less smooth, less coordinated and less controlled performances. While some suggest that the relationship is a direct consequence of reduced muscle strength associated to increased age, there is a lack of research that has systematically investigated the relationships between age, strength and hand dexterity.
Therefore, the aim of this study was to examine the associations between age, grip strength and dexterity. We performed three phases of analyses. Firstly, we evaluated the simple relationships between pairs of variables; replicating the existing literature; and found significant relationships of increased age and reduced strength; increased age and reduced dexterity, and; reduced strength and reduced dexterity.
Secondly, we used standard Multiple Regression MR models to determine which of the age and strength factors accounted for the greater variance in dexterity. The results showed that both age and strength made significant contributions to the data variance, but that age explained more of the variance in steadiness and line tracking dexterity, whereas strength explained more of the variance in aiming and tapping dexterity.
In a third phase of analysis, we used MR analyses to show an interaction between age and strength on steadiness hand dexterity. Simple Slopes post-hoc analyses showed that the interaction was explained by the middle to older aged adults showing a relationship between reduced strength and reduced hand steadiness, whereas younger aged adults showed no relationship between strength and steadiness hand dexterity. The results are discussed in terms of how age and grip strength predict different types of hand dexterity in adults.
The hand is the most active and interactive part of the upper extremity. Hand dexterity is a term used to explain a range of different hand abilities and performances. These include reaction time; hand preference; wrist flexion speed; finger tapping speed; aiming; hand stability and arm stability e.
From these, four main factors are considered as the most characteristic and reliable for the evaluation of hand dexterity.
These include: i steadiness; ii tracking; iii aiming where typically the participant points to a target object , and iv tapping where the participant taps as fast as possible for a set time period [ 1 ]; [ 2 ]; [ 3 ]; [ 4 ]; [ 5 ]. The relationship between increased age and reduced hand dexterity has been widely reported in both the clinical and scientific literature.
Participants reached to grasp either a small cylinder using a precision grip or a large cylinder using a whole hand prehension. The actions performed by the two groups were similarly coordinated with similar times to peak for wrist velocity and acceleration from movement initiation i.
However, the older aged participants made significantly slower movements than the younger aged adults, replicating previous findings e. Although movement speed can be encapsulated within the term of hand dexterity, it is worth noting that slower movements with increased age may not necessarily correspond to a reduced performance for the other dexterity factors e. This point will be investigated in the present study. Despite numerous studies demonstrating a significant relationship between increased age and reduced hand dexterity, few studies have attempted to investigate the causes of the relationship.
Instead, a common explanation is provided in the discussion of these papers stating that the relationship between increased age and reduced hand dexterity is likely caused by a decline in musculoskeletal strength and mass see for example [ 12 ]; [ 13 ]; [ 14 ]; [ 15 ]; [ 16 ]; [ 17 ]; [ 18 ].
More precise investigations of hand strength have also demonstrated diminished strength with increased age e. Furthermore, changes in muscle mass with increased age has been linked to changes in peripheral and central nerve conduction [ 32 ]; [ 33 ]; [ 34 ] , proprioception [ 35 ] and changes in the human motor unit that relate to a degeneration of the nervous system [ 23 ]; [ 36 ] ; all of which are likely to impact hand dexterity.
Given the overwhelming evidence for relationships between age and hand dexterity, and between age and grip strength, it is perhaps surprising that there are very few studies that have investigated the relationships between age, grip strength and hand dexterity together in one study.
Instead, the few studies considering the three factors in a single study have investigated differences in these factors for different age groups of participants.
For example, Marmon et al. The results showed significant differences between the young and older age groups for the measures of index finger abduction, precision pinch and handgrip strengths, and further for the measures of hand dexterity. A further analysis showed evidence of significant associations among similar tests i. As a final multiple regression analysis showed that the time to complete two functional measures, the Grooved Pegboard and the game Operation were significantly predicted by index finger and grip strength or by pinch steadiness, index finger steadiness and grip strength respectively.
The aim of the current study was to extend these findings and investigate, using regression analyses, the relationships and interactions between age, grip strength and hand dexterity in adults.
We hypothesised to replicate previous research by showing negative relations between age and strength, and age and hand dexterity, with increased age being related to reduced strength and hand dexterity. We also hypothesised a positive relationship between strength and dexterity so that reduced strength was related to reduced hand dexterity. In a second phase of analyses, we then sought to extend the research findings by determining the variance of age and strength on the different components of dexterity i.
In a final phase of analyses, we explored interactions in age and strength on hand dexterity. All participants gave written informed consent to participate in the study, and the study was approved by the School of Sport and Exercise Sciences, University of Birmingham ethical committee in accordance with the ethical standards established by the Declaration of Helsinki.
Age 2 normal manual dexterity
All participants were recruited from the city of Birmingham UK following advertising the project at local community social groups and by giving short presentations about the project. Prior to giving an invitation to participate in the study, potential participants were pre-screened via an informal verbal discussion to determine eligibility. This information was collected using a purpose written self-report health questionnaire to assess for arthritis, and an informal verbal interview, all performed immediately prior to the testing sessions.
Any participants not meeting the criteria were not included in the study. For the main study, we assessed hand dominance Edinburgh handedness inventory: [ 38 ] and measured grip strength for both hands and dexterity for the dominant hand only. To measure grip strength we used a handgrip dynamometer Takei Scientific Instruments, Japan that has been shown to be an easy, fast and reliable method [ 39 ].
Fine motor skill
Participants were positioned sitting upright, with their elbows by their left and right sides, and flexed to right angles. A neutral wrist position held the dynamometer in their hand to be tested. The handle of the dynamometer was adjusted so that the base of the dynamometer was positioned with the rest on first metacarpal heel of palm , and the handle rested on the middle of the four fingers prior to testing.
HG Gundam AGE-2 Normal Review
The results were recorded as kilograms taken from the digital display of the dynamometer to the nearest 0. The digital display of the dynamometer displayed the maximum strength within a trial and the value was reset to zero before each subsequent measurement. The test is a standardised diagnostic tool used to provide valid and reliable assessments of hand dexterity see [ 43 ]; [ 44 ]; [ 45 ].
The VTS part of the test consists of a main computer with test interface management software and the MLS part consists of a peripheral panel containing a variety of different tests. Test-retest reliability has been reported for the MLS to range from.
Aging movement control
From the MLS tests, we used measures of steadiness, line tracking, aiming and tapping explained in the procedure section ; thus measuring the different components most characteristic for the evaluation of hand dexterity performance [ 1 ]; [ 2 ]; [ 3 ]; [ 4 ]; [ 5 ].
The MLS was placed on a wooden testing table, and participants sat on a stable wooden chair with back support in a normal sitting posture with slightly bent forearms. Participants were positioned at the mid-point of the table, perpendicular to the MLS and throughout the tests were instructed not to make contact with the wooden table or MLS i.
Participants took part in one session that lasted approximately ninety minutes. At the beginning of the session, after providing informed consent, participants were given the set of questionnaires that were used for the inclusion criteria. If a participant was not compatible with the inclusion criteria, they were not included in the study.
Following the questionnaires, and confirmation of their inclusion, participants performed the grip dynamometry assessment.
The participant squeezed the dynamometer with maximum effort for at least 5 seconds. Handgrip strength was tested three times with a minimum of 60 seconds rest was provided for recovery between each attempt. Maximum grip strength was recorded as the highest value of three trials. Note that the maximum value was used rather than the mean of three trials allowing for a measure that was independent of fatigue, which may have been possible in some of the participants.
Before commencement of the selected MLS tests, each test was verbally explained and demonstrated to the participant with a brief period provided for the participant to familiarise themselves with each test. The same order of tests was used for all participants as the software was unable to randomise the order of the tests.
Age and Grip Strength Predict Hand Dexterity in Adults
At the end of each test sequence, a break was provided. In the fixed sequence of tests, the first MLS test was the steadiness test. This involved the participant to vertically insert a pen stylus 2mm diameter into a pre-assigned hole 5. If the participant touched the sides they simply had to correct and position the stylus in the centre of the hole and continue until the end of the 32 seconds period. Measurements recorded by the software were the number of times the stylus came into contact with the sides or the bottom of the hole and the total duration of the contact time.
The second test was line tracking. This involved the insertion of the pen stylus into a grooved track and tracing the pen stylus through the track without touching the sides or the bottom. The test was undertaken at a self-selected pace. If the sides were touched, participants had to correct the position of the pen stylus and continue along the grooved track until the end. Measurements recorded were the number of times the stylus touched the side or bottom, the total duration of any touches and the total duration of the tracking.
The third test was the aiming test.
This involved the participant touching 20 brass disks 5mm diameter that were arranged in a row with the pen stylus. The distance between each disk was 4mm. The participant was instructed to tap one circle in the row after the other using the pen stylus, moving from right to the left across the disks. Measurements recorded were the number of correct taps, the number of incorrect taps, the total duration of any incorrect tap and the total duration to complete.
Advice and Expertise
The final task was tapping. This involved the participant tapping a square plate 40 mm 2 with the pen stylus as many times as within 32 seconds. The measurement recorded was the total number of taps. The VTS software recorded all measurements. Each dependent variable consisted of a composite performance score calculated using the Fleishman-factor of weighted variables from each measure e.
Fine Motor Development Checklist
The data analysis was undertaken in three phases. In the first phase, we report the simple relationships between two of the variables using simple regression analysis; between age and strength; age and each dependent measure of the MLS; and strength and each dependent measure of the MLS. The aims of these first analyses were to replicate the existing findings in the literature. In the second phase of analysis, the three variables were compared together using standard multiple regression.
In a third phase, we modified the variables to allow analyses of interactions. The independent variables of age and grip strength were mean centred to provide numerical stability see recommendations by Cohen and Cohen [ 47 ]; and Aitken and West [ 48 ]. No outliers among the cases were found. Then a standard MR was used to analyse the predictive variance between the independent variables of age and strength, and each dependent dexterity measure.
Where both independent variables had a significant contribution to the dependent variable, a further standard MR analysis was undertaken using the mean centred data and the mean centred cross product of age and strength to test for an interaction see [ 47 ]. In addition, post hoc Simple Slopes Technique analyses were used to further investigate the interaction see [ 47 ]; [ 48 ].
This was done to determine specific values of centred age, that were one standard deviation below the sample mean, the mean, and one standard deviation above the mean; in this instance to represent low aged, mean aged and high aged adults, respectively, and the same to represent low strength, mean strength and high strength adults, respectively.
As hypothesised, this showed that increased age was related to decreased strength, with the linear best fit showing a decline of 0. There were also significant simple relationships between age and each dependent measure of the MLS see Fig.