Age and Gender Stratified Adult Myometric Reference Values of Isometric Intrinsic Hand Strength

Abstract

Study Design:

Descriptive Normative

Introduction:

Intrinsic hand strength can be impacted by hand arthritis, peripheral nerve injuries, and Spinal Cord Injuries. Grip dynamometry does not isolate intrinsic strength and manual muscle testing is not sensitive to change in grades 4 and 5. The Rotterdam Intrinsic Hand Myometer (RIHM) is a reliable and valid test of intrinsic hand strength however, no adult normative data is available.

Purpose of the Study:

1) Describe age and gender stratified intrinsic hand strength norms in persons 21 years + and 2) Determine if factors known to predict grip dynamometry also predict measures of intrinsic hand strength.

Methods:

Three trials of 5 measures of maximal isometric intrinsic strength were performed bilaterally by 607 ’healthy-handed’ adult males and females. Average strength values were stratified by age and gender. Data were analyzed to determine the influence of demographic and anthropometric variables on intrinsic strength.

Results:

Intrinsic strength generally followed age and gender trends similar to grip dynamometry. Age, gender, body Mass Index (BMI), and the interaction between gender and BMI were predictors of intrinsic strength whereas, in most cases, the hand being tested did not predict intrinsic strength.

Discussion:

With the addition of these findings, age and gender-stratified hand intrinsic strength norms now span from age 4 through late adulthood. Many factors known to predict grip dynamometry also predict intrinsic myometry. Additional research is needed to evaluate the impact of vocational and avocational demands on intrinsic strength.

Conclusions:

These norms can be referenced to evaluate and plan hand therapy and surgical interventions for intrinsic weakness.

Introduction

The hand plays a vital role in human functioning. Adequate hand strength influences performance in daily activities, recreational, and vocational pursuits¹. Many have studied the relationships between diminished gross hand strength and function as well as the predictive nature of hand strength on functional independence^2-4. Additional studies have also demonstrated that hand strength testing is a useful assessment of disease staging and rehabilitation progression⁵.

Until more recently, dynamometric measures of hand strength have not been specific to isolated muscles of the hand⁶. Grip dynamometry⁷, a reliable and conventional measure of hand strength, is a gross indicator of combined extrinsic and intrinsic hand strength and not directly responsive to change in the strength of isolated hand intrinsics⁸. A more selective measure of hand strength is manual muscle testing (MMT)⁹ yet it is not sensitive to change unless profound weakness is present⁸. ”Dynamometry” or “myometry” affords clinicians and researchers a more responsive option for strength testing when strength, as per MMT, is grade 4 or higher⁸. The terms “dynamometry” and “myometry” are used interchangeably and, for the purpose of this study, we will be using the term “myometry”.

Numerous populations who are often seen by hand surgeons and therapists experience intrinsic hand muscle weakness. These populations include, but aren’t limited to those with median nerve¹⁰, ulnar nerve¹¹, and Brachial Plexus injuries¹²; stroke¹³; leprosy¹⁴; Charcot Marie Tooth Disease¹⁵; spinal cord injuries¹⁶; and thumb carpometacarpal osteoarthritis^17,18. Measurement tools are necessary to selectively quantify and be sensitive to change in the strength of these muscles in these populations.

One such tool is the Rotterdam Intrinsic Hand Myometer (RIHM). The RIHM^™ (Med.Engineers, Rotterdam, Netherlands) is a digital strain gauge designed to test the maximum strength of five isolated intrinsic hand muscles (see Figure 1) and is described to have excellent accuracy^19,20 and acceptable criterion validity with MMT (r≥.53, p<.05). Among healthy adults, inter-rater and intra-rater reliability are excellent (ICC ≥0.81 and ICC≥.92 respectively) ^19,20. Another strength of the tool is that there are already age and gender stratified normative (i.e., reference) values in children and adolescents aged 4-20²². Age and gender stratification of this data is imperative given that these factors are known to impact gross hand strength²³ (Mathiowetz et al., 1985). Only one other study²⁴ has reported on adult norms for 3 measures of intrinsic strength via use of another myometer however it was limited by a sample of 31 participants and it did not stratify values according to hand, age or gender.

Fig. 1.

Rotterdam intrinsic hand myometer.

Establishing intrinsic reference values stratified by age and gender will allow therapist and surgeon researchers and clinicians to 1) compare clients’ intrinsic strength to equals with uninjured hands for intervention planning and goal-setting purposes and 2) avoid the confounding effect of age and gender on strength when comparing intrinsic hand strength of those with and without clinical conditions suspected to directly influence intrinsic hand strength.

Purposes of the Study

The primary purpose of this study was to expand upon earlier descriptive research²² by stratifying intrinsic muscle strength according to age and gender for persons aged 21+. In doing so, hand surgeons and therapists will gain an understanding of the extent to which intrinsic strength of the healthy hand changes across the lifespan and how it differs by gender. A secondary purpose was to explore if age, gender, hand pain, hand dominance, hand (right versus left), or BMI are predictors of 5 measures of intrinsic hand strength among those aged 21+. These relationships were explored because these are variables previously demonstrated to influence gross grasp strength^{25, 23} and to test our decision to age and gender-stratify.

Methods

Design.

Descriptive normative design.

Participants.

Male and Female participants, aged 21+ years, were recruited via convenience sampling at a Midwestern state fair, university campus, and senior and assistive living centers between 2014-2017. Eligible participants were free of CNS conditions affecting upper limbs, known median or ulnar nerve damage, rheumatological or cardiac conditions, deformity of tested digits, pain exacerbated by testing, and the inability to follow standardized procedures. Among persons aged 50+, those with self-reported hand osteoarthritis and age-related musculoskeletal disorders were included so long as the pain associated with such precluded them from testing. In those instances where ulnar or median nerve injury was reported, the strength of only the uninvolved digits or contralateral side was tested. Following screening, written informed consent was received prior to the initiation of data collection.

Procedures.

The study myometers were calibrated on an annual basis immediately prior to the initiation of data collection as per manufacturer specifications²⁶. A total of 10 evaluators gathered participant data across a 3 year span. Nine of the evaluators were graduate occupational therapy research students and the 10^th was the principal investigator, an occupational therapist with over 15 years of experience and Certified Hand Therapist (CHT) credentialing. The decision to include students is supported by the findings of McGee¹⁹ who reports high agreement between novice student raters and that of an experienced occupational therapist when using the RIHM and testing procedures identical to those used for this study to test the hand strength in healthy-handed adults. A manualized protocol²⁷ was followed and all graduate students received 2.5 hours of training by the principal investigator and were expected to demonstrate service competency prior to evaluating. Assessment fidelity was monitored by the principal investigator at 50% of all evaluation sessions. Following screening, participants’ hand dominance (i.e., hand used for writing), height, and weight were ascertained through self-report. Self-reported ‘writing hand^28, height and weight²⁹ are all stated to be in high agreement with associated observational measures.

Isometric strength testing was performed with the participant seated and the elbow of the upper limb resting on a tabletop surface. The postures of the forearm, wrist and the digit being tested were standardized so as to best control for the effects of undesired intrinsic and extrinsic muscles. Although the procedures were standardized to isolate motions which areproduced by hand intrinsics, some tests might not be specific to an individual muscle but rather might be testing a pair or group. For this reason, we will be referring to these tests in terms of the motions rather than actual muscles presumed to produce such movements. These motions, and the presumed muscles producing such, included Index Finger Abduction (First Dorsal Interosseous), Index Finger Metacarpophalangeal Flexion (First Dorsal Interosseous/Lumbrical), Small Finger Abduction (Abductor Digiti Minimi), Thumb Metacarpophalangeal Flexion (Flexor Pollicis Brevis), and Thumb Carpometacarpal Palmar Abduction (Abductor Pollicis Brevis). See figures 2-6.

Fig. 2.

Index finger metacarpophalangeal abduction.

Fig. 6.

Thumb carpometacarpal palmar abduction.

Following 1 practice trial, 3 trials of the 5 aforementioned measures were taken bilaterally. Thirty seconds of rest were offered between trials. The hand and the sequence of movements tested were randomized through use of the Qualtrics data management system so as to control for any order effects. The output of each trial was recorded in newtons (N) and manually entered into the Qualtrics system. The time commitment, per participant, was approximately 20-25 minutes.

Analytical Methods.

Statistical analyses were performed via use of Statistical Package of the Social Sciences (SPSS) version 22 and SAS version 9.3. The qualities of the sample (e.g., gender, hand dominance, ethnicity, and race) were characterized via use of descriptive statistics. The first purpose was addressed through use of summary statistics, and tests of skewness/kurtosis³⁰. After calculating the mean of the three trials per measure, hand strength data was stratified according to gender, hand dominance, and by decade from ages 21-59, by 15 year increments for the 60-74 and 75-89 year old strata, and was grouped by gender and hand dominance for all of those 90+ years of age. This was done in a manner consistent with that of normative grip strength values presented in The NIH ToolBox³¹ and by Mathiowetz et al.²³. Tukey’s Fences Test³² was used to test the effect of outliers on the mean strength measurements. The constant, (k), was chosen to be a conservative “3”. After removing those values that fell within the upper and lower 5th percentiles, the “trimmed mean” strength value was compared to the 95th percentile CI of the actual mean to determine the effect of outlier removal. If trimmed means fell within the 95% CI of the sample means, the removal of outliers was deemed prudent.

The second purpose was addressed via use of backward stepwise mixed effects linear modeling with P_removal = 0.1 and P_entry = 0.05. SAS (Proc Mixed) was used to estimate the effect of and interactions between factors known to predict gross grasp strength (e.g., age, gender, hand, handedness, and body mass index) on each measure of intrinsic using a mixed-effects linear model with hands as repeated factor and subjects as random effect to incorporate the correlation between repeated measurements from each subject. Body Mass Index BMI was calculated [(mass (kg)/height (m)) ²] using the participants self-reported height and weight. The influence of participants’ avocational and vocational backgrounds was not considered for feasibility purposes given the already lengthy survey and measurement procedures. Regression coefficients, standardized regression coefficients, and the coefficient of determination (R²) were determined for each regression model.

Results

A total of 629 people were recruited for the study. Of the 629 recruited, 22 were determined to be ineligible. Of those excluded, 9 had rheumatoid arthritis, 5 presented with a history of stroke, 3 had Parkinson’s disease, 1 had already participated, 1 presented with radial-forearm deficiencies bilaterally, 1 presented with congenital polydactyly with reconstructions bilaterally, 1 participant was unable to motor plan and follow commands, and 1 presented with gout in bilateral hands.

In total, data from 607 participants were analyzed (257 males and 350 females). The average age of participants’ was 54.2 (20.1) with a minimum age of 21 and maximum age of 103 years. Additional characteristics of these participants are described in Table 1, and the five mean strength measurements according to age, gender, and hand dominance are outlined in Tables 2-5 (Graphically represented in online Appendix in Figures 7-11).

Table 1.

Demographic characteristics of Participants (N=607)

Characteristics		n(%)
Gender
	Male	257(42.3)
	Female	350(57.7)
Hand Dominance
	Right	547(90.1)
	Left	60(8.9)
Ethnicity
	Hispanic or Latino	14(2.3)
	Non-Hispanic or Latino	593(97.7)
Race
	White	560(92.3)
	Black or African American	6(1.0)
	Asian	19(3.1)
	American Indian or Alaska Native	4(0.7)
	Multiracial	12(2.0)
	Other	6(1.0)

Table 2.

Intrinsic Hand Muscle Measurements of Fingers in Males.^a

			Dominant Hand						Non-Dominant Hand
Age (yr.)	Muscle	n	Min	Max	Mean	SE	SD	n	Min	Max	Mean	SE	SD
21-29	IF MPA	36.0	50.7	126.1	74.3	3.1	18.4	36.0	43.4	114.7	71.6	2.9	17.1
	IF MPF	36.0	44.4	132.2	86.0	3.9	23.3	36.0	47.3	123.2	82.0	3.5	21.2
	SF MPA	36.0	25.2	82.4	47.9	2.2	13.5	36.0	22.8	75.4	46.7	1.8	11.1
30-39	IF MPA	29.0	25.3	143.3	72.8	4.6	25.0	29.0	19.0	110.8	66.1	3.6	19.6
	IF MPF	29.0	45.5	133.4	81.0	4.0	21.3	29.0	45.3	134.6	79.1	4.3	23.2
	SF MPA	29.0	7.6	89.1	50.2	3.4	18.5	29.0	21.3	80.5	47.1	2.5	13.6
40-49	IF MPA	28.0	28.8	108.5	73.7	3.7	19.5	28.0	35.1	99.7	69.3	3.6	19.3
	IF MPF	28.0	40.9	118.3	80.3	3.5	18.4	28.0	40.4	115.8	77.7	4.0	21.2
	SF MPA	28.0	22.0	88.3	46.1	2.7	14.3	28.0	16.9	80.8	45.2	2.9	15.4
50-59	IF MPA	58.0	25.9	108.7	63.2	2.1	15.8	57.0	32.8	103.8	62.5	2.2	16.3
	IF MPF	57.0	40.5	122.3	67.3	2.2	16.4	56.0	37.8	98.4	65.9	2.0	15.0
	SF MPA	58.0	18.5	77.9	42.5	1.5	11.3	57.0	18.3	66.9	43.2	1.5	11.3
60-74	IF MPA	72.0	24.3	104.2	58.6	1.9	16.3	71.0	27.0	91.8	56.7	1.8	15.0
	IF MPF	72.0	22.4	131.8	67.2	2.2	18.6	71.0	33.5	122.1	66.4	1.9	16.4
	SF MPA	72.0	14.9	66.3	40.4	1.3	10.8	71.0	16.6	76.9	39.2	1.4	11.9
75-89	IF MPA	25.0	24.7	77.7	51.4	3.0	15.0	25.0	24.5	79.5	52.2	3.1	15.3
	IF MPF	25.0	39.5	88.3	63.9	2.7	13.5	24.0	36.4	103.1	65.4	3.3	16.1
	SF MPA	25.0	17.3	53.8	36.7	1.8	8.9	24.0	23.1	55.5	37.7	2.1	10.2
90+	IF MPA	8.0	24.1	51.9	36.8	2.9	8.2	8.0	24.2	50.7	37.3	3.5	9.8
	IF MPF	8.0	26.5	63.9	48.0	3.7	10.4	8.0	31.5	55.2	43.3	3.1	8.8
	SF MPA	7.0	25.6	37.8	32.3	1.6	4.2	8.0	18.6	45.2	29.9	2.8	8.0
All	IF MPA	256.0	24.1	143.3	63.7	1.2	19.7	254.0	19.0	114.7	61.5	1.1	18.1
	IF MPF	255.0	22.4	133.4	72.0	1.3	20.5	252.0	31.5	134.6	70.4	1.2	19.7
	SF MPA	255.0	7.6	89.1	43.1	0.8	13.1	253.0	16.6	80.8	42.3	0.8	12.6

^aNote: Average of three trials are reported. Values are reported in Newtons. IF = Index Finger; SF = Small Finger; MPA = Metacarpophalangeal Abduction; MPF = Metacarpophalangeal Flexion.

Table 5.

Intrinsic Hand Muscle Measurements of Thumbs in Females.^a

			Dominant Hand						Non-Dominant Hand
Age (yr.)	Muscle	n	Min	Max	Mean	SE	SD	n	Min	Max	Mean	SE	SD
21-29	Thumb PA	55.0	26.2	85.9	45.2	1.6	11.9	56.0	21.0	89.8	44.4	1.9	14.5
	Thumb MPF	55.0	27.0	91.1	64.3	2.0	15.1	54.0	22.5	95.6	65.4	2.2	15.9
30-39	Thumb PA	43.0	23.9	90.3	52.6	2.4	15.5	41.0	22.6	86.4	53.8	2.3	14.8
	Thumb MPF	42.0	44.9	100.3	72.0	2.2	14.3	41.0	41.7	96.7	70.7	2.0	12.7
40-49	Thumb PA	42.0	30.8	100.7	50.2	2.2	14.1	42.0	23.1	91.8	49.8	2.2	14.5
	Thumb MPF	42.0	29.3	119.7	68.4	3.2	20.5	42.0	17.4	106.3	65.4	3.0	19.2
50-59	Thumb PA	67.0	26.7	86.6	45.6	1.4	11.1	67.0	21.9	96.0	45.2	1.5	12.1
	Thumb MPF	67.0	22.6	107.7	62.8	2.0	16.0	67.0	30.6	109.0	62.4	1.9	15.4
60-74	Thumb PA	74.0	17.2	87.6	44.7	1.6	13.6	72.0	24.1	79.7	42.8	1.4	12.3
	Thumb MPF	72.0	25.8	98.2	55.9	2.0	16.9	69.0	29.2	98.7	55.4	1.7	13.8
75-89	Thumb PA	42.0	16.9	78.5	37.7	2.2	14.0	42.0	16.6	69.4	35.0	2.2	14.0
	Thumb MPF	41.0	25.9	87.6	53.4	2.4	15.3	41.0	17.7	80.7	49.5	2.2	13.9
90+	Thumb PA	18.0	12.0	37.0	22.9	1.4	5.8	18.0	11.5	32.3	20.9	1.2	4.9
	Thumb MPF	17.0	22.5	65.7	41.4	2.6	10.6	17.0	16.4	61.9	37.5	2.8	11.7
All	Thumb PA	341.0	12.0	100.7	44.6	0.8	14.4	338.0	11.5	96.0	43.6	0.8	15.0
	Thumb MPF	336.0	22.5	119.7	61.2	1.0	17.7	331.0	16.4	109.0	60.0	0.9	17.0

^aNote: Average of three trials are reported. Values are reported in Newtons. PA = Palmar Abduction; MPF =Metacarpophalangeal Flexion.

In some instances only selected measures of intrinsic strength were taken. All median innervated measurements (i.e., thumb MP flexion, index finger MP flexion, and thumb CMC palmar abduction) were excluded in five participants who underwent carpal tunnel release surgery or had a diagnosis of carpal tunnel syndrome bilaterally. In other instances, only unilateral measurements were excluded. This occurred in one person who had a right carpal tunnel release, one with combined left ulnar (i.e., index finger abduction, index finger MP flexion, and small finger abduction)/median nerve injuries, one with right thumb surgery (i.e., both thumb movements), one participant with left hand C6-C7 radiculopathy (i.e., all measurements), and one participant with Dupuytren’s contracture presenting along the 5th ray (i.e., small finger abduction).

After screening for outliers, 6 outlying mean strength measurements were removed. This included the removal of 3 dominant hand index finger MP flexion measurements, 1 non-dominant index finger MP flexion measurement, 1 dominant small finger MP abduction measurement, and 1 non dominant thumb MP flexion measurement. All affected “trimmed” strata means fell within the 95% CI of the original strata means and were thus determined to be prudent. Following the removal of these outliers, participants’ mean strength values were determined to be normally distributed. Skewness and kurtosis statistics were all within the acceptable skewness range of −2.1 to +2.1 and kurtosis range of −7.1 to +7.1 for all strata³³.

Due to 20 participants not reporting their height or weight, these missing values were predicted using a multiple imputation analysis³⁴. Five iterations of the imputations were run with gender, height and weight being used as predictors of the missing height or weight values. An average of the 5 imputed values was then taken.

Intrinsic hand strength followed a declining trend with age; generally peaking in the 30s and 40s. Mean strength was greatest in thumb MP flexion and least in 5th digit MP abduction. Age, gender, BMI, and the combined effects of BMI and Gender (male) were significant predictors of all measures of intrinsic strength. The positive relationship between BMI and intrinsic strength was only noted in males. For example, in males, for every increase of BMI of .55, an increase of 1 newton of index finger MP strength would be expected (Table 8, Online Supplement). The interaction between BMI and Hand dominance was a predictor only for index finger MP abduction and flexion strength and hand (right/left) was not a predictor in any instance. When comparing the standardized regression coefficients, the interaction between gender and BMI appeared to have the largest effect on intrinsic hand strength whereas age appeared to have the smallest in all instances except for the two measures of index finger strength. In these two measures, hand dominance proved to be the smallest significant predictor. Overall, these models explained between 60 and 63% of the variance in intrinsic strength. See tables 6-10 (online supplement) for additional details on the regression analyses results.

Discussion

The purposes of this descriptive-normative study were to further establish normative values for intrinsic hand strength throughout the adult lifespan and to establish what, if any, demographic features predict intrinsic hand strength. Data were stratified according to age, gender, and hand dominance and predictors of intrinsic hand strength were evaluated via use of a mixed linear model analysis.

Participants.

Sample demographics were similar to that of the region where this study was conducted in the Midwestern United States³⁵ in terms of ethnicity, but was slightly more homogenous in terms of race (92% white vs. 85% white). The sample was also more female than is the general demographics of the region (58% vs. 50%). This came as no surprise given that it is well established that female participation in large scale epidemiological research is notably more prevalent. We were intentional in our efforts to select venues where the males were highly representative and even resorted to selectively recruiting only males in the less well represented strata when female numbers were high. Similar to the issue of gender, recruitment of younger adults was more challenging even when taking steps to find community settings where younger adults are highly representative. These findings, however, are not surprising considering that others have reported a similar phenomenon when conducting epidemiological research³⁶. Our decision to close the study to recruitment with these numbers is supported by the recommendations of Lutz³⁷, who described that 20-30 participants per strata are needed to sufficiently estimate sub-population (i.e., strata) means. Finally, the proportion of handedness was consistent with that which is described internationally (i.e., right dominance in 70-95% of persons) ³⁸.

Intrinsic Hand Strength.

Intrinsic hand strength appears to follow a pattern that is similar to that of grip strength norms; intrinsic hand strength declines with age. Kallen et al.³⁹ and Mathiowetz⁷ identify that gross grasp strength increases in young adults, but steadily declines beginning in the 4th decade of life. There were some instances where a decline was more notable in both genders beginning in the 30s (e.g., SF MP Abduction) and other times where it appeared that females’ intrinsic strength began declining a decade earlier (e.g., thumb palmar abduction and MP flexion). These trends could be explained by vocational or avocational factors that influence hand strength and change across the lifespan or differ by gender however this would require further exploration.

Because there is evidence to suggest there are larger declines in intrinsic muscle strength than in extrinsic muscle strength with aging⁴⁰, it might be inferred that these similar grip dynamometry trends might be functions of deteriorating intrinsic strength. These inferences are further supported by evidence that 50% of maximal grip force is explained by intrinsic muscle function⁴¹. Predictors for intrinsic muscle strength are similar to the predictors for grip dynamometry measurements with the exception of hand dominance. Hand strength decreases at a similar rate regardless of which hand is dominant. Age, BMI, and gender have previously been described to be significant independent predictors of hand grasp strength^42,43 however the findings of the present study suggest the effects of BMI on intrinsic hand strength presents differently in men than it does in women. This might be explained by the work of Janssen et al.⁴⁴, who described that male’s skeletal muscle accounted for nearly 40% of their weight whereas in women, only 30%. Males have significantly more skeletal muscle mass than females, and the differences are even greater in the upper extremity. Thus, as BMI increases, male’s skeletal muscle mass will account for nearly 10% more of their weight.

The final regression model for all strength measures explained between 60 and 63% of the strength variance. While these are strong explanatory models⁴⁵, between 40 and 37% of the variance in intrinsic strength is unexplained. It is challenging to forecast what additional factors may have led to better constructed models however it has been found in previous research that anthropometric variables, such as forearm circumference and length, and hand positively predict with grip strength^{46, 47}. Moreover, it could be speculated that the inclusion of vocational information may have contributed to stronger models however some have reported that the type of work, or vocational status, show weak to no associations with grip strength⁴⁶. Relatedly, avocational pursuits such as musical instrument play, knitting, or gaming may have contributed to the model but this data was not gathered given the already large burden on volunteers.

The decision to stratify according to age and gender is supported by the results of the linear modeling analyses and the decision to stratify by hand dominance was supported in 2 out of the 5 measurements. Although some literature would suggest that dominance has differing effects on right vs. left hand strength⁴⁷, the linear modeling analyses did not reveal there to be apparent interaction effect between the hand being tested and its dominance on intrinsic strength. These factors, coupled with the non-significance of the effect of hand being tested on intrinsic strength, support the decision to stratify by hand dominance. The data, however, were not stratified according to BMI given that it was not predictive of strength across genders.

Prior research has suggested that maximal hand strength values of greater than 2 SD below the norm are indicative of clinically relevant weakness⁴⁸ or sarcopenia⁴⁹. Interpreting these values accordingly might help to inform surgeons on when to prescribe rehabilitation versus intervene surgically for conditions such as carpal tunnel syndrome. The validation of this interpretation, however, requires further exploration. In contrast to this approach, it is common practice to compare the strength of the affected hand to that of the contralateral hand when evaluating impairment and for the purposes of goal-setting⁵⁰ however hand surgery and hand therapy patients often present with bilateral symptomology and, in these cases, reference values would be necessary. Examples of this might be measuring the effectiveness of tendon transfers in person with tetraplegia or the treatment of persons with leprosy, Guillain Barre, and Charcot Marie Tooth.

Conclusions

The Rotterdam Intrinsic Hand Myometer is known to be a reliable and valid instrument and, given the findings of this study now possesses normative data which spans from ages 4 through late adulthood. These reference values can inform evaluation findings, goal setting, treatment, and the success of intervention outcomes. As others have established the associations between grip strength, proximal upper limb strength^{3, 51}, and functional performance, the association between intrinsic strength and functional performance also requires exploration.

Limitations.

The convenience sampling strategy does predispose these findings to sampling biases and could limit generalizability to areas of the world with differing demographic compositions. Another limitation to this study was the use of subjective reporting of height, weight, and medical history. Self-reporting could lead to false BMI calculations and underreporting of the presence of medical conditions or related symptomatology however, the literature does support that self-reported height and weight are highly associated with actual values²⁹. Lastly, we did not gather vocational data and this could have been a factor which explained some of the unaccounted for variance in our regression models.

Future research might also include case-control study with age and gender matched persons with and without conditions of the hand. Psychometric testing in clinical populations such as 1st CMC osteoarthritis can also be conducted in future research. Given that this study did not evaluate for the influence of vocation or avocation on intrinsic hand strength, additional study of such is needed.

Fig. 3.

Index finger metacarpophalangeal flexion.

Fig. 4.

Small finger metacarpophalangeal abduction.

Fig. 5.

Thumb metacarpophalangeal flexion.

Table 3.

Intrinsic Hand Muscle Measurements of Thumbs in Males.^a

			Dominant Hand						Non-Dominant Hand
Age (yr.)	Muscle	n	Min	Max	Mean	SE	SD	n	Min	Max	Mean	SE	SD
21-29	Thumb PA	36.0	33.4	119.8	72.1	3.1	18.8	36.0	29.7	99.9	72.6	3.1	18.5
	Thumb MPF	36.0	59.5	155.0	97.1	3.6	21.4	36.0	49.1	139.0	92.0	3.4	20.5
30-39	Thumb PA	29.0	30.0	129.9	82.7	4.8	25.8	29.0	28.1	134.5	75.2	4.8	25.9
	Thumb MPF	29.0	49.1	148.5	103.0	5.3	28.5	29.0	43.6	144.9	95.6	4.8	25.9
40-49	Thumb PA	28.0	37.6	124.8	81.6	4.4	23.5	28.0	39.1	134.4	79.0	4.4	23.3
	Thumb MPF	28.0	55.9	176.3	100.8	5.3	28.2	28.0	62.8	189.1	99.4	5.0	26.3
50-59	Thumb PA	58.0	25.7	106.0	69.7	2.4	18.0	57.0	28.6	107.8	69.7	2.2	16.7
	Thumb MPF	58.0	28.9	171.0	86.0	3.5	26.6	56.0	42.2	176.0	87.8	3.0	22.2
60-74	Thumb PA	72.0	27.2	128.4	69.8	2.7	22.6	71.0	28.2	125.9	67.6	2.5	21.4
	Thumb MPF	72.0	37.5	169.3	87.6	3.2	27.6	71.0	30.2	136.0	86.0	3.0	25.0
75-89	Thumb PA	24.0	21.3	80.3	52.3	3.5	17.0	24.0	17.4	94.4	52.7	4.0	19.5
	Thumb MPF	25.0	37.6	119.2	73.4	4.2	21.0	24.0	33.2	114.1	78.6	4.5	22.1
90+	Thumb PA	8.0	11.1	61.5	30.4	5.1	14.5	8.0	17.3	60.8	36.3	5.3	15.0
	Thumb MPF	8.0	24.4	82.9	54.2	6.2	17.6	8.0	36.5	70.8	51.0	4.7	13.2
All	Thumb PA	255.0	11.1	129.9	70.0	1.5	23.3	253.0	17.3	134.5	68.5	1.4	22.1
	Thumb MPF	256.0	24.4	176.3	89.3	1.7	27.7	252.0	30.2	189.1	88.0	1.6	24.8

^aNote: Average of three trials are reported. Values are reported in Newtons. PA = Palmar Abduction; MPF =Metacarpophalangeal Flexion.

Table 4.

Intrinsic Hand Muscle Measurements of fingers in Females^a.

			Dominant Hand						Non-Dominant Hand
Age (yr.)	Muscle	n	Min	Max	Mean	SE	SD	n	Min	Max	Mean	SE	SD
21-29	IF MPA	55.0	15.2	79.3	46.4	1.8	13.5	56.0	14.8	72.5	44.4	1.7	13.0
	IF MPF	55.0	18.4	96.7	53.1	2.0	14.9	55.0	21.1	90.5	51.8	1.8	13.6
	SF MPA	55.0	10.8	47.3	28.4	1.3	9.6	56.0	9.4	44.3	28.1	1.1	8.1
30-39	IF MPA	44.0	27.6	72.8	50.0	1.5	10.1	42.0	30.8	68.4	47.4	1.5	10.0
	IF MPF	42.0	20.7	82.7	55.8	1.7	10.9	41.0	33.0	88.9	55.8	1.9	11.9
	SF MPA	44.0	13.5	54.5	30.7	1.3	8.6	42.0	15.7	49.7	29.3	1.1	7.1
40-49	IF MPA	43.0	16.0	76.8	49.3	2.1	13.8	42.0	8.5	73.4	48.3	2.3	14.8
	IF MPF	43.0	29.2	93.1	54.5	2.5	16.4	42.0	3.4	94.0	52.2	2.6	16.7
	SF MPA	43.0	4.5	54.5	28.6	1.3	8.3	42.0	5.5	43.0	27.5	1.3	8.7
50-59	IF MPA	67.0	23.2	63.5	42.6	1.2	9.6	67.0	23.0	65.3	43.8	1.2	9.8
	IF MPF	67.0	22.3	87.9	47.7	1.4	11.6	67.0	26.3	70.6	48.1	1.2	9.8
	SF MPA	66.0	13.3	45.8	25.2	0.8	6.6	65.0	15.8	42.0	25.8	0.6	5.1
60-74	IF MPA	73.0	14.6	63.3	39.7	1.3	11.4	72.0	18.4	69.7	38.7	1.2	10.0
	IF MPF	72.0	20.5	90.0	45.6	1.4	12.0	71.0	26.3	78.6	42.3	1.3	10.5
	SF MPA	74.0	8.7	41.8	24.6	0.8	6.9	73.0	12.2	44.0	25.8	0.8	6.9
75-89	IF MPA	44.0	17.5	73.3	38.5	1.7	11.5	44.0	15.8	70.0	38.8	1.6	10.7
	IF MPF	42.0	24.3	66.4	46.8	1.6	10.7	40.0	13.1	74.3	42.9	1.8	11.2
	SF MPA	43.0	11.8	39.4	24.6	0.9	6.0	44.0	9.9	44.5	24.6	1.2	8.0
90+	IF MPA	19.0	11.8	45.7	30.4	2.0	8.5	19.0	11.1	46.9	31.3	2.2	9.4
	IF MPF	19.0	19.6	67.9	39.6	2.6	11.2	18.0	23.4	57.4	38.2	1.8	7.7
	SF MPA	20.0	7.2	36.6	21.6	1.3	5.9	19.0	13.5	35.2	22.4	1.3	5.8
All	IF MPA	345.0	11.8	79.3	43.2	0.7	12.5	342.0	8.5	73.4	42.5	0.6	12.0
	IF MPF	340.0	18.4	131.4	49.7	0.8	14.1	334.0	3.4	94.0	47.8	0.7	13.0

^aNote: Average of three trials are reported. Values are reported in Newtons. IF = Index Finger; SF = Small Finger; MPA = Metacarpophalangeal Abduction; MPF = Metacarpophalangeal Flexion.

• Age and gender stratified norms are now available for five measures of intrinsic hand strength.

• These norms can be referenced to goal-set, evaluate and plan hand therapy and surgical interventions for intrinsic weakness.

• Age, gender, body Mass index, and the combined effects of male gender and BMI were predictors of intrinsic strength.