Voluntary handgrip strength (HGS) is significantly associated with other body muscles functioning (18,24), thus it is used as an indicator of overall body muscle strength (1,5,26). Handgrip strength is the most frequently used indicator of muscle function for clinical purposes (23) because it has been shown to be a strong indicator of functional status (12,15,23) and of nutritional status (12,23,31) and also has shown to be a promising undernutrition screening tool (9,21). Furthermore, HGS impairment is strongly associated with increased postoperative complications (23), lower short and long-term survival (15,23), longer hospital stay (22,23), and higher hospitalization rate (23). Low HGS is described as a predictor of disability (25) and frailty (29) for older adults and is used for frailty (10) and sarcopenia diagnoses (6).
Hand dynamometry offers numerous advantages over other nutritional, functional, and health status indicators as it is an inexpensive, easy-to-use, portable method. Moreover, HGS measurements are noninvasive, quick to perform, reliable, exhibiting low intraobserver and between-observer variability, and do not require specialized professionals (4).
There are several models of dynamometers available. The Jamar dynamometer is recommended by the American Society of Hand Therapists for HGS measurements (7) and it is frequently chosen as the standard criterion for interinstrument agreement studies. The studies that compared the agreement between Jamar and other models of dynamometers for HGS measurement in free-living subjects (11,19,20,27) and in undernourished institutionalized older adults (11) exhibited variability in the provided results. (3,11,19,20,27).
Compared with the Jamar, the MicroFET4 (Hoggan Scientific, LLC, Salt Lake City, UT, USA), Smedley's (Baseline, White Plains, NY, USA), Eisenhut (Eisenhut Instruments GmbH, Frittlingen, Germany), Sammons Preston Rolyan Bulb (Patterson Medical Holdings, Inc., Warrenville, IL, USA), Grippit (AB Detektor, Goteborg, Sweden), Rolyan (Smith & Nephew, Inc., Germantown, WI, USA), and DynEx (Fabrication Enterprises, Inc., White Plains, NY, USA) dynamometers have shown excellent measurement accuracy in the laboratory (r2 > 0.999), but in individuals, they have shown a variable error, depending on the tested devices and subject characteristics (3,11,19,20,27). Given these results, and because these differences are caused by identifiable factors, there is room for improvement of the characteristics that may allow to reduce HGS measurement errors. Thus, accuracy can be improved, with benefits for clinical and other settings.
The available dynamometers have variable resolutions, and the improvement of the resolution can allow to better document and discriminate muscle strength measurement. Differences in HGS values from 2.2 to 8.7 kgf and with large limits of agreement, previously found between the Jamar and other 4 dynamometers, Grippit, Smedley's, Eisenhut, and Sammons Preston Rolyan Bulb (15,23), led to the hypothesis that a dynamometer of smaller dimension, being lighter, and with different ergonomics, including 2 handles of different shapes, would improve HGS measurement, especially for low HGS readings. Although bigger dimension and heavy dynamometers may be appropriate for some individuals, handling them could be difficult for some population groups such as children, frail, sarcopenic, or undernourished subjects. Pediatric and frail subjects will have to apply more effort and strength to support the device than do others, thus increasing the odds of producing differential errors. Furthermore, lighter and smaller dynamometers are more portable and easier to be carried by measurers and handled by evaluated subjects in daily practice, such as in clinical settings.
Furthermore, in a study conducted among 314 inpatients, aged between 18 and 96 years, mean age 57.3 (SD: 18.7) years, a high proportion of participants were shown to exhibit zero or extremely low HGS values, measured with an Eisenhut dynamometer (21). When HGS data were summarized in percentiles by sex, age categories (<65 and ≥65 years), and nutritional risk, the 10th percentile was 0 kgf for all included women and for all the nutritionally at-risk men. These findings may suggest that this dynamometer is not appropriate for accurate readings of low HGS values.
Additionally, previous studies on hospitalized patients have shown lower HGS values than those obtained from healthy control subjects (13) and inferior to normative HGS data (18,22,25,26). The low resolution and high weight and dimensions of the available dynamometers may not provide reliable HGS readings among frail and undernourished subjects. Thus, a new dynamometer that could overcome these shortcomings was developed, the Bodygrip.
The purposes of this study were first to examine the measurement precision of the Bodygrip for HGS measurement evaluated in the laboratory, and second to examine the Bodygrip reliability for HGS measurement in free-living and hospitalized subjects. The ergonomic effect of using the Bodygrip with 2 different handles was also explored.
Experimental Approach to the Problem
In this study, the Bodygrip and Jamar reliability and agreement were evaluated in a sample of free-living and of inpatient volunteers on a cross-sectional study conducted between April and May 2014.
A convenience sample of free-living subjects was recruited among students and staff from University of Porto and relatives of the department staff. All participants were free from neuromuscular diseases, orthopedic dysfunction, deformity, or current injury of the nondominant upper limb that restrained correct performance of the HGS technique. Sex and age of each participant were recorded. This sample (n = 114) comprised 82 women and 32 men aged between 18 and 89 years (mean [SD] = 31  years).
The sample of inpatients was recruited from a university hospital in Porto. A consecutive sampling approach was used. From the daily list of patients admitted to cardiology, endocrinology, gastroenterology, internal medicine, orthopedics, and otolaryngology wards, those who met the inclusion criteria were invited to participate in the study. Patients were eligible if they were ≥65 years old, conscious, and cooperative. Only inpatients ≥65 year old were included because we sought for a high proportion of patients at undernutrition risk, which is more common among the older population (28). Patients incapable of performing the HGS technique, defined as an inability to understand verbal instructions or having a condition in which the patient could not perform the technique correctly, and subjects in isolation were excluded from the study. The sample of inpatients comprised 22 women and 28 men aged between 65 and 93 years (mean [SD] = 76  years).
The research was conducted according to the guidelines established by the Declaration of Helsinki and approved by the Ethics Committee of Hospital São João (sample of free-living subjects) and the Institutional Review Board and the Ethics Committee of Hospital Center of Porto (sample of inpatients). After explaining the study purpose, written informed consent was obtained from all study participants. The HGS measurement protocol was explained to each participant, and HGS was obtained for each participant under the same conditions.
Bodygrip Development and Precision Evaluation
The Bodygrip dynamometer was developed at System Integration and Process Automation Research Unit from the Institute of Science and Innovation in Mechanical and Industrial Engineering, Faculty of Engineering of University of Porto, patent process P300.3-PP2, request number: 108818, Septmber 14, 2015.
In this study, a curved handle was selected because the handle of the recommended dynamometer, the Jamar, is curved. Additionally, it was hypothesized that the curved handle that accompanied the shape of the fingers would better accommodate all fingers and could produce more reliable and reproducible HGS measurements, namely in frail and in undernourished subjects. The linear handle was used as a comparison basis to better understand whether ergonomic improvement would have impact on the measurement reliability. The present prototype has a parallelepiped shape with dimensions of 0.114 × 0.022 × 0.045 m and weighs 0.250 kg. The Jamar grip handle is an ergonomic surface of smooth type, whereas the surface of the prototype presents roughness avoiding handle rotation during tests. This material used increases the adhesion level while performing HGS measurement. In the Jamar, the measurement range is of 90 kgf, whereas the prototype offers ±100 kgf. Characteristics of the Bodygrip and Jamar dynamometers are presented in Table 1.
The measurement precision of Bodygrip and Jamar was tested in the laboratory, against a working standard load cell system (14) (Model LBS Miniature Compression Load Button, and its signal conditioning with a digital indicator, Model 9820, from Interface), for a force range between 0.0 and 113.0 kgf. Dynamometers' precision tested in the laboratory was excellent, Bodygrip: r2 = 0,9998 and Jamar: r2 = 0.9991.
Nondominant HGS was measured in kgf with a Jamar Plus + Hand dynamometer model (Sammons Preston, Bolingbrook, IL) and with the Bodygrip with each of the 2 handles. The handle of Jamar can be adjusted to different positions and, for this study, it was customized to offer a handling restriction similar to the Bodygrip body dimension. Handgrip strength was tested with the Jamar at the second position, and Bodygrip using the curved and the straight handles, randomly. Each individual performed 2 HGS measurements with the nondominant hand with the Jamar and Bodygrip using each handle, with an interval of 1 minute between the first and the second measurement and between each dynamometer test.
Handgrip strength was obtained in one session with subjects in a chair or on a bed, without arm rest. The nondominant hand was tested. Measurements were conducted with the shoulder of the tested extremity adducted and neutrally rotated, with the arm naturally rested by the side of the body. The elbow was flexed to an angle of 90°, and the forearm and wrist in neutral position (8) and therefore with the thumb up. Elbows were unsupported during HGS measurements. When measurements were obtained with participants in a chair, they were instructed to not move the trunk. When measurements were done in the bed, subjects were lying at approximately 30° in the bed with elbows unsupported. Participants were instructed to maintain the standardized position during the tests. If participants changed the position during tests, a new measurement was performed with the participant in the correct position (Figure 1). Participants were instructed to exert their maximum strength; however, no verbal encouragement was given.
Inpatients' sex, age, and clinical history were obtained from medical records, and the undernutrition risk was evaluated by Nutritional Risk Screening (16). All data including the HGS measurement was obtained by 2 registered nutritionists. To reduce the possibility of interviewers introducing bias in data gathering, the procedures were trained before beginning the study.
The Kolmogorov-Smirnov test was used to test the distribution of variables. Because of nonparametric distribution, continuous variables are reported as median and interquartile range (IQR) (30). For the free-living subjects, age was summarized using tertiles, according to the cutoffs of the sample distribution. These cutoffs were 20 and 24 years. The sample of inpatients was too small to conduct an analysis using tertiles. Consequently, 2 groups were created, using the inpatient sample's median value of 76 years. Categorical variables are reported as frequencies. Differences in maximum HGS values between nutritionally at-risk and not nutritionally at-risk inpatients were compared using the Mann-Whitney test.
Test-retest reliability was explored by determining the differences between the first and second HGS measurements for each individual and dynamometer, which were compared using the Wilcoxon test. The SEM, coefficient of variance (SD/mean), and effect size were also calculated. In addition, a single-measures 2-way random-effect model was used to estimate the intraclass correlation coefficients (ICCs) between first and second measurement obtained with each dynamometer.
Comparison between instruments comprised differences in HGS measurements between the 2 dynamometers, which were determined by subtracting the maximum value obtained with the Jamar from the maximum value obtained with the Bodygrip using each handle, and SEM was calculated. The effect size, coefficient of variance, and the ICCs for single measures, between maximum HGS obtained with the Jamar and with the Bodygrip (for each handle), were also determined. Test-retest and comparison analyses were performed for the total sample and also for the free-living and inpatient samples separately.
The visual agreement for maximum HGS values between the Jamar and the Bodygrip with each handle was evaluated with Bland and Altman plots (2), and limits of agreement were calculated. Differences in HGS measurements between both dynamometers were also studied according to sex, age, nutrition status, and the order of dynamometer application.
Results were considered significant when p ≤ 0.05. Statistical analyses were conducted using the Software Package for Social Sciences (SPSS) for Windows (version 21.0; SPSS, Inc., Chicago, IL, USA) and Microsoft Excel (version 2007; Microsoft, Redmond, WA, USA).
Descriptive data on HGS are presented in Table 2. For the free-living participants, HGS measured with the Jamar varied from 9.6 to 71.4 kgf, whereas for the inpatients, HGS ranged from 4.1 to 40.7 kgf.
Significant differences between first and second HGS measurements obtained with the Jamar and with the Bodygrip (using both handles) were found when analyzing all data together and for the free-living sample. These differences ranged from 0.4 (2.9) to 1.4 (3.9) kgf, p ≤ 0.007. Otherwise, for inpatient sample, no significant differences between first and second HGS measurements for both dynamometers were found. Values for those differences ranged from 0.1 (2.1) to 1.0 (4.4) kgf, p ≥ 0.092 (Table 2).
Also regarding test-retest reliability, analyses concerning the effect size revealed small differences between first and second HGS measurements obtained with the Bodygrip except with the linear handle for the free-living subjects, for whom this difference was medium. With the Jamar, differences for inpatients were small, but were medium for the free-living and total samples. Otherwise, the coefficients of variance ranged between −46.22 and 8.14%. The Jamar presents smaller coefficients of variance compared with those of Bodygrip. The coefficients of variance for the Bodygrip are smaller for the curve-shaped handle compared with the straight-shaped handle, except for the inpatient sample. Correlation between first and second measurement obtained with the Jamar and with the Bodygrip was excellent with ICCs varying from 0.93 to 0.98 (Table 3). The SEM for percentage differences between first and second HGS measurements was 0.3% for both Jamar and Bodygrip with straight and curved handles.
Association between maximum HGS values obtained with the Jamar and Bodygrip are presented in Figure 2 (0.86 ≤ r2 ≤ 0.91). Correlation between maximum HGS values (from each 2 sequential measurements) obtained with the Jamar and with the Bodygrip was excellent with ICCs varying from 0.93 to 0.95 (Table 3). Nevertheless, significant median differences between HGS obtained with the Jamar and with the Bodygrip ranging from 1.3 (4.9) to 2.1 (2.7) kgf were found, p ≤ 0.009. Differences between measurements obtained with the Jamar and Bodygrip are similar for both handles and smaller for the sample of free-living subjects (Table 3).
As shown also in Table 3, effect size analyses showed that difference between Jamar and Bodygrip using each of the 2 handles was small for the free-living participants, medium when data were computed for total sample, and large for the inpatient sample. The coefficients of variance ranged between 1.30 and 4.32%; for the inpatient sample were smaller for the Bodygrip with the straight handle (Table 3).
SEM for percentage differences between maximum HGS obtained with the Jamar and with the Bodygrip was equal to 0.4%, using both the straight and curved handles. When maximum HGS values obtained with the Jamar were compared with those gathered with the Bodygrip, mean differences of −0.5 (limits of agreement: −4.6; 3.5) kgf with the curved handle and of 1.0 (−7.7; 9.7) kgf with the straight handle were found for the healthy participants. For inpatients, mean differences and limits of agreement were −1.0 (−3.8; 1.9) kgf and 2.1 (−3.3; 7.5) kgf, respectively, for curved and straight handles (Figure 3).
According to Nutritional Risk Screening, 36% of inpatients were nutritionally at-risk. No significant differences in HGS between not nutritionally at-risk and nutritionally at-risk participants were found for measurements obtained with the Jamar, respectively, 19.3 (14.0) vs. 17.7 (11.6) kgf, p = 0.390, or with Bodygrip using the curved handle, 17.3 (14.6) vs. 17.5 (12.6) kgf, p = 0.960, or using the straight handle, 16.7 (14.1) vs. 18.0 (14.0) kgf, p = 0.984. The results were similar when the data were stratified by sex (data not shown).
The HGS differences between instruments were explored according to sex, age, and nutrition status. Median differences and IQR between HGS obtained with the Jamar and with the Bodygrip ranging from 0.8 (5.0) kgf, p = 0.006, to 2.0 (2.3) kgf, p = 0.026 (curved handle), and from 1.4 (4.8) kgf, p = 0.024, to 3.3 (3.5) kgf, p = 0.009 (straight handle), were found for free-living and hospitalized women, respectively. For the free-living men, when the Jamar was compared with the Bodygrip, differences were 1.9 (6.2) kgf, p = 0.274, for the curved handle and 0.4 (5.5) kgf, p = 0.161, for the straight handle. For the hospitalized men, differences were 1.5 (4.1) kgf, p = 0.026 (curved handle), and 1.5 (3.5) kgf, p = 0.009 (straight handle).
Fifty-six percent of the sample of free-living subjects comprised young adults aged ≤21 years. The remaining individuals were homogeneously distributed across age ranges, with 6% (n = 7) aged >70 years. For the free-living subjects aged ≤20 and 21–24 years, differences between HGS obtained with the Jamar and with the Bodygrip dynamometers were, respectively, 0.7 (5.7) kgf, p = 0.124, and 0.4 (6.2) kgf, p = 0.497, for the curved handle and 1.8 (6.0) kgf, p = 0.078, and 0.1 (7.2) kgf, p = 0.681, for the straight handle. For participants aged ≥25 years, differences were 2.1 (3.7) kgf, p = 0.002 (curved handle), and 1.4 (3.9) kgf, p = 0.022 (straight handle). For the inpatients, these differences were 2.6 (5.2) kgf, p = 0.002, and 2.0 (3.1) kgf, p = 0.002 (curved handle), and 2.4 (2.9) kgf, p < 0.001, and 1.4 (4.6) kgf, p = 0.004 (straight handle), respectively, for those aged <75 and ≥75 years.
When the Jamar was compared with Bodygrip curved handle, differences (IQR) were 2.9 (4.1), p < 0.001, for not nutritionally at-risk patients and 0.3 (2.4), p = 0.248, for nutritionally at-risk patients. Results were similar for the straight handle; for not nutritionally at-risk patients, a median difference of 2.8 (3.0) kgf was found (p < 0.001), whereas for nutritionally at-risk patients, that difference was 0.0 (2.7) kgf (p = 0.214).
For the inpatients at undernutrition risk, the ICCs between maximum HGS values obtained with the Jamar and with the Bodygrip using both handles were 0.97, p < 0.001. For the inpatients not at undernutrition risk, the ICC between maximum HGS values obtained with the Jamar and with the Bodygrip with the straight handle was 0.95, p < 0.001, and between the Jamar and Bodygrip with the curved handle was 0.96, p < 0.001.
Additionally, the order of application of the dynamometers was registered for a sample of 123 of the 164 participants included, and the HGS differences between Jamar and Bodygrip using each handle were evaluated. Because differences were determined by subtracting the maximum value obtained with the Jamar from the maximum value obtained with the Bodygrip using each handle, a positive difference means that the Jamar produced higher HGS values than did the Bodygrip and a negative difference means the opposite. When the Jamar was used before the Bodygrip, differences were statistically significant (p ≤ 0.019) and ranged from 1.5 (3.1) to 3.5 (4.9) kgf. Otherwise, when the Bodygrip with each handle was used before the Jamar, differences ranged from −1.1 (9.5) to 0.3 (6.0) kgf, p ≥ 0.130. Interestingly, when the Jamar was used in second, differences in HGS between Jamar and Bodygrip were significant only for measurements performed with the Bodygrip after using Jamar, 2.0 (3.2) kgf, p = 0.001, for the curved handle and 2.1 (3.1) kgf, p = 0.046, for the straight handle. Differences in HGS between Jamar and Bodygrip for measurements performed with the Bodygrip before using the Jamar were −0.1 (4.0) kgf, p = 0.481, for the curved handle and 1.4 (6.7) kgf, p = 0.779, for the straight handle.
This study examined the reliability of the Bodygrip for HGS measurement and compared it with the Jamar. The dynamometers' measurement precision tested in the laboratory was excellent and comparable to the precision previously reported for the Jamar Hydraulic Hand, Rolyan Hydraulic Hand, Smedley's Hand, Sammons Preston Rolyan Bulb, and Eisenhut dynamometers (11,20).
Significant median differences between the first and second HGS measurement for Jamar and Bodygrip dynamometers were found among free-living and hospitalized participant samples. Nevertheless, SEM analyses revealed small differences between intrainstrument measurements (0.3%). Considering the ICCs found, the interinstrument reliability between them was excellent, similar to those reported by Mathiowetz (0.90–0.97) (20) and by Bohannon (≥0.96) (3).
Despite the excellent ICCs, significant median differences between HGS obtained with the Jamar and with the Bodygrip were found. Nevertheless, they are lower and comparable to those reported by Shechtman (27) between the Jamar digital dynamometer and the DynEx (of 1.2–2.2 kgf). Moreover, SEM analyses of the present study revealed small differences between interinstrument measurements (0.4%). However, the differences found in the present study are higher than those reported by Mathiowetz between the Jamar and Rolyan hydraulic hand dynamometers (approximately from 0.045 to 0.73 kgf) (20).
Nevertheless, it is important to highlight that the Jamar produced higher HGS values than did the Bodygrip. These findings are in line with those previously obtained from comparisons of Jamar with the DynEx (27) or the Rolyan (20) dynamometers. However, HGS measurements acquired with the MicroFET 4 tended to be slightly higher than those obtained with the Jamar, from 0.998 to 1.4 kgf, (3) but these differences are lower than those reported in the present study. The dissimilarities found between measurements from different devices are in line with previous findings by our research team and suggest that individual characteristics strongly influence HGS measurement (11).
Association between maximum HGS values obtained with the Jamar and with the Bodygrip using each handle was very good and higher for the inpatient sample. Bland and Altman plots revealed that measurements obtained with the curved handle are closer to those obtained by the Jamar given the lower mean value, which is close to zero. The smaller dispersion of data evidenced by the smaller limits of agreement, and a smaller effect size for both free-living subjects and inpatients, indicates that the results of Bodygrip are closer to those of Jamar when using the curved handle compared with the straight handle. One possible explanation is that the curved-shape handle allows better adjustment of the whole hand, emphasizing the relevance of grip handle ergonomics to improve the measurement reliability. To our knowledge, the importance of handle ergonomics in HGS measurement error is shown first.
These mean differences and limits of agreement were lower than those previously reported between the Jamar and Grippit (19), Smedley's, Eisenhut, and Sammons Preston Rolyan Bulb dynamometers (11). These results highlight that the Bodygrip is a reliable alternative to the Jamar for measuring HGS of free-living and hospitalized subjects. Moreover, and despite the statistical significance differences, interinstrument low SEM reinforces the adequacy of Bodygrip for measuring HGS. Indeed, some characteristics of Bodygrip could explain these small differences when compared with Jamar, such as its dimensions (0.114 m) and weight (0.250 kg). Because reliability of dynamometers should be assessed in the setting where they are intended to be used (17), the inclusion of hospitalized patients can be considered a study strength. Moreover, to our knowledge, no previous study has evaluated the interdynamometer reliability in hospitalized samples with undernourished patients. To test this new prototype, subjects presenting a wide age range, with different health status and a large range of HGS values, were recruited. In the present study, an innovative approach was taken to understand how individual characteristics could interfere with equipment ergonomics, HGS measurements, and its differences between the devices.
Differences in HGS between Jamar and Bodygrip were negligible for the free-living sample under 25 years old and for the free-living men. Differences were smaller for the participants at undernutrition risk compared with those who were not at undernutrition risk. These findings show that the discrepancy in HGS data between dynamometers is influenced by subjects' characteristics (sex, age) and also by the magnitude of HGS values. It is demonstrated that the order of dynamometer application and the existence of undernutrition risk also influence the measurement error. However, HGS differences between devices according to sex, age, nutrition status, and the order of application of the dynamometers should be further explored in larger samples and other age groups, such as children. Furthermore, the single contribution and importance to measurement error of each of those characteristics should be further explored by controlling the effect of the others. Moreover, the wide variation in the coefficient of variance values reflects the dispersion of data, highlighting the need to explore the individual characteristic factors affecting HGS measurement in larger samples.
It would also be of great interest to evaluate the effect of disease symptoms and pharmacological treatment on the comparability between dynamometers. However, given the enormous variety of clinical situations of the inpatient sample, chosen specially to simulate the diversity of a hospital setting, these effects could not be addressed within this study and warrants further evaluation.
Moreover, only 2 different handles were tested. Regarding the different results obtained with each one in this exploratory study, further research should also investigate the best handle design to improve HGS measurement reliability and reproducibility. Although the maximum value has been referred as a less informative variable for reliability analyses (11,19,20,27), the maximum HGS value was used because the protocol used by American Society of Hand Therapists (8) recommends it for HGS assessment.
Findings of this study show that the 2 dynamometers exhibit excellent interinstrument reliability for HGS measurement in subjects with different conditions presenting a wide range of HGS values. The Bodygrip with the curved handle produces results closer to those obtained with the use of Jamar, than with the Bodygrip with the straight handle.
A new dynamometer, the Bodygrip, was developed and tested. The Bodygrip, with the ergonomic curved-shape handle is reliable for HGS measurement and has practical applicability in adult populations. Two grip handles were used, and it is shown for the first time that grip handle ergonomics is important for HGS measurement reliability for both free-living subjects and ill and undernourished patients.
This new dynamometer can add value to HGS measurement because this study has demonstrated that device ergonomics is relevant to HGS measurement reliability among subjects with a wide age range and with different nutritional status.
R. S. Guerra as a PhD student received a scholarship from FCT—Foundation for Science and Technology, financing program POPH/FSE, under the project (SFRH/BD/61656/2009). The applicant, University of Porto, submitted the patent claim in September 2015.
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