Hand Grip Strength in Pregnant and Non-Pregnant Females

AUTHORS

Chidozie Emmanuel Mbada 1 , 2 , * , Adebanjo Babalola Adeyemi 3 , Olalekan Omosebi 1 , Adekemi Eunice Olowokere 4 , Funmilola Adenike Faremi 4

1 Department of Medical Rehabilitation, College of Health Sciences, Obafemi Awolowo University, Ile–Ife, Nigeria

2 African Population and Health Research Center, Nairobi, Kenya

3 Department of Obstetrics, Gynaecology and Perinatology, College of Health Sciences, Obafemi Awolowo University, Ile-Ife, Nigeria

4 Department of Nursing Science, College of Health Sciences, Obafemi Awolowo University, Ile-Ife, Nigeria

How to Cite: Mbada C E, Adeyemi A B, Omosebi O, Olowokere A E, Faremi F A. Hand Grip Strength in Pregnant and Non-Pregnant Females, Middle East J Rehabil Health Stud. 2015 ; 2(2):e27641. doi: 10.17795/mejrh-27641.

ARTICLE INFORMATION

Middle East Journal of Rehabilitation and Health: 2 (2); e27641
Published Online: April 25, 2015
Article Type: Research Article
Received: February 2, 2015
Revised: February 23, 2015
Accepted: March 8, 2015
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Abstract

Background: Hand Grip Strength (HGS) is a predictor of upper extremity function, and changes in muscles strength and physical function and capabilities to undertake activities of daily living. Despite toll of pregnancy on musculoskeletal system, assessment of HGS in antenatal care is not a routine practice yet.

Objectives: The current study aimed to compare HGS in pregnant and non-pregnant females and also investigated the correlation of HGS among the groups.

Patients and Methods: The current case control study included 174 females (87 pregnant and age-matched non-pregnant controls respectively). HGS was assessed using a hand held Jamar dynamometer. Body adiposity was assessed by a Bioelectric Impedance Analysis machine. Data were analyzed using descriptive and inferential statistics at P < 0.05.

Results: The results showed that the pregnant and non-pregnant subjects could be compared regarding the age (29.7 ± 5.3 vs. 28.2 ± 5.8 years; P = 0.440). There was significant difference in dominant HGS (26.8 ± 8.9 vs. 29.3 ± 7.1 kgf; P = 0.044) and non-dominant HGS (24.7 ± 8.5 vs. 28.6 ± 8.4 kgf; P = 0.002) between pregnant and non-pregnant subjects, respectively. Physical characteristics weakly correlated with HGS for both dominant and non-dominant hands [correlation (r) ranges from 0.00 - 0.250]. Measures of adiposity significantly correlated with HGS in pregnant and non-pregnant females, respectively (P < 0.05). However, there were significant increases in the measures of adiposity with high parity, gravidity, and advances in stage of pregnancy (P < 0.05).

Conclusions: The current study revealed that pregnant females had significantly lower HGS compared with non-pregnant ones. High parity and gravidity and later stage of pregnancy led to significantly lower HGS. Higher level of adiposity led to poorer performance of HGS in females. It is recommended to evaluate HGS in antenatal care, which may have diagnostic and prognostic benefits.

Keywords

Hand Grip Strength Pregnancy Body Adiposity Bioelectric Impedance Analysis

Copyright © 2015, Semnan University of Medical Sciences. This is an open-access article distributed under the terms of the Creative Commons Attribution-NonCommercial 4.0 International License (http://creativecommons.org/licenses/by-nc/4.0/) which permits copy and redistribute the material just in noncommercial usages, provided the original work is properly cited.

1. Background

Hand Grip Strength (HGS) is reported as an indicator of the total body strength (1, 2), an objective test for physical capability (3), and a valid predictor of work capacity (4, 5), degree of disease/injury, and rehabilitation outcomes (6-8). A better performance on the HGS is associated with high functional index of nutritional status (9, 10), reduced risk of a series of ill health outcomes (6-8, 11) and decreased functional limitations (3-5, 12), disability (13, 14), and morbidity and mortality rates especially among older populations (15, 16).

HGS, as a physiological variable, is influenced by a gamut of factors not limited to socio-demographic (17, 18), anthropometric and morphologic (19-21), and pathophysiologic (22, 23) variables. There is substantial evidence in the literature indicating higher preponderance of poor HGS among females compared with males (24-28). However, the determinants and predictors of the higher predilection for poor HGS among females seem to have been inadequately explored.

Pregnancy, parity, and menopause are peculiar physiologic events in a female’s life. Pregnancy is typified by a series of physiological, psychological and physical alterations. Particularly, musculoskeletal changes resulting from pregnancy are widely acknowledged, though, its magnitude is scarcely quantified (29). However, menopause and pregnancy are implicated in reduced HGS in females. Some available studies showed that pregnant females had lower upper extremity strength than non-pregnant ones (30). Similarly, decreases in the strength are noticed in postpartum females (31). Whereas, some other studies showed no significant difference in HGS between pregnant and non-pregnant females (32, 33). Therefore, the outcomes of the available few studies are inconclusive. However, inclusion of HGS assessment in antenatal care may have diagnostic and prognostic benefits, since it is not a routine practice in most settings yet.

2. Objectives

The current study aimed to compare HGS between pregnant and non-pregnant females. In addition, the study sought to investigate the correlation between HGS and anthropometric and obstetric characteristics among the two groups.

3. Patients and Methods

A total of 174 (87 pregnant and age-matched non-pregnant controls respectively) females participated in this case control study. The pregnant group was recruited from females attending antenatal clinic of the Obafemi Awolowo University Teaching Hospital Complex (OAUTHC), Ile-Ife, Nigeria, and Health Centre of the Obafemi Awolowo University (OAU), Ile-Ife, Nigeria, respectively. The non-pregnant subjects comprised of age-matched staff of the OAUTHC and OAU, respectively. The participants were consecutively recruited into the study. Inclusion criteria were being within the reproductive age of less than 45 years, having neither movement restriction nor positive history of neurological disorder, hand joint disease or injury to upper extremity, and having no cognitive deficit. Based on the data from clinical records, the pregnant females recruited into the current study had no related disease.

The Ethical Committee of the OAUTHC, Ile-Ife, Nigeria, approved the study. The heads of the antenatal clinics of the OAUTHC and Health Centre of the OAU, Ile-Ife, Nigeria, respectively gave permission for the study. All participants signed informed consent letters to participate in the study.

3.1. Procedures and Measurements

3.1.1. Assessment of Hand Grip Strength

HGS was measured using a Jamar dynamometer (Model 84466; Takei Kiki Kogyo, Tokyo, Japan). Participants held the test arm of the dynamometer at a 90°C elbow flexion with the forearm in neutral position and the hand parallel to the forearm. Participants were instructed to squeeze the dynamometer maximally three times for both hands (right and left). This procedure was repeated in sitting position and all the measures were recorded (34, 35).

3.1.2. Assessment of Percent Body Fat

Percent Body Fat (PBF) was assessed using an Omron BF306 (Mod. HBF-306-E. CC, Japan) Bioelectrical Impedance Analysis (BIA) machine. Participants were instructed to take away all metal objects (such as earrings, chains, wrist watches etc.), stand erect with the feet together and also hold the BIA machine in both hands in such a way that the hands cover the metal surfaces of the machine. The participants were then instructed to hold the arms straight at 90° of shoulder flexion. Dryness of the palms was ensured by using a dry towel to clean the palmar surface of each participant’s hand. The height, weight, gender, and age of each of the subjects were fed into the micro data processor of the instrument. The participants stood still until a new set of data were displayed on the meter. This method is based on the behavior of biological structures subjected to a constant low-level alternating current (36). The PBF was rounded.

Lean Body Mass (LBM) (kg): This was calculated from the PBF estimate of the BIA. LBM was calculated by subtracting fat weight (kg) from the total body weight (kg). LBM = Total body weight–Fat weight. Fat weight was calculated from the BIA estimate of the PBF using the following Equation:

1)

Therefore,

2)

Weight and height were assessed following the standard procedures. A bathroom weighing scale (Inters Ikea BV) calibrated from 0 - 120 kg was used to measure the body weight with the accuracy of 1.0 kg. A height meter (HM210D) was used to assess height in centimeters (cm). Subjects were asked to stand barefoot on the platform of the scale while looking straight. A straight ruler was placed on the vertex of the head and the corresponding value was recorded. Body Mass Index (BMI) was calculated as the ratio of weight to height squared, i.e. BMI (Kg/m2) = Weight (kg) ÷ height (m2). Other obstetric variables (such as the stage of pregnancy, number of pregnancies, parity) were collected from the pregnant group’s case charts.

3.2. Data Analysis

Data were summarized using descriptive statistics of mean and standard deviation. Inferential statistics of independent t-test was used to compare HGS, anthropometric and socio-demographic variables between pregnant and non-pregnant females. Pearson’s product moment correlation analysis was used to test the relationship between HGS and independent variables. Analysis was carried out using SPSS version 16.0 (SPSS Inc., Chicago, IL, USA). P < 0.05 was considered as the level of significance.

4. Results

Table 1 shows the general characteristics and the HGS of all subjects. The mean age of the pregnant and the non-pregnant groups was 29.7 ± 5.3 years and 28.2 ± 5.8 years, respectively. There was a significant difference in the dominant HGS (26.8 ± 8.9 vs. 29.3 ± 7.1 kgf; P = 0.044) and non-dominant HGS (24.7 ± 8.5 vs. 28.6 ± 8.4 kgf; P = 0.002), respectively. The obstetric characteristics of the participants are shown in Table 2. The majority of the pregnant group subjects were primiparous (71.8%), while most of the non-pregnant subjects were multiparous (61.3%).

The measures of adiposity and HGS of the pregnant females by parity, gravidity, and stage of pregnancy, compared using a One-Way ANOVA and LSD Post-Hoc test, are presented in Table 3. The results showed significant increase in the measures of adiposity with higher number of parity mostly between nulliparous and primiparous (P < 0.05). Significant increase in the measures of adiposity with higher number of gravidity was found between nulligravida and primigravida (P < 0.05). However, some adiposity measures did not show any significant difference between primigravida and multigravida (P > 0.05). Based on the stage of pregnancy, there were significant differences in the dominant and non-dominant HGS, respectively (P < 0.05).

The three different HGS trials for both dominant and non-dominant hand, compared using a One-Way ANOVA and LSD Post-Hoc test, is presented in Table 4. The result indicated significant difference in the dominant and non-dominant HGS trials, respectively (P < 0.05). LSD post-hoc analysis revealed that the second trial scores were significantly higher than those of the 1st trial (P < 0.05). The second and third trials did not follow a definite trend of difference with regards to the changes in the mean scores; however, there were no significant differences between the second and third trials (P > 0.05).

Relationship between HGS and physical characteristics of the pregnant and non-pregnant participants are presented in Table 5. The results showed that the physical characteristics weakly correlated with HGS with correlation co-efficient (r) ranging from 0.00 - 0.250 for both dominant and non-dominant hands.

Table 1. Independent t-test Comparison of General Characteristics and Hand Grip Strength of the Pregnant and Non-Pregnant Females a
Pregnant (n = 87)Non-pregnant (n = 87)
VariableMean ± SDMean ± SDt-calP Value
Age, y29.7 ± 5.328.2 ± 5.81.70.440
Weight, Kg73.8 ± 10.262.6 ± 9.47.50.278
Height, m1.63 ± 5.21.61 ± 7.22.30.002 b
BMI, Kg/m²27.6 ± 4.123.9 ± 3.95.90.201
PBF, %34.9 ± 6.130.3 ± 6.84.30.621
LBM, kg48.6 ± 5.444.1 ± 7.64.50.074
BFM, kg25.2 ± 7.318.5 ± 5.66.80.003 b
DHGS26.8 ± 8.929.3 ± 7.1-2.00.044 b
NDHGS24.7 ± 8.528.6 ± 8.4-3.10.002 b

a Abbreviations: BMI, Body Mass Index; PBF, Percentage Body Fat; LBM, Lean Body Mass; BFM, Body Fat Mass; DHGS, Dominant Hand Grip Strength; NDHGS, Non-Dominant Hand Grip Strength.

b P < 0.05 was considered as level of significance.

Table 2. Obstetric Characteristics of the Subjects a
VariableAll SubjectsPregnant Non-Pregnant
Parity
Nulliparous80 (46)40 (50)40 (50)
Primiparous39 (22.4)28 (71.8)11 (28.2)
Multiparous44 (25.3)17 (38.64)27 (61.36)
Gravidity
Nulligravida37 (21.3)-37 (42.53)
Primigravida56 (32.2)39 (44.82)17 (19.54)
Multigravida81 (46.6)48 (55.17)33 (37.93)
Stage of pregnancy
1st Trimester-12 (69)-
2nd trimester-27 (15.5)-
3rd Trimester-48 (27.6)-

aValues are presented as No (%)

Table 3. Comparing the Adiposity and Hand Grip Strength of the Pregnant Females by Parity, Gravidity and Stage of Pregnancy, Using One-Way ANOVA and LSD Post-hoc Test a
VariableMean ± SDF-RatioP Value
Parity
BMI9.4150.001 b
Nulliparous24.37 ± 4.32 c
Primiparous27.44 ± 4.55 c
Multiparous27.05 ± 3.71 c
PBF1.3960.281
Nulliparous31.55 ± 5.72
Primiparous33.71 ± 7.07
Multiparous32.77 ± 8.28
LBM8.3970.001 b
Nulliparous44.18 ± 6.12 c
Primiparous48.59 ± 6.85 c
Multiparous48.38 ± 7.57 c
BFM6.6590.002 b
Nulliparous19.86 ± 6.02 c
Primiparous24.51 ± 8.15 c
Multiparous23.22 ± 7.97 c
Gravidity
BMI19.820.001 b
Nulliparous22.4 ± 4.02 c
Primiparous25.6 ± 4.02 c
Multiparous27.43 ± 3.97 c
PBF5.790.004 b
Nulliparous29.22 ± 4.26 c
Primiparous32.73 ± 6.09 c
Multiparous33.63 ± 7.67 c
LBM14.8530.001 b
Nulliparous41.49 ± 5.73 c
Primiparous46.34 ± 6.45 c
Multiparous48.47 ± 6.76 c
BFM18.5940.001 b
Nulliparous16.27 ± 3.07 c
Primiparous22.02 ± 6.13 c
Multiparous24.30 ± 8.01 c
Stage of pregnancy
BMI0.0770.926
1st Trimester27.21 ± 3.25
2nd Trimester27.77 ± 5.07
3rd Trimester27.57 ± 3.81
PBF0.3030.739
1st Trimester35.31 ± 6.11
2nd Trimester34.72 ± 6.48
3rd Trimester34.04 ± 5.94
LBM1.3390.268
1st Trimester47.00 ± 4.22
2nd Trimester47.80 ± 5.89
3rd Trimester49.36 ± 5.23
BFM0.0120.988
1st Trimester25.00 ± 6.51
2nd Trimester5.37 ± 7.94
3rd Trimester25.17 ± 7.19
Parity
DHGS9.4150.001 b
Nulliparous26.37 ± 4.32 c
Primiparous29.44 ± 4.55 c
Multiparous29.05 ± 3.71 c
NDHGS6.6590.002 b
Nulliparous19.86 ± 6.02 c
Primiparous24.51 ± 8.15 c
Multiparous23.22 ± 7.97 c
Gravidity
DHGS17.820.001 b
Nulliparous25.4 ± 5.02 c
Primiparous27.6 ± 6.03 c
Multiparous29.43 ± 5.97 c
NDHGS12.650.001 b
Nulliparous18.25 ± 1.05 c
Primiparous20.04 ± 5.13 c
Multiparous22.30 ± 6.01 c
Stage of pregnancy
DHGS0.0670.826
First Trimester27.21 ± 3.25
Second Trimester26.35 ± 5.07
Third Trimester25.57 ± 3.81
NDHGS0.0120.988
FirstTrimester25.00 ± 6.51
Second Trimester22.37 ± 3.23
Third Trimester21.17 ± 2.25

a Abbreviations: BMI, Body Mass Index; PBF, Percentage Body Fat; LBM, Lean Body Mass; BFM, Body Fat Mass; DHGS, Dominant Hand Grip Strength, NDHGS, Non-Dominant Hand Grip Strength.

b P < 0.05 was considered as level of significance.

c For a particular variable, mode means different superscripts are significantly different (P < 0.05). Mode means the same superscripts are not significantly different (P > 0.05). When only one contrast is significant, one of the cells means no superscript attached.

Table 4. Comparing the Three Trial Assessments of Hand Grip Strength, Using One-Way ANOVA and LSD Post-hoc Test a, b
VariableFirst TrialSecond TrialThird TrialF-RatioP Value
Mean ± SDMean ± SDMean ± SD
All participants
DHGS26.7 ± 9.1 d28.8 ± 9.3 d28.6 ± 9.2 d9.790.002 c
NDHGS27.5 ± 10.0 d26.4 ± 9.4 d25.9 ± 9.8 d6.040.015 c
Pregnant
DHGS25.1 ± 9.7 d26.8 ± 9.7 d28.5 ± 9.8 d15.130.001 c
NDHGS25.1 ± 9.2 d24.9 ± 9.623.9 ± 9.1 d2.0540.155
Non-pregnant
DHGS28.2 ± 8.3 d30.8 ± 8.6 d28.8 ± 8.9 d0.3890.534
NDHGS29.9 ± 10.3 d27.9 ± 9.1 d27.9 ± 10.1 d4.0000.049 c

a N = 174

b Abbreviations: DHGS, Dominant Hand Grip Strength; NDHGS, Non-Dominant Hand Grip Strength.

d For a particular variable, mode means different superscripts are significantly different (P < 0.05). Mode means the same superscripts are not significantly different (P > 0.05). When only one contrast is significant, one of the cells means no superscript attached.

c P < 0.05 was considered as level of significance.

Table 5. Pearson’s Product Moment Correlation Test of Relationship Between Hand Grip Strength and Physical Characteristics of the Pregnant and Non-Pregnant Females a
Variable Pregnant GroupNon-pregnant Group
DHGSNDHGSDHGSNDHGS
r (p)r (p)r (p)r (p)
Age0.086 (0.427) b0.034 (0.752) b0.067 (0.537) b-0.099 (0.361)
Weight0.080 (0.463) b0.073(0.502)0.047 (0.666) b0.028 (0.799) b
Height0.203 (0.059) b0.241 (0.025) b-0.028(0.800)-0.113 (0.296)
BMI-0.021 (0.844)0.080 (0.460)0.071 (0.516) b0.147 (0.175) b
PBF0.211 (0.030) b0.030 (0.785) b0.006 (0.953) b-0.023 (0.832)
LBM-0.080 (0.459)0.024 (0.823) b-0.063 (0.561)0.026 (0.814) b
BFM0.171 (0.113) b0.048 (0.659) b-0.036 (0.740)0.012 (0.916) b
Pregnancy stage0.185 (0.85) b0.078 (0.645) b

a Abbreviations: BMI, Body Mass Index; PBF, Percentage Body Fat; LBM, Lean Body Mass; BFM, Body Fat Mass.

b Indicates significant co-efficient (r) ranging from 0.00 - 0.250.

5. Discussion

The study subjects were relatively young. A majority of the pregnant females were primiparous and were also in the first trimester stage of pregnancy while most of the non-pregnant participants were multiparous. A majority of the pregnant subjects were multigravida while most of the non-pregnant participants were nulligravida. The groups were largely comparable in their anthropometric parameters except for height and body fat mass values, which were higher in the pregnant group. Comparability of the anthropometric and morphologic parameters between the groups of the study may help to eliminate co-founding factors for the difference between the groups. This is because anthropometric and morphological parameters are important indicators and determinants of physical performance test results (37-39) including HGS performance (19-21).

The comparison of the measures of adiposity of the groups based on parity, gravidity, and stage of pregnancy showed that females with higher parity had significantly higher measures of adiposity. In addition, higher gravidity led to increase in measures of adiposity. Koch et al. (40) observed that parity modestly influenced BMI in their study and concluded that parity causes increase in body adiposity but not necessarily following an abdominal pattern. The child bearing years are described as important life stages for females that may result in substantial weight gain, leading to the development of obesity (41). Resultant increase in weight gain and body fat associated with parity is linked with excessive gestational weight gain (42). Akbarzade et al. (43) reported that maternal weight gain has consequences including a decrease in non-reactive parameters of non-stress test (non-stress test is the most common way to evaluate the fetus during pregnancy) and the number of accelerations of the fetal heart rate, which is the most important index for fetal health.

The current study tested the reliability of one trial versus three HGS trials in pregnant and non-pregnant females. Current recommendations state that taking the mean of three repeated grip trials provides more reliable results than only one trial (44). However, some others advocate for the best of three trials (45, 46) while others investigators prefer a single trial (47, 48). However, the repeated measure analysis used in the current study showed significant difference in the HGS trials for the dominant and non-dominant hand, respectively. Post-hoc analysis revealed that the second trial scores were significantly higher than those of the first trial. However, there were no significant differences between mean scores of the second and third trials. The findings of the study were in tandem with the study indicating that maximum HGS readings occur most frequently with the first or second attempt of a series of successive trials (49). However, the American Society of Hand Therapist recommended that the mean of the three successive trials be used as a measure of hand grip strength (34). In line with the above, the current study used the mean value of the three trials of HGS assessment for both dominant and non-dominant hand in the final analysis.

The non-pregnant group in the current study had significantly higher HGS than the pregnant group. Morrissey (32) carried out a comparative study on HGS between pregnant and non-pregnant females and found no significant difference between the groups. Comparison of the HGS of the pregnant females by parity, gravidity, and stage of pregnancy was also carried out in this study, and significant differences were found in the dominant hand grip strength and non-dominant hand grip strength among the pregnant females. It indicates that the obstetric characteristics such as parity, gravidity, and stage of pregnancy have significant effect on the HGS in females. Pregnancy-related alteration in musculoskeletal system may account for the significantly lower HGS observed among the pregnant group in the current study. Pregnancy leads to alteration in collagen metabolism and increased connective tissue pliability and extensibility, which result from altered levels of relaxin, estrogen, and progesterone. Their ligamentous tissues are predisposed to laxity with resultant reduced joint stability. To allow the birth of the baby the symphysis pubis, sacroiliac joints, and the tensile strengths of muscles are particularly affected and this ligamentous laxity may continue for six months postpartum (50). Comparison of the pattern of HGS in this population showed significant differences between the dominant and non-dominant HGS of the pregnant and non-pregnant groups, respectively. Similarly, studies among other populations showed consistent trend of higher HGS in the dominant upper extremity compared with the non-dominant limb. Results of the current study showed that HGS weakly correlated with physical characteristics among pregnant and non-pregnant groups.

A potential limitation of this study was unevenly matched groups. Since the control group could not be matched by trimester, gravidity, and parity, age was the major matching criterion in the current study. However, the physiological and physical changes in pregnancy (51, 52) coupled with reduced physical activity and energy expenditure (53) put the pregnant females at disadvantage of having poorer HGS assessment results. In addition, further studies should validate the use of BIA and BMI as the measures of body composition in pregnancy. Although, BIA is reported as an easy, fast, non-invasive, and accurate method to estimate the body water composition during pregnancy (54, 55), however, it may have high frequency of errors (56, 57); while BMI may not represent a true body composition status since it does not consider significant parameters such as total lean body mass and fat content (58).

It was concluded that pregnant females had significantly lower HGS compared with non-pregnant ones. High parity and gravidity, and the later stage of pregnancy led to significantly lower HGS. Level of adiposity significantly influences the performance of HGS in females.

Acknowledgements

Footnote

References

  • 1.

    Efficacy of Handgrip Strength in Predicting Total Body Strength Among High Performance Athletes. Proceedings of the International Colloquium on Sports Science, Exercise, Engineering and Technology 2014 (ICoSSEET 2014). : 29 -38

  • 2.

    Massy-Westropp N, Rankin W, Ahern M, Krishnan J, Hearn TC. Measuring grip strength in normal adults: reference ranges and a comparison of electronic and hydraulic instruments. J Hand Surg Am. 2004; 29(3) : 514 -9 [DOI][PubMed]

  • 3.

    Bohannon RW, Peolsson A, Massy-Westropp N, Desrosiers J, Bear-Lehman J. Reference values for adult grip strength measured with a Jamar dynamometer: a descriptive meta-analysis. Physiotherapy. 2006; 92(1) : 11 -5 [DOI]

  • 4.

    Trippolini MA, Dijkstra PU, Cote P, Scholz-Odermatt SM, Geertzen JH, Reneman MF. Can functional capacity tests predict future work capacity in patients with whiplash-associated disorders? Arch Phys Med Rehabil. 2014; 95(12) : 2357 -66 [DOI][PubMed]

  • 5.

    Gross DP, Battie MC. Does functional capacity evaluation predict recovery in workers' compensation claimants with upper extremity disorders? Occup Environ Med. 2006; 63(6) : 404 -10 [DOI][PubMed]

  • 6.

    Martin-Ponce E, Hernandez-Betancor I, Gonzalez-Reimers E, Hernandez-Luis R, Martinez-Riera A, Santolaria F. Prognostic value of physical function tests: hand grip strength and six-minute walking test in elderly hospitalized patients. Sci Rep. 2014; 4 : 7530 [DOI][PubMed]

  • 7.

    Di Monaco M, Castiglioni C, De Toma E, Gardin L, Giordano S, Di Monaco R, et al. Handgrip strength but not appendicular lean mass is an independent predictor of functional outcome in hip-fracture women: a short-term prospective study. Arch Phys Med Rehabil. 2014; 95(9) : 1719 -24 [DOI][PubMed]

  • 8.

    Roberts HC, Syddall HE, Cooper C, Aihie Sayer A. Is grip strength associated with length of stay in hospitalised older patients admitted for rehabilitation? Findings from the Southampton grip strength study. Age Ageing. 2012; 41(5) : 641 -6 [DOI][PubMed]

  • 9.

    Kaur N, Koley S. An Association of Nutritional Status and Hand Grip Strength in Female Labourers of North India. Anthropologist. 2010; 12(4) : 237 -43

  • 10.

    Hornby ST, Nunes QM, Hillman TE, Stanga Z, Neal KR, Rowlands BJ, et al. Relationships between structural and functional measures of nutritional status in a normally nourished population. Clin Nutr. 2005; 24(3) : 421 -6 [DOI][PubMed]

  • 11.

    Norman K, Stobaus N, Kulka K, Schulzke J. Effect of inflammation on handgrip strength in the non-critically ill is independent from age, gender and body composition. Eur J Clin Nutr. 2014; 68(2) : 155 -8 [DOI][PubMed]

  • 12.

    Norman K, Stobaus N, Gonzalez MC, Schulzke JD, Pirlich M. Hand grip strength: outcome predictor and marker of nutritional status. Clin Nutr. 2011; 30(2) : 135 -42 [DOI][PubMed]

  • 13.

    Giampaoli S, Ferrucci L, Cecchi F, Lo Noce C, Poce A, Dima F, et al. Hand-grip strength predicts incident disability in non-disabled older men. Age Ageing. 1999; 28(3) : 283 -8 [PubMed]

  • 14.

    Beumer A, Lindau TR. Grip strength ratio: a grip strength measurement that correlates well with DASH score in different hand/wrist conditions. BMC Musculoskelet Disord. 2014; 15 : 336 [DOI][PubMed]

  • 15.

    Koopman JJ, van Bodegom D, van Heemst D, Westendorp RG. Handgrip strength, ageing and mortality in rural Africa. Age Ageing. 2014; [DOI][PubMed]

  • 16.

    Gary R. Evaluation of frailty in older adults with cardiovascular disease: incorporating physical performance measures. J Cardiovasc Nurs. 2012; 27(2) : 120 -31 [DOI][PubMed]

  • 17.

    Moy F, Chang E, Kee K. Predictors of Handgrip Strength among the Free Living Elderly in Rural Pahang, Malaysia. Iran J Public Health. 2011; 40(4) : 44 -53 [PubMed]

  • 18.

    Wagner PR, Ascenço S, Wibelinger LM. Hand grip strength in the elderly with upper limbs pain. Rev Dor. São Paulo. 2014; 15(3) : 182 -5

  • 19.

    Adedoyin RA, Ogundapo FA, Mbada C, Adekanla BA, Johnson OE, Onigbinde TA, et al. Reference Values for Handgrip Strength Among Healthy Adults in Nigeria. Hong Kong Physiotherapy Journal. 2009; 27(1) : 21 -9 [DOI]

  • 20.

    Barut C, Dogan A, Buyukuysal MC. Anthropometric aspects of hand morphology in relation to sex and to body mass in a Turkish population sample. Homo. 2014; 65(4) : 338 -48 [DOI][PubMed]

  • 21.

    Aghazadeh F, Lee K, Waikar A. Impact of anthropometric and personal variables on grip strength. J Hum Ergol (Tokyo). 1993; 22(2) : 75 -81 [PubMed]

  • 22.

    Kallman DA, Plato CC, Tobin JD. The role of muscle loss in the age-related decline of grip strength: cross-sectional and longitudinal perspectives. J Gerontol. 1990; 45(3) -8 [PubMed]

  • 23.

    Pizzato TM, Baptista CR, Souza MA, Benedicto MM, Martinez EZ, Mattiello-Sverzut AC. Longitudinal assessment of grip strength using bulb dynamometer in Duchenne Muscular Dystrophy. Braz J Phys Ther. 2014; 18(3) : 245 -51 [PubMed]

  • 24.

    Montoye HJ, Lamphiear DE. Grip and arm strength in males and females, age 10 to 69. Res Q. 1977; 48(1) : 109 -20 [PubMed]

  • 25.

    Aniansson A, Rundgren A, Sperling L. Evaluation of functional capacity in activities of daily living in 70-year-old men and women. Scand J Rehabil Med. 1980; 12(4) : 145 -54 [PubMed]

  • 26.

    Christine LW. Women, sport, and performance 1985;

  • 27.

    Koley S, Kaur N. A Study on Handgrip Strength and some Anthropometric Variables in Younger and Older Female Laborers of Jalandhar, Punjab, India. Int J Biol Anthropol. 2009; 3(2)

  • 28.

    Aoki H, Demura S. The effect of gender and lateral dominance on gripping muscle power in young adults. Sport Sciences for Health. 2008; 3(1-2) : 1 -6 [DOI]

  • 29.

    Mbada CE, Ojedoyin OO, Ayanniyi O, Adeyemi AB, Olagbegi OM, Adekanla BA, et al. Comparative assessment of back extensor muscles' endurance between nulliparous and parous women. Journal of Back and Musculoskeletal Rehabilitation. 2007; 20(4) : 143 -9

  • 30.

    Masten WY, Smith JL. Reaction time and strength in pregnant and nonpregnant employed women. J Occup Med. 1988; 30(5) : 451 -6 [PubMed]

  • 31.

    Treuth MS, Butte NF, Puyau M. Pregnancy-related changes in physical activity, fitness, and strength. Med Sci Sports Exerc. 2005; 37(5) : 832 -7 [PubMed]

  • 32.

    Morrissey SJ. Work place design recommendations for the pregnant worker. International Journal of Industrial Ergonomics. 1998; 21(5) : 383 -95 [DOI]

  • 33.

    Dumas G, Charpentier K, Wang M, Leger A. Comparison of strength between pregnant and non-pregnant women (Abstract). American Society of Biomechanics Annual Conferences. 2008;

  • 34.

    Fess EE. Clinical Assessment Recommendations. 1992; : 41–5

  • 35.

    Kuzala EA, Vargo MC. The relationship between elbow position and grip strength. Am J Occup Ther. 1992; 46(6) : 509 -12 [PubMed]

  • 36.

    Van Loan MD. Bioelectrical impedance analysis to determine fat-free mass, total body water and body fat. Sports Med. 1990; 10(4) : 205 -17 [PubMed]

  • 37.

    Jeune B, Skytthe A, Cournil A, Greco V, Gampe J, Berardelli M, et al. Pregnancy and lower limb varicose veins: prevelance and risk factors. Vasc Bras. 2010; 9(2) : 29 -35

  • 38.

    Moncef C, Said M, Olfa N, Dagbaji G. Influence of morphological characteristics on physical and physiological performances of tunisian elite male handball players. Asian J Sports Med. 2012; 3(2) : 74 -80 [PubMed]

  • 39.

    Amri S. Anthropometric Correlates of Motor Performance. Movement, Health and Exercise. 2012; 1(1) : 75 -92

  • 40.

    Koch E, Bogado M, Araya F, Romero T, Diaz C, Manriquez L, et al. Impact of parity on anthropometric measures of obesity controlling by multiple confounders: a cross-sectional study in Chilean women. J Epidemiol Community Health. 2008; 62(5) : 461 -70 [DOI][PubMed]

  • 41.

    Gunderson EP. Childbearing and obesity in women: weight before, during, and after pregnancy. Obstet Gynecol Clin North Am. 2009; 36(2) : 317 -32 [DOI][PubMed]

  • 42.

    Ohlin A, Rossner S. Maternal body weight development after pregnancy. Int J Obes. 1990; 14(2) : 159 -73 [PubMed]

  • 43.

    Akbarzade M, Rafiee B, Asadi N, Zare N. Correlation Between Maternal Body Mass Index, Non-stress Test Parameters and Pregnancy Outcomes in Nulliparous Women. Womens Health. 2014; 1(3)

  • 44.

    Coldham F, Lewis J, Lee H. The reliability of one vs. three grip trials in symptomatic and asymptomatic subjects. J Hand Ther. 2006; 19(3) : 318 -26 [DOI][PubMed]

  • 45.

    Fess EE, Moran C. Clinical. Assessment. Recommendations. 1981;

  • 46.

    Pryce JC. The wrist position between neutral and ulnar deviation that facilitates the maximum power grip strength. J Biomech. 1980; 13(6) : 505 -11 [PubMed]

  • 47.

    Kellor M, Frost J, Silberberg N, Iversen I, Cummings R. Hand strength and dexterity. Am J Occup Ther. 1971; 25(2) : 77 -83 [PubMed]

  • 48.

    Kamimura T, Ikuta Y. Evaluation of grip strength with a sustained maximal isometric contraction for 6 and 10 seconds. J Rehabil Med. 2001; 33(5) : 225 -9 [PubMed]

  • 49.

    Mathiowetz V, Weber K, Volland G, Kashman N. Reliability and validity of grip and pinch strength evaluations. J Hand Surg Am. 1984; 9(2) : 222 -6 [PubMed]

  • 50.

    Brook G, Brayshaw E, Coldon Y, Davis S, Evans G, Hawkers R, et al. Physiotherapy in women's Health. 2003;

  • 51.

    Borg-Stein J, Dugan SA, Gruber J. Musculoskeletal aspects of pregnancy. Am J Phys Med Rehabil. 2005; 84(3) : 180 -92 [PubMed]

  • 52.

    Silversides LK, Colman PM. Physiological changes of pregnancy. Health Sci. 2012; 69(4) : 567 -74

  • 53.

    Koushkie Jahromi M, Namavar Jahromi B, Hojjati S. Relationship between Daily Physical Activity During Last Month of Pregnancy and Pregnancy Outcome. Iran Red Crescent Med J. 2011; 13(1) : 15 -20 [PubMed]

  • 54.

    Ghezzi F, Franchi M, Balestreri D, Lischetti B, Mele MC, Alberico S, et al. Bioelectrical impedance analysis during pregnancy and neonatal birth weight. Eur J Obstet Gynecol Reprod Biol. 2001; 98(2) : 171 -6 [PubMed]

  • 55.

    Toro-Ramos T, Hoffman DJ, Sichieri R. Estimates of body composition during pregnancy using bioelectrical impedance analysis. The FASEB Journal. 2012; 26(1_MeetingAbstracts) : 813.1

  • 56.

    Kyle UG, Bosaeus I, De Lorenzo AD, Deurenberg P, Elia M, Manuel Gomez J, et al. Bioelectrical impedance analysis-part II: utilization in clinical practice. Clin Nutr. 2004; 23(6) : 1430 -53 [DOI][PubMed]

  • 57.

    Sun G, French CR, Martin GR, Younghusband B, Green RC, Xie YG, et al. Comparison of multifrequency bioelectrical impedance analysis with dual-energy X-ray absorptiometry for assessment of percentage body fat in a large, healthy population. Am J Clin Nutr. 2005; 81(1) : 74 -8 [PubMed]

  • 58.

    Sakkas GK. Visceral Adiposity and not only total body fat content should be viewed as a critical parameters in Health prognosis in renal failure. Nephro-Urol Mon. 2012; 4(1) : 393 -4 [DOI]

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