Reference equations for handgrip strength: Normative values in young adult and middle-aged subjects

Accepted Manuscript Reference equations for handgrip strength: normative values in young adult and middle-aged subjects Jordão Lopes, Samantha Torres Grams, Edy Floriano da Silva, Luana Adriano de Medeiros, Christina May Moran de Brito, Wellington Pereira Yamaguti PII:

S0261-5614(17)30109-7

DOI:

10.1016/j.clnu.2017.03.018

Reference:

YCLNU 3089

To appear in:

Clinical Nutrition

Received Date: 27 September 2016 Revised Date:

14 March 2017

Accepted Date: 20 March 2017

Please cite this article as: Lopes J, Grams ST, Silva EFd, Medeiros LAd, Brito CMMd, Yamaguti WP, Reference equations for handgrip strength: normative values in young adult and middle-aged subjects, Clinical Nutrition (2017), doi: 10.1016/j.clnu.2017.03.018. This is a PDF file of an unedited manuscript that has been accepted for publication. As a service to our customers we are providing this early version of the manuscript. The manuscript will undergo copyediting, typesetting, and review of the resulting proof before it is published in its final form. Please note that during the production process errors may be discovered which could affect the content, and all legal disclaimers that apply to the journal pertain.

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ORIGINAL ARTICLE

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Reference equations for handgrip strength: normative values in young adult and

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middle-aged subjects

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Jordão Lopes, Samantha Torres Grams, Edy Floriano da Silva, Luana Adriano de

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Medeiros, Christina May Moran de Brito, Wellington Pereira Yamaguti

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Rehabilitation Service, Hospital Sírio-Libanês, São Paulo, SP, Brazil

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Corresponding Author:

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Wellington Pereira Yamaguti, PhD

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Rua Dona Adma Jafet, 91 (Centro de Reabilitação)

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São Paulo, SP, Brazil

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CEP: 01308-050

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E-mail: [email protected] or [email protected]

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Phone number: +55 11 94556-7557

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Abstract

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Background & Aims: Handgrip strength (HS) has been widely used as a functionality

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parameter of the upper limbs (UL) and general health. The measurement of HS by

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dynamometry is a low cost, non-invasive method of simple applicability, widely used in

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pulmonary rehabilitation and in critical care units. However, there are no reports in the

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literature of reference equations for the Brazilian population involving young and middle-

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aged adults. The aim of this study was to establish reference equations to predict

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normal HS for young and middle-aged adults through demographic and anthropometric

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data.

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Methods: This is a cross-sectional study with a sample of 80 healthy subjects (40 men

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and 40 women), aged 20-60 years. Inclusion criteria were: 1) BMI between 18.5 and 30

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kg/m2; 2) presence of dominant hand; 3) no cardiac, pulmonary, metabolic, or

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neurologic diseases; 4) lack of musculoskeletal disorders; 5) no history of fractures or

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trauma of the UL. Anthropometric measurements of the UL were obtained by a tape

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(hand length and width, forearm circumference and length). The dominance of hands

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was defined by the Dutch Handedness Questionnaire. HS measures were obtained by a

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manual hydraulic dynamometer, according to the recommendations of the American

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Association of Hand Therapists. Data were analyzed with SPSS for Windows, version

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17.0, and treated with descriptive and inferential analysis. Normality was evaluated by

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Kolmogorov-Smirnov.

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analysis were also used.

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Pearson or Spearman coefficients and multiple regression

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Results: HS was significantly higher for men compared to women, and also higher for

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the dominant hand (HSD) compared to the non-dominant hand (HSND) (p<0.05). No

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significant differences were found for HS between the age groups 20-30, 30-40, 40-50

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and 50-60 years (p> 0.05). No correlation was found between HS and age. A weak

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correlation was found between HS and BMI. A moderate correlation of HS was

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observed with weight and height. Finally, moderate and high correlations were found

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between HS and anthropometric variables of UL. The best reference equations with R2,

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adjusted to 0.71 and 0.70, were respectively:

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HSDkg = -15.490 + (10.787 x Gender male=1; female=0) + (0.558 x Forearm circumference) +

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(1.763 x Hand Length);

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HSNDkg = -9.887 + (12.832 x Gender male=1; female=0) + (2.028 x Hand Length).

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Conclusion: The variability of HS is largely explained by gender, forearm

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circumference, and hand length.

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Keywords: anthropometry; hand strength; dynamometry; nutrition assessment;

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muscular function assessment; reference values.

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Introduction

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According to the current definition, sarcopenia is a syndrome characterized by

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progressive and generalized loss of skeletal muscle mass and strength with a risk of

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adverse outcomes such as physical disability, poor quality of life, and death.1-3 Even

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though sarcopenia is originally known as a condition related to aging, its development

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may be secondary to catabolic and chronic diseases such as chronic obstructive

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pulmonary disease,4 heart failure,5 and chronic kidney disease,6 also associated to

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cancer7 and present in critically ill patients.8

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For the diagnosis of sarcopenia it is necessary to observe the presence of both low

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muscle mass and low muscle function (performance or strength).1,2 To assess the

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muscle mass, several techniques can be used, for instance, body images techniques

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(computed

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absorptiometry and ultrasound), bioimpedance analysis and anthropometric measures

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(mid-upper arm circumference, skin fold thickness and calf circumference).1,9 To

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evaluate the physical performance, a wide range of tests are available, including the

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Short Physical Performance Battery (SPPB), usual gait speed, 6-min walk test, timed

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get-up-and-go test (TGUG), and the stair climb power test. Finally, to measure muscle

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strength there are fewer well-validated techniques that involve the assessment of

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strength using isokinetic dynamometers and handgrip strength.1

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magnetic

resonance

imaging,

dual

energy

X-ray

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tomography,

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Among the methods to assess the muscular strength, handgrip strength (HS)

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measurement has been widely used because it is a simple, fast, inexpensive and

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efficacious test which uses a portable device.10 This method correlates closely with

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measures of muscle strength from other muscle groups, including the lower limbs,11 and

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is a useful tool to identify mobility limitation12,13 and physical.14 Furthermore, handgrip is

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a marker of nutrition status15 and better predictor of clinical outcomes than muscle

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mass,12,16 has a powerful predictor of cause-specific and total mortality, and may help

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identify patients at increased risk of health deterioration.10,17-19

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HS is generally influenced by a person’s level of physical activity, type of occupation,

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hand dominance and anthropometric characteristics such as forearm circumference,

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body height and weight.15, 20, 21 Since demographic factors and ethnicity also affect HS,

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several studies have reported normative data of HS from different populations,

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especially from high-income countries and European ethnicity.22-26 To the Brazilian

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population, some studies have been published defining normal values for age ranges in

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adults and the elderly.27,28 Only one study proposes reference equation for individuals

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older than 50 years.29 Therefore, the aim of this study was to establish reference

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equations to predict normal HS for young and middle-aged adults of the Brazilian

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population through demographic and anthropometric data.

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Methods

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Subjects

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This study had a cross-sectional design and included healthy subjects in a convenience

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sample, aged 20-60 years. They were recruited among students and employees of a

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private and tertiary hospital in São Paulo (Brazil), as well as their relatives. Data were

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collected from February 2013 to December 2013. Inclusion criteria were as follows: 1)

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BMI between 18.5 and 30 kg/m2; 2) presence of hand dominance; 3) absence of

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cardiac, pulmonary, metabolic or neurological disease; 4) absence of chronic renal

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failure, musculoskeletal disorders or early postoperative period (<30 days for medium-

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sized surgeries and <60 days for large ones); and 5) absence of fracture history or

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trauma of the upper limbs. The exclusion criteria were: 1) presence of pain at the time of

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evaluation; and 2) inability to understand or perform any procedure during the protocol.

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This study was approved by the Ethics Committee on Research of the Hospital Sírio-

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Libanês (HSL2013/05), and written informed consent was given by all participants.

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Demographic and Anthropometric evaluation

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After

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investigate and obtain additional information, including age, type of work and

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occupation, sports activities, health status, medication, previous surgeries, smoking

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habits, symptoms of pain or tingling in the upper limbs, reporting of range of motion

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limitation in the upper limbs, history of fractures or injuries, and whether subjects were

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engaged in any medical treatment that would involve prescription medication, over-the-

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counter drugs or allied health support.

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the inform consent was obtained, we applied a questionnaire in order to

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Anthropometric data of all individuals were collected. Body weight (expressed in kg) was

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measured using a digital balance (Toledo®, Model 2096PP/2, Inc., Brazil) with the

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subjects wearing light clothes and no shoes. Height (expressed in meters) was

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measured twice for each subject using the stadiometer of the same balance. In addition,

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we calculated the body mass index (BMI) by means of the ratio between the weight and

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the square of height (kg / m²). Subjects were classified as underweight (BMI < 18.5

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kg/m2), normal (18.5 kg/m2 < BMI < 25 kg/m2) or overweight (BMI ≥ 25 kg/m2). The

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study also included anthropometric measurements of the hand width (measured at the

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level of the distal palmar crease); hand length (measured from the distal wrist crease to

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the tip of the longest finger); forearm length (distance between lateral humeral

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epicondyle and radial styloid process); and the forearm circumference (measured at the

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midpoint of forearm length).22 All measurements were performed using the same tape.

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Habitual physical activity

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The habitual physical activity (HFA) score was quantified by applying a cross-culturally

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adapted and validated version for use in Brazil30 of the Baecke’s questionnaire.31 This

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instrument consists of 16 questions that cover three HPA scores for the last 12 months:

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1) score of occupational physical activity (OPA) with eight questions; 2) score of

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physical exercise in leisure (PEL) with four questions; and 3) score of leisure and

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locomotion activities (LLA) with four questions. The answers are scored on a scale of 0

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to 5 points and the final result is expressed in a summary index.

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Handedness evaluation

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The handedness of the participants was defined by the Dutch Handedness

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Questionnaire. This is a self-assessment questionnaire consisting of 16 items of manual

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activities. The subjects should report which hand is usually used for each activity or

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whether both hands are used. If the subject does not have a clear preference, the use of

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both hands should be indicated. Each item may be coded from 0 to 2, with "left"

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receiving a score of 0, "right" receiving a score of 2, and "both" receiving a score of 1.

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The total score could range from 0 (i.e. extremely left-handed) to 32 (i.e. extremely

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right-handed). Therefore, the subjects were classified as: 1) strongly left-handed

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subjects (score ≤ 4); 2) ambidextrous (5 ≤ score ≤ 27); and 3) strongly right-handed

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subjects (score ≥ 28).32

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Handgrip dynamometry

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HS was measured in both sides (dominant and non-dominant) by means of a manual

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hydraulic dynamometer (SH 5001; SAEHAN corporation; Masan; Yangdeok-Dong;

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South Korea), according to the recommendations of the American Association of Hand

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Therapists.33 Thus, the subjects were asked to remain seated in a chair with their

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shoulders in a neutral position, one hand resting on the thigh and the elbow of the

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member to be evaluated flexed at 90 degrees with the forearm in neutral rotation,34 and

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wrists between 0º and 30º of flexion and between 0º and 15º of ulnar deviation.35 For all

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subjects, the movable handle of the dynamometer was individually adjusted according

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to the size of the hands so that the handle was positioned under the second phalanges

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of the index, middle and ring fingers.36,37 The subjects were instructed to grip the

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dynamometer with maximum strength in response to a standardized voice command,38

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and to hold the grip for three seconds. The measurements for the dominant and the

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non-dominant handgrip strength were done in a random order, established by a simple

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lottery. The rest period between measurements was at least one minute and the best

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value of three acceptable evaluations for each hand was considered for statistical

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analysis.28,39

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Statistical analysis

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Statistical analysis was carried out using statistical packages SPSS 17.0 (SPSS Inc.,

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USA). A sample size of 77 subjects was calculated using the results from a previous

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study36: Adjusted r2 = 0.36 (average of the two worst values of Adjusted r2), alpha value

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of 0.05 and a power of 0.9. In all age ranges, we decided to recruit an equal number of

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males and females, and because of this criteria, we collected data of 80 subjects (10

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men and 10 women in each age range). Data distribution normality was evaluated by

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the Kolmogorov- Smirnov test. Data were described as median [interquartile range

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25%-75%] or mean ± standard deviation. Mann-Whitney and Student's t-test were used

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to compare the subjects’ characteristics between male and female genders. Paired

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Sample t-test or Wilcoxon test were used to compare HS for the dominant hand (HSD)

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and for the non-dominant hand (HSND). One-way ANOVA or Kruskal- Wallis test were

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used to compare HSD and HSND, allocated according to age group and gender. We

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calculated Pearson or Spearman correlation coefficients and applied a model of multiple

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linear regression HSD and HSND as dependent variables; demographic and

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anthropometric data as independent variables). Multicollinearity was avoided by

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removing the variables with high correlation (r>0.70, or r<-0.70) and the variables with

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variance inflation factor (VIF) > 4 from the statistical model. Statistical significance level

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was considered as p<0.05.

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Results

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The study sample included 80 healthy subjects (40 male and 40 female). Data of all

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demographic and anthropometric variables are presented in Table1. The subjects’ age

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ranged from 21 to 57 years (young adults and middle-aged subjects). Median age was

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39.5 [29.3 – 49.8] years, with no statistical difference between men and women. In

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general, the subjects presented a normal body composition: one participant showed low

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weight (1.25%), forty-five were normal (56.25%), thirty-four were overweight (42.5%)

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and no participant was obese. As expected, men were heavier and taller than women.

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Regarding physical activity measured by Baecke’s score, twenty-seven participants

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reached a score higher than eight (33.75%), while the remaining fifty-three individuals

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(66.25%) were considered inactive (HPA score <8). HS values are presented in two

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groups: HSD and HSND, according to the score of the Dutch Handedness

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Questionnaire. All women (100%) and 97.5% of men were right-handed, only one man

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(2.5%) was left-handed and no participant was ambidextrous.

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Influence of gender

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HSD, HSND and the other anthropometric measures (hand width and forearm

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circumference) were also significantly higher in men when compared to women.

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Observed values for HS ranged between 16-34 kg (non-dominant) and 18-36 kg

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(dominant) in women, and between 24-58 kg (non-dominant) and 32-54 (dominant) in

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men (Table 1).

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Influence of handedness

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When the sample was stratified by age groups, it was observed that HSD was

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significantly greater than HSND in male (p = 0.002) and in female (p < 0.001) in all age

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groups (Table 2). Overall mean difference between hand dominance was 4.38% for

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men and 15% for women (Table 1). Men presented significantly greater HSD and HSND

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in comparison to women in all age groups (Table 2).

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Influence of age and anthropometric measures

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No difference was observed in HSD and HSND between age groups for both men and

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women (p>0.05) (Table 2). The correlations of HSD and HSND with demographic (age)

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and anthropometric variables (height, weight, BMI, hand width, and forearm

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circumference) were evaluated and are described in Table 3. There were no

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correlations between age and both HSD and HSND (p>0.05). There was a positive and

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low correlation between BMI and both HSD and HSND (r=0.30 and r=0.32,

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respectively). A positive and moderate correlation of both HSD and HSND with height

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(r=0.68 and r=0.68, respectively), weight (r=0.64 and r=0.67; respectively), hand length

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(r=0.66 and r=0.68, respectively), and forearm length (r=0.66 and r=0.68, respectively)

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was observed. Finally, there was a positive and high correlation of both HSD and HSND

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with width (r=0.72 and r=0.71, respectively) and forearm circumference (r=0.72, r=0.71,

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respectively). All these correlations were statistically significant (p<0.05).

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A multiple regression model showed that 71% (p<0.001) of the variability in HSD could

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be explained by gender, forearm circumference and hand length, while 70% (p<0.001)

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of the variability in HSND was explained by gender and hand length. The reference

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equations for HS were:

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HSDkg = -15.490 + (10.787 x Gendermale=1; female=0) + (0.558 x Forearm circumference) +

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(1.763 x Hand Length);

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HSNDkg = -9.887 + (12.832 x Gendermale=1; female=0) + (2.028 x Hand Length).

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Discussion

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It was demonstrated in the present study that healthy subjects aged 20-60 years

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present large variability in HS (16 – 58 kg), and 71% of this variance can be explained

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by gender, forearm circumference and hand length in dominant hand, and 70% of this

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variance can be explained by gender and hand length in non-dominant hand.

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Furthermore, reference equations were established using these variables, easily

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applicable in clinical and research settings.

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Previously to our study, in 2009, a Brazilian research group published reference

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equations for HS from a sample of 54 subjects.29 However, that study presented some

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limitations. Firstly, the study included no subjects younger than 50 years old, which is a

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limitation since many subjects are affected by such diseases in this age range.

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Secondly, the regression coefficients were modest (67.7% in dominant hand and 54.6%

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in non-dominant hand), increasing the chance of bias in predicting HS. In fact, this was

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confirmed when that equation was applied in an a posteriori study.40 The intraclass

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correlation coefficients between the predicted value and the obtained value in that

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study40 were low (0.52 in dominant hand and 0.42 in non-dominant hand), indicating

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little agreement between the predicted and obtained values in both hands and

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concluding that the reference equations for HS evaluated had low predictive validity for

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a population of middle-aged and elderly Brazilian men.

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In the present study, HS proved to be significantly greater in the dominant hand. This

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finding can be corroborated by other studies on HS.27,29 In addition, the present results

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demonstrated that gender and anthropometric measurements of the hand influence the

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HS in dominant and non-dominant hands in healthy subjects. In relation to gender, our

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findings are in agreement with several studies which have shown that HS is higher in

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male when compared to female.22,23,25 Significant correlations were also verified among

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HS and anthropometric measurements of the hand in previous studies.41,42

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The clinical relevance of our data is clear since using absolute values for evaluating

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patients usually causes bias in the results. Adopting a reference equation for the

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correcting values for gender and anthropometric measurements allows a more

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adequately interpretation of the results, considering individual characteristics, facilitating

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more reliable comparisons between groups. Despite all efforts, there were some

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limitations. Only subjects with age between 20-60 years were included in the present

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study. Therefore, our reference equations cannot be applied in elderly people. The use

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of a convenience sample was another limitation, even though both the number of

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participants in each age range as well as the male-female proportion of subjects were

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carefully taken into consideration.

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Conclusion

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According to our results, it can be concluded that variability of the HS in healthy

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subjects can be explained by gender, forearm circumference, and hand length. A

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reference equation could be established based on these demographic and

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anthropometric variables. The equation might be feasible in clinical practice since it

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requires the evaluation of simple parameters. The predictive equations will help health

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professionals and researchers to better estimate the expected handgrip strength,

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improving the interpretation of the data.

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Conflict of interest statement: none declared

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This research did not receive any specific grant from funding agencies in the public,

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commercial, or not-for-profit sectors.

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Tables

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Table 1 Demographic and anthropometric characteristics of the study subjects (all

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sample and by gender) p-value

39.5 [29.3 – 49.8]

40 [29.3 – 49.8]

39 [29.3 – 49.5]

0.855

(21 – 57)

(21 – 57)

(23 – 56)

1.68 [1.58 – 1.72]

1.72 [1.69 – 1.78]

(1.47 – 1.88)

(1.56 – 1.88)

(1.47 – 1.74)

69.6 ± 12.5

77.7 ± 9.6

61.4 ± 9.2

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Weight (kg)

Female (n = 40)

BMI (kg/m2)

Dominant HL (cm)

(57 – 100)

(45 – 80)

24.8 ± 3.3

25.9 ± 2.4

23.8 ± 3.7

(17.9 – 34.2)

(21.4 – 29.4)

(17.9 – 34.2)

7.7 [6.9 – 8.5]

7.8 [6.8 – 8.6]

7.6 [7.1 – 8.3]

(5.3 – 11.1)

(5.3 – 10.1)

(5.3 – 11.1)

18 [17.5 – 19]

19 [18 – 19.5]

17.5 [16.6 - 18]

(15 – 21)

(16 – 21)

(15 – 19.5)

18 [17.5 – 19]

19 [18 – 19.5]

17.5 [17 - 18]

(15 – 22)

(16 – 22)

(15 – 19.5)

25 [22.5 – 26.9]

26.3 [25.6 – 27.9]

22.6 ± 2.2

(18.5 – 31)

(23 – 31)

(18.5 - 28)

24.5 [22 – 26.5]

26.5 [25 – 27.4]

22 [20.6 - 23]

(18.5 – 30.5)

(23 – 30.5)

(18.5 - 28)

34 [30 – 43.8]

43.5 [38 – 48]

30 [22.3 - 32]

(18 – 54)

(32 – 54)

(18 – 36)

32 [26 - 42]

42 [38 - 46]

26 [22 - 28]

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Non-Dominant HL (cm)

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Dominant FC (cm)

Non-Dominant FC (cm)

HSND (kg)

1.59 [1.55 – 1.67]

(45 – 100)

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HPA score

HSD (kg)

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Height (m)

Male (n = 40)

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Age (yrs)

Total group (n = 80)

<0.001*

<0.001*

0.005*

0.840

<0.001*

<0.001*

<0.001*

<0.001*

<0.001*

<0.001*

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(16 – 58)

(24 – 58)

(16 - 34)

Data are expressed as median [interquartile range 25-75%] or mean ± standard deviation, and

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range (minimum value – maximum value). P-value refers to the difference between male and

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female subjects. *p<0.05. n: number of subjects; yrs: years; m: meters; cm: centimeters; kg:

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kilograms; BMI: body mass index; HPA score: Baecke's habitual physical activity score; HL:

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hand length; FC: forearm circumference; HSD: handgrip strength in dominant hand; HSND:

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handgrip strength in non-dominant hand.

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Table 2 Handgrip strength of dominant and non-dominant hands distributed according

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to age group and gender Age group (yrs)

Male (n = 40) HSD (kg)

20 – 29

44.6 ± 6.0

HSND (kg)

41.4 ± 5.5*

26.9 ± 4.1

24.1 ± 4.6*

(32 – 50)

(22 – 32)

(18 – 32)

45.1 ± 6.8

28.7 ± 5

26.2 ± 3.9*

(34 – 54)

(34 – 58)

(22 – 36)

(20 – 32)

41.7 ± 4.4

39.2 ± 6.8*

28.8 ± 5.5

27.1 ± 5*

(34 - 48)

(24 – 46)

(20 – 36)

(20 – 34)

42.1 ± 7.1

40.2 ± 7.3*

26.7 ± 5.3

24.6 ± 4.2*

(30 – 52)

(18 – 34)

(16 - 29)

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50 - 59

HSD (kg)

45 ± 7.1

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40 - 49

Female (n = 40)

HSND (kg)

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(36 – 50) 30 - 39

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(32 – 54)

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Data are expressed as mean ± standard deviation, and range (minimum value – maximum

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value). *p<0.05 when compared to HSD. n: number of subjects; yrs: years; kg: kilograms; HSD:

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handgrip strength in dominant hand; HSND: handgrip strength in non-dominant hand.

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Table 3 – Pearson’s and Spearman’s correlation values of HS, age and anthropometric

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variables. HSD

p-value

HSND (n = 80)

-0.10

0.400

Height (m)

0.68

<0.001*

Weight (kg)

0.64

<0.001*

BMI (kg/m2)

0.30

0.007*

Dominant HW (cm)

0.72

<0.001*

0.67

<0.001*

-

0.71

<0.001*

<0.001*

-

-

-

0.68

<0.001*

<0.001*

-

-

-

0.71

<0.001*

0.66

<0.001*

-

-

-

-

0.68

<0.001*

0.66 0.72

TE D

-

M AN U

-

Non-Dominant FC (cm)

Non-Dominant FL (cm)

<0.001*

-

Non-Dominant HL (cm)

Dominant FL (cm)

0.68

0.004*

-

Dominant FC (cm)

0.629

0.32

Non-Dominant HW (cm) Dominant HL (cm)

-0.06

SC

Age (yrs)

RI PT

(n = 80)

p-value

*p < 0.05. n: number of subjects; yrs: years; m: meters; cm: centimeters; kg: kilograms; BMI:

339

body mass index; HPA score: Baecke's habitual physical activity score; HW: hand width; HL:

340

hand length; FC: forearm circumference; FL: forearm length; HSD: handgrip strength in

341

dominant hand; HSND: handgrip strength in non-dominant hand.

343 344 345 346

AC C

342

EP

338

ACCEPTED MANUSCRIPT

347

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348

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