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Original Article

Reference ranges of handgrip strength from 125,462 healthy adults in 21 countries: a prospective urban rural epidemiologic (PURE) study

Darryl P. Leong1,*, Koon K. Teo1, Sumathy Rangarajan1, V. Raman Kutty2, Fernando Lanas3, Chen Hui4, Xiang Quanyong5, Qian Zhenzhen6, Tang Jinhua7, Ismail Noorhassim8,
Khalid F AlHabib9, Sarah J. Moss10, Annika Rosengren11, Ayse Arzu Akalin12, Omar Rahman13, Jephat Chifamba14, Andrés Orlandini15, Rajesh Kumar16, Karen Yeates17, Rajeev Gupta18, Afzalhussein Yusufali19, Antonio Dans20, Álvaro Avezum21, Patricio Lopez-Jaramillo22, Paul Poirier23, Hosein Heidari24, Katarzyna Zatonska25, Romaina Iqbal26, Rasha Khatib27, Salim Yusuf1

Article first published online: 12 APR 2016

DOI: 10.1002/jcsm.12112

How to Cite

Leong, D. P., Teo, K. K., Rangarajan, S., Kutty, V. R., Lanas, F., Hui, C., Quanyong, X., Zhenzhen, Q., Jinhua, T., Noorhassim, I., AlHabib, K. F., Moss, S. J., Rosengren, A., Akalin, A. A., Rahman, O., Chifamba, J., Orlandini, A., Kumar, R., Yeates, K., Gupta, R., Yusufali, A., Dans, A., Avezum, Á., Lopez-Jaramillo, P., Poirier, P., Heidari, H., Zatonska, K., Iqbal, R., Khatib, R., and Yusuf, S. (2016) Reference ranges of handgrip strength from 125,462 healthy adults in 21 countries: a prospective urban rural epidemiologic (PURE) study. Journal of Cachexia, Sarcopenia and Muscle, 7: 535–546. doi: 10.1002/jcsm.12112.

Author Information

1

The Population Health Research Institute, McMaster University and Hamilton Health Sciences, Hamilton, ON, Canada

2

Health Action by People, ‘Chemmanam’, Navarangam Lane, Medical College Post Office, Trivandrum, India

3

Universidad de La Frontera, Chile

4

Medical Research & Biometrics Center, National Center for Cardiovascular Diseases, FuWai Hospital, Beijing, China

5

Jiangsu Provincial Center for Disease Control &12 Prevention, Nanjing City, China

6

Jiangxinzhou community health service center, Nanjing City, China

7

Xiaohang Hospital, Nanjing City, China

8

Universiti Kebangsaan Malaysia, Medical Center(UKMMC), Kuala Lumpur, Malaysia

9

Department of Cardiac Sciences, King Fahad Cardiac Center, College of Medicine, King Saud University, Riyadh, Saudi Arabia

10

North-West University, Physical activity, Sport and Recreation Research Focus Area, Faculty of Health Sciences, Potchefstroom, South Africa

11

Sahlgrenska University Hospital/Östra Hospital, Göteborg, Sweden

12

Department of Family Medicine and Department of Medical Education, Yeditepe University Medical Faculty, Atasehir, Istanbul, Turkey

13

Independent University, Bangladesh, Bangladesh

14

University of Zimbabwe College of Health Sciences, Department of Physiology, Harare

15

Estudios Clínicos Latino America, Rosario, Argentina

16

PGIMER School of Public Health, Chandigarh, India

17

Department of Medicine, Queen's University, Kingston, ON, Canada

18

Fortis Escorts Hospital, Jaipur, India

19

Hatta Hospital, Dubai Health Authority, Dubai

20

College of Medicine, University of the Philippines – Manila, Malate, Philippines

21

Dante Pazzanese Institute of Cardiology, São Paulo, Brazil

22

Fundacion Oftalmologica de Santander (FOSCAL), Universidad de Santander (UDES), Bucaramanga, Colombia

23

Institut universitaire de cardiologie et de pneumologie de Québec, Québec, Canada

24

Cardiac Rehabilitation Research Center, Isfahan University of Medical Sciences, Isfahan, Iran

25

Department of Social Medicine Medical University of Wroclaw, Poland

26

Departments of Community Health Sciences and Medicine, Aga Khan University, Pakistan

27

Institute of Community and Public Health, Birzeit University, Ramallah, Palestine

*Correspondence to: Darryl Leong, C3-106 DBRI Building, Hamilton General Hospital, 237 Barton Street East, Hamilton ON L8L 2X2, Canada: Tel: +1 905 521 2100, ext 40382; Fax: +1 905 297 3789, Email: leongd@phri.ca

Abstract

Background

The measurement of handgrip strength (HGS) has prognostic value with respect to all-cause mortality, cardiovascular mortality and cardiovascular disease, and is an important part of the evaluation of frailty. Published reference ranges for HGS are mostly derived from Caucasian populations in high-income countries. There is a paucity of information on normative HGS values in non-Caucasian populations from low- or middle-income countries. The objective of this study was to develop reference HGS ranges for healthy adults from a broad range of ethnicities and socioeconomically diverse geographic regions.

Methods

HGS was measured using a Jamar dynamometer in 125,462 healthy adults aged 35-70 years from 21 countries in the Prospective Urban Rural Epidemiology (PURE) study.

Results

HGS values differed among individuals from different geographic regions. HGS values were highest among those from Europe/North America, lowest among those from South Asia, South East Asia and Africa, and intermediate among those from China, South America, and the Middle East. Reference ranges stratified by geographic region, age, and sex are presented. These ranges varied from a median (25th–75th percentile) 50 kg (43–56 kg) in men <40 years from Europe/North America to 18 kg (14–20 kg) in women >60 years from South East Asia. Reference ranges by ethnicity and body-mass index are also reported.

Conclusions

Individual HGS measurements should be interpreted using region/ethnic-specific reference ranges.


Introduction

There is convincing evidence to indicate that handgrip strength (HGS) is of prognostic importance in the general population[1-6] and in those with existing disease.[7] HGS has prognostic value with respect to all-cause mortality,[3, 5, 6, 8, 9] cardiovascular mortality,[5, 10] and cardiovascular disease (CVD).[5] independently of recognised confounding factors, including dietary habits, physical activity, and socioeconomic status. Weak HGS is also associated with high case-fatality rates in individuals who develop any of a range of major illnesses,[5] suggesting that low muscle strength may be an important indicator of vulnerability to disease and of frailty. Moreover, HGS is rapid and simple to measure, and is inexpensive. It is therefore appealing as a tool to stratify an individual's risk of developing CVD, or of susceptibility to death from an incident illness. HGS correlates closely with measures of muscle strength from other muscle groups, including the lower limbs.[11, 12] Its prognostic value, the simplicity of measurement with minimal training, portability, and low cost make it an attractive clinical test to evaluate an individual's overall health in clinical or epidemiologic settings. HGS evaluation is a core part of the clinical evaluation of frailty.[13] HGS measurement is not, however, in widespread use as a risk-stratifying tool.

The lack of globally applicable reference ranges for HGS may account at least in part for its failure to be adopted clinically. Reference ranges for HGS have been reported in a number of studies, however the large majority of these studies have been undertaken in convenience samples of individuals of predominantly European ethnicity and in high-income countries.[14-21] There is a paucity of normative, population-derived data on HGS, particularly from non-Caucasian populations in low- to middle-income countries.[8, 22, 23] Given that HGS represents the product of age, general health, and comorbid conditions, an understanding of what constitutes “normal” HGS in different ethnic groups and geographic regions is important. Therefore, the objective of this study was to develop reference HGS ranges for healthy adults from a broad range of ethnicities and socioeconomically diverse geographic regions.

The Prospective Urban Rural Epidemiology (PURE) study is a prospective cohort study of in excess of 160,000 community-based adults from 21 low-, middle- and high-income countries.[24] The present study is an analysis of the 125,462 healthy PURE participants from these 21 countries who had HGS measured.

Methods

Study design and participants

The design of the PURE study have been described previously.[24] In brief, participating countries were selected to represent significant socioeconomic heterogeneity. For reasons of feasibility, proportionate sampling of all countries worldwide, or of regions within countries, was not undertaken. Countries selected included Canada, Saudi Arabia, Sweden, United Arab Emirates (high-income countries), Argentina, Brazil, Chile, China, Colombia, Iran, Malaysia, Poland, South Africa, Turkey, Philippines (middle-income countries), Bangladesh, India, Pakistan, Palestine, Tanzania, and Zimbabwe (low-income countries). Within both urban and rural communities in each country, households were selected to achieve representative sampling within the community. pecific methods used to approach households may have varied according to country context. For example, in low-income settings, a community announcement may be made through a community leader, followed by door-to-door visits. In high-income settings, initial approaches may have been made by telephone. Guidelines for the selection of countries, communities, households, and individuals to participate are presented in the Appendix, Table A1. Household members were invited to participate if aged 35-70 years.

Procedures

Trained study personnel administered a standardised set of questions to participants. These questions elicited self-reported ethnicity, demographics, cardiovascular risk factors, co-morbid conditions, education status, employment status, physical activity levels, tobacco and alcohol use, and dietary patterns. Study personnel also measured participant anthropometrics (height, weight, and waist circumference). Education was classified as up to secondary school, secondary school, and university/trade school.

HGS was measured using a Jamar dynamometer (Sammons Preston, Bolingbrook, IL, USA) according to a standardised protocol.[25] The arm was positioned at the side of the body and the dynanometer held with elbow flexed to 900. The participant was asked to squeeze the device as hard as possible for 3 seconds. The measurement was repeated twice more at intervals of at least 30 seconds. For the first study participants, three measurements were made from the participant's non-dominant hand. During the course of the study, the protocol was amended so that three measurements were made from both hands of each participant. For the present analysis, we used only the maximum values obtained from each hand. Overall HGS was then calculated as the mean of non-dominant and dominant hand HGS.[5] To permit estimation of overall HGS in participants where values were missing for one hand but present for the other hand, we imputed values for the missing hand using the coefficient and constant from the linear regression of non-dominant and dominant hand HGS.[5] We also present reference ranges where HGS is the maximum value obtained from both hands (Appendix).[26]

The PURE study was approved by the appropriate research ethics committees and has been performed in accordance with the ethical standards laid down in the 1964 Declaration of Helsinki and its later amendments, and also in accordance with relevant national laws governing human research ethics.

Statistical analysis

For the present analysis, because we sought to describe reference ranges among healthy individuals, participants were not included if HGS was not measured in either hand, sex was not recorded, or if the participant had a history of cancer, chronic obstructive pulmonary disease, tuberculosis, Chagas disease, human immunodeficiency virus, stroke, coronary artery disease, heart failure, or diabetes. Countries were grouped to permit adequate participant numbers for stratified analyses. Canada, Sweden, Poland, and Turkey were considered Europe/North America; Argentina, Brazil, Colombia, and Chile were considered South America; United Arab Emirates, Saudi Arabia, Iran, and Palestine were considered Middle East; South Africa, Tanzania, and Zimbabwe were considered Africa; Malaysia and Philippines were considered South East Asia; Pakistan, India, and Bangladesh were considered South Asia; and China was analysed individually. Within each region, the median (25th–75th percentile) HGS was calculated stratified by age (35–40 years, 41–50 years, 51–60 years, and 61–70 years) and sex. The reference range is considered the 25th-75th percentile of HGS within each stratum. The analysis was repeated stratifying by ethnicity and by body-mass index. The expected HGS as a function of age, stratified by country and sex, was estimated by restricted cubic spline regression with four knots. We performed sensitivity analyses excluding participants who reported difficulty using their fingers to grasp or handle.

Results

The proportion of those eligible for the PURE study that provided consent was 78%. Of 189,990 individuals who did consent to participate, 31,109 had a history of an illness that necessitated exclusion from this analysis. A further 33,419 participants were not included in this analysis because HGS was not measured. Therefore the present study is based on 125,462 individuals. Participant characteristics are displayed in Table 1. Education levels were highest in Europe/North America and lowest in Africa. Men had higher employment rates than women, and employment rates were lowest in Africa. Physical activity levels were lowest in the Middle East, and were also low in South East Asia and China. Dietary caloric intake was lowest in Africa, and the percentage of caloric intake from protein was lowest in South Asia, followed by Africa. Europeans were on average tallest, heaviest, and exhibited the largest waist circumference.

Table 1. Participant characteristics stratified by geographic region. Displayed are median (25th–75th percentile) values, mean ± standard deviation values, or column percentages
CharacteristicEurope/North AmericaSouth AmericaMiddle EastAfricaSouth East AsiaSouth AsiaChina
WomenMenWomenMenWomenMenWomenMenWomenMenWomenMenWomenMen
N9362722112,163770442413901302212826002409714,72910,97623,88416,878
Age, years

51

(44–58)

52

(44–59)

50

(43–58)

50

(43–59)

45

(39–52)

46

(40–53)

49

(41–57)

50

(42–58)

49

(42–57)

52

(44–59)

45

(38–54)

47

(40–56)

50

(42–57)

51

(42–58)

Rural location2930414943395352555554535154
Education              
Primary2218586159357169393760443727
Secondary2828262230382829444331395056
Post-secondary5054161711271217209171317
Employed6874607046831014427150825368
Physical activity              
Low810101524281615142017201319
Medium3934352954363833433439274439
High5356555622364652434644534342
Tobacco use              
Former27351630<11229218<18<19
Current14231925<1302247332944352
Never5942654599587644955091489739
Alcohol use              
Former57612023925<1516
Current60723362011950510<122546
Never35216126100977841938599739448
Daily caloric intake, kcal

1941

(1513–2481)

2379

(1852–3004)

2026

(1561–2562)

2216

(1723–2824)

2099

(1622–2677)

2332

(1879–2887)

1848

(1337–2646)

1925

(1365–2708)

2462

(1661–3417)

2535

(1745–3674)

1869

(1468–2477)

2164

(1643–2880)

1784

(1423–2198)

2125

(1704–2621)

Percentage of caloric intake from protein16.5 ± 2.816.3 ± 2.716.9 ± 3.516.4 ± 3.417.1 ± 2.417.2 ± 2.213.6 ± 3.013.2 ± 3.116.7 ± 3.416.6 ± 3.411.5 ± 1.911.5 ± 2.015.5 ± 2.814.8 ± 2.9
Height, cm161 ± 7.2175 ± 7.8156 ± 7.0169 ± 7.6156 ± 6.2170 ± 6.9157 ± 6.6167 ± 7.2152 ± 6.4163 ± 6.9153 ± 6.6165 ± 7.2156 ± 5.8167 ± 6.5
Weight, kg72 ± 1585 ± 1569 ± 1578 ± 1771 ± 1578 ± 1570 ± 2062 ± 1562 ± 1469 ± 1554 ± 1360 ± 1460 ± 1169 ± 12
Waist circumference, cm85 ± 1395 ± 1289 ± 1394 ± 1289 ± 1391 ± 1285 ± 1579 ± 1183 ± 1289 ± 1275 ± 1379 ± 1379 ± 1083 ± 10
Body-mass index, kg/m227.7 ± 6.0427.7 ± 5.6028.2 ± 5.8527.5 ± 5.0429.3 ± 5.7627.0 ± 4.8228.3 ± 7.6922.0 ± 5.3426.4 ± 5.42

25.8±

4.77

23.2±

5.33

22.1±

4.44

24.6±

4.07

24.4±

3.83

HGS reference ranges by geographic region, age stratum, and sex are presented in Table 2. HGS among men exceeded HGS in women, and there was a progressive decline in HGS with increasing age. Within each age and sex stratum, up to 33% variation in median HGS values was observed among the different regions. Highest HGS values were found in Europe/North America, and lowest values in Africa, South Asia, and Southeast Asia. Average HGS stratified as a function of age, stratified by sex and geographic region is displayed in Figure 1. Expected HGS together with 95% confidence limits as a function of age, stratified by sex and country are displayed in Figure 2. HGS reference ranges by ethnicity, age stratum, and sex are presented in the Table 3. The observed values of HGS in each ethnic group reflected the geographic region where the ethnic group predominates. The median, 25th and 75th percentiles for HGS stratified by sex, age, geographic region, and body-mass index are presented in the Appendix Table A2. For this analysis, age was dichotomized to ≤50 years and >50 years, and body-mass index was categorized as underweight (body-mass index <18.5 kg/m2), healthy weight (body-mass index 18.5 to <25 kg/m2), overweight (body-mass index 25 to <30 kg/m2), and obese (body-mass index ≥30 kg/m2). This analysis suggests a positive association between HGS and body-mass index, although the relationship was less pronounced or even reversed in obese individuals.

Table 2. Median (25th–75th percentile) handgrip strength (HGS) in kg, stratified by age, sex, and region
RegionHandAge 35-40 yearsAge 41-50 yearsAge 51-60 yearsAge 61-70 years
WomenMenWomenMenWomenMenWomenMen
Europe/North AmericaAverage

30 (26–35) n = 1332

50 (43–56) n = 897

30 (25–34) n = 3195

49 (42–56) n = 2365

27 (23–31) n = 3110

46 (39–52) n = 2512

25 (21–29) n = 1725

42 (36–47) n = 1447

 Dominant hand

31 (26–36) n = 1332

51 (44–58) n = 896

30 (26–35) n = 3190

50 (43–57) n = 2363

28 (24–32) n = 3100

47 (40–54) n = 2509

26 (22–30) n = 1721

42 (36–48) n = 1445

 Non-dominant hand

29 (24–34) n = 1329

48 (41–55) n = 896

29 (24–33) n = 3182

48 (42–54) n = 2358

26 (22–30) n = 3091

45 (38–51) n = 2504

24 (20–28) n = 1713

40 (34–46) n = 1434

South AmericaAverage

29 (23–33) n = 2222

45 (39–52) n = 1321

27 (21–31) n = 4152

43 (37–50) n = 2662

25 (21–29) n = 3645

41 (33–46) n = 2196

23 (19–27) n = 2144

37 (31–42) n = 1525

 Dominant hand

32 (28–36) n = 353

50 (43–55) n = 283

31 (28–35) n = 816

46 (41–52) n = 661

29 (26–32) n = 809

45 (40–50) n = 619

27 (24–30) n = 398

41 (36–46) n = 387

 Non-dominant hand

27 (22–32) n = 2218

44 (38–50) n = 1318

26 (20–30) n = 4142

42 (36–49) n = 2657

24 (20–29) n = 3637

40 (32–45) n = 2190

22 (18–26) n = 2140

36 (30–40) n = 1524

Middle EastAverage

26 (22–30) n = 1372

45 (40–51) n = 1042

25 (22–29) n = 1625

43 (38–48) n = 1646

23 (20–27) n = 886

40 (35–46) n = 791

21 (18–24) n = 358

35 (31–40) n = 422

 Dominant hand

27 (22–30) n = 1349

46 (40–52) n = 1032

26 (22–30) n = 1594

44 (38–49) n = 1635

24 (20–28) n = 873

41 (36–46) n = 790

22 (18–25) n = 347

36 (31–40) n = 418

 Non-dominant hand

25 (21–29) n = 1369

44 (38–50) n = 1040

25 (20–29) n = 1615

42 (36–48) n = 1632

23 (20–26) n = 881

40 (34–45) n = 789

20 (18–24) n = 353

34 (30–40) n = 419

AfricaAverage

21 (13–30) n = 705

37 (26–44) n = 255

24 (14–30) n = 985

38 (26–44) n = 393

20 (11–27) n = 844

32 (22–41) n = 386

18 (10–25) n = 488

30 (21–38) n = 248

 Dominant hand

21 (13–30) n = 689

38 (28–46) n = 248

24 (14–30) n = 926

38 (24–44) n = 383

19 (11–26) n = 779

32 (21–40) n = 352

18 (10–25) n = 471

30 (21–39)n = 236

 Non-dominant hand

21 (13–30) n = 674

36 (26–44) n = 249

23 (14–30) n = 945

36 (26–44) n = 385

20 (11–26) n = 770

32 (21–40) n = 377

20 (11–24) n = 425

30 (20–38) n = 243

South East AsiaAverage

23 (19–27) n = 1091

40 (34–44) n = 562

22 (19–26) n = 2234

37 (32–42) n = 1320

20 (17–23) n = 1739

33 (29–38) n = 1331

18 (14–21) n = 938

29 (24–33) n = 884

 Dominant hand

24 (20–28) n = 1091

40 (34–46) n = 561

24 (20–28) n = 2232

38 (33–44) n = 1320

21 (18–24) n = 1735

34 (30–40) n = 1330

18 (15–22) n = 937

30 (24–34) n = 883

 Non-dominant hand

22 (18–26) n = 1089

38 (32–42) n = 560

22 (18–25) n = 2226

36 (30–40) n = 1316

19 (16–22) n = 1716

32 (28–37) n = 1321

18 (14–20) n = 902

28 (22–32) n = 877

South AsiaAverage

23 (19–27) n = 5662

35 (31–41) n = 3279

21 (18–25) n = 4729

33 (29–39) n = 3593

19 (16–23) n = 2833

31 (25–35) n = 2505

19 (15–23) n = 1505

27 (22–32) n = 1599

 Dominant hand

22 (18–26) n = 1502

36 (30–42) n = 910

21 (17–24) n = 1403

33 (28–40) n = 1036

20 (16–22) n = 839

32 (25–37) n = 727

19 (14–22) n = 435

28 (22–34) n = 455

 Non-dominant hand

22 (18–26) n = 5652

34 (30–40) n = 3269

20 (17–24) n = 4711

32 (28–38) n = 3587

18 (15–22) n = 2815

30 (24–34) n = 2503

18 (14–22) n = 1495

26 (21–30) n = 1594

ChinaAverage

28 (24–32) n = 4774

45 (40–50) n = 3197

28 (23–32) n = 7773

43 (37–48) n = 5153

26 (22–29) n = 7749

40 (34–45) n = 5363

23 (20–27) n = 3588

36 (31–41) n = 3165

 Dominant hand

30 (25–33) n = 4774

46 (40–52) n = 3196

28 (24–32) n = 7771

44 (38–50) n = 5150

26 (22–30) n = 7747

41 (35–46) n = 5360

24 (20–28) n = 3585

37 (32–42) n = 3162

 Non-dominant hand

27 (23–31) n = 4757

43 (38–48) n = 3191

26 (22–30) n = 7743

41 (36–47) n = 5131

25 (20–29) n = 7691

39 (33–44) n = 5347

22 (18–26) n = 3551

35 (30–40) n = 3150

Figure 1.

Figure 1.

Average handgrip strength as a function of age. Nth = North; Sth = South.

Figure 2.

Figure 2.

Estimated handgrip strength (solid line) as a function of age. The dotted curves represent ±1 standard deviation, and the dashed curves represent ±2 standard deviations.

Table 3. Median (25th–75th percentile) overall handgrip strength (in kg) stratified by age, sex, and ethnicity
EthnicityAge 35-40 yearsAge 41-50 yearsAge 51-60 yearsAge 61-70 years
WomenMenWomenMenWomenMenWomenMen
South Asian23 (19–27) n = 572335 (31–41) n = 332621 (18–25) n = 483334 (29–39) n = 367419 (16–23) n = 290031 (25–35) n = 256919 (15–23) n = 153327 (22–32) n = 1630
Chinese28 (24–32) n = 471645 (40–50) n = 317528 (23–32) n = 785443 (37–48) n = 517426 (22–29) n = 783240 (34–45) n = 541623 (20–27) n = 360436 (31–41) n = 3181
Malaysian23 (19–27) n = 102140 (34–45) n = 51823 (19–26) n = 207337 (32–42) n = 121420 (17–24) n = 162933 (29–38) n = 1236

18 (14–21) n = 891

29 (24–34) n = 841
Persian27 (23–31) n = 78147 (42–52) n = 60126 (22–30) n = 102544 (38–49) n = 106824 (20–27) n = 61140 (36–46) n = 551

22 (19–25) n = 256

35 (31–41) n = 290
Arab24 (21–29) n = 59743 (37–48) n = 45025 (21–29) n = 62142 (37–47) n = 62123 (20–27) n = 29040 (34–45) n = 263

20 (17–23) n = 106

34 (30–38) n = 138
African22 (13–31) n = 73338 (27–45) n = 26824 (14–30) n = 104038 (26–44) n = 42020 (11–27) n = 91433 (23–41) n = 428

18 (10–25) n = 535

31 (22–38) n = 280
European30 (26–35) n = 106650 (43–56) n = 69430 (25–35) n = 245649 (42–56) n = 176128 (23–32) n = 236446 (40–52) n = 184925 (21–29) n = 134441 (35–47) n = 1112
Latin American29 (23–33) n = 214345 (39–52) n = 128727 (22–31) n = 399943 (37–50) n = 259125 (21–30) n = 350441 (34–46) n = 211123 (19–27) n=202537 (31–42) n=1447

Repeating the main analysis after excluding participants who reported difficulty using their fingers to grasp or handle did not substantially change the medians, 25th and 75th percentile values in each stratum (findings not presented).

Discussion

This study has reported reference ranges for HGS derived from healthy community-dwelling adults aged 35-70 years in 21 countries of all income strata. The key finding from this analysis is that median HGS differs among the geographic regions and ethnic groups studied. Therefore individual HGS measurements should be interpreted using region/ethnic-specific reference ranges.

Interpretation of HGS measurement

Numerous studies have reported reference ranges for HGS measurement (Table 4). These studies have each involved populations from single countries, and have employed different approaches to measuring and reporting HGS ranges. The large majority of reports are from high-income countries, and from populations of predominantly European ethnicity. There is a paucity of data from low-income countries, despite the fact that HGS measurement as an inexpensive risk-stratifying test may be best suited to these resource-challenged settings.

Table 4. Representative studies reporting reference ranges for handgrip strength among healthy adults or adults from the general population
StudyPopulationnAge range (years)DynamometerHand
Frederiksen et al.[15]Danes; general population834245–102Smedley (TTM; Tokyo, Japan)Maximal value from both
Tveter et al.[16]Norwegians; volunteers from work places, schools, community centres37018–90Average from both
Vaz et al.[23]Indians; university students and faculty10245–67Harpenden (CMS Weighing Equipment, London, UK); Smedley (TTM, Tokyo, Japan)Non–dominant
Mathiowetz et al.[14]Americans; volunteers from shopping centres, a rehabilitation centre, a university62820–75Jamar (Jackson, MI, USA)Both
Ribom et al.[17]Swedish men; general population99970–80Jamar (Jackson, MI, USA)Maximal value from both
Massy–Westropp et al.[18]Australian; general population2678>20JamarBoth
Schlüssel et al.[22]Brazil; general population3050>20Jamar (Sammons–Preston, Korea)Maximal value from both
Lauretani et al.[19]Italy; general population1030>20
Günther et al.[20]Germany; volunteers from workplaces, retirement homes76920–95NexGen (Ergonomics Inc, Quebec, Canada)Average of each hand
Snih et al.[8]Mexican Americans in southern states; general population2488≥65 yearsJamar (J.A.Preston Corp., Clifton, NJ, USA)Dominant hand
Kenny et al.[21]Irish; general population5819≥50 yearsBaseline (Fabrication Enterprises Inc., White Plains, NY, USA)Maximum value from both

The values of HGS observed in Europe and North America, and South America in the present study are similar to those reported in other studies of individuals from European countries,[15] the US,[14] and Brazil[22] respectively. This finding confirms the reproducibility of HGS measurement from an epidemiologic perspective, and provides face validity to the PURE data. Our study extends on existing literature to report reference ranges for HGS from seven geographic regions around the world, many of which have not previously been studied. We found considerable heterogeneity in median HGS among healthy adults from these different regions. This finding is an important one because we have previously reported that HGS is predictive of mortality and CVD independently of country income.[5] The present study will allow the measurement of an individual's HGS to be placed into their regional context.

Ethnic variations in muscle strength

Our findings are consistent with previous work that demonstrates variations in skeletal muscle mass from individuals of different ethnicities.[27] Taken together, these findings raise the hypothesis that genetically mediated ethnic differences in muscle strength exist. In addition, variations in muscle strength between people from different countries may be attributed in part to differences in socio-economic status. In a Spanish study of 1785 adolescents, a modest association between socio-economic status and muscle strength was observed.[28] A more profound difference in socio-economic status (in absolute terms) among participants from countries of contrasting income may therefore be expected to be associated with a larger differences in HGS. It is also likely that differences in muscle strength among diferent countries reflects variation in dietary patterns. There is a well-recognized association between dietary protein intake, which varies among different countries, and muscle strength.[29]

Remaining uncertainties

While we have speculated about potential reasons for the differences in HGS among different countries and ethnicities, the nature of these differences has not been resolved. It is also uncertain which reference range is best applied to individuals who migrate from one country to another, or who are from an ethnic minority within a particular country. These uncertainties are related to a lack of understanding of what constitute the most important determinants of muscle strength, whether ethnic and genetic factors are more important than environmental factors, and what duration and extent of exposure to environmental influences is needed to cause change in an individual's physical characteristics. While it is likely that differences in dietary quality and physical activity levels, as examples of environmental determinants of HGS, account at least in part for the variation in HGS observed among different regions, we do not present reference ranges adjusted for these factors because in a given individual, it is difficult to interpret their observed HGS when compared with the expected HGS of an individual with a globally average diet and physical activity level.

Limitations

Individuals over the age of 70 years and younger than 35 years were not included, so this study is unable to report reference ranges for HGS outside this range. Eligible individuals who declined to participate in PURE, or in whom HGS was not measured, and individuals whose HGS may have been influenced by musculoskeletal diseases of the hand, may have introduced bias or errors.

Conclusion

The expected HGS measurement for an individual of a given age and sex varies according to their geographic region and/or ethnicity. HGS measurements should be interpreted with awareness of such contextual factors. Further research is needed to evaluate possible determinants of muscle strenth in order to understand the factors that underlie the differences in muscle strength among different healthy populations.

Acknowledgements

Dr. Leong is supported by the E.J. Moran Campbell Department of Medicine Internal Career Award, McMaster University. Dr. Yusuf is funded by the Marion Burke Chair of the Heart and Stroke foundation of Canada. Dr. AlHabib is supported by the Deanship of Scientific Research at King Saud University, Riyadh, Saudi Arabia (Research group number: RG -1436-013). The authors certify that they comply with the ethical guidelines for authorship and publishing of the Journal of Cachexia, Sarcopenia and Muscle.[30]

Conflict of interest statement

Darryl P. Leong; Koon K. Teo; Sumathy Rangarajan; V. Raman Kutty; Fernando Lanas; Chen Hui; Xiang Quanyong; Qian Zhenzhen; Tang Jinhua; Ismail Noorhassim; Khalid F AlHabib; Sarah J. Moss; Annika Rosengren; Ayse Arzu Akalin; Omar Rahman; Jephat Chifamba; Andrés Orlandini; Rajesh Kumar; Karen Yeates; Rajeev Gupta; Afzalhussein Yusufali; Antonio Dans; Álvaro Avezum; Patricio Lopez-Jaramillo; Paul Poirier; Hosein Heidari; Katarzyna Zatonska; Romaina Iqbal; Rasha Khatib; and Salim Yusuf declare that they have no conflict of interest.

Appendix Appendix

Table A1. Guidelines for the selection of countries, communities, households and individuals recruited in PURE
Countries
1. HIC, MIC and LIC, with the bulk of the recruitment from low- and middle-income regions.
2. Committed local investigators with experience in recruiting for population studies.
Communities
1. Select both urban and rural communities. Use the national definition of the country to determine urban and rural communities.
2. Select rural communities that are isolated (distance of >50 km or lack easy access to commuter transportation) from urban centers. However, consider ability to process bloods samples, eg, villages in rural developing countries should be within 45-min drive of an appropriate facility.
3. Define community to a geographical area, eg, using postal codes, catchment area of health service/clinics, census tracts, areas bordered by specific streets or natural borders such as a river bank.
4. Consider feasibility for long-term follow-up, eg, for urban communities, choose sites that have a stable population such as residential colonies related to specific work sites in developing countries. In rural areas, choose villages that have a stable population. Villages at greater distance from urban centers are less susceptible to large migration to urban centers.
5. Enlist a community organization to facilitate contact with the community, eg, in urban areas, large employers (government and private), insurance companies, club, religious organizations, clinic or hospital service regions. In rural areas, local authorities such as priests or community elders, hospital or clinic, village leader, or local politician.
Individual
1. Broadly representative sampling of adults 35 to 70 years within each community unit.
2. Consider feasibility for long-term follow-up when formulating community sampling framework, eg, small percentage random samples of large communities may be more difficult to follow-up because they are dispersed by distance. In rural areas of developing countries that are not connected by telephone, it may be better to sample entire community (ie, door-to-door systematic sampling).
3. The method of approach of households/individuals may differ between sites. In MIC and HIC, followed up by phone contact may be the practical first means of contact. In LIC, direct household contact through household visits may be the most appropriate means of first contact.
4. Once recruited, all individuals are invited to a study clinic to complete standardized questionnaires and have a standardized set of measurements.
Table A2. Median (25th-75th percentile) overall handgrip strength stratified by sex, age, body-mass index, and geographic region
Women
SE = Southeast. Underweight = body-mass index (BMI) <18.5kg/m2; healthy weight = BMI 18.5 to <25kg/m2; overweight = BMI 25 to <30kg/m2; obese = BMI≥30kg/m2.
Region≤50 years>50 years
UnderweightHealthy weightOverweightObeseUnderweightHealthy weightOverweightObese
Europe/ North America

28 (24-32) n=56

31 (26-35) n=1911

30 (26-34) n=1307

29 (24-34) n=1230

25 (19-31) n=39

27 (23-31) n=1601

27 (22-30) n=1740

26 (21-30) n=1438

South America

25 (20-31) n=75

27 (23-31) n=2140

27 (21-31) n=2294

28 (22-33) n=1803

22 (19-27) n=66

23 (20-28) n=1508

23 (20-29) n=2139

24 (20-29) n=2011

Middle East23 (20-25) n=35

25 (22-29) n=629

26 (22-30) n=1183

25 (22-30) n=1134

21 (18-24) n=14

21 (18-25) n=215

23 (20-26) n=495

23 (20-27) n=508

Africa23 (19-27) n=96

25 (16-30) n=546

23 (13-30) n=413

20 (12-30) n=605

21 (13-27) n=93

22 (12-27) n=410

20 (10-27) n=330

15 (10-25) n=474

SE Asia21 (18-25) n=126

22 (19-26) n=1246

23 (19-27) n=1169

24 (20-28) n=750

17 (13-20) n=120

19 (15-22) n=2046

20 (16-23) n=982

19 (16-23) n=547

South Asia21 (18-25) n=2096

23 (19-27) n=4621

23 (19-27) n=2591

23 (19-27) n=1010

18 (14-21) n=820

19 (15-23) n=2046

20 (17-25) n=1020

21 (17-25) n=426

China26 (21-29) n=304

28 (23-31) n=7510

29 (24-33) n=3882

29 (25-33) n=791

21 (17-25) n=350

24 (21-28) n=5792

26 (22-30) n=4199

25 (21-30) n=960

Men
Region≤50 years>50 years
UnderweightHealthy weightOverweightObeseUnderweightHealthy weightOverweightObese
Europe/ North America

32 (26-41) n=10

48 (41-54) n=951

49 (43-56) n=1544

50 (44-58) n=739

33 (29-47) n=9

43 (38-49) n=1007

45 (38-51) n=1938

44 (38-51) n=994

South America

37 (33-43) n= 33

41 (35-47) n=1255

45 (39-51) n=1720

46 (40-52) n=928

33 (30-39) n=48

36 (31-42) n=1081

40 (33-45) n=1584

41 (34-47) n=975

Middle East

38 (35-41) n=47

43 (38-49) n=876

44 (39-50) n=1144

44 (38-49) n=603

34 (31-39) n=24

37 (32-42) n=399

39 (34-45) n=504

39 (34-46) n=278

Africa

35 (29-42) n=146

38 (26-44) n=396

36 (22-48) n=68

29 (15-45) n=30

31 (26-36) n=121

32 (22-41) n=363

34 (20-45) n=88

27 (17-36) n=48

SE Asia

34 (28-38) n=51

36 (31-41) n=760

39 (34-44) n=747

39 (33-44) n=299

28 (21-32) n=105

31 (25-36) n=972

32 (28-38) n=789

33 (29-39) n=328

South Asia

31 (27-37) n=1481

35 (30-39) n=3600

36 (31-41) n=1474

37 (29-41) n=265

25 (21-31) n=1040

30 (25-35) n=2115

32 (27-37) n=742

31 (25-37) n=181

China

39 (34-44) n=190

42 (37-48) n=4597

45 (40-51) n=2980

46 (40-51) n=539

33 (28-39) n=298

38 (32-43) n=4790



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