Blackwell Science, LtdOxford, UKGGIGeriatrics and Gerontology International1444-15862005 Blackwell Science Asia Pty LtdMarch 2005515965Original ArticleGender differences in motor performanceAS Buchman et al.
Geriatrics and Gerontology International 2005; 5: 59–65
ORIGINAL ARTICLE
Gender differences in upper extremity motor performance of older persons Aron S Buchman,1,2 Robert S Wilson,1,3 Julia L Bienias1,4 and David A Bennett1,2 1
Rush Alzheimer’s Disease Center, Rush University Medical Center, 2Department of Neurological Sciences, Rush University Medical Center, 3Department of Psychology, Rush University Medical Center and 4 Rush Institute for Healthy Aging, Department of Internal Medicine, Rush University Medical Center, Chicago, IL, USA
Background: Motor performance declines with age. Although gender differences in motor strength and speed have been widely reported, the extent to which these differences are maintained in old age has not been well established. Methods: Upper extremity motor performance was assessed in 234 men and 530 women Catholic clergy members aged 65 years or older with no clinical evidence of dementia who were participants in the Religious Orders Study. As part of a uniform clinical evaluation, upper extremity motor performance including strength (grip and pinch dynamometry), movement speed including finger tapping and Purdue pegboard and muscle bulk of the arm were collected. Results: Men were stronger than women at all ages but this difference became less prominent at older ages. Women scored higher on the Purdue Pegboard than men whereas men had faster maximal finger tapping rates than women. Gender differences in speed were not modified by age. Men had greater muscle bulk than women at all ages and these differences were not modified by age. These relationships were not modified by participants with a clinical diagnosis of Parkinson’s disease or stroke or by hormone replacement therapy in women. Conclusions: Gender differences in upper extremity speed and muscle bulk appear to be relatively stable with increasing age, whereas gender differences in strength were reduced in the oldest old. Longitudinal studies are needed to determine if men and women differ in the rate of decline of strength in old age. Keywords: aging, gender, movement speed, muscle bulk, strength.
Introduction Older people, on average, perform worse on tests of motor function than younger people. For example muscle strength in 80-year-old people is only 30%-50% of the strength of 20-year-olds.1,2 In an 80-year-old, the
Accepted for publication 31 May 2004. Correspondence: Dr Aron S. Buchman, MD, Rush University Medical Center, Rush Alzheimer’s Disease Center, Armour Academic Facility, Suite #1027B, 600 South Paulina Street, Chicago, IL 60612, USA. Email: [email protected]
speed of even simple movements such as the maximal rate of finger tapping or comfortable walking speed is 30% lower than a 20-year-old.3 Walking speed is reduced to the degree that in a recent large cohort of nonagenarians, less than 7% of the participants walked faster than one meter per second, the minimal speed necessary to cross at a signaled intersection.4 Older people with impaired motor function have been found to be at increased risk for disability, common neurologic diseases such as Alzheimer’s disease and death.5,6 Motor dysfunction is a dominant feature of frailty in the elderly which predicts disability and mortality.7 These findings underscore the importance of 59
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motor function for the maintenance of health and independence in old age. Men and women differ in motor function, although most data are from young or middle-aged adults. On average, men are stronger than women. Men also tend to walk more quickly than women, but on measures of fine motor speed such as the Purdue pegboard, women are faster than men. The extent to which gender differences are maintained in old age is not clear since few large studies have had adequate numbers of older men and women of comparable age. In this study we examined gender and age differences on several measures of motor function in the upper extremities in older participants free of dementia. We used data from the Religious Order Study, a clinicalpathologic study of aging and Alzheimer’s disease in Catholic nuns, priests and brothers. We assessed upper extremity strength using grip and pinch dynamometry, movement speed with a finger tapping test and the Purdue Pegboard and muscle bulk of the arm. In analyses, we first examined the associations of age and gender with each motor measure. We then tested whether gender modified the association of age with strength, movement speed or muscle bulk.
Methods Participants All subjects were participants in the Religious Orders Study, an ongoing longitudinal study of aging and Alzheimer’s Disease (AD). Older Catholic nuns, priests, and brothers were recruited from about 40 groups across the United States (see Acknowledgments). The study was approved by the Institutional Review Board of Rush University Medical Center. Eligibility for these analyses required an age of 65 years or older and absence of a clinical diagnosis of dementia. Each person underwent a uniform structured evaluation, which included a medical history, neurological examination, assessment of cognitive function, and review of brain scan when available. On the basis of this evaluation, an experienced neurologist or geriatrician diagnosed dementia and other common neurologic conditions affecting cognitive or physical function. The diagnosis of dementia followed the criteria of the joint working group of the National Institute of Neurological and Communicative Disorders and Stroke and the Alzheimer’s Disease and Related Disorders Association (NINCDS/ADRDA). Details of the clinical evaluation have been previously reported.8–10 Clinical evaluations for the study commenced in January 1994 and 942 participants underwent baseline evaluation through to June 2002 when the data set was frozen for analyses. The quantitative assessments of motor function on which we report in these analyses were added beginning Octo60
ber 1996. Of 872 people undergoing quantitative motor testing since 1996, 764 (88%) were free of dementia and were ≥ 65 years old and eligible for these analyses.
Strength Grip strength was measured using the Jamar hydraulic hand dynamometer (Lafayette Instruments, Lafayette, IN, USA). This sealed hydraulic system features a dualscale readout that displays isometric grip force from 0 to 90 kg. Pinch strength was measured using the Jamar hydraulic pinch dynamometer, which measures pinch strength from 0 to 20 kg (Lafayette Instruments, Lafayette, IN, USA). Two trials of grip and pinch strength were obtained for each hand. The four trials were averaged together to yield measures of grip and pinch strength. A composite score was created by converting grip and pinch measures to z scores and then computing the average of the z scores.
Movement speed Using the Purdue Pegboard the number of pegs that could be placed in 30 s was recorded. Two trials were recorded for each hand. The four trials were averaged to provide a Pegboard score. To measure finger tapping, participants tapped an electronic tapper (Western Psychological Services, Los Angeles, CA, USA) with their index finger as quickly as possible for 10 s. Two trials were performed for each hand. The four trials were averaged together to yield a tapping score. A composite score of movement speed was created by converting Purdue Pegboard and finger tapping scores to z scores and then computing the average of the z scores.
Muscle bulk Skin calipers were used to measure triceps skin folds (TSF mm). The mid-arm circumference (MAC) was measured with a flexible tape measure. Muscle bulk was calculated by the equation: Mid-arm muscle area = (MAC - [3.14 ¥ TSF/10])2/12.56.11
Covariates Gender and race were recorded at the baseline interview. Race questions and categories were those used by the 1990 U.S. Census. Gender was coded as ‘1’ for men, ‘0’ for women. Age in years was computed from selfreported birth data and date of the clinical examination at which the strength measures were collected. Education (reported highest grade or years of education) was
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obtained at the time of cognitive testing. Height in meters and weight in kilograms were obtained at each visit and were used to calculated body mass index (BMI), which has been used as one measure of obesity. Current or past use of hormone replacement therapy was documented at the initial interview. We also documented the presence of seven chronic conditions that could influence the relation of gender to strength. The diagnosis of cancer or previous trauma with loss of consciousness was based on the participants’ reports at the annual interviews. History of diabetes was defined as use of antidiabetic medication or participant report of clinically diagnosed diabetes or both. A similar definition was used for the history of hypertension or thyroid disease. Myocardial infarction was defined as clinically diagnosed heart attack, coronary thrombosis, coronary occlusion or myocardial infarction, as reported by the participant. History of stroke was defined as probable or possible as diagnosed at the clinical evaluation by a neurologist on the basis of a uniform structured examination and medical history as previously reported.8 A diagnosis of Parkinson’s disease was based on the participant’s report that they had a history of Parkinson’s disease and received levodopa treatment.
Data analysis We examined the distributions of and Pearson correlations among the motor measures (strength, movement speed and muscle bulk). These correlations were performed separately for men and women and controlled for age. Linear regression models were used to determine the association of the outcome measures (muscle bulk, strength and movement speed) with age and gender. A number of models were tested including the terms: age and gender alone; age and gender together; age, gender and a term for their interaction. In addition, terms were added to these models for education, sum of chronic conditions or stroke to determine if they modified the relationship of age, gender or their interaction to the outcome measures. Similar regression models with the outcome measure of strength were tested after the participants with Parkinson’s disease were excluded. To determine the effect of hormone replacement therapy on strength in women, a term for hormone use was included in a model examining the association of strength and age in women. Regression analyses used composite motor measures. A composite motor score has the advantage of increasing power by reducing random variability and floor and ceiling effects. Raw scores from each test were converted to z scores using the mean and standard deviation. A person’s z scores across individual motor tests were averaged to yield a single composite score of strength and movement speed. Models were examined graphically and
analytically and assumptions were judged to be adequately met. Programming was done in SAS.12
Results Description of the men and women of the cohort There were 234 men and 530 women in the study. The racial composition of the cohort consisted of: white 91.24%; black 7.86%; and other 0.91%. Men were younger and more educated than women. Level of global cognitive function, as measured by the Mini-Mental Status Examination, and BMI were similar in men and women. Eighty-five percent of the cohort had two or less chronic conditions and there were no significant differences in the total number of chronic conditions between men and women (DF 529; t 1.19; P = 0.1175). The percent of persons with each of the individual conditions included: myocardial infarction (13.7%); malignancy (33.6%); head injury (26.8%); stroke (8.0%); diabetes (12.2%); hypertension (46.5%) and thyroid disease (17.2%). Four men and no women had a history of Parkinson’s disease.
Metric properties of motor measures The mean grip strength in the cohort was 25.1 kg (SD ± 10.26; [range 1.81; 60]). The mean pinch strength was 6.5 kg (SD ± 2.14; range 0.91, 21.81). Men were stronger than women (Table 1). The average Purdue peg score was 10.8 (SD ± 2.6 pegs, [range 0–17] pegs). The mean finger tapping score was 54 (SD ± 7.8 taps, [range 18–79]). While men were faster on tapping, women were faster on Purdue Pegboard (Table 1). The mean measure of arm muscle bulk for the cohort was 47.9 cm2 (SD ± 14.78; [range 13.4–122.8 cm2]); arm muscle bulk was larger in men than women (Table 1).
Composite motor measures Grip and pinch strength measures were highly correlated (r = 0.80, P = 0.0001), after these measures were z scored, we combined them to form a composite measure of strength. It ranged from -2.39 to 3.26 with higher scores indicating greater strength (Table 2). Finger tapping and Purdue peg placement were moderately correlated (r = 0.41, P = 0.0001), after these measures were converted to z-scores, we combined them in a composite measure of movement speed. It ranged from -3.97 to 2.10 with higher scores indicating faster motor performance (Table 2). We also analyzed finger tapping and Purdue peg placement separately.
Correlations of motor measures Arm muscle bulk was moderately related to muscle strength in both men and women, but was unrelated to 61
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motor speed. Muscle strength and motor speed were moderately correlated in both men and women (Table 2).
Gender differences in motor function Gender differences in strength To determine whether the relation of strength to age differed for men and women, we constructed a linear regression model with terms for age, gender and their interaction (Table 3). In this analysis, the young old were stronger than the old old and men were stronger than women as one might expect. However, there was a significant negative interaction of age and gender indicating that the male advantage in strength was smaller in the old old compared to the young old. For example, the predicted difference in strength was about 0.7 kg greater for a 65-year-old man compared with a woman at age 65, but the difference was only about 0.5 kg at age 85. These findings were unchanged in secondary analyses, which included terms for education, chronic conditions and stroke (results not shown). These findings were also unchanged when analyses were repeated after
removing the four participants with a clinical diagnosis of Parkinson’s disease. In women the association of age and strength did not depend on whether or not they had received hormone replacement therapy (results not shown). To visually examine this effect, we used the main model to plot strength as a function of age separately for men and women (Fig. 1). In the figure, the strength scores for men are higher than women at all ages. However, at higher ages, the disparity between strength in men and women becomes less prominent.
Gender differences in movement speed We used a similar approach to analyze gender differences in movement speed (Table 3). The young old were faster than the old. In contrast to strength, however, women were faster than men, and there was no age– gender interaction. The findings were unchanged in secondary analyses controlling for education and the number of chronic conditions (results not shown). As the two tasks used to construct the composite movement speed measure were only moderately
Table 1 Characteristics of the cohort
Number of participants Age (years) Mini-Mental Status Exam Education (years) Body mass index (kg/m2) Number chronic conditions Grip strength (kg) Pinch strength (kg) Purdue Pegboard (number of pegs) Finger taps in 10 s Muscle bulk (cm2)
Men
Women
234 (30.6%) 74.8 (6.02) (65, 91) 28.4 (1.48) (23, 30) 19.0 (3.80) (6, 28) 28.0 (4.58) (19.2, 47.4) 0.22 (0.159) (0, 0.71) 35.2 (9.90) (8.6, 60.2) 8.5 (1.81) (3.0, 14.9) 10.4 (2.35) (0, 16.5) 55.9 (8.10) (29, 75) 57.8 (12.00) (29.2, 98.0)
530 (69.4%) 77.1 (7.24) (65, 96) 28.4 (1.73) (20, 30) 17.8 (2.85) (3, 30) 27.3 (5.20) (10.9, 47.4) 0.23 (0.174) (0, 0.86) 20.7 (6.68) (1.81, 46.7) 5.6 (1.65) (0.80, 21.8) 11.0 (2.71) (0, 16.75) 53.5 (7.49) (18, 79) 43.6 (13.80) (13.4, 122.8)
Mean, standard deviation and range except where noted.
Table 2 Upper extremity motor function measures Sex Men
Women
*P-values.
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Motor measure Strength Movement speed Muscle bulk Strength Movement speed Muscle bulk
Mean (SD)
Range
Correlations Strength Movement speed
0.96 (0.85) 0.025 (0.85)
-1.55–3.26 -3.97–2.10
– –
0.41 (< 0.0001*) –
57.8 (12.00) -0.42 (0.65) -0.009 (0.84)
29.2–98.0 -2.39–2.70 -3.97–1.74
– – –
– 0.34 (< 0.0001*) –
–
–
43.6 (13.8)
13.4–122.8
Muscle bulk 0.24 (0.0003*) 0.03 (NS*) – 0.09 (0.034*) -0.05 (NS*) –
Gender differences in motor performance
correlated, we also analyzed each task separately. Women were faster than men on the Purdue Pegboard ([ bˆ = -1.096 (S.E. 0.184)] P < 0.0001); whereas men tapped faster than women ([ bˆ = 1.454 (S.E. 0.573)] P = 0.0114). Performance on each task was negatively related to age, and the gender differences did not vary with age (both Ps < 0.0001).
Gender differences in muscle bulk Finally, we examined gender differences in muscle bulk in a similar linear regression model (Table 3). Men had more muscle bulk than women, muscle bulk was inversely related to age and this association was similar for men and women. These findings were unchanged in analyses controlling for education or the number of chronic conditions (results not shown).
Figure 1 Gender differences in strength. Plot of linear regression of the predicted strength (y axis) and age (x axis) to assess the association of strength and age for men and women. The model used had three terms (1) age; (2) gender; and (3) a term for the interaction of age and gender. The plot shows that men (solid line) are stronger than women (dashed line) at all ages but the difference in strength between men and women is less prominent in older persons.
Discussion In this cross-sectional study of Catholic clergy members older than 65 years, we compared the relation of age to several measures of upper extremity motor performance in men and women. All measures were related to age. Men were stronger and had more bulk, women were faster on Purdue Pegboard but men were faster on finger tapping. We found that the male advantage in arm strength was slightly less prominent in older old persons compared to younger old persons but gender differences in muscle bulk and movement speed did not vary with age. These cross-sectional data raise the possibility that gender differences in strength may be reduced in the older old. Although a number of studies have compared strength in men and women of different ages, few data are available regarding gender differences in motor performance among persons older than 65 years. A community-based study of older persons reported that the negative association of age with grip strength was stronger in men than women, consistent with the findings of the present study.13 That study did not include other measures of motor function. A similar age by gender interaction was observed in cross-sectional analyses of the Baltimore Longitudinal Study of Aging, but these analyses included young and middle-aged adults, so it is difficult to know whether the effects would be seen in persons over the age of 65.14,15 Given the importance of motor function for the maintenance of health in older persons, more research focusing on older people is needed. A longitudinal design makes it possible to directly compare decline in motor function in older men and women, but among the few longitudinal studies that have been done, results have been inconsistent. One study reported a greater rate of decline in grip strength for women as compared to men during a 4-year period, but after 8 years of observation, the difference was no longer significant.13,16 Two additional studies reported
Table 3 Linear regressions of main outcomes Outcomes
Covariate
Parameter estimate (SE)
P-value
Strength
Age Gender Age† Gender Age Gender Age† Gender Age Gender Age† Gender
-0.050 (0.004) 1.253 (0.048) -0.020 (0.008) -0.061 (0.004) -0.122 (0.059) 0.006 (0.009) -0.363 (0.079) 13.276 (1.048) -0.013 (0.163)
< 0.0001 < 0.0001 0.0078 < 0.0001 0.0378 0.5210 < 0.0001 < 0.0001 0.9353
Movement Speed
Muscle Bulk
†
Gender is coded as ‘1’ for men, ‘0’ for women. Age was coded in years, centered at 75.
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greater decline of grip strength in women as compared to men,17 but another study found that grip strength declined more in men than women.18 It is likely that much longer follow-up will be required to document the gender interaction in a longitudinal study. It is uncertain why we found that the male strength advantage was less pronounced at higher ages. Declining levels of testosterone levels in males may be one of the factors that modifies the male strength advantage with increasing age.19 It is also possible that the male strength advantage becomes less prominent because men are more likely than women to suffer from a variety of chronic neurologic disorders associated with aging. There is a higher rate of myocardial infarction, stroke and possibly Parkinson’s disease in men as compared to women.19–21 Although we controlled for these variables when clinically identified, we cannot exclude the possibility that subclinical disease is contributing to our findings. Recent work has suggested that frailty in the elderly may be associated with subclinical cardiovascular disease as well as MRI evidence of brain ischemia.22 The results of the present study are cross sectional and longitudinal data will be needed to verify these findings. Men and women often differ in education, occupation, and related lifestyle variables that are closely associated with physical function, making it difficult to separate gender effects from those resulting from other markers of socioeconomic status. Older women in the general population tend to have fewer years of formal education, less prestigious occupations and fewer financial resources than men, factors that are related to health and disability in old age. A unique feature of the present cohort is that socioeconomic and lifestyle differences between men and women are probably substantially less than in the general population, reducing the likelihood that gender comparisons were confounded by socioeconomic factors. Movement speed was tested with finger tapping and Purdue pegboard. The results in this study were consistent with prior research that men tapped more rapidly than women and women were faster at placing pegs than men.23,24 These gender differences did not vary with increasing age. Recent work found similar gender differences between simple finger tapping and repeating sequences of finger tapping movements.25 This suggests that there may be gender differences in reliance on manual praxis that becomes more apparent with tasks that require more demands about movement selection. The strengths of the present study include the use of multiple measures of motor performance in the same limb and the assessment of a large number of healthy older men and women who did not have clinical dementia. A study limitation is that this cohort is composed of older persons who differ from the general population in education, socioeconomic status and lifestyle, making it important that these results be replicated in 64
more diverse cohorts. In addition, few participants, especially men, were older than 85 years, so the results of this study may not be generalized beyond this age. Finally although the motor measures in this study are standard in community-based research, it is possible that a more detailed evaluation of motor function might yield different results.
Acknowledgments This research was supported by National Institute on Aging Grants R01 AG15819, K08 NS01575 and P30 AG10161. We are indebted to the hundreds of nuns, priests, and brothers from the following groups participating in the Religious Orders Study: Archdiocesan Priests of Chicago, IL, Dubuque, IA and Milwaukee, WI; Benedictine Monks, Lisle, IL, Collegeville, MN and St. Meinrad, IN; Benedictine Sisters of Erie, PA; Benedictine Sisters of the Sacred Heart, Lisle, IL; Capuchins, Appleton, WI; Christian Brothers, Chicago, IL, and Memphis, TN; Diocesan Priests of Gary, IN; Dominicans of River Forest, IL; Felician Sisters, Chicago, IL; Franciscan Handmaids of Mary, New York, NY; Franciscans, Chicago, IL; Holy Spirit Missionary Sisters, Techny, IL; Maryknolls, Los Altos, CA; Maryknoll, New York, NY; Norbertines, DePere, WI; Oblate Sisters of Providence, Baltimore, MD; Passionists, Chicago, IL; Presentation Sisters, B.V.M., Dubuque, IA; Servites, Chicago, IL; Sinsinawa Dominican Sisters, Chicago, IL and Sinsinawa, WI; Sisters of Charity, B.V.M., Chicago, IL and Dubuque, IA; Sisters of the Holy Family, New Orleans, LA; Sisters of the Holy Family of Nazareth, DesPlaines, IL; Sisters of Mercy of the Americas, Chicago, IL, Aurora, IL and Erie, PA; Sisters of St. Benedict, St. Cloud and St. Joseph, MN; Sisters of St. Casimir, Chicago, IL; Sisters of St. Francis of Mary Immaculate, Joliet, IL; Sisters of St. Joseph of LaGrange, LaGrange Park, IL; Society of Divine Word, Techny, IL; Trappists, Gethsemani, KY and Peosta, IA; and Wheaton Franciscan Sisters, Wheaton, IL. We also thank Julie Bach, MSW, coordinator of the Religious Orders Study, Liping Gu, MS, for statistical programming; George Dombrowski, MS and Greg Klein for data management.
References 1 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: M82– M88. 2 Vandervoort AA. Aging of the human neuromuscular system. Muscle Nerve 2002; 25: 17–25.
Gender differences in motor performance 3 Nutt JG, Lea ES, Van Houten L, Schuff RA, Sexton GJ. Determinants of tapping speed in normal control subjects and subjects with Parkinson’s disease: Differing effects of brief and continued practice. Mov Disord 2000; 15: 843– 849. 4 Nybo H, Gaist D, Jeune B, McGue M, Vaupel JW, Christensen K. Functional status and self-rated health in 2262 nonagenarians: the Danish 1905 Cohort Survey. J Am Geriatr Soc 2001; 49: 601–609. 5 Wilson RS, Schneider JA, Beckett LA, Evans DA, Bennett DA. Progression of gait disorder and rigidity and risk of death in older persons. Neurology 2002; 58: 1815–1819. 6 Shinkai S, Watanabe S, Kumagai S et al. Walking speed as a good predictor for the onset of functional dependence in a Japanese rural community population. Age Ageing 2000; 29: 441–446. 7 Fried LP, Tangen CM, Walston J et al. Frailty in older adults: Evidence for a phenotype. J Gerontol A Biol Sci Med Sci 2001; 56: M146–M156. 8 Schneider JA, Wilson RS, Cochran EJ et al. Relation of cerebral infarctions to dementia and cognitive function in older persons. Neurology 2003; 60: 1082–1088. 9 Wilson RS, Beckett LA, Barnes LL et al. Individual differences in rates of change in cognitive abilities of older persons. Psychol Aging 2002; 17: 179–193. 10 Bennett DA, Wilson RS, Schneider JA et al. Natural history of mild cognitive impairment in older persons. Neurology 2002; 59: 198–205. 11 Heymsfield SB, McManus C, Smith J, Stevens V, Nixon DW. Anthropometric measurement of muscle mass: Revised equations for calculating bone-free arm muscle area. Am J Clin Nutr 1982; 36: 680–690. 12 SAS Institute Inc SAS/STAT User’s Guide, Version 8. Cary, NC: SAS Institute Inc, 2000. 13 Bassey EJ, Harries UJ. Normal values for handgrip strength in 920 men and women aged over 65 years, and longitudinal changes over 4 years in 620 survivors. Clin Sci (Lond) 1993; 84: 331–337.
14 Lynch NA, Metter EJ, Lindle RS et al. Muscle quality. I. Age-associated differences between arm and leg muscle groups. J Appl Physiol 1999; 86: 188–194. 15 Lindle RS, Metter EJ, Lynch NA et al. Age and gender comparisons of muscle strength in 654 women and men aged 20–93 yr. J Appl Physiol 1997; 83: 1581–1587. 16 Bassey EJ. Longitudinal changes in selected physical capabilities: Muscle strength, flexibility and body size. Age Ageing 1998; 27: 12–16. 17 Era P, Rantanen T. Changes in physical capacity and sensory/psychomotor functions from 75 to 80 years of age and from 80 to 85 years of age – a longitudinal study. Scand J Soc Med Suppl 1997; 53: 25–43. 18 Desrosiers J, Hebert R, Bravo G, Rochette A. Age-related changes in upper extremity performance of elderly people: A longitudinal study. Exp Gerontol 1999; 34: 393–405. 19 Morley JE. Andropause: Is it time for the geritrician to treat it? J Gerontol 2001; 56A: M263–M265. 20 Sacco SE, Whisnant JP, Broderick JP, Phillips SJ, O’Fallon WM. Epidemiological characteristics of lacunar infarcts in a population. Stroke 1991; 22: 1236–1241. 21 Mayeux R, Denaro J, Hemenegildo N et al. A populationbased investigation of Parkinson’s disease with and without dementia. Relationship to age and gender. Arch Neurol 1992; 49: 492–497. 22 Newman AB, Gottdiener JS, McBurnie MA et al. for the Cardiovascular Health Study Research Group. Associations of subclinical cardiovascular disease with frailty. J Gerontol 2001; 56A: M158–M166. 23 Cousins MS, Corrow C, Finn M, Salamone JD. Temporal measures of human finger tapping: effects of age. Pharmacol Biochem Behav 1998; 59: 445–449. 24 Desrosiers J, Hebert R, Bravo G, Dutil E. Upper-extremity motor co-ordination of healthy elderly people. Age Ageing 1995; 24: 108–112. 25 Chipman K, Hampson E, Kimura D. A sex difference in reliance on vision during manual sequencing tasks. Neuropsychologia 2002; 40: 910–916.
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Geriatrics and Gerontology International 2005; 5: 59–65
ORIGINAL ARTICLE
Gender differences in upper extremity motor performance of older persons Aron S Buchman,1,2 Robert S Wilson,1,3 Julia L Bienias1,4 and David A Bennett1,2 1
Rush Alzheimer’s Disease Center, Rush University Medical Center, 2Department of Neurological Sciences, Rush University Medical Center, 3Department of Psychology, Rush University Medical Center and 4 Rush Institute for Healthy Aging, Department of Internal Medicine, Rush University Medical Center, Chicago, IL, USA
Background: Motor performance declines with age. Although gender differences in motor strength and speed have been widely reported, the extent to which these differences are maintained in old age has not been well established. Methods: Upper extremity motor performance was assessed in 234 men and 530 women Catholic clergy members aged 65 years or older with no clinical evidence of dementia who were participants in the Religious Orders Study. As part of a uniform clinical evaluation, upper extremity motor performance including strength (grip and pinch dynamometry), movement speed including finger tapping and Purdue pegboard and muscle bulk of the arm were collected. Results: Men were stronger than women at all ages but this difference became less prominent at older ages. Women scored higher on the Purdue Pegboard than men whereas men had faster maximal finger tapping rates than women. Gender differences in speed were not modified by age. Men had greater muscle bulk than women at all ages and these differences were not modified by age. These relationships were not modified by participants with a clinical diagnosis of Parkinson’s disease or stroke or by hormone replacement therapy in women. Conclusions: Gender differences in upper extremity speed and muscle bulk appear to be relatively stable with increasing age, whereas gender differences in strength were reduced in the oldest old. Longitudinal studies are needed to determine if men and women differ in the rate of decline of strength in old age. Keywords: aging, gender, movement speed, muscle bulk, strength.
Introduction Older people, on average, perform worse on tests of motor function than younger people. For example muscle strength in 80-year-old people is only 30%-50% of the strength of 20-year-olds.1,2 In an 80-year-old, the
Accepted for publication 31 May 2004. Correspondence: Dr Aron S. Buchman, MD, Rush University Medical Center, Rush Alzheimer’s Disease Center, Armour Academic Facility, Suite #1027B, 600 South Paulina Street, Chicago, IL 60612, USA. Email: [email protected]
speed of even simple movements such as the maximal rate of finger tapping or comfortable walking speed is 30% lower than a 20-year-old.3 Walking speed is reduced to the degree that in a recent large cohort of nonagenarians, less than 7% of the participants walked faster than one meter per second, the minimal speed necessary to cross at a signaled intersection.4 Older people with impaired motor function have been found to be at increased risk for disability, common neurologic diseases such as Alzheimer’s disease and death.5,6 Motor dysfunction is a dominant feature of frailty in the elderly which predicts disability and mortality.7 These findings underscore the importance of 59
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motor function for the maintenance of health and independence in old age. Men and women differ in motor function, although most data are from young or middle-aged adults. On average, men are stronger than women. Men also tend to walk more quickly than women, but on measures of fine motor speed such as the Purdue pegboard, women are faster than men. The extent to which gender differences are maintained in old age is not clear since few large studies have had adequate numbers of older men and women of comparable age. In this study we examined gender and age differences on several measures of motor function in the upper extremities in older participants free of dementia. We used data from the Religious Order Study, a clinicalpathologic study of aging and Alzheimer’s disease in Catholic nuns, priests and brothers. We assessed upper extremity strength using grip and pinch dynamometry, movement speed with a finger tapping test and the Purdue Pegboard and muscle bulk of the arm. In analyses, we first examined the associations of age and gender with each motor measure. We then tested whether gender modified the association of age with strength, movement speed or muscle bulk.
Methods Participants All subjects were participants in the Religious Orders Study, an ongoing longitudinal study of aging and Alzheimer’s Disease (AD). Older Catholic nuns, priests, and brothers were recruited from about 40 groups across the United States (see Acknowledgments). The study was approved by the Institutional Review Board of Rush University Medical Center. Eligibility for these analyses required an age of 65 years or older and absence of a clinical diagnosis of dementia. Each person underwent a uniform structured evaluation, which included a medical history, neurological examination, assessment of cognitive function, and review of brain scan when available. On the basis of this evaluation, an experienced neurologist or geriatrician diagnosed dementia and other common neurologic conditions affecting cognitive or physical function. The diagnosis of dementia followed the criteria of the joint working group of the National Institute of Neurological and Communicative Disorders and Stroke and the Alzheimer’s Disease and Related Disorders Association (NINCDS/ADRDA). Details of the clinical evaluation have been previously reported.8–10 Clinical evaluations for the study commenced in January 1994 and 942 participants underwent baseline evaluation through to June 2002 when the data set was frozen for analyses. The quantitative assessments of motor function on which we report in these analyses were added beginning Octo60
ber 1996. Of 872 people undergoing quantitative motor testing since 1996, 764 (88%) were free of dementia and were ≥ 65 years old and eligible for these analyses.
Strength Grip strength was measured using the Jamar hydraulic hand dynamometer (Lafayette Instruments, Lafayette, IN, USA). This sealed hydraulic system features a dualscale readout that displays isometric grip force from 0 to 90 kg. Pinch strength was measured using the Jamar hydraulic pinch dynamometer, which measures pinch strength from 0 to 20 kg (Lafayette Instruments, Lafayette, IN, USA). Two trials of grip and pinch strength were obtained for each hand. The four trials were averaged together to yield measures of grip and pinch strength. A composite score was created by converting grip and pinch measures to z scores and then computing the average of the z scores.
Movement speed Using the Purdue Pegboard the number of pegs that could be placed in 30 s was recorded. Two trials were recorded for each hand. The four trials were averaged to provide a Pegboard score. To measure finger tapping, participants tapped an electronic tapper (Western Psychological Services, Los Angeles, CA, USA) with their index finger as quickly as possible for 10 s. Two trials were performed for each hand. The four trials were averaged together to yield a tapping score. A composite score of movement speed was created by converting Purdue Pegboard and finger tapping scores to z scores and then computing the average of the z scores.
Muscle bulk Skin calipers were used to measure triceps skin folds (TSF mm). The mid-arm circumference (MAC) was measured with a flexible tape measure. Muscle bulk was calculated by the equation: Mid-arm muscle area = (MAC - [3.14 ¥ TSF/10])2/12.56.11
Covariates Gender and race were recorded at the baseline interview. Race questions and categories were those used by the 1990 U.S. Census. Gender was coded as ‘1’ for men, ‘0’ for women. Age in years was computed from selfreported birth data and date of the clinical examination at which the strength measures were collected. Education (reported highest grade or years of education) was
Gender differences in motor performance
obtained at the time of cognitive testing. Height in meters and weight in kilograms were obtained at each visit and were used to calculated body mass index (BMI), which has been used as one measure of obesity. Current or past use of hormone replacement therapy was documented at the initial interview. We also documented the presence of seven chronic conditions that could influence the relation of gender to strength. The diagnosis of cancer or previous trauma with loss of consciousness was based on the participants’ reports at the annual interviews. History of diabetes was defined as use of antidiabetic medication or participant report of clinically diagnosed diabetes or both. A similar definition was used for the history of hypertension or thyroid disease. Myocardial infarction was defined as clinically diagnosed heart attack, coronary thrombosis, coronary occlusion or myocardial infarction, as reported by the participant. History of stroke was defined as probable or possible as diagnosed at the clinical evaluation by a neurologist on the basis of a uniform structured examination and medical history as previously reported.8 A diagnosis of Parkinson’s disease was based on the participant’s report that they had a history of Parkinson’s disease and received levodopa treatment.
Data analysis We examined the distributions of and Pearson correlations among the motor measures (strength, movement speed and muscle bulk). These correlations were performed separately for men and women and controlled for age. Linear regression models were used to determine the association of the outcome measures (muscle bulk, strength and movement speed) with age and gender. A number of models were tested including the terms: age and gender alone; age and gender together; age, gender and a term for their interaction. In addition, terms were added to these models for education, sum of chronic conditions or stroke to determine if they modified the relationship of age, gender or their interaction to the outcome measures. Similar regression models with the outcome measure of strength were tested after the participants with Parkinson’s disease were excluded. To determine the effect of hormone replacement therapy on strength in women, a term for hormone use was included in a model examining the association of strength and age in women. Regression analyses used composite motor measures. A composite motor score has the advantage of increasing power by reducing random variability and floor and ceiling effects. Raw scores from each test were converted to z scores using the mean and standard deviation. A person’s z scores across individual motor tests were averaged to yield a single composite score of strength and movement speed. Models were examined graphically and
analytically and assumptions were judged to be adequately met. Programming was done in SAS.12
Results Description of the men and women of the cohort There were 234 men and 530 women in the study. The racial composition of the cohort consisted of: white 91.24%; black 7.86%; and other 0.91%. Men were younger and more educated than women. Level of global cognitive function, as measured by the Mini-Mental Status Examination, and BMI were similar in men and women. Eighty-five percent of the cohort had two or less chronic conditions and there were no significant differences in the total number of chronic conditions between men and women (DF 529; t 1.19; P = 0.1175). The percent of persons with each of the individual conditions included: myocardial infarction (13.7%); malignancy (33.6%); head injury (26.8%); stroke (8.0%); diabetes (12.2%); hypertension (46.5%) and thyroid disease (17.2%). Four men and no women had a history of Parkinson’s disease.
Metric properties of motor measures The mean grip strength in the cohort was 25.1 kg (SD ± 10.26; [range 1.81; 60]). The mean pinch strength was 6.5 kg (SD ± 2.14; range 0.91, 21.81). Men were stronger than women (Table 1). The average Purdue peg score was 10.8 (SD ± 2.6 pegs, [range 0–17] pegs). The mean finger tapping score was 54 (SD ± 7.8 taps, [range 18–79]). While men were faster on tapping, women were faster on Purdue Pegboard (Table 1). The mean measure of arm muscle bulk for the cohort was 47.9 cm2 (SD ± 14.78; [range 13.4–122.8 cm2]); arm muscle bulk was larger in men than women (Table 1).
Composite motor measures Grip and pinch strength measures were highly correlated (r = 0.80, P = 0.0001), after these measures were z scored, we combined them to form a composite measure of strength. It ranged from -2.39 to 3.26 with higher scores indicating greater strength (Table 2). Finger tapping and Purdue peg placement were moderately correlated (r = 0.41, P = 0.0001), after these measures were converted to z-scores, we combined them in a composite measure of movement speed. It ranged from -3.97 to 2.10 with higher scores indicating faster motor performance (Table 2). We also analyzed finger tapping and Purdue peg placement separately.
Correlations of motor measures Arm muscle bulk was moderately related to muscle strength in both men and women, but was unrelated to 61
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motor speed. Muscle strength and motor speed were moderately correlated in both men and women (Table 2).
Gender differences in motor function Gender differences in strength To determine whether the relation of strength to age differed for men and women, we constructed a linear regression model with terms for age, gender and their interaction (Table 3). In this analysis, the young old were stronger than the old old and men were stronger than women as one might expect. However, there was a significant negative interaction of age and gender indicating that the male advantage in strength was smaller in the old old compared to the young old. For example, the predicted difference in strength was about 0.7 kg greater for a 65-year-old man compared with a woman at age 65, but the difference was only about 0.5 kg at age 85. These findings were unchanged in secondary analyses, which included terms for education, chronic conditions and stroke (results not shown). These findings were also unchanged when analyses were repeated after
removing the four participants with a clinical diagnosis of Parkinson’s disease. In women the association of age and strength did not depend on whether or not they had received hormone replacement therapy (results not shown). To visually examine this effect, we used the main model to plot strength as a function of age separately for men and women (Fig. 1). In the figure, the strength scores for men are higher than women at all ages. However, at higher ages, the disparity between strength in men and women becomes less prominent.
Gender differences in movement speed We used a similar approach to analyze gender differences in movement speed (Table 3). The young old were faster than the old. In contrast to strength, however, women were faster than men, and there was no age– gender interaction. The findings were unchanged in secondary analyses controlling for education and the number of chronic conditions (results not shown). As the two tasks used to construct the composite movement speed measure were only moderately
Table 1 Characteristics of the cohort
Number of participants Age (years) Mini-Mental Status Exam Education (years) Body mass index (kg/m2) Number chronic conditions Grip strength (kg) Pinch strength (kg) Purdue Pegboard (number of pegs) Finger taps in 10 s Muscle bulk (cm2)
Men
Women
234 (30.6%) 74.8 (6.02) (65, 91) 28.4 (1.48) (23, 30) 19.0 (3.80) (6, 28) 28.0 (4.58) (19.2, 47.4) 0.22 (0.159) (0, 0.71) 35.2 (9.90) (8.6, 60.2) 8.5 (1.81) (3.0, 14.9) 10.4 (2.35) (0, 16.5) 55.9 (8.10) (29, 75) 57.8 (12.00) (29.2, 98.0)
530 (69.4%) 77.1 (7.24) (65, 96) 28.4 (1.73) (20, 30) 17.8 (2.85) (3, 30) 27.3 (5.20) (10.9, 47.4) 0.23 (0.174) (0, 0.86) 20.7 (6.68) (1.81, 46.7) 5.6 (1.65) (0.80, 21.8) 11.0 (2.71) (0, 16.75) 53.5 (7.49) (18, 79) 43.6 (13.80) (13.4, 122.8)
Mean, standard deviation and range except where noted.
Table 2 Upper extremity motor function measures Sex Men
Women
*P-values.
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Motor measure Strength Movement speed Muscle bulk Strength Movement speed Muscle bulk
Mean (SD)
Range
Correlations Strength Movement speed
0.96 (0.85) 0.025 (0.85)
-1.55–3.26 -3.97–2.10
– –
0.41 (< 0.0001*) –
57.8 (12.00) -0.42 (0.65) -0.009 (0.84)
29.2–98.0 -2.39–2.70 -3.97–1.74
– – –
– 0.34 (< 0.0001*) –
–
–
43.6 (13.8)
13.4–122.8
Muscle bulk 0.24 (0.0003*) 0.03 (NS*) – 0.09 (0.034*) -0.05 (NS*) –
Gender differences in motor performance
correlated, we also analyzed each task separately. Women were faster than men on the Purdue Pegboard ([ bˆ = -1.096 (S.E. 0.184)] P < 0.0001); whereas men tapped faster than women ([ bˆ = 1.454 (S.E. 0.573)] P = 0.0114). Performance on each task was negatively related to age, and the gender differences did not vary with age (both Ps < 0.0001).
Gender differences in muscle bulk Finally, we examined gender differences in muscle bulk in a similar linear regression model (Table 3). Men had more muscle bulk than women, muscle bulk was inversely related to age and this association was similar for men and women. These findings were unchanged in analyses controlling for education or the number of chronic conditions (results not shown).
Figure 1 Gender differences in strength. Plot of linear regression of the predicted strength (y axis) and age (x axis) to assess the association of strength and age for men and women. The model used had three terms (1) age; (2) gender; and (3) a term for the interaction of age and gender. The plot shows that men (solid line) are stronger than women (dashed line) at all ages but the difference in strength between men and women is less prominent in older persons.
Discussion In this cross-sectional study of Catholic clergy members older than 65 years, we compared the relation of age to several measures of upper extremity motor performance in men and women. All measures were related to age. Men were stronger and had more bulk, women were faster on Purdue Pegboard but men were faster on finger tapping. We found that the male advantage in arm strength was slightly less prominent in older old persons compared to younger old persons but gender differences in muscle bulk and movement speed did not vary with age. These cross-sectional data raise the possibility that gender differences in strength may be reduced in the older old. Although a number of studies have compared strength in men and women of different ages, few data are available regarding gender differences in motor performance among persons older than 65 years. A community-based study of older persons reported that the negative association of age with grip strength was stronger in men than women, consistent with the findings of the present study.13 That study did not include other measures of motor function. A similar age by gender interaction was observed in cross-sectional analyses of the Baltimore Longitudinal Study of Aging, but these analyses included young and middle-aged adults, so it is difficult to know whether the effects would be seen in persons over the age of 65.14,15 Given the importance of motor function for the maintenance of health in older persons, more research focusing on older people is needed. A longitudinal design makes it possible to directly compare decline in motor function in older men and women, but among the few longitudinal studies that have been done, results have been inconsistent. One study reported a greater rate of decline in grip strength for women as compared to men during a 4-year period, but after 8 years of observation, the difference was no longer significant.13,16 Two additional studies reported
Table 3 Linear regressions of main outcomes Outcomes
Covariate
Parameter estimate (SE)
P-value
Strength
Age Gender Age† Gender Age Gender Age† Gender Age Gender Age† Gender
-0.050 (0.004) 1.253 (0.048) -0.020 (0.008) -0.061 (0.004) -0.122 (0.059) 0.006 (0.009) -0.363 (0.079) 13.276 (1.048) -0.013 (0.163)
< 0.0001 < 0.0001 0.0078 < 0.0001 0.0378 0.5210 < 0.0001 < 0.0001 0.9353
Movement Speed
Muscle Bulk
†
Gender is coded as ‘1’ for men, ‘0’ for women. Age was coded in years, centered at 75.
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greater decline of grip strength in women as compared to men,17 but another study found that grip strength declined more in men than women.18 It is likely that much longer follow-up will be required to document the gender interaction in a longitudinal study. It is uncertain why we found that the male strength advantage was less pronounced at higher ages. Declining levels of testosterone levels in males may be one of the factors that modifies the male strength advantage with increasing age.19 It is also possible that the male strength advantage becomes less prominent because men are more likely than women to suffer from a variety of chronic neurologic disorders associated with aging. There is a higher rate of myocardial infarction, stroke and possibly Parkinson’s disease in men as compared to women.19–21 Although we controlled for these variables when clinically identified, we cannot exclude the possibility that subclinical disease is contributing to our findings. Recent work has suggested that frailty in the elderly may be associated with subclinical cardiovascular disease as well as MRI evidence of brain ischemia.22 The results of the present study are cross sectional and longitudinal data will be needed to verify these findings. Men and women often differ in education, occupation, and related lifestyle variables that are closely associated with physical function, making it difficult to separate gender effects from those resulting from other markers of socioeconomic status. Older women in the general population tend to have fewer years of formal education, less prestigious occupations and fewer financial resources than men, factors that are related to health and disability in old age. A unique feature of the present cohort is that socioeconomic and lifestyle differences between men and women are probably substantially less than in the general population, reducing the likelihood that gender comparisons were confounded by socioeconomic factors. Movement speed was tested with finger tapping and Purdue pegboard. The results in this study were consistent with prior research that men tapped more rapidly than women and women were faster at placing pegs than men.23,24 These gender differences did not vary with increasing age. Recent work found similar gender differences between simple finger tapping and repeating sequences of finger tapping movements.25 This suggests that there may be gender differences in reliance on manual praxis that becomes more apparent with tasks that require more demands about movement selection. The strengths of the present study include the use of multiple measures of motor performance in the same limb and the assessment of a large number of healthy older men and women who did not have clinical dementia. A study limitation is that this cohort is composed of older persons who differ from the general population in education, socioeconomic status and lifestyle, making it important that these results be replicated in 64
more diverse cohorts. In addition, few participants, especially men, were older than 85 years, so the results of this study may not be generalized beyond this age. Finally although the motor measures in this study are standard in community-based research, it is possible that a more detailed evaluation of motor function might yield different results.
Acknowledgments This research was supported by National Institute on Aging Grants R01 AG15819, K08 NS01575 and P30 AG10161. We are indebted to the hundreds of nuns, priests, and brothers from the following groups participating in the Religious Orders Study: Archdiocesan Priests of Chicago, IL, Dubuque, IA and Milwaukee, WI; Benedictine Monks, Lisle, IL, Collegeville, MN and St. Meinrad, IN; Benedictine Sisters of Erie, PA; Benedictine Sisters of the Sacred Heart, Lisle, IL; Capuchins, Appleton, WI; Christian Brothers, Chicago, IL, and Memphis, TN; Diocesan Priests of Gary, IN; Dominicans of River Forest, IL; Felician Sisters, Chicago, IL; Franciscan Handmaids of Mary, New York, NY; Franciscans, Chicago, IL; Holy Spirit Missionary Sisters, Techny, IL; Maryknolls, Los Altos, CA; Maryknoll, New York, NY; Norbertines, DePere, WI; Oblate Sisters of Providence, Baltimore, MD; Passionists, Chicago, IL; Presentation Sisters, B.V.M., Dubuque, IA; Servites, Chicago, IL; Sinsinawa Dominican Sisters, Chicago, IL and Sinsinawa, WI; Sisters of Charity, B.V.M., Chicago, IL and Dubuque, IA; Sisters of the Holy Family, New Orleans, LA; Sisters of the Holy Family of Nazareth, DesPlaines, IL; Sisters of Mercy of the Americas, Chicago, IL, Aurora, IL and Erie, PA; Sisters of St. Benedict, St. Cloud and St. Joseph, MN; Sisters of St. Casimir, Chicago, IL; Sisters of St. Francis of Mary Immaculate, Joliet, IL; Sisters of St. Joseph of LaGrange, LaGrange Park, IL; Society of Divine Word, Techny, IL; Trappists, Gethsemani, KY and Peosta, IA; and Wheaton Franciscan Sisters, Wheaton, IL. We also thank Julie Bach, MSW, coordinator of the Religious Orders Study, Liping Gu, MS, for statistical programming; George Dombrowski, MS and Greg Klein for data management.
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