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T. Neves1,3, M. Bomfim Martin Lopes2, M.G. Crespilho Souza3, E. Ferriolli4, C.A. Fett3, W.C. Rezende Fett3


1. Department of Physical Education, University of the State of Mato Grosso, Diamantino, MT, Brazil; 2. Department of Physical Education, Physical Education College, IPE Faculty of Technology, Cuiabá, MT, Brazil; 3Department of Physical Education, Nucleus of Studies in Physical Fitness, Computers, Metabolism, and Sports and Health, Federal University of Mato Grosso, Cuiabá, MT, Brazil; 4. Department of Internal Medicine, Faculty of Medicine of Ribeirão Preto, University of São Paulo, Ribeirão Preto, SP, Brazil.

Corresponding Author: Thiago Neves, Department of Physical Education, University of the State of Mato Grosso, 166, Rui Barbosa Street, Eldorado Garden, ZIP Code 78.400-000, Diamantino, MT, Brazil, E-mail address: thiago.alimt@gmail.com. Telephone: +5565-99957-9709. Fax: +55653336-1446.

J Aging Res Clin Practice 2018;7:60-68
Published online April 5, 2018, http://dx.doi.org/10.14283/jarcp.2018.12



Background: The magnitude of “Sarcopenia” and “Dynapenia” as a public health problem is not well established, nor is the relationship of declines strength and muscle mass to physical disability and/or loss of mobility. Objectives: Test the hypothesis that the elderly with sarcopenia are more likely to physical disability than are those with dynapenia. Design: Cross-sectional study. Setting/Participants: A total of 387 older adults (≥65 years old) from the FIBRA Study in Cuiabá, Mato Grosso, Brazil. Measurements: Sarcopenia was diagnosed according to the European Working Group on Sarcopenia in Older People (EWGSOP), which includes the presence of low muscle mass, plus low muscle strength or low physical performance. Dynapenia was defined as handgrip strength <30kgf (men) and <20kgf (women). Data relating to socio-demographic, behavioral, health conditions, physical disability, the level of physical activity, body composition, hand grip strength and the Short Physical Performance Battery were collected. Results: Regarding the loss of mobility, sarcopenia was associated with age ≥75 years, female, sedentary lifestyle, stroke, arthritis, and falls (OR = 2.95, 95% CI: 1.07 – 8.09); with no association for physical disability in BADL and IADL. Dynapenia had no association with loss of mobility; however, for disability in BADL and IADL, it was associated with the elderly aged ≥80 years old and arthritis (OR = 2.35, 95% CI: 1.42 – 3.88). Conclusion: Dynapenia is more sensitive to the prevention of future self-reported physical disability, in comparison to sarcopenia which can be used in clinical practice as a screening tool for the early decline in mobility..

Key words: Physical disability, mobility, activities of daily living, sarcopenia, dynapenia.



Physical disability usually occurs in older adults, and it is estimated that 20% to 30% of individuals over 70 years old have difficulties in performing basic and instrumental activities of daily living that require mobility and locomotion. Sarcopenia, which is defined as the loss of muscle mass associated with the presence of low muscle function (strength or physical performance), is one of the main causes of mobility loss and disability related to aging (1–4).
Sarcopenia is a syndrome characterized by the progressive and widespread loss of skeletal muscle mass and strength related to the age, leading to the risk of adverse outcomes, such as physical disability, poor quality of life and death (1). Complementary to the definition of sarcopenia, the recent discussion is that the decline in muscle strength can be given to a combination of muscular and neural factors and not only to reduced muscle mass, so recent questions about the inclusion of muscle mass and strength in the same concept (1, 5, 6).
Recently, results from some studies that analyzed muscle strength and muscle mass and their effect in physical disability, finding that muscle strength is a better predictor of disability (5). Dynapenia is the age-associated loss of muscle strength (5) and premature death (7,8). Thus, the term “dynapenia” was created to describe the functional impairment of the entire neuromuscular apparatus, and it was also claimed that sarcopenia has its original definition limited to the decline in age-related skeletal muscle mass (9). There is no evidence that the definition of sarcopenia has clinical importance (6), but this term attempts to achieve its widespread use. The proposal of the term dynapenia focuses on the aspect of performance seeking to overcome this dichotomy. However, some authors do not agree with the distinction between the terms “dynapenia” and “sarcopenia”, due to the risk of confusion between the nomenclatures (1).
The Fragility in Brazilian Elderly Research Network (FIBRA Network) was designed and developed to investigate and survey data on the prevalence, characteristics, and risk profiles for the biological fragility syndrome, among other syndromes in Brazilian elderly population. This study was performed with urban residents in localities with different levels of human development, in different geographic regions, considering socio-demographic, anthropometric, physical health, physical and mental functionality, and psychological variables (10).
Therefore, this study aimed to test the hypothesis that the elderly with sarcopenia (loss of physical performance and muscle mass) are more likely to physical disability and comorbidities than those with dynapenia (loss of physical performance).


Materials and methods


This research is a subproject of the Fragility in Brazilian Elderly Research Network (FIBRA Network) and consists of an exploratory cross-sectional multidisciplinary and multicentric population-based study, conducted in the period between 2009 and 2010 in 17 Brazilian regions selected by the criterion of quota sampling, with different indices of human development.
Regarding the present study, 513 elderly residents in the urban area of Cuiabá (Mato Grosso State, Brazil) were interviewed through registration forms from the census database of the IBGE, which registered 17,329 older adults. Participants aged under 65 years, or with severe mental retardation, severe or unstable Parkinson’s disease, terminal stage; amputations, and severe orthopedic limitations were not considered in this study.
Thus, only 387 older adults met all the inclusion criteria and completed all the evaluation stages of this study. All participants were previously informed about the study proposal and procedures they would be submitted to. Then they were asked to sign a consent form, approved by the Research Ethics Committee (protocol No. 196/96 CNS, approval number 632/09) of the Hospital Universitário Júlio Müller of the Federal University of Mato Grosso (HUJM-UFMT).

Anthropometric measurements

The body mass of the volunteers was determined using an electronic platform scale (ID 1500, Filizola®, Brazil) with a capacity of 200 kg and a precision of 0.1 kg. The elderly stood up in the middle of the platform scale, with their feet joined and arms along the body. Their height was measured with their body in an upright position, in bare feet, joined and close to the scale, using a portable stadiometer (Sanny®, Profissional model, Brazil) with a precision of 0.1 cm.
The body mass index was calculated by dividing the weight (in kilograms) by the squared height (in meters) (kg/m2). The reference values adopted for the body mass index were those suggested and suitable for the elderly, who are categorized in: <22.0 kg/m² = low weight, from 22.0 kg/m² to 27.0 kg/m² = eutrophic, and >27.0 kg/m² = excess weight (11). The circumferences of the abdomen (AC), waist (WC), calf (CC) and hip (HC) were measured using a flexible and inextensible plastic metric tape (Sanny®, Brazil) with a precision of 0.1 cm. The reference values for AC were ≥94.0 cm for men and ≥80.0 cm for women (12). The CC was used to verify the nutritional status, considering well-nourished those elderly who presented values ≥31 cm, for both genders (13).

Diagnosis and Classification of Sarcopenia

Sarcopenia was diagnosed according to consensus of the European Working Group on Sarcopenia in Older People (EWGSOP), which recommends the use of low muscle mass accompanied by low muscle function (strength or physical performance) for the diagnosis of sarcopenia (1). Thus, the diagnosis of sarcopenia in the present study sample required the confirmation of low muscle mass, in addition to the reduced muscle strength or poor physical performance (Figure 1).


Profile of the study using the consensus of the European Working Group on Sarcopenia in Older People (EWGSOP), suggested in case you find sarcopenia in older individuals. SMI = skeletal muscle mass index obtained by the absolute mass of the skeletal muscles divided by squared height in meters (kg/m²)

Profile of the study using the consensus of the European Working Group on Sarcopenia in Older People (EWGSOP), suggested in case you find sarcopenia in older individuals. SMI = skeletal muscle mass index obtained by the absolute mass of the skeletal muscles divided by squared height in meters (kg/m²)


Skeletal Muscle Mass Measurement

Muscle mass was estimated by skeletal muscle mass (SMM), using the mathematical equation of Lee (14).

SMM (kg) = 0.244 x body mass + 7.8 x height + 6.6 x gender – 0.098 x age + ethnicity – 3.3
The body mass was determined in kilograms and the height measured in meters. The age (years), gender (1 for men and 0 for women), race (-1.2 for Asians, 1.4 for Afro-descendants, and 0 for Caucasians) were also considered.
This equation was validated in the Brazilian population using the dual energy X-ray (DXA) method, and there was a high correlation between the methods (r = 0.86 for men and r = 0.90 for women, p<0.05). Moreover, there was a strong correlation between DXA and the predictive equation to determine the prevalence of sarcopenia (k = 0.74, p<0.001), with a high specificity (89%) and sensitivity (86%) (15).
The absolute skeletal muscle mass was converted to a skeletal muscle mass index (SMI), divided by squared height (kg/m2). The SMI was used to adjust the height and mass of non-skeletal muscle tissues, being used in several epidemiological studies (16, 17). The low muscle mass was defined by the SMI, with the cut-off point based on 20% of the lowest percentile of the population distribution, representing an SMI of ≤6.47 kg/m2 for women and ≤9.33 kg/m2 for men (16).

Muscle Strength Measurement

Muscle strength was evaluated by the hand grip strength, using a manual hydraulic dynamometer (Saehan Corporation®, Model SH5001, 973, Yangdeok-Dong, Masan 630-728, Korea). For this measurement, the elderly sat on an armless chair, and were positioned with the elbow flexed at 90°; shoulder adducted, forearm in a neutral position, and the wrist between 0° and 30° of extension. Three successive measurements were performed (at about 15 seconds between each one), and the best score of three trials was recorded for analysis. Cut-off values with a hand grip strength less than 30 kgf in men and 20 kgf in women  were considered to represent low muscle strength (1, 4).

Four-Meter Walking Test

The gait speed (meters/second) was determined by assessing the low physical performance of the lower limbs by the 4-meter walking test (4mWT) of the Short Physical Performance Battery (SPPB) (18). The average walking speed of the elderly was calculated by dividing the walking distance by the time spent in the test. The cut-off point of ≤0.8 m/s was used to identify low physical performance (1,4).

Loss of mobility

Loss of mobility was evaluated through the Short Physical Performance Battery (SPPB) (18), which is an instrument composed of three tests that evaluate, in sequence, the standing static balance, gait speed in usual step (measured in two times in a certain round-trip route of 4 meters) and the muscle strength of the lower limbs by the movement of standing up from and sitting down on a chair five consecutive times. The SPPB test is scored on a 0–12 scale, with higher scores indicating a higher functional level. The elderly who scored ≤7 points were considered at risk for mobility loss, because of their clinical relevance was associated with the triage of the elderly at risk of developing future disabilities, in addition to being objective, standardized and multidimensional. The variable of risk for loss of final mobility was dichotomous. A score of 0 indicates a higher functional level (>7 points in the SPPB) and 1 indicates a risk for mobility loss (≤7 points in the SPPB) (19).

Diagnosis and Classification of Dynapenia

Measures of upper extremity muscle strength were isometric shoulder adduction and handgrip. We selected the handgrip for the present analysis because the assessment of handgrip is easy, reliable, and inexpensive. Using the cut-off points indicated the Dynapenia was defined using the criteria with a hand grip strength less than 30 kgf in men and 20 kgf in women, considering with dynapenia those who exclusively lost only muscular strength (1, 4). Included in the classification individuals who had only loss of muscle strength (Figure 1).

Functional capacity

The functional capacity of the elderly for the basic activities of daily living (BADL) and instrumental activities of daily living (IADL) was evaluated by the Katz scale (20) and Lawton & Brody scale (21), respectively. Interviewees were asked if they had difficulties in performing the BADL (transfer, go to the bathroom, take a bath, urinary continence, get dressed, and eat) and the IADL (use a telephone, use mean of transportation, do/go shopping, cook, do light housework, do heavy housework, take medicines, and manage their money). The respondents who indicated difficulty or deficiency in performing one or more of the tasks were classified as having physical disability both in BADL and IADL. The final physical disability variable was dichotomous. A score of 0 indicates no limitation in BADL and IADL, whereas 1 indicates any limitation in BADL and/or IADL.

Physical Activity Level

The assessment of physical activity level was defined using self-report on weekly frequency and the daily duration of physical exercises, active sports, and domestic activities carried out in the week prior to the evaluation, based on items from the Minnesota Leisure Time Activity Questionnaire (22), validated for Brazil (23). For this research, the content, statements, and sequence of the questionnaire items were adapted to the study conducted by the FIBRA Network. Items describing common activities among the Brazilian elderly were kept, and questions on frequency and duration were included, intending to enrich the information on the regularity of the activity practices (if they had been practiced in the last 14 days).
The questionnaire was composed of 42 closed yes or no questions. Each dichotomous answer was followed by other questions about the continuity of activities during the evaluated period (if the elderly had performed each activity in the last two weeks), weekly frequency (how many days in a week) and duration (how many minutes a day).
The elderly who performed at least 150 minutes of weekly moderate-intensity physical activity, or 120 minutes of vigorous-intensity physical activities, following the recommendations of the American College of Sports Medicine (ACSM) and American Heart Association (AHA) (24), were considered active.

Geriatric Depression Scale (GDS)

The depressive symptoms were evaluated using the short version (15 items) of the Geriatric Depression Scale (GDS) (25). These items, together, showed a good diagnostic accuracy, with adequate sensitivity, specificity, and reliability, and can be an alternative for triage mood disorders in the elderly population. Participants with a score of ≥6 in the GDS were considered as having depressive symptoms.

Statistical analysis

The data were analyzed by using the Statistical Package for Social Sciences (SPSS for Windows, version 20.0). The Kolmogorov-Smirnov test was used to verify the normality of the independent variables. The descriptive statistics were presented as mean, standard deviation, median, and minimum – maximum; sample distribution was described, and the prevalence of sarcopenia and dynapenia of the population sample was calculated. For the independent samples, the T-student test was used if the data were parametric and the Mann-Whitney test if the data were non-parametric, and the chi-square test was used to examine the differences in the basic characteristics between the two groups. Values of p≤0.05 were considered significant.
Multiple logistic regression analysis was used to evaluate the effect of sarcopenia and dynapenia on physical disability and loss of mobility. For the degree of mobility, the dummy variables were created and coded, as follows: normal mobility = 0, loss of mobility = 1, whereas for physical disability, the dummy variables were created and coded, as follows: without physical disability = 0, with physical disability = 1, and Odds Ratio (OR) were subsequently computed for these factors. Associations with p≤0.20 in the univariate analysis were selected for logistic regression, for which the step-by-step advance method was used. Model 1 includes sarcopenia as an independent variable and model 2 includes dynapenia.



The general characteristics of the sample of elderly are summarized in Table 1. The participants’ mean age was 72 years, most of them weren’t married, white, but had on mean 4 years of schooling, and received less than R$510,00 monthly. Regarding the occurrence of health problems, there was a prevalence of hypertension, diabetes, arthritis/rheumatism, and osteoporosis, with a high cardiovascular risk since the waist circumference was higher than the reference value: 94.0 cm for women and 105.0 cm for men. Sarcopenia and dynapenia were in 15% and 38% of the elderly, respectively, and were higher in women than in men (Table 1).

Table 1 The general characteristics of the sample of elderly by genders, Cuiabá, Mato Grosso, Brazil (2010)

Table 1
The general characteristics of the sample of elderly by genders, Cuiabá, Mato Grosso, Brazil (2010)


The majority were women; among them, there was a higher percentage of older people, with an income lower than R$ 510.00 monthly, excess weight, and a higher percentage of fat, arterial hypertension, arthritis, osteoporosis, and occurrence of falls, compared to men (Table 1).
The elderly with sarcopenia and dynapenia had functional and physical performance significantly lower in comparison to those classified as normal, and were slower and reported more dependencies in ADL (Table 2).

Table 2 Functional performance and physical dependence on 387 seniors living in Cuiabá, Mato Grosso, Brazil (2010)

Table 2
Functional performance and physical dependence on 387 seniors living in Cuiabá, Mato Grosso, Brazil (2010)

Different letters show significant statistical difference between the groups (p ≤ 0.05). Mann-Whitney test with data expressed as median (minimum-maximum). SPPB – Short Physical Performance Battery. BADL – basic activities of daily living. IADL – instrumental activities of daily living.


The logistic regression analysis for loss of mobility and disability in BADL and IADL is shown in Table 3. In model 1, the odds ratio (OR) and 95% CI for the factors statistically associated with loss of mobility were: being 75 years old or older, woman, sedentary, have had a stroke, arthritis, falls, and sarcopenia. The factors associated with disability in BADL and IADL were: being 80 years old or older, have had arthritis, and being a woman.

The logistic regression analysis for loss of mobility and disability in BADL and IADL is shown in Table 3. In model 1, the odds ratio (OR) and 95% CI for the factors statistically associated with loss of mobility were: being 75 years old or older, woman, sedentary, have had a stroke, arthritis, falls, and sarcopenia. The factors associated with disability in BADL and IADL were: being 80 years old or older, have had arthritis, and being a woman. In model 2, the OR and 95% CI for factors statistically associated with loss of mobility were the same as those found in model 1, but dynapenia was not associated with loss of mobility. The factors associated with disability in BADL and IADL were being 80 years old or older, have had arthritis and dynapenia.

Table 3 Multiple logistic regression models to test the association of physical dependence or loss of mobility with sarcopenia and dynapenia in the study in 387 seniors living in Cuiabá, Mato Grosso, Brazil (2010)

Table 3
Multiple logistic regression models to test the association of physical dependence or loss of mobility with sarcopenia and dynapenia in the study in 387 seniors living in Cuiabá, Mato Grosso, Brazil (2010)

OR – Odds ratio. CI – Confidence interval. SPPB – Short Physical Performance Battery. BADL – basic activities of daily living. IADL – instrumental activities of daily living.



Perhaps the most relevant aspect of the present study is the observation that both classifications (sarcopenia and dynapenia) were significantly associated with physical disability and comorbidities, with a prevalence of 15% and 38%, respectively. Therefore, a division of these classifications is necessary because only the classification as sarcopenia, as proposed by some authors (1), would underestimate an important percentage of individuals with high risk for health and physical disability. Few studies involving elderly individuals have carried out these associations separately. Loss of mobility was only associated with sarcopenia; however, there was an association of self-reported physical disability in BADL and IADL only with dynapenia. Our results suggest that the association between sarcopenia and loss of mobility could be explained by the present comorbidities, the sedentary lifestyle, and the occurrence of falls.
The prevalence of sarcopenia varies among different populations, due to differences relating to age, gender, diagnostic method, and evaluation instruments (26–29). Different instruments used to define sarcopenia, as well as the age group and incompatible living habits of the study population may cause different diagnoses of its prevalence. Because of this variability, it is necessary to emphasize the importance of adopting a standardized and operational definition of sarcopenia for multidimensional geriatric assessment, similarly to the one adopted in the present study.
It is believed that the evaluation of muscle strength by the isolated hand grip strength is useful only in the triage phase of dynapenia, because it explains about 40% of the variation in the strength of the lower limbs, suggesting, for the diagnosis, the evaluation of the muscular strength by the extension of the Knee due to its association with gait speed and physical function (5). Other researchers observed that hand grip strength was a strong predictor of gait speed reduction and self-reported physical disability (in BADL and IADL) (30). These researchers found, in the elderly with low hand grip strength, a higher incidence of physical disability in IADL, and this correlation was higher in women (2.28, 95% CI = 1.59 – 3.27) than in men (1.90, 95% CI = 1.13 – 3.17) (31).
However, in this study, the hand grip strength was used as a method to define the dynapenia, since it is a good indicator of the strength of the whole body, given that a low hand grip strength is strongly associated with a high probability of mortality, the risk of complications and development of physical disability (8,32). Moreover this method makes easier the strength measurement, and it is significantly less expensive and accessible to developing countries, such as Brazil.
Sarcopenia was associated with an increase in loss of mobility, with advancing age, especially in sedentary women, with arthritis or stroke, and with a history of falls. These results together suggest that reductions in skeletal muscle mass accompanied by a decline in strength or physical performance with the aging, as suggested in the EWGSOP document, cause loss of mobility, and if these declines reach a critical point, the physical function can be compromised (33,34).
Data used from the longitudinal Health Aging and Body Composition Study, which observed 3,075 elderly Americans, showed that the lowest quintile of muscle mass was associated with a poor performance of the lower limbs in both genders (35), and they also showed an association with loss of mobility, similar to the results found in our study (34).
The Health, Welfare and Aging (SABE in Portuguese) study, conducted in Brazil with 478 elderly individuals aged 60 years or over, compared the association of sarcopenia and dynapenia with the incidence of deficiency in mobility or IADL, and with disability in basic and instrumental activities of daily living. The authors observed that sarcopenia was associated with a deficiency in mobility or IADL (2.38, 95% CI 1.10 – 5.17), whereas dynapenia was neither associated with physical disability nor with the loss of mobility (33), corroborating, in part, our findings since the dynapenia was associated with self-reported physical disability. Melton et al. (36) reported an association of sarcopenia with walking difficulty in older men and women.
Several studies have shown a relationship between sarcopenia and self-reported physical disability, using scales of basic and instrumental activities of daily living (16,17,37,38), evidencing that women and men with sarcopenia were 3.6 and 4.1 times, respectively, more likely to physical disability in comparison to individuals without sarcopenia (16). On the other hand, some authors reported that only severe sarcopenia was independently associated with an increase in the probability of functional damage and physical disability in the elderly, after adjustments for potential variables of confusion, such as age, race, health behaviors, and comorbidities (37), in addition, they showed that the effect of sarcopenia on physical disability was considerably lower (38,39). However, in our study, the self-reported physical disability was not associated with sarcopenia.
Another study carried out in Australia with 1,705 elderly men, aimed to determine the association among loss of strength, mass and muscle quality, functional limitation, and physical disability, concluded that the muscle strength measurement is the best one to measure age-related muscle change and that it is associated with the deficiency in instrumental activities of daily living and functional limitation (3), corroborating our results. In a sample of 1,030 elderly Italians, some researchers concluded that isometric hand grip strength is strongly related to muscle power of the lower extremities, knee extensor torque, and calf cross-sectional muscle area, and that the decrease in hand grip strength is a clinical marker of mobility loss (walking speed <0.8m/s) better than the decline in muscle mass (4). In other words, conversely to our findings, these researchers evidenced that low values of muscle strength can predict, regardless of other risk factors, the incidence of physical disability (31).
However, in our study, we did not find this association with sarcopenia, perhaps because the elderly participants did not have a high degree of disability in ADL, which could lead to a poor functional performance, explaining this dissociation, besides the fact that these activities are related to works that do not require strength, muscular endurance, and walking speed (40). The differences may be related to diversities in outcome measurements and characteristics of the studied populations, in addition to the fact that physical disability is self-reported, which can hide the true relationship between sarcopenia and physical disability in these elderly. In this sense, a battery of physical tests may be adequately sensitive to support the diagnosis of present and future dependencies and comorbidities (41).
Also, our study indicated that dynapenia was associated with disability in ADL, agreeing with some studies that reported the relationship between dynapenia (measured through hand grip strength) and ADL (31,32). Furthermore, these studies indicated that strength and body mass index (BMI) were positively and negatively associated with the disability in ADL, respectively (39). In this study, the occurrence of falls and sedentary lifestyle were other factors associated with loss of mobility. As found in other studies, older men and women, who are less physically active, have less skeletal muscle mass, which can increase the prevalence of physical disability (42). Thus, the effects of physical exercise, including a simple walk, can protect against the loss of mobility in older adults. Falls and their related injuries are a major health problem in the elderly population and are associated with an increase in morbidity and physical disability (16).
From the results presented here, the following limitation can be considered: 1) The fact this is a cross-sectional study, so the cause-and-effect relationships could not be established. 2) The use of regression equations to estimate muscle mass can underestimate or overestimate the prevalence of sarcopenia. However, few studies have used the DEXA to estimate muscle mass in elderly populations and epidemiological studies because of the high cost. Therefore, simple and feasible options that have the same function without causing population risk are indicated. Furthermore, the equation used in the present study was validated in American and Brazilian populations, presenting a high correlation with magnetic resonance and DXA (14,15). 3) The use of the sarcopenia equation (equation that assists in the diagnosis of sarcopenia by estimating skeletal muscle mass) does not include BMI, it only includes the weight and height in its logistic regression analysis. However, it is known that 50% of the variance of muscle mass is explained by BMI, preventing the identification of other factors related to muscle mass. 4) The FIBRA Study aimed to evaluate the population of elderly residents in the community and did not include the elderly from asylums and hospitals. Thus, the relationship between sarcopenia and physical disability and between dynapenia and physical disability cannot be considered for all elderly population.
Finally, regarding the dynapenia, few population studies were found, as it is a recent issue (32,43). However, the prevalence of dynapenia, as reported for sarcopenia, shows differences among the previous studies (32,43). Probably, the discrepancies among the results can be related to the lack of sufficient evidence in the literature to identify specific cut-off points, complete assessment of risk factors, and the lack of consensus relating to methods and instruments used to define the final diagnostic algorithm. Nevertheless, it is observed in the present study that, among the used methods, the one used to classify dynapenia was more sensitive to associate a higher percentage of the studied population with the factors related to self-reported physical disability.



In summary, this study is relevant because it focused on a large sample of elderly residents in the community, which represents the elderly population in a large Latin American city, in addition to comparing dynapenia with sarcopenia, using the EWGSOP criteria as factors of risk for the loss of mobility and physical disability in ADL.
It also evidenced that individuals who lost strength in addition to muscle mass were more likely to the loss of mobility than those who only lost muscle strength. However, the elderly with dynapenia showed a high disability in self-reported ADL. These associations were measured by the presence of comorbidities, sedentary lifestyle, and occurrence of falls.
The classification of dynapenia differs from the classification of sarcopenia (according to the EWGSOP) in qualitative and quantitative aspects, and we found a higher percentage of individuals classified as having dynapenia. This fact demonstrates that, at least in this population, the classification as dynapenia is more sensitive to prevent future physical dependencies in comparison to the classification as sarcopenia, and can be used in clinical practice as a screening tool for the early decline of mobility. Thus, we emphasize the need for an active lifestyle and the inclusion of physical exercise programs to protect old people against the loss of mobility.


Author affiliations: Center for Physical Fitness, Informatics, Metabolism, Sports and Health, Faculty of Physical Education, Federal University of Mato Grosso, Cuiabá, Mato Grosso State, Brazil (Thiago Neves, Marcela Bomfim Martin Lopes, Milene Giovana Crespilho Souza, Carlos Alexandre Fett, Waléria Christiane Rezende Fett). We thank the members of the Fragility in Brazilian Elderly Research Network (FIBRA Network) who assisted with the scientific and data collection team, in particular the general coordinator of this study, Eduardo Ferriolli, professor at the University of São Paulo, Medical School of Ribeirão Preto , Department of Clinical Medicine, Division of General Medical Clinic and Geriatrics. This research was supported by the National Council of Scientific and Technological Development – CNPq (nº 17/2006) and by the Foundation for Research Support of the State of Mato Grosso – FAPEMAT (002.017/2007). The funding body had no role in the design, data collection, data analysis and interpretation of the study, article writing, or in the decision to submit the manuscript.

Role of the Funding Source: This research was supported by the National Council of Scientific and Technological Development – CNPq (nº 17/2006) and by the Foundation for Research Support of the State of Mato Grosso – FAPEMAT (002.017/2007).

Conflict of interest: None declared.

Ethical standard: The experiments described in this manuscript comply with the current of laws of Brazil.



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C. Siordia1, A.N. Lewis2


1. PhD, Graduate School of Public Health, University of Pittsburgh; 2. PhD, College of Health and Behavioral Studies, James Madison University

Corresponding Author: C Siordia, 30 North Bellefield Ave, Pittsburgh, PA 15213. Phone: 1-142-383-1708. Email: cas271@pitt.edu


The term “mobility disability” is used in different academic disciplines to discuss conceptualizations of physical movement. Inadequate attention has been paid to how this umbrella term refers to various forms of measurements on both hypothetical and enacted function. Refining what is meant by mobility disability may impact clinical practice by providing more specific information to clinicians. Less ambiguous labeling may have the potential to advance research by lowering measurement imprecision. We complement discussion by presenting empirical analysis on 5,995 participants (aged > 65) from National Health and Aging Trends Study (NHATS-2011). Ambiguous labeling of mobility may unintentionally obscure what is known about perceived capacity for ambulation and stair-climbing. Because creating low-cost and readily-available measures of health in the population has the potential to advance public health knowledge, efforts should continue to standardize and clarify measures of mobility. Key words: Ambulation, disability, function, labeling; measurement, mobility.

Key words: Ambulation, disability, function, labeling, measurement, mobility.


The term “mobility” is widely used in health, disability, clinical, and rehabilitation research. The term is broad and encompasses a wide variety of phenomena. The term “mobility” was recently defined in the Disability and Society journal as “the capacity to navigate one’s way through different spaces and places” (1). The term mobility also accompanies other forms of movements, such as those with “power mobility devices” (2) and has been used to define migratory behaviors such as “cross-border mobility” (3). Measuring movement, be it independent or with assistance, is important as it quantifies “existential implications of the performance of place through mobility” (4). The “mobility disability” label generally refers to: ability to perform physical function tasks. The term has been defined in one or multiple items from a wide variety of subjective and objective measurements (5-12), like two consecutive self-reports of having difficulty walking ¼ mile or climbing 10 stairs (13). A review of instruments used to assess mobility in older adult populations is available elsewhere (14). Research has used a wide array of measures for mobility disability. While common language facilitates discourse, imprecise terminology has the potential to hide the fact that inter-study comparability on (what appears to be) the same topic is not possible. Standardizing the use of highly specified labels through public consensus may help solve this issue.

As eloquently explained by others (15), it is important to understand how “capacity to function” and “actual performance” differ: the first refers to function in the hypothetical sense while the latter to function in the enacted sense. More specifically, self-reports on ability to perform physical function tasks measure hypothetical movements while observed performance measures enacted movements. Technically, hypothetical movement refers to an individual’s perceived potential to perform a particular task while enacted movements refer to an individual’s ability to perform a task as per validation by an external evaluator. Treating hypothetical and enacted mobility as the same thing—by using one label—has the potential to obscure what is understood about an individual’s physical capacity.

Unlike enacted physical movements that are objectively measured by a trained observer or electronic device like an accelerometer, assessment of hypothetical mobility is undertaken by asking individuals to self-evaluate and report their ability to perform a particular task. The labeling of subjective measures is the primary concern of this commentary. In particular, we are concerned with self-reported ability to walk long distances and climb-steps. Self-reported ability to walk long distances measures an individual’s perceived potential to walk. Thus, the following “root label” is recommended: Perceived Potential for Ambulation Ability (PPAA). The root label PPAA could be more highly specified by including a “sub-label”—like the “distance” mentioned in the question. For example, if a 1 mile or 1 kilometer question is used, the following sub-labels could be added: PPAA1m; PPAA1k.

Note the term “ambulation ability” has been used before (16) and to refer to something different than what is being discussed in this commentary. Because survey questions pertaining to ability to walk over long distances presumably refer to “linear ambulation” (i.e., walking horizontally on a flat surface with 0° of incline), walking up steps is framed in this commentary as being radically different. Hypothetically, stair-climbing in the respondent’s mind refers to “non-linear ambulation” (i.e., walking upwards on flat surfaces over a non-0° incline). Because linear and non-linear ambulation may differ in terms of physical demands, they should be labeled separately. Self-reported ability to walk-up stairs/steps measures an individual’s perceived potential to climb stairs/steps. Thus, the following root label is recommended: Perceived Potential for Stair-Climbing Ability (PPSCA). If a survey question on ability to walk-up “one flight of steps” or “20 steps” is used, the root label PPSCA could be further specified with sub-labels as follows: PPSCA1flight; PPSCA20stairs.

Research on the biomechanics of ambulation has shown that stair-climbing is more demanding than linear ambulation (15). Perceived potential to walk over a long distance or climb steps can be evaluated by at least two methods: (1) memory retrieval of relevant event; (2) or by evaluating capacity from a cognitive model. Perceived Potential from Memory Retrieval (PP-MR) refers to self-evaluations from actual events retrieved from memory. For example, when asked about ability to walk up 20 steps, a person may remember attempting the task and failing (or succeeding) and use that as the method for determining their capacity. Perceived Potential from Cognitive Model (PP-CM) is more difficult to describe and refers to using mental scenarios to self-evaluate ability to perform tasks. Because survey questions, in theory, have the ability to lead a respondent to self-evaluate his or her ability to perform a particular physical function task by, presumably, invoking cognitive representations of the environments, PP-CM is presumed to be possible.

Because linear and non-linear ambulation exert different biomechanical demands and because their subjective assessment may magnify how self-evaluation processes (i.e., PP-MR or PP-CM) affect perceived potential to perform tasks, walking (PPAA) and climbing (PPSCA) should be explored separately (17). By extension, these arguments could be used to explain why combining PPAA and PPSCA into one composite score has the potential to create an ambiguous measure of physical capacity—where (PPAA + PPSCA) = increased potential for measurement bias (18-20). In order to show evidence of how our discussion may be able to disambiguate research by highlighting the presence of “ambiguous mobility disability phenotypes”, we provide a brief empirical analysis.


Our analysis uses “Round 1” data (year 2011) from the National Health and Aging Trends Study (NHATS) of persons aged > 65 designed to investigate physical function in later life (22). Details of the study have been published before (22). Our brief analysis includes Latinos (LAT), Non-Latino-Blacks (NLB), and Non-Latino-Whites (NLW) who completed a 3-meter walk test without the use of any assistive device or person. A total of 5,995 NHATS participants are used in the analysis.

PPAA is computed from answers to the following NHATS questions: In the last month, were you able to walk 3 blocks by yourself and without your cane or walker?—could be labeled as “PPAA3blocks”; and In the last month, were you able to walk 6 blocks, or about half a mile, by yourself and without your cane or walker?—could be labeled as “PPAA6blocks”. Those responding “yes” receive a “1” on a binary variable for each question. We then combined them as follows: PPAA=0 if unable to walk 3 or 6 blocks; PPAA=1 if only able to walk 3 blocks; and PPAA=2 if able to walk 3 and 6 blocks. PPSCA is computed from answers to the following NHATS questions: In the last month, were you able to walk up 10 stairs by yourself and without your cane or walker?—could be labeled as “PPSCAA10steps”; and In the last month, were you able to walk up 20 stairs, about two flights, by yourself and without your cane or walker?—could be labeled as “PPAA20steps”. Those responding “yes” receive a “1” on a binary variable for each question. We then combined them as follows: PPSCA=0 if unable to walk up 10 stairs; PPSCA=1 if only able to walk up 10 stairs; and PPSCA=2 if able to walk up 20 stairs. PPAA and PPSCA were summed to create the Composite Score (CS) and produce the following groups: “clearly” able disability” (CS=0); “ambiguous mobility disability phenotype” (CS= 1); and “clearly” unable to perform tasks (CS=2).

Because PPAA, PPSCA, and SC represent “subjective” measures, we contrast their distribution by an “objective” measure”: gait speed. The three-meter “usual pace” gait speed was used as part of the short physical performance battery (SPPB) test and was assessed at the participant’s home by a trained interviewer (22). We measure gait speed as “meters per-second” (m/sec). We then combined PPAA scores with “normal” gait speed (i.e., >1.01 m/sec) as advised elsewhere [22] and “abnormal” gait speed (i.e., <1.00 m/sec) to create the “PPAA by normality of gait speed” groups presented in Table 1. We also combined PPSCA scores with normal and abnormal gait speed to create the “PPSCA by normality of gait speed” groups and additionally combined CS scores with normal and abnormal gait speed to create the “CS by normality of gait speed” groups.

We present the distribution of PPAA, PPSCA, and CS scores by race-ethnic groups and by normality of gait speed. We also provide multivariate logistic regression results predicting “ambiguous mobility disability phenotype” (i.e., CS=1) while adjusting for: race; ethnicity; sex; age; and educational attainment—using the following categories: < junior high school (>1st-8th grade); high school (includes 9th-12th grade and high school graduates); some college (includes vocational, technical, business, or trade school certificate or diploma beyond high school level); and > college graduate (includes: some college but no degree; associate’s degree; bachelor’s degree; and master’s, professional, or doctoral degree). We managed data and regressions using SAS 9.3® software. We discussed “percent change in the expected likelihood”: [100×(OR-1)]—i.e., [100×(eβx-1)].


Table 1 shows descriptive statistics for sample of 5,995 observations. Table 2 presents how NLBs, NLWs, and LATs are distributed over the variables used to predict ambiguous mobility disability phenotype. From Table 2, see that about one-fourth of all study subjects

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in the analysis sample are categorized as having an ambiguous mobility disability phenotype; the majority are NLWs; females; born in the US; and have a high school education or below. Table 3 presents the regression results. As may have been expected from a previous publication (22), the following groups are associated with having a greater likelihood of having an ambiguous mobility disability phenotype: females; those over age 75; and those with some college education or below. For example, when compared to those with a college education, individuals with a junior high education or below are 72% more likely to have an ambiguous mobility disability phenotype—i.e., a complex combination between ability to walk blocks and climb stairs. When compared to those males, females are 65% more likely to self-report their perceived potential for mobility over the counter alternative to report an ambiguous mobility disability phenotype. The regression results suggest that ambiguous mobility disability phenotype is not normally distributed when “markers of social stratification” are considered (23).

Table 1 Distribution of PPAA, PPSCA, and Composite Score by Normality of Gait Speed

1. Perceived Potential for Ambulation Ability; 2. Non-Latino-White; 3. Non-Latino-Black; 4. Latino; 5. Perceived Potential for Step-Climbing Ability; 6. Composite score (PPAA+PPSCA); 7. Gait > 1.01 m/sec; 8. Has normal gait and report inability to walk or climb steps; 9. Has normal gait and reports some inability to walk or climb steps; 10. Has normal gait and reports full ability to walk and climb steps; 11. Gait < 1.00 m/sec; 12. Has abnormal gait and report inability to walk or climb steps; 13. Has abnormal gait and reports some inability to walk or climb steps; 14. Has abnormal gait and reports full ability to walk and climb steps


Table 2 Descriptive statistics for variables in regression model

1. Non-Latino-White; 2Non-Latino-Black; 3. Latino; 4. Has a Composite Score (PPAA+PPSCA) that is between 2 and 3—which may represent a multitude of different scenarios between perceived potential to walk blocks and climb-steps

Table 3 Results from multivariate logistic regression model predicting “ambiguous mobility disability phehotype”1

***α<0.001 **α<0.01; 1. Has a Composite Score (PPAA+PPSCA) that is between 2 and 3—which may represent a multitude of different scenarios between perceived potential to walk blocks and climb-steps; 2. Odds ratio; 3. 95% Wald lower confidence limit; 4. 95% Wald upper confidence limit; 5. Percent change:[(odds ratio-1)*100]



From our introductory discussion, we concluded that advancing research may be plausible through clear labeling of mobility-related measures. Although cumbersome, the use of technical labels has the potential to improve the level of precision in the public discourse over “mobility disability.” Improving clarity in the labeling of measures may help clinicians better understand risk factors for abnormal lower extremity mobility. Use of the label mobility disability to refer to some measure of physical capacity is not only customary; it also empowers authors in the development of manuscripts with persuasive rhetoric. Unfortunately, the use of common language has the potential to simultaneously facilitate the consumption of technical information and slows scientific progress through the use of ambiguous terms. To be clear, although the use of common language facilitates discussion, it may concurrently limit scientific knowledge by unintentionally encouraging inappropriate inter-study comparisons. As we continue to explore how best to produce low-cost and readily available measures of sub-clinical physical capacity in population studies (21), efforts should continue to use existing data sources and to provide more precise labels of physical function.

Author Contribution: CS had the original idea and completed the first draft of the manuscript after completing data analysis. ANL significantly improved the draft by framing the discussion and focusing the goals of the project. Both CS and ANL were fully involved in the study and preparation of the manuscript. The material within our manuscript has not been and will not be submitted for publication elsewhere.

Conflict of Interest: Neither CS nor ANL have any conflict of interest with JARCP.

Funding: CS was supported by the NIH grant number U01 AG023744.


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M.E.L. van den Berg1, M. Crotty1


1. Flinders University, School of Medicine, Dep of Rehabilitation, Aged & Extended Care, Adelaide, Australia

Corresponding Author: Dr Maayken van den Berg, Flinders University, School of Medicine, Dep of Rehabilitation, Aged & Extended Care, Repatriation General Hospital, Daws Road, Daw Park l South Australia l 5041, E: maayken.vandenberg@flinders.edu.au, T: +61 8 8275 1297 l F: +61 8 8275 1130



Background: Decline in mobility is commonly observed following stroke. Reducing the impact of stroke is key to the maintainance of functional independence. Objectives: To determine the acceptability and adherence of a water-based exercise program post-stroke. Design: A single-blind randomised controlled pilot study with masked outcome assessment. Setting: Rehabilitation Unit, Adelaide, South Australia. Participants: 22 community-dwelling older people e living with strokes (6 months-3 years post-stroke). Intervention: Subjects were randomized to either: a six-week water-based intervention group (WG), thrice- weekly; a six-week gym-based intervention group (GG), thrice-weekly; or a six-week chronic disease self-management course (CG), once-weekly. Measurements: Assessments took place at baseline, post-intervention and at 3 months follow-up. Primary outcome measures was the 6-minute walk test. Secondary outcomes were measures of balance, body composition, cognition, ADL, goal attainment, quality of life, sleep and fatigue. Results: Recruitment was difficult with only 20% of those approached meeting entry criteria and consenting. A larger increase in walking speed and reduced use of walking aids post-intervention was observed in the WG, however, differences between groups were not significant. No between-group differences were found for any secondary outcomes. The average attendance rate was 90% (n=6). Conclusion: Subjects tolerated the moderate to high intensity water-based exercise program and adherance was good. Although we can not draw firm conclusions due to study completion failure the results suggest that a relatively short program of water-based exercise in stroke survivors is safe and feasible and can improve functional mobility. Hydrotherapy can be delivered with minimal supervision and a well powered trial is needed to assess the effects in chronic stroke patients


Key words: Stroke, water-based exercise, mobility, randomised controlled trial.



There are approximately 48.000 stroke events amongst Australians each year. It is the second cause of disease burden in Australia, in terms of ‘healthy’ life lost due to poor health or disability (1). Loss or limitation of functional movement is a common consequence of stroke. Around 21% will experience a decline in mobility in the first three years which leads to a disruption in usual functioning (2). Reducing the impact of stroke is the key to maintenance of independence and quality of life.

The benefits of water-based exercise have been demonstrated in patients with a range of conditions such as rheumatoid arthritis , osteoarthritis , fibromyalgia and also in the general older adult population (3). Additionally, previous studies have shown high levels of adherence with water-based exercise (4). Water-based exercise is possible for patients who are non-ambulatory or have balance issues however there is little evidence supporting water-based exercises after stoke. The objective of this study was to assess the acceptability and adherence of a water-based exercise program in individuals six months to three years post-stroke. Given the susceptibility to deterioration of functional mobility after stroke, succesful completion of this study was to inform a future trial. It was anticipated that the water environment would allow patients to exercise at a higher level than would have been possible on land, translating into greater improvements to function.




This was a single blind randomised controlled pilot study with masked outcome assessments. Participants were recruited via the rehabilitation service at the Repatriation General Hospital and key inclusion criteria were: six months to three years since first stroke; community dwelling; independent ambulation with or without gait aids; Mini Mental State Exam score of at least 18; ability to accept instruction and able to give consent. Reasons for exclusion were: subsequent stroke; major medical complications following stroke; unstable cardiac conditions; urinary or fecal incontinence; open wounds; tinea; unstable epilepsy or seizures; other comorbid conditions that might contraindicate participation in gym- or water-based exercise; inability to carry out the exercise program; and current participation in a concurrent exercise program.

All eligible participants willing to take part in the study provided written informed consent and were then randomized to receive either: a six-week water-based exercise intervention (3 times/week); a six-week gym- based exercise intervention (3 times/week); or no exercise intervention (waiting list control). Random group allocation was centrally managed by a pharmacist external to the project. Randomisation was generated by a computer software program.


The water-based intervention group (WG) received three pool sessions per week for a total of six weeks. Each session was of 40 minutes duration (including aerobic warm up and stretching cool-down) and consisted of a standardised resistance program. Exercises included sideways walking, hip flexion, hip extension, hip adduction, and hip abduction, knee cycling, calf raises, upper body resistance exercises. The intensity of which varied according to each individual’s ability, with progressive increase in load over the six week period. Likewise, the gym-based intervention group (GG) received three 40-minute gym sessions (including aerobic warm-up and stretching cool-down) per week for a total of six weeks following a standardised resistance program of which the intensity varied according to each individual’s ability, with progressive increase in load over the six week period. Exercises included: bike and arm ergometers, seated bench press, hipflexion, hip extension, hip adduction and hip abduction, triceps pull-down and knee flexion and knee extension. The no-exercise control group (CG) attended a chronic disease self-management course once a week for six weeks. Each session was of 2.5 hours duration and focused on topics such as: symptom management; effective communication with your doctor; and how to lessen frustration, fight fatigue, make daily tasks easier and get more out of life.


Assessments took place at baseline, immediately post- intervention at 6 weeks and at 3 months follow-up. The primary outcome was gait performance as measured by the six minute walk test (6MTW) (5). Secondary outcome measures were the Modified Berg Balance Scale (MBSS) (6), bioelectrical impedance, Mini Mental Status Examination (MMSE) (7), Modified Barthel Index (MBI) (7), Goal Attainment Scale (GAS)(8), SF-36 (7), Motor Assessment Scale (MAS) (9), MOS Sleep Scale (10), and 10-item Fatigue Assessment Scale (11). Data on demographics (sex, age, etc.), medical history and medications were collected from medical case records or from the

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subject at baseline. Side effects were monitored but none were reported

Stastictical analysis

Primary analysis for this trial was undertaken using intention to treat principles. Due to the small sample size, non-parametric statistics was used for data analysis. The one-way analysis Kruskall-Wallis test for independent samples was used to determine if there was a statistically significant difference between the groups.



Recruitment commenced in December 2007 and ceased in July 2008. Twenty (16%) of the potential participants could not be contacted (e.g phone cut off or phone not aswered). A total of 106 stroke survivors were approached

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for the study. Please refer to Table 1 for detailed information on recruitment. A total of 22 (20%) of the patients approached consented and were randomised. Patients characteristics are shown in Table 2. There were 2 withdrawals, 1 in the GG and 1 in the CG. The remaining 20 participants were followed up at the 6- week post-intervention assessment. However, the study was terminated prior to the scheduled end date due to funding difficulties and follow-up data at 3 months was collected of 6 patients only. As a result of premature abortion planned sample size could not be achieved and data collection could not be completed.

The exercise intervention was standardized for all subjects, consisting of resistance exercises performed in either the gym or pool. Exercises essentially exerted the same muscle groups in subjects regardless of randomisation to the pool or gym. Variance of intensity (low/medium/high) depended on an individual’s ability, however during the intervention period the training load was progressively increased according to the principle of progressive overload (Kraemer).

Study outcomes are presented in Table 3. A larger improvement in gait performance on the 6MTW was evident post-intervention and a reduced use of walking aids was observed in the WG. However, significant differences between groups were not present. A noteworthy improvement in optimal sleep was observed in the WG as measured with the MOS Sleep Scale. The GAS scores indicated that the WG evaluated themselves best on overall achievement of personal set goals. No significant differences were observed between groups in any of the secondary outcome measures.


Table 1: Recruitment

Adherence was monitored for 6 participants in the WG and the average attendance rate was 90%.



We compared water-based therapy to gym-based therapy and no exercise intervention. We demonstrated the feasibility of our protocol in that subjects could tolerate moderate to high intensity exercise programs using a water-based program. Also, the results suggest that a relatively short program of water-based exercise can improve functional mobility in stroke survivors. Although we cannot draw firm conclusions due to the fact that the study was aborted to completion, studies with small samples add to the body of literature and should contribute to meta-analysis efforts. Accordingly, we hope that the presented data will be used in future meta-analyses which will overcome the limitation of small sample size by pooling study results to generate a single best estimate.

Water-based exercise is considered to be a safe and effective alternative to land-based exercise. Very few studies have been conducted water-based exercises in stroke survivors and only one (12) has measured gait performance. In this study with 12 community-dwelling individuals treatment effects on gait performance were significantly in favour of water-based exercises compared to no-water based exercises (12). Our study results show a trend towards improved walking performance in the WG, however due to the small sample size results did not reach significance and definite conclusions can not be drawn.

Subjects in the WG trained 3 times a week for 40 min and exercised mainly at 50-60% of their baseline age- predicted HR maximum without discomfort. This is consistent with the recommendations by the American Heart Association (13) who prescribes exercise in stroke patients at 50-80% of maximal heart rate, 3-7 days a week with a duration of 20-60 min/day. However, to elicit a training effect increasing the dose may yield better results (14). Studies that have previously shown improvements are based on either 8 or 12-week training programs (15, 16). Adherence was good with a 90% attendance rate in the WG. Due to the physical properties of water, such as buoyancy and hydrostatic pressure, the greater variety of movements, easy-to-do low-impact exercise, pleasant recreational environment and reduced fear of falling may encourage adherence to the training program.


Table 2: Baseline and outcome measures


In summary, subjects tolerated the program and the findings of the pilot study are promising considering the relatively short length of the program and incomplete study results. A well powered trial is needed to assess the effectiveness of a water-based exercise program poststroke.
Based on the findings of this pilot study we recommend that a sample size of 152 subjects is required to detect a minimal clinically important difference of 50m (17), based on a two-tailed test at 0.80% power and a significance level of 0.05.


Acknowledgements: We acknowledge the help of the patients and hospital staff. We also thank Repatriation Research Foundation for funding.

Funding: This study was sponsored by The Foundation Daw Park Grants for Medical Research (2007/2008). The sponsor had no role in the design and conduct of the study; in the collection, analysis, and interpretation of data; in the preparation of the manuscript; or in the review or approval of the manuscript.

Conflict of interest disclosure: Dr Maayken van den Berg is not aware of any conflict of interest. Prof Maria Crotty is not aware of any conflict of interest.



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