Physical fitness is considered a major factor contributing to the maintenance of independent living and everyday competence. In line with this notion, it has been shown that several years of amateur dancing experience can exert beneficial effects not only on balance and posture but also on tactile, motor, and cognitive functions in older people. This raises the question of whether an even more extensive schedule of dancing, including competitive tournaments, would further enhance these positive effects. We therefore assessed posture, balance, and reaction times, as well as motor, tactile, and cognitive performance in older expert ballroom dancers with several years of competitive experience. We found substantially better performance in the expert group than in the controls in terms of expertise-related domains like posture, balance, and reaction times. However, there was no generalization of positive effects to those domains that were found to be improved in amateur dancers, such as tactile and cognitive performance, suggesting that there might be an optimal range of intervention intensity to maintain health and independence throughout the human lifespan.
In addition to a general decline in physical fitness [
One of the basic accomplishments of gerontology is the recognition of the tremendous heterogeneity and interindividual variability in the elderly [
We recently showed that a regular schedule of amateur dancing over many years throughout old age not only promotes posture and balance, but also has a wide range of beneficial effects on reaction times (RTs), motor behavior, and tactile and cognitive performance by comparing such individuals with an aged-matched nondancer control group [
Here, we extended these studies by investigating the impact of dancing at a higher level of expertise. One of the rationales for this study was to obtain information about whether a more extensive schedule of dancing, including competitive tournaments, would further enhance the range or magnitude of beneficial effects. We compared a group of neurologically healthy older subjects with many years of expert and competitive experience of dancing (ED) to a gender-, age-, and education-matched nondancer control group (CG). In this study, the term “expert” is defined as those who regularly attend dance competitions and dance contests and undergo training at intensities of more than 4 h/week. Comparable to our previous study on amateur dancers, we measured posture and balance, cognitive, attentional, intellectual, perceptual, and sensorimotor performance.
A total of 49 healthy volunteers (60–94 years) participated in our study. Subjects were recruited by advertisements in newspapers, poster announcements, and word-of-mouth advertising. All subjects reported their medical history and current medication and underwent the Mini-Mental Status Examination (MMSE) [
During dance competitions, all subjects in the ED group were assigned to a starting group referred to as “seniors IV” (age > 66 years). For the competition, 10 different dances had to be performed in a mandatory order, including the slow waltz, tango, Viennese waltz, slowfox, quickstep, samba, cha-cha-cha, rumba, paso doble, and jive, each of which lasted for 1.5–2 min. On the basis of points given by adjudicators during the contests, the subjects of our ED group were assigned the highest German grade (S) within the corresponding starting group. Therefore, subjects of the ED group had to be particularly fit with regard to mobility, muscle flexibility, and body composition. Although literature reports indicate a lower cardio-respiratory performance (i.e., maximal oxygen uptake or
Given the average workload of 4.5 h/week plus assumed 2.5 h/week for dancing competition adds up to 7 h a week, which totals 350 h per year, which sums up to 7500 h, which is the typical workload range required to qualify for becoming expert [
Lifestyle and general activity levels were assessed using the Everyday Competence Questionnaire (ECQ) [
All subjects were asked to comment on the questions with as much detail as possible, thus allowing insight into their habits and living conditions. The answers were converted into numerical scores according to an item-specific scale. Altogether, subjects could achieve 0–54 points. The scores were normalized to a scale from 0 to 1 by dividing the number of points achieved by the maximum possible scores per item. For a detailed description, see [
Based on figural reasoning, general intelligence was assessed using the Raven’s Standard Progressive Matrices (RSPM) [
Single row of the nonverbal geriatric concentration test (AKT). Subjects had to mark 20 symbols equivalent to the one at the top in five rows of 55 similar looking patterns within a maximum time limit of 30 s. After an initial training session, three consecutive sessions were run. Needed times for each session were averaged for evaluating individual performance.
We performed multiple-choice RT measurements in a finger-selection visuotactile task adapted from the study of Alegria and Bertelson [
We applied the
Hand-arm fine-motor performance was evaluated using a computer-based test battery for clinical neuropsychological research (MLS; Dr. G. Schuhfried GmbH, Mödling, Austria). The system consists of a work plate with 2 pencils for left and right hand use. We tested speed, accuracy, and maintenance of upper limb position during execution of fine motor movements of the left and right arms, hands, and fingers by using the following tests for:
Touch threshold was evaluated using a staircase procedure by probing the fingertips of the left and right index fingers with von Frey filaments ranging from 0.25 to 294 mN on logarithmic scaling (Marstocknervtest, Marburg, Germany).
Spatial 2-point discrimination thresholds (
To pool the data obtained from the various tests, we defined 5 domains covering similar functional categories. “Cognitive performance” comprised data from the AKT and the RSPM. “Tactile performance” comprised data from
To compare performances across all tests and all subjects, we calculated normalized performance indices (IPs) for each subject, and each test as (wp-ip)/(wp-bp), where wp is the worst performance of all subjects, ip is the individual performance, and bp is the best performance of all subjects. The best IP is 1, while the worst IP is 0. Indices were subsequently averaged across tasks belonging to a particular domain as described above.
In all cases, we reported averages and standard error of the mean (SEM). We used the Mann-Whitney
We tested cognitive, posture, balance, and sensorimotor performance in the 2 groups of older participants, matched for gender, age, and education, who had an extended history of expert and competitive dancing (ED), or no dancing experience (control group; CG). The ED group had a superior performance in most of the tests (Table
Comparison of cognitive, posture, balance and sensorimotor status of ED and CG.
Variables | ED | (Range) | CG | (Range) | Effect size | ||
---|---|---|---|---|---|---|---|
Age (years) | (66–77) | (61 | −0.345 | 0.730 | |||
Female (%) | 54.55 | 78.94 | 0.121 | ||||
Education-level (schoolyears) | (8–12) | (6 | −0.696 | 0.486 | |||
Everyday competence (ECQ) | (9.13–12.28) | (5.04 | −2.996 | 0.003 | 1.34 | ||
RSPM1 | (15–23.5) | (7 | −2.776 | 0.006 | 1.04 | ||
Geriatric-concentration-test (AKT) | (51.30–55) | (47 | −4.997 | ≤0.001 | 0.21 | ||
Multiple choice reaction times (ms), L | (541.75–795.84) | (581.01 | −2.294 | 0.022 | 1.03 | ||
Multiple choice reaction times (ms), R | (551.69–745.10) | (580.51 | −2.195 | 0.028 | 1.02 | ||
Romberg test (s), eyes open | (60–60) | (7.22 | −3.951 | ≤0.001 | 3.36 | ||
Romberg test (s), eyes closed | (7.22–60) | (2 | −1.250 | 0.211 | 0.38 | ||
Standing-turn (steps) | (2–8) | (3 | −1.765 | 0.078 | 0.78 | ||
Standing-turn (s) | (1–4) | (1.77 | −2.815 | 0.005 | 1.28 | ||
Up&go (s) | (4–6) | (5.54 | −3.819 | ≤0.001 | 3.02 | ||
| |||||||
Steadiness (error), L | (3–61) | (0 | −0.394 | 0.694 | 0.07 | ||
Steadiness (error), R | (3–45) | (0 | −1.475 | 0.140 | 0.17 | ||
| |||||||
Aiming (error), L | (0–3) | (0 | −1.584 | 0.113 | 0.26 | ||
Aiming (error), R | (0–2) | (0 | −2.808 | 0.005 | 1.18 | ||
Aiming (s), L | (6.81–15.75) | (7.19 | −0.760 | 0.447 | 0.30 | ||
Aiming (s), R | (6.50–12.26) | (7.96 | −1.889 | 0.059 | 0.71 | ||
Pin plugging (s), L | (42.92–90.92) | (37.64 | −0.086 | 0.932 | 0.49 | ||
Pin plugging (s), R | (35.59–51.56) | (37 | −2.343 | 0.019 | 0.87 | ||
| |||||||
Tapping (hits), L | (134–202) | (102 | −1.902 | 0.057 | 0.73 | ||
Tapping (hits), R | (134–215) | (107 | −0.748 | 0.454 | 0.16 | ||
| |||||||
Touch-threshold (mN), LID | (0.12–0.56) | (0.08 | −0.775 | 0.438 | 0.08 | ||
Touch-threshold (mN), RID | (0.12–0.95) | (0.08 | −1.035 | 0.301 | 0.09 | ||
2-Point-discrimination-threshold (mm), LID | (1.90–3.67) | (2.20 | −2.515 | 0.012 | 0.96 | ||
2-Point-discrimination-threshold (mm), RID | (1.86–4.55) | (2.89 | −2.434 | 0.015 | 0.92 |
ED: expert dancer, CG: control group; L: left hand, R: right hand; LID: left index finger, RID: right index finger.
Values are means, SEM.
1Raven Standard Progressive Matrices, subset of 30 items.
Performance of expert dancers (ED) and a matched control group (CG) for selected tests covering cognitive, posture and balance, motor, and tactile domains. Participants of the ED group showed (a) higher scores in the RSPM (
The ED group showed significantly higher ECQ scores than the CG group (
Posture and balance assessment showed significant differences between the 2 groups for the
The calculation of IP for each test and each subject allowed a direct comparison of performances across all tests and all subjects and facilitated grouping into functional domains covering cognition, RTs, posture and balance, motor performance, and tactile performance. As shown in Table
Indices of performance (IP) averaged across individual tasks describing cognition, reaction times, posture and balance, and motor, and tactile performance for both groups.
Domain | ED | (Range) | CG | (Range) | Effect size | ||
---|---|---|---|---|---|---|---|
Cognitive performance | (0.38–1) | (0–1) | −1.389 | 0.165 | 0.47 | ||
Reaction time | (0.49–0.93) | (0–0.87) | −3.462 | 0.001 | 1.02 | ||
Posture and balance | (0–1) | (0–1) | −5.599 | ≤0.001 | 1.26 | ||
Motor performance | (0–1) | (0–1) | −1.753 | 0.080 | 0.19 | ||
Tactile performance | (0–0.99) | (0–1) | −1.485 | 0.138 | 0.44 |
ED: expert dancer, CG: control group; Values are means, SEM.
Our findings indicated a general advantage for the ED group, which spans cognitive, perceptual, and motor performance. In order to obtain insight into possible differences in the overall distribution of IPs within a given domain, we grouped the IP for each domain into >0.5 and <0.5 values and compared the percentage of occurrence of IPs >0.5 across groups, where 0 indicates the worst and 1indicates the best performance.
In 3 of the 5 domains analyzed, the CG group had a significantly higher number of IPs that was lower than 0.5 (subjects with IP <0.5, cognition: ED = 9.09%, CG = 36.26%,
We have recently shown that a regular schedule of many years of amateur dancing in old age has a wide range of beneficial effects not only on posture, but also on sensorimotor and cognitive performance [
According to our hypothesis about the impact of multi-year dancing activities, we expected a broad range of beneficial effects. Therefore, we needed to test many different domains from cognitive functions to basic sensory abilities. Criteria for selecting a test included a brief time needed to complete the test, general acceptance, and a wide extension. In this sense, a particular test served as a surrogate for a given domain, implying that other tests for this field would have shown similar effects. Raven’s matrices were selected as a measure of general intelligence. Floor or ceiling effects have been described when using the Advanced (ceiling) or Colored Progressive Matrices (floor effects) [
We included a CG that was characterized by having no record of dancing or sporting activities for at least 5 years. We used the ECQ questionnaire to characterize both cohorts of participants. The ECQ addresses specific aspects of so-called instrumental activities of daily living, such as housekeeping, daily routine, manual skills, mobility, sports, subjective well-being, linguistic abilities, and leisure-time activities. Participants in the CG had lower ECQ scores, indicating a more passive and sedentary lifestyle. These data imply a close association between a lack of sporting activities and lifestyle, the identification of which was not our primary goal when we selected subjects.
It is well acknowledged that selecting an adequate control group for any type of “expert” subpopulation poses a major challenge [
Subjects in the ED group performed better in most of the tasks investigated in this study. However, analysis of the individual IPs, which allowed comparison across all tests and subjects for the 5 domains (cognition, RT, posture and balance, motor performance, and tactile performance) showed a significantly better performance in the ED group with regard to RT and posture and balance only. Superior postural performance can be directly linked to the requirements imposed by dancing. A similar argument can be made for the finding of faster RTs in the ED group, which might be attributable to the requirements for both high attention and fast and well-coordinated motor responses. In contrast to the previously studied group of elderly amateur dancers [
In the previous study performed in a group of amateur dancers, we showed that the best performers of each task were present in both the dancing and the CG with similar frequency, but that the amateur dancing group lacked the number of poor performers that were frequently found within the control group [
Another line of argument for the limited positive impact of expertise at old age comes from functional imaging studies. It has been shown that learning piano playing in amateurs elicits stronger activation in a number of brain areas in comparison to the brain activation found in professional piano players, who practice playing to maintain high levels of expertise [
For many years, dance has been successfully established as a therapeutic tool in the elderly to improve cardiovascular parameters, muscle strength, and posture and balance [
Compared to activities such as exercising, walking, or playing an instrument, dance has the advantage of combining many diverse features including physical activity, social and emotional interaction, and sensory stimulation, each of which is well documented to have beneficial effects. Accordingly, there might also be many mechanisms mediating the positive outcomes of dancing. In healthy elderly individuals, physical fitness and cognitive performance are closely associated [
It must be recognized that the present study, as well as our previous study with amateur dancers [
Our data showed that a regular, multiyear schedule of expert and competitive ballroom dancing in a cohort of older individuals preserves posture and balance parameters to a remarkable extent and has a positive impact on RT. However, our results provided no evidence for more widespread beneficial effects on related domains such as tactile and cognitive performance. These findings suggest that not all doses of exercise are helpful for alleviating age-relating deterioration but hint at a more inverted U-shape, dose-response function with optimal ranges of intervention intensity required to have maximal beneficial effects. Accordingly, it might be important to adjust, depending on the individual level of activity and expertise, the challenges of intervention programs to maintain health and functional independence throughout life.
Given the dramatic demographic changes within industrialized countries characterized by an increasing probability of reaching old and very old age, there is an urgent need for measures permitting an independent lifestyle into old age. Since there is a close association between physical fitness and cognitive performance, a number of studies investigated the impact of interventional programs on the basis of dancing for the treatment of age-related functional degradation [
Expert dancer group
Nondancer control group
Reaction times
Everyday competence questionnaire
Raven Standard Progressive Matrices
Geriatric Concentration test
Indices of performance
Mini Mental Status Examination
Instrumental activities of daily living
2-point discrimination threshold
Left index finger
Right index finger.
One Author (Jan-Christoph Kattenstroth) is a recipient of a stipend from the Allgemeiner Deutscher Tanzlehrerverband (ADTV). The sponsors had no influence on design, execution, analysis and interpretation of data, or writing of the study.
J. C. Kattenstroth and T. Kalisch contributed equally to this paper.
The authors would like to thank Ms. and Mr. Fremerey for helping them recruiting expert dancer. Parts of the work have been supported by a Grant from the Deutsche Forschungsgemeinschaft to HRD (DFG Di 334/10-4 and 19-1).