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Aging and Physiological Lessons from Master Athletes

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Abstract

Sedentary aging is often characterized by physical dysfunction and chronic degenerative diseases. In contrast, masters athletes demonstrate markedly greater physiological function and more favorable levels of risk factors for cardiovascular disease, osteoporosis, frailty, and cognitive dysfunction than their sedentary counterparts. In many cases, age‐related deteriorations of physiological functions as well as elevations in risk factors that are typically observed in sedentary adults are substantially attenuated or even absent in masters athletes. Older masters athletes possess greater functional capacity at any given age than their sedentary peers. Impressive profiles of older athletes provide insight into what is possible in human aging and place aging back into the domain of “physiology” rather than under the jurisdiction of “clinical medicine.” In addition, these exceptional aging athletes can serve as a role model for the promotion of physical activity at all ages. The study of masters athletes has provided useful insight into the positive example of successful aging. To further establish and propagate masters athletics as a role model for our aging society, future research and action are needed. © 2020 American Physiological Society. Compr Physiol 10:261‐296, 2020.

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Figure 1. Figure 1. Declines in 100‐ and 2000‐m rowing performance with advancing age. Both short‐ and longer distance rowing performance decline with advancing age in the curvilinear fashion. Data are from world record rowing times registered on Concept2 indoor rowers.
Figure 2. Figure 2. Progression of 100‐m sprint running times (men A and women B), 400‐m running times (men C and women D), and 100‐m freestyle swimming times (men E and women F) from 1975 to 2013. The progressions of exercise performance times are progressively greater as the ages of participants increase. The general trends are similar across different athletic events. Reproduced, with permission, from Akkari A, et al., 2015 5.
Figure 3. Figure 3. Changes in the number of participating athletes in the World Masters Games from 1989 to 2017. There are substantial increases in the participants in masters athletic competitions in recent years.
Figure 4. Figure 4. A hypothetical diagram showing that masters athletes have attenuated reductions of age‐related brain functional decline and dementia risk when compared with sedentary adults. Lifelong exercise training may have the cumulative effects for mitigating behavioral and physiological functional declines associated with aging.
Figure 5. Figure 5. Age‐related differences in cognitive performance based on the NIH (National Institute of Health) Toolbox scores. The unadjusted fluid (n = 1265), crystallized (n = 1161), and global (n = 1164) intelligence scores were collected from a normative sample (age range = 18–85 years) in the United States. Note that fluid intelligence decreases progressively with age, while crystallized intelligence is maintained until very old age. As a result, global intelligence remains at a high level until middle age, and then starts declining in later life. The data were obtained from the NIH Toolbox technical manual (nihtoolbox.org/).
Figure 6. Figure 6. Cognitive performance in middle‐aged endurance athletes and sedentary adults. This study suggests that long‐term endurance training may attenuate age‐related declines in fluid intelligence that consists of memory and executive function. *P < 0.05. Reproduced, with permission, from Tarumi T, et al., 2013 332 with permission.
Figure 7. Figure 7. T1‐weighted brain images acquired from representative young and old subjects who have normal cognitive function. Note that a 76‐year‐old individual has significant brain atrophy with enlarged ventricles and increased spacings between cortical gyri and sulci, when compared with the 28‐year‐old subject. Figures 7,8,9 show imaging data from the same individuals.
Figure 8. Figure 8. Fluid‐attenuated inversion recovery images acquired from representative young and old subjects who have normal cognitive function. Note that a 76‐year‐old individual has periventricular white matter hyperintensities (WMH) near the anterior and posterior horns of the lateral ventricle and deep WMH at the centrum semiovale when compared with the 28‐year‐old subject. Figures 7,8,9 show imaging data from the same individuals.
Figure 9. Figure 9. Diffusion tensor images acquired from representative young and old subjects who have normal cognitive function. Note that a 76‐year‐old individual has significant attenuations of fractional anisotropy at major cerebral white matter fiber tracts. This suggests the overall reductions of fiber tract integrity when compared with the 28‐year‐old subject. Conversely, radial diffusivity is increased in a 76‐year‐old individual, which suggests axonal demyelination that may be contributing to the reduced fractional anisotropy. Figures 7,8,9 show imaging data from the same individuals.
Figure 10. Figure 10. Carotid arterial blood pressure (CABP) and cerebral blood flow velocity (CBFV) waveforms measured from the representative, healthy young (31‐year‐old female), middle‐aged (54‐year‐old male), and old (80‐year‐old female) subjects. CBF velocity was normalized to the mean value and expressed in percentage to focus on the pulsatility amplitude around the mean. CBF velocity was recorded from the middle cerebral artery using transcranial Doppler. Note that CABP and CBFV pulsatility progressively increase with age. This suggests that increased cardiovascular pulsatility is transmitted into the cerebral circulation.
Figure 11. Figure 11. Conceptual interrelationship among α‐MN disruption, sarcopenia, sarcosthenia, and dynapenia. α‐MN discharge determines fiber‐type‐specific adaptations via electrical activation and development of mechanical tension. Accordingly, α‐MN disruption can directly and indirectly (via sarcopenia and sarcosthenia) cause dynapenia.
Figure 12. Figure 12. Peak muscular power, normalized for body mass, assessed in masters athletes with different athletic specializations and plotted against age. Reproduced, with permission, from Michaelis I, et al., 2008 213.
Figure 13. Figure 13. Comparison of percent declines per decade in muscle strength, power, and mass. Studies that provided that information in master athletes were selected. Note the comparatively small scatter of power values on the y‐axis. Percent changes per decade were calculated from regression equations in published literature as 1000 × slope/intercept. Where these equations were not available, they were calculated from the data reported in the literature. Zero values in parentheses indicate nonsignificant decrements with age.
Figure 14. Figure 14. The mechanostat concept considers tissue's mechanoadaptation as a negative feedback system, analogous to a thermostat. While thermostats enable constancy of temperature, the mechanostat keeps the tissue strains constant by adding or removing material in response to altering forces. Material evidence for the mechanostat concept had been provided by Rubin and Lanyon 288, whose data are exemplified in the present diagram. Reproduced, with permission, from Gruber M, et al., 2019 112.
Figure 15. Figure 15. Illustration of the structural measures: cross‐sectional area (CSA), area moment of resistance (R), and the area moment of inertia (I). Given are four beams with simple geometric shape and the human tibia, all five with identical CSA. The greater the R, the greater the beam or bone resistance to bending. The greater the I, the greater the resistance to torsion. I and R vary with the direction. Given are the values for x (anteroposterior) and y (lateral) flexion. The further the material is from the structure's center, the greater the I and R. Thus, material eccentricity provides an idea of a structure's relative adaptation to bending and torsion. Reproduced, with permission, from Rittweger J, et al., 2000 278.
Figure 16. Figure 16. Bone strength indicators for the tibia shaft in a cohort of 375 masters sprinters, middle‐ and long‐distance runners, race walkers, and sedentary control subjects. (A) Percent ratios of values in the athlete groups versus sedentary adults. Thus, a reading of 125% indicates “25% stronger than normal.” (B) Cortical area in the same cohort as a function of age. Each athletic group was divided into six equally large age groups, the mean values of which are indicated by the symbols. The black solid line represents mean values of all athletes. The gray line represents means from the sedentary group. The larger cortical area that young runners benefit from is not present in runners above age 80. *p < 0.05, **p < 0.01, ***p < 0.001. Reproduced, with permission, from Wilks DC, et al., 2009 363.
Figure 17. Figure 17. Age‐associated changes in basal cardiovascular functions and structures in healthy but sedentary adults when the values at young age (20 years) were expressed as baseline. Data are derived from a variety of sources 65,66,122,193,218,220,249,320,329.
Figure 18. Figure 18. Age‐associated reductions in maximal oxygen consumption with advancing age in sedentary, recreationally active, and endurance‐trained women. The rate of decline in maximal oxygen consumption with increasing subject group age was lowest in sedentary women, greater in recreationally active women, and greatest in endurance‐trained women. Reproduced, with permission, Fitzgerard MD, et al., 1997 86.
Figure 19. Figure 19. Carotid artery compliance and beta‐stiffness index of middle‐aged sedentary controls (54 ± 2 years), masters runners (52 ± 2 years), and masters swimmers (56 ± 2 years). Carotid artery compliance was significantly greater, and β‐stiffness index was significantly lower in masters runners and swimmers than in sedentary controls as indicated by *. Reproduced, with permission, from Nualnim N, et al., 2011 240 with permission.


Figure 1. Declines in 100‐ and 2000‐m rowing performance with advancing age. Both short‐ and longer distance rowing performance decline with advancing age in the curvilinear fashion. Data are from world record rowing times registered on Concept2 indoor rowers.


Figure 2. Progression of 100‐m sprint running times (men A and women B), 400‐m running times (men C and women D), and 100‐m freestyle swimming times (men E and women F) from 1975 to 2013. The progressions of exercise performance times are progressively greater as the ages of participants increase. The general trends are similar across different athletic events. Reproduced, with permission, from Akkari A, et al., 2015 5.


Figure 3. Changes in the number of participating athletes in the World Masters Games from 1989 to 2017. There are substantial increases in the participants in masters athletic competitions in recent years.


Figure 4. A hypothetical diagram showing that masters athletes have attenuated reductions of age‐related brain functional decline and dementia risk when compared with sedentary adults. Lifelong exercise training may have the cumulative effects for mitigating behavioral and physiological functional declines associated with aging.


Figure 5. Age‐related differences in cognitive performance based on the NIH (National Institute of Health) Toolbox scores. The unadjusted fluid (n = 1265), crystallized (n = 1161), and global (n = 1164) intelligence scores were collected from a normative sample (age range = 18–85 years) in the United States. Note that fluid intelligence decreases progressively with age, while crystallized intelligence is maintained until very old age. As a result, global intelligence remains at a high level until middle age, and then starts declining in later life. The data were obtained from the NIH Toolbox technical manual (nihtoolbox.org/).


Figure 6. Cognitive performance in middle‐aged endurance athletes and sedentary adults. This study suggests that long‐term endurance training may attenuate age‐related declines in fluid intelligence that consists of memory and executive function. *P < 0.05. Reproduced, with permission, from Tarumi T, et al., 2013 332 with permission.


Figure 7. T1‐weighted brain images acquired from representative young and old subjects who have normal cognitive function. Note that a 76‐year‐old individual has significant brain atrophy with enlarged ventricles and increased spacings between cortical gyri and sulci, when compared with the 28‐year‐old subject. Figures 7,8,9 show imaging data from the same individuals.


Figure 8. Fluid‐attenuated inversion recovery images acquired from representative young and old subjects who have normal cognitive function. Note that a 76‐year‐old individual has periventricular white matter hyperintensities (WMH) near the anterior and posterior horns of the lateral ventricle and deep WMH at the centrum semiovale when compared with the 28‐year‐old subject. Figures 7,8,9 show imaging data from the same individuals.


Figure 9. Diffusion tensor images acquired from representative young and old subjects who have normal cognitive function. Note that a 76‐year‐old individual has significant attenuations of fractional anisotropy at major cerebral white matter fiber tracts. This suggests the overall reductions of fiber tract integrity when compared with the 28‐year‐old subject. Conversely, radial diffusivity is increased in a 76‐year‐old individual, which suggests axonal demyelination that may be contributing to the reduced fractional anisotropy. Figures 7,8,9 show imaging data from the same individuals.


Figure 10. Carotid arterial blood pressure (CABP) and cerebral blood flow velocity (CBFV) waveforms measured from the representative, healthy young (31‐year‐old female), middle‐aged (54‐year‐old male), and old (80‐year‐old female) subjects. CBF velocity was normalized to the mean value and expressed in percentage to focus on the pulsatility amplitude around the mean. CBF velocity was recorded from the middle cerebral artery using transcranial Doppler. Note that CABP and CBFV pulsatility progressively increase with age. This suggests that increased cardiovascular pulsatility is transmitted into the cerebral circulation.


Figure 11. Conceptual interrelationship among α‐MN disruption, sarcopenia, sarcosthenia, and dynapenia. α‐MN discharge determines fiber‐type‐specific adaptations via electrical activation and development of mechanical tension. Accordingly, α‐MN disruption can directly and indirectly (via sarcopenia and sarcosthenia) cause dynapenia.


Figure 12. Peak muscular power, normalized for body mass, assessed in masters athletes with different athletic specializations and plotted against age. Reproduced, with permission, from Michaelis I, et al., 2008 213.


Figure 13. Comparison of percent declines per decade in muscle strength, power, and mass. Studies that provided that information in master athletes were selected. Note the comparatively small scatter of power values on the y‐axis. Percent changes per decade were calculated from regression equations in published literature as 1000 × slope/intercept. Where these equations were not available, they were calculated from the data reported in the literature. Zero values in parentheses indicate nonsignificant decrements with age.


Figure 14. The mechanostat concept considers tissue's mechanoadaptation as a negative feedback system, analogous to a thermostat. While thermostats enable constancy of temperature, the mechanostat keeps the tissue strains constant by adding or removing material in response to altering forces. Material evidence for the mechanostat concept had been provided by Rubin and Lanyon 288, whose data are exemplified in the present diagram. Reproduced, with permission, from Gruber M, et al., 2019 112.


Figure 15. Illustration of the structural measures: cross‐sectional area (CSA), area moment of resistance (R), and the area moment of inertia (I). Given are four beams with simple geometric shape and the human tibia, all five with identical CSA. The greater the R, the greater the beam or bone resistance to bending. The greater the I, the greater the resistance to torsion. I and R vary with the direction. Given are the values for x (anteroposterior) and y (lateral) flexion. The further the material is from the structure's center, the greater the I and R. Thus, material eccentricity provides an idea of a structure's relative adaptation to bending and torsion. Reproduced, with permission, from Rittweger J, et al., 2000 278.


Figure 16. Bone strength indicators for the tibia shaft in a cohort of 375 masters sprinters, middle‐ and long‐distance runners, race walkers, and sedentary control subjects. (A) Percent ratios of values in the athlete groups versus sedentary adults. Thus, a reading of 125% indicates “25% stronger than normal.” (B) Cortical area in the same cohort as a function of age. Each athletic group was divided into six equally large age groups, the mean values of which are indicated by the symbols. The black solid line represents mean values of all athletes. The gray line represents means from the sedentary group. The larger cortical area that young runners benefit from is not present in runners above age 80. *p < 0.05, **p < 0.01, ***p < 0.001. Reproduced, with permission, from Wilks DC, et al., 2009 363.


Figure 17. Age‐associated changes in basal cardiovascular functions and structures in healthy but sedentary adults when the values at young age (20 years) were expressed as baseline. Data are derived from a variety of sources 65,66,122,193,218,220,249,320,329.


Figure 18. Age‐associated reductions in maximal oxygen consumption with advancing age in sedentary, recreationally active, and endurance‐trained women. The rate of decline in maximal oxygen consumption with increasing subject group age was lowest in sedentary women, greater in recreationally active women, and greatest in endurance‐trained women. Reproduced, with permission, Fitzgerard MD, et al., 1997 86.


Figure 19. Carotid artery compliance and beta‐stiffness index of middle‐aged sedentary controls (54 ± 2 years), masters runners (52 ± 2 years), and masters swimmers (56 ± 2 years). Carotid artery compliance was significantly greater, and β‐stiffness index was significantly lower in masters runners and swimmers than in sedentary controls as indicated by *. Reproduced, with permission, from Nualnim N, et al., 2011 240 with permission.
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Further Reading
 1.Baker J, Horton S, Weir P, editors. The Masters Athlete: Understanding the Role of Sport and Exercise in Optimizing Aging. New York, NY: Routledge, 2010.
 2.Harridge SD, Lazarus NR. Physical activity, aging, and physiological function. Physiology 32 (2): 152‐161, 2017.

Further Reading

Baker, J., S. Horton, and P. Weir (eds). The Masters Athlete: Understanding the Role of Sport and Exercise in Optimizing Aging. Routledge, New York, NY 2010.

Harridge, S.D. and N.R. Lazarus. Physical Activity, Aging, and Physiological Function. Physiology 32(2): 152-161, 2017.


 

Teaching Material

Hirofumi Tanaka, Takashi Tarumi, Jörn Rittweger. Aging and Physiological Lessons from Master Athletes. Compr Physiol 10: 2020, 261-296.

Didactic Synopsis

Major Teaching Points:

*Sedentary aging is associated with marked declines in key physiological functions.

*Masters athletes are able to achieve exceptional athletic and physiological functional performance.

*The study of masters athletes has provided useful insight into the positive example of successful aging.

*Endurance athletes in middle and old ages have attenuated cognitive decline and brain structural and functional deteriorations compared with the age-matched sedentary adults.

*Masters Athletes lose their neuromuscular power at a rate of 8% per decade, whereas muscle mass is reduced by ~5% per decade.

*Arm bones can benefit substantially even if upper body exercise (e.g., competitive tennis) is started in adulthood.

*Age-related bone loss in Masters athletes seems comparable to the general population.

*Older masters athletes possess greater functional capacity at any given age than their sedentary peers.

*Strenuous exercise training performed by Masters endurance athletes may be associated with heightened risks of developing atrial fibrillation and coronary artery atherosclerosis.

*Future research and action are needed to further establish and propagate Masters athletics as a role model for our aging society.

 


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How to Cite

Hirofumi Tanaka, Takashi Tarumi, Jörn Rittweger. Aging and Physiological Lessons from Master Athletes. Compr Physiol 2019, 10: 261-296. doi: 10.1002/cphy.c180041