The DOI matches its Crossref record; 8 of the 8 references it cites were found in a registry or an index.
The Effects of Aging and Training on Skeletal Muscle
Abstract
Aging results in a gradual loss of muscle function, and there are predictable age-related alterations in skeletal muscle function. The typical adult will lose muscle mass with age; the loss varies according to sex and the level of muscle activity. At the cellular level, muscles loose both cross-sectional area and fiber numbers, with type II muscle fibers being the most affected by aging. Some denervation of fibers may occur. The combination of these factors leads to an increased percentage of type I fibers in older adults. Metabolically, the glycolytic enzymes seem to be little affected by aging, but the aerobic enzymes appear to decline with age. Aged skeletal muscle produces less force and there is a general “slowing” of the mechanical characteristics of muscle. However, neither reduced muscle demand nor the subsequent loss of function is inevitable with aging. These losses can be minimized or even reversed with training. Endurance training can improve the aerobic capacity of muscle, and resistance training can improve central nervous system recruitment of muscle and increase muscle mass. Therefore, physical activity throughout life is encouraged to prevent much of the age-related impact on skeletal muscle.
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Citations
Cites
High-Intensity Strength Training in Nonagenarians: Effects on Skeletal Muscle
Fiatarone, M. A. (1990) · JAMA · doi:10.1001/jama.1990.03440220053029 · Cited by 1,593
Leg extensor power and functional performance in very old men and women.
Bassey, E. J., Fiatarone, M. A., O'neill, E. F., Kelly, M., Evans, W. J., & Lipsitz, L. A. (1992) · Clinical Science · doi:10.1042/cs0820321 · Cited by 943
Contractile properties of skeletal muscles from young, adult and aged mice.
Brooks, S. V., & Faulkner, J. A. (1988) · The Journal of Physiology · doi:10.1113/jphysiol.1988.sp017279 · Cited by 777
Lexell, J., Henriksson‐Larsén, K., Winblad, B., & Sjöström, M. (1983) · Muscle & Nerve · doi:10.1002/mus.880060809 · Cited by 582
Grimby, G., & Saltin, B. (1983) · Clinical Physiology · doi:10.1111/j.1475-097x.1983.tb00704.x · Cited by 513
A physiological comparison of young and older endurance athletes
Heath, G. W., Hagberg, J. M., Ehsani, A. A., & Holloszy, J. O. (1981) · Journal of Applied Physiology · doi:10.1152/jappl.1981.51.3.634 · Cited by 459 · cited 1×
“maximal oxygen consumption declines about 10% per decade.(33,49) Some of the decline is related to central delivery”
BackgroundWhat is the effect of ageing on type 2 muscle fibres?
Lexell, J., & Downham, D. (1992) · Journal of the Neurological Sciences · doi:10.1016/0022-510x(92)90297-x · Cited by 133
Effect of aging on energy-rich phosphagens in human skeletal muscles
Möller, P., Bergström, J., Fürst, P., & Hellström, K. (1980) · Clinical Science · doi:10.1042/cs0580553 · Cited by 90 · cited 2×
“Total phosphagen content is due less to the previously mentioned muscle mass decreases; any changes in the elderly are due to a change in their activity pattern rather than any inherent age-related modifications.(6,12,44,48)”
Background
Cited by
Control of support limb muscles in recovery after tripping in young and older subjects
Pijnappels, M., Bobbert, M. F., & van Dieën, J. H. (2005) · Experimental Brain Research · doi:10.1007/s00221-004-2014-y · Cited by 167
Thomson, D. M., & Gordon, S. E. (2005) · Journal of Applied Physiology · doi:10.1152/japplphysiol.00811.2004 · Cited by 131
Responses to Maximal Strength Training in Different Age and Gender Groups
Kittilsen, H. T., Goleva-Fjellet, S., Freberg, B. I., Nicolaisen, I., Støa, E. M., Bratland-Sanda, S., Helgerud, J., Wang, E., Sæbø, M., & Støren, Ø. (2021) · Frontiers in Physiology · doi:10.3389/fphys.2021.636972 · Cited by 26
Vigelsø, A., Gram, M., Wiuff, C., Hansen, C. N., Prats, C., Dela, F., & Helge, J. W. (2016) · European Journal of Applied Physiology · doi:10.1007/s00421-015-3302-x · Cited by 13
Organotypic cultures as aging associated disease models
Sanchez, M. M., Bagdasarian, I. A., Darch, W., & Morgan, J. T. (2022) · Aging · doi:10.18632/aging.204361 · Cited by 12
Metadata
- Authors
- Kirkendall, D. T., & Garrett, W. E.
- Venue
- The American Journal of Sports Medicine
- Publisher
- SAGE Publications
- Published
- 1998-07
- Volume
- 26
- Issue
- 4
- Pages
- 598-602
- ISSN
- 0363-5465 (ISSN-L)
- 1552-3365
- OpenAlex
- W2154866540
- Cited by
- 263
- References
- 8
- FWCI
- 3.61
- Type
- journal article
- Language
- en
- Open access
- closed
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Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).
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