The DOI matches its Crossref record; 1 of the 1 references it cites were found in a registry or an index.
Femoral Neck Structure in Adult Female Athletes Subjected to Different Loading Modalities
Open accessAbstract
Loading modality is a strong external determinant of structure and concomitant strength of the femoral neck. Particularly effective seem to be loadings, which arise from high impacts or impacts from atypical loading directions. Introduction: Physical loading plays an important role, not only in the process of bone modeling and remodeling, but also in shaping a mechanically appropriate bone structure. This study aimed at testing the hypothesis that the type of loading partly determines the femoral neck structure. Materials and Methods: A total of 255 premenopausal female athletes representing volleyball, hurdling, squash-playing, soccer, speed skating, step aerobics, weight-lifting, orienteering, cross-country skiing, cycling, and swimming and their 30 nonathletic counterparts were measured with DXA. Besides the conventional areal BMD (aBMD) of the femoral neck, the hip structure analysis (HSA) was used to estimate the cross-sectional area (CSA), subperiosteal width (W), and section modulus (Z, an index of bone strength) at the narrowest section of the femoral neck. Also, training history, muscle strength, and calcium intake were assessed. The above-mentioned sports were classified according to the type of loading they apparently produce at the hip region; that is, high-impact loading (volleyball, hurdling), odd-impact loading (squash-playing, soccer, speed-skating, step aerobics), high-magnitude loading (weightlifting), low-impact loading (orienteering, cross-country skiing), and nonimpact loading (swimming, cycling). Results: High-impact and odd-impact loading sports were associated with the highest age-, weight-, and height-adjusted aBMD (23% and 29% higher values compared to nonathletic referents), CSA (22% and 27%), and Z (22% and 26%). In contrast, repetitive, nonimpact loading sports were not associated with any clear benefit in any bone value compared with the referents. The W at the narrowest femoral neck section was similar in all groups. Body height and weight accounted virtually for one-half of the variation in Z, whereas the type of loading predicted 13% of the total variation of this variable—clearly more than the 2% attributable to isometric leg extension strength. Both high-impact and odd-impact loading modalities were associated with a large benefit in Z, corresponding to >1 SD in the reference group, whereas repetitive, low-impact loading showed a benefit that was only one-half of that. Surprisingly, high-magnitude loading (weightlifting) was not associated with a statistically significant increase in Z. Conclusion: We conclude that mechanical loading and its modality are strong external determinants of structure and concomitant strength of the femoral neck. Particularly effective seem to be loadings, which arise from high impacts or impacts from atypical loading directions.
Overview
The claims and statistics of this paper haven’t been checked yet.
Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.
Integrity signals
Registry
Cites
Statistics
Verification
Claims the paper makes
The claims and statistics of this paper haven’t been checked yet.
Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.
Claims other papers make about this one
Each is checked against this paper’s own text: does it say what the citing paper says it does?
In the citing paper
“In young adults, the benefits of regular exercise have been suggested to depend upon the type of activity, being greater in high impact activities such as sprinting whereas little benefit is evident in lower impact activities such as walking, cycling, or swimming [8–10].”
From Hip and spine bone mineral density are greater in master sprinters, but not endurance runners compared with non-athletic controls (2018) · cites this paper as [8]
Self-check
Percentages, sums and reported differences re-computed from the paper’s own numbers.
The self-check needs the paper’s full text.
Citations
Cites
Bone mineral density of female athletes in different sports
Heinonen, A., Oja, P., Kannus, P., Sievänen, H., Mänttäri, A., & Vuori, I. (1993) · Bone and Mineral · doi:10.1016/s0169-6009(08)80086-4 · Cited by 206
Self-citation
Cited by
De Souza, M. J., Nattiv, A., Joy, E., Misra, M., Williams, N. I., Mallinson, R. J., Gibbs, J. C., Olmsted, M., Goolsby, M., Matheson, G., et al. (2014) · British Journal of Sports Medicine · doi:10.1136/bjsports-2013-093218 · Cited by 661
Martyn-St James, M., & Carroll, S. (2009) · British Journal of Sports Medicine · doi:10.1136/bjsm.2008.052704 · Cited by 299
Vitamin D and the athlete: current perspectives and new challenges
Owens, D. J., Allison, R., & Close, G. L. (2018) · Sports Medicine · doi:10.1007/s40279-017-0841-9 · Cited by 223
Recovery of muscle atrophy and bone loss from 90 days bed rest: Results from a one-year follow-up
Rittweger, J., & Felsenberg, D. (2009) · Bone · doi:10.1016/j.bone.2008.10.044 · Cited by 120
Kohrt, W. M., Wherry, S. J., Wolfe, P., Sherk, V. D., Wellington, T., Swanson, C. M., Weaver, C. M., & Boxer, R. S. (2018) · Journal of Bone and Mineral Research · doi:10.1002/jbmr.3428 · Cited by 105
Metadata
- Authors
- Nikander, R., Sievänen, H., Heinonen, A., & Kannus, P.
- Venue
- Journal of Bone and Mineral Research
- Publisher
- Oxford University Press (OUP)
- Published
- 2005-03-01
- Volume
- 20
- Issue
- 3
- Pages
- 520-528
- ISSN
- 0884-0431 (ISSN-L)
- 1523-4681
- OpenAlex
- W2086561363
- Cited by
- 261
- References
- 1
- FWCI
- 11.14
- Type
- journal article
- Language
- en
- Open access
- bronze
About these checks
Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.
Statistics and arithmetic are recomputed, not judged.
Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.
What counts as a claim ›How we measure confidence ›How we check this ›
Are you an author, or do you see a problem with this page? Request a review
Data sources
Bibliographic data: Semantic Scholar, OpenAlex, Crossref.
Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).
Semantic Scholar’s data is described in: Kinney, R., et al. (2023). The Semantic Scholar Open Data Platform. arXiv:2301.10140.