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Subsystems Contributing to the Decline in Ability to Walk: Bridging the Gap Between Epidemiology and Geriatric Practice in the InCHIANTI Study
Abstract
BACKGROUND: Older patients are often referred to geriatricians because of complaints of progressive difficulties in walking. The diagnostic and therapeutic approach to these patients is complex. Multiple physiologic subsystems may influence the ability to walk, and no standard criteria are currently available to establish whether these subsystems are functioning within the normal range. To address this lack of knowledge we conducted the InCHIANTI study. OBJECTIVE: To identify measures that clinicians can use to understand the causes of walking difficulties in older persons. DESIGN: A population‐based study of persons living in the Chianti geographic area (Tuscany, Italy). PARTICIPANTS: 1453 persons (age‐range 20–102 years; 91.6% of the eligible) selected from city registry of Greve in Chianti and Bagno a Ripoli (Tuscany, Italy), using a multistage sampling method. MEASUREMENTS: Factors that influence walking ability were classified into six main physiologic subsystems: central nervous system, perceptual system, peripheral nervous system, muscles, bone/joints, and energy production/delivery. Measures of the integrity and functioning of each of these proposed subsystems were identified and administered to all participants. CONCLUSIONS: Data collected in InCHIANTI will be used to identify the main risk factors that influence loss of the ability to walk in older persons, to define physiologic subsystems that are critical for walking, to select the best measures of their integrity, and to establish critical ranges in these measures that are compatible with “normal” walking ability. The final goal is to translate epidemiological research into a geriatric clinical tool that makes possible more precise diagnosis and more effective treatment in patients with walking dysfunction.
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Landi, F., Marzetti, E., Liperoti, R., Pahor, M., Russo, A., Martone, A. M., Colloca, G., Capoluongo, E., & Bernabei, R. (2013) · Journal of the American Medical Directors Association · doi:10.1016/j.jamda.2013.04.012 · Cited by 54
Meaningful Improvement in Gait Speed in Hip Fracture Recovery
Alley, D. E., Hicks, G. E., Shardell, M., Hawkes, W., Miller, R., Craik, R. L., Mangione, K. K., Orwig, D., Hochberg, M., Resnick, B., et al. (2011) · Journal of the American Geriatrics Society · doi:10.1111/j.1532-5415.2011.03560.x · Cited by 54
Inflammation and Trajectory of Renal Function in Community‐Dwelling Older Adults
Salimi, S., Shardell, M. D., Seliger, S. L., Bandinelli, S., Guralnik, J. M., & Ferrucci, L. (2018) · Journal of the American Geriatrics Society · doi:10.1111/jgs.15268 · Cited by 48
Self-citationO’Keefe, J. H., Tintle, N. L., Harris, W. S., O’Keefe, E. L., Sala-Vila, A., Attia, J., Garg, G. M., Hure, A., Bork, C. S., Schmidt, E. B., et al. (2024) · Stroke · doi:10.1161/strokeaha.123.044281 · Cited by 46
Self-citationMild thyroid hormone excess is associated with a decreased physical function in elderly men
Ceresini, G., Ceda, G. P., Lauretani, F., Maggio, M., Bandinelli, S., Guralnik, J. M., Cappola, A. R., Usberti, E., Morganti, S., Valenti, G., et al. (2011) · The Aging Male · doi:10.3109/13685538.2011.606514 · Cited by 41
Self-citationGonadal status and physical performance in older men
Maggio, M., Ceda, G. P., Lauretani, F., Bandinelli, S., Metter, E. J., Guralnik, J. M., Basaria, S., Cattabiani, C., Luci, M., Dall'Aglio, E., et al. (2011) · The Aging Male · doi:10.3109/13685538.2010.518179 · Cited by 38
Self-citationBartali, B., Benvenuti, E., Corsi, A. M., Bandinelli, S., Russo, C. R., Di Iorio, A., Lauretani, F., & Ferrucci, L. (2002) · Sozial- und Präventivmedizin¶Social and Preventive Medicine¶Médecine social et préventive · doi:10.1007/pl00012644 · Cited by 37
Self-citationTimed up and go test predicts mortality in older adults in Peru: a population-based cohort study
Ascencio, E. J., Cieza-Gómez, G. D., Carrillo-Larco, R. M., & Ortiz, P. J. (2022) · BMC Geriatrics · doi:10.1186/s12877-022-02749-6 · Cited by 35
Gene expression markers of age-related inflammation in two human cohorts
Pilling, L. C., Joehanes, R., Melzer, D., Harries, L. W., Henley, W., Dupuis, J., Lin, H., Mitchell, M., Hernandez, D., Ying, S.-X., et al. (2015) · Experimental Gerontology · doi:10.1016/j.exger.2015.05.012 · Cited by 24
Self-citationMaggio, M., Cattabiani, C., Lauretani, F., Artoni, A., Bandinelli, S., Schiavi, G., Vignali, A., Volpi, R., Ceresini, G., Lippi, G., et al. (2012) · Atherosclerosis · doi:10.1016/j.atherosclerosis.2012.09.014 · Cited by 24
Self-citation
Metadata
- Authors
- Ferrucci, L., Bandinelli, S., Benvenuti, E., Di Iorio, A., Macchi, C., Harris, T. B., & Guralnik, J. M.
- Venue
- Journal of the American Geriatrics Society
- Publisher
- Wiley
- Published
- 2000-12
- Volume
- 48
- Issue
- 12
- Pages
- 1618-1625
- ISSN
- 0002-8614 (ISSN-L)
- 1532-5415
- OpenAlex
- W1985305462
- Cited by
- 804
- References
- 8
- FWCI
- 30.52
- Type
- journal article
- Language
- en
- Open access
- closed
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 ›
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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.