Literature DB >> 15563372

Gait unsteadiness and fall risk in two affective disorders: a preliminary study.

Jeffrey M Hausdorff1, Chung-Kang Peng, Ary L Goldberger, Andrew L Stoll.   

Abstract

BACKGROUND: In older adults, depression has been associated with increased fall risk, but the reasons for this link are not fully clear. Given parallels between major depression and Parkinson's disease, we hypothesized that major depression and related affective disorders would be associated with impairment in the ability to regulate the stride-to-stride fluctuations in gait cycle timing.
METHODS: We measured stride-to-stride fluctuations of patients with two forms of mood disorders, unipolar major depressive disorder (MDD) and bipolar disorder, and compared their gait to that of a healthy control group. The primary outcomes were two measures of gait unsteadiness that have been associated with fall risk: stride time variability and swing time variability.
RESULTS: Compared to the control group, the two patient groups tended to walk more slowly and with decreased swing time and increased stride time. However, none of these differences was statistically significant. Compared to the control group, swing time variability was significantly larger in the subjects with bipolar disorder (p < 0.0001) and in the subjects with MDD (p < 0.0004).
CONCLUSIONS: Patients with MDD and patients with bipolar disorder display gait unsteadiness. This perturbation in gait may provide a mechanistic link connecting depression and falls. The present findings also suggest the possibility that measurement of variability of gait may provide a readily quantifiable objective approach to monitoring depression and related affective disorders.

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Year:  2004        PMID: 15563372      PMCID: PMC538754          DOI: 10.1186/1471-244X-4-39

Source DB:  PubMed          Journal:  BMC Psychiatry        ISSN: 1471-244X            Impact factor:   3.630


  27 in total

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  28 in total

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Review 4.  Assessing the stability of human locomotion: a review of current measures.

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5.  Functional Data Analyses of Gait Data Measured Using In-Shoe Sensors.

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9.  Subsensory vibrations to the feet reduce gait variability in elderly fallers.

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