Skip to content
2000
  1. Home
  2. A-Z Publications
  3. Current Neurovascular Research
  4. Volume 21, Issue 2
  5. Article
Volume 21, Issue 2
  • ISSN: 1567-2026
  • E-ISSN: 1875-5739

Abstract

Background

This study aims to explore the correlation between body composition, encompassing factors such as muscle mass and fat distribution, and gait performance during both single-task walking (STW) and dual-task walking (DTW) in patients diagnosed with cerebral small vessel disease (CSVD).

Methods

The data of hospitalized patients diagnosed with CSVD, including cadence, stride time, velocity and stride length, as well as information on variability, asymmetry and coordination during both STW and DTW, were assessed. The number of falls reported by each participant was also assessed.

Results

A total of 95 CSVD patients were assessed, and the results showed that individuals with low appendicular skeletal muscle mass (ASM), which includes both the low ASM group and the combination of low ASM and high body fat (BF) group, had reduced velocity or cadence, shortened stride length, and prolonged stride time across all walking modalities compared to the control group. Only the combination of the low ASM and high BF group exhibited a deterioration in the coefficient of variation (CV) for all basic parameters and the Phase Coordination Index (PCI) compared to the control group across all walking patterns. Conversely, patients in the high BF group displayed a decline in basic parameters, primarily during cognitive DTW. Concurrently, the high BF group showed a significant increase in the CV and the PCI compared to the control group only during cognitive DTW. Furthermore, regardless of gender, both ASM and BF independently correlated with the occurrence of falls.

Conclusions

CSVD patients with varying body compositions could allocate different levels of attention to their daily walking routines.

© 2024 Bentham Science Publishers
Loading

Article metrics loading...

/content/journals/cnr/10.2174/0115672026307602240321081657
2024-03-28
2025-01-24

  • From This Site

    /content/journals/cnr/10.2174/0115672026307602240321081657
    dcterms_title,dcterms_subject,pub_keyword
    -contentType:Contributor -contentType:Concept -contentType:Institution
    10
    5
Loading full text...

Full text loading...

References

  1. MitchellE. WalkerR. Global ageing: Successes, challenges and opportunities.Br. J. Hosp. Med.20208121910.12968/hmed.2019.0377 32097073
     [Google Scholar]
  2. JudgeRoy JO, Davis B III, Ounpuu S. Step length reductions in advanced age: The role of ankle and hip kinetics.J. Gerontol. A Biol. Sci. Med. Sci.199651A6M303M31210.1093/gerona/51A.6.M303 8914503
     [Google Scholar]
  3. Ben ChaabaneN. ConzeP.H. LempereurM. Quantitative gait analysis and prediction using artificial intelligence for patients with gait disorders.Sci. Rep.20231312309910.1038/s41598‑023‑49883‑8 38155189
     [Google Scholar]
  4. ToebesM.J.P. HoozemansM.J.M. FurrerR. DekkerJ. van DieënJ.H. Local dynamic stability and variability of gait are associated with fall history in elderly subjects.Gait Posture201236352753110.1016/j.gaitpost.2012.05.016 22748312
     [Google Scholar]
  5. GanzD.A. LathamN.K. Prevention of falls in community-dwelling older adults.N. Engl. J. Med.2020382873474310.1056/NEJMcp1903252 32074420
     [Google Scholar]
  6. García-de-VillaS. NeiraG.G.V. ÁlvarezM.N. A database with frailty, functional and inertial gait metrics for the research of fall causes in older adults.Sci. Data202310156610.1038/s41597‑023‑02428‑0 37626053
     [Google Scholar]
  7. HuysmansS.M.D. SendenR. JacobsE. Gait alterations in patients with adult spinal deformity.N Am Spine Soc J20241710030610.1016/j.xnsj.2023.100306 38293567
     [Google Scholar]
  8. HennahC. DoumasM. Dual-task walking on real-world surfaces: Adaptive changes in walking speed, step width and step height in young and older adults.Exp. Gerontol.202317711220010.1016/j.exger.2023.112200 37160198
     [Google Scholar]
  9. XiaC. XieH. LiT. DingY. ZhàoH. HuangY. Spatiotemporal gait characteristics during single- and dual-task walking are associated with the burden of cerebral small vessel disease.Front. Neurol.202314128594710.3389/fneur.2023.1285947 38020659
     [Google Scholar]
  10. ClarkD.J. Automaticity of walking: Functional significance, mechanisms, measurement and rehabilitation strategies.Front. Hum. Neurosci.2015924610.3389/fnhum.2015.00246 25999838
     [Google Scholar]
  11. WardlawJ.M. SmithE.E. BiesselsG.J. Neuroimaging standards for research into small vessel disease and its contribution to ageing and neurodegeneration.Lancet Neurol.201312882283810.1016/S1474‑4422(13)70124‑8 23867200
     [Google Scholar]
  12. HilalS. MokV. YounY.C. WongA. IkramM.K. ChenC.L.H. Prevalence, risk factors and consequences of cerebral small vessel diseases: data from three Asian countries.J. Neurol. Neurosurg. Psychiatry201788866967410.1136/jnnp‑2016‑315324 28600443
     [Google Scholar]
  13. WardlawJ.M. DebetteS. JokinenH. De LeeuwF.E. PantoniL. ChabriatH. ESO Guideline on covert cerebral small vessel disease.Eur. Stroke J.202162CXICLXII
     [Google Scholar]
  14. BoyerK.A. HayesK.L. UmbergerB.R. Age-related changes in gait biomechanics and their impact on the metabolic cost of walking: Report from a national institute on aging workshop.Exp. Gerontol.202317311210210.1016/j.exger.2023.112102 36693530
     [Google Scholar]
  15. Paranhos AmorimD.N. NascimentoD.C. StoneW. AlvesV.P. Coelho Vilaça e SilvaK.H. Body composition and functional performance of older adults.Osteoporos. Sarcopenia202282869110.1016/j.afos.2022.04.002 35832415
     [Google Scholar]
  16. JafariNasabian P, Inglis JE, Reilly W, Kelly OJ, Ilich JZ. Aging human body: Changes in bone, muscle and body fat with consequent changes in nutrient intake.J. Endocrinol.20172341R37R5110.1530/JOE‑16‑0603 28442508
     [Google Scholar]
  17. OhY.H. ChoiS. LeeG. SonJ.S. KimK.H. ParkS.M. Changes in body composition are associated with metabolic changes and the risk of metabolic syndrome.J. Clin. Med.202110474510.3390/jcm10040745 33668451
     [Google Scholar]
  18. LaRocheD.P. KralianR.J. MillettE.D. Fat mass limits lower-extremity relative strength and maximal walking performance in older women.J. Electromyogr. Kinesiol.201121575476110.1016/j.jelekin.2011.07.006 21824789
     [Google Scholar]
  19. MuehlbauerT. GranacherU. BordeR. HortobágyiT. Non-discriminant relationships between leg muscle strength, mass and gait performance in healthy young and old adults.Gerontology2018641111810.1159/000480150 28918423
     [Google Scholar]
  20. Bani HassanE. PhuS. VogrinS. Diagnostic value of mid-thigh and mid-calf bone, muscle, and fat mass in osteosarcopenia: A pilot study.Calcif. Tissue Int.2019105439240210.1007/s00223‑019‑00582‑5 31292687
     [Google Scholar]
  21. Chojdak-ŁukasiewiczJ. DziadkowiakE. ZimnyA. ParadowskiB. Cerebral small vessel disease: A review.Adv. Clin. Exp. Med.202130334935610.17219/acem/131216 33768739
     [Google Scholar]
  22. ZhangY. ChangP. LiuN. Correlation between lenticulostriate arteries and white matter microstructure changes in patients with cerebral small vessel disease.Front. Neurosci.202317120253810.3389/fnins.2023.1202538 37817799
     [Google Scholar]
  23. ZhàoH. WeiW. LiuY. GaoJ. HuangY. Cognitive frailty among elderly chinese patients with cerebral small vessel disease: A structural MRI study.Front. Med.2020739710.3389/fmed.2020.00397 33015078
     [Google Scholar]
  24. PlotnikM. GiladiN. HausdorffJ.M. A new measure for quantifying the bilateral coordination of human gait: Effects of aging and Parkinson’s disease.Exp. Brain Res.2007181456157010.1007/s00221‑007‑0955‑7 17503027
     [Google Scholar]
  25. SwansonC.W. FlingB.W. Associations between gait coordination, variability and motor cortex inhibition in young and older adults.Exp. Gerontol.201811316317210.1016/j.exger.2018.10.002 30296454
     [Google Scholar]
  26. RichmondS.B. SwansonC.W. PetersonD.S. FlingB.W. A temporal analysis of bilateral gait coordination in people with multiple sclerosis.Mult. Scler. Relat. Disord.20204510244510.1016/j.msard.2020.102445 32791490
     [Google Scholar]
  27. HanS.H. KimC.O. KimK.J. Quantitative analysis of the bilateral coordination and gait asymmetry using inertial measurement unit-based gait analysis.PLoS One20191410e022291310.1371/journal.pone.0222913 31574130
     [Google Scholar]
  28. KalronA. Gait variability across the disability spectrum in people with multiple sclerosis.J. Neurol. Sci.20163611610.1016/j.jns.2015.12.012 26810506
     [Google Scholar]
  29. LingC.H.Y. de CraenA.J.M. SlagboomP.E. Accuracy of direct segmental multi-frequency bioimpedance analysis in the assessment of total body and segmental body composition in middle-aged adult population.Clin. Nutr.201130561061510.1016/j.clnu.2011.04.001 21555168
     [Google Scholar]
  30. ChenF. WuL. ChenY. A comparison of bioelectrical impedance analysis and air displacement plethysmography to assess body composition in children.Front. Public Health202311116455610.3389/fpubh.2023.1164556 37469700
     [Google Scholar]
  31. KimM.K. HanK. KwonH.S. Normal weight obesity in K orean adults.Clin. Endocrinol.201480221422010.1111/cen.12162 23362933
     [Google Scholar]
  32. KimD.H. LimH. ChangS. KimJ.N. RohY.K. ChoiM.K. Association between body fat and bone mineral density in normal-weight middle-aged koreans.Korean J. Fam. Med.201940210010510.4082/kjfm.17.0082 30441887
     [Google Scholar]
  33. BaumgartnerR.N. KoehlerK.M. GallagherD. Epidemiology of sarcopenia among the elderly in New Mexico.Am. J. Epidemiol.1998147875576310.1093/oxfordjournals.aje.a009520 9554417
     [Google Scholar]
  34. Cruz-JentoftA.J. BaeyensJ.P. BauerJ.M. Sarcopenia: European consensus on definition and diagnosis.Age Ageing201039441242310.1093/ageing/afq034 20392703
     [Google Scholar]
  35. ChenL.K. WooJ. AssantachaiP. Asian working group for sarcopenia: 2019 consensus update on sarcopenia diagnosis and treatment.J. Am. Med. Dir. Assoc.202021330030710.1016/j.jamda.2019.12.012 32033882
     [Google Scholar]
  36. ZhouZ. HuangY. WangJ. SuH. TangH. WangY. A novel digital biomarker of sarcopenia in frail elderly: New combination of gait parameters under dual-task walking.Front. Aging Neurosci.202315108731810.3389/fnagi.2023.1087318 36891555
     [Google Scholar]
  37. KimB. YoumC. ParkH. LeeM. ChoiH. Association of muscle mass, muscle strength, and muscle function with gait ability assessed using inertial measurement unit sensors in older women.Int. J. Environ. Res. Public Health20221916990110.3390/ijerph19169901 36011529
     [Google Scholar]
  38. BeurskensR. MuehlbauerT. GranacherU. Association of dual-task walking performance and leg muscle quality in healthy children.BMC Pediatr.2015151210.1186/s12887‑015‑0317‑8 25652949
     [Google Scholar]
  39. WardlawJ.M. SmithC. DichgansM. Small vessel disease: Mechanisms and clinical implications.Lancet Neurol.201918768469610.1016/S1474‑4422(19)30079‑1 31097385
     [Google Scholar]
  40. FinsterwalderS. WuehrM. GesierichB. Minor gait impairment despite white matter damage in pure small vessel disease.Ann. Clin. Transl. Neurol.20196102026203610.1002/acn3.50891 31524338
     [Google Scholar]
  41. LimJ. KimJ. SeoK. van EmmerikR.E.A. LeeS. The effects of mobile texting and walking speed on gait characteristics of normal weight and obese adults.Mot. Contr.202024458860410.1123/mc.2020‑0006 32916659
     [Google Scholar]
  42. ShaikA.R. Al QahtaniM. AhmadF. Impacts of adiposity on the attentional cost of sensory-motor performance associated with mobility in a dual-task paradigm.Int. J. Environ. Res. Public Health202219201311810.3390/ijerph192013118 36293706
     [Google Scholar]
  43. YangY. ShieldsG.S. GuoC. LiuY. Executive function performance in obesity and overweight individuals: A meta-analysis and review.Neurosci. Biobehav. Rev.20188422524410.1016/j.neubiorev.2017.11.020 29203421
     [Google Scholar]
  44. VisserM. GoodpasterB.H. KritchevskyS.B. Muscle mass, muscle strength, and muscle fat infiltration as predictors of incident mobility limitations in well-functioning older persons.J. Gerontol. A Biol. Sci. Med. Sci.200560332433310.1093/gerona/60.3.324 15860469
     [Google Scholar]
  45. BeaversK.M. BeaversD.P. HoustonD.K. Associations between body composition and gait-speed decline: Results from the health, aging, and body composition study.Am. J. Clin. Nutr.201397355256010.3945/ajcn.112.047860 23364001
     [Google Scholar]
  46. MerchantR.A. ChanY.H. LingN. DenishkrshnaA. LimZ. WatersD. Association of physical function and body composition with falls in pre-frail older adults with poor physical performance: A cross-sectional study.Arch. Gerontol. Geriatr.202310910495710.1016/j.archger.2023.104957 36780754
     [Google Scholar]
  47. G R Neri S, Tiedemann A, B Gadelha A, M Lima R. Body fat distribution in obesity and the association with falls: A cohort study of Brazilian women aged 60 years and over.Maturitas2020139646810.1016/j.maturitas.2020.06.009 32747043
     [Google Scholar]
/content/journals/cnr/10.2174/0115672026307602240321081657
Loading
Relationship between Body Composition and Gait Characteristics in Patients with Cerebral Small Vessel Disease
Curr Neurovasc Res 21, 205 (2024); https://doi.org/10.2174/0115672026307602240321081657
/content/journals/cnr/10.2174/0115672026307602240321081657
/content/journals/cnr/10.2174/0115672026307602240321081657
Loading

Data & Media loading...

Supplements

Supplementary material is available on the publisher’s website along with the published article.

file format download Download

  • Article Type:     Research Article
Keyword(s): body fat; Cerebral small vessel diseases; dual-task walking; gait; muscle mass; single-task walking (STW)

Most Cited Most Cited RSS feed

This is a required field
Please enter a valid email address
Approval was a Success
Invalid data
An Error Occurred
Approval was partially successful, following selected items could not be processed due to error
Please enter a valid_number test