Literature DB >> 32965610

A combined stepping and visual tracking task predicts cognitive decline in older adults better than gait or visual tracking tasks alone: a prospective study.

Yosuke Osuka1, Hunkyung Kim2, Yutaka Watanabe3, Yu Taniguchi4, Narumi Kojima2, Satoshi Seino5, Hisashi Kawai6, Ryota Sakurai5, Hiroki Inagaki2, Shuichi Awata2, Shoji Shinkai7.   

Abstract

BACKGROUND: It is unclear whether motor-cognitive dual tasks predict cognitive decline better than either motor or cognitive tasks alone. AIMS: To examine the utility of the novel motor-cognitive dual-task test [Stepping Trail Making Test (S-TMT)], as a predictor of cognitive decline, and compare its predictive performance with single motor or cognitive tests.
METHODS: This 2-year population-based prospective study included 626 adults aged ≥ 70 years from Takashimadaira, Itabashi, Tokyo. The S-TMT measured the time taken to step on 16 numbers in order. Gait speed and TMT-A were assessed with standardized methods as single motor and cognitive tasks, respectively. A decline in the Mini-Mental State Examination score by ≥ 3 points over 2 years was defined as a significant cognitive decline.
RESULTS: Over 2 years, 97 (15.5%) experienced cognitive decline. After adjusting for confounders, binary logistic regression models showed no significant associations between gait speed, TMT-A time tertiles, and risk of cognitive decline, but participants in the longest tertile of S-TMT time were more likely to develop cognitive decline than those of the shortest tertile (odds ratio 2.14; 95% confidence interval 1.17-3.90). Only the addition of the S-TMT time to the covariates model significantly improved the reclassification indices for predicting cognitive decline (net reclassification improvement: 0.31, P < 0.01; integrated discrimination improvement: 0.01, P = 0.02). DISCUSSION AND
CONCLUSION: Only the S-TMT was significantly associated with cognitive decline and improved reclassification indices, indicating that it is more useful for predicting cognitive decline than individual gait speed or visual tracking tests alone.

Entities:  

Keywords:  C-statistics; Integrated discrimination improvement; Net reclassification improvement; Predictive performance

Mesh:

Year:  2020        PMID: 32965610     DOI: 10.1007/s40520-020-01714-w

Source DB:  PubMed          Journal:  Aging Clin Exp Res        ISSN: 1594-0667            Impact factor:   3.636


  35 in total

Review 1.  Poor Gait Performance and Prediction of Dementia: Results From a Meta-Analysis.

Authors:  Olivier Beauchet; Cédric Annweiler; Michele L Callisaya; Anne-Marie De Cock; Jorunn L Helbostad; Reto W Kressig; Velandai Srikanth; Jean-Paul Steinmetz; Helena M Blumen; Joe Verghese; Gilles Allali
Journal:  J Am Med Dir Assoc       Date:  2016-02-04       Impact factor: 4.669

2.  Cognitive ability and physical performance in middle-aged African Americans.

Authors:  Theodore K Malmstrom; Fredric D Wolinsky; Elena M Andresen; J Philip Miller; Douglas K Miller
Journal:  J Am Geriatr Soc       Date:  2005-06       Impact factor: 5.562

Review 3.  Walking Pace and the Risk of Cognitive Decline and Dementia in Elderly Populations: A Meta-analysis of Prospective Cohort Studies.

Authors:  Minghui Quan; Pengcheng Xun; Cheng Chen; Ju Wen; Yiyu Wang; Ru Wang; Peijie Chen; Ka He
Journal:  J Gerontol A Biol Sci Med Sci       Date:  2016-12-07       Impact factor: 6.053

4.  A prospective study of gait performance and subsequent cognitive decline in a general population of older Japanese.

Authors:  Yu Taniguchi; Hiroto Yoshida; Yoshinori Fujiwara; Yutaka Motohashi; Shoji Shinkai
Journal:  J Gerontol A Biol Sci Med Sci       Date:  2012-03-02       Impact factor: 6.053

5.  Handgrip strength and cognitive decline in older Mexican Americans.

Authors:  Ana Alfaro-Acha; Soham Al Snih; Mukaila A Raji; Yong-Fang Kuo; Kyriakos S Markides; Kenneth J Ottenbacher
Journal:  J Gerontol A Biol Sci Med Sci       Date:  2006-08       Impact factor: 6.053

6.  Physical frailty predicts future cognitive decline - a four-year prospective study in 2737 cognitively normal older adults.

Authors:  T W Auyeung; J S W Lee; T Kwok; J Woo
Journal:  J Nutr Health Aging       Date:  2011-08       Impact factor: 4.075

7.  Gait speed or gait variability, which one to use as a marker of risk to develop Alzheimer disease? A pilot study.

Authors:  S Gillain; M Dramé; F Lekeu; V Wojtasik; C Ricour; J-L Croisier; E Salmon; J Petermans
Journal:  Aging Clin Exp Res       Date:  2015-06-16       Impact factor: 3.636

8.  Independent predictors of cognitive decline in healthy elderly persons.

Authors:  Scott Marquis; M Milar Moore; Diane B Howieson; Gary Sexton; Haydeh Payami; Jeffrey A Kaye; Richard Camicioli
Journal:  Arch Neurol       Date:  2002-04

9.  Assessing the temporal relationship between cognition and gait: slow gait predicts cognitive decline in the Mayo Clinic Study of Aging.

Authors:  Michelle M Mielke; Rosebud O Roberts; Rodolfo Savica; Ruth Cha; Dina I Drubach; Teresa Christianson; Vernon S Pankratz; Yonas E Geda; Mary M Machulda; Robert J Ivnik; David S Knopman; Bradley F Boeve; Walter A Rocca; Ronald C Petersen
Journal:  J Gerontol A Biol Sci Med Sci       Date:  2012-12-18       Impact factor: 6.053

10.  Gait speed under varied challenges and cognitive decline in older persons: a prospective study.

Authors:  Nandini Deshpande; E Jeffrey Metter; Stefania Bandinelli; Jack Guralnik; Luigi Ferrucci
Journal:  Age Ageing       Date:  2009-06-23       Impact factor: 10.668

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  2 in total

1.  Dual-Task Gait as a Predictive Tool for Cognitive Impairment in Older Adults: A Systematic Review.

Authors:  Felipe Ramírez; Myriam Gutiérrez
Journal:  Front Aging Neurosci       Date:  2021-12-24       Impact factor: 5.750

Review 2.  Predictive Validity of Motor Fitness and Flexibility Tests in Adults and Older Adults: A Systematic Review.

Authors:  Nuria Marín-Jiménez; Carolina Cruz-León; Alejandro Perez-Bey; Julio Conde-Caveda; Alberto Grao-Cruces; Virginia A Aparicio; José Castro-Piñero; Magdalena Cuenca-García
Journal:  J Clin Med       Date:  2022-01-10       Impact factor: 4.241

  2 in total

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