HOMEPRODUCTSCOMPANYCONTACTFAQResearchDictionaryPharmaSign Up FREE or Login

Association of Combined Slow Gait and Low Activity Fragmentation With Later Onset of Cognitive Impairment.

AbstractImportance:
Among older people, slow walking is an early indicator of risk for Alzheimer disease (AD). However, studies that have assessed this association have not considered that slow walking may have different causes, some of which are not necessarily associated with higher AD risk.
Objective:
To evaluate whether low activity fragmentation among older adults with slow gait speed indicates neurological causes of slow walking that put these individuals at higher risk of AD.
Design, Setting, and Participants:
This prospective cohort study performed survival analyses using data from the Baltimore Longitudinal Study of Aging. Participants included 520 initially cognitively normal persons aged 60 years or older. New diagnoses of mild cognitive impairment (MCI) or AD were adjudicated during a mean (SD) follow-up of 7.3 (2.7) years. Initial assessment of gait speed and activity fragmentation occurred from January 3, 2007, to May 11, 2015, with follow-up completed on December 31, 2020. Data were analyzed from February 1 to May 15, 2021.
Exposures:
Gait speed for 6 m and activity fragmentation assessed by accelerometry.
Main Outcomes and Measures:
Associations of gait speed, activity fragmentation, and their interaction with incident MCI/AD were evaluated using Cox proportional hazards models, adjusted for covariates.
Results:
Among the 520 participants (265 women [51.0%]; 125 Black participants [24.0%]; 367 White participants [70.6%]; mean [SD] age, 73 [8] years), MCI/AD developed in 64 participants. Each 0.05-m/s slower gait was associated with a 7% increase in risk of developing MCI/AD (hazard ratio [HR], 1.07 [95% CI, 1.00-1.15]; P = .04). Activity fragmentation alone was not associated with MCI/AD risk (HR, 0.83 [95% CI, 0.56-1.23]; P = .35), but there was a significant interaction between gait speed and activity fragmentation (HR, 0.92 [95% CI, 0.87-0.98]; P = .01). At low activity fragmentation (-1 SD), each 0.05-m/s slower gait speed was associated with a 19% increase in hazard of developing MCI/AD (HR, 1.19 [95% CI, 1.07-1.32]), whereas at higher activity fragmentation (+1 SD), gait speed was not associated with MCI/AD (HR, 1.01 [95% CI, 0.93-1.10]). Among participants with slow gait, higher activity fragmentation was associated with higher odds of having lower extremity osteoarthritis (odds ratio, 1.31 [95% CI, 1.01-1.69]) and less decline in pegboard dominant hand performance (β = 0.026 [SE, 0.009]; P > .05).
Conclusions and Relevance:
These findings suggest that frequent rests among older adults with slow gait speed are associated with lower risk of future MCI/AD and that this behavioral strategy is associated with a lower likelihood of subclinical neurological impairment.
AuthorsQu Tian, Stephanie A Studenski, Yang An, Pei-Lun Kuo, Jennifer A Schrack, Amal A Wanigatunga, Eleanor M Simonsick, Susan M Resnick, Luigi Ferrucci
JournalJAMA network open (JAMA Netw Open) Vol. 4 Issue 11 Pg. e2135168 (11 01 2021) ISSN: 2574-3805 [Electronic] United States
PMID34792590 (Publication Type: Journal Article, Research Support, N.I.H., Extramural, Research Support, N.I.H., Intramural)
Topics
  • Aged
  • Aged, 80 and over
  • Aging (physiology, psychology)
  • Alzheimer Disease (diagnosis, physiopathology)
  • Baltimore
  • Cognitive Dysfunction (diagnosis, physiopathology)
  • Female
  • Humans
  • Longitudinal Studies
  • Male
  • Middle Aged
  • Proportional Hazards Models
  • Prospective Studies
  • Risk Assessment (methods, statistics & numerical data)
  • Walking Speed (physiology)

Join CureHunter, for free Research Interface BASIC access!

Take advantage of free CureHunter research engine access to explore the best drug and treatment options for any disease. Find out why thousands of doctors, pharma researchers and patient activists around the world use CureHunter every day.
Realize the full power of the drug-disease research graph!


Choose Username:
Email:
Password:
Verify Password:
Enter Code Shown: