"Study protocol for the ≥65 years NOrthern jutland Cohort of Fall risk Assessment with Objective measurements (the NOCfao study)"

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Abstract

BACKGROUND: Accidental falls are common among community-dwellers, probably due to the level of physical activity and impaired postural stability. Today, fall risk prediction tools' discriminative validity are only moderate. In order to increase the accuracy, multiple variables such as highly validated objective field measurements of physical activity and impaired postural stability should be adressed in order to predict falls. The main aim of this paper is to describe the ≥65 years NOrthern jutland Cohort of Fall risk Assessment with Objective measurements (NOCfao) investigating the association between physical activity and impaired postural stability and the risk of fall episodes among community-dwelling older adults.

METHODS: The study consists of a baseline session where the participants are asked to respond to three questionnaires, perform physical tests (i.e., measuring strength in the upper and lower extremities, balance, and walking speed), participate in an assessment of pain sensitivity, and to wear an ankle mounted pedometer for measuring physical activity for 5 days. Subsequently, the fall incidences and the circumstances surrounding the falls during the previous 1 to 2 months will be recorded throughout a one-year follow-up period.

DISCUSSION: This study will add to the present-day understanding of the association between physical activity and impaired postural stability and the risk of fall episodes among community-dwelling older adults. These data will provide valid and reliable information on the relationship between these variables and their significance for community-dwelling older adults.

TRIAL REGISTRATION: ClinicalTrials.gov identifier: NCT2995317. Registered December 13th, 2016.

Original languageEnglish
Article number198
JournalBMC Geriatrics
Volume20
Issue number1
ISSN1471-2318
DOIs
Publication statusPublished - 8 Jun 2020

Keywords

  • Accelerometry
  • Elderly
  • Fall detection
  • Older people
  • Physical activity
  • Physical behavior
  • Physical exposures
  • Risk prediction
  • Technical measurements

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