Evidence map›Paper›PMID 37265982›Full record

ArticleCanadian geriatrics journal : CGJ2023

Leisure Sedentary Time is Associated with Self-Reported Falls in Middle-aged and Older Females and Males: an Analysis of the CLSA.

Lúcio G Lustosa, David Rudoler, Olga Theou, Shilpa Dogra

Abstract read
In one paragraph

Article in Canadian geriatrics journal : CGJ, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.

0numbers the graph read from it
0cells of the map it votes in
3citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

3 citing papers in PubMed.

  1. Article
  2. Article
  3. Article
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

4 authors.

Lúcio G LustosaFaculty of Health Sciences (Kinesiology), Ontario Tech University, Oshawa, ON.
David RudolerFaculty of Health Sciences (Kinesiology), Ontario Tech University, Oshawa, ON.
Olga TheouDepartment of Medicine, Dalhousie University, Halifax, NS.
Shilpa DograFaculty of Health Sciences (Kinesiology), Ontario Tech University, Oshawa, ON.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Aim: The purpose of this analysis was to report the prevalence of falls and falls-related injuries among those reporting different volumes of weekly sedentary time, and to understand the association of sedentary time and falls, accounting for functional fitness. Methods: Baseline and first follow-up data from the Canadian Longitudinal Study on Aging (CSLA) were analyzed (n=22,942). Participants self-reported whether they had a fall in the past 12 months (at baseline) and whether they had an injury that was a result of a fall (follow-up). In-home interviews collected self-reported leisure sedentary time using the Physical Activity Scale for Elderly. Functional fitness was assessed using grip strength, timed-up-and-go, and chair rise tests during clinic visits. Results: The prevalence of falls was higher among those who reported higher sedentary time. For example, among males aged 65 and older who reported lower sedentary time (<1,080 min/week), the prevalence of falls in the past 12 months (at baseline) was 7.8% compared to 9.8% in those reporting higher sedentary time. The odds of reporting a fall (at baseline) was 21% higher in those who reported higher sedentary time (OR: 1.21; 95%CI: 1.11-1.33) in adjusted models. No associations were found between sedentary time and injuries due to a fall. Conclusions: Reporting high volumes of sedentary time may increase the risk of falls. Future research using device-based estimates of total sedentary time and breaks in sedentary time is needed to further elucidate this association.

Indexed as

agingCLSAfunctional fitnesssedentary behavioursitting

Identifiers

PMID37265982
PMCPMC10198681

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Registered trials

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.