Evidence map›Paper›PMID 35978947›Full record

ArticleFrontiers in aging neuroscience2022

Association between walking speed and cognitive domain functions in Chinese suburban-dwelling older adults.

Hong Wang, Hui Zhang, Yaoxin Chen, Ming Cai, Cailian Guo, Peijie Chen

Open access · goldAbstract read
In one paragraph

Article in Frontiers in aging neuroscience, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 12 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
12citing papers in PubMed, 1 pooled it
1.1field-weighted citation impact, top 21% of its field
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

12 citing papers in PubMed, 1 synthesis or guideline pooled it, 11 citations in OpenAlex.

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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

6 authors at 2 institutions in 1 country.

Hong WangSchool of Kinesiology, Shanghai University of Sport, Shanghai, China.
Hui ZhangJiangwan Hospital of Shanghai Hongkou District, Shanghai University of Medicine and Health Science Affiliated First Rehabilitation Hospital, Shanghai, China.
Yaoxin ChenCollege of Rehabilitation Sciences, Shanghai University of Medicine and Health Sciences, Shanghai, China.
Ming CaiCollege of Rehabilitation Sciences, Shanghai University of Medicine and Health Sciences, Shanghai, China.
Cailian GuoSchool of Kinesiology, Shanghai University of Sport, Shanghai, China.
Peijie ChenSchool of Kinesiology, Shanghai University of Sport, Shanghai, China.
Shanghai University of Medicine and Health Sciences · CNShanghai University of Sport · CN

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Objective: To examine the relationship among walking speed, cognitive impairment, and cognitive domain functions in older men and women living in a Chinese suburban community. Methods: In total, 625 elderly (72.54 ± 5.80 years old) men ( Results: Around 11.6% of men and 14.2% of women had slow walking speeds. After adjusting for age, body mass index (BMI), education level, spouse, faller, the Geriatric Depression Scale (GDS) score, heart disease, stroke, arthritis, and low back pain, walking speed was negatively related to cognitive impairment in men ( Conclusion: The relationship between walking speed and cognitive impairment was only significant in men, but the association with impaired orientation was found in both men and women. Assessing the walking speed of the elderly is beneficial, which may help with early detection and early therapeutic prevention of cognitive impairment.

Indexed as

cognitive domain functionscognitive impairmentorientationsex-differenceslow walking speed

Identifiers

PMID35978947
PMCPMC9377637
OpenAlexW4289169866

What OpenQuestion holds

Textmetadata
LicenceCC BY
Read underepoch 390

Registered trials

None linked

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.