Evidence map›Paper›PMID 36429561›Full record

ArticleInternational journal of environmental research and public health2022

The Incidence of Falls and Related Factors among Chinese Elderly Community Residents in Six Provinces.

Kun Wang, Meijun Chen, Xiaoyue Zhang, Lanchao Zhang, Chun Chang, Yu Tian, Xiaofeng Wang, Zhijing Li, Ying Ji

Abstract read
In one paragraph

Article in International journal of environmental research and public health, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 15 papers.

0numbers the graph read from it
0cells of the map it votes in
15citing 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

15 citing papers in PubMed.

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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

9 authors.

Kun WangDepartment of Social Medicine and Health Education, School of Public Health, Peking University Health Science Center, Beijing 100191, China.
Meijun ChenSchool of Public Health, The University of Hong Kong, Hong Kong 999077, China.
Xiaoyue ZhangDepartment of Social Medicine and Health Education, School of Public Health, Peking University Health Science Center, Beijing 100191, China.
Lanchao ZhangDepartment of Social Medicine and Health Education, School of Public Health, Peking University Health Science Center, Beijing 100191, China.
Chun ChangDepartment of Social Medicine and Health Education, School of Public Health, Peking University Health Science Center, Beijing 100191, China.
Yu TianXinjiekou Community Health Service Center of Xicheng District, Beijing 100035, China.
Xiaofeng WangRonghua Community Health Service Center of Beijing Economic-Technological Development Area, Beijing 100176, China.
Zhijing LiSchool of Health Humanities, Peking University Health Science Center, Beijing 100191, China.
Ying JiDepartment of Social Medicine and Health Education, School of Public Health, Peking University Health Science Center, Beijing 100191, China.ORCID 0000-0001-5957-2204

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

This cross-sectional study classified the factors related to falls among residents ≥ 60 years old in China in order to provide evidence for the prevention of falls in the elderly. A total of 2994 participants were enrolled, and the correlations between social demography, physical health, self-health management awareness, family support, and fall risk were analyzed. Factors influencing falls were classified by location, cause, and the activity during falls. Suffering from osteoarthropathy (OR = 1.761, 95% CI: 1.234-2.513,

Indexed as

Accidental FallsAgedChinaCross-Sectional StudiesHumansIncidenceMiddle AgedRisk FactorsChinese older peoplefallsfamily supportrisk factorsself-health management awareness

Identifiers

PMID36429561
PMCPMC9690932

What OpenQuestion holds

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LicenceCC BY
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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.