Evidence map›Paper›PMID 33920050›Full record

ArticleInternational journal of environmental research and public health2021

Multilevel Factors Associated with Frailty among the Rural Elderly in Korea Based on the Ecological Model.

Ah Ram Jang, Ju Young Yoon

Open access · goldAbstract read
In one paragraph

Article in International journal of environmental research and public health, 2021. 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
0.1field-weighted citation impact, top 56% 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

3 citing papers in PubMed, 4 citations in OpenAlex.

  1. Article
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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

2 authors at 1 institution in 1 country.

Ah Ram JangCenter for Human-Caring Nurse Leaders for the Future by Brain Korea 21 (BK 21) Four Project, College of Nursing, Seoul National University, Seoul 03080, Korea.ORCID 0000-0002-6148-5131
Ju Young YoonCenter for Human-Caring Nurse Leaders for the Future by Brain Korea 21 (BK 21) Four Project, College of Nursing, Seoul National University, Seoul 03080, Korea.ORCID 0000-0003-3944-0663
Seoul National University · KR

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Frailty is prevalent in the rural elderly and, as a result, they are vulnerable to serious health problems. The purpose of this study was to examine the multilevel factors affecting frailty among the rural elderly using the ecological model. A total of 386 participants aged 65 years or older from 60 rural areas were included in the study. Frailty was measured using the Cardiovascular Health Study frailty index. Multilevel logistic regression analysis was used to identify the factors affecting frailty among the rural elderly. The results show that the levels of prevalence for robust, pre-frailty, and frailty groups were 81 (21%), 216 (56%), and 89 (23%), respectively. As for intrapersonal factors, old age, lower than middle school education, low and moderate levels of physical activity, depressive symptoms, and cognitive dysfunction significantly increased the risk of frailty; however, no interpersonal and community factors were significant in affecting frailty. The findings indicate that individualized strategies to encourage physical activity, prevent depressive symptoms, and preserve cognitive function are needed to prevent frailty in the rural elderly.

Indexed as

FrailtyAgedCross-Sectional StudiesFrail ElderlyGeriatric AssessmentHumansPrevalenceRepublic of KoreaRural Populationecological modelfrailtymultilevel analysismultilevel factorsrural elderly

Identifiers

PMID33920050
PMCPMC8071005
OpenAlexW3153592016

What OpenQuestion holds

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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.