Evidence map›Paper›PMID 30429143›Full record

ArticleBMJ open2018

Quality of life, loneliness and health-related characteristics among older people in Liaoning province, China: a cross-sectional study.

Yaxin Zhu, Jie Liu, Bo Qu, Zhe Yi

Abstract read
In one paragraph

Article in BMJ open, 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 21 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
21citing papers in PubMed, 1 pooled it
–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

21 citing papers in PubMed, 1 synthesis or guideline pooled it.

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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

4 authors.

Yaxin ZhuDepartment of Social Medicine, School of Public Health, China Medical University, Shenyang, People's Republic of China.
Jie LiuDepartment of Health Statistics, School of Public Health, China Medical University, Shenyang, People's Republic of China.
Bo Qu *Department of Health Statistics, School of Public Health, China Medical University, Shenyang, People's Republic of China.
Zhe Yi *Department of Prothodontics, School of Stomatology, China Medical University, Shenyang, People's Republic of China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

objectivesThe aim of the study was to examine the relations among quality of life (QOL), loneliness and health-related characteristics in a sample of Chinese older people.

designCross-sectional study.

settingCommunities in Dandong city, Liaoning province, China.

participantsSample of 732 older people aged 60 and older who were living in Dandong, Liaoning province, China.

methodsA questionnaire was administered to the participants face-to-face. The questionnaire contained four sections: demographic characteristics, health-related characteristics, the EQ-5D Scale and the UCLA Loneliness Scale. The t-test, F-test and multivariable linear regression analyses were performed to individually test associations between the demographic data, health-related characteristics, loneliness and QOL.

resultsChronic diseases, loneliness, age and smoking status were negatively associated with QOL (p<0.05). Satisfaction with health services, income and physical activity were positively associated with QOL (p<0.05).

conclusionsLoneliness, chronic diseases and health service satisfaction were important factors related to low QOL among older people in China. The findings indicate that reducing loneliness, managing chronic diseases and improving the health service may help to improve the QOL for older people.

Indexed as

Health StatusQuality of LifeAgedAged, 80 and overChinaChronic DiseaseCross-Sectional StudiesExerciseFemaleGeriatric AssessmentHumansLogistic ModelsLonelinessMaleMiddle AgedPatient Satisfactionlonelinessolder peoplequality of life

Identifiers

PMID30429143
PMCPMC6252650

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LicenceCC BY-NC
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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.