Evidence map›Paper›PMID 24766880›Full record

ArticleHealth and quality of life outcomes2014

Exploratory analysis of health-related quality of life among the empty-nest elderly in rural China: an empirical study in three economically developed cities in eastern China.

Ying Liang, Wei Wu

Abstract read
In one paragraph

Article in Health and quality of life outcomes, 2014. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 45 papers, 2 of them syntheses that pooled it.

0numbers the graph read from it
0cells of the map it votes in
45citing papers in PubMed, 2 pooled it
–field-weighted citation impact
1 · What the graph read from it

What it found

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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

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3 · Its place in the literature

Who cites it

45 citing papers in PubMed, 2 syntheses or guidelines pooled it.

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4 · The record

Corrections and comments

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5 · Who and what money

Authors and funding

2 authors.

Ying LiangDepartment of Social Work and Social Policy, School of Social and Behavioral Sciences, Nanjing University, Nanjing 210023, Jiangsu province, People's Republic of China. njulucy79@gmail.com.
Wei Wu

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundAlong with rapid economic development, the aging process in China is gradually accelerating. The living conditions of empty-nest rural elderly are worrisome. As a more vulnerable group, empty-nest elderly are facing more urgent health problems. This study explores the health-related quality of life (HRQOL) of empty-nest elderly in rural China and aims to arouse more social concern for their HRQOL.

methodsResearch subjects were empty-nest rural elderly from three cities: Nanjing, Suzhou, and Wenzhou (ages ≥ 60, n = 967). This study used the five-dimensional European quality of health scale (EQ-5D) and the 12-item Short Form Health Survey (SF-12) to measure the HRQOL of the respondents. Spearman correlation coefficient, stereotype logistic regression, ordered probit regression and multinomial logistic regression, and Structural equation model (SEM) methods are employed to study the relationship.

results(1) The Spearman correlation coefficient shows that the correlations of similar domains between the SF-12 and the EQ-5D scales are relatively strong. (2) Men's scores are higher than that of women's in general health (GH) and anxiety/depression (AD) models. (3) The scores of physical component summary (PCS), physical functioning (PF), mental health (MH), and usual activities (UA) decline with age. (4) Apart from PCS, vitality (VT), and role-emotional (RE) as dependent variables, the education passes all the significance tests. The higher the education is, the higher the scores of physical or psychological health are. (5) The scores of PCS and bodily pain (BP) of empty-nest elderly are divorced or higher in other marital status. (6) In SEM analysis, the effect of basic information of empty-nest elderly on SF-12 scale is more significant.

conclusionsFirst, the frequency histograms of EQ-5D show that the scores of empty-nest elderly in rural China are generally low. Second, in all SF-12 items, the HRQOL is low. Third, men's scores are higher than that of women's. The elderly with higher education reported higher scores than those with lower education. Fourth, the effect of socio-demographic variables of the rural Chinese empty-nest elderly on SF-12 scores is more significant, whereas the effect on EQ-5D scores is less significant.

Indexed as

Quality of LifeActivities of Daily LivingAgedAged, 80 and overAge FactorsAnxietyChinaDepressionEducational StatusEmpirical ResearchFamilyFemaleHealth StatusHumansLogistic ModelsMale

Identifiers

PMID24766880
PMCPMC4016644

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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.