Evidence map›Paper›PMID 36650472›Full record

ArticleBMC psychiatry2023

Association between age and loneliness in different residential type and gender groups: evidence from China.

Yang Wang, Weikang Jiang, Lei Wu

Abstract read
In one paragraph

Article in BMC psychiatry, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 8 papers.

0numbers the graph read from it
0cells of the map it votes in
8citing 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

8 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

3 authors.

Yang WangDepartment of Social Work and Social Policy, School of Sociology and Population Studies, Renmin University of China, No. 59, Zhongguancun Street, Haidian District, Beijing, China.
Weikang JiangSchool of Public Administration, Xiangtan University, Xiangtan, China.
Lei WuDepartment of Social Work and Social Policy, School of Sociology and Population Studies, Renmin University of China, No. 59, Zhongguancun Street, Haidian District, Beijing, China. leiwu@ruc.edu.cn.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundAge has been identified as a prominent predictor of loneliness, although the findings about the relationship between age and loneliness are inconclusive. This study examines the relationship between age and loneliness in the context of China, with a focus on residential and gender differences.

methodsData were from the Chinese General Social Survey (CGSS) of 2017. A total of 3899 respondents were included. Loneliness was measured using a three-item Short Loneliness Scale. Age, squared terms of age, residential type, gender, and other socio-demographic characteristics were included in the study. Regression analyses were conducted among the total sample and subgroups of different gender and residential type subgroups, to investigate the association between age and loneliness.

resultsThere is a reverse U-shaped tendency between age and loneliness that peaks at the age of 47. This tendency is true of the male subgroup, that peaks at the age of 55, while the female respondents do not share that tendency. The inverted U-shaped distribution holds true for urban but not for rural residents. The female respondents reported a higher level of loneliness than the male. The rural respondents reported higher loneliness than their counterparts.

conclusionsThis study demonstrates that an inverted U-shaped tendency between age and loneliness existed for the entire group, and the male and urban subgroups. Implications for service and practice are proposed based on the empirical findings.

Indexed as

LonelinessChinaEast Asian PeopleFemaleHumansMaleRural PopulationUrban PopulationAgeChinaGenderLonelinessResidential type

Identifiers

PMID36650472
PMCPMC9843997

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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.