Evidence map›Paper›PMID 35672842›Full record

ArticleBMC public health2022

Classifying and characterizing the development of self-reported overall quality of life among the Chinese elderly: a twelve-year longitudinal study.

Xitong Huang, Minqiang Zhang, Junyan Fang, Qing Zeng, Jinqing Wang, Jia Li

Abstract read
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Article in BMC public health, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers.

0numbers the graph read from it
0cells of the map it votes in
4citing papers in PubMed
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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

4 citing papers in PubMed.

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4 · The record

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5 · Who and what money

Authors and funding

6 authors.

Xitong HuangSchool of Psychology, South China Normal University, West of Zhongshan Avenue, Tianhe District, Guangzhou City, 510631, Guangdong Province, China.
Minqiang ZhangSchool of Psychology, South China Normal University, West of Zhongshan Avenue, Tianhe District, Guangzhou City, 510631, Guangdong Province, China. Zhangminqiang@m.scnu.edu.cn.
Junyan FangSchool of Psychology, South China Normal University, West of Zhongshan Avenue, Tianhe District, Guangzhou City, 510631, Guangdong Province, China.
Qing ZengSchool of Psychology, South China Normal University, West of Zhongshan Avenue, Tianhe District, Guangzhou City, 510631, Guangdong Province, China.
Jinqing WangSchool of Psychology, South China Normal University, West of Zhongshan Avenue, Tianhe District, Guangzhou City, 510631, Guangdong Province, China.
Jia LiSchool of Psychology, South China Normal University, West of Zhongshan Avenue, Tianhe District, Guangzhou City, 510631, Guangdong Province, China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundTo promote healthy aging, the information about the development of quality of life (QoL) is of great importance. However, the explorations of the heterogeneity in the change of QoL under the Chinese context were limited. This study aimed to identify potential different development patterns of QoL and the influential factors using a longitudinal, nationally representative sample of the Chinese elderly.

methodsWe adopted a five-wave longitudinal dataset from the Chinese Longitudinal Healthy Longevity Survey (CLHLS), and a total of 1645 elderly were obtained. The sample had a mean age of 72.7 years (SD = 6.64) and was 47.2% male. Overall QoL was measured through self-report during the longitudinal process. We utilized the conditional growth mixture model (GMM) with time-invariant covariates (TICs) to explore various development patterns and associated factors.

resultsThree distinct trajectories of self-reported overall QoL were identified: the High-level Steady Group (17.08%), the Mid-level Steady Group (63.10%), and the Low-level Growth Group (19.82%). Results also indicated that several factors predicted distinct trajectories of self-reported overall QoL. Those elderly who received enough financial resources, had adequate nutrition, did not exhibit any disability, engaged in leisure activities, and did less physical labor or housework at the baseline were more likely to report a higher level of overall QoL over time.

conclusionsThere existed three development patterns of self-reported overall QoL in elders, and the findings provided valuable implications for the maintenance and improvement of QoL among the Chinese elderly. Future studies could examine the influence of other confounding factors.

Indexed as

Health StatusQuality of LifeAgedChinaFemaleHumansLongitudinal StudiesMaleSelf ReportChinese elderlyChinese longitudinal healthy longevity surveyGrowth mixture modelSelf-reported overall quality of life

Identifiers

PMID35672842
PMCPMC9175517

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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.