Evidence map›Paper›PMID 31200646›Full record

ArticleBMC geriatrics2019

The distribution and correlates of self-rated health in elderly Chinese: the China Kadoorie Biobank study.

Xingyue Song, Jing Wu, Canqing Yu, Wenhong Dong, Jun Lv, Yu Guo, Zheng Bian, Ling Yang, Yiping Chen, Zhengming Chen and 3 more

Abstract read
In one paragraph

Article in BMC geriatrics, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 7 papers.

0numbers the graph read from it
0cells of the map it votes in
7citing 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

7 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

13 authors.

Xingyue SongDepartment of Epidemiology and Biostatistics, and Ministry of Education Key Laboratory of Environment and Health, and State Key Laboratory of Environmental Health (Incubating), School of Public Health, Tongji Medical College, Huazhong University of Science and Technology, 13 Hangkong Rd, Wuhan, 430030, China.
Jing WuDepartment of Epidemiology and Biostatistics, and Ministry of Education Key Laboratory of Environment and Health, and State Key Laboratory of Environmental Health (Incubating), School of Public Health, Tongji Medical College, Huazhong University of Science and Technology, 13 Hangkong Rd, Wuhan, 430030, China.
Canqing YuDepartment of Epidemiology and Biostatistics, School of Public Health, Peking University Health Science Center, 38 Xueyuan Rd, Beijing, 100191, China.
Wenhong DongDepartment of Epidemiology and Biostatistics, and Ministry of Education Key Laboratory of Environment and Health, and State Key Laboratory of Environmental Health (Incubating), School of Public Health, Tongji Medical College, Huazhong University of Science and Technology, 13 Hangkong Rd, Wuhan, 430030, China.
Jun LvDepartment of Epidemiology and Biostatistics, School of Public Health, Peking University Health Science Center, 38 Xueyuan Rd, Beijing, 100191, China.
Yu GuoChinese Academy of Medical Sciences, Dong Cheng District, Beijing, China.
Zheng BianChinese Academy of Medical Sciences, Dong Cheng District, Beijing, China.
Ling YangClinical Trial Service Unit & Epidemiological Studies Unit (CTSU), Nuffield Department of Population Health, University of Oxford, Oxford, UK.
Yiping ChenClinical Trial Service Unit & Epidemiological Studies Unit (CTSU), Nuffield Department of Population Health, University of Oxford, Oxford, UK.
Zhengming ChenClinical Trial Service Unit & Epidemiological Studies Unit (CTSU), Nuffield Department of Population Health, University of Oxford, Oxford, UK.
An PanDepartment of Epidemiology and Biostatistics, and Ministry of Education Key Laboratory of Environment and Health, and State Key Laboratory of Environmental Health (Incubating), School of Public Health, Tongji Medical College, Huazhong University of Science and Technology, 13 Hangkong Rd, Wuhan, 430030, China. panan@hust.edu.cn.
Liming LiDepartment of Epidemiology and Biostatistics, School of Public Health, Peking University Health Science Center, 38 Xueyuan Rd, Beijing, 100191, China. lmleeph@vip.163.com.
China Kadoorie Biobank Collaborative Group

Funding

Medical Research Council MC_U137686851Medical Research Council MC_UU_00017/1Medical Research Council MC_UU_12026/2Wellcome Trust 088158/Z/09/ZWellcome Trust 104085/Z/14/ZWellcome Trust 202922/Z/16/ZWellcome Trust 212946/Z/18/Z
6 · The paper itself

Abstract

backgroundSelf-rated health (SRH) have been widely used as a valid indicator of health status at the population and individual level. We aimed to investigate the distribution and correlates of global SRH and age-comparative SRH in elderly Chinese.

methodsSurvey of 57,693 men and 67,089 women aged 60 years and above was conducted in five rural (Gansu, Sichuan, Hunan, Henan, Zhejiang) and five urban areas (Heilongjiang, Shandong, Jiangsu, Guangxi, Hainan) in China between 2004 and 2008. Logistic regression models were used to calculate the relations of different factors with global SRH and age-comparative SRH.

resultsAmong the participants, 38.33% reported their global SRH as good or excellent while 61.67% as fair or poor, and 17.70% reported better age-comparative SRH while 17.99% as worse. In the multivariate model, compared to women, men tended to report a good global SRH and better age-comparative SRH, urban residents tend to report good global SRH and better age-comparative SRH. The socioeconomic and health behavior factors that were associated with good global SRH and better age-comparative SRH (with varying strengths of association) included: high educational level, high household income, house ownership, quitting smoking by own choices, occasional and current alcohol drinking, overweight, and high physical activity level. The factors that were associated with poor global SRH and worse age-comparative SRH included: quitting smoking by illness, former drinking, underweight, and weight lost ≥2.5 kg in the previous year.

conclusionsWe found a moderate level of good global SRH and a low level of better age-comparative SRH among elderly Chinese. We identified a number of demographic, socioeconomic and health behavior factors that were related to SRH measures. Our study emphasizes the importance of incorporating both global and age-comparative SRH measures in future studies, and considering gender inequalities and urban/rural disparity, as well as socioeconomic status and health behaviors as important modifiers of health.

Indexed as

Asian PeopleBiological Specimen BanksHealth StatusSelf ReportAdultAgedAlcohol DrinkingChinaFemaleHealth BehaviorHumansMaleMiddle AgedProspective StudiesRural PopulationSmokingChinese populationCorrelatesDistributionSelf-rated health

Identifiers

PMID31200646
PMCPMC6570897

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Registered trials

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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.