Evidence map›Paper›PMID 23063218›Full record

ArticleSocial science & medicine (1982)2012

An exploratory multilevel analysis of income, income inequality and self-rated health of the elderly in China.

Zhixin Feng, Wenfei Winnie Wang, Kelvyn Jones, Yaqing Li

Abstract read
In one paragraph

Article in Social science & medicine (1982), 2012. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 32 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
32citing 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

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

  1. Pooled it
  2. Observational
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  8. Inequalities in Resource Distribution and Healthcare Service Utilization of Long-Term Care in China.International journal of environmental research and public health · 2023
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  15. The impacts of pollution and its associated spatial spillover effects on ill-health in China.Environmental science and pollution research international · 2021
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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.

Zhixin FengSchool of Geographical Sciences, University of Bristol, University Road, Bristol BS8 1SS, UK. frankfengs@gmail.com
Wenfei Winnie Wang
Kelvyn Jones
Yaqing Li

Funding

Demographic Analysis on Determinants of Healthy Longevity in ChinaR01AG023627 · NIA · DUKE UNIVERSITY · PI ZENG, YI · 2004 to 2014
$3.9M
NIA NIH HHS R01 AG023627NIA NIH HHS R01 AG23627-01
6 · The paper itself

Abstract

In the last three decades, China has experienced rapid economic development and growing economic inequality, such that economic disparities between rural and urban areas, as well as coastal and interior areas have deepened. Since the late 1990s China has also experienced an ageing population which has attracted attention to the wellbeing of the rapidly growing number of elderly. This research aims to characterise province differences in health and to explore the effects of individual income and economic disparity in the form of income inequality on health outcomes of the elderly. The study is based on the Chinese Longitudinal Healthy Longevity Survey data collected in 2008 for 23 provinces. Multilevel logistic models are employed to investigate the relationship between income, income inequality and self-rated health for the elderly using both individual and province-level variables. Results are presented as relative odds ratios, and for province differentials as Median Odds Ratios. The analysis is deliberately exploratory so as to find evidence of income effects if they exist and particular attention is placed on how province-level inequality (contemporaneous and lagged) may moderate individual relationships. The results show that the health of the elderly is not only affected by individual income (the odds of poor health are 3 times greater for the elderly with the lowest income compared to those at the upper quartile) but also by a small main effect for province-level income inequality (odds ratio of 1.019). There are significant cross-level interactions such that where inequality is high there are greater differences between those with and without formal education, and between men and women with the latter experiencing poorer health.

Indexed as

Health StatusIncomeSocial ClassAgedAged, 80 and overChinaFemaleHealth SurveysHumansLogistic ModelsMaleMiddle AgedOdds Ratio

Identifiers

PMID23063218
PMCPMC3696131

What OpenQuestion holds

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Registered trials

None linked

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.