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Published in: International Journal for Equity in Health 1/2019

Open Access 01-12-2019 | Stroke | Research

Disease and disparity in China: a view from stroke and MI disease

Authors: Yao Yao, Gordon Liu, Linhong Wang, Hanqing Zhao, Zhenping Zhao, Mei Zhang, Meijiao Wang, Limin Wang

Published in: International Journal for Equity in Health | Issue 1/2019

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Abstract

Background

The actual distribution of stroke and myocardial infarction (MI) associated with social economic status (SES) among the Chinese population is unclear. We aim to understand the development of disparity in stroke and myocardial infarction (MI) across different income groups in Chinese population.

Methods

Data about stroke and MI disease, income, gender, and areas were obtained from China Chronic Disease and Risk Factor (CCDRF) Survey in 2007, 2010, and 2013. Respondents were categorized into different income groups according to their income rank, disease rate was calculated in each group, and difference in disparities between genders, health behaviors, and areas were further identified. Association of disease prevalence rate and income was verified by logistic regression. Trends in stroke and MI disease prevalence rate across income gradients; trends in the correlation between stroke and MI disease prevalence rate and income over time; variation in stroke and MI disease levels and its disparity across income groups by gender, region, and health behavior. Disease prevalence rate is age-adjusted by using China census 2010 population structure as a standard.

Results

Three waves of survey were included, the sample size in each wave was 45,095 (year 2007), 84,117 (year 2010), and 134,962 (year 2013). Four major findings were delivered. First, the stroke and MI prevalence rate of Chinese population increased from 2007 to 2013. Second, for each survey wave, a negative correlation between stroke and MI risk with income was identified, and this correlation became weaker over time. The gap in stroke and MI prevalence rate between the richest people and the poorest people decreased from 2007 (gap = 2.5 percentage points) to 2013 (gap = 1.6 percentage points). Third, the identified health inequality varied across genders, regions, and health behaviors. For example, female population used to face a sharper decline in prevalence rate when income grew, this correlation, however, faded over time. The rural-urban difference in disease risk was found to be the largest in the bottom income group (in 2013, the prevalence rate in urban area was 5%, which was 1.8% higher than rural places), this rural-urban difference converged as income increased. Fourth, conditioning on the smoking behavior, the negative association of income and stroke and MI prevalence rate was identified, however, conditioning on the drinking behavior, the association of income and disease morbidity was inconclusive.

Conclusion

During 2007 and 2013, the Chinese residents experienced a growth in stroke and MI prevalence rate, meanwhile, the increase in income was associated with a decrease in prevalence rate. However, this health disparity became weaker over time since the prevalence rate was more equally distributed across income gradients as time passed by. Although male population faced a systematically higher stroke and MI disease risk than female, the prevalence disparity in different income groups were similar in both sexes in 2013. In addition, there were also regional differences in inequality in terms of the association of disease and income.
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Footnotes
4
The weighting factor is applied to the sampling scheme with inconsistent sample selection probabilities, and the post-adjustment weights, which makes the sample structure of the survey consistent with the sample structure of the 2010 China Census.
 
5
The missing of ID and Weights means that the record is incomplete or incorrect in raw data. Sample characteristics in both missing-data-group and non-missing-data group is compared and available under request.
 
6
The data for 2007 is based on the diagnosis of doctors in primary health care institutions; in 2010, it was based on the presence of disease attack. Therefore, in 2010, some people were diagnosed but did not experience a disease attack within past 12 months, some may experience a disease attack without being diagnosed. So, compared with 2007, the measured prevalence of stroke and MI in 2010 is biased. The stroke and MI relevant question in 2013 is similar to that in 2007 except for the type of medical institutions included in. Since some respondents are not diagnosed by the county-level medical institutions or above, so the measured prevalence rate may be underestimated. At the same time, the costs of different medical institutions are different, so those who do not go to the medical institutions at or above the county level may because they cannot afford. Thus, compared with 2007, the 2013 question may lead to an underestimation of prevalence rate within low-income population.
 
7
Due to the limited questions in questionnaires, we define the ever-smoker and non-smoker from the following questions: 1. Do you smoke currently? 2. Have you ever smoked?
 
8
In addition, the correlation analysis between disease prevalence and income was also computed, and all turned out to be insignificant.
 
9
People is categorized into ever smoked group and never smoked group due to data according to questionnaire.
 
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Metadata
Title
Disease and disparity in China: a view from stroke and MI disease
Authors
Yao Yao
Gordon Liu
Linhong Wang
Hanqing Zhao
Zhenping Zhao
Mei Zhang
Meijiao Wang
Limin Wang
Publication date
01-12-2019
Publisher
BioMed Central
Published in
International Journal for Equity in Health / Issue 1/2019
Electronic ISSN: 1475-9276
DOI
https://doi.org/10.1186/s12939-019-0986-2

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