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

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 popu...

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Autores principales: Yao, Yao, Liu, Gordon, Wang, Linhong, Zhao, Hanqing, Zhao, Zhenping, Zhang, Mei, Wang, Meijiao, Wang, Limin
Formato: Online Artículo Texto
Lenguaje:English
Publicado: BioMed Central 2019
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6558805/
https://www.ncbi.nlm.nih.gov/pubmed/31186000
http://dx.doi.org/10.1186/s12939-019-0986-2
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author Yao, Yao
Liu, Gordon
Wang, Linhong
Zhao, Hanqing
Zhao, Zhenping
Zhang, Mei
Wang, Meijiao
Wang, Limin
author_facet Yao, Yao
Liu, Gordon
Wang, Linhong
Zhao, Hanqing
Zhao, Zhenping
Zhang, Mei
Wang, Meijiao
Wang, Limin
author_sort Yao, Yao
collection PubMed
description 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. ELECTRONIC SUPPLEMENTARY MATERIAL: The online version of this article (10.1186/s12939-019-0986-2) contains supplementary material, which is available to authorized users.
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spelling pubmed-65588052019-06-13 Disease and disparity in China: a view from stroke and MI disease Yao, Yao Liu, Gordon Wang, Linhong Zhao, Hanqing Zhao, Zhenping Zhang, Mei Wang, Meijiao Wang, Limin Int J Equity Health Research 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. ELECTRONIC SUPPLEMENTARY MATERIAL: The online version of this article (10.1186/s12939-019-0986-2) contains supplementary material, which is available to authorized users. BioMed Central 2019-06-11 /pmc/articles/PMC6558805/ /pubmed/31186000 http://dx.doi.org/10.1186/s12939-019-0986-2 Text en © The Author(s). 2019 Open AccessThis article is distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated.
spellingShingle Research
Yao, Yao
Liu, Gordon
Wang, Linhong
Zhao, Hanqing
Zhao, Zhenping
Zhang, Mei
Wang, Meijiao
Wang, Limin
Disease and disparity in China: a view from stroke and MI disease
title Disease and disparity in China: a view from stroke and MI disease
title_full Disease and disparity in China: a view from stroke and MI disease
title_fullStr Disease and disparity in China: a view from stroke and MI disease
title_full_unstemmed Disease and disparity in China: a view from stroke and MI disease
title_short Disease and disparity in China: a view from stroke and MI disease
title_sort disease and disparity in china: a view from stroke and mi disease
topic Research
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6558805/
https://www.ncbi.nlm.nih.gov/pubmed/31186000
http://dx.doi.org/10.1186/s12939-019-0986-2
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