Disease and disparity in China: a view from stroke and MI disease - Yao Yao; Gordon Liu; Linhong Wang; Hanqing Zhao; Zhenping Zhao; Mei Zhang; Meijiao Wang; Limin Wang (BMC, 2019)
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.