Spatiotemporal variations in ischemic heart disease mortality and related risk factors in China between 2010 and 2015: a multilevel analysis

BACKGROUND: To explore the relationship between geographical differences of mortality and related risk factors in ischemic heart disease (IHD) in China. METHODS: Data were collected from the nationally representative China Mortality Surveillance System to calculate annual IHD mortality counts (2010–2015). Descriptive analysis was used to analyze the IHD mortality among Chinese population from 2010 to 2015. Negative binomial regression was used to investigate potential spatiotemporal variation and correlations with age, gender, urbanization, and region. RESULTS: The overall IHD mortality was 221.17/100,000, accounting for 1.51 million deaths in 2015. The standardized IHD mortality rate increased by 5.51% from 2010 to 2015 among people aged 40 years and older. Multilevel analysis indicated significant differences in gender, regions, and age. High urbanization rate (risk ratio [RR] = 0.728, 95% confidence interval [CI] = (0.631, 0.840)) and average high-density lipoprotein (HDL) (RR = 0.741, 95%CI: 0.616,0.891) were negatively associated with IHD mortality. IHD mortality was significantly higher in populations with a low rate of medical insurance coverage (RR = 1.218, 95%CI: 1.007, 1.473), as well as the average body mass index (BMI) (RR = 1.436, 95%CI: 1.135, 1.817) and systolic blood pressure (SBP) (RR = 1.310, 95%CI: 1.019, 1.684). While the relationship with current smoking rate, excessive intake of red meat, insufficient vegetable or fruits intake didn’t show the statistical significance. The negative correlation between the average sedentary time and IHD mortality was not conclusive due to the possible deviation of the data. CONCLUSIONS: The mortality of IHD showed an upward trend for people aged 40 years and older in China during 2010–2015, which should be paid attention to. Therefore, some risk factors should be controlled, such as SBP, overweight/obesity. HDL is a protective factor, as well as higher urbanization rate, family income level, and medical insurance coverage.