Trends and associated factors in place of death among individuals with cardiovascular disease in China, 2008-2020: A population-based study.

BACKGROUND

Cardiovascular disease (CVD) is the leading cause of death (COD) in China. Understanding the characteristics of place of death (POD) among CVD deaths would be of great importance to evaluate the healthcare service utilization at the end stage of life. Limited studies have reported the POD distribution among CVD deaths, and little was known about the associated factors of hospital CVD deaths.

METHODS

By using data from National Mortality Surveillance System (NMSS) in China, this study presented the characteristics of POD distribution during 2008 and 2020. Afterwards, multilevel logistic regression was used to explore associated factors of hospital CVD deaths and quantify the magnitude to which the spatial variations of hospital CVD deaths could be explained by those associated factors.

FINDINGS

During 2008-2020, there was 7101871 CVD deaths collected by NMSS in China, with 77·13% home deaths and 18·49% hospital deaths. Shanghai (59·40%) had the highest percentage of hospital CVD deaths. Age, sex, ethnicity, marital status, education, occupation, underlying COD were significant influential factors of hospital CVD deaths. Spatial variations were shown at provincial level, with 33·88% of them being explained by factors at individual level.

INTERPRETATION

Home was the leading POD among CVD deaths in China, those CVD decedents characterized as the female, the youngest, Han population, the married, the retiree, lived in urban areas, with higher socioeconomic status and died of chronic CVDs had a higher probability of hospital deaths. Providing accessible and available healthcare services were priorities to improve quality of end-of-life care, significant variations among provinces and sub-population also reminded us of the requirements for equal healthcare resources allocation and multiple options for minorities of POD preference at the end stage of life.

FUNDING

National Key Research & Development Program of China (grant number 2018YFC1315301).