ABSTRACT
Objective To analyze the trend of heart disease death and the life expectancy without cause of death in Qidong City, Jiangsu Province from 1990 to 2019, and to provide reference for the prevention and control of heart disease. Methods Data on heart disease deaths among residents in Qidong City from 1990 to 2019 were collected through the Qidong City Death Registration and Monitoring System. The crude mortality rate (CR) and Chinese age-standardized mortality rate (CASR), potential years of life loss (PYLL), average years of life loss (AYLL), potential life loss years rate (PYLLR), life expectancy, and life expectancy without cause of death were calculated, and the annual percentage change (APC) was used to analyze the trend of heart disease death. Using SAS9.2 software, the death trend prediction was conducted by the ARIMA model in time series analysis. Results From 1990 to 2019, 27,762 residents died of heart disease in Qidong City, with a CR of 81.20/100 000 and an APC of 3.734%. There were 12 358 deaths of heart disease in men, with a CR of 73.24/100 000 and an APC of 3.86%, while there were 15 404 deaths of heart disease in women, with a CR of 88.95/100 000 and an APC of 3.63%. CR showed an upward trend (all P < 0.001). The PYLL for heart disease was 66 192.00 person-years, the AYLL was 13.23 person-years, and the PYLLR was 2.16‰. The life expectancy loss from heart disease was gradually increasing: 0.89 years in 1990 to 1.85 years in 2019, with an APC of 0.405% (P<0.001, a statistically significant trend). The prediction results showed that in 2029, the life expectancy after heart disease would reach 88.17 years. Conclusion From 1990 to 2019, the crude mortality rate of heart disease in Qidong City has showed an increasing trend, leading to an increasing loss of life due to heart disease year by year. The mortality rate and life loss of heart disease in women are higher than those in men. Targeted intervention measures should be further adopted to reduce the mortality rate of heart disease among residents in Qidong.
ABSTRACT
Objective To understand the death status, mortality trend, cause of death and life loss of injury and poisoning among residents in Qidong City, Jiangsu Province from 1990 to 2019, and to provide a reference for formulating public health policies. Methods Data on injury and poisoning death of residents in Qidong City from 1990 to 2019 were collected through the death cause registration and monitoring system of Qidong City, Jiangsu Province. Indicators such as crude death rate (CR) and standardized death rate (CASR), average years of lost life (AYLL), and potential years of life lost rate (PYLLR) were calculated. Annual percentage change (APC) was used to analyze the trend of death from injury and poisoning. Results From 1990 to 2019, 18 163 residents in Qidong City, Jiangsu Province died of injuries and poisoning. The CR was 53.12/100 000 (APC=0.74%), and the CASR was 39.43/100 000 (APC=-1.86%). The male CR was 66.90 100 000 (APC=0.75%), and the male CASR was 52.42/100 000 (APC=-1.75%), while the female CR was 39.69/100 000 (APC=0.73%), and the female CASR was 26.63/100 000 (APC=-2.14%). Analysis of the standardized mortality rate showed a downward trend year by year (P<0.001). PYLL caused by injury and poisoning was 318 502.50 person-years (APC=-4.00%), AYLL was 26.02 years/person (APC=-3.26%) and the PYLLR was 10.39‰ (APC=-3.54%). The top five death causes of injury and poisoning are motor vehicle accidents, suicide, drowning, accidental falls and accidental poisoning, accounting for 87.17% of the total deaths from injuries and poisoning. Drowning was the leading cause of death for children aged from 0 to 14. Motor vehicle accidents were the leading cause of death for residents aged from 15 to 64, and accidental falls were the leading cause of death for residents over 65. Conclusion Injury and poisoning are one of the main causes of death among residents in Qidong City, Jiangsu Province. The distribution characteristics of injurie and poisoning deaths of different genders and ages are different. According to their distribution characteristics, targeted and specific measures should be taken to reduce mortality.