The injury mortality and its trend change among residents＜18 years old in Chongqing from 2012 to 2021
Objective To analyze the injury mortality and its trend change among residents＜18 years old in Chongqing from 2012 to 2021,and provide the basis for improving the prevention and control measures of injury in residents＜18 years old.Methods Injury case data among residents＜18 years old in Chongqing from 2012 to 2021 were from Chongqing death surveillance system.The x2 test was used to analyze the data,the trend change of the injury mortality was analyzed by annual percent change(APC).The used software was SPSS 25.0 Results The injury mortality among residents＜18 years old in Chongqing decreased from 25.52/105 in 2012 to 9.99/105 in 2021(P＜0.01),and APC was-10.68％.The injury mortality rates of each year in males were significantly higher than those in females(P＜0.05,P＜0.01).The APC values of injury mortality in males and females were-10.86％and-10.15％(P＜0.01).From 2012 to 2017,the injury mortality rates of residents＜18 years old in rural areas were significantly higher than those in urban areas(P＜0.05 or P＜0.01).From 2012 to 2017,the APC values of injury mortality in urban residents＜18 years old and rural residents＜18 years old were-4.40％and-11.49％(P＜0.05 or P＜0.01).The Injury mortality rates in 0-4 age group,5-14 age group and 15-17 age group showed the annual decrease 12.89％,10.06％and 7.04％,respectively(P＜0.01).The top five death causes in residents＜18 years old were drowning,road traffic accidence,fall,accidental suffocation and suicide.The APC values of injury mortality for drowning,road traffic accidence and accidental suffocation were-13.15％,-14.62％and-10.42％,respectively(P＜0.01),and APC of suicide mortality was 8.22％(P＜0.01).Conclusion The injury mortality in residents＜18 years old showed downward trend,the males and rural residents＜18 years old were the focus of the intervention.It should strengthen the injury prevention and control for residents＜18 years old in Chongqing.
Residents＜18 years oldInjuryMortalityTrend analysis
NETL
NSTL
万方数据
