Prediction of premature mortality of major chronic and non-communicable diseases and exploration of influencing factors in Anhui Province
Objective To analyze and predict the future trend of the premature mortality of major chronic and non-communicable diseases in Anhui Province,evaluate the implementation of the"Healthy China 2030"Plan,and explore its influencing factors.Methods Using data from death-cause surveillance and statistical yearbooks in Anhui,the trend prediction and analysis on influencing factors were conducted by using methods such as time series accumulation and logarithmic linear Joinpoint regression,principal component regression.Results In Anhui,28.10％of the deaths were premature ones,of which 84.40％were attributed to chronic and non-communicable diseases.In premature deaths attributed to chronic and non-communicable diseases,the deaths caused by malignant tumor and cardiovascular disease accounted for 45.88％and 41.65％respectively.The prediction results showed that the premature mortality of major chronic and non-communicable diseases would decrease in Anhui in the future,and by 2030,the goal in the"Healthy China 2030"Plan would be reached only in rural area.To reduce premature death,it is necessary to pay attention to the prevention and control of malignant tumor and cardiovascular disease.Men in urban area are the key population.Factors that reflect urban infrastructure had a significant impact on premature mortality of major chronic non-communicable diseases,such as garden and green space area per capita.Factors such as concentration of PM2.5 had a negative impact on premature mortality of chronic non-communicable diseases,while factors such as garden and green space area per capita had a positive impact.Conclusions Disease burden caused by chronic and non-communicable diseases,such as malignant tumor,exits in Anhui.Men in urban area are key population in the prevention and control of chronic and non-communicable diseases in the future.
Chronic and non-communicable diseasePremature mortalityPredictionPrincipal componentInfluence factor
NETL
NSTL
万方数据
