Modelling and prediction of global non-communicable diseases

doi:10.1186/s12889-020-08890-4

	Modelling and prediction of global non-communicable diseases
	Wang, Yang 1,2; Wang, Jinfeng 1,2
刊名	BMC PUBLIC HEALTH
	2020-06-01
卷号	20 期号:1 页码:13
关键词	Non-communicable diseases Geotree Socio-economic factors Prediction
DOI	10.1186/s12889-020-08890-4
通讯作者	Wang, Jinfeng(wangjf@lreis.ac.cn)
英文摘要	Background Non-communicable diseases (NCDs) are the main health and development challenge facing humankind all over the world. They are inextricably linked to socio-economic development. Deaths caused by NCDs should be different in different socio-economic development stages. The stratified heterogeneity of NCD deaths is currently not fully explored. Methods Countries were classified according to their socio-economic types and development stages, which were illustrated as a tree-like structure called Geotree. NCD deaths were linked to the countries and so were attached to the Geotree, which was modelled by a multilevel model (MLM) approach. Accordingly, the levels of NCD death indexes were predicted for 2030. Results Through the Geotree structure constructed in the study, it can be seen that the NCD death index has obvious stratified heterogeneity; that is, the NCD death index shows different trends in different country types and socio-economic development stages. In the first-level branches (country type), as national income increases, NCD mortality rate decreases and the proportion of NCD deaths to total deaths increases. In the secondary-level trunks (socio-economic development stage), as a country's development stage rises, the NCD mortality rate decreases and the proportion of NCD deaths to total deaths increases. In addition, combined with the hierarchical nature of the evolution tree model, the MLM was used to predict the global NCD death index for 2030. The result was that by 2030, the global average age-standardized NCD mortality rate would be 510.54 (per 100,000 population) and the global average mortality for NCD deaths of the total number of deaths would be 75.26%. Conclusions This study found that there is a significant association between socio-economic factors and NCD death indicators in the tree-like structure. In the Geotree, countries on the same branch or trunk can learn from countries with higher development stages to formulate more effective NCD response policies and find the right prevention and treatment path.
资助项目	National Natural Science Foundation of China[41531179] ; National Natural Science Foundation of China[41421001] ; Ministry of Science and Technology of China[2016YFC1302504]
WOS关键词	CARDIOVASCULAR RISK-FACTORS ; SOCIOECONOMIC-STATUS ; MULTILEVEL ANALYSIS ; DIETARY-FAT ; TOBACCO USE ; LOW-INCOME ; COUNTRIES ; URBANIZATION ; EPIDEMIOLOGY ; INEQUALITIES
WOS研究方向	Public, Environmental & Occupational Health
语种	英语
出版者	BMC
WOS记录号	WOS:000538058600018
资助机构	National Natural Science Foundation of China ; Ministry of Science and Technology of China
内容类型	期刊论文
源URL	[http://ir.igsnrr.ac.cn/handle/311030/159482]
专题	中国科学院地理科学与资源研究所
通讯作者	Wang, Jinfeng
作者单位	1.Chinese Acad Sci, Inst Geog Sci & Nat Resources Res, State Key Lab Resources & Environm Informat Syst, Beijing 100101, Peoples R China 2.Univ Chinese Acad Sci, Beijing 100049, Peoples R China
推荐引用方式 GB/T 7714	Wang, Yang,Wang, Jinfeng. Modelling and prediction of global non-communicable diseases[J]. BMC PUBLIC HEALTH,2020,20(1):13.
APA	Wang, Yang,&Wang, Jinfeng.(2020).Modelling and prediction of global non-communicable diseases.BMC PUBLIC HEALTH,20(1),13.
MLA	Wang, Yang,et al."Modelling and prediction of global non-communicable diseases".BMC PUBLIC HEALTH 20.1(2020):13.