Spatiotemporal trends and ecological determinants of cardiovascular mortality among 2844 counties in mainland China, 2006–2020: a Bayesian modeling study of national mortality registries

BMC Medicine

Research Article

Yong Huo¹  Chengdong Xu²  Peng Yin³  Limin Wang³  Jinling You³  Maigeng Zhou³  Jiangmei Liu³  Lin Lin³  Jinlei Qi³  Ziwei Song³  Wei Wang³  Yunning Liu³  Lijun Wang³  Pengpeng Ye⁴  Junming Li⁵ 

[1] Department of Cardiology, Peking University First Hospital, No. 8 Xishiku Street, Xicheng District, 100034, Beijing, China;Institute of Geographic Sciences and Natural Resources Research, Chinese Academy of Sciences, Beijing, China;National Center for Chronic and Noncommunicable Disease Control and Prevention, Chinese Center for Disease Control and Prevention, No. 27 Nanwei Road, Xicheng District, 100050, Beijing, China;National Center for Chronic and Noncommunicable Disease Control and Prevention, Chinese Center for Disease Control and Prevention, No. 27 Nanwei Road, Xicheng District, 100050, Beijing, China;The George Institute for Global Health, Faculty of Medicine and Health, University of New South Wales, Sydney, Australia;School of Statistics, Shanxi University of Finance and Economics, Taiyuan, Shanxi, China;

关键词: Cardiovascular mortality;    China;    Spatiotemporal characteristics;    nonmedical ecological determinants;    Hierarchical Bayesian model;    Population-based strategy;   

DOI  :  10.1186/s12916-022-02613-9

 received in 2022-07-08, accepted in 2022-10-17,  发布年份 2022

来源: Springer

【 摘 要 】

BackgroundCardiovascular disease (CVD) is the leading cause of death in China. No previous study has reported CVD mortality at county-level, and little was known about the nonmedical ecological factors of CVD mortality at such small scale in mainland China. Understanding the spatiotemporal variations of CVD mortality and examining its nonmedical ecological factors would be of great importance to tailor local public health policies.MethodsBy using national mortality registration data in China, this study used hierarchical spatiotemporal Bayesian model to demonstrate spatiotemporal distribution of CVD mortality in 2844 counties during 2006 to 2020 and investigate how nonmedical ecological determinants have affected CVD mortality inequities from the spatial perspectives.ResultsDuring 2006–2020, the age-standardized mortality rate (ASMR) of CVD decreased from 284.77 per 100,000 in 2006 to 241.34 per 100,000 in 2020. Among 2844 counties, 1144 (40.22%) were hot spots counties with a higher CVD mortality risk compared to the national average and located mostly in northeast, north central, and westernmost regions; on the contrary, 1551 (54.53%) were cold spots counties and located mostly in south and southeast coastal counties. CVD mortality risk decreased from 2006 to 2020 was larger in counties where CVD mortality rate had been higher in 2006 in most of the counties, vice versa. Nationwide, nighttime light intensity (NTL) was the major influencing factor of CVD mortality, a higher NTL appeared to be negatively associated with a lower CVD mortality, with one unit increase in NTL, and the CVD mortality risk will decrease 11% (relative risk of NTL was estimated as 0.89 with 95% confidence interval of 0.83–0.94).ConclusionsSubstantial between-county discrepancies of CVD mortality distribution were observed during past 15 years in mainland China. Nonmedical ecological determinants were estimated to significantly explain the overall and local spatiotemporal patterns of this CVD mortality risk. Targeted considerations are needed to integrate primary care with clinical care through intensifying further strategies to narrow unequally distribution of CVD mortality at local scale. The approach to county-level analysis with small area models has the potential to provide novel insights into Chinese disease-specific mortality burden.

【 授权许可】

CC BY   
© The Author(s) 2022

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