Citation

Li Y, Chen SF, Dong XJ, Zhao XJ. Public Health 2019; 180: 90-99.

Affiliation

Team of Neonatal & Infant Development, Health and Nutrition, NDHN School of Biology and Pharmaceutical Engineering, Wuhan Polytechnic University, 1 South Park Road, Changqing Garden, Wuhan, Hubei 430023, PR China; Department of Nutrition and Food Science, Texas A&M University, College Station, TX 77843, USA; School of Public Health, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, Hubei 430030, PR China. Electronic address: dzrdez@163.com.

Copyright

(Copyright © 2019, Elsevier Publishing)

DOI

10.1016/j.puhe.2019.11.006

PMID

31875529

Abstract

OBJECTIVE: We aimed to predict population composition, mortality, sociodemographic index (SDI), and cause-specific disability-adjusted life year (DALY) rate in China from 2018 through 2021. STUDY DESIGN: Using the time series method autoregressive integrated moving average (ARIMA) models on all available data, mainly Statistics Year Report by the Global Burden of Disease Study 2017, we predicted populations, deaths, DALYs attributable to disease conditions, and injuries (causes) for China from 2018 through 2021 at levels 0, 1, 2, and 3.

METHODS: The time series method ARIMA models was used on history data.

RESULTS: The predicted total population and SDI in China are increasing from 2018 through 2021. The under-5 mortality is decreasing; from 10.24% to 0.65% in the period 1990-2021. The all-cause DALY rate decreases. The top causes of DALY rate are non-communicable diseases (level 1), cardiovascular diseases (level 2), and stroke (level 3). For the leading 22 level 2 causes in 2018, the trend of ranking in 2021 is as follows: unchanged, 15; increasing, 4; and decreasing, 3. For the leading 169 level 3 causes in 2018, the trend of ranking in 2021 is: as follows: unchanged, 49; increasing, 63; and decreasing 57.

CONCLUSIONS: Cause-specific and time-dependent health policy should be steered to reduce the major burden focuses and to improve population health.

Copyright © 2019 The Royal Society for Public Health. Published by Elsevier Ltd. All rights reserved.

Language: en

Keywords

Causes; China; Disability-adjusted life years; Prediction