Prediction of cause-specific disability-adjusted life years in China from 2018 through 2021: a systematic analysis

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.

Keywords: Causes; China; Disability-adjusted life years; Prediction.