4.7 Article

Global burden analysis and AutoGluon prediction of accidental carbon monoxide poisoning by Global Burden of Disease Study 2019

Journal

ENVIRONMENTAL SCIENCE AND POLLUTION RESEARCH
Volume 29, Issue 5, Pages 6911-6928

Publisher

SPRINGER HEIDELBERG
DOI: 10.1007/s11356-021-15895-y

Keywords

Carbon monoxide poisoning; Global Burden of Disease; Incidence; Prevalence; Estimated annual percentage change

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ACOP is the most common occupational toxic disease, with approximately 0.97 million incidence cases and 41,142 deaths globally in 2019. The morbidity and mortality of ACOP have been decreasing from 1990 to 2019, with females having higher morbidity and lower mortality. This correlation helps evaluate the level and status of public health services in various countries.
Accidental carbon monoxide poisoning (ACOP) is the most common occupational toxic disease, but related data are scarce or non-existent in many countries. This article investigates the global burden of ACOP based on the Global Burden of Disease Study 2019 (GBD 2019) and the World Bank database. In our study, numbers and age-standardized rates of ACOP prevalence, incidence, deaths, disability-adjusted life years (DALYs), years lived with disability (YLDs), and years of life lost (YLLs) were analyzed at global, regional, and national level. Besides, the estimated annual percentage change (EAPC) of age-standardized rates were calculated by generalizing the linear model. Age, sex, and Socio-demographic Index (SDI) are included to access their internal relevance. Globally, in 2019, there were approximately 0.97 million ACOP incidence cases (95% CI 0.66 million to 1.4 million), and 41,142 (95% UI 32,957 to 45,934) people died from it. Compared with 1990, the morbidity and mortality of ACOP in 2019 are on a downward trend. By sexes, from 1990 to 2019, females have higher morbidity and lower mortality. This correlation enables us to evaluate the level and status of public health services in various countries. We also evaluated the correlation between ACOP and economic parameters and use newly released machine learning tool-AutoGluon to predict the epidemiology of ACOP. The results of this study can be used by the health authorities to consider the burden of ACOP that could be addressed with preventive and therapeutic measures.

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