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

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Abstract

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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Data availability

All data are available from authors. The data that support the findings of this study are available in GBD2019 at http://ghdx.healthdata.org/gbd-results-tool.

Abbreviations

ACOP:

accidental carbon monoxide poisoning

GBD:

global burden of disease

ASDR:

age-standardized death rate

ASIR:

age-standardized incidence rate

ASPR:

age-standardized prevalence rate

DALYs:

disability-adjusted life years

YLDs:

lived with disability

YLLs:

years of life lost

EAPC:

estimated annual percentage change

SDI:

Socio-demographic Index

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Acknowledgements

We thank Zaizai Cao, **angjie Lin, and Yuanyuan Hao for consulting some coding questions and for algorithm discussion.

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Authors and Affiliations

  1. Department of Emergency Medicine, Second Affiliated Hospital, Zhejiang University School of Medicine, Hangzhou, China

    Fei Liu, **angkang Jiang & Mao Zhang

  2. Key Laboratory of The Diagnosis and Treatment of Severe Trauma and Burn of Zhejiang Province, Hangzhou, China

    Fei Liu, **angkang Jiang & Mao Zhang

  3. Zhejiang Provincial Clinical Research Center for Emergency and Critical Disease, Hangzhou, China

    Fei Liu, **angkang Jiang & Mao Zhang

Authors
  1. Fei Liu
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  2. **angkang Jiang
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  3. Mao Zhang
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Contributions

MZ designed the research. XJ collected and analyzed the data. FL analyzed the data and wrote the article.

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Correspondence to Mao Zhang.

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The authors declare no competing interests.

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Fei Liu and **angkang Jiang are first authors.

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Liu, F., Jiang, X. & Zhang, M. Global burden analysis and AutoGluon prediction of accidental carbon monoxide poisoning by Global Burden of Disease Study 2019. Environ Sci Pollut Res 29, 6911–6928 (2022). https://doi.org/10.1007/s11356-021-15895-y

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