Predicting Diabetes and Estimating Its Economic Burden in China Using Autoregressive Integrated Moving Average Model

Objectives: To predict the number of people with diabetes and estimate the economic burden in China. Methods: Data from natural logarithmic transformation of the number of people with diabetes in China from 2000 to 2018 were selected to fit the autoregressive integrated moving average (ARIMA) model,...

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Detalles Bibliográficos
Autores principales: Zhu, Di, Zhou, Dongnan, Li, Nana, Han, Bing
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Frontiers Media S.A. 2022
Materias:
Public Health Archive
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8810486/
https://www.ncbi.nlm.nih.gov/pubmed/35126031
http://dx.doi.org/10.3389/ijph.2021.1604449
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author Zhu, Di
Zhou, Dongnan
Li, Nana
Han, Bing
author_facet Zhu, Di
Zhou, Dongnan
Li, Nana
Han, Bing
author_sort Zhu, Di
collection PubMed
description Objectives: To predict the number of people with diabetes and estimate the economic burden in China. Methods: Data from natural logarithmic transformation of the number of people with diabetes in China from 2000 to 2018 were selected to fit the autoregressive integrated moving average (ARIMA) model, and 2019 data were used to test it. The bottom-up and human capital approaches were chosen to estimate the direct and indirect economic burden of diabetes respectively. Results: The number of people with diabetes in China would increase in the future. The ARIMA model fitted and predicted well. The number of people with diabetes from 2020 to 2025 would be about 94, 96, 97, 98, 99 and 100 m respectively. The economic burden of diabetes from 2019 to 2025 would be about $156b, $160b, $163b, $165b, $167b, $169b and $170b respectively. Conclusion: The situation of diabetes in China is serious. The ARIMA model can be used to predict the number of people with diabetes. We should allocate health resources in a rational manner to improve the prevention and control of diabetes.
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spelling pubmed-88104862022-02-04 Predicting Diabetes and Estimating Its Economic Burden in China Using Autoregressive Integrated Moving Average Model Zhu, Di Zhou, Dongnan Li, Nana Han, Bing Int J Public Health Public Health Archive Objectives: To predict the number of people with diabetes and estimate the economic burden in China. Methods: Data from natural logarithmic transformation of the number of people with diabetes in China from 2000 to 2018 were selected to fit the autoregressive integrated moving average (ARIMA) model, and 2019 data were used to test it. The bottom-up and human capital approaches were chosen to estimate the direct and indirect economic burden of diabetes respectively. Results: The number of people with diabetes in China would increase in the future. The ARIMA model fitted and predicted well. The number of people with diabetes from 2020 to 2025 would be about 94, 96, 97, 98, 99 and 100 m respectively. The economic burden of diabetes from 2019 to 2025 would be about $156b, $160b, $163b, $165b, $167b, $169b and $170b respectively. Conclusion: The situation of diabetes in China is serious. The ARIMA model can be used to predict the number of people with diabetes. We should allocate health resources in a rational manner to improve the prevention and control of diabetes. Frontiers Media S.A. 2022-01-20 /pmc/articles/PMC8810486/ /pubmed/35126031 http://dx.doi.org/10.3389/ijph.2021.1604449 Text en Copyright © 2022 Zhu, Zhou, Li and Han. https://creativecommons.org/licenses/by/4.0/This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) and the copyright owner(s) are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.
spellingShingle Public Health Archive
Zhu, Di
Zhou, Dongnan
Li, Nana
Han, Bing
Predicting Diabetes and Estimating Its Economic Burden in China Using Autoregressive Integrated Moving Average Model
title Predicting Diabetes and Estimating Its Economic Burden in China Using Autoregressive Integrated Moving Average Model
title_full Predicting Diabetes and Estimating Its Economic Burden in China Using Autoregressive Integrated Moving Average Model
title_fullStr Predicting Diabetes and Estimating Its Economic Burden in China Using Autoregressive Integrated Moving Average Model
title_full_unstemmed Predicting Diabetes and Estimating Its Economic Burden in China Using Autoregressive Integrated Moving Average Model
title_short Predicting Diabetes and Estimating Its Economic Burden in China Using Autoregressive Integrated Moving Average Model
title_sort predicting diabetes and estimating its economic burden in china using autoregressive integrated moving average model
topic Public Health Archive
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8810486/
https://www.ncbi.nlm.nih.gov/pubmed/35126031
http://dx.doi.org/10.3389/ijph.2021.1604449
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