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

Overview

Journal Int J Public Health

Specialty Public Health

Date 2022 Feb 7

PMID 35126031

Authors

Di Zhu

Dongnan Zhou

Nana Li

Bing Han

Affiliations

Soon will be listed here.

Abstract

To predict the number of people with diabetes and estimate the economic burden in China. 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. 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. 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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References

Pan X, Wang L, Pan A . Epidemiology and determinants of obesity in China. Lancet Diabetes Endocrinol. 2021; 9(6):373-392. DOI: 10.1016/S2213-8587(21)00045-0. View

Ding D, Lawson K, Kolbe-Alexander T, Finkelstein E, Katzmarzyk P, van Mechelen W . The economic burden of physical inactivity: a global analysis of major non-communicable diseases. Lancet. 2016; 388(10051):1311-24. DOI: 10.1016/S0140-6736(16)30383-X. View

Ilie O, Cojocariu R, Ciobica A, Timofte S, Mavroudis I, Doroftei B . Forecasting the Spreading of COVID-19 across Nine Countries from Europe, Asia, and the American Continents Using the ARIMA Models. Microorganisms. 2020; 8(8). PMC: 7463904. DOI: 10.3390/microorganisms8081158. View

Ettaro L, Songer T, Zhang P, Engelgau M . Cost-of-illness studies in diabetes mellitus. Pharmacoeconomics. 2004; 22(3):149-64. DOI: 10.2165/00019053-200422030-00002. View

Lozano R, Naghavi M, Foreman K, Lim S, Shibuya K, Aboyans V . Global and regional mortality from 235 causes of death for 20 age groups in 1990 and 2010: a systematic analysis for the Global Burden of Disease Study 2010. Lancet. 2012; 380(9859):2095-128. PMC: 10790329. DOI: 10.1016/S0140-6736(12)61728-0. View

Jannasch F, Kroger J, Schulze M . Dietary Patterns and Type 2 Diabetes: A Systematic Literature Review and Meta-Analysis of Prospective Studies. J Nutr. 2017; 147(6):1174-1182. DOI: 10.3945/jn.116.242552. View

Sato R . Disease management with ARIMA model in time series. Einstein (Sao Paulo). 2013; 11(1):128-31. PMC: 4872983. DOI: 10.1590/s1679-45082013000100024. View

Aryee G, Kwarteng E, Essuman R, Nkansa Agyei A, Kudzawu S, Djagbletey R . Estimating the incidence of tuberculosis cases reported at a tertiary hospital in Ghana: a time series model approach. BMC Public Health. 2018; 18(1):1292. PMC: 6258486. DOI: 10.1186/s12889-018-6221-z. View

Yang D, Yang Y, Li Y, Han R . Physical Exercise as Therapy for Type 2 Diabetes Mellitus: From Mechanism to Orientation. Ann Nutr Metab. 2019; 74(4):313-321. DOI: 10.1159/000500110. View

10.

Ferrao J, Earland D, Novela A, Mendes R, Tungadza A, Searle K . Malaria Temporal Variation and Modelling Using Time-Series in Sussundenga District, Mozambique. Int J Environ Res Public Health. 2021; 18(11). PMC: 8198511. DOI: 10.3390/ijerph18115692. View

11.

Arocha Rodulfo J . Sedentary lifestyle a disease from xxi century. Clin Investig Arterioscler. 2019; 31(5):233-240. DOI: 10.1016/j.arteri.2019.04.004. View

12.

Shin Y, Kim Y . Psychological Stress Accompanied by a Low-Variety Diet Is Positively Associated with Type 2 Diabetes in Middle-Aged Adults. Nutrients. 2020; 12(9). PMC: 7551696. DOI: 10.3390/nu12092612. View

13.

Bommer C, Heesemann E, Sagalova V, Manne-Goehler J, Atun R, Barnighausen T . The global economic burden of diabetes in adults aged 20-79 years: a cost-of-illness study. Lancet Diabetes Endocrinol. 2017; 5(6):423-430. DOI: 10.1016/S2213-8587(17)30097-9. View

14.

Bommer C, Sagalova V, Heesemann E, Manne-Goehler J, Atun R, Barnighausen T . Global Economic Burden of Diabetes in Adults: Projections From 2015 to 2030. Diabetes Care. 2018; 41(5):963-970. DOI: 10.2337/dc17-1962. View

15.

Earnest A, Evans S, Sampurno F, Millar J . Forecasting annual incidence and mortality rate for prostate cancer in Australia until 2022 using autoregressive integrated moving average (ARIMA) models. BMJ Open. 2019; 9(8):e031331. PMC: 6707661. DOI: 10.1136/bmjopen-2019-031331. View

16.

Fang P, Liu X, Huang L, Zhang X, Fang Z . Factors that influence the turnover intention of Chinese village doctors based on the investigation results of Xiangyang City in Hubei Province. Int J Equity Health. 2014; 13:84. PMC: 4226902. DOI: 10.1186/s12939-014-0084-4. View

17.

Chan J, Zhang Y, Ning G . Diabetes in China: a societal solution for a personal challenge. Lancet Diabetes Endocrinol. 2014; 2(12):969-79. DOI: 10.1016/S2213-8587(14)70144-5. View

18.

Afroz A, Alramadan M, Hossain M, Romero L, Alam K, Magliano D . Cost-of-illness of type 2 diabetes mellitus in low and lower-middle income countries: a systematic review. BMC Health Serv Res. 2018; 18(1):972. PMC: 6296053. DOI: 10.1186/s12913-018-3772-8. View

19.

Ma R, Lin X, Jia W . Causes of type 2 diabetes in China. Lancet Diabetes Endocrinol. 2014; 2(12):980-91. DOI: 10.1016/S2213-8587(14)70145-7. View

20.

Tarricone R . Cost-of-illness analysis. What room in health economics?. Health Policy. 2005; 77(1):51-63. DOI: 10.1016/j.healthpol.2005.07.016. View