摘要
Background: This study projects the trend of disease burden and economic burden of diabetes in 33 Chinese provinces and nationally during 2020–2030 and investigates its spatial disparities. Methods: Time series prediction on the prevalence and disability-adjusted life-year (DALY) rates of diabetes was conducted using a Bayesian modelling approach in 2020–2030. The top-down method and the human capital method were used to predict the direct and indirect costs of diabetes for each Chinese province. Global and local spatial autocorrelation analyses were used to identify geographic clusters of low-or high-burden areas. Findings: Diabetes prevalence in Chinese adults aged 20–79 years was projected to increase from 8.2% to 9.7% during 2020–2030. During the same period, the total costs of diabetes would increase from $250.2 billion to $460.4 billion, corresponding to an annual growth rate of 6.32%. The total costs of diabetes as a percentage of GDP would increase from 1.58% to 1.69% in China during 2020–2030, suggesting a faster growth in the economic burden of diabetes than China's economic growth. Consistently, the per-capita economic burden of diabetes would increase from $231 to $414 in China during 2020–2030, with an annual growth rate of 6.02%. High disease and economic burden areas were aggregated in Northeast and/or North China. Interpretation: Our study projects a significant growth of disease and economic burden of diabetes in China during 2020–2030, with strong spatial aggregation in northern Chinese regions. The increase in the economic burden of diabetes will exceed that of GDP. Funding: National Natural Science Foundation of China, Outstanding Young Scholars Funding.
| 源语言 | 英语 |
|---|---|
| 文章编号 | 100700 |
| 期刊 | The Lancet Regional Health - Western Pacific |
| 卷 | 33 |
| DOI | |
| 出版状态 | 已出版 - 4月 2023 |
联合国可持续发展目标
此成果有助于实现下列可持续发展目标:
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可持续发展目标 3 良好健康与福祉
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可持续发展目标 8 体面工作和经济增长
学术指纹
探究 'Projected rapid growth in diabetes disease burden and economic burden in China: a spatio-temporal study from 2020 to 2030' 的科研主题。它们共同构成独一无二的指纹。引用此
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