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Analysis of the changing trend of cataract disease burden in China from 1990 to 2021 and the prediction of the development trend

Published on Dec. 30, 2024Total Views: 452 times Total Downloads: 106 times Download Mobile

Author: HUANG Kexin 1 CHEN Qingfeng 1, 2

Affiliation: 1. School of Information and Management, Guangxi Medical University, Nanning 530021, China 2. School of Computer, Electronics and Information, Guangxi University, Nanning 530004, China

Keywords: Cataract Disease burden Prevalence Disability-adjusted life year

DOI: 10.12173/j.issn.1004-4337.202409054

Reference: Huang KX, Chen QF. Analysis of the changing trend of cataract disease burden in China from 1990 to 2021 and the prediction of the development trend[J]. Journal of Mathematical Medicine, 2024, 37(12): 888-898. DOI: 10.12173/j.issn.1004-4337.202409054[Article in Chinese]

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Abstract

Objective  To understand the current disease burden of cataract in China in 2021, and predict the development trend of disease burden of cataract in China from 2022 to 2050.

Methods  The data of cataract disease burden in China and the world were obtained from the Global Burden of Disease Study 2021 (GBD 2021). The data included prevalence, disability-adjusted life year (DALY), and age-standardized rate. These indicators were used to describe the current situation of the disease burden of cataract in China and the world in 2021, and the estimated annual percentage change (EAPC) was used to analyze the change trend of the disease burden of cataract in China from 1990 to 2021. Furthermore, a Bayesian age-period-cohort model was constructed using R 4.2.3 software to predict the overall prevalence and DALY changes for cataract in China from 2022 to 2050.

Results  From 1990 to 2021, the number of individuals with cataract globally increased from 42.332[95% uncertain interval (UI): 37.403-47.527] million to 100.571 (95%UI: 88.772-114.033) million, while in China, the number increased from 5.684 (95%UI: 4.918-6.514) million to 19.785 (95%UI: 16.950-22.758) million, representing a 137.6% and 248.1% increase, respectively. The disease burden indicators for cataract were consistently higher in women than men during this period, and the disease burden increased with age. The peak burden for cataract in both global and Chinese populations was observed in the 70-75 age group. According to projections from a Bayesian age-period-cohort model, by 2050, the estimated number of men with cataract in China will be 31.733 million, and the number of women with cataract will be approximately 54.561 million. The predicted absolute number of DALY associated with cataract in men will be approximately 1.117 million per year, and the corresponding number for women will be approximately 2.428 million per year.

Conclusion  The disease burden of cataract in China has increased from 1990 to 2021, with a higher prevalence among women compared to men. Predictive models indicate that age-standardized prevalence rates will continue to rise over the next three decades, suggesting a persistent high burden of cataract in China. The escalating disease burden of cataract posed a significant challenge, necessitating concerted efforts from government, healthcare institutions, and society as a whole to implement effective measures to reduce cataract incidence and disability rates, ensuring the well-being of the population.

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References

1.GBD 2019 Blindness and Vision Impairment Collaborators, Vision Loss Expert Group of the Global Burden of Disease Study. Causes of blindness and vision impairment in 2020 and trends over 30 years, and prevalence of avoidable blindness in relation to VISION 2020: the right to sight: an analysis for the Global Burden of Disease Study[J]. Lancet Glob Health, 2021, 9(2): e144-e160. DOI: 10.1016/S2214-109X(20)30489-7.

2.倪连红, 刘慧茹, 李维娜, 等. 年龄相关性白内障患者术后视觉质量的影响因素[J]. 中华老年多器官疾病杂志, 2024, 23(7): 537-540. [Ni LH, Liu HR, Li WN, et al. Factors affecting postoperative visual quality in patients with age-related cataract[J]. Chinese Journal of Multiple Organ Diseases in the Elderly, 2024, 23(7): 537-540.] DOI: 10.11915/j.issn.1671-5403.2024.07.116.

3.Shu Y, Shao Y, Zhou Q, et al. Changing trends in the disease burden of cataract and forecasted trends in China and globally from 1990 to 2030[J]. Clin Epidemiol, 2023, 15: 525-534. DOI: 10.2147/CLEP.S404049.

4.Son KY, Ko J, Kim E, et al. Deep learning-based cataract detection and grading from slit-lamp and retro-illumination photographs: model development and validation study[J]. Ophthalmol Sci, 2022, 2(2): 100147. DOI: 10.1016/j.xops.2022.100147.

5.颜钰玲, 薛春燕. 人工智能在白内障诊断的应用进展[J]. 眼科学报, 2024, 39(3): 160-168. [Yan YL, Xue CY. Advances in artificial intelligence for cataract diagnosis[J]. Eye Science, 2024, 39(3): 160-168.] DOI: 10.12419/24040106.

6.GBD 2021 Diseases and Injuries Collaborators. Global incidence, prevalence, years lived with disability (YLDs), disability-adjusted life-years (DALYs), and healthy life expectancy (HALE) for 371 diseases and injuries in 204 countries and territories and 811 subnational locations, 1990-2021: a systematic analysis for the Global Burden of Disease Study 2021[J]. Lancet, 2024, 403(10440): 2133-2161. DOI: 10.1016/S0140-6736(24)00757-8.

7.Gordis L. Epidemiology (4th edition)[M]. Philadelphia: Saunders, 2008.

8.吴霞, 张译匀, 姚承志, 等. 1990—2021年中国归因于饮食因素的缺血性心脏病疾病负担变化趋势及预测研究[J]. 中国全科医学, 2025, 28(3): 305-312. [Wu X, Zhang YY, Yao CZ, et al. Trend and prediction of changes in the disease burden of diet-related ischemic heart disease in China, 1990-2021[J]. Chinese General Practice, 2025, 28(3): 305-312.] https://link.cnki.net/urlid/13.1222.R.20240828.1030.010.

9.Ahmad OB, Boschi-Pinto C, Lopez AD, et al. Age standardization of rates: a new WHO standard[J]. Geneva: World Health Organization, 2001, 9(10): 1-14. https://www.researchgate.net/publication/284696312.

10.Hankey BF, Ries LA, Kosary CL, et al. Partitioning linear trends in age-adjusted rates[J]. Cancer Causes Control, 2000, 11(1): 31-35. DOI: 10.1023/a:1008953201688.

11.郑荣寿, 陈万青. 基于贝叶斯方法的年龄-时期-队列预测模型的介绍[J]. 中华预防医学杂志, 2012, 46(7): 648-650. [Zheng RS, Chen WQ. Introduction of age-period-cohort prediction model based on Bayesian method[J]. Chinese Journal of Preventive Medicine, 2012, 46(7): 648-650.] DOI: 10.3760/cma.j.issn.0253-9624. 2012.07.016.

12.Zetterberg M, Celojevic D. Gender and cataract-the role of estrogen[J]. Curr Eye Res, 2015, 40(2): 176-190. DOI: 10.3109/02713683.2014.898774.

13.Klein BE, Klein R, Linton KL. Prevalence of age-related lens opacities in a population. The Beaver Dam Eye Study[J]. Ophthalmology, 1992, 99(4): 546-552. DOI: 10.1016/s0161-6420(92)31934-7.

14.陈文黎, 徐依, 姜聪聪, 等. 1990-2019年中国白内障患病率和伤残调整寿命年的趋势分析[J]. 国际眼科杂志, 2024, 24(2): 182-188. [Chen WL, Xu Y, Jiang CC, et al. Trends in prevalence and disability-adjusted life years of cataract in China from 1990 to 2019[J]. International Eye Science, 2024, 24(2): 182-188.] DOI: 10.3980/j.issn.1672-5123.2024.2.02.

15.娄尚, 袁兆康. 我国老年性白内障流行病学的调查研究[J]. 南昌大学学报(医学版), 2012, 52(6): 98-99, 101. [Lou S, Yuan ZK. A study on the epidemiology of senile cataract in China[J]. Journal of Nanchang University (Medical Sciences), 2012, 52(6): 98-99, 101.] DOI: 10.3969/j.issn.1000-2294.2012.06.031.

16.Weintraub JM, Willett WC, Rosner B, et al. A prospective study of the relationship between body mass index and cataract extraction among US women and men[J]. Int J Obes Relat Metab Disord, 2002, 26(12): 1588-1595. DOI: 10.1038/sj.ijo.0802158.

17.Kanthan GL, Mitchell P, Burlutsky G, et al. Fasting blood glucose levels and the long-term incidence and progression of cataract-the Blue Mountains Eye Study[J]. Acta Ophthalmol, 2011, 89(5): e434-e438. DOI: 10.1111/j.1755-3768.2011.02149.x.

18.郭霞, 张丽红. 白内障手术患者施行健康教育的方法及对预后影响分析[J]. 中国药物与临床, 2020, 20(5): 873-874. [Guo X, Zhang LH. Analysis of the methods of health education for cataract surgery patients and its impact on prognosis[J]. Chinese Remedies & Clinics, 2020, 20(5): 873-874.] DOI: 10.11655/zgywylc2020.05.094.

19.李晓新. 直观教学法在白内障术前宣传教育中的应用 [J]. 华西医学, 2017, 32(2): 254-257. [Li XX. Application of intuitive teaching method in preoperative cataract publicity and education[J]. West China Medical Journal, 2017, 32(2): 254-257.] DOI: 10.7507/1002-0179.201505095.

20.康玲. 视频宣讲在白内障围手术期健康教育中的应用 [J]. 吉林医学, 2012, 33(28): 6208-6210. [Kang  L. The application of video preaching in perioperative cataract health education[J]. Jilin Medical Journal, 2012, 33(28): 6208-6210.] DOI: 10.3969/j.issn.1004-0412.2012.28.107.

21.邹庆欣. 白内障的筛查和康复治疗在防盲治盲中的应用效果研究[J]. 婚育与健康, 2023, 29(9): 55-57. [Zou  QX. Study on the application effect of cataract screening and rehabilitation therapy in the prevention and treatment of blindness[J]. Fertility & Health, 2023, 29(9): 55-57.] DOI: 10.3969/j.issn.1006-9488.2023.09.019.

22.王力, 曹利群, 王颖, 等. 彩色多普勒超声在高原地区白内障患者术前筛查中的应用价值研究[J]. 人民军医, 2021, 64(7): 626-629, 638. [Wang L, Cao LQ, Wang  Y, et al. Study on the application value of color Doppler ultrasound in preoperative screening of cataract patients in highland areas[J]. People's Military Surgeon, 2021, 64(7): 626-629, 638.] DOI: 10.3969/j.issn.1000-9736. 2021.07.010.

23.郭娜, 徐红芹, 蒋沁, 等. "江苏博爱光明行"健康扶贫医疗救助项目的实践探究[J]. 江苏卫生事业管理, 2021, 32(6): 832-836. [Guo N, Xu HQ, Jiang  Q, et al. A practical exploration of the "Jiangsu Boai Brightness Tour" medical assistance program for health poverty alleviation[J]. Jiangsu Health System Management, 2021, 32(6): 832-836.] DOI: 10.3969/j.issn.1005-7803.2021.06.038.

24.孙新, 杨梅, 王鹏. 基于智能移动终端的老年眼健康分级诊疗模式研究[J]. 中国信息界, 2024, (3): 17-19. [Sun  X, Yang M, Wang P. Research on hierarchical diagnosis and treatment model of elderly eye health based on intelligent mobile terminal[J]. Information China, 2024, (3): 17-19.] https://www.cqvip.com/doc/journal/3345454177.

25.张鑫. 探讨优质护理对白内障超声乳化术后干眼症的预防及发病率影响[J]. 黑龙江中医药, 2021, 50(5): 270-271. [Zhang X. Exploring the effect of quality nursing care on the prevention and morbidity of dry eye after cataract ultrasonoemulsification[J]. Heilongjiang Journal of Traditional Chinese Medicine, 2021, 50(5): 270-271.] https://www.cqvip.com/doc/journal/985515994.

26.范慧敏, 柏心如, 韩雅婷, 等. 孟德尔随机化分析饮食因素与白内障的因果关系[J]. 齐齐哈尔医学院学报, 2024, 45(12): 1192-1196. [Fan HM, Bai XR, Han  YT, et al. Causal relationship between dietary factors and cataract: a Mendelian randomisation analysis[J]. Journal of Qiqihar Medical University, 2024, 45(12): 1192-1196.] DOI: 10.3969/j.issn.1002-1256.2024.12.017.

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