Age-period-cohort analysis and prediction of burden of asthma attributed to tobacco in China from 1990 to 2019

doi:10.16138/j.1673-6087.2023.03.09

Abstract

Abstract:

Objective To study the burden of asthma attributed to tobacco in China from 1990 to 2019, and to provide scientific basis for asthma prevention and control. Methods Using the Global Burden of Disease (GBD) 2019 database, we analyzed the trends of standardized mortality rates and standardized disability-adjusted life year(DALY) rates of asthma attributed to tobacco in China from 1990 to 2019. An age-period-cohort model was utilized to analyze the age, period, and birth cohort effects of the mortality rate of tobacco - related asthma, and an autoregressive integrated moving average model(ARIMA) was adopted to forecast the standardized mortality rates and standardized DALY rates of tobacco-related asthma for the next 5 years (2020-2024). Results Compared to 1990, the total number of deaths attributed to tobacco-related asthma in China was 5 037 in 2019, decreased 30.40% (7 237). The total DALY in 2019 were 200 700 person - years, decreased 13.54% compared to 231 000 person - years in 1990. From 1990 to 2019, the standardized mortality rate of the total population showed a decreasing trend, with an average annual decrease rate of 4.40% (95% CI: -4.63% - -4.16%), and the standardized DALY rate of the total population also showed a downward trend, with an average annual decrease of 3.43% (95% CI: -3.80% - -3.06%). The results of age effect indicated that the mortality rate of tobacco-related asthma increased with age (35-85 years) for males and the total population, reached peak in 85-89 age group, while female’s peak was in the 95 and over age group. From the perspective of period and cohort effects, the risk of death of tobacco-related asthma decreased over time in females, males, and the total population. The forecast results showed that the standardized mortality rate would decrease from 0.17/100 000 in 2020 to 0.05/100 000 in 2024, and the standardized DALY rate would decrease from 6.61/100 000 in 2020 to 3.65/100 000 in 2024. Conclusions The burden of asthma attributed to tobacco in China has shown a downward trend in the past few decades, which is closely related to health education, medical technology progress and the implementation of public health policies. In the future, it is necessary to adjust prevention and control strategies according to the actual situation to further reduce the disease burden of asthma.

Key words: Disability-adjusted life year, Age-period-cohort model, Predict, Epidemiology

CLC Number:

R562

KANG Min, SHI Jing. Age-period-cohort analysis and prediction of burden of asthma attributed to tobacco in China from 1990 to 2019[J]. Journal of Internal Medicine Concepts & Practice, 2025, 20(03): 242-247.

Figures/Tables 5

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References 20

[1]	Liu H, Zhang J, Liu L, et al. Global disease burden and attributable risk factor analysis of asthma in 204 countries and territories from 1990 to 2019[J]. Allergy Asthma Immunol Res, 2023, 15(4): 473-495.
[2]	Rutter C, Silverwood R, Pérez Fernández V, et al. The Global Burden of Asthma[J]. Int J Tuberc Lung Dis, 2022, 26(1): 20-23. pmid: 36284412
[3]	GBD Chronic Respiratory Disease Collaborators. Global, regional, and national deaths, prevalence, disability-adjusted life years, and years lived with disability for chronic obstructive pulmonary disease and asthma, 1990-2015: a systematic analysis for the Global Burden of Disease Study 2015[J]. Lancet Respir Med, 2017, 5(9):691-706. doi: 10.1016/S2213-2600(17)30293-X pmid: 28822787
[4]	Huang K, Yang T, Xu J, et al. Prevalence, risk factors, and management of asthma in China: a national cross- sectional study[J]. Lancet, 2019, 394(10196): 407-418. doi: S0140-6736(19)31147-X pmid: 31230828
[5]	Merhej T, Zein JG. Epidemiology of asthma: prevalence and burden of disease[J]. Adv Exp Med Biol, 2023,1426:3-23.
[6]	Miller RL, Grayson MH, Strothman K. Advances in asthma: new understandings of asthma’s natural history, risk factors, underlying mechanisms, and clinical management[J]. J Allergy Clin Immunol, 2021, 148(6): 1430-1441.
[7]	Strzelak A, Ratajczak A, Adamiec A, et al. Tobacco smoke induces and alters immune responses in the lung triggering inflammation, allergy, asthma and other lung diseases: a mechanistic review[J]. Int J Environ Res Public Health, 2018, 15(5): 1033.
[8]	GBD 2017 Risk Factor Collaborators. Global, regional, and national comparative risk assessment of 84 behavioural, environmental and occupational, and metabolic risks or clusters of risks for 195 countries and territories, 1990-2017: a systematic analysis for the Global Burden of Disease Study 2017[J]. Lancet, 2018, 392(10159):1923-1994. doi: S0140-6736(18)32225-6 pmid: 30496105
[9]	GBD 2019 Diseases and Injuries Collaborators. Global burden of 369 diseases and injuries in 204 countries and territories, 1990-2019: a systematic analysis for the Global Burden of Disease Study 2019[J]. Lancet, 2020, 396(10258): 1204-1222. doi: 10.1016/S0140-6736(20)30925-9 pmid: 33069326
[10]	Cao J, Eshak ES, Liu K, et al. Age-period-cohort analysis of stroke mortality attributable to high sodium intake in China and Japan[J]. Stroke, 2019, 50(7): 1648-1654. doi: 10.1161/STROKEAHA.118.024617 pmid: 31195942
[11]	He Q, Mok TN, Sin TH, et al. Global, regional, and national prevalence of gout from 1990 to 2019: age-period-cohort analysis with future burden prediction[J]. JMIR Public Health Surveill, 2023, 9: e45943.
[12]	Yang J, Li L, Shi Y, et al. An ARIMA model with adaptive orders for predicting blood glucose concentrations and hypoglycemia[J]. IEEE J Biomed Health Inform, 2019, 23(3): 1251-1260.
[13]	陈雯, 刘艳, 宇传华. 1990-2019年中国归因于吸烟的膀胱癌疾病负担年龄-时期-队列分析及预测[J]. 中国卫生统计, 2023, 40(5): 642-645.
[14]	Miller RL, Grayson MH, Strothman K. Advances in asthma: new understandings of asthma’s natural history, risk factors, underlying mechanisms, and clinical management[J]. J Allergy Clin Immunol, 2021, 148(6): 1430-1441.
[15]	Mahmoody Vanolya N, Jelokhani-Niaraki M. The use of subjective-objective weights in GIS-based multi-criteria decision analysis for flood hazard assessment: a case study in Mazandaran, Iran[J]. GeoJournal, 2021, 86: 379-398.
[16]	Cormier M, Lemière C. Occupational asthma[J]. Int J Tuberc Lung Dis, 2020, 24(1): 8-21. doi: 10.5588/ijtld.19.0301 pmid: 32005302
[17]	Yang M, Wang D, Gan S, et al. Increasing incidence of asbestosis worldwide, 1990-2017: results from the Global Burden of Disease study 2017[J]. Thorax,2020, 75(9): 798-800.
[18]	Reddel HK, Bacharier LB, Bateman ED, et al. Global initiative for asthma strategy 2021: executive summary and rationale for key changes[J]. Eur Respir J, 2021, 59(1):2102730.
[19]	鲍春英, 宋淑范. 戒烟对哮喘控制及气道炎性反应的影响[J]. 航空航天医学杂志, 2021, 32(6): 661-663.
[20]	Thomson NC. The Role of smoking in asthma and chronic obstructive pulmonary disease overlap[J]. Immunol Allergy Clin North Am, 2022, 42(3): 615-630.

组别	年份	死亡数（n）	死亡率（/10万）	标化死亡率（/10万）	DALY（万人年）	DALY率（/10万）	标化DALY率（/10万）
女性	1990	662	0.12	0.20	1.63	2.84	4.04
	2019	448	0.06	0.05	1.48	2.12	1.49
变化率		（-32.33）	（-50.00）	（-75.00）	（-9.21）	（-25.35）	(-63.12）
男性	1990	6575	1.08	2.21	21.58	35.37	53.41
	2019	4589	0.63	0.61	18.59	25.65	19.93
变化率		（-30.21）	-（41.67）	（-72.40）	（-13.87）	（-27.48）	（-62.68）
全人群	1990	7 237	0.61	1.04	23.21	19.61	27.05
	2019	5 037	0.35	0.28	20.07	14.11	10.21
变化率		（-30.40）	（-42.62）	（-73.08）	（-13.54）	（-28.05）	（-62.26）

组别	标化死亡率				标化DALY率
组别	年份	APC（95%CI）	t	P	年份	APC（95%CI）	t	P
女性	1990—2000	-0.69（-1.02~-0.3）	-4.28	<0.05	1990—2002	-0.63（-0.96~-0.30）	-3.97	<0.05
	2000—2004	-3.57（-5.24~-1.8）	-4.37	<0.05	2002—2011	-7.86（-8.34~-7.39）	-33.18	<0.05
	2004—2009	-10.25（-11.16~-9.34）	-22.39	<0.05	2011—2016	-5.26（-6.63~-3.86）	-7.73	<0.05
	2009—2019	-6.80（-7.04~-6.5）	-56.25	<0.05	2016—2019	0.97（-1.43~3.44）	0.84	0.41
	1990—2019^a	-4.91（-5.20~-4.6）	-31.77	<0.05	1990—2019^a	-3.57（-3.94~-3.20）	-18.42	<0.05
男性	1990—1995	-0.44（-1.73~0.86）	-0.71	0.49	1990—1995	-0.68（-2.02~0.68）	-1.05	0.31
	1995—2004	-4.26（-4.70~-3.82）	-19.82	<0.05	1995—2002	-3.66（-4.48~-2.84）	-9.15	<0.05
	2004—2007	-11.01（-14.12~-7.79）	-6.86	<0.05	2002—2009	-7.11（-7.84~-6.38）	-19.65	<0.05
	2007—2019	-4.18（-4.40~-3.9）	-39.92	<0.05	2009—2019	-2.16（-2.54~-1.78）	-11.76	<0.05
	1990—2019^a	-4.31（-4.72~-3.8）	-19.88	<0.05	1990—2019^a	-3.49（-3.84~-3.14）	-19.12	<0.05
全人群	1990—1995	-0.24（-1.12~0.63）	-0.58	0.57	1990—2000	-1.85（-2.29~-1.40）	-8.64	<0.05
	1995—2004	-3.99（-4.29~-3.6）	-26.47	<0.05	2000—2009	-6.55（-7.06~-6.04）	-25.85	<0.05
	2004—2008	-10.16（-11.31~-8.99）	-17.36	<0.05	2009—2015	-3.56（-4.68~-2.43）	-6.51	<0.05
	2008—2019	-4.42（-4.60~-4.2）	-50.93	<0.05	2015—2019	0.04（-1.72~1.82）	0.04	0.97
	1990—2019^a	-4.40（-4.63~-4.1）	-35.69	<0.05	1990—2019^a	-3.43（-3.80~-3.06）	-17.67	<0.05