亚洲5国居民1990 — 2019年特应性皮炎发病 趋势年龄–时期–队列分析

樊文龙; 陈东宇; 王红心; 杨晓雨; 何玉清

doi:10.11847/zgggws1138656

亚洲5国居民1990 — 2019年特应性皮炎发病趋势年龄–时期–队列分析

doi: 10.11847/zgggws1138656

樊文龙¹,
陈东宇¹,
王红心¹,
杨晓雨¹,
何玉清^{1, 2, ,}

1.
广东医科大学公共卫生学院流行病与卫生统计学系广东医科大学医学系统生物学研究所，广东东莞 523808
2.
东莞市寮步医院

基金项目: 国家自然科学基金（81773312）；广东省“扬帆计划引进紧缺拔尖”人才项目（201433005）

详细信息

作者简介:
樊文龙（1996 – ），男，江西南昌人，硕士在读，研究方向：流行病与卫生统计学

通讯作者:
何玉清，E-mail：dr.hyq@hotmail.com

中图分类号: R 751；R 195
计量
- 文章访问数: 95
- HTML全文浏览量: 32
- PDF下载量: 16
- 被引次数: 0
出版历程
- 接收日期: 2022-03-28
- 网络出版日期: 2023-02-24
- 刊出日期: 2023-05-10

Trends in incidence of atopic dermatitis among residents of five Asian countries, 1990 – 2019: an age-period-cohort analysis

1.
Department of Epidemiology and Health Statistics, School of Public Health, Institute of Medical Systems Biology, Guangdong Medical University, Dongguan, Guangdong Province 523808, China

摘要

摘要: 目的了解中国和亚洲4个发达国家居民1990 — 2019年特应性皮炎（AD）的发病趋势及年龄、时期、出生队列对AD发病率的影响，为我国AD的预防控制提供参考依据。方法收集2019年全球疾病负担研究（GBD 2019）数据库中1990 — 2019年中国、日本、韩国、以色列和新加坡亚洲5国居民AD发病率相关数据，采用年估计变化百分比（EAPC）描述AD发病率的变化趋势，并构建年龄 – 时期 – 队列（APC）模型分析AD发病率的年龄、时期、出生队列效应及其对发病率的风险。结果 1990 — 2019年中国居民AD年龄标化发病率逐年递增，EAPC值为0.0212%（95%CI = 0.0077%～0.0347%）；而日本、韩国、以色列和新加坡居民AD年龄标化发病率均逐年递减，EAPC值依次为 − 0.0433%（95%CI = − 0.0655%～− 0.0211%）、 − 0.0206%（95%CI = − 0.0380%～− 0.0032%）、 − 0.0073%（95%CI = − 0.0077% ～− 0.0069%）和− 0.0276%（95%CI = − 0.0452%～− 0.0099%）。APC模型分析结果显示，0～4岁和70～94岁居民是亚洲5国AD发病的高危人群；中国居民AD发病风险随时期推移而增加、随出生年份推进而下降，而日本、韩国、以色列和新加坡4个亚洲发达国家居民AD发病风险则随时期推移而下降、随出生年份推进而上升。结论中国居民1990 — 2019年AD的发病率逐年增加，较亚洲其他发达国家AD的防治工作需进一步完善，尤其应重点关注儿童和老年人AD的预防和控制。
- 特应性皮炎(AD) /
- 发病趋势 /
- 年龄 – 时期 – 队列（APC）模型 /
- 亚洲
Abstract: Objective To examine the trend in the incidence of atopic dermatitis (AD) and the influence of age, period and birth cohort on AD incidence among residents of China and four developed Asian countries from 1990 – 2019, and to provide a reference for the prevention and control of AD in China. Methods The data on the incidence of AD among residents of China and four Asian countries ( Japan, Korea, Israel and Singapore) from 1990 – 2019 were extracted from the Global Burden of Disease Study 2019 (GBD 2019) database. Estimated annual percentage change (EAPC) was used to describe country-specific trend in the incidence of AD and an age-period-cohort (APC) model was constructed to analyze effects of age, period and birth cohort on AD incidence. Results The annual age standardized incidence of AD among residents in China increased from 1990 – 2019 with an EAPC value of 0.0212% (95 confidence interval [95%CI]: 0.0077% – 0.0347%). In contrast, the annual age standardized incidence of AD decreased during the 30-year period among the residents of Japan, South Korea, Israel, and Singapore, with the EAPC values of – 0.0433% (95%CI = – 0.0655% – – 0.0211%), – 0.0206% (95%CI: – 0.0380% – – 0.0032%), – 0.0073% (95%CI: – 0.0077% – – 0.0069%), and – 0.0276% (95%CI: – 0.0452% – – 0.0099%), respectively. The results of APC model analysis showed that the residents aged 0 – 4 years and 70 – 94 years were at high risk of AD incidence in China and in the four Asian countries. The risk of AD incidence among the residents in China increased over time but decreased with the year of birth; while, the risk of AD incidence among residents of in the four Asian countries decreased over time but increased with the year of birth. Conclusion The incidence of AD among residents in China has increased year by year from 1990 to 2019, indicating that in comparison with the situation in the four developed Asian countries, the prevention and control of AD need to be promoted among residents in China, especially among the children and the elderly.
- atopic dermatitis /
- incidence trend /
- age-period-cohort model /
- Asia

HTML全文

图 1 亚洲五国居民1990 — 2019年AD年龄标化发病率变化趋势

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图 2 中国居民1990 — 2019年年龄、时期、出生队列AD发病风险变化趋势

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图 6 新加坡居民1990 — 2019年年龄、时期、出生队列AD发病风险变化趋势

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图 3 日本居民1990 — 2019年年龄、时期、出生队列AD发病风险变化趋势

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图 4 韩国居民1990 — 2019年年龄、时期、出生队列AD发病风险变化趋势

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图 5 以色列居民1990 — 2019年年龄、时期、出生队列AD发病风险变化趋势

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表 1 亚洲五国居民1990 — 2019年AD发病率APC模型的效应系数

项目	中国	日本	韩国	以色列	新加坡
年龄效应（岁）
0～4	0.6156 ^a	2.1046 ^a	1.9784 ^a	1.9340 ^a	1.9643 ^a
5～9	− 0.2351 ^a	0.5706 ^a	0.4960 ^a	0.4389 ^a	0.5080 ^a
10～14	− 0.4857 ^a	− 0.2636 ^a	− 0.2216 ^a	− 0.2593 ^a	− 0.1837 ^a
15～19	− 0.2312 ^a	− 0.5398 ^a	− 0.4758 ^a	− 0.4602 ^a	− 0.4244 ^a
20～24	0.0171	− 0.5594 ^a	− 0.5207 ^a	− 0.4090 ^a	− 0.4618 ^a
25～29	0.0684 ^a	− 0.4983 ^a	− 0.4540 ^a	− 0.3281 ^a	− 0.4335 ^a
30～34	− 0.0280	− 0.4288 ^a	− 0.4155 ^a	− 0.3368 ^a	− 0.4156 ^a
35～39	− 0.1482 ^a	− 0.3735 ^a	− 0.3919 ^a	− 0.3947 ^a	− 0.4014 ^a
40～44	−0.1801 ^a	− 0.3346 ^a	− 0.3561 ^a	− 0.4134 ^a	− 0.3614 ^a
45～49	− 0.1335 ^a	− 0.3410 ^a	− 0.3424 ^a	− 0.4135 ^a	− 0.3451 ^a
50～54	− 0.0021	− 0.2733 ^a	− 0.2809 ^a	− 0.3835 ^a	− 0.2886 ^a
55～59	0.0508 ^a	− 0.1759 ^a	− 0.1851 ^a	− 0.3435 ^a	− 0.2068 ^a
60～64	0.0317	− 0.0802 ^a	− 0.0794 ^a	− 0.2387 ^a	− 0.1176 ^a
65～69	0.0320	0.0311	0.0277	− 0.0016	− 0.0173
70～74	0.0641 ^a	0.1065 ^a	0.0978 ^a	0.1988 ^a	0.0651 ^a
75～79	0.1036 ^a	0.1429 ^a	0.1517 ^a	0.2579 ^a	0.1332 ^a
80～84	0.1264 ^a	0.2161 ^a	0.2277 ^a	0.2926 ^a	0.2181 ^a
85～89	0.1504 ^a	0.3273 ^a	0.3342 ^a	0.3977 ^a	0.3356 ^a
90～94	0.1839 ^a	0.3695 ^a	0.4100 ^a	0.4624 ^a	0.4329 ^a
时期效应（年份）
1990 — 1994	− 0.0128	0.0176	0.0192	0.0141	0.0262 ^a
1995 — 1999	− 0.0097	0.0110	0.0121	0.0082	0.0155
2000 — 2004	− 0.0030	0.0032	0.0038	0.0028	0.0091
2005 — 2009	0.0037	− 0.0037	− 0.0046	− 0.0027	− 0.0025
2010 — 2014	0.0083	− 0.0103	− 0.0117	− 0.0085	− 0.0211
2015 — 2019	0.0135	− 0.0179	− 0.0188	− 0.0141	− 0.0271 ^a
出生队列效应（年份）
1900 — 1904	0.0502	− 0.0763	− 0.0681	− 0.0553	− 0.0712
1905 — 1909	0.0493	− 0.0672 ^a	− 0.0584	− 0.0498	− 0.0813 ^a
1910 — 1914	0.0455	− 0.0585 ^a	− 0.0496	− 0.0454	− 0.0781 ^a
1915 — 1919	0.0411	− 0.0505 ^a	− 0.0438	− 0.0398	− 0.0574 ^a
1920 — 1924	0.0386	− 0.0408	− 0.0380	− 0.0350	− 0.0517 ^a
1925 — 1929	0.0334	− 0.0361	− 0.0291	− 0.0270	− 0.0418
1930 — 1934	0.0265	− 0.0338	− 0.0233	− 0.0220	− 0.0292
1935 — 1939	0.0180	− 0.0291	− 0.0259	− 0.0183	− 0.0201
1940 — 1944	0.0081	− 0.0224	− 0.0243	− 0.0158	− 0.0082
1945 — 1949	0.0061	− 0.0161	− 0.0231	− 0.0134	− 0.0119
1950 — 1954	0.0050	− 0.0106	− 0.0187	− 0.0077	− 0.0157
1955 — 1959	0.0020	− 0.0048	− 0.0095	− 0.0007	− 0.0072
1960 — 1964	− 0.0038	0.0028	0.0009	0.0035	− 0.0154
1965 — 1969	− 0.0107	0.0089	0.0095	0.0058	0.0038
1970 — 1974	− 0.0182	0.0150	0.0169	0.0098	− 0.0359
1975 — 1979	− 0.0160	0.0205	0.0211	0.0133	0.0243
1980 — 1984	− 0.0141	0.0258	0.0245	0.0180	− 0.0125
1985 — 1989	− 0.0132	0.0325	0.0250	0.0232	0.0425
1990 — 1994	− 0.0204	0.0424 ^a	0.0301	0.0316	0.0373
1995 — 1999	− 0.0347	0.0514 ^a	0.0439 ^a	0.0343	0.0745 ^a
2000 — 2004	− 0.0372	0.0604 ^a	0.0543 ^a	0.0397	0.0740 ^a
2005 — 2009	− 0.0423	0.0642 ^a	0.0513 ^a	0.0459 ^a	0.0741 ^a
2010 — 2014	− 0.0561	0.0608 ^a	0.0572 ^a	0.0507 ^a	0.0872 ^a
2015 — 2019	− 0.0570	0.0617 ^a	0.0771 ^a	0.0542 ^a	0.1201 ^a
注：a P < 0.05。

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参考文献(26)

[1]	Laughter MR, Maymone MBC, Mashayekhi S, et al. The global burden of atopic dermatitis: lessons from the Global Burden of Disease Study 1990 – 2017[J]. British Journal of Dermatology, 2021, 184(2): 304 – 309. doi: 10.1111/bjd.19580
[2]	Tsai TF, Rajagopalan M, Chu CY, et al. Burden of atopic dermatitis in Asia[J]. The Journal of Dermatology, 2019, 46(10): 825 – 834. doi: 10.1111/1346-8138.15048
[3]	Dong WL, An J, Yu M, et al. The prevalence and year lived with disability of atopic dermatitis in China: findings from the global burden of disease study 2019[J]. World Allergy Organization Journal, 2021, 14(11): 100604. doi: 10.1016/j.waojou.2021.100604
[4]	Andersen YMF, Egeberg A, Gislason GH, et al. Risk of myocardial infarction, ischemic stroke, and cardiovascular death in patients with atopic dermatitis[J]. Journal of Allergy and Clinical Immun-ology, 2016, 138(1): 310 – 312.e3. doi: 10.1016/j.jaci.2016.01.015
[5]	Weidinger S, Novak N. Atopic dermatitis[J]. The Lancet, 2016, 387(10023): 1109 – 1122. doi: 10.1016/S0140-6736(15)00149-X
[6]	Smith TR, Wakefield J. A review and comparison of age - period - cohort models for cancer incidence[J]. Statistical Science, 2016, 31(4): 591 – 610.
[7]	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]. The Lancet, 2020, 396(10258): 1204 – 1222. doi: 10.1016/S0140-6736(20)30925-9
[8]	北京协和医院, 世界卫生组织国际分类家族合作中心. 疾病和有关健康问题的国际统计分类第十次修订本(ICD-10)[M]. 董景五, 译. 2版. 北京: 人民卫生出版社, 2008: 603 – 668.
[9]	Liu ZQ, Jiang YF, Yuan HB, et al. The trends in incidence of primary liver cancer caused by specific etiologies: results from the Global Burden of Disease Study 2016 and implications for liver cancer prevention[J]. Journal of Hepatology, 2019, 70(4): 674 – 683. doi: 10.1016/j.jhep.2018.12.001
[10]	Cao GY, Jing WZ, Liu J, et al. The global trends and regional differences in incidence and mortality of hepatitis A from 1990 to 2019 and implications for its prevention[J]. Hepatology Inter-national, 2021, 15(5): 1068 – 1082. doi: 10.1007/s12072-021-10232-4
[11]	Yang XR, Chen H, Zhang TC, et al. Global, regional, and national burden of blindness and vision loss due to common eye diseases along with its attributable risk factors from 1990 to 2019: a systematic analysis from the global burden of disease study 2019[J]. Aging (Albany NY), 2021, 13(15): 19614 – 19642.
[12]	Guido D, Leonardi M, Mellor-Marsá B, et al. Pain rates in general population for the period 1991 – 2015 and 10 - years prediction: results from a multi - continent age - period - cohort analysis[J]. The Journal of Headache and Pain, 2020, 21(1): 52. doi: 10.1186/s10194-020-01108-3
[13]	Bai RH, Huang H, Li MM, et al. Temporal trends in the incidence and mortality of skin malignant melanoma in China from 1990 to 2019[J]. Journal of Oncology, 2021, 2021: 9989824.
[14]	Yang Y, Schulhofer-Wohl S, Fu WJ, et al. The intrinsic estimator for age - period - cohort analysis: what it is and how to use it[J]. American Journal of Sociology, 2008, 113(6): 1697 – 1736. doi: 10.1086/587154
[15]	Luo LY. Assessing validity and application scope of the intrinsic esti-mator approach to the age - period - cohort problem[J]. Demography, 2013, 50(6): 1945 – 1967. doi: 10.1007/s13524-013-0243-z
[16]	Miranda MDM, Nielsen B, Nielsen JP. Inference and forecasting in the age - period - cohort model with unknown exposure with an application to mesothelioma mortality[J]. Journal of the Royal Statistical Society:Series A (Statistics in Society), 2015, 178(1): 29 – 55. doi: 10.1111/rssa.12051
[17]	Nutten S. Atopic dermatitis: global epidemiology and risk factors[J]. Annals of Nutrition and Metabolism, 2015, 66(S1): 8 – 16.
[18]	Fishbein AB, Silverberg JI, Wilson EJ, et al. Update on atopic dermatitis: diagnosis, severity assessment, and treatment selection[J]. The Journal of Allergy and Clinical Immunology:In Practice, 2020, 8(1): 91 – 101. doi: 10.1016/j.jaip.2019.06.044
[19]	Park YM, Lee SY, Kim WK, et al. Risk factors of atopic dermatitis in Korean schoolchildren: 2010 international study of asthma and allergies in childhood[J]. Asian Pacific Journal of Allergy and Immunology, 2016, 34(1): 65 – 72.
[20]	Dharma C, Lefebvre DL, Tran MM, et al. Patterns of allergic sensitization and atopic dermatitis from 1 to 3 years: effects on allergic diseases[J]. Clinical and Experimental Allergy, 2018, 48(1): 48 – 59. doi: 10.1111/cea.13063
[21]	World Health Organization. Ageing and health[EB/OL]. (2021 – 10 – 04)[2022 – 02 – 10].https://www.who.int/news-room/fact-sheets/detail/ageing-and-health.
[22]	吕婷, 王宏伟. 老年特应性皮炎的认识和管理[J]. 中国皮肤性病学杂志, 2019, 33(8): 949 – 954. doi: 10.13735/j.cjdv.1001-7089.201810075
[23]	Lee BW, Detzel PR. Treatment of childhood atopic dermatitis and economic burden of illness in Asia Pacific countries[J]. Annals of Nutrition and Metabolism, 2015, 66 Suppl 1: 18 – 24.
[24]	王宇. 疾病预防控制的社会意义[J]. 中国公共卫生, 2018, 34(1): 1 – 3.
[25]	Global Burden of Disease 2020 Health Financing Collaborator Network. Tracking development assistance for health and for COVID-19: a review of development assistance, government, out-of-pocket, and other private spending on health for 204 countries and territories, 1990 – 2050[J]. The Lancet, 2021, 398(10308): 1317 – 1343. doi: 10.1016/S0140-6736(21)01258-7
[26]	Cohen AK, Syme SL. Education: a missed opportunity for public health intervention[J]. American Journal of Public Health, 2013, 103(6): 997 – 1001. doi: 10.2105/AJPH.2012.300993