Trend of pulmonary tuberculosis reported incidence in four core megacities of China from 2015 to 2024: a population-based study using Joinpoint regression model

doi:10.19982/j.issn.1000-6621.20260181

Abstract

Abstract:

Objective: To analyze the temporal trends in pulmonary tuberculosis (PTB) incidence in major Chinese megacities (Beijing, Shanghai, Guangzhou, and Shenzhen) from 2015 to 2024 using Joinpoint regression, providing evidence for the formulation of targeted prevention and control measures. Methods: Data on reported PTB cases in core megacities from 2015 to 2024 were collected; descriptive analysis was used to assess incidence characteristics, and Joinpoint regression was applied to analyze temporal trends. Results: From 2015 to 2024, the average annual reported incidence rates per 100000 population were 30.55 in Beijing, 56.24 in Guangzhou, 24.83 in Shanghai, and 36.68 in Shenzhen. Joinpoint regression analysis revealed that the reported incidence rate in Beijing showed a gradual downward trend from 2015 to 2021 (APC=-4.36%, P=0.070) and a rapid downward trend from 2021 to 2025 (APC=-11.58%, P<0.001); In Guangzhou, the annual average reported incidence rate showed the greatest decline (AAPC=-10.03%, P<0.001), with a rapid decline from 2015 to 2021 (APC=-11.41%, P<0.001) and a gradual decline from 2021 to 2024 (APC=-7.19%, P=0.008). The reported incidence rates among men in the four cities of Beijing, Shanghai, Guangzhou and Shenzhen (38.22 per 100000, 32.30 per 100000, 64.10 per 100000 and 43.82 per 100000) were all higher than those among women (22.34 per 100000, 16.85 per 100000, 33.54 per 100000, 28.09 per 100000). In Beijing and Shanghai, the rate of decline in the reported incidence among men (AAPC=-6.88%, -8.85%) was higher than that among women (AAPC=-6.38%, -7.32%); while in Guangzhou and Shenzhen, the rate of decline in reported incidence among men (AAPC=-9.43%, -5.30%) was slower than that among women (AAPC=-10.36%, -5.98%); The decline in reported incidence rates was greater in the 15-59 age group than in other age groups (AAPC=-9.10%, P<0.001; AAPC=-10.02%, P=0.001; AAPC=-12.06%, P<0.001; AAPC=-9.72%, P=0.003). Conclusion: From 2015 to 2024, the standardized reported incidence rates of pulmonary tuberculosis in the four major core megacities all showed a downward trend, while the etiological positivity rates all showed an upward trend. The standardized reported incidence rate in males was consistently higher than that in females, and the average annual reported incidence rate among the elderly aged 60 years and above was the highest. It is recommended that regionalized periodic screening be implemented for the elderly population, health education in occupational settings be strengthened for young and middle-aged men, and screening strategies be dynamically adjusted based on the smart monitoring systems of megacities, in order to promote a shift in tuberculosis control from passive detection to active intervention.

Key words: Tuberculosis, pulmonary, Incidence, Regression analysis, Cities

CLC Number:

R521

Chen Anni, Meng Yujie, Li Tao, Zheng Huan, Wang Songwang. Trend of pulmonary tuberculosis reported incidence in four core megacities of China from 2015 to 2024: a population-based study using Joinpoint regression model[J]. Chinese Journal of Antituberculosis, 2026, 48(9): 1386-1393. doi: 10.19982/j.issn.1000-6621.20260181

Figures/Tables 5

地区/指标	报告发病数 (例)	报告发病率 (/10万)	标准化报告发病率(/10万)
地区/指标	报告发病数 (例)	报告发病率 (/10万)	合计	2015年	2016年	2017年	2018年	2019年	2020年	2021年	2022年	2023年	2024年
北京	66683	30.55	28.39	34.79	33.66	34.67	31.87	29.74	26.31	28.69	24.27	20.59	19.29
性别
男性	42791	38.22	34.59	44.28	42.18	42.97	38.29	35.88	30.85	34.17	28.16	25.20	23.91
女性	23892	22.34	21.63	24.94	23.89	25.66	24.74	22.87	21.30	23.12	19.97	15.71	14.09
年龄组(岁)
0~14	354	1.39	1.39	1.66	1.68	1.89	1.59	2.05	1.27	1.06	1.25	0.80	0.77
15~59	44414	29.54	29.54	37.58	36.22	37.28	33.56	31.43	27.59	29.33	24.24	18.85	16.69
≥60	21915	50.84	50.84	57.13	55.68	57.27	55.18	50.59	46.01	53.03	46.44	45.47	45.89
上海	57943	24.83	21.76	28.07	27.65	26.46	25.81	24.57	22.13	20.75	11.89	16.16	14.13
性别
男性	38942	32.30	27.34	36.13	34.99	33.27	32.95	31.42	27.20	24.88	13.99	20.32	18.21
女性	19001	16.85	15.65	18.82	18.89	18.54	17.86	17.73	16.51	16.63	9.77	11.86	9.88
年龄组(岁)
0~14	237	1.95	1.95	2.43	3.14	2.46	1.66	2.40	1.89	1.55	1.21	1.58	1.34
15~59	37822	22.34	22.34	28.55	28.68	27.59	27.15	25.45	23.72	21.61	11.47	14.82	12.20
≥60	19884	38.38	38.38	51.07	47.69	45.66	44.47	42.85	36.19	36.25	23.57	34.67	32.95
广州	89693	56.24	60.08	90.97	85.15	81.60	66.73	58.59	52.39	45.28	42.50	41.06	36.54
性别
男性	61103	64.10	79.89	120.82	115.31	110.21	90.08	73.06	64.15	58.65	57.88	57.26	51.46
女性	28590	33.54	38.74	57.31	52.29	50.63	42.25	40.93	38.32	31.53	27.34	25.03	21.79
年龄组(岁)
0~14	607	3.05	3.05	5.18	4.62	3.38	3.58	4.36	2.80	2.28	1.94	2.02	2.12
15~59	66729	55.41	55.41	89.22	86.10	82.47	66.87	60.13	54.40	42.42	36.69	32.77	29.13
≥60	22357	116.87	116.87	179.26	159.20	153.68	126.84	105.41	93.20	96.22	101.10	106.60	94.68
深圳	55347	36.68	39.58	46.42	45.11	54.48	44.31	40.49	34.83	36.29	29.59	33.95	30.28
性别
男性	36110	43.82	48.06	54.25	55.24	66.65	56.77	46.27	40.59	43.79	36.77	42.55	37.68
女性	19237	28.09	29.31	35.91	33.10	39.36	30.35	32.37	27.20	27.08	21.73	24.31	21.72
年龄组(岁)
0~14	378	1.67	1.67	1.31	2.16	2.26	2.28	2.17	1.36	0.79	1.21	1.56	2.03
15~59	48451	41.28	41.28	59.47	58.62	67.22	53.53	50.59	35.01	34.84	27.55	28.38	25.52
≥60	6518	59.66	59.66	45.51	40.60	61.43	53.40	43.04	66.33	75.27	63.70	83.91	73.54

References 25

[1]	徐彩红, 赵雁林. 全球加速扩展结核病预防性治疗行动计划背景下的中国对策[J]. 中华结核和呼吸杂志, 2022, 45(3): 308-312. doi:10.3760/cma.j.cn112147-20210722-00520.
[2]	屈燕, 李涛, 马文斌, 等. 世界卫生组织《2025年全球结核病报告》解读[J]. 结核与肺部疾病杂志, 2025, 6(6): 613-623. doi:10.19983/j.issn.2096-8493.20250178.
[3]	Lönnroth K, Raviglione M. The WHO’s new End TB Strategy in the post-2015 era of the Sustainable Development Goals[J]. Trans R Soc Trop Med Hyg, 2016, 110(3): 148-150. doi:10.1093/trstmh/trv108.
[4]	刘沼悦, 刘俊萍, 王楠, 等. 基于LASSO-logistic回归探析中国边境地区流动人口结核病防治健康教育影响因素[J]. 中国卫生事业管理, 2024, 41(9):1043-1047, 1080.
[5]	何雨昕, 陈坚, 廖建英, 等. 基于Joinpoint模型的2008-2023年百色市HIV/TB双重感染流行趋势分析[J]. 热带医学杂志, 2025, 25(2): 263-267. doi:10.3969/j.issn.1672-3619.2025.02.025.
[6]	丁远路, 肖文静, 陶芳芳, 等. 基于Joinpoint回归模型的2009-2023年上海市肺结核报告发病趋势分析[J]. 中国防痨杂志, 2025, 47(10):1289-1299. doi:10.19982/j.issn.1000-6621.20250123.
[7]	宋媛媛, 李涛, 夏辉, 等. 1997-2023年全国肺结核报告发病流行病学特征[J]. 中国防痨杂志, 2024, 46(10):1198-1208. doi:10.19982/j.issn.1000-6621.20240382.
[8]	杨超, 王晶, 唐桂林. 2012-2021年北京市通州区流动人口肺结核患者就诊延迟的变化趋势及影响因素分析[J]. 疾病监测, 2023, 38(9): 1033-1038. doi:10.3784/jbjc.202303300140.
[9]	李雪秋, 刘群, 唐科, 等. 2011-2020年广州市肺结核死亡趋势及年龄-时期-队列模型分析[J]. 中国防痨杂志, 2025, 47(1): 44-50. doi:10.19982/j.issn.1000-6621.20240323.
[10]	郑光敏, 王挺, 张丹妮, 等. “十三五”期间广州市不同结核病防治管理模式实施效果评价[J]. 中国防痨杂志, 2024, 46(2): 199-205. doi:10.19982/j.issn.1000-6621.20230373.
[11]	赵云, 徐芳, 王琛, 等. 分子诊断技术联合相关细胞因子表达水平检测对肺结核与非结核分枝杆菌肺病的鉴别诊断价值分析[J]. 新发传染病电子杂志, 2025, 10(5): 53-58. doi:10.19871/j.cnki.xfcrbzz.2025.05.010.
[12]	童海涛, 郑叶, 周静, 等. 早期分泌抗原靶标6免疫组织化学联合抗酸染色法检测在结核病病理诊断中的价值[J]. 安徽医药, 2026, 30(1):160-164, 后插6. doi:10.3969/j.issn.1009-6469.2026.01.032.
[13]	Bulizani I C, Ribeiro S, Silva A C, et al. Tuberculosis detection actions in Primary Health Care during the COVID-19 pandemic[J]. Rev Bras Enferm, 2025, 78(5): e20240389. doi:10.1590/0034-7167-2024-0389.
[14]	Li T, Li J, Du X, et al. Age-Specific Pulmonary Tuberculosis Notification Rates-China, 2008-2018[J]. China CDC Wkly, 2022, 4(38): 841-846. doi:10.46234/ccdcw2022.176.
[15]	陈莉莉, 李朋, 蔡凤珠, 等. 基于Joinpoint跃变模型的2010-2022年上海市浦东新区肺结核流行特征分析[J]. 职业与健康, 2024, 40(9): 1195-1200. doi:10.13329/j.cnki.zyyjk.2024.0240.
[16]	Dong Z, Wang Q Q, Yu S C, et al. Age-period-cohort analysis of pulmonary tuberculosis reported incidence, China, 2006-2020[J]. Infect Dis Poverty, 2022, 11(1): 85. doi:10.1186/s40249-022-01009-4.
[17]	马建军, 张铁娟, 于世晖, 等. 1990-2021年中国结核病疾病负担变化趋势分析[J]. 中华流行病学杂志, 2025, 46(6): 951-959. doi:10.3760/cma.j.cn112338-20240812-00497.
[18]	兰勇兵, 柯雅蕾, 吕筠, 等. 中国10个地区成年人结核病发病率的流行病学特征分析[J]. 中华流行病学杂志, 2026, 47(1):21-27. doi:10.3760/cma.j.cn112338-20250609-00388.
[19]	王飞, 石晓冬, 郑皓, 等. 回答一个核心问题, 把握十个关系--《北京城市总体规划(2016年-2035年)》的转型探索[J]. 城市规划, 2017, 41(11): 9-16, 32. doi:10.11819/cpr20171103a.
[20]	赖静文. 上海市和深圳市不同结核病防治服务体系模式下的工作成效分析[J]. 结核病与肺部健康杂志, 2019, 8(1): 24-28. doi:10.3969/j.issn.2095-3755.2019.01.007.
[21]	孙闪华, 李艳圆, 陶荔莹, 等. 2011-2020年北京市儿童肺结核报告登记及流行病学特征分析[J]. 结核与肺部疾病杂志, 2021, 2(4):305-310. doi:10.3969/j.issn.2096-8493.20210137.
[22]	Liao Q, Feng H, Li Y, et al. Evaluation of an artificial intelligence (AI) system to detect tuberculosis on chest X-ray at a pilot active screening project in Guangdong, China in 2019[J]. J Xray Sci Technol, 2022, 30(2): 221-230. doi:10.3233/XST-211019.
[23]	Lai P, Cai W, Qu L, et al. Pulmonary Tuberculosis Notification Rate Within Shenzhen, China, 2010-2019: Spatial-Temporal Analysis[J]. JMIR Public Health Surveill, 2024, 10: e57209. doi:10.2196/57209.
[24]	吴惠忠, 周芳静, 廖庆华, 等. 2019年广东省连江口镇≥5岁常住人口肺结核主动筛查策略实施效果分析[J]. 中国防痨杂志, 2021, 43(10):1032-1038. doi:10.3969/j.issn.1000-6621.2021.10.011.
[25]	Teo A K J, Rahevar K, Morishita F, et al. Tuberculosis in older adults: case studies from four countries with rapidly ageing populations in the western pacific region[J]. BMC Public Health, 2023, 23(1): 370. doi:10.1186/s12889-023-15197-7. pmid: 36810018

年份	北京	上海	广州	深圳
2015	2647(46.59)	2495(37.83)	4609(45.04)	2770(50.83)
2016	2500(44.80)	2351(37.00)	4301(43.82)	2604(48.03)
2017	2494(42.36)	2378(39.85)	4165(43.73)	2867(44.57)
2018	2736(48.75)	3496(57.92)	4444(49.66)	3491(64.80)
2019	3323(60.66)	3815(63.91)	4976(60.13)	3839(72.28)
2020	2953(60.97)	3466(63.97)	4528(58.44)	3980(76.14)
2021	3609(65.23)	3455(65.66)	4565(59.54)	4212(79.79)
2022	3318(69.39)	1843(64.55)	4304(60.99)	3482(78.19)
2023	3213(75.21)	3016(71.45)	4463(65.37)	3905(81.10)
2024	3231(76.62)	2808(71.96)	4442(71.37)	3619(81.33)
合计	30024(57.87)	29123(55.39)	44797(54.42)	34769(66.57)