Study on the epidemic characteristics of tuberculosis and its correlation with meteorological factors in Hotan Region from 2016 to 2022
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摘要:
目的 分析和田地区2016―2022年结核病流行特征及探讨气象因素对结核病发病风险的影响，为防控结核病的流行提供参考依据。 方法 用描述性研究分析2016―2022年和田地区结核病在时间、地区和人群中的流行特征，使用分布滞后非线性模型分析不同气象条件对结核病日发病数的影响。 结果 和田地区2016―2022年累计报告结核病38 006例，男性报告病例数高于女性，且农民、60~＜70岁患者占比较高; 洛浦县(1 070例)和墨玉县(1 047例)结核病的年均报告病例数较多，且洛浦县结核病年均发病率最高(377.95/10万)。平均温度过低是结核病发病的危险因素，在-11.00 ℃时风险最大，但差异无统计学意义(RR=1.27, 95% CI: 0.74~2.18)，且在滞后3 d时，发病风险最高(RR=2.58, 95% CI: 1.44~4.60); 相对湿度较低或较高均会增加结核病的发病风险; 当累计日照时长超过12 h，RR值均＞1.00(P＜0.05)，且在滞后2 d时，结核病发病风险最高(RR=1.10, 95% CI: 0.98~1.24)。 结论 和田地区结核病患者主要集中在农民和高年龄组人群，洛浦县和于田县结核病负担较高，应注意平均温度过低、较低或较高的相对湿度和累计日照时间过长对结核病的影响。 Abstract:Objective To analyze the epidemic characteristics of tuberculosis in Hotan Prefecture from 2016 to 2022 and to explore the impact of meteorological factors on the risk of tuberculosis onset, aiming to provide a reference basis for preventing and controlling the epidemic of tuberculosis. Methods Descriptive research was employed to analyze the epidemic characteristics of tuberculosis in Hotan Prefecture in terms of time, region, and population from 2016 to 2022. The distributed lag non-linear model was utilized to analyze the impact of different meteorological conditions on the daily incidence of tuberculosis. Results From 2016 to 2022, a total of 38 006 tuberculosis patients were reported in Hotan Prefecture. The incidence number among males was higher than that among females. Farmers and patients aged 60- < 70 accounted for the highest proportion. The average annual number of reported cases was relatively high in Luopu County (1 070 cases) and Moyu County (1 047 cases), and Luopu County had the highest average annual incidence rate (377.95 per 100 000). Low average temperature was a risk factor for tuberculosis onset. At -11.00 ℃, the relative risk (RR) value was the highest (RR=1.27, 95% CI: 0.74-2.18), but there was no significant difference, and with a lag of 3 days, the risk of onset was the highest (RR=2.58, 95% CI: 1.44-4.60). Relatively low or high humidity would increase the risk of tuberculosis onset. When the cunulative sunshine exposure time exceeded 12 hours, the RR values were all greater than 1.00 (P < 0.05), and with a lag of 2 days, the risk of onset was the highest (RR=1.10, 95% CI: 0.98-1.24). Conclusions Tuberculosis patients in Hotan Prefecture are mainly concentrated among farmers and the elderly population. The tuberculosis burden is relatively high in Luopu and Yutian County. Attention should be paid to the impact of low average temperature, relatively low or high humidity, and long cumulative sunshine duration on tuberculosis. -
图 1 和田地区2016―2022年结核病发病情况变化趋势
Figure 1. The trends of tuberculosis incidence in Hotan Prefecture from 2016 to 2022
图 2 和田地区2016―2022年结核病分人群发病情况
A：不同职业病例数分布情况; B：不同年龄组病例数分布情况。
Figure 2. The incidence of tuberculosis among different populations in Hotan Prefecture from 2016 to 2022
A: the distribution of the number of cases among different occupations; B: the distribution of the number of cases among different age groups.
图 3 和田地区气象因素对结核病发病的总体累积效应
A：平均温度; B：相对湿度; C：累计日照; D：平均风速。
Figure 3. The overall cumulative effect of meteorological factors on the incidence of tuberculosis in Hotan Prefecture
A: average temperature; B: relative humidity; C: cumulative sunshine duration; D: average wind velocity.
图 4 极端高值气象条件下不同滞后天数与结核病发病的关联性
A：平均温度; B：相对湿度; C：累计日照; D：平均风速。
Figure 4. Association between different lag days and tuberculosis incidence under extreme high value meteorological conditions
A: average temperature; B: relative humidity; C: cumulative sunshine duration; D: average wind velocity.
图 5 极端低值气象条件下不同滞后天数与结核病发病的关联性
A：平均温度; B：相对湿度; C：累计日照; D：平均风速。
Figure 5. Association between different lag days and tuberculosis incidence under extreme low value meteorological conditions
A: average temperature; B: relative humidity; C: cumulative sunshine hours; D: average wind velocity.
表 1 和田地区各区县2016―2022年结核病发病情况
Table 1. Incidence of tuberculosis in cities and counties of Hotan Prefecture from 2016 to 2022
地区
Regions2016年year 2017年year 2018年year 2019年year 发病数
Number of cases发病率
Incidence rate/100 000-1发病数
Number of cases发病率
Incidence rate/100 000-1发病数
Number of cases发病率
Incidence rate/100 000-1发病数
Number of cases发病率
Incidence rate/100 000-1民丰县Minfeng County 203 518.08 176 457.35 282 757.53 123 312.11 于田县Yutian County 909 286.60 828 238.96 1 692 486.03 1 064 357.72 洛浦县Luopu County 1 151 403.49 1 598 567.83 1 987 691.83 980 367.99 和田县Hotan County 803 273.92 1 081 348.95 1 630 556.03 721 212.89 策勒县Qira County 627 357.14 316 117.11 1 247 562.51 353 202.12 皮山县Pishan County 775 269.62 915 316.23 893 343.79 1 047 349.09 和田市Hotan City 484 141.89 570 119.63 836 226.92 998 249.70 墨玉县Moyu County 1 165 199.68 1 376 202.21 2 454 436.09 1 109 192.63 合计Total 6 117 261.24 6 860 268.62 11 021 458.22 6 395 268.91 地区
Regions2019年year 2020年year 2021年year 年均Annual average 发病数
Number of cases发病率
Incidence rate/100 000-1发病数
Number of cases发病率
Incidence rate/100 000-1发病数
Number of cases发病率
Incidence rate/100 000-1发病数
Number of cases发病率
Incidence rate/100 000-1民丰县Minfeng County 45 114.99 48 118.22 110 248.85 141 361.02 于田县Yutian County 886 242.39 632 175.41 579 226.38 941 287.64 洛浦县Luopu County 620 222.90 569 188.80 584 202.82 1 070 377.95 和田县Hotan County 620 223.46 572 154.70 429 124.70 837 270.66 策勒县Qira County 306 179.89 219 119.80 191 120.12 466 236.96 皮山县Pishan County 838 186.95 409 137.61 325 114.69 743 245.43 和田市Hotan City 879 203.89 539 114.72 381 67.69 670 160.63 墨玉县Moyu County 426 79.75 446 78.80 355 61.72 1 047 178.70 合计Total 4 620 180.07 3 434 131.51 2 954 118.76 5 914 241.05 
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[1] World Health organization. Global Tuberculosis Report 2024[EB/OL]. (2024-09-06)[2025-01-06]. https://www.who.int/teams/global-tuberculosis-programme/tb-reports/global-tuberculosis-report-2024 .[2] Deng LL, Zhao F, Li ZW, et al. Epidemiological characteristics of tuberculosis incidence and its macro-influence factors in Chinese mainland during 2014-2021[J]. Infect Dis Poverty, 2024, 13(1): 34. DOI: 10.1186/s40249-024-01203-6. [3] Zhang Y, Wang XQ, Liu NQ, et al. Intervention effect of new tuberculosis control model on tuberculosis incidence in Xinjiang[J]. Infect Drug Resist, 2023, 16(2023): 7485-7496. DOI: 10.2147/IDR.S441899. [4] Chang ML, Emam M, Chen XD, et al. An investigation of the effects of meteorological factors on the incidence of tuberculosis[J]. Sci Rep, 2024, 14(1): 2088. DOI: 10.1038/s41598-024-52278-y. [5] 刘聪, 陈仁杰, 阚海东. "双碳"背景下的空气污染和气候变化流行病学研究进展与展望[J]. 中华流行病学杂志, 2023, 44(3): 353-359. DOI: 10.3760/cma.j.cn112338-20220824-00732.Liu C, Chen RJ, Kan HD. Progress and future perspective of epidemiological research of air pollution and climate change in the context of achieving carbon peaking and carbon neutrality goals[J]. Chin J Epidemiol, 2023, 44(3): 353-359. DOI: 10.3760/cma.j.cn112338-20220824-00732. [6] Sun SH, Chang QX, He JY, et al. The association between air pollutants, meteorological factors and tuberculosis cases in Beijing, China: a seven-year time series study[J]. Environ Res, 2023, 216(Pt 2): 114581. DOI: 10.1016/j.envres.2022.114581. [7] Gasparrini A, Armstrong B, Kenward MG. Distributed lag non-linear models[J]. Stat Med, 2010, 29(21): 2224-2234. DOI: 10.1002/sim.3940. [8] Luo CY, Qian J, Liu YQ, et al. Long-term air pollution levels modify the relationships between short-term exposure to meteorological factors, air pollution and the incidence of hand, foot and mouth disease in children: a DLNM-based multicity time series study in Sichuan Province, China[J]. BMC Public Health, 2022, 22(1): 1484. DOI: 10.1186/s12889-022-13890-7. [9] 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.Song YY, Li T, Xia H, et al. Analysis of the epidemiological characteristics of national reported pulmonary tuberculosis incidence, 1997-2023 [J]. Chin J Antituberc, 2024,46(10):1198-1208. DOI: 10.19982/j.issn.1000-6621.20240382. [10] 王乐, 依帕尔·艾海提, 王森路, 等. 2012―2022年新疆肺结核疫情分析[J]. 疾病预防控制通报, 2024, 39(4): 1-5. DOI: 10.13215/j.cnki.jbyfkztb.2401029.Wang L, Yipaer AHT, Wang SL, et al. Analysis of the tuberculosis epidemic in Xinjiang from 2012 to 2022[J]. Bull Dis Control Prev, 2024, 39(4): 1-5. DOI: 10.13215/j.cnki.jbyfkztb.2401029. [11] 中华人民共和国中央人民政府. 国家卫生健康委发布《中国吸烟危害健康报告2020》[EB/OL]. (2021-05-30)[2025-02-21]. https://www.gov.cn/xinwen/2021-05/30/content_5613994.htm .[12] Dong Z, Wang QQ, Yu SC, 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. [13] Lyu HL, Wang LH, Zhang XL, et al. Further analysis of tuberculosis in eight high-burden countries based on the global burden of disease study 2021 data[J]. Infect Dis Poverty, 2024, 13(1): 70. DOI: 10.1186/s40249-024-01247-8. [14] 新疆维吾尔自治区统计局. 各地、州、市、县(市)地区生产总值[EB/OL]. (2022-03-01)[2025-01-06]. https://tjj.xinjiang.gov.cn/tjj/gmjjsm/202203/89d4cb95c3154532a9a14f31f020e1e6.shtml .[15] 张燕, 王森路, 日孜宛古力·热合曼, 等. 新疆维吾尔自治区和田地区"肺结核主动筛查+全疗程住院治疗"模式对患者发现的效果[J]. 中国防痨杂志, 2024, 46(2): 145-150. DOI: 10.19982/j.issn.1000-6621.20230284.Zhang Y, Wang SL, Riziwanguli RHM, et al. Evaluation of the implementation effect of "active tuberculosis screening+ full-course hospitalization" model for patient detection in Hotan Prefecture, Xinjiang Uygur Autonomous Region[J]. Chin J Antituberc, 2024, 46(2): 145-150. DOI: 10.19982/j.issn.1000-6621.20230284. [16] Zhang WY, Wu Y, Wen B, et al. Non-pharmaceutical interventions for COVID-19 reduced the incidence of infectious diseases: a controlled interrupted time-series study[J]. Infect Dis Poverty, 2023, 12(1): 15. DOI: 10.1186/s40249-023-01066-3. [17] 和田地区行政公署. 和田概况[EB/OL]. (2024-03-12)[2025-01-11]. https://www.xjht.gov.cn/article/show.php?itemid=258216 .[18] Nie YW, Lu YQ, Wang CC, et al. Effects and interaction of meteorological factors on pulmonary tuberculosis in Urumqi, China, 2013-2019[J]. Front Public Health, 2022, 10: 951578. DOI: 10.3389/fpubh.2022.951578. [19] Huang K, Hu CY, Yang XY, et al. Contributions of ambient temperature and relative humidity to the risk of tuberculosis admissions: a multicity study in Central China[J]. Sci Total Environ, 2022, 838(Pt3): 156272. DOI: 10.1016/j.scitotenv.2022.156272. [20] Liyew AM, Clements ACA, Akalu TY, et al. Ecological-level factors associated with tuberculosis incidence and mortality: a systematic review and Meta-analysis[J]. PLoS Glob Public Health, 2024, 4(10): e0003425. DOI: 10.1371/journal.pgph.0003425. [21] Wang J, Li W, Huang WZ, et al. The associations of ambient fine particles with tuberculosis incidence and the modification effects of ambient temperature: a nationwide time-series study in China[J]. J Hazard Mater, 2023, 460: 132448. DOI: 10.1016/j.jhazmat.2023.132448. [22] Del Mar Díez Galán M, Redondo-Bravo L, Gómez-Barroso D, et al. The impact of meteorological factors on tuberculosis incidence in Spain: a spatiotemporal analysis[J]. Epidemiol Infect, 2024, 152: e58. DOI: 10.1017/S0950268824000499. -
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