安徽省三市大气污染物和绿地暴露对初治结核病患者病亡率的影响

doi:10.19982/j.issn.1000-6621.20230310

摘要/Abstract

摘要：

目的：探讨大气污染物和绿地暴露对初治结核病患者治疗期间病亡率的影响,从环境监测层面上为结核病患者的健康管理提供科学依据。方法：收集安徽省合肥市、淮南市、黄山市2015年1月1日至2020年12月31日的29519例初治结核病患者的数据。通过环境监测站收集大气污染物细颗粒物[空气动力学直径≤2.5μm 的颗粒(particulate matter with an aerodynamic diameter ≤2.5μm,PM_2.5)]、可吸入颗粒物[空气动力学直径≤10μm的颗粒(particulate matter with an aerodynamic diameter ≤10μm,PM₁₀)]、一氧化碳(CO)、二氧化氮(NO₂)数据。应用Cox比例风险模型计算大气污染物暴露与初治结核病患者病亡率的风险比(HR)及其95%置信区间(95%CI),同时结合绿地暴露进行亚组分析。结果：29519例结核病患者中,有369例(1.25%)在治疗期间死亡。多因素Cox回归分析结果显示,PM_2.5每增加10μg/m³,患者的死亡风险上升15.6%(HR=1.156,95%CI:1.146~1.165),PM₁₀每增加10μg/m³,患者的死亡风险上升18.3%(HR=1.183,95%CI:1.176~1.190),CO每增加0.10mg/m³,患者的死亡风险上升6.7%(HR=1.067,95%CI:1.060~1.074),NO₂每增加10μg/m³,患者的死亡风险上升2.8%(HR=1.028,95%CI:1.019~1.037)。将绿地暴露按照四分位数(Q₁~Q₄)由低到高进行分组后,大气污染物对病亡率的影响随绿地暴露的提升逐渐降低[以PM_2.5为例,其在250m和500m缓冲区归一化植被指数对病亡率的HR值,Q₁分别为1.218(95%CI:1.197~1.240)和1.231(95%CI:1.210~1.253),Q₄分别下降至1.125(95%CI:1.106~1.146)和1.138(95%CI:1.118~1.159)]。结论：大气污染物暴露是初治结核病患者治疗期间的危险因素,更高的绿化程度能够降低因暴露于大气污染物所导致的死亡风险。

关键词: 结核, 空气污染物, 环境暴露, 回顾性研究, 因素分析, 统计学

Abstract:

Objective: To explore the effect of exposure to air pollutants and greenness on mortality during the treatment of newly treated tuberculosis patients, and to provide a scientific basis for the health management of tuberculosis patients at the environmental level. Methods: Data were collected from 29519 newly treated tuberculosis patients from January 1, 2015 to December 31, 2020 in Hefei City, Huainan City, and Huangshan City, Anhui Province. Data on atmospheric pollutants fine particulate matter (particulate matter with an aerodynamic diameter ≤2.5 μm, PM_2.5), inhalable particulate matter (particulate matter with an aerodynamic diameter ≤10 μm, PM₁₀), carbon monoxide (CO), and nitrogen dioxide (NO₂) were collected through environmental monitoring stations. Cox proportional risk model was applied to calculate the risk ratios (HR) and the 95% confidence intervals (95%CI) for all-cause mortality of air pollutant exposures and newly treated tuberculosis patients, and subgroup analyses were also performed combining with greenness exposure. Results: Of the 29519 tuberculosis patients, 369 (1.25%) died during treatment. The results of multifactorial Cox regression analyses showed that the risk of death increased by 15.6% with every 10 μg/m³ increasement in PM_2.5 (HR=1.156, 95%CI: 1.146-1.165), 18.3% with every 10 μg/m³ increasement in PM₁₀ (HR=1.183, 95%CI: 1.176-1.190); with every 0.10 mg/m³ increase in CO, the risk of death increased by 6.7% (HR=1.067, 95%CI: 1.060-1.074), and with every 10 μg/m³ increase in NO₂, the risk of death increased by 2.8% (HR=1.028, 95%CI: 1.019-1.037). After being divided into different groups based on greenness exposure from low to high by quartiles (Q₁ to Q₄), the effect of air pollutants on mortality rate gradually decreased with elevated greenness exposures (PM_2.5, for example, the HR values of normalized vegetation index on disease mortality rate in the 250 m and 500 m buffer zones were 1.218 (95%CI: 1.197-1.240) and 1.231 (95%CI: 1.210-1.253) for Q₁, respectively, and decreased to 1.125 (95%CI: 1.106-1.146) and 1.138 (95%CI: 1.118-1.159) for Q₄, respectively). Conclusion: Exposure to atmospheric pollutants is a risk factor during the treatment of newly treated tuberculosis patients, and higher levels of greenness can reduce the risk of mortality due to exposure to atmospheric pollutants.

Key words: Tuberculosis, Air pollutants, Environmental exposure, Retrospective studies, Factor analysis, statistical

中图分类号:

R181
R52

赵嘉文, 张永忠, 李振华, 毛毅铖, 张菁菁, 胡成洋, 张秀军, 阚晓红. 安徽省三市大气污染物和绿地暴露对初治结核病患者病亡率的影响[J]. 中国防痨杂志, 2024, 46(1): 75-84. doi: 10.19982/j.issn.1000-6621.20230310

Zhao Jiawen, Zhang Yongzhong, Li Zhenhua, Mao Yicheng, Zhang Jingjing, Hu Chengyang, Zhang Xiujun, Kan Xiaohong. Effects of air pollutants and greenness exposure on the mortality of newly treated tuberculosis patients in three cities, Anhui Province[J]. Chinese Journal of Antituberculosis, 2024, 46(1): 75-84. doi: 10.19982/j.issn.1000-6621.20230310

图/表 8

图1

表1

初治结核病患者的一般人口学资料 [例(构成比,%)]

特征	全范围		NDVI 250m缓冲区				NDVI 500m缓冲区				Z值		P值
特征	全范围		低暴露		高暴露		低暴露		高暴露		Z值		P值
性别^a											-1.920		0.055
男性	20937(70.93)		10167(68.84)		10770(73.02)		10184(68.98)		10753(72.87)
女性	8582(29.07)		4602(31.16)		3980(26.98)		4579(31.02)		4003(27.13)
年龄组(岁)^a											-1.497		0.134
<64	21311(72.19)		11628(78.73)		9683(65.65)		11636(78.82)		9675(65.57)
≥65	8208(27.81)		3141(21.27)		5067(34.35)		3127(21.18)		5081(34.43)
工作环境^a											7.136		<0.001
室内	17872(60.54)		6215(42.08)		11657(79.03)		6171(41.80)		11701(79.30)
室外	11647(39.46)		8554(57.92)		3093(20.97)		8592(58.20)		3055(20.70)
居住地^a											-8.413		<0.001
城市	9211(31.20)		8095(54.81)		1116(7.57)		8234(55.77)		977(6.62)
乡村	20308(68.80)		6674(45.19)		13634(92.43)		6529(44.23)		13779(93.38)
所在城市											0.758		0.448
合肥	18087(61.27)		10296(69.71)		7791(52.82)		10337(70.02)		7750(52.52)
淮南	8288(28.08)		3882(26.28)		4406(29.87)		3853(26.10)		4435(30.06)
黄山	3144(10.65)		591(4.01)		2553(17.31)		573(3.88)		2571(17.42)
患者来源^a											-4.056		<0.001
健康检查或结核病接触者检查	305(1.03)		189(1.28)		116(0.79)		195(1.32)		110(0.75)
因症就诊	4260(14.43)		1836(12.43)		2424(16.43)		1826(12.37)		2434(16.49)
转诊	24954(84.54)		12744(86.29)		12210(82.78)		12742(86.31)		12212(82.76)
结核病分型^a											-48.090		<0.001
原发性肺结核	5(0.02)		2(0.01)		3(0.02)		2(0.01)		3(0.02)
血行播散性肺结核	146(0.49)		65(0.44)		81(0.55)		67(0.45)		79(0.54)
继发性肺结核		27253(92.32)		13684(92.65)		13569(91.99)		13696(92.77)		13557(91.87)
气管支气管结核		1795(6.08)		885(5.99)		910(6.17)		877(5.94)		918(6.22)
结核性胸膜炎		93(0.32)		26(0.18)		67(0.46)		21(0.14)		72(0.49)
肺外结核		227(0.77)		107(0.73)		120(0.81)		100(0.69)		127(0.86)
是否重症^a												-2.822		0.005
是		540(1.83)		372(2.52)		168(1.14)		380(2.57)		160(1.08)
否		28979(98.17)		14397(97.48)		14582(98.86)		14383(97.43)		14596(98.92)
管理方式^a												3.110		0.002
全程督导		20457(69.30)		11474(77.69)		8983(60.90)		11531(78.11)		8926(60.49)
强化期督导		8965(30.37)		3273(22.16)		5692(38.59)		3206(21.72)		5759(39.03)
自服药		97(0.33)		22(0.15)		75(0.51)		26(0.17)		71(0.48)
合计		29519(100.00)		14769(50.03)		14750(49.97)		14763(50.01)		14756(49.99)

表1

表2

2015—2020年环境因素的统计信息

环境因素	$x ˉ$ ±s	中位数(四分位数)[M(Q₁,Q₃)]	最小值	最大值
颗粒污染物
PM_2.5	48.03±15.44	47.43(36.69,58.93)	12.61	103.35
PM₁₀	76.85±20.03	76.28(63.39,90.23)	25.03	142.22
气态污染物
CO	0.79±0.19	0.78(0.66,0.90)	0.04	1.58
NO₂	34.85±13.35	33.70(23.60,44.71)	7.65	80.75
NDVI
250m缓冲区	0.416±0.130	0.402(0.310,0.513)	0.015	0.872
500m缓冲区	0.424±0.131	0.412(0.316,0.523)	0.011	0.910

表2

图2

表3

表4

图3

图4

参考文献 27

[1]	李果, 庞先琼, 徐华, 等. 潜伏性结核感染诊治进展. 中国防痨杂志, 2021, 43 (1): 91-95. doi:10.3969/j.issn.1000-6621.2021.01.017.
[2]	蒋骏, 李云, 姜伟, 等. 肺结核密切接触者结核分枝杆菌潜伏感染情况及影响因素分析. 结核与肺部疾病杂志, 2023, 4(4): 318-322. doi:10.19983/j.issn.2096-8493.20230065.
[3]	Burusie A, Enquesilassie F, Addissie A, et al. Effect of smoking on tuberculosis treatment outcomes: A systematic review and meta-analysis. PLoS One, 2020, 15(9): e0239333. doi:10.1371/journal.pone.0239333.
[4]	Popovic I, Soares Magalhaes RJ, Ge E, et al. A systematic literature review and critical appraisal of epidemiological studies on outdoor air pollution and tuberculosis outcomes. Environ Res, 2019, 170: 33-45. doi:10.1016/j.envres.2018.12.011. pmid: 30557690
[5]	Peng Z, Liu C, Xu B, et al. Long-term exposure to ambient air pollution and mortality in a Chinese tuberculosis cohort. Sci Total Environ, 2017, 580: 1483-1488. doi:10.1016/j.scitotenv.2016.12.128.
[6]	Blount RJ, Pascopella L, Catanzaro DG, et al. Traffic-Related Air Pollution and All-Cause Mortality during Tuberculosis Treatment in California. Environ Health Perspect, 2017, 125(9): 097026. doi:10.1289/EHP1699.
[7]	杨博逸, 张一丹, 黄文忠, 等. 绿地暴露与中国人群健康关联的研究进展. 环境与职业医学, 2022, 39(1): 30-35. doi:10.11836/JEOM21402.
[8]	Chen L, Liu C, Zou R, et al. Experimental examination of effectiveness of vegetation as bio-filter of particulate matters in the urban environment. Environ Pollut, 2016, 208(Pt A): 198-208. doi:10.1016/j.envpol.2015.09.006.
[9]	Hirabayashi S, Nowak DJ. Comprehensive national database of tree effects on air quality and human health in the United States. Environ Pollut, 2016, 215: 48-57. doi:10.1016/j.envpol.2016.04.068. pmid: 27176764
[10]	Markevych I, Schoierer J, Hartig T, et al. Exploring pathways linking greenspace to health: Theoretical and methodological guidance. Environ Res, 2017, 158: 301-317. doi:10.1016/j.envres.2017.06.028. pmid: 28672128
[11]	Crouse DL, Pinault L, Balram A, et al. Urban greenness and mortality in Canada’s largest cities: a national cohort study. Lancet Planet Health, 2017, 1(7): e289 -e297. doi:10.1016/S2542-5196(17)30118-3.
[12]	Ge E, Gao J, Ren Z, et al. Greenness exposure and all-cause mortality during multi-drug resistant tuberculosis treatment: A population-based cohort study. Sci Total Environ, 2021, 771: 145422. doi:10.1016/j.scitotenv.2021.145422.
[13]	James P, Hart JE, Banay RF, et al. Exposure to Greenness and Mortality in a Nationwide Prospective Cohort Study of Women. Environ Health Perspect, 2016, 124(9): 1344-1352. doi:10.1289/ehp.1510363.
[14]	Guo B, Wu H, Pei L, et al. Study on the spatiotemporal dynamic of ground-level ozone concentrations on multiple scales across China during the blue sky protection campaign. Environ Int, 2022, 170: 107606. doi:10.1016/j.envint.2022.107606.
[15]	Zhao S, Shi A, An H, et al. Does the low-carbon city pilot contribute to the blue sky defense? Evidence from China. Environ Sci Pollut Res Int, 2023, 30(35): 84595-84608. doi:10.1007/s11356-023-28262-w.
[16]	GBD 2019 Risk Factors Collaborators. Global burden of 87 risk factors in 204 countries and territories, 1990—2019: a systematic analysis for the Global Burden of Disease Study 2019. Lancet, 2020, 396(10258): 1223-1249. doi:10.1016/S0140-6736(20)30752-2.
[17]	Liu Y, Zhao S, Li Y, et al. Effect of ambient air pollution on tuberculosis risks and mortality in Shandong, China: a multi-city modeling study of the short- and long-term effects of pollutants. Environ Sci Pollut Res Int, 2021, 28(22): 27757-27768. doi:10.1007/s11356-021-12621-6.
[18]	D’Amato G, Cecchi L, D’Amato M, et al. Urban air pollution and climate change as environmental risk factors of respira-tory allergy: an update. J Investig Allergol Clin Immunol, 2010, 20(2): 95-102;

[19]	Ibironke O, Carranza C, Sarkar S, et al. Urban Air Pollution Particulates Suppress Human T-Cell Responses to Mycobacterium Tuberculosis. Int J Environ Res Public Health, 2019, 16(21):4112. doi:10.3390/ijerph16214112.
[20]	Pompilio A, Di Bonaventura G. Ambient air pollution and respiratory bacterial infections, a troubling association: epidemiology, underlying mechanisms, and future challenges. Crit Rev Microbiol, 2020, 46(5): 600-630. doi:10.1080/1040841X.2020.1816894. pmid: 33059504
[21]	Kim H, Yu S, Choi H. Effects of particulate air pollution on tuberculosis development in seven major cities of Korea from 2010 to 2016: methodological considerations involving long-term exposure and time lag. Epidemiol Health, 2020, 42: e2020012. doi:10.4178/epih.e2020012.
[22]	Rose JJ, Wang L, Xu Q, et al. Carbon Monoxide Poisoning: Pathogenesis, Management, and Future Directions of Therapy. Am J Respir Crit Care Med, 2017, 195(5): 596-606. doi:10.1164/rccm.201606-1275CI.
[23]	Leung CC, Yew WW, Chan CK, et al. Smoking adversely affects treatment response, outcome and relapse in tuberculosis. Eur Respir J, 2015, 45(3): 738-745. doi:10.1183/09031936.00114214. pmid: 25359352
[24]	Valin N, Hejblum G, Borget I, et al. Management and treatment outcomes of tuberculous patients, eastern Paris, France, 2004. Int J Tuberc Lung Dis, 2009, 13(7): 881-887.
[25]	杨婷, 谢芳晖, 姚蓉. 老年住院肺结核患者躯体功能情况及影响因素分析. 结核与肺部疾病杂志, 2023, 4 (5): 383-390. doi:10.19983/j.issn.2096-8493.20230077.
[26]	Negin J, Abimbola S, Marais BJ. Tuberculosis among older adults-time to take notice. Int J Infect Dis, 2015, 32: 135-137. doi:10.1016/j.ijid.2014.11.018. pmid: 25809769
[27]	Huang C, Sun K, Hu J, et al. Estimating 2013— 2019 NO₂ exposure with high spatiotemporal resolution in China using an ensemble model. Environ Pollut, 2022, 292(Pt A):118285. doi:10.1016/j.envpol.2021.118285.