苏州市大气污染物暴露与肺结节进展风险的队列研究

张心悦; 陈劼; 石逸秋; 刘博; 徐瑞宁; 刘可夫; 王莉娜

doi:10.16462/j.cnki.zhjbkz.2024.02.001

苏州市大气污染物暴露与肺结节进展风险的队列研究

doi: 10.16462/j.cnki.zhjbkz.2024.02.001

1.
东南大学公共卫生学院流行病与卫生统计学系，南京 210009
2.
南京医科大学附属苏州医院放射科，南京医科大学姑苏学院，苏州市立医院，苏州 215008

基金项目:

南京医科大学姑苏学院科研项目 GSKY20210209

江苏省研究生科研与实践创新计划项目 SJCX23_0095

详细信息

通讯作者:
王莉娜，E-mail：lnwang@seu.edu.cn

中图分类号: R181.2; R122.7
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出版历程
- 收稿日期: 2023-06-24
- 修回日期: 2023-10-27
- 网络出版日期: 2024-03-30
- 刊出日期: 2024-02-10

A cohort study of air pollutant exposure with the risk of pulmonary nodules progression in Suzhou City

1.
Department of Epidemiology and Biostatistics, School of Public Health, Southeast University, Nanjing 210009, China
2.
Department of Radiology, the Affiliated Suzhou Hospital of Nanjing Medical University, Gusu School, Nanjing Medical University, Suzhou Municipal Hospital, Suzhou 215008, China

Funds:

Scientific Research Project of Gusu School in Nanjing Medical University GSKY20210209

Postgraduate Research and Practice Innovation Program of Jiangsu Province SJCX23_0095

More Information

Corresponding author: WANG Lina, E-mail: lnwang@seu.edu.cn

摘要

摘要: 目的探究常见大气污染物暴露对肺结节进展风险的影响。方法基于苏州市立医院体检肺结节阳性人群构建队列，采用环境监测站点空气污染物数据计算个体基线前一年大气污染物平均日暴露浓度。随访肺结节患者结节进展，根据Fleischner协会提出的肺结节管理指南判断结局。采用Log-rank检验比较肺结节进展率，通过Cox比例风险回归模型估计肺结节进展风险。结果共纳入785例肺结节阳性个体，在中位随访23.50个月中有354例出现肺结节进展。较高浓度的SO₂、NO₂、PM_2.5和PM₁₀暴露组人群发生肺结节进展时间相比较低浓度组更短。多因素校正后，PM_2.5(HR=1.48, 95% CI : 1.06~2.06，P＜0.01)和PM₁₀(HR=1.56, 95% CI : 1.08~2.25，P=0.02)暴露浓度最高组(Q4)肺结节进展风险高于最低组(Q1)，并且肺结节进展风险与PM₁₀暴露浓度呈正向剂量-反应关系。结论高浓度大气污染物暴露下肺结节进展速度较快且风险增加，有必要加强对高浓度大气污染物暴露下的肺结节患者的随访和管理工作。
- 肺结节 /
- 大气污染物 /
- 队列研究 /
- Cox比例风险回归模型
Abstract: Objective This study aimed to investigate the impact of exposure to common air pollutants on the risk of pulmonary nodule progression. Methods A cohort was constructed including individuals identified with pulmonary nodules from a medical examination at a hospital in Suzhou. The average daily exposure concentrations of air pollutants in the year prior to baseline were estimated using the data from environmental monitoring stations. The nodule progression and outcomes were diagnosed by the guidelines for the management of pulmonary nodules proposed by the Fleischner Society. The log-rank test was used to compare the differences in progression rates, and the Cox proportional hazards model was used to estimate the risk of pulmonary nodule progression. Results A total of 785 individuals identified with pulmonary nodules at baseline were included, and among them, 354 cases were observed with progression of pulmonary nodules during a median follow-up of 23.50 months. The individuals exposed to higher concentrations of NO₂, PM_2.5, and PM₁₀ had higher progression rates. Subjects with the highest exposure group (Q4) for PM_2.5 (HR=1.48, 95% CI: 1.06-2.06, P < 0.01) and PM₁₀ (HR=1.56, 95% CI: 1.08-2.25, P=0.02) had significantly higher risks of pulmonary nodules progression compared to that of the lowest exposure group (Q1), and there was a positive dose-response relationship between pulmonary nodules progression risks and highest level of PM₁₀ exposure. Conclusions With the increased levels of air pollutants, the risk of pulmonary nodule progression is increased. It is necessary to strengthen the follow-up management of individuals with pulmonary nodules who are expose to the high levels of air pollutants.
- Lung nodule progression /
- Air pollutants /
- Cohort study /
- Cox proportional risk regression model

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图 1 可吸入颗粒物暴露与肺结节进展的剂量反应关系

Figure 1. Dose-response relationship between respirable particulate matter exposure and progression of lung nodules

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图 2 大气污染物暴露对不同亚组人群肺结节进展的影响

Figure 2. Effect of air pollutant exposure on the progression of pulmonary nodules in different subpopulations

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表 1 研究对象基线特征

Table 1. Baseline characteristics of the study population

特征 Characteristics	肺结节进展 ^① Progression of lung nodules ^①		合计 ^① Total ^① (n=785)	W值 ^③ value	P值 value
特征 Characteristics	无 No (n=431)	有 Yes (n=354)	合计 ^① Total ^① (n=785)	W值 ^③ value	P值 value
性别 Gender				NA	0.61
男性 Male	262(60.79)	208(58.76)	470(59.87)
女性 Female	169(39.21)	146(41.24)	315(40.13)
随访时间/月 Follow-up time/months	17.22±8.15	15.89±6.41	16.62±7.44	74 488	0.64
年龄/岁 Age/years	47.05±12.78	50.38±11.89	48.55±12.49	64 138	< 0.01
体质指数/(kg·m^-2) Body mass index/(kg·m^-2)	24.36±3.60	24.58±6.50	24.46±5.12	58 605	0.95
高血压 ^② Hypertension ^②				NA	0.01
是 Yes	89(20.65)	102(28.81)	191(24.33)
否 No	320(74.25)	232(65.54)	552(70.32)
糖尿病 ^② Diabetes ^②				NA	0.30
是 Yes	23(5.35)	26(7.35)	49(6.25)
否 No	380(88.17)	303(85.59)	683(87.01)
其他肺部疾病 ^② Other lung diseases ^②				NA	0.83
是 Yes	54(14.88)	45(15.52)	99(15.16)
否 No	293(67.98)	234(66.10)	527(67.13)
吸烟 ^② Smoking ^②				NA	0.94
是 Yes	131(30.75)	109(31.05)	240(30.89)
否 No	295(68.45)	241(68.08)	536(68.28)
饮酒 ^② Alcohol intake ^②				NA	1.00
是 Yes	37(8.69)	30(8.57)	67(8.63)
否 No	390(90.49)	317(89.55)	707(90.06)
工作环境 ^② Working environment ^②				NA	0.13
室内 Interior	257(76.04)	198(81.48)	455(78.31)
室外 Outdoor	81(18.79)	45(12.71)	126(16.05)
SO₂/(μg·m^-3)	5.37±1.20	6.09±1.31	5.69±1.32	51 601	< 0.01
NO₂/(μg·m^-3)	38.23±3.50	41.11±3.42	39.53±3.75	41 085	< 0.01
O₃/(μg·m^-3)	116.53±6.52	113.51±6.49	115.16±6.67	93 023	< 0.01
CO/(mg·m^-3)	0.66±0.09	0.62±0.09	0.64±0.09	91 193	< 0.01
PM₁₀/(μg·m^-3)	53.52±4.21	56.60±4.53	54.91±4.62	43 244	< 0.01
PM_2.5/(μg·m^-3)	35.30±3.40	37.85±3.11	36.45±3.51	42 711	< 0.01
注：NA，缺乏有效值。 ①以人数(占比/%)或x±s表示；②表示该变量有缺失值；③连续型变量采用Wilcoxon检验(W值)，分类变量采用Fisher′s精确概率法检验。 Note：NA, not available. ① Number of people (proportion/%) or x±s; ② Indicates that the variable has missing values; ③ The Wilcoxon test (W-value) was used for continuous variables and the Fisher′s test for categorical variables.

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表 2 不同室外大气污染物年平均日暴露水平中位进展时间及进展率比较

Table 2. Comparison of median progression times and progression rates for different outdoor air pollutant annual mean daily exposure levels

大气污染物 Air pollutants	中位进展时间/月(95% CI) Median time to progress/months (95% CI)				Q1~Q4生存率检验 Test for difference in survival rates from Q1 to Q4
大气污染物 Air pollutants	Q1	Q2	Q3	Q4	差异检验P值 Test of difference P value	趋势检验P值 Trend test P value
SO₂	24.02(23.56~NA)	24.02(23.13~28.06)	14.03(13.83~20.27)	14.16(13.80~23.89)	0.48	0.20
NO₂	24.15(23.56~NA)	24.38(23.56~NA)	15.74(13.83~24.12)	14.16(13.83~23.13)	0.11	0.02
CO	15.74(13.83~24.11)	23.46(14.59~24.38)	20.11(13.83~23.72)	24.77(23.56~NA)	0.25	0.43
O₃	17.35(13.90~24.21)	23.52(13.90~25.13)	23.56(22.90~24.74)	23.56(21.10~24.38)	0.89	0.47
PM_2.5	24.77(23.56~NA)	24.38(23.56~NA)	14.46(13.83~24.28)	14.03(13.83~21.39)	0.05	0.01
PM₁₀	24.77(24.02~NA)	23.56(23.52~25.89)	16.10(13.90~23.89)	14.19(13.83~23.72)	0.03	0.05
注：NA，缺乏有效值。 Note：NA, not available.

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表 3 大气污染物暴露水平与肺结节进展风险关联

Table 3. Association between air pollutants exposure levels and risk of lung nodule progression

变量 Variable	模型 ^① Model^①	HR值 value (95% CI) ^②				污染物浓度每增加10 /(μg·m^-3) For each 10 increase in pollutant concentration /(μg·m^-3) HR值 value (95% CI)
变量 Variable	模型 ^① Model^①	Q1 ^③	Q2	Q3	Q4
SO₂	模型1 Model1	1.00	0.96(0.67~1.36)	1.14(0.84~1.55)	1.14(0.85~1.54)	1.50(0.66~3.39)
	模型2 Model2	1.00	1.04(0.73~1.48)	1.14(0.84~1.56)	1.21(0.89~1.63)	1.40(0.62~3.16)
	模型3 Model3	1.00	1.05(0.74~1.50)	1.14(0.83~1.56)	1.22(0.90~1.65)	1.40(0.61~3.23)
NO₂	模型1 Model1	1.00	1.37(0.92~2.03)	1.45(1.00~2.10)	1.58(1.10~2.27)	1.37(1.01~1.86)
	模型2 Model2	1.00	1.22(0.82~1.82)	1.43(0.99~2.06)	1.43(0.99~2.05)	1.29(0.95~1.75)
	模型3 Model3	1.00	1.21(0.81~1.81)	1.42(0.98~2.05)	1.42(0.99~2.05)	1.29(0.95~1.76)
CO	模型1 Model1	1.00	0.85(0.63~1.17)	1.05(0.81~1.37)	0.79(0.57~1.09)	0.10(0.98~1.01)
	模型2 Model2	1.00	0.82(0.61~1.10)	0.96(0.74~1.26)	0.78(0.56~1.08)	0.99(0.98~1.00)
	模型3 Model3	1.00	0.81(0.60~1.09)	0.95(0.72~1.24)	0.78(0.56~1.08)	0.99(0.98~1.00)
O₃	模型1 Model1	1.00	1.06(0.79~1.41)	1.11(0.84~1.47)	1.10(0.82~1.49)	1.03(0.88~1.21)
	模型2 Model2	1.00	1.09(0.82~1.45)	1.12(0.85~1.49)	1.14(1.84~1.53)	1.05(0.89~1.24)
	模型3 Model3	1.00	1.09(0.82~1.46)	1.13(0.85~1.51)	1.14(0.84~1.54)	1.05(0.89~1.24)
PM_2.5	模型1 Model1	1.00	1.05(0.72~1.53)	1.09(0.78~1.52)	1.40(1.01~1.94)	1.52(1.07~2.16)
	模型2 Model2	1.00	1.09(0.74~1.60)	1.19(0.85~1.67)	1.46(1.05~2.03)	1.55(1.10~2.20)
	模型3 Model3	1.00	1.09(0.74~1.60)	1.18(0.84~1.66)	1.48(1.06~2.06)	1.56(1.09~2.22)
PM₁₀	模型1 Model1	1.00	1.79(1.22~2.64)	1.63(1.13~2.35)	1.66(1.15~2.39)	1.35(1.07~1.69)
	模型2 Model2	1.00	1.46(0.98~2.17)	1.47(1.02~2.12)	1.58(1.10~2.27)	1.38(1.10~1.73)
	模型3 Model3	1.00	1.44(0.97~2.14)	1.48(1.03~2.14)	1.56(1.08~2.25)	1.38(1.09~1.74)
注：①模型1，未调整混杂因素；模型2，调整性别+年龄+体质指数(body mass index，BMI)；模型3，调整性别+年龄+BMI+吸烟+学历+工作环境+高血压+糖尿病+其他肺部疾病；②根据人群年均大气污染物日暴露浓度分布的四分位数由低到高，将参与者分为Q1~Q4共4组；③对照组。 Note: ① Models, unadjusted for confounders; Model 2, adjusted for sex+age+body mass index (BMI); Model 3, adjusted for sex+age+BMI+smoking+education+work environment+hypertension+diabetes+other lung diseases; ② Participants were divided into four groups from Q1 to Q4 according to the lowest to highest quartile of the distribution of annual mean daily exposure concentrations of air pollutants in the population; ③ Control group.

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