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中华肺部疾病杂志(电子版) ›› 2023, Vol. 16 ›› Issue (03) : 312 -317. doi: 10.3877/cma.j.issn.1674-6902.2023.03.003

论著

陕西省成人慢性阻塞性肺疾病危险因素及预测模型
张译梵, 张海华, 王瑛, 高贵洲, 王晓东, 屈林, 张涛()   
  1. 710032 陕西,空军军医大学第二附属医院胸腔外科
    710032 陕西,空军军医大学第二附属医院呼吸内科
  • 收稿日期:2023-02-05 出版日期:2023-06-25
  • 通信作者: 张涛
  • 基金资助:
    陕西省重点产业创新链(2023-ZDLSF-51)

Analysis and predictive model of adult chronic obstructive pulmonary disease in Shaanxi Province

Yifan Zhang, Haihua Zhang, Ying Wang, Guizhou Gao, Xiaodong Wang, Lin Qu, Tao Zhang()   

  1. Department of Thoracic Surgery, Tangdu Hospital, Fourth Military Medical University, 710032 Xi′an, China
    Department of Respiratory Medicine, Tangdu Hospital, Fourth Military Medical University, 710032 Xi′an, China
  • Received:2023-02-05 Published:2023-06-25
  • Corresponding author: Tao Zhang
引用本文:

张译梵, 张海华, 王瑛, 高贵洲, 王晓东, 屈林, 张涛. 陕西省成人慢性阻塞性肺疾病危险因素及预测模型[J]. 中华肺部疾病杂志(电子版), 2023, 16(03): 312-317.

Yifan Zhang, Haihua Zhang, Ying Wang, Guizhou Gao, Xiaodong Wang, Lin Qu, Tao Zhang. Analysis and predictive model of adult chronic obstructive pulmonary disease in Shaanxi Province[J]. Chinese Journal of Lung Diseases(Electronic Edition), 2023, 16(03): 312-317.

目的

分析陕西省成人慢性阻塞性肺疾病(chronic obstructive pulmonary disease, COPD)的危险因素,建立预测模型,为陕西省开展COPD综合防控工作提供参考依据。

方法

选择2021年6月至2021年12月空军军医大学第二附属医院肺功能室检查的1 160例患者为对象,COPD患者580例为观察组,健康者580例为对照组,两组完成相关问卷,比较单因素后对相关因素行多因素分析,建立列线图预测模型。

结果

COPD危险因素是高龄(OR=9.908,95%CI:2.937~33.422)、吸烟史(OR=2.074,95%CI:1.605~2.681) 、职业粉尘接触史(OR=1.934,95%CI:1.308~2.859)、家族呼吸道疾病史(OR=1.856,95%CI:1.303~2.643)、儿童时期呼吸道病史(OR=1.804,95%CI: 1.284~2.534)、生物质燃料使用史(OR=1.469,95%CI:1.048~2.061)。COPD风险预测模型AUC值为0.739;校准曲线Y与X直线相近;绘制决策曲线在阈值0.0~1.0范围内。吸烟年限与日吸烟量与COPD存在剂量-反应相关性,戒烟1年以上可以少量减少COPD风险。

结论

COPD危险因素是高龄、吸烟史、职业粉尘接触史、家族呼吸道疾病史、儿童时期呼吸道病史、生物质燃料使用史,应采取相关措施预防COPD,根据上述因素建立的COPD风险预测模型具有临床意义。

Objective

To analyze the risk factors that lead to chronic obstructive pulmonary disease and establish a relevant prediction model to provide a reference for the comprehensive prevention and control of chronic obstructive pulmonary disease in Shaanxi Province.

Methods

A total of 1 160 patients who underwent pulmonary function examination in the Second Affiliated Hospital of Air Force Medical University from June 2021 to December 2021 were selected as subjects, including 580 patients with chronic obstructive pulmonary disease (observation group)and 580 control groups, requiring them to complete the relevant questionnaire. After comparing the single factors, it was analyzed that the relevant factors and established a column to establish a column. The nomogram predicts the model.

Results

The risk factors of chronic obstructive pulmonary disease are the age (OR=9.908, 95%CI: 2.937-33.422), the history of smoking (OR= 2.074, 95%CI: 1.605-2.681), and the history of occupational dust contact (OR=1.934, 95%CI: 1.308-2.859), the history of family respiratory disease (OR=1.856, 95%CI: 1.303-2.643), the history of respiratory tract medical period (OR=1.804, 95%CI: 1.284-2.534), and the history of biomass fuel (OR=1.469, 95%CI: 1.048-2.061). According to the chronic obstructive pulmonary risk prediction model constructed by risk factors, the AUC value is 0.739; the calibration curve Y and X are similar; the decision-making curve is within the range of 0.0-1.0. The smoking period and daily smoking volume and chronic obstructive pulmonary disease have dosage-reaction correlation and can reduce the risk of chronic obstructive pulmonary disease for more than 1 year.

Conclusions

The risk factors of patients with chronic obstructive pulmonary disease are the history of age, the history of smoking, the history of occupational dust contact, the history of family respiratory diseases, the history of the respiratory tract disease, and the history of biomass fuel. Chronic obstructive pulmonary risk prediction model has certain predictive value.

表1 COPD危险因素单因素分析[n(%)]
临床资料 总计(n=1 160) 观察组(n=580) 对照组(n=580) P
性别       0.000
620(53.4) 358(61.7) 262(45.2)  
540(46.6) 222(38.3) 318(54.8)  
教育情况       0.000
初中及以下 632(54.5) 337(58.1) 295(50.9)  
高中及中专 216(18.6) 119(20.5) 97(16.7)  
本科及以上 312(26.9) 124(21.4) 188(32.4)  
粉尘接触史       0.000
1 015(87.5) 484(83.4) 531(91.6)  
145(12.5) 96(16.6) 49(8.4)  
儿童时期呼吸道病史       0.000
957(82.5) 446(76.9) 511(88.1)  
203(17.5) 134(23.1) 69(11.9)  
生物质燃料       0.000
962(82.9) 457(78.8) 505(87.1)  
198(17.1) 123(21.2) 75(12.9)  
吸烟史       0.000
691(59.6) 285(49.1) 406(70.0)  
469(40.4) 295(50.9) 174(30.0)  
被动吸烟史       0.000
838(72.2) 453(78.1) 385(66.4)  
322(27.8) 127(21.9) 195(33.6)  
家族呼吸道病史       0.000
975(84.1) 461(79.5) 514(88.6)  
185(15.9) 119(20.5) 66(11.4)  
饮酒习惯       0.002
从不 977(84.2) 486(83.8) 491(84.7)  
偶尔 31(2.7) 7(1.2) 24(4.1)  
经常 152(13.1) 87(15.0) 65(11.2)  
高血压史       0.007
908(78.3) 435(75.0) 473(81.6)  
252(21.7) 145(25.0) 107(18.4)  
饮用绿茶习惯       0.019
从不 854(73.6) 423(72.9) 431(74.3)  
偶尔 98(8.4) 39(6.7) 59(10.2)  
经常 208(17.9) 118(20.3) 90(15.5)  
宠物饲养史       0.053
957(82.5) 466(80.3) 491(84.7)  
203(17.5) 114(19.7) 89(15.3)  
运动习惯       0.058
662(57.1) 315(54.3) 347(59.8)  
498(42.9) 265(45.7) 233(40.2)  
糖尿病史       0.678
1 058(91.2) 527(90.9) 531(91.6)  
102(8.8) 53(9.1) 49(8.4)  
BMI(kg/m2)       0.695
<18.5 41(3.5) 20(4.0) 21(3.3)  
18.5~24.9 514(44.3) 217(43.6) 297(44.9)  
>25 604(52.1) 261(52.4) 343(51.9)  
表2 COPD危险因素多因素分析
图1 COPD风险预测模型列线图
图2 COPD风险预测模型DCA曲线(训练集)
图3 COPD患者风险预测模型DCA曲线(验证集)
图4 吸烟习惯及戒烟情况与COPD风险森林图
1
任成山,王关嵩,钱桂生. 慢性阻塞性肺疾病的成因及其治疗的困惑与希望[J/CD].中华肺部疾病杂志(电子版), 2019, 12(2): 127-141.
2
Wang C, Xu J, Yang L, et al. Prevalence and risk factors of chronic obstructive pulmonary disease in China (the China Pulmonary Health[CPH] study): a national cross-sectional study[J]. Lancet, 2018, 391(10131): 1706-1717.
3
中华医学会呼吸病学分会慢性阻塞性肺疾病学组,中国医师协会呼吸医师分会慢性阻塞性肺疾病工作委员会.慢性阻塞性肺疾病诊治指南(2021年修订版)[J]. 中华结核和呼吸杂志2021, 44(3): 170-205.
4
Vogelmeier CF, Criner GJ, Martínez FJ, et al. Global strategy for the diagnosis, management, and prevention of chronic obstructive lung disease 2017 report: GOLD executive summary[J]. Arch Bronconeumol, 2017, 53(3): 128-149.
5
Zhao X, Du C. Effect of smoking status on spirometric lung age in adult Chinese Men[J]. Health Soc Care Community, 2022, 30 (4): 1384-1390.
6
肺功能检查指南-肺容量检查[C]. 第八届东北地区呼吸疾病学术会议暨吉林省医学会呼吸病学分会第十三次学术会议论文集,2016: 105-110.
7
Jensen RL, Teeter JG, England RD, et al. Instrument accuracy and reproducibility in measurements of pulmonary function[J]. Chest, 2007, 132(2): 388-395.
8
Miller MR, Hankinson J, Brusasco V, et al. Standardisation of spirometry[J]. Eur Respir J, 2005, 26(2): 319-338.
9
Global, regional, and national deaths, prevalence, disability-adjusted life years, and years lived with disability for chronic obstructive pulmonary disease and asthma, 1990-2015: a systematic analysis for the Global Burden of Disease Study 2015[J]. Lancet Respir Med, 2017, 5(9): 691-706.
10
Skloot GS.The effects of aging on lung structure and function[J].Clin Geriatr Med, 2017, 33(4): 447-457.
11
Brandsma CA, De Vries M, Costa R, et al. Lung ageing and COPD: is there a role for ageing in abnormal tissue repair?[J]. Eur Respir Rev, 2017, 26(146):170073.
12
Wang M, Luo X, Xu S, et al. Trends in smoking prevalence and implication for chronic diseases in China: serial national cross-sectional surveys from 2003 to 2013[J]. Lancet Respir Med, 2019, 7(1): 35-45.
13
Vij N, Chandramani-Shivalingappa P, Van Westphal C, et al. Cigarette smoke-induced autophagy impairment accelerates lung aging, COPD-emphysema exacerbations and pathogenesis[J]. Am J Physiol Cell Physiol, 2018, 314(1): C73-C87.
14
Walters MS, De BP, Salit J, et al. Smoking accelerates aging of the small airway epithelium[J]. Respir Res, 2014, 15(1): 94.
15
Xiao D, Chen Z, Wu S, et al. Prevalence and risk factors of small airway dysfunction, and association with smoking, in China: findings from a national cross-sectional study[J].Lancet Respir Med, 2020, 8(11): 1081-1093.
16
Verbanck S, Schuermans D, Paiva M, et al. Small airway function improvement after smoking cessation in smokers without airway obstruction[J]. Am J Respir Crit Care Med, 2006, 174(8): 853-857.
17
Chang JT, Meza R, Levy DT, et al. Prediction of COPD risk accounting for time-varying smoking exposures[J]. PLoS One, 2021, 16(3): e0248535.
18
Aldrich TK, Weakley J, Dhar S, et al. Bronchial reactivity and lung function after world trade center exposure[J]. Chest, 2016, 150(6): 1333-1340.
19
Sunil VR, Vayas KN, Fang M, et al. World Trade Center (WTC) dust exposure in mice is associated with inflammation, oxidative stress and epigenetic changes in the lung[J]. Exp Mol Pathol, 2017, 102(1): 50-58.
20
郭薇薇,刘美霞,杨 凤,等. 2019年上海市小微型企业粉尘接触工人尘肺病主动监护结果分析[J]. 环境与职业医学2021, 38(8): 877-882.
21
黄 真,张炳旭. 2019年天津市滨海新区粉尘作业人员职业健康结果分析[J]. 公共卫生与预防医学2021, 32(6): 142-145.
22
薛来俊,李 军,卢建国,等. 陶瓷粉尘暴露对作业人员呼吸系统的影响[J]. 中国工业医学杂志2021, 34(4): 351-352.
23
Hersh CP, Hokanson JE, Lynch DA, et al. Family history is a risk factor for COPD[J]. Chest, 2011, 140(2): 343-350.
24
Okyere DO, Bui DS, Washko GR, et al. Predictors of lung function trajectories in population-based studies: A systematic review[J]. Respirology, 2021, 26(10): 938-959.
25
Zhang D, Newton CA. Familial Pulmonary Fibrosis: Genetic Features and Clinical Implications[J]. Chest, 2021, 160(5): 1764-1773.
26
Sheikh SI, Pitts J, Ryan-Wenger NA, et al. Environmental exposures and family history of asthma[J]. J Asthma, 2016, 53(5): 465-470.
27
Belgrave DCM, Granell R, Turner SW, et al. Lung function trajectories from pre-school age to adulthood and their associations with early life factors: a retrospective analysis of three population-based birth cohort studies[J]. Lancet Respir Med, 2018, 6(7): 526-534.
28
Miura S, Iwamoto H, Omori K, et al. Accelerated decline in lung function in adults with a history of remitted childhood asthma[J]. Eur Respir J, 2022, 59(1): 2100305.
29
Hayden LP, Cho MH, Raby BA, et al. Childhood asthma is associated with COPD and known asthma variants in COPDGene: a genome-wide association study[J]. Respir Res, 2018, 19(1): 209.
30
Adeloye D, Song P, Zhu Y, et al. Global, regional, and national prevalence of, and risk factors for, chronic obstructive pulmonary disease (COPD) in 2019: a systematic review and modelling analysis[J]. Lancet Respir Med, 2022, 10(5): 447-458.
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