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目的了解驾驶员肺功能临床特点,将肺功能减退筛查的预防工作关口前移。方法以2014年8月至2015年4月在我院健康体检的546名驾驶员为调查对象,采用简单随机抽样的直抽样法抽取100名无呼吸道症状男性驾驶员进行肺功能检查。结合吸烟史、年龄和体质指数(BMI)进行分析,应用SPSS 17.0软件进行统计学处理,肺功能指标与吸烟、年龄、驾龄和BMI的相关性用多元logistic回归分析,采用逐步回归法stepwise选项,进行各分类组间比较。结果 100名男驾驶员中有肺功能障碍15例(15%),以轻度阻塞性通气功能障碍为主(11例,占11%)。吸烟者较不吸烟者、40岁以上较40岁以下的驾驶员肺通气各项指标均降低;肺活量(VC)随BMI的增加而增加,BMI为18~24 kg/m2者以用力肺活量(FVC)/预计值、75%肺活量最大呼气流量(PEF75)/预计值均值最高,BMI为25~28 kg/m2者以第1秒用力呼气容积(FEV1)/FVC、PEF25/预计值、PEF50/预计值均值最高,BMI>28 kg/m2者,除VC均值最高外,其余指标均值都处于最低水平。吸烟量越大,肺功能各指标越低;戒烟后肺功能各指标有所改善,并且随戒烟时间延长,肺功能各指标上升明显。多因素logistic回归分析结果显示,年龄、驾龄、BMI、吸烟与否、吸烟量和戒烟情况是肺功能的影响因素。结论通过肺功能的检测可早期发现病例,提倡把肺功能检查纳入健康体检中,以提高人们对疾病早期的认识,减少慢性阻塞性肺疾病的发病率,具有重大的临床应用价值。
Objective To understand the clinical features of the driver’s lung function, the screening of lung function prevention work advancement. Methods A total of 546 pilots in our hospital from August 2014 to April 2015 were enrolled in this study. 100 randomly selected male drivers without respiratory symptoms were enrolled in this study. Combined with smoking history, age and body mass index (BMI) analysis, SPSS 17.0 software was used for statistical analysis. The correlation between lung function indexes and smoking, age, driving experience and BMI was analyzed by multivariate logistic regression, stepwise regression stepwise method, The comparison between the various groups. Results Among 100 male drivers, 15 (15%) had pulmonary dysfunction, with mild obstructive ventilatory dysfunction (11 cases, 11%). Lung smokers were less smokers, drivers over the age of 40 and 40 years of age were lower lung ventilation indicators were reduced; vital capacity (VC) increased with the increase of BMI, BMI 18 ~ 24 kg / m2 were forced vital capacity (FVC ) / Predicted, PEF 75 / predicted average, BMI 25 to 28 kg / m 2 at FEV 1 / FVC, PEF 25 / predicted, PEF 50 / The highest average expected value, BMI> 28 kg / m2, in addition to the highest average VC, the other indicators are at the lowest level. The greater the amount of smoking, the lower the index of lung function; after smoking cessation improved each index of pulmonary function, and with the extension of smoking cessation, various indexes of pulmonary function increased significantly. Multivariate logistic regression analysis showed that age, driving experience, BMI, smoking or not, smoking and smoking cessation were the influencing factors of pulmonary function. Conclusion The detection of pulmonary function can detect cases early and advocate the incorporation of pulmonary function tests into healthy physical examination to improve people’s awareness of the disease early and reduce the incidence of chronic obstructive pulmonary disease, which has great clinical value.