补呼气量、残气量、深吸气量及最大呼气流速参考值的地理分布

【作者】 王欣；

【导师】 葛淼；

【作者基本信息】 陕西师范大学 ， 环境科学， 2010， 硕士

【摘要】 目的：肺功能指标是临床诊断和预防疾病的重要参考依据,只有拥有一套准确的统一参考标准,才能更好地进行诊断和治疗,因此制定肺功能各项指标的参考值就显得尤为重要。补呼气量和深吸气量在肺功能临床应用上具有很重要的意义,若补呼气量与深吸气量明显减小,则说明存在严重阻塞性通气疾病,有可能存在胸廓扩张受限的疾病,肺组织受到严重损害等。残气量增加,则表现为小气道过早闭合等肺气肿、肺心病。最大呼气流速的测定不仅可以鉴别治疗是否有效,监测慢性哮喘、无症状哮喘、运动性哮喘和是否为肺源性或心源性的肺部疾病,还可以用来进行病情恶化的早期诊断与治疗。定量的测定研究这些肺功能指标,是临床诊断和预防疾病的重要依据,不仅可以为临床检验提供科学的参考依据,为职业病患者的肺功能损害评级提供依据,还可以指导相关医学的研究进行方法论研究。方法：本论文的创新之处是能定量的从地理环境因素着手,运用线性和非线性的方法对比研究不同年龄不同性别中国人补呼气量、深吸气量、残气量及最大呼气流速与地理环境因素的关系；运用克里格(Kringing)方法,借助ArcGIS软件中的ArcMap模块内插出中国各个地区不同年龄段的男女性健康人肺功能四项指标参考值。不少文献也报道过拉萨、西宁、江苏及海南等地的老年人、成年人及少年儿童肺功能的正常参考值,但都只是定性地描述某个地区对应的参考值与海拔或者气候有一定的关系,或者个别研究人员有限地测定了当地健康人的肺功能正常值；还有学者运用线性的方法,研究了单一因素对肺功能指标的影响,像本论文这样对肺功能四项指标正常参考值与地理因素进行专题系统的以中国整个地域环境为背景研究他们之间关系的还未见报道。结果：(1)通过向相关单位购买或者手工及网络检索大量的文献资料,收集了全国各地区的肺功能正常值,分别为：青春期男性补呼气量2729例、青春期女性补呼气量2711例、青年女性补呼气量8220例、青年男性残气量3744例、青年男性深吸气量6100例、中老年男性最大呼气峰值流速4091例和青年男性最大呼气峰值流速9661例。(2)根据国家测绘中心提供的共享资料、相关地理典著和文献,收集了全国4383个市县地区的七项地理指标：海拔高度(X1,m)、年日照时数(X2,h)、年平均气温(X3,℃)、年平均相对湿度(X4,%)、年降水量(X5,mm)、气温年较差(X6,℃)、年平均风速(X7,m／s)。(3)对肺功能四项指标与七项地理因素进行线性和非线性的分析研究,建立它们之间的多元线性回归模型,曲线估计模型和主成分分析模型。通过各个模型的对比研究,寻找出各个指标的最优预测模型,分别为：①青春期男性补呼气量参考值的主成分分析模型：Y ERV=1.658+0.00000692x1+0.0000828x2-0.00563x3-0.00409x4-0.000109x5+0.00452x6-0.0677x7②青春期女性补呼气量参考值与地理因素的曲线估计模型：Y ERV=1.662×0.964X3③青年女性补呼气量参考值与地理因素的多元线性回归模型：Y ERV=-1.930+0.00013x1+0.00043x2-0.0253x3+0.0375x4-0.075x7④青年男性残气量参考值与地理因素的多元线性回归模型：Y RV=3226.156-0.094x1-14.064x4-242.442x7⑤青年男性深吸气量参考值与地理因素的多元线性回归模型：Y IC=1.294-0.051X3+0.019X4+0.023X6⑥中老年男性最大呼气峰值流速参考值与地理因素的主成分分析模型：Y PEF=7.845-0.000355x1-0.000120x2+0.00154x3+0.00108x4-0.000130x5+0.0120x6-0.408x7⑦青年男性最大呼气峰值流速参考值与地理因素的主成分分析模型：Y PEF=7.839+0.000266x1+0.000485x2-0.0135x3-0.0193x4-0.000146x5-0.00951x6-0.119x7(4)运用预测模型和地统计分析方法,借助ArcGIS软件中的ArcMap模块,在已经矢量化好的地图上加载中国4383个地区的肺功能参考值和对应的地理属性值,通过克里格(Kringing)法插值出肺功能四项指标的参考值的空间趋势分布图。结论：通过以上的模型可以估算出整个中国各个地区不同年龄男女性的肺功能参考值,给临床检验医学和社会心理医学带来科学便捷的参考标准,并可以在分布图上清楚地看出肺功能四项指标分布趋势走向及分布规律。更多还原

【Abstract】 Objective:Pulmonary function indices are important reference for clinical diagnosis and prevention of disease, only a unified and accurate reference standard can better help to diagnosis and therapy, thus it is particularly necessary to formulate the normal reference value. Expiratory reserve volume (ERV)and inspiratory capacity (IC) have an important significance in the clinical application of pulmonary function. If expiratory reserve volume and inspiratory capacity are obviously decrease, it shows that there exists serious obstructive ventilation diseases, might cause thoracic expansion to be limited and lung tissue to be damaged seriously and so on. The increased Residual volume (RV) indicates that small airway prematurely closing, such as emphysema and cor pulmonale, etc. Determination of Peak expiratory flow (PEF) can be used to identify treatment is effectived or not, monitor chronic asthma, non-symptoms or athletic asthma and judge whether lung disease is caused by lung or heart disease, and also can be used for early diagnosis and treatment the disease deterioration. That studying these lung function indices quantitatively, is an important basis for clinical diagnosis and prevent disease. That can not only provide scientific basis for clinical testing and lung function damage rating of occupational disease patients, and also give methodology guidance for other medical research. Methods:The innovation of this paper is that, using linear and non-linear methods do research on the relationship between geographical factors and Chinese’s Expiratory reserve volume, inspiratory capacity, Residual volume, the maximum of expiratory flows in different age for different gender. Applying kriging method, with the ArcMap module of ArcGIS softwares gets the normal reference of four indices of lung function in healthy people in different age in different region of China. Although many literatures have also reported normal reference value of lung function of the elderly, adults,teenager and children in Lhasa, Xining, Jiangsu, hainan, etc, but they are only qualitative description to the relationship between the reference value and altitude or climate; some researchers have also just determinated local normal value of lung function,others only use simple linear method to study the effect of the single factor on lung function indices. By far, no paper does such systemic study on the relationship between them based on China entire geographical environment. Results:(1)Buying the material through the relevant units or retrieving by manual and network, the normal value of lung function in different region in China are collected, they are as follows:ERV of 2729 healthy adolescent boys, ERV of 2711 healthy adolesent girls, ERV of 8220 healthy younger women, RV of 3744 healthy younger men, IC of 6100 younger men, PEF of 4091 healthy middle-aged men and PEF of 9661 healthy young men in the national regions.(2) According to sharing data from the national surveying and mapping center and related geographical literatures and works, seven geographic indices in 4383 regions are obtained: altitude(X1,m), annual sunshine duration(X2,h), annual mean air temperature(X3,℃),annual mean relative humidity(X4,%),annual precipitation amount(X5,mm), annual range of air temprature(X6,℃)and annual mean wind speed(X7,m/s).(3)By the linear and nonlinear analysis for four indices of lung function with seven geographical factors, build multivariate linear regression model, curve estimation model, and principal component analysis model between them, and then compare different models of each index, choose the optimal prediction model, respectively is as follows:①Principal component analysis model of normal reference value of ERV of adolescent boys: Y ERV=1.658+0.00000692x1+0.0000828x2-0.00563x3-0.00409x4-0.000109x5+0.00452x6-0.0677x7②Curve estimation model of normal reference value of ERV of adolescent girls: YERV=1.662×0.964X3③Multivariate linear regression model of normal reference value of ERV of younger women: YERV=-1.930+0.00013x1+0.00043x2-0.0253x3+0.0375x4-0.075x7④Multivariate linear regression model of normal reference value of RV of younger men: Y RV=3226.156-0.094x1-14.064x4-242.442x7⑤Multivariate linear regression model of normal reference value of IC of younger men: Y IC=1.294-0.051x3+0.019x4+0.023x6⑥Principal component analysis model of normal reference value of PEF of middle-aged and older men: Y PEF=7.845-0.000355x1-0.000120x2+0.00154x3+0.00108x4-0.000130x5+0.0120x6-0.408x7⑦Principal component analysis model of normal reference value of PEF of younger men: Y PEF=7.839+0.000266x1+0.000485x2-0.0135x3-0.0193x4-0.000146x5-0.00951x6-0.119x7(4) According to prediction model and geostatistical analysis method, using the ArcMap module of ArcGIS softwares, loads normal reference value of lung function and attribute value of geographical factors of 4383 regions into the well-vectored map, and then applying the Kriging interpolation method to get spatial distribution map of normal reference value of lung function of four indices respectively.Conclusion:The above model can estimate the Chinese regions different age and different gender’s normal reference lung function, it can provide scientific reference standard for clinical medicine and social psychology conveniently, and also can clearly find distribution trend about four indices of lung function from the map.更多还原