Agarwal Dhiraj, Parker Richard A, Pinnock Hilary, Roy Sudipto, Ghorpade Deesha, Salvi Sundeep, Khatavkar Parag, Juvekar Sanjay
Vadu Rural Health Program, KEM Hospital Research Centre, Pune, India.
Edinburgh Clinical Trials Unit, Usher Institute, The University of Edinburgh, Edinburgh, UK.
Eur Respir J. 2020 Sep 17;56(3). doi: 10.1183/13993003.02129-2019. Print 2020 Sep.
Interpretation of spirometry involves comparing lung function parameters with predicted values to determine the presence/severity of the disease. The Global Lung Function Initiative (GLI) derived reference equations for healthy individuals aged 3-95 years from multiple populations but highlighted India as a "particular group" for whom further data are needed. We aimed to derive predictive equations for spirometry in a rural Western Indian adult population.We used spirometry data previously collected (2008-2012) from 1258 healthy adults (aged 18 years and over) by the Vadu Health and Demographic Surveillance System. We constructed sex-stratified prediction equations for forced expiratory volume in 1 s (FEV), forced vital capacity (FVC), and FEV/FVC using the Generalised Additive Model for Location, Scale and Shape (GAMLSS) method to derive the best fitting model of each outcome as a function of age and height.When compared with GLI Ethnicity Codes 1 (White Caucasian) and 5 (Other/Mixed), the Western Indian adult population appears to have lower lung volumes on average, though the FEV/FVC ratio is comparable. Both age and height were predictive of mean FEV and FVC; and for females, the variability of response was also dependent on age. FEV/FVC appears to have a very strong age effect, highlighting the limitations of using a fixed 0.7 cut-off value.The use of GLI normal values may result in overdiagnosis of lung disease in this population. We recommend that the values and equations generated from this study should be used by physicians in their routine practice for diagnosing disease and its severity in adults from the Western Indian population.
肺功能测定的解读包括将肺功能参数与预测值进行比较，以确定疾病的存在/严重程度。全球肺功能倡议（GLI）从多个群体中得出了3至95岁健康个体的参考方程，但强调印度是一个“特殊群体”，需要更多数据。我们旨在得出印度西部农村成年人群体肺功能测定的预测方程。我们使用了瓦杜健康与人口监测系统先前（2008 - 2012年）收集的1258名健康成年人（18岁及以上）的肺功能测定数据。我们使用位置、尺度和形状的广义相加模型（GAMLSS）方法构建了1秒用力呼气量（FEV）、用力肺活量（FVC）和FEV/FVC的性别分层预测方程，以得出每个结果作为年龄和身高函数的最佳拟合模型。与GLI种族代码1（白种人）和5（其他/混合）相比，印度西部成年人群体平均肺容积似乎较低，不过FEV/FVC比值相当。年龄和身高均能预测平均FEV和FVC；对于女性，反应的变异性也取决于年龄。FEV/FVC似乎有非常强的年龄效应，凸显了使用固定的0.7临界值的局限性。使用GLI正常数值可能会导致该人群中肺部疾病的过度诊断。我们建议医生在日常临床实践中使用本研究得出的数值和方程，以诊断印度西部成年人群体的疾病及其严重程度。
