Bandyopadhyay A, Dalui R, Pal S, Bhattacharjee I, Goswami B, Roy A S
Sports and Exercise Physiology Laboratory, Department of Physiology, University of Calcutta, University College of Science and Technology , Kolkata, India.
Physiol Int. 2016 Jun 1;103(2):191-201. doi: 10.1556/036.103.2016.2.6.
Rapid economic and industrial growths imposed significant impact on human health including the pulmonary health. Questions were raised regarding the validity of the existing prediction norms of pulmonary function tests (PFTs) in a particular population. The present study was conducted to investigate the applicability of the existing norms for PFTs in young healthy non-smoking female university students of Kolkata, India. Significant difference was noted in vital capacity (VC), forced vital capacity (FVC), and forced expiratory volume in 1 s (FEV) when the present data were compared with the earlier study in similar population. Correlation statistic revealed significant relationship of age and body height with all the PFT parameters. Body mass had significant correlation with VC, FVC, FEV as a percentage of FVC (FEV), and peak expiratory flow rate (PEFR). Regression equations have been computed for predicting PFTs from age and body height. There has been a change of PFTs in the studied population for the last couple of decades due to increased environmental pollution in the course of economical and industrial developments. Regression equations computed in this study are not only recommended to predict PFT parameters in the studied population, but they are also considered more reliable owing to their substantially smaller standard error of estimate than those proposed in the previous study.
快速的经济和工业增长对人类健康,包括肺部健康产生了重大影响。人们对特定人群中现有肺功能测试(PFT)预测标准的有效性提出了质疑。本研究旨在调查现有PFT标准在印度加尔各答年轻健康非吸烟女大学生中的适用性。将本研究数据与之前类似人群的研究进行比较时,发现肺活量(VC)、用力肺活量(FVC)和第1秒用力呼气量(FEV)存在显著差异。相关统计显示年龄和身高与所有PFT参数之间存在显著关系。体重与VC、FVC、FVC占比的FEV(FEV)以及呼气峰值流速(PEFR)具有显著相关性。已计算出根据年龄和身高预测PFT的回归方程。在过去几十年中,由于经济和工业发展过程中环境污染加剧,研究人群的PFT发生了变化。本研究计算出的回归方程不仅被推荐用于预测研究人群的PFT参数,而且由于其估计标准误差比之前研究中提出的标准误差小得多,因此被认为更可靠。