First Affiliated Hospital of Guangzhou Medical University, Guangzhou, China
Copyright 2016, American College of Chest Physicians. All Rights Reserved.
SESSION TITLE: Pulmonary Physiology
SESSION TYPE: Original Investigation Poster
PRESENTED ON: Saturday, April 16, 2016 at 11:45 AM - 12:45 PM
PURPOSE: Although there are over 1.34 billion Chinese in the world, nationwide spirometric reference values for Chinese are unavailable. The aim of this study was to establish spirometric reference values for Chinese with a large sample.
METHODS: We enrolled healthy non-smokers in 24 centers of China from January 2007 to June 2010. Spirometry was performed according to American Thoracic Society and European Respiratory Society guidelines. Reference equations were established using the Lambda-Mu-Sigma method and compared with other published equations. Caucasian reference values adjusted with ethnic conversion factors were validated with Chinese measured spirometry data.
RESULTS: 7115 eligible individuals aged 4-80 years (50.9% females) were recruited. Reference equations against age and height by gender were established, including predicted values and lower limits of normal (LLNs). Validated with Chinese data, the percentage differences of Caucasian reference values adjusted with ethnic conversion factors were -10.2% to 1.8%, and the percentages of subjects under LLNs were 0.1% to 8.9%. Compared with previous studies, the predicted values of this study were higher than those of Hong Kong and Taiwan, and lower than those of Caucasian.
CONCLUSIONS: This study established new reference values including LLNs for Chinese with a large sample, while Caucasian references with adjustment were inappropriate for Chinese.
CLINICAL IMPLICATIONS: The new reference values could provide better interpretation of spirometry in Chinese. Spirometric reference values between different races (such as Caucasian and Chinese) might not be adjusted with fixed ethnic conversion factors for all ages.
DISCLOSURE: The following authors have nothing to disclose: Wenhua Jian, Yi Gao, Chuangli Hao, Ning Wang, Tao Ai, Chuanhe Liu, Yongjian Xu, Jian Kang, Yang Lan, Huahao Shen, Wei-jie Guan, Mei Jiang, Nanshan Zhong, Jin-ping Zheng
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