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  3. Epidemiology and Preventive Medicine / 流行病學與預防醫學研究所
  4. Predictive Equations Using Regression Analysis of Pulmonary Function for Healthy Children in Northeast China
 
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Predictive Equations Using Regression Analysis of Pulmonary Function for Healthy Children in Northeast China

Resource
PLoS One, 8(5)
Journal
PLoS ONE
Journal Volume
8
Journal Issue
5
Date Issued
2013
Author(s)
YUNG-LING LEE  
Ma, Ya-Nan
Wang, Jing
Dong, Guang-Hui
Liu, Miao-Miao
Wang, Da
Liu, Yu-Qin
Zhao, Yang
Ren, Wan-Hui
Lee, Yungling Leo
Zhao, Ya-Dong
He, Qin-Cheng
Hills, Robert K.
DOI
10.1371/journal.pone.0063875
URI
http://www.scopus.com/inward/record.url?eid=2-s2.0-84877121980&partnerID=MN8TOARS
http://scholars.lib.ntu.edu.tw/handle/123456789/382261
Abstract
Background:There have been few published studies on spirometric reference values for healthy children in China. We hypothesize that there would have been changes in lung function that would not have been precisely predicted by the existing spirometric reference equations. The objective of the study was to develop more accurate predictive equations for spirometric reference values for children aged 9 to 15 years in Northeast China.Methodology/Principal Findings:Spirometric measurements were obtained from 3,922 children, including 1,974 boys and 1,948 girls, who were randomly selected from five cities of Liaoning province, Northeast China, using the ATS (American Thoracic Society) and ERS (European Respiratory Society) standards. The data was then randomly split into a training subset containing 2078 cases and a validation subset containing 1844 cases. Predictive equations used multiple linear regression techniques with three predictor variables: height, age and weight. Model goodness of fit was examined using the coefficient of determination or the R2 and adjusted R2. The predicted values were compared with those obtained from the existing spirometric reference equations. The results showed the prediction equations using linear regression analysis performed well for most spirometric parameters. Paired t-tests were used to compare the predicted values obtained from the developed and existing spirometric reference equations based on the validation subset. The t-test for males was not statistically significant (p>0.01). The predictive accuracy of the developed equations was higher than the existing equations and the predictive ability of the model was also validated.Conclusion/Significance:We developed prediction equations using linear regression analysis of spirometric parameters for children aged 9-15 years in Northeast China. These equations represent the first attempt at predicting lung function for Chinese children following the ATS/ERS Task Force 2005 guidelines on spirometry standardization. ? 2013 Ma et al.
SDGs

[SDGs]SDG3

Other Subjects
accuracy; adolescent; age; allergic rhinitis; article; asthma; body height; body weight; bronchitis; bronchus mucus; child; China; controlled study; coughing; cross-sectional study; diagnostic test accuracy study; female; forced expiratory volume; forced vital capacity; human; lung function; major clinical study; male; mathematical parameters; maximal mid expiratory flow; multiple linear regression analysis; peak expiratory flow; pneumonia; predictive equation; predictive value; predictor variable; reference value; school child; spirometry; validation study; wheezing; Adolescent; Child; China; Demography; Female; Health; Humans; Linear Models; Lung; Male; Reproducibility of Results; Respiratory Function Tests
Type
journal article
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