title: Regional differences in prediction models of lung function in Germany.
abstract: BACKGROUND
  Little is known about the influencing potential of specific characteristics on lung function in different populations. The aim of this analysis was to determine whether lung function determinants differ between subpopulations within Germany and whether prediction equations developed for one subpopulation are also adequate for another subpopulation.
  
  
  METHODS
  Within three studies (KORA C, SHIP-I, ECRHS-I) in different areas of Germany 4059 adults performed lung function tests. The available data consisted of forced expiratory volume in one second, forced vital capacity and peak expiratory flow rate. For each study multivariate regression models were developed to predict lung function and Bland-Altman plots were established to evaluate the agreement between predicted and measured values.
  
  
  RESULTS
  The final regression equations for FEV1 and FVC showed adjusted r-square values between 0.65 and 0.75, and for PEF they were between 0.46 and 0.61. In all studies gender, age, height and pack-years were significant determinants, each with a similar effect size. Regarding other predictors there were some, although not statistically significant, differences between the studies. Bland-Altman plots indicated that the regression models for each individual study adequately predict medium (i.e. normal) but not extremely high or low lung function values in the whole study population.
  
  
  CONCLUSIONS
  Simple models with gender, age and height explain a substantial part of lung function variance whereas further determinants add less than 5% to the total explained r-squared, at least for FEV1 and FVC. Thus, for different adult subpopulations of Germany one simple model for each lung function measures is still sufficient.
authors.affiliation: Helmholtz Zentrum München, Center for Environmental Health, Institute of Epidemiology, Neuherberg, Germany. schnabel@helmholtz-muenchen.de
authors.forename: Eva
authors.initials: E
authors.lastname: Schnabel
authors.forename: Chih-Mei
authors.initials: CM
authors.lastname: Chen
authors.forename: Beate
authors.initials: B
authors.lastname: Koch
authors.forename: Stefan
authors.initials: S
authors.lastname: Karrasch
authors.forename: Rudolf A
authors.initials: RA
authors.lastname: Jörres
authors.forename: Torsten
authors.initials: T
authors.lastname: Schäfer
authors.forename: Claus
authors.initials: C
authors.lastname: Vogelmeier
authors.forename: Ralf
authors.initials: R
authors.lastname: Ewert
authors.forename: Christoph
authors.initials: C
authors.lastname: Schäper
authors.forename: Henry
authors.initials: H
authors.lastname: Völzke
authors.forename: Anne
authors.initials: A
authors.lastname: Obst
authors.forename: Stephan B
authors.initials: SB
authors.lastname: Felix
authors.forename: H-Erich
authors.initials: HE
authors.lastname: Wichmann
authors.forename: Sven
authors.initials: S
authors.lastname: Gläser
authors.forename: Joachim
authors.initials: J
authors.lastname: Heinrich
mesh_terms: D000328:Adult; D000367:Age Factors; D000368:Aged; D000369:Aged, 80 and over; D001827:Body Height; D003430:Cross-Sectional Studies; D005260:Female; D005541:Forced Expiratory Volume; D005858:Germany / Q000453:epidemiology; D006801:Humans; D008168:Lung / Q000503:physiopathology*; D008171:Lung Diseases / Q000175:diagnosis* / Q000453:epidemiology / Q000503:physiopathology; D008297:Male; D008875:Middle Aged; D010366:Peak Expiratory Flow Rate; D011237:Predictive Value of Tests; D012016:Reference Values; D012044:Regression Analysis; D012111:Residence Characteristics; D012129:Respiratory Function Tests; D012737:Sex Factors; D012907:Smoking / Q000009:adverse effects; D014797:Vital Capacity; D055815:Young Adult