title: Reference values for spirometry - report from the Obstructive Lung Disease in Northern Sweden studies.
abstract: BACKGROUND
  Abnormal lung function is commonly identified by comparing observed spirometric values to corresponding reference values. It is recommended that such reference values for spirometry are evaluated and updated frequently. The aim of this study was to estimate new reference values for Swedish adults by fitting a multivariable regression model to a healthy non-smoking general population sample from northern Sweden. Further aims were to evaluate the external validity of the obtained reference values on a contemporary sample from south-western Sweden, and to compare them to the Global Lung Function Initiative (GLI) reference values.
  
  
  METHODS
  Sex-specific multivariable linear regression models were fitted to the spirometric data of n=501 healthy non-smoking adults aged 22-91 years, with age and height as predictors. The models were extended to allow the scatter around the outcome variable to depend on age, and age-dependent spline functions were incorporated into the models to provide a smooth fit over the entire age range. Mean values and lower limits of normal, defined as the lower 5th percentiles, were derived.
  
  
  RESULTS
  This modelling approach resulted in unbiased estimates of the spirometric outcomes, and the obtained estimates were appropriate not only for the northern Sweden sample but also for the south-western Sweden sample. On average, the GLI reference values for forced expiratory volume in one second (FEV1) and, in particular, forced expiratory vital capacity (FVC) were lower than both the observed values and the new reference values, but higher for the FEV1/FVC ratio.
  
  
  CONCLUSIONS
  The evaluation based on the sample of healthy non-smokers from northern Sweden show that the Obstructive Lung Disease in Northern Sweden reference values are valid. Furthermore, the evaluation based on the south-western Sweden sample indicates a high external validity. The comparison with GLI brought further evidence to the consensus that, when available, appropriate local population-specific reference values may be preferred.
authors.affiliation: The OLIN Unit, Division of Occupational and Environmental Medicine, Department of Public Health and Clinical Medicine, Umeå University, Umeå, Sweden.
authors.forename: Helena
authors.initials: H
authors.lastname: Backman
authors.affiliation: Division of Medicine, Department of Public Health and Clinical Medicine, Umeå University, Umeå, Sweden.
authors.forename: Anne
authors.initials: A
authors.lastname: Lindberg
authors.affiliation: Division of Mathematical Sciences, Chalmers University of Technology, Gothenburg, Sweden.
authors.forename: Anders
authors.initials: A
authors.lastname: Odén
authors.affiliation: Krefting Research Centre, Institute of Medicine, University of Gothenburg, Gothenburg, Sweden.
authors.forename: Linda
authors.initials: L
authors.lastname: Ekerljung
authors.affiliation: The OLIN Unit, Division of Occupational and Environmental Medicine, Department of Public Health and Clinical Medicine, Umeå University, Umeå, Sweden.
authors.forename: Linnéa
authors.initials: L
authors.lastname: Hedman
authors.affiliation: HUCH Heart and Lung Center, Peijas Hospital, Helsinki University Central Hospital, Helsinki, Finland.
authors.forename: Annette
authors.initials: A
authors.lastname: Kainu
authors.affiliation: HUS Medical Imaging Centre, Department of Clinical Physiology and Nuclear Medicine, Helsinki University Central Hospital, Helsinki, Finland.
authors.forename: Anssi
authors.initials: A
authors.lastname: Sovijärvi
authors.affiliation: The OLIN Unit, Division of Occupational and Environmental Medicine, Department of Public Health and Clinical Medicine, Umeå University, Umeå, Sweden ; Krefting Research Centre, Institute of Medicine, University of Gothenburg, Gothenburg, Sweden.
authors.forename: Bo
authors.initials: B
authors.lastname: Lundbäck
authors.affiliation: The OLIN Unit, Division of Occupational and Environmental Medicine, Department of Public Health and Clinical Medicine, Umeå University, Umeå, Sweden.
authors.forename: Eva
authors.initials: E
authors.lastname: Rönmark
keywords: Z-scores; linear regression; percentiles; reference equations; reference sample; spline functions