Regional differences in prediction models of lung function in Germany

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 FEV(1) 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.