A comparison of longitudinal statistical methods in studies of pulmonary function decline
Creators: name: Dimich-Ward, Helen D.
Publisher: name: University of British Columbia
Year: 2011

description: Three longitudinal pulmonary function data sets were analyzed by several statistical methods for the purposes of: 1) determining to what degree the conclusions of an analysis for a given data set are method dependent; 2) assessing the properties of each method across the different data sets; 3) studying the correlates of FEV₁ decline including physical, behavioral, and respiratory factors, as well as city of residence and type of work. 4) assessing the appropriateness of modelling the standard linear relationship of FEV₁ with time and providing alternative approaches; 5) describing longitudinal change in various lung function variables, apart from FEV₁. The three data sets were comprised of (1) yearly data on 141 veterans with mild chronic bronchitis, taken at three Canadian centres, for a maximum of 23 years of follow-up; their mean age at the start of the study was 49 years (s.d.=9) and only 10.6% were nonsmokers during the follow-up; (2) retrospective data on 384 coal workers categorized into four groups according to vital status (dead or alive) and smoking behavior, with irregular follow-up intervals ranging from 2 to 12 measurements per individual over a period of 9 to 30 years; (3) a relatively balanced data set on 269 grain workers and a control group of 58 civic workers, which consisted of 3 to 4 measurements taken over an average follow-up of 9 years. Their mean age at first measurement was 37 years (s.d.=10) and 53.2% of the subjects did not smoke. A review of the pulmonary and statistical literature was carried out to identify methods of analysis which had been applied to calculate annual change in FEV₁. Five methods chosen for the data analyses were variants of ordinary least squares approaches. The other four methods were based on the use of transformations, weighted least squares, or covariance structure models using generalized least squares approaches. For the coal workers, the groups that were alive at the time of ascertainment had significantly smaller average FEV₁ declines than the deceased groups. Post-retirement decline in FEV₁ was shown by one statistical method to significantly increase for coal workers who smoked, while a significant decrease was observed for nonsmokers. Veterans from Winnipeg consistently showed the lowest decline estimates in comparison to Halifax and Toronto; recorded air pollution measurements were found to be the lowest for Winnipeg, while no significant differences in smoking behavior were found between the veterans of each city. The data set of grain workers proved most ameniable to all the different analytical techniques, which were consistent in showing no significant differences in FEV₁ decline between the grain and civic workers groups and the lowest magnitude of FEV₁ decline. It was shown that quadratic and allometric analyses provided additional information to the linear description of FEV₁ decline, particularly for the study of pulmonary decline among older or exposed populations over an extended period of time. Whether the various initial lung function variables were each predictive of later decline was dependent on whether absolute or percentage decline was evaluated. The pattern of change in these lung function measures over time showed group differences suggestive of different physiological responses. Although estimates of FEV₁ decline were similar between the various methods, the magnitude and relative order of the different groups and the statistical significance of the observed inter-group comparisons were method-dependent No single method was optimal for analysis of all three data sets. The reliance on only one model, and one type of lung function measurement to describe the data, as is commonly found in the pulmonary literature, could lead to a false interpretation of the result Thus a comparative approach, using more than one justifiable model for analysis is recommended, especially in the usual circumstances where missing data or irregular follow-up times create imbalance in the longitudinal data set.