Background: In observational studies, imbalanced background characteristics hamper addressing
causal questions, because a randomisation is usually not feasible for ethical and
practical reasons. The Propensity score (PS) method reduces the measured background
characteristics to a single composite characteristic and therefore enables a straightforward
assessment. The present analysis aimed to compare the estimation by means of PS with
a previous assessment of shift systems and their effects on the employee's health
using conventional regression models. Materials and Methods: Two different shift schedules (3×12 and 4×12) were compared with a daytime working
system to investigate potential differenzial effects on the employee's health status
assessed with the Work Ability Index (WAI). A total of 924 participants (278 3×12,
321 4×12 shift workers, and 325 day workers) were recruited for the study. The outcomes
of interest were the WAI sum score and its dimensions, dichotomized at the medians.
PS was defined as the probability of being exposed in any of the two working time
schedules, as a function of the individuals' background characteristics. A logistic
regression model was used to estimate PS for each subject. Stratified comparisons
were then made using Mantel-Haenszel test. Results: Age, BMI, living alone, smoking status, and the number of children represented major
imbalances between the groups. Based on the PS, no significant differences in terms
of WAI and its individual dimensions were found in either of the pair comparisons.
The results were consistent with those found with the model-based analyses. Discussion: The PS method is considered especially advantageous in comparisons of more than two
groups, in case of different underlying heterogeneities between the pairs. Although
such heterogeneity exists in the present dataset, the outcomes across both analyses
were comparable. Nevertheless, the PS method can only adjust for measured confounders
and will never overcome its a posteriori nature in terms of assignment of exposure.
