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On the basis of these models, we fitted the corresponding logistic models in which the cumulative variables were replaced by the indicator variables of their quartiles.
Using cumulative variables such as 'ever smoking' or 'ever employed' may lead to misclassification given the fact that it is the cumulative, rather than the instantaneous.
The two indexes, both individually and combined (total cumulative sun exposures), were considered for the analyses, although when there was no distinct difference between leisure and holiday sun exposure, only the results for total cumulative variables are shown.
In order to identify predictors of MetS, different Cox regression models were tested in which baseline demographic and anthropometric variables were included in addition to cumulative variables related to disease activity.
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Moreover, several interactions between the DMARD groups and the cumulative variable did reach statistical significance.
In model 2 just the 'MTX, SSZ and HCQ ever' group showed a significant interaction with the cumulative variable.
We also created a cumulative variable for the number of years of the 30 year study period that the person experienced headaches, as well as treatment for headaches.
As a cumulative variable we calculated the maximum percentage of the highest prescribable dosage multiplied by the years this DMARD was used.
The relative risk for the cumulative variable for an IQR increase in ozone was found to be 1.07 (RR = 1.07; 95% CI: 1.03, 1.11).
Therefore, we determined the presence of interactions between any of the DMARD groups and the maximum used dosages, days of DMARD use and a cumulative variable.
Moreover, the untransformed cumulative exposure variables had lower AIC values than the log-transformed variables, so only the results for untransformed variables are presented.
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