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Unexpectedly in the bivariate analysis we did not identify any significant associations between lifestyle variables (other than sleep) and MES in this sample.
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For bivariate analysis, we included the trait TG as well.
After bivariate analysis, we conducted a multivariable analysis.
After bivariate analysis, we conducted a multivariable analysis using forward selection techniques.
For bivariate analysis, we computed odds ratios and confidence intervals using the trend chi squared test.
In a bivariate analysis we found no significant gender differences regarding the total number of diseases.
The 3 variables in the final regression model were all statistically significant in bivariate analysis, and we do not believe they are spurious associations arising solely from an overfitted regression model.
Among men, quality of life was significantly lowest among at risk drinkers in bivariate analysis, but did not contribute to drinking pattern status when controlling for other covariates.
In this study, the association between depression and sleep disturbances was evident and significant on bivariate analysis, but did not remain significant on logistic regression analyses.
The 2004 case control study of infants with a gestational age of 33 to 35 weeks by Figueras-Aloy et al. [ 21] found an OR of 1.62 in the bivariate analysis that did not remain significant in the multivariate analysis.
A measure of disease severity, site of TB involvement (i.e. miliary/meningeal), was associated with poorer survival in bivariate analysis but did not remain so after adjustment for HIV status.
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