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Prevalence ratios.
Binomial regression estimated adjusted prevalence ratios (PR).
The prevalence ratios were adjusted for age, smoking and job strain.
Crude prevalence ratios (PR) and prevalence differences (PD) were obtained with classical tabular methods.
*Adjusted prevalence ratios estimated using multivariable logistic regression followed by marginal standardization.
The prevalence ratios according to age groups with 95% confidence intervals were calculated.
Crude and adjusted prevalence ratios were obtained using binary regression model.
Data were analyzed using Poisson regression to obtain the crude and adjusted prevalence ratios (PRs).
Prevalence ratios and 95% confidence intervals were estimated with log binomial regression models.
Poisson regression was used to estimate prevalence ratios (PR) of injury.
Prevalence ratios of frailty and pre-frailty were explored using multivariate and univariate Poisson regression analysis with Stepwise selection criteria.
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