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A multiple logistic regression analysis was conducted.

†Six significant variables (p < 0.1) from the univariate analyses were included in the multiple logistic regression analysis.

cVariable was not included in the multiple logistic regression analysis.

Associated factors were identified by hierarchical multiple logistic regression analysis.

bAdjusted rates of having a sunburn in the past year are predicted marginals obtained from the multiple logistic regression analysis.

Table 3 gives the results from the multiple logistic regression analysis, estimating the effect of multiconfounders.

Odds ratios resulting from multiple logistic regression analysis comparing the occurrence of at least one hospitalization during the follow-up period in surviving patients of the same groups.

Prediction rules were derived from multiple logistic regression analysis.

OR: Odds ratio, derived from multiple logistic regression analysis.

*Adjusted odds ratio from multiple logistic regression analysis.

Table 5 shows the cumulative risk scores obtained from multiple logistic regression analysis.