Logistic regression assumes a function of the mean of the response variable is assumed to be linearly related to the explanatory variables.
Since you are not showing any complex sample design elements in the surveylogistic code why are you using surveylogistic?
Chi-square tests are for homogeneity or independence or measures of association. So your test is asking "are the variables associated", not "how does a change is one variable relate to a change in the other".
Also weight has somewhat different meaning between the two procedures.
Proc freq: If you use a WEIGHT statement, PROC FREQ assumes that an observation represents n observations, which will effectively change the sample size used for calculations.
Surveylogistic weight variable contains sampling weights, which are not the same.
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