“men”, (total – 1300)
In women’s case those factors are notional for certain types of ban
only (see table 2):
Analysis displays that decision of supporting some bans are
connected. For example, if women and men support smoking ban in
hospitals, then they will most likely have positive response towards ban
in campuses, closed sport facilities. Similarly, how if men and women
support ban in cafes and restaurants, with the highest possibility they
will also support a ban of smoking in bars and clubs. The results can be
taken into account by the state for creating an anti-tobacco policy.
502
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