There is no question that awfact (a generic term for awfactt, etc.) is a random variable, and when the weight is multiplied by awfact/100, the product has a substantial random component, especially for women under age 24. The all-woman factor is calculated for a single year of age, such as age 15, as the number of women (girls?) in the household population who are age 15 divided by the number at that age who are ever-married. Thus awfact is a random variable and it has an associated sampling error. However, I recommend that you simply proceed with using the net weight as if it had no random component.

But what do you mean by "confidence intervals for cross tabulations"? A cross-tab is a table of frequencies from the sample, for example the number of cases in the sample in each combination of current age group and current contraceptive method. You should use weights for those frequencies. Then you can calculate percentages, measures of association, etc., all of which could have a confidence interval. Please clarify what you mean by that term.

Here is an example using the latest Egypt survey, with was an EMW survey.

set more off
use e:\DHS\DHS_data\IR_files\EGIR61FL.dta, clear

* what is the proportion of women age 20+ who had a birth before age 20?
* age at first birth is v212
* must restrict to women age 20+; say we restrict to current age 20-24

keep if v013==2
tab v212

gen teen_birth=0
replace teen_birth=1 if v212<20

gen wtt=v005*awfactt/100
svyset v021 [pweight=wtt], strata(v022)
svy: prop teen_birth 

* repeat for wealth categories; must use awfactw rather than awfactt
gen wtw=v005*awfactw/100
svyset v021 [pweight=wtw], strata(v022)
svy: prop teen_birth, over(v190)