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KDHS 2022 : Table 11.13.1 Nutritional status of women age 2049 [message #28293] |
Sun, 10 December 2023 03:43 |
sokiya
Messages: 78 Registered: May 2017 Location: Nairobi
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Senior Member |
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I am trying to replicate Table 11.13.1 Nutritional status of women age 2049 using the code below that I extracted from the DHS GitHub repo
use "KEIR8AFL.dta", clear
cap label define yesno 0"No" 1"Yes"
gen wt=v005/1000000
*** Anemia indicators ***
//Any anemia
gen nt_wm_any_anem=0 if v042==1 & v455==0
replace nt_wm_any_anem=1 if v457<4
label values nt_wm_any_anem yesno
label var nt_wm_any_anem "Any anemia - women"
//Mild anemia
gen nt_wm_mild_anem=0 if v042==1 & v455==0
replace nt_wm_mild_anem=1 if v457==3
label values nt_wm_mild_anem yesno
label var nt_wm_mild_anem "Mild anemia - women"
//Moderate anemia
gen nt_wm_mod_anem=0 if v042==1 & v455==0
replace nt_wm_mod_anem=1 if v457==2
label values nt_wm_mod_anem yesno
label var nt_wm_mod_anem "Moderate anemia - women"
//Severe anemia
gen nt_wm_sev_anem=0 if v042==1 & v455==0
replace nt_wm_sev_anem=1 if v457==1
label values nt_wm_sev_anem yesno
label var nt_wm_sev_anem "Severe anemia - women"
*** Anthropometry indicators ***
* age of most recent child
gen age = v008 - b3_01
* to check if survey has b19, which should be used instead to compute age.
scalar b19_included=1
capture confirm numeric variable b19_01, exact
if _rc>0 {
* b19 is not present
scalar b19_included=0
}
if _rc==0 {
* b19 is present; check for values
summarize b19_01
if r(sd)==0 | r(sd)==. {
scalar b19_included=0
}
}
if b19_included==1 {
drop age
gen age=b19_01
}
//Height less than 145cm
gen nt_wm_ht= v438<1450 if inrange(v438,1300,2200)
label values nt_wm_ht yesno
label var nt_wm_ht "Height under 145cm - women"
//Mean BMI
gen bmi=v445/100
summarize bmi if inrange(bmi,12,60) & (v213!=1 & (v208==0 | age>=2)) [iw=wt]
gen nt_wm_bmi_mean=round(r(mean),0.1)
label var nt_wm_bmi_mean "Mean BMI - women"
//Normal weight
gen nt_wm_norm= inrange(v445,1850,2499) if inrange(v445,1200,6000)
replace nt_wm_norm=. if (v213==1 | age<2)
label values nt_wm_norm yesno
label var nt_wm_norm "Normal BMI - women"
//Thin
gen nt_wm_thin= inrange(v445,1200,1849) if inrange(v445,1200,6000)
replace nt_wm_thin=. if (v213==1 | age<2)
label values nt_wm_thin yesno
label var nt_wm_thin "Thin BMI - women"
//Mildly thin
gen nt_wm_mthin= inrange(v445,1700,1849) if inrange(v445,1200,6000)
replace nt_wm_mthin=. if (v213==1 | age<2)
label values nt_wm_mthin yesno
label var nt_wm_mthin "Mildly thin BMI - women"
//Moderately and severely thin
gen nt_wm_modsevthin= inrange(v445,1200,1699) if inrange(v445,1200,6000)
replace nt_wm_modsevthin=. if (v213==1 | age<2)
label values nt_wm_modsevthin yesno
label var nt_wm_modsevthin "Moderately and severely thin BMI - women"
//Overweight or obese
gen nt_wm_ovobese= inrange(v445,2500,6000) if inrange(v445,1200,6000)
replace nt_wm_ovobese=. if (v213==1 | age<2)
label values nt_wm_ovobese yesno
label var nt_wm_ovobese "Overweight or obese BMI - women"
//Overweight
gen nt_wm_ovwt= inrange(v445,2500,2999) if inrange(v445,1200,6000)
replace nt_wm_ovwt=. if (v213==1 | age<2)
label values nt_wm_ovwt yesno
label var nt_wm_ovwt "Overweight BMI - women"
//Obese
gen nt_wm_obese= inrange(v445,3000,6000) if inrange(v445,1200,6000)
replace nt_wm_obese=. if (v213==1 | age<2)
label values nt_wm_obese yesno
label var nt_wm_obese "Obese BMI - women"
tabstat nt_wm_ht nt_wm_bmi_mean nt_wm_norm nt_wm_thin nt_wm_mthin nt_wm_modsevthin nt_wm_ovobese nt_wm_ovwt nt_wm_obese [fw=wt] if inrange(age, 20, 49) & sshort == 0, statistics(mean) save
but the results are not matching. Any help will be appreciated.
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Re: KDHS 2022 : Table 11.13.1 Nutritional status of women age 2049 [message #28327 is a reply to message #28293] |
Thu, 14 December 2023 13:56 |
Bridgette-DHS
Messages: 3199 Registered: February 2013
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Senior Member |
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Following is a response from Senior DHS staff member, Tom Pullum:
The following Stata lines will match table 11.13.1 exactly. I just include the results for the wealth quintiles and the total.
To get the match I had to express the ranges a little differently than in the table headings. Note that it is necessary to omit women who had a birth in the past two months or are pregnant from the BMI indicator.
For tabstat you need to use fweights. You can avoid the use of tabstat, but I think it's a nice command and it is under-used. It is used in the GitHub version.
Something I had never encountered before, and that I only figured out by trial and error, is that for "short", i.e. height less than 145 cm, to get a match you must drop the 5 shortest women in the sample. Apparently a lower plausible bound for height was enforced--but no upper bound. As I said, I have never seen this before and I don't know whether it is done for other tables on anthropometry in this survey or is done for other surveys.
use "...KEIR8BFL.DTA" , clear
gen ht=v438/10 if v438<9994
gen short=0 if ht<.
replace short=100 if ht<145
gen bmi=v445/100 if v445<9998
replace bmi=. if b19_01<2 | v213==1
foreach lv in normal totalthin mildlythin modsevthin overwtobese overwt obese {
gen bmi_`lv'=0 if bmi<.
}
replace bmi_normal =100 if bmi>=18.5 & bmi<25
replace bmi_totalthin =100 if bmi<18.5
replace bmi_mildlythin =100 if bmi>=17.0 & bmi<18.5
replace bmi_modsevthin =100 if bmi<17.0
replace bmi_overwtobese=100 if bmi>=25.0 & bmi<.
replace bmi_overwt =100 if bmi>=25.0 & bmi<30.0
replace bmi_obese =100 if bmi>=30.0 & bmi<.
tabstat bmi* [fweight=v005] if v013>1, statistics(mean) by(v190)
tab v190 if v013>1 & bmi<. [iweight=v005/1000000]
* to match the table for "short" we must drop the 6 shortest women!
sort ht
tabstat short [fweight=v005] if v013>1 & _n>6, statistics(mean) by(v190)
tab v190 if v013>1 & short<. & _n>6 [iweight=v005/1000000]
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