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Post Natal Care check [message #23781] Tue, 30 November 2021 02:34 Go to previous message
Francois is currently offline  Francois
Messages: 9
Registered: February 2017
Location: KIGALI
Member
Hello,
I am trying to reproduce the Table 9.9 and Table 9.11 ,The percentage of women with a pnc chek during the first 2days after birth for both mothers and newborn using GITHUB Codes. I am getting the different numbers in frequencies and percentages, Probably variables used changed but don't know where are mistakes. Thank you for your assistance
Here are the codes used:

*=====PNC INDICATORS========
cd"C:\Users\ICF Rwanda\Desktop\district\DHS6"
use RWIR81FL, clear

gen age = v008 - b3_01
gen w=v005/1000000

scalar drop _all

** To check if survey has m51_1, which was in the surveys before 2005.

scalar m51_included=1
capture confirm numeric variable m51_1, exact
if _rc>0 {
* m51_1 is not present
scalar m51_included=0
}
if _rc==0 {
* m51_1 is present; check for values
summarize m51_1
if r(sd)==0 | r(sd)==. {
scalar m51_included=0
}
}

*** Mother's PNC ***

if m51_included==1 {

//PNC timing for mother
recode m51_1 (100/103 = 1 "<4hr") (104/123 200 = 2 "4-23hrs") (124/171 201/202 = 3 "1-2 days") ///
(172/197 203/206 = 4 "3-6 days") (207/241 301/305=5 "7-41 days") ///
(198/199 298/299 398/399 998/999 = 9 "dont know/missing") (242/297 306/397 = 0 "no pnc check") , g(rh_pnc_wm_timing)
replace rh_pnc_wm_timing = 0 if m50_1==0 | m50_1==9
replace rh_pnc_wm_timing = 0 if (m52_1>29 & m52_1<97) | m52_1==.
replace rh_pnc_wm_timing=. if age>=24 | bidx_01!=1
label var rh_pnc_wm_timing "Timing after delivery for mother's PNC check"

//PNC within 2days for mother
recode rh_pnc_wm_timing (1/3= 1 "Visit w/in 2 days") (0 4 5 9 = 0 "No Visit w/in 2 days"), g(rh_pnc_wm_2days)
label var rh_pnc_wm_2days "PNC check within two days for mother"

//PNC provider for mother
** This is country specific and could be different for different surveys, please check footnote of the table for this indicator in the final report.
recode m52_1 (0 = 0 "No check") (11 = 1 "Doctor") (12/13 = 2 "Nurse/Midwife") ( 14/15 = 3 "Other skilled provider") (16/90 = 4 "Non-skilled provider") (96 = 5 "Other") ///
( else = 9 "Don't know or missing") if age<24 & rh_pnc_wm_2days==1, gen(rh_pnc_wm_pv)
replace rh_pnc_wm_pv = 0 if rh_pnc_wm_2days==0 & age<24
label var rh_pnc_wm_pv "Provider for mother's PNC check"
}

if m51_included==0 {
cap drop rh_pnc_wm_timing

//PNC timing for mother
*did the mother have any check
gen momcheck = 0 if age<24
replace momcheck = 1 if (m62_1==1 | m66_1==1) & age<24

*create combined timing variable
gen pnc_wm_time = 999 if (age<24 & momcheck==1)
*start with women who delivered in a health facility with a check
replace pnc_wm_time = m63_1 if inrange(m64_1,11,29) & age<24
*Account for provider of PNC- country specific- see table footnotes
replace pnc_wm_time = 0 if (pnc_wm_time < 1000 & m64_1 >30 & m64_1 < 100 & age<24)
*Add in women who delivered at home with a check
replace pnc_wm_time = m67_1 if (pnc_wm_time == 999 & inrange(m68_1, 11,29) & age<24)
*Account for provider of PNC- country specific- see table footnotes
replace pnc_wm_time = 0 if m67_1 < 1000 & m68_1 >30 & m68_1 < 100 & age<24
*Add in women who had no check
replace pnc_wm_time = 0 if momcheck == 0 & age<24

*Recode variable into categories as in FR
recode pnc_wm_time (0 242/299 306/899 = 0 "No check or past 41 days") ( 100/103 = 1 "<4hrs") (104/123 200 = 2 "4-23hrs") (124/171 201/202 = 3 "1-2days") ///
(172/197 203/206 = 4 "3-6days") (207/241 301/305 = 5 "7-41days") (else = 9 "Don't know/missing") if age<24, gen(rh_pnc_wm_timing)
*label variable
label var rh_pnc_wm_timing "Timing after delivery for mother's PNC check"

//PNC within 2days for mother
recode rh_pnc_wm_timing (1/3 = 1 "Within 2 days") (0 4 5 9 = 0 "Not in 2 days"), gen(rh_pnc_wm_2days)
label var rh_pnc_wm_2days "PNC check within two days for mother"

//PNC provider for mother
** This is country specific and could be different for different surveys, please check footnote of the table for this indicator in the final report.

*Providers of PNC for facility deliveries
recode m64_1 (0 = 0 "No check") (11 = 1 "Doctor") (12/13 = 2 "Nurse/Midwife") ( 14/15 = 3 "Other skilled provider") (16/90 = 4 "Non-skilled provider") (96 = 5 "Other") ///
( else = 9 "Don't know or missing") if age<24 & rh_pnc_wm_2days==1, gen(pnc_wm_pv_hf)
replace pnc_wm_pv_hf = 0 if rh_pnc_wm_2days==0 & age<24

*Providers of PNC for home deliveries or checks after discharge
recode m68_1 (0 = 0 "No check") (11 = 1 "Doctor") (12/13 = 2 "Nurse/Midwife") ( 14/15 = 3 "Other skilled provider") (16/90 = 4 "Non-skilled provider") (96 = 5 "Other") ///
( else = 9 "Don't know or missing") if age<24 & rh_pnc_wm_2days==1 , gen(pnc_wm_pv_home)
replace pnc_wm_pv_home = 0 if rh_pnc_wm_2days==0 & age<24

*Combine two PNC provider variables
clonevar rh_pnc_wm_pv = pnc_wm_pv_hf
replace rh_pnc_wm_pv = pnc_wm_pv_home if (pnc_wm_pv_hf==9 & rh_pnc_wm_2days==1 & age<24)
*label variable
label var rh_pnc_wm_pv "Provider for mother's PNC check"
}



*** Newborn's PNC ***

* some surveys (usally older surveys) do not have PNC indicators for newborns. For this you would need variables m70_1, m71_1, ..., m76_1
scalar m70s_included=1
forvalues i=1/6 {
capture confirm numeric variable m7`i'_1, exact
if _rc>0 {
scalar m70s_included=0
}
if _rc==0 {
summarize m7`i'_1
if r(sd)==0 | r(sd)==. {
scalar m70s_included=0
}
}
}

*survey has newborn PNC indicators
if m70s_included==1 {

if m51_included==1 {

//PNC timing for newborn
recode m71_1 (207/297 301/397 = 0 "No check or past 7 days") ( 100 = 1 "less than 1 hour") (101/103 = 2 "1-3 hours") (104/123 200 = 3 "4 to 23 hours") (124/171 201/202 = 4 "1-2 days") ///
(172/197 203/206 = 5 "3-6 days new") (198/199 298/299 398/399 998/999 = 9 "dont know/missing") if age<24 , gen(rh_pnc_nb_timing)

*Recode babies with no check and babies with check by unskilled prov back to 0
replace rh_pnc_nb_timing = 0 if (m70_1==0 | m70_1==9)
*Account for provider of PNC- country specific- see table footnotes
replace rh_pnc_nb_timing = 0 if (m72_1>29 & m72_1<97) | m72_1==.
replace rh_pnc_nb_timing = . if age>=24 | bidx_01!=1

*label variable
label var rh_pnc_nb_timing "Timing after delivery for newborn's PNC check"

//PNC within 2days for newborn
recode rh_pnc_nb_timing (1/4 = 1 "Visit within 2 days") (0 5 9 = 0 "No Visit within 2 days"), g(rh_pnc_nb_2days)
*label variable
label var rh_pnc_nb_2days "PNC check within two days for newborn"

//PNC provider for newborn
** this is country specific, please check table in final report
recode m72_1 (0 = 0 "No check") (11 = 1 "Doctor") (12/13 = 2 "Nurse/Midwife") ( 14/15 = 3 "Other skilled provider") (16/90 = 4 "Non-skilled provider") (96 = 5 "Other") ///
( 98/99 = 9 "Don't know or missing") if age<24 & rh_pnc_nb_timing<9 & rh_pnc_nb_timing>0, gen(rh_pnc_nb_pv)
replace rh_pnc_nb_pv = 0 if rh_pnc_nb_2days ==0 & age<24
label var rh_pnc_nb_pv "Provider for newborn's PNC check"

}

if m51_included==0 {

//PNC timing for newborn

*Newborn check
gen nbcheck = 1 if (m70_1==1 | m74_1==1 )
*create combined timing variable
gen pnc_nb_timing_all = 999 if age<24 & nbcheck==1

*start with women who delivered in a health facility with a check
replace pnc_nb_timing_all = m75_1 if inrange(m76_1,11,29) & age<24
*Account for provider of PNC- country specific- see table footnotes
replace pnc_nb_timing_all = 0 if pnc_nb_timing_all < 1000 & m76_1 >30 & m76_1 < 100 & age<24

*Add in women who delivered at home with a check
replace pnc_nb_timing_all = m71_1 if (pnc_nb_timing_all==999 & inrange(m72_1,11,29) & age<24)
*Account for provider of PNC- country specific- see table footnotes
replace pnc_nb_timing_all = 0 if (m71_1 < 1000 & m72_1 >30 & m72_1 < 100 & age<24)
*Add in women who had no check
replace pnc_nb_timing_all = 0 if (nbcheck!=1) & age<24

*Recode variable into categories as in FR
recode pnc_nb_timing_all (0 207/297 301/397 = 0 "No check or past 7 days") ( 100=1 "less than 1 hour") (101/103 =2 "1-3 hours") (104/123 200 = 3 "4 to 23 hours") (124/171 201/202 = 4 "1-2 days") ///
(172/197 203/206 = 5 "3-6 days new") (else = 9 "Don't know or missing") if age<24 , gen (rh_pnc_nb_timing)
*label variable
label var rh_pnc_nb_timing "Timing after delivery for mother's PNC check"

//PNC within 2days for newborn
recode rh_pnc_nb_timing (1/4 = 1 "visit within 2 days") (0 5 9 = 0 "No Visit within 2 days"), g(rh_pnc_nb_2days)
label var rh_pnc_nb_2days "PNC check within two days for newborn"

//PNC provider for newborn
** This is country specific and could be different for different surveys, please check footnote of the table for this indicator in the final report.

*Providers of PNC for home deliveries or checks after discharge
recode m72_1 (0 = 0 "No check") (11 = 1 "Doctor") (12/13 = 2 "Nurse/Midwife") ( 14/15 = 3 "Other skilled provider") (16/90 = 4 "Non-skilled provider") (96 = 5 "Other") ///
( else = 9 "Don't know or missing") if age<24 & rh_pnc_nb_2days==1, gen(pnc_nb_pv_home)
replace pnc_nb_pv_home = 0 if rh_pnc_nb_2days==0 & age<24

*Providers of PNC for facility deliveries
recode m76_1 (0 = 0 "No check") (11 = 1 "Doctor") (12/13 = 2 "Nurse/Midwife") ( 14/15 = 3 "Other skilled provider") (16/90 = 4 "Non-skilled provider") (96 = 5 "Other") ///
( else = 9 "Don't know or missing") if age<24 & rh_pnc_nb_2days==1 , gen(pnc_nb_pv_hf)
replace pnc_nb_pv_hf = 0 if rh_pnc_nb_2days==0 & age<24

*Combine two PNC provider variables
clonevar rh_pnc_nb_pv = pnc_nb_pv_hf
replace rh_pnc_nb_pv = pnc_nb_pv_home if (pnc_nb_pv_hf ==9) & rh_pnc_nb_2days ==1 & age<24
*label variable
label var rh_pnc_nb_pv "Provider for newborns's PNC check"

}
}

*survey does not have newborn PNC indicators
if m70s_included==0 {
* replace indicators as missing
gen rh_pnc_nb_timing = .
gen rh_pnc_nb_2days = .
gen rh_pnc_nb_pv = .
}

*=======TABLES PRODUCED=======
ta rh_pnc_nb_2days[iw=w] //for Newborn


PNC check within two
days for newborn
Freq. Percent Cum.

No Visit within 2 days 798.142952 25.19 25.19
visit within 2 days 2,370.5574 74.81 100.00

Total 3,168.7003 100.00


ta rh_pnc_wm_2days[iw=w] // for Mom or mother
PNC check
within two
days for
mother
Freq. Percent Cum.

Not in 2 days 932.12392 29.42 29.42
Within 2 days 2,236.5764 70.58 100.00

Total 3,168.7003 100.00









AF
 
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