Home » Topics » Mortality » MM9 in the NGIR7BFL dataset of NDHS is from MM9$01 - MM9$20 (maternal mortality) (When variables exist in multiples, which variable should be used for the analysis )
| MM9 in the NGIR7BFL dataset of NDHS is from MM9$01 - MM9$20 (maternal mortality) [message #29501] |
Fri, 28 June 2024 16:02  |
prekan2000
Messages: 7
Registered: June 2024
|
Member |
|
|
Dear DHS Team,
Good evening.
Please I have several questions.
I'm working on variable MM9, M13 and M14.
I understand that MM9 in the Nigeria Demographic Health Survey (NDHS) indicates if the respondent's sister was pregnant when she died, if she died during childbirth, within 6 weeks after the delivery or within 2 months after the delivery.
However, the SPSS dataset NGIR7BFL has some variables I am interested in and they are all in multiples.
MM9 is from MM9$01 - MM9$20 (maternal mortality)
M13 is from M13$1 - M13$6 (timing of first antenatal check)
M14 is from M14$1 - M14$6 (number of antenatal visits)
Please, how can I combine the variables mm9_01 to mm9_20 to a single variable?
Please, how can I combine the variables m13_01 to m13_6 to a single variable?
Please, how can I combine the variables m14_01 to m14_6 to a single variable?
My dillemma, is which of these variables in these ranges for MM9, M13 and M14 should be analysed?
My research is looking at the association between timing of first antenatal check and number of antenatal visits during pregnancy, and maternal mortality when controlling for highest educational level, and ethnicity among pregnant women in Nigeria.
Thank you
[Updated on: Sat, 29 June 2024 18:48] Report message to a moderator |
|
|
|
|
|
|
|
| Re: MM9 in the NGIR7BFL dataset of NDHS is from MM9$01 - MM9$20 (maternal mortality) [message #30110 is a reply to message #30069] |
Tue, 24 September 2024 20:53  |
Janet-DHS
Messages: 891
Registered: April 2022
|
Senior Member |
|
|
Following is a response from DHS staff member, Tom Pullum:
I only use Stata and will respond with that, but you should be able to translate to SPSS. I think the problem is that when you reshape the data you are keeping the full allowance of up to 20 siblings. You need to delete the lines of data that go beyond the number of siblings that a woman actually had. Also you need to restrict to women who died at age 15-49.
I entered the following lines:
use "...NGIR7BFL.DTA", clear
* remove leading zeroes in the subscripts
rename *_0* *_*
* For this example just keep mm1 and mm7 and mm9
keep v001 v002 v003 mm1_* mm9_*
reshape long mm1_ mm9_, i(v001 v002 v003) j(index)
rename *_ *
tab mm1, m
* Drop the lines that go beyond the woman's actual number of siblings
drop if mm1==.
tab mm9 if mm1==2 & mm7>=15 & mm7<=49,m
I see 616,859 blank lines in the data, before dropping the lines with mm1=1:
. tab mm1, m
mm1 | Freq. Percent Cum.
------------+-----------------------------------
male | 112,971 13.51 13.51
female | 106,590 12.74 26.25
. | 616,859 73.75 100.00
------------+-----------------------------------
Total | 836,420 100.00
The last line in the program produces this:
. tab mm9 if mm1==2 & mm7>=15 & mm7<=49,m
mm9 | Freq. Percent Cum.
------------------------+-----------------------------------
death not related | 2,484 67.52 67.52
died while pregnant | 415 11.28 78.80
died during delivery | 535 14.54 93.34
6 weeks after delivery | 202 5.49 98.83
2 months after delivery | 43 1.17 100.00
------------------------+-----------------------------------
Total | 3,679 100.00
There are no "missing" cases if you restrict to women age 15-49 at death. These are the only siblings to whom mm9 applies.
Note that there is an updated version of the files, with "C" in place of "B".
Please let us know if you are still seeing blanks or NA cases
|
|
|
|
|
|
|
|
| Re: MM9 in the NGIR7BFL dataset of NDHS is from MM9$01 - MM9$20 (maternal mortality) [message #30148 is a reply to message #30138] |
Thu, 03 October 2024 14:18 |
Janet-DHS
Messages: 891
Registered: April 2022
|
Senior Member |
|
|
Following is a response from DHS staff member, Tom Pullum:
You can calculate the number of siblings with these lines (in Stata), before reshaping the IR file:
use "C:\Users\26216\ICF\Analysis - Shared Resources\Data\DHSdata\NGIR7BFL.DTA", clear
rename *_0* *_*
* Calculate the number of siblings each woman has
gen nsibs=0
forvalues lsibs=1/20 {
replace nsibs=nsibs+1 if mm1_`lsibs'<.
}
tab nsibs
tab nsibs [iweight=v005/1000000]
summarize nsibs [iweight=v005/1000000]
The weighted mean is 5.23 siblings. Note that you have to allow for the possibility of 0 siblings. This can be modified to give the number of siblings who are males, females, still alive, etc. I am repeating the Stata lines I gave earlier, because what I pasted the first time omitted m7. The full program is below--but it does not include the lines to calculate the adult and maternal mortality rates. Those lines are on our GitHub site.
use "C:\Users\26216\ICF\Analysis - Shared Resources\Data\DHSdata\NGIR7BFL.DTA", clear
rename *_0* *_*
* Calculate the number of siblings each woman has
gen nsibs=0
forvalues lsibs=1/20 {
replace nsibs=nsibs+1 if mm1_`lsibs'<.
}
tab nsibs
tab nsibs [iweight=v005/1000000]
summarize nsibs [iweight=v005/1000000]
* For this example just keep mm1 and mm7 and mm9
keep v001 v002 v003 mm1_* mm7_* mm9_*
reshape long mm1_ mm7_ mm9_, i(v001 v002 v003) j(index)
rename *_ *
tab mm1, m
* Drop the lines that go beyond the woman's actual number of siblings
drop if mm1==.
tab mm9 if mm1==2 & mm7>=15 & mm7<=49,m |
|
|
|
|
|
|
|
|
|
|
|
Goto Forum:
Current Time: Tue Nov 26 18:47:44 Coordinated Universal Time 2024
|
The DHS Program User Forum
Members
Search
Help
Register
Login
Home
