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Home » Data » Weighting data » SSU variables in the Mauritania DHS2019-2021 (The number of pregnant women who delivered their last child in the past five years preceding to the survey in Mauritania)
SSU variables in the Mauritania DHS2019-2021 [message #28730] Thu, 29 February 2024 13:56 Go to next message
kinden is currently offline  kinden
Messages: 5
Registered: February 2024
Member
Dear DHS team,

According to the DHS Household and Sampling Manual, the DHS surveys are two stage surveys. The sampling units for the first stage of selection is called the Primary Sampling Unit (PSU) with probability sampling of EAs; the sampling unit for the second stage of selection is called the Secondary Sampling Unit (SSU) with random sampling of households in the selected EAs.

I try to extract the data to identify the following categories of pregnant women who delivered their last child in the past five years preceding to the Mauritania DHS2019-2021 survey.
(1) The number of pregnant women who delivered their last child after August 2019 in the regions of Hodh Gharbi and Guidimakha
(2) The number of pregnant women who delivered their last child before August 2019 in the regions of Hodh Gharbi and Guidimakha
(3) The number of pregnant women who delivered their last child after August 2019 in other regions than Hodh Gharbi and Guidimakha
(4) The number of pregnant women who delivered their last child before August 2019 in other regions than Hodh Gharbi and Guidimakha

However, I could only get the data regarding the number of women in the sample in the PSU: 39,793 women in 39,793 households.
What is the secondary sampling unit(ssu) variable in DHS data set?
My objective is not to produce sampling error but rather to identify the sample size of the above-mentioned different categories of pregnant women.

Any suggestions would be appreciated.
Thank you!
Re: SSU variables in the Mauritania DHS2019-2021 [message #28735 is a reply to message #28730] Fri, 01 March 2024 07:45 Go to previous messageGo to next message
Bridgette-DHS is currently offline  Bridgette-DHS
Messages: 3043
Registered: February 2013
Senior Member
Following is a response from Senior DHS Stata Specialist, Tom Pullum:

The variable to identify PSUs is v001 (duplicated as v021) and the variable for households, which are the SSUs, is v002. However, you don't need either of them. The following lines will give a table for the number of births that the sampled women had before August 2019, during August 2019, or after August 2019, for each region (v024), not just the two regions you mentioned.

Note that these are numbers of births to women in the sample. The number of births after August 2019 is affected by when the woman was interviewed. The fieldwork started in November 2019 and was stopped in March 2020 (there were 2 interviews in April 2020), and then resumed for two months in February-March 2021. If you are trying to get at the impact of COVID-19 on fertility, you will have to take the date of interview into account. Only the 5,016 women interviewed in 2021 could possibly show a COVID-19 effect.

* Number of births in the Mauritania 2019-21 survey before/after August 2019, by region

use "C:\Users\26216\ICF\Analysis - Shared Resources\Data\DHSdata\MRBR71FL.DTA", clear

* Find the cmc for August 2019
summarize b3 if b1==8 & b2==2019
* August 2019 is b3=1436

* Construct a variable for the timing of births in the birth histories
gen birthdate=1
replace birthdate=2 if b3==1436
replace birthdate=3 if b3>1436

label define bd 1 "Before August 2019" 2 "In August 2019" 3 "After August 2019"
label values birthdate bd
tab v024 birthdate [iweight=v005/1000000]

Here is the table of weighted frequencies:

                      |            birthdate
               region | Before Au  In August  After Aug |     Total
----------------------+---------------------------------+----------
        hodh echargui | 5,398.926  40.237882 165.757235 |5,604.9211 
          hodh gharbi |4,306.5666  28.994562 137.206754 | 4,472.768 
               assaba | 3,542.996  19.488518  85.435286 |  3,647.92 
               gorgol | 3,866.476   21.88072  100.96081 | 3,989.317 
               brakna | 2,995.976  21.032225  97.846587 | 3,114.855 
               trarza | 1,992.851  16.385234  51.722557 | 2,060.959 
                adrar |676.115868   2.597507  16.480042 |695.193417 
   dakhlet nouadhibou |  1,097.09   4.328784  28.115727 | 1,129.534 
               tagant |867.836632   5.258122   23.18794 |896.282694 
           guidimagha |  3,860.71  23.182374 104.898378 | 3,988.791 
tiris zemour et inchi |589.395148    6.91581  15.450279 |611.761237 
     nouakchott ouest | 1,339.084   8.220457 146.107834 | 1,493.412 
      nouakchott nord |  4,009.97  17.350836 347.069054 |  4,374.39 
       nouakchott sud | 3,567.589  18.178068 302.901025 | 3,888.668 
----------------------+---------------------------------+----------
                Total | 38,111.58 234.051099   1,623.14 | 39,968.77

Re: SSU variables in the Mauritania DHS2019-2021 [message #28782 is a reply to message #28735] Thu, 07 March 2024 12:20 Go to previous messageGo to next message
kinden is currently offline  kinden
Messages: 5
Registered: February 2024
Member
Thank you so much, Bridgette.
Your response is very helpful.

Yet, the table below shows the number of livebirths.
How can I get the number of the last child born before/after August 2019 among the classified pregnant women by region?

Could you also confirm the collected data (5,016 women interviewed) in 2021 were only from Nouakchott as the DHS report says?

Kind regards,
Kazumi
Re: SSU variables in the Mauritania DHS2019-2021 [message #28841 is a reply to message #28782] Mon, 18 March 2024 08:15 Go to previous messageGo to next message
Bridgette-DHS is currently offline  Bridgette-DHS
Messages: 3043
Registered: February 2013
Senior Member
Following is a response from Senior DHS staff member, Tom Pullum:

We apologize for the delay in this response.

The variable for region, v024, has the following categories:

. label list V024
V024:
           1 hodh echargui
           2 hodh gharbi
           3 assaba
           4 gorgol
           5 brakna
           6 trarza
           7 adrar
           8 dakhlet nouadhibou
           9 tagant
          10 guidimagha
          11 tiris zemour et inchiri
          12 nouakchott ouest
          13 nouakchott nord
          14 nouakchott sud

Nouakshott is divided into west, north, and south. The weighted and unweighted numbers of women in the regions is obtained with the IR file:

. use "...MRIR71FL.DTA"

. tab v024

                 region |      Freq.     Percent        Cum.
------------------------+-----------------------------------
          hodh echargui |      1,327        8.44        8.44
            hodh gharbi |      1,402        8.92       17.37
                 assaba |      1,380        8.78       26.15
                 gorgol |      1,449        9.22       35.37
                 brakna |      1,454        9.25       44.62
                 trarza |      1,320        8.40       53.02
                  adrar |        808        5.14       58.16
     dakhlet nouadhibou |        643        4.09       62.26
                 tagant |        920        5.85       68.11
             guidimagha |      1,786       11.37       79.48
tiris zemour et inchiri |        787        5.01       84.49
       nouakchott ouest |        728        4.63       89.12
        nouakchott nord |        910        5.79       94.91
         nouakchott sud |        800        5.09      100.00
------------------------+-----------------------------------
                  Total |     15,714      100.00

. tab v024 [iweight=v005/1000000]

                 region |      Freq.     Percent        Cum.
------------------------+-----------------------------------
          hodh echargui |2,033.68582       12.94       12.94
            hodh gharbi | 1,579.5074       10.05       22.99
                 assaba | 1,249.2951        7.95       30.94
                 gorgol | 1,292.7495        8.23       39.17
                 brakna | 1,281.9262        8.16       47.33
                 trarza | 961.483433        6.12       53.45
                  adrar | 297.682976        1.89       55.34
     dakhlet nouadhibou | 538.786626        3.43       58.77
                 tagant | 349.098656        2.22       60.99
             guidimagha | 1,243.5337        7.91       68.91
tiris zemour et inchiri |  273.47023        1.74       70.65
       nouakchott ouest | 792.569719        5.04       75.69
        nouakchott nord | 2,073.0319       13.19       88.88
         nouakchott sud | 1,747.1787       11.12      100.00
------------------------+-----------------------------------
                  Total |     15,714      100.00

However, in order to get the 5016 that you refer to, I have to go to the BR file, in which the cases are all the children in the birth histories:

. use "...MRBR71FL.DTA", clear

. tab v024

                 region |      Freq.     Percent        Cum.
------------------------+-----------------------------------
          hodh echargui |      3,560        8.95        8.95
            hodh gharbi |      3,865        9.71       18.66
                 assaba |      3,902        9.81       28.46
                 gorgol |      4,355       10.94       39.41
                 brakna |      3,467        8.71       48.12
                 trarza |      2,841        7.14       55.26
                  adrar |      1,832        4.60       59.86
     dakhlet nouadhibou |      1,388        3.49       63.35
                 tagant |      2,300        5.78       69.13
             guidimagha |      5,467       13.74       82.87
tiris zemour et inchiri |      1,800        4.52       87.39
       nouakchott ouest |      1,279        3.21       90.61
        nouakchott nord |      1,936        4.87       95.47
         nouakchott sud |      1,801        4.53      100.00
------------------------+-----------------------------------
                  Total |     39,793      100.00

. tab v024 [iweight=v005/1000000]

                 region |      Freq.     Percent        Cum.
------------------------+-----------------------------------
          hodh echargui | 5,604.9211       14.02       14.02
            hodh gharbi | 4,472.7679       11.19       25.21
                 assaba | 3,647.9203        9.13       34.34
                 gorgol | 3,989.3172        9.98       44.32
                 brakna | 3,114.8548        7.79       52.12
                 trarza | 2,060.9592        5.16       57.27
                  adrar | 695.193417        1.74       59.01
     dakhlet nouadhibou | 1,129.5344        2.83       61.84
                 tagant | 896.282694        2.24       64.08
             guidimagha |3,988.79101        9.98       74.06
tiris zemour et inchiri | 611.761237        1.53       75.59
       nouakchott ouest |  1,493.412        3.74       79.33
        nouakchott nord |4,374.38955       10.94       90.27
         nouakchott sud | 3,888.6678        9.73      100.00
------------------------+-----------------------------------
                  Total | 39,968.772      100.00

By adding the numbers in regions 12, 13, and 14, weighted and unweighted, in the IR and BR files, I found that the 5016 is the sum of the weighted frequencies in the BR file. I have highlighted those numbers in yellow. In other words, I can confirm that there are 5016 BIRTHS, NOT WOMEN, and these are WEIGHTED frequencies, NOT UNWEIGHTED.

You also ask for "the number of the last child born before/after August 2019 among the classified pregnant women by region". I have tried to understand your question but can you clarify it? Are you trying to match a table in the final report, or are you doing something new?

As before, I do not know why you are particularly interested in August 2019, and I don't know whether you intend to include that month 2019 in "before" or "after". I don't know whey you are limiting yourself to women who are pregnant, which I interpret to mean pregnant at the time of the survey.

If I interpret your question literally, you want to restrict yourself to women who are pregnant at the time of the survey (v213=1), and to the most recent birth (bidx=1) and you want to know how many of those births were before or after August 2019, by region. Here are the Stata lines for doing that. Let us know if you want something else.

use "...MRBR71FL.DTA", clear

* Find the cmc for August 2019
summarize b3 if b1==8 & b2==2019
* August 2019 is b3=1436

* Construct a variable for the timing of births in the birth histories
gen birthdate=1
replace birthdate=2 if b3==1436
replace birthdate=3 if b3>1436

label define bd 1 "Before August 2019" 2 "In August 2019" 3 "After August 2019"
label values birthdate bd

tab v024 birthdate if bidx==1 & v213==1 [iweight=v005/1000000]

. tab v024 birthdate if bidx==1 & v213==1 [iweight=v005/1000000]

                      |            birthdate
               region | Before Au  In August  After Aug |     Total
----------------------+---------------------------------+----------
        hodh echargui |149.223643   2.148514          0 |151.372157 
          hodh gharbi |151.271238          0          0 |151.271238 
               assaba | 76.345168          0          0 | 76.345168 
               gorgol |102.743707          0          0 |102.743707 
               brakna | 42.965639          0          0 | 42.965639 
               trarza | 53.324355          0          0 | 53.324355 
                adrar | 13.528143          0          0 | 13.528143 
   dakhlet nouadhibou | 26.032095          0          0 | 26.032095 
               tagant | 23.939958          0          0 | 23.939958 
           guidimagha | 81.070053          0    .723028 | 81.793081 
tiris zemour et inchi | 15.290715          0          0 | 15.290715 
     nouakchott ouest | 17.218033          0    .792849 | 18.010882 
      nouakchott nord | 91.418925   2.031406   6.741004 |100.191335 
       nouakchott sud | 83.416651    5.80855   5.440926 | 94.666127 
----------------------+---------------------------------+----------
                Total |927.788323    9.98847  13.697807 |  951.4746
Re: SSU variables in the Mauritania DHS2019-2021 [message #28914 is a reply to message #28841] Wed, 27 March 2024 17:45 Go to previous messageGo to next message
kinden is currently offline  kinden
Messages: 5
Registered: February 2024
Member
Thank you so much once again, Bridgette.
It is very useful to confirm that 5016 is the sum of the weighted frequencies in the BR file.

And yes, I would like to restrict the data to women who are pregnant at the time of the survey (v213=1), and to the most recent birth (bidx=1) and I want to know how many of those births were before or after August 2019, by region, assuming that most pregnant women delivered one baby at their last birth.
The reasons why I am interested in before/after August 2019 are that the intervention of my interest has started since December 2018 (9 months before August 2019) and that I would like to analyze key issues around ANC service delivery.

What I still do not understand from your two useful responses is why the number of livebirths after August 2019 is different between the data from the first response (1,623.14 - weighted) and those from the second response (13.697 - unweighted?)?
These numbers are supposed to be similar as no women will be able to deliver another baby from August 2019 onwards during the survey period, non?



* Number of births in the Mauritania 2019-21 survey before/after August 2019, by region

use "C:\Users\26216\ICF\Analysis - Shared Resources\Data\DHSdata\MRBR71FL.DTA", clear

* Find the cmc for August 2019
summarize b3 if b1==8 & b2==2019
* August 2019 is b3=1436

* Construct a variable for the timing of births in the birth histories
gen birthdate=1
replace birthdate=2 if b3==1436
replace birthdate=3 if b3>1436

label define bd 1 "Before August 2019" 2 "In August 2019" 3 "After August 2019"
label values birthdate bd
tab v024 birthdate [iweight=v005/1000000]

Here is the table of weighted frequencies:

| birthdate
region | Before Au In August After Aug | Total
----------------------+---------------------------------+--- -------
hodh echargui | 5,398.926 40.237882 165.757235 |5,604.9211
hodh gharbi |4,306.5666 28.994562 137.206754 | 4,472.768
assaba | 3,542.996 19.488518 85.435286 | 3,647.92
gorgol | 3,866.476 21.88072 100.96081 | 3,989.317
brakna | 2,995.976 21.032225 97.846587 | 3,114.855
trarza | 1,992.851 16.385234 51.722557 | 2,060.959
adrar |676.115868 2.597507 16.480042 |695.193417
dakhlet nouadhibou | 1,097.09 4.328784 28.115727 | 1,129.534
tagant |867.836632 5.258122 23.18794 |896.282694
guidimagha | 3,860.71 23.182374 104.898378 | 3,988.791
tiris zemour et inchi |589.395148 6.91581 15.450279 |611.761237
nouakchott ouest | 1,339.084 8.220457 146.107834 | 1,493.412
nouakchott nord | 4,009.97 17.350836 347.069054 | 4,374.39
nouakchott sud | 3,567.589 18.178068 302.901025 | 3,888.668
----------------------+---------------------------------+--- -------
Total | 38,111.58 234.051099 1,623.14| 39,968.77




use "...MRBR71FL.DTA", clear

* Find the cmc for August 2019
summarize b3 if b1==8 & b2==2019
* August 2019 is b3=1436

* Construct a variable for the timing of births in the birth histories
gen birthdate=1
replace birthdate=2 if b3==1436
replace birthdate=3 if b3>1436

label define bd 1 "Before August 2019" 2 "In August 2019" 3 "After August 2019"
label values birthdate bd

tab v024 birthdate if bidx==1 & v213==1 [iweight=v005/1000000]

. tab v024 birthdate if bidx==1 & v213==1 [iweight=v005/1000000]

| birthdate
region | Before Au In August After Aug | Total
----------------------+---------------------------------+--- -------
hodh echargui |149.223643 2.148514 0 |151.372157
hodh gharbi |151.271238 0 0 |151.271238
assaba | 76.345168 0 0 | 76.345168
gorgol |102.743707 0 0 |102.743707
brakna | 42.965639 0 0 | 42.965639
trarza | 53.324355 0 0 | 53.324355
adrar | 13.528143 0 0 | 13.528143
dakhlet nouadhibou | 26.032095 0 0 | 26.032095
tagant | 23.939958 0 0 | 23.939958
guidimagha | 81.070053 0 .723028 | 81.793081
tiris zemour et inchi | 15.290715 0 0 | 15.290715
nouakchott ouest | 17.218033 0 .792849 | 18.010882
nouakchott nord | 91.418925 2.031406 6.741004 |100.191335
nouakchott sud | 83.416651 5.80855 5.440926 | 94.666127
----------------------+---------------------------------+--- -------
Total |927.788323 9.98847 13.697807 | 951.4746




Kind regards,
Kazumi
Re: SSU variables in the Mauritania DHS2019-2021 [message #28920 is a reply to message #28914] Thu, 28 March 2024 13:07 Go to previous messageGo to next message
Bridgette-DHS is currently offline  Bridgette-DHS
Messages: 3043
Registered: February 2013
Senior Member

Following is a response from Senior DHS staff member, Tom Pullum:

The table with 1, 623.14 births after August 2019 was constructed with this command: "tab v024 birthdate [iweight=v005/1000000]". The table with just 13.697 births after August 2019 was constructed with "tab v024 birthdate if bidx==1 & v213==1 [iweight=v005/1000000]". Both frequencies were weighted, but the second and much smaller frequency was limited to the most recent birth (bidx=1) and to women who are pregnant at the time of the survey (v213=1). They are a very small subset of the births in the first table. These tables were what I understood you to be requesting.

You say that you are trying to measure the potential impact of an intervention related to ANC care. I don't see how either of these tables could be used to describe such an impact. This is an interesting question, but this survey may not be appropriate for answering it. I would like to help but the question is outside the scope of the user forum. I hope other users can help.

Here is a journal article that may help, but it uses two successive surveys:

Mallick, Lindsay, Trinadh Dontamsetti, Thomas Pullum, and Julia Fleuret. 2019. Using the Uganda Demographic and Health Surveys from 2011 and 2016 to assess changes in Saving Mothers, Giving Life intervention districts. J. of Global Health Research 3. doi:10.29392/joghr.3.e2019026.

Re: SSU variables in the Mauritania DHS2019-2021 [message #28936 is a reply to message #28920] Fri, 29 March 2024 13:08 Go to previous messageGo to next message
kinden is currently offline  kinden
Messages: 5
Registered: February 2024
Member
Thank you so much for your prompt reply.
I do understand that this is not the forum to conduct an additional analysis to measure the potential impact of an intervention related to ANC care.

What I am trying to do here is to verify the feasibility of my planned analysis on ANC service delivery.
If there are zero livebirth after August 2019 in most regions except Nouakchott, my analysis will not be feasible.
Thus, I have asked to clarify the differences of the previous two responses.

Kind regards,
Kazumi
Re: SSU variables in the Mauritania DHS2019-2021 [message #28945 is a reply to message #28936] Mon, 01 April 2024 08:20 Go to previous message
Bridgette-DHS is currently offline  Bridgette-DHS
Messages: 3043
Registered: February 2013
Senior Member
Following is a response from Senior DHS staff member, Tom Pullum:

My previous response said what was the difference between the two tables. I'm still not quite sure what your hypothesis is, about the difference between Nouakchott and the rest of Mauritania, but the comparisons that I believe you are trying to make would have to take account of the date of interview, which affects the length of time after August 2019 that the woman could have had a birth.

As you would know, the data collection for Mauritania was spread over 3 calendar years, 2019-2021. Most of the fieldwork was between late November 2019 and March of 2020. Because of Covid, fieldwork was suspended, and was not resumed and completed until February-March 2021. As it happens, the three areas that make up Nouakchott were the only areas that were surveyed in 2021.

Here is a table that gives the century month code (cmc, hv008) and the number of interviews in each month of data collection. This table has households as units and is unweighted. Ignore the "totals" row and column:
. tab hv006 hv007, summarize(hv008) means freq

             Means and Frequencies of date of interview (cmc)

  month of |       year of interview
interview |      2019       2020       2021 |     Total
-----------+---------------------------------+----------
         1 |         .       1441          . |      1441
           |         0       2540          0 |      2540
-----------+---------------------------------+----------
         2 |         .       1442       1454 |  1443.591
           |         0       2545        389 |      2934
-----------+---------------------------------+----------
         3 |         .       1443       1455 | 1447.8632
           |         0       2009       1369 |      3378
-----------+---------------------------------+----------
        11 |      1439          .          . |      1439
           |       115          0          0 |       115
-----------+---------------------------------+----------
        12 |      1440          .          . |      1440
           |      2691          0          0 |      2691
-----------+---------------------------------+----------
     Total |  1439.959  1441.9251  1454.7787 | 1443.3902
           |      2806       7094       1758 |     11658

The cmc's for February-March 2021 are 1454 and 1455. In those months, 389 and 1369 households, respectively, were interviewed.  

Next, still with households as units, I get the number of interviews by region and cmc as follows:

tab hv024 hv008

                      |                           date of interview (cmc)
               region |      1439       1440       1441       1442       1443       1454       1455 |     Total
----------------------+-----------------------------------------------------------------------------+----------
        hodh echargui |        14        498        281        218        136          0          0 |     1,147 
          hodh gharbi |         6        133        266        402        219          0          0 |     1,026 
               assaba |         9        325        279        283        198          0          0 |     1,094 
               gorgol |        14        263        263        267        129          0          0 |       936 
               brakna |         6        246        298        263        239          0          0 |     1,052 
               trarza |        15        254        275        292        190          0          0 |     1,026 
                adrar |         7        230        157        134        140          0          0 |       668 
   dakhlet nouadhibou |         8        141        147        141        231          0          0 |       668 
               tagant |        14        226        241        197         51          0          0 |       729 
           guidimagha |        16        279        169        118        245          0          0 |       827 
tiris zemour et inchi |         6         96        164        230        231          0          0 |       727 
     nouakchott ouest |         0          0          0          0          0        103        479 |       582 
      nouakchott nord |         0          0          0          0          0        174        417 |       591 
       nouakchott sud |         0          0          0          0          0        112        473 |       585 
----------------------+-----------------------------------------------------------------------------+----------
                Total |       115      2,691      2,540      2,545      2,009        389      1,369 |    11,658 

This table shows that, as I said, Nouakchott was not visited until 2021. For that reason alone, you would expect more births there in the interval since August 2019 than in the parts of Mauritania that were visited in late 2019 and early 2020.

To me, it is notable that the date collection is neatly divided, geographically, into pre-covid and post-covid, giving a kind of natural experimental design for potential effects of covid. But I don't see this as a good design for assessing the impact of an intervention in August 2019 in Nouakchott. Any potential effect of that intervention will be completely confounded with the potential effect of covid during the interruption to fieldwork.

If you have other questions, perhaps other users can help.
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