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Home » Topics » Unmet Need » Getting Unmet Need & Demand Satisfied Estimates to Match StatCompiler for 5 Different Surveys (Getting Unmet Need & Demand Satisfied Estimates to Match StatCompiler for 5 Different Surveys)
Getting Unmet Need & Demand Satisfied Estimates to Match StatCompiler for 5 Different Surveys [message #16217] Mon, 26 November 2018 17:28 Go to next message
cgreenba is currently offline  cgreenba
Messages: 12
Registered: October 2017
Member
Dear all,

I am working on a report looking at demand satisfied among youth across different DHS surveys and am having a difficult time matching the new definition of unmet need and demand satisfied numbers that I am getting in Stata with the estimates in StatCompiler for a few of the surveys that I have included in my analysis: the 2011-12 Honduras DHS, the 2006 Nepal DHS, the 2006 Niger DHS, the 2010 Rwanda DHS, and the 2011 Uganda DHS. For the surveys that did not have the new unmet need variable (v626a), I used either the general or survey specific recoding of unmet need do file produced by Sarah Bradley - attached below - but am still getting different estimates.

Here are the estimates that I get in Stata:
Honduras 2011-12 - Unmet need (all women) 15-19: 4.8%
Honduras 2011-12 - Unmet need (all women) 20-24: 7.6%
Honduras 2011-12 - Unmet need (all women) 15-24: 6.1%
Honduras 2011-12 - Demand satisfied by modern methods (all women) 15-19: 66.8%
Honduras 2011-12 - Demand satisfied by modern methods (all women) 20-24: 75.0%
Honduras 2011-12 - Demand satisfied by modern methods (all women) 15-24: 72.2%
Nepal 2006 - Unmet need (all women) 15-19: 37.8%
Nepal 2006 - Unmet need (all women) 20-24: 33.2%
Nepal 2006 - Unmet need (all women) 15-24: 34.7%
Nepal 2006 - Demand satisfied by modern methods (all women) 15-19: 25.7%
Nepal 2006 - Demand satisfied by modern methods (all women) 20-24: 43.4%
Nepal 2006 - Demand satisfied by modern methods (all women) 15-24: 38.4%
Niger 2006 - Unmet need (all women) 15-19: 6.9%
Niger 2006 - Unmet need (all women) 20-24: 15.4%
Niger 2006 - Unmet need (all women) 15-24: 11.1%
Niger 2006 - Demand satisfied by modern methods (all women) 15-19: 10.6%
Niger 2006 - Demand satisfied by modern methods (all women) 20-24: 16.7%
Niger 2006 - Demand satisfied by modern methods (all women) 15-24: 15.0%
Rwanda 2010 - Unmet need (all women) 15-19: 1.0%
Rwanda 2010 - Unmet need (all women) 20-24: 7.3%
Rwanda 2010 - Unmet need (all women) 15-24: 4.0%
Rwanda 2010 - Demand satisfied by modern methods (all women) 15-19: 62.3%
Rwanda 2010 - Demand satisfied by modern methods (all women) 20-24: 69.1%
Rwanda 2010 - Demand satisfied by modern methods (all women) 15-24: 68.3%
Uganda 2011 - Unmet need (all women) 15-19: 7.8%
Uganda 2011 - Unmet need (all women) 20-24: 25.3%
Uganda 2011 - Unmet need (all women) 15-24: 15.5%
Uganda 2011 - Demand satisfied by modern methods (all women) 15-19: 41.5%
Uganda 2011 - Demand satisfied by modern methods (all women) 20-24: 41.8%
Uganda 2011 - Demand satisfied by modern methods (all women) 15-24: 41.7%

Here are the estimates that StatCompiler lists:
Honduras 2011-12 - Unmet need (all women) 15-19: 6.5%
Honduras 2011-12 - Unmet need (all women) 20-24: 9.7%
Honduras 2011-12 - Unmet need (all women) 15-24: 7.9%
Honduras 2011-12 - Demand satisfied by modern methods (all women) 15-19: 62.0%
Honduras 2011-12 - Demand satisfied by modern methods (all women) 20-24: 72.1%
Honduras 2011-12 - Demand satisfied by modern methods (all women) 15-24: 68.6%
Nepal 2006 - Unmet need (all women) 15-19: 12.2%
Nepal 2006 - Unmet need (all women) 20-24: 26.7%
Nepal 2006 - Unmet need (all women) 15-24: 18.7%
Nepal 2006 - Demand satisfied by modern methods (all women) 15-19: 25.9%
Nepal 2006 - Demand satisfied by modern methods (all women) 20-24: 43.6%
Nepal 2006 - Demand satisfied by modern methods (all women) 15-24: 38.5%
Niger 2006 - Unmet need (all women) 15-19: 6.9%
Niger 2006 - Unmet need (all women) 20-24: 15.2%
Niger 2006 - Unmet need (all women) 15-24: 11.0%
Niger 2006 - Demand satisfied by modern methods (all women) 15-19: 22.4%
Niger 2006 - Demand satisfied by modern methods (all women) 20-24: 35.0%
Niger 2006 - Demand satisfied by modern methods (all women) 15-24: 31.6%
Rwanda 2010 - Unmet need (all women) 15-19: 2.2%
Rwanda 2010 - Unmet need (all women) 20-24: 10.3%
Rwanda 2010 - Unmet need (all women) 15-24: 6.1%
Rwanda 2010 - Demand satisfied by modern methods (all women) 15-19: 45.3%
Rwanda 2010 - Demand satisfied by modern methods (all women) 20-24: 62.1%
Rwanda 2010 - Demand satisfied by modern methods (all women) 15-24: 59.8%
Uganda 2011 - Unmet need (all women) 15-19: 10.5%
Uganda 2011 - Unmet need (all women) 20-24: 27.5%
Uganda 2011 - Unmet need (all women) 15-24: 18.1%
Uganda 2011 - Demand satisfied by modern methods (all women) 15-19: 34.9%
Uganda 2011 - Demand satisfied by modern methods (all women) 20-24: 39.9%
Uganda 2011 - Demand satisfied by modern methods (all women) 15-24: 38.4%

Is anyone aware of why I might be seeing these discrepancies? Is StatCompiler using a different sample, even in the indicator marked all women? Do I need to used a different weighting scheme other than the sample weights provided? I tried to match using the earlier definition of unmet need at as well, but that did not work. Any help or information would be greatly appreciated!

Here is my code in case it helps:
gen indiv_weight = v005/1000000

gen modern_contraception=0
replace modern_contraception=1 if v313==3
replace modern_contraception=. if v313==.

gen any_contraception=0
replace any_contraception=1 if v313==3 | v313==1 | v313==2
replace any_contraception=. if v313==.

gen unmet_need=0
replace unmet_need=1 if v626a==1 | v626a==2
replace unmet_need=. if v626a==.
* OR: gen umet_need=unmettot


gen demand_satisfied=.
replace demand_satisfied=0 if unmet_need==1
replace demand_satisfied=0 if v313==0 | v313==1 | v313==2
replace demand_satisfied=1 if v313==3
replace demand_satisfied=. if unmet_need==0 & any_contraception==0 | unmet_need==. | modern_contraception==.

proportion unmet_need if v013==1 | v013==2 [pweight = indiv_weight]
proportion unmet_need if v013==1 [pweight = indiv_weight]
proportion unmet_need if v013==2 [pweight = indiv_weight]
proportion demand_satisfied if v013==1 | v013==2 [pweight = indiv_weight]
proportion demand_satisfied if v013==1 [pweight = indiv_weight]
proportion demand_satisfied if v013==2 [pweight = indiv_weight]

Thank you so much!

Best regards,
Charlotte
Re: Getting Unmet Need & Demand Satisfied Estimates to Match StatCompiler for 5 Different Surveys [message #16323 is a reply to message #16217] Thu, 13 December 2018 15:19 Go to previous message
Trevor-DHS is currently offline  Trevor-DHS
Messages: 632
Registered: January 2013
Senior Member
Around the time that the revised unmet need definition was being produced, several recode datasets were produced containing early versions of the revised definition, and classify some non-currently married women differently from the final definition. Principally the difference is that in v626a certain non-currently married women are classified as "not married and not sexually active" before checking whether they are pregnant or postpartum amenorrheic. In the final revised definition, women who are pregnant or postpartum amenorrheic can have an unmet need even if they are currently "not married and not sexually active". For these surveys we recommend using the survey-specific code found at the bottom of the unmet need page on our website. This applies to Honduras 2011-12, Rwanda 2010-11, Uganda 2011, and to other surveys from roughly the same period.

For Nepal 2006 the numbers you quote from the Stata code are for currently married women, not all women. We should not be presenting data for all women in the STATcompiler as the questions needed for unmet need were only asked for currently married women - we will remove this from STATcompiler. The estimate currently in STATcompiler for all women would be an estimate if you assumed that all non-currently married women have no need.

For Niger 2006, when I run the survey-specific Stata code I match the STATcompiler estimates and not the Stata estimates that you provide.


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