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Estimating and Matching Under5 Mortality by cluster units [message #8516]

Sat, 07 November 2015 20:11

MildredA
Messages: 3
Registered: November 2015
Location: United Kingdom

Member

Hello Everyone,

Apologies for asking what could be basic questions to many. This is because I am new to DHS data and statistics as a whole.

I need help with estimating under5 mortality rates for all survey clusters for Nigerian DHS since 2003. I have studied the guide to dhs statistics and the recode manual and could not understand it. I would be very grateful if anyone could help me identify the variables and the steps/equation I need to compute U5 mortality rates in very simple terms in SPSS.

Also, I am not sure which recode file (birth, household, individual or children) to use to generate the U5 mortality rates. How do I aggregate categorical variables such as ethnicity and age groups by clusters such that, each category becomes a new variable expressed in percentages for all cluster points.

Since, I will be merging data from 2003-2013, I will like to know whether the same sample clusters are used to collect information for the the three DHS years in Nigeria.

Please help me out, my dissertation is hanging on this.

Kind regards

Mildred Ajebon

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Re: Estimating and Matching Under5 Mortality by cluster units [message #8523 is a reply to message #8516]

Sun, 08 November 2015 16:56

Reduced-For(u)m
Messages: 292
Registered: March 2013

Senior Member

Mildred,

There is a lot to answer here, but a question first:

Do you want to estimate "cluster" (meaning Primary Sampling Unit) averages of child mortality? That will be impossible given cluster-specific sample sizes. In general, you need thousands of children to accurately estimate that rate, and there are only a handful of children per cluster (more if you go way back in time, but then you are getting cluster- and time- differences).

Also - DHS sampling units generally changes from survey to survey, so you can't usually compare them over time.

If I'm wrong about either of these assumptions regarding what you are doing, let me know. If not, I don't think this project is feasible.

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Re: Estimating and Matching Under5 Mortality by cluster units [message #8524 is a reply to message #8523]

Sun, 08 November 2015 18:25

MildredA
Messages: 3
Registered: November 2015
Location: United Kingdom

Member

Thanks a million for your response.

Firstly, the most important huddle for me to cross at this point is to generate proportion of deaths (under5, maternal and if possible, adult mortality)for different geographical units within Nigeria. That is, the risk of under5, maternal and adult mortality in area clusters/LGAs. Technically, I want to be able to generate a comparative measure of mortality for geographical areas within Nigeria and perhaps, other DHS countries. This will help me understand within-country variation in health.

I would be grateful if anyone could help suggest which recode file to use, what variables to include and how to compute these in SPSS. Merging data over time was something is not the central theme of my work. I could do away with that. It was something extra I thought I could do.

Secondly, if cluster points are not maintained across surveys, what is the best way to compare risk of dying across geographical areas for the different survey years? Is it feasible to use Local Government Area (LGA)boundaries to map the distribution of under5 mortality?. I am a geographer, it is important for me to be able to map results for the smallest area unit possible for visualization.

Regards

[Updated on: Sun, 08 November 2015 18:56]

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Re: Estimating and Matching Under5 Mortality by cluster units [message #8606 is a reply to message #8524]

Fri, 20 November 2015 16:12

Trevor-DHS
Messages: 805
Registered: January 2013

Senior Member

You cannot compute the mortality rates at the level of LGAs. The sample was not designed to be representative at these levels and the sample size is too small to give you valid results at this level. The mortality estimates can only be validly produced for the disaggregations presented in the report.

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