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Re: Calculating Under 5 Mortality Rate [message #10880 is a reply to message #10874]

Wed, 28 September 2016 01:25

lonrwo1
Messages: 3
Registered: September 2016

Member

Thank you Liz/Dr Pullum,

Thank you very much indeed for your reply. Unfortunately I'm working to an end of the week deadline, so the stata program in two weeks will sadly be of no use to me.

My understanding was that the code I am running to generate U5 mortality rate matches what is described by Dr Tom in his post and also on section C page 94 of the Guide to DHS Statistics.

gen hypage=(v008-b3)
gen survivelength=.
replace survivelength=hypage
replace survivelength=b7 if b5==0
gen dead=(b5==0)
ltable survivelength dead if hypage <60, int(0,1,3,6,12,24,36,48,60) failure

When running the above code I get the following lifetable output

Beg. Cum. Std.
Interval Total Deaths Lost Failure Error [95% Conf. Int.]
------------------------------------------------------------ -------------------
0 1 6079 176 61 0.0291 0.0022 0.0252 0.0337
1 3 5842 38 219 0.0355 0.0024 0.0311 0.0405
3 6 5585 38 315 0.0423 0.0026 0.0375 0.0477
6 12 5232 47 652 0.0515 0.0029 0.0461 0.0575
12 24 4533 53 1119 0.0641 0.0033 0.0579 0.0710
24 36 3361 14 1147 0.0688 0.0036 0.0622 0.0761
36 48 2200 6 1093 0.0722 0.0038 0.0651 0.0800
48 60 1101 1 1100 0.0739 0.0042 0.0662 0.0825
------------------------------------------------------------ -------------------

You can see that the cumulative failure for the last interval 48 - 60 months is 0.739, x 1000 =73.9 or 74 per 1,000. This is the U5 mortality rate reported in the KDHS 2009 - Fig 8.2 page 107, so this seems to me, to confirm that this is the correct method to use. My confusion comes from the fact that when including other variables e.g. by(province) to the ltable code i.e.

ltable survivelength dead if hypage <60, by (province) int(0,1,3,6,12,24,36,48,60) failure

the U5 rates (cumulative failure for last age interval x 1,000) for each province are;

1. very different from what is reported in the report(## per 1,000)

2. alongside being different the observed difference in rates is also not proportionate to what is reported in the report e.g. Central Province (No. 2) is 51 per 1,000 in the report but increases to 79 when using the above ltable, compared to Nyanza province (No.5) which is 151 per 1,000 in the report but reduces to 126 when using the above ltable method. It something to do with the way DHS calculate the stratum specific (e.g. province) rates?

I would be most grateful if you could provide any further insight into this apparent discrepancy.

Kind Regards,

Rob

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[Message index]

		Calculating Under 5 Mortality Rate By: gemma1224 on Fri, 11 March 2016 11:46
		Re: Calculating Under 5 Mortality Rate By: Bridgette-DHS on Tue, 22 March 2016 14:41
		Re: Calculating Under 5 Mortality Rate By: peterliberia on Fri, 25 March 2016 05:19
		Re: Calculating Under 5 Mortality Rate By: Liz-DHS on Tue, 29 March 2016 14:55
		Re: Calculating Under 5 Mortality Rate By: dhs_bee on Wed, 01 June 2016 21:31
		Re: Calculating Under 5 Mortality Rate By: Liz-DHS on Wed, 01 June 2016 23:15
		Re: Calculating Under 5 Mortality Rate By: lonrwo1 on Mon, 26 September 2016 15:50
		Re: Calculating Under 5 Mortality Rate By: lonrwo1 on Mon, 26 September 2016 15:54
		Re: Calculating Under 5 Mortality Rate By: Liz-DHS on Tue, 27 September 2016 10:08
		Re: Calculating Under 5 Mortality Rate By: Liz-DHS on Tue, 27 September 2016 12:16
		Re: Calculating Under 5 Mortality Rate By: lonrwo1 on Wed, 28 September 2016 01:25
		Re: Calculating Under 5 Mortality Rate By: Liz-DHS on Mon, 03 October 2016 14:07
		Re: Calculating Under 5 Mortality Rate By: Olutosin on Mon, 10 October 2016 20:54
		Re: Calculating Under 5 Mortality Rate By: Bridgette-DHS on Tue, 11 October 2016 07:24
		Re: Calculating Under 5 Mortality Rate By: Olutosin on Thu, 20 October 2016 17:56
		Re: Calculating Under 5 Mortality Rate By: harry_92 on Sun, 25 November 2018 15:39

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