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Calculating Pregnant and Lactating Women To Target in Supplementary Feeding Program

This question was posted the Prevention and treatment of moderate acute malnutrition forum area and has 3 replies. You can also reply via email – be sure to leave the subject unchanged.

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Anonymous 422

Normal user

22 Dec 2014, 05:03

Is there a easy/simple way of calculating number of pregnant women to target in Supplementary feeding. the prevalence of pregnant women < 21 MUAC is known and entire population is known

Mark Myatt

Consultant Epideomiologist

Frequent user

22 Dec 2014, 17:18

Is this document useful?

Shishay

Normal user

13 Jan 2015, 21:55

Dear Mark,

The document is really helpful thank you. But here all surveys are done using under five to get the prevalence, so how do we predict the prevalence P&LW mainly for TSFP not BSFP

Thank you

Mark Myatt

Consultant Epideomiologist

Frequent user

15 Jan 2015, 13:58

It seems that you are asking how to estimate prevalence of GAM in pregnant and lactating women (PLW) from the prevalence of GAM in children aged 6-59 months. Is that correct?

At a "conceptual" level we might expect the two prevalences to be linked to each other but reality might be different. I have seen (e.g.) mothers restrict intake to protect their children from malnutrition. I have also seen mothers restrict their intake to produce a small foetus in order to reduce the likelihood of a birth accident. Also, there will be problems of using different indicators in children and PLW with W/H being strongly influenced by body shape. I know of no attempt to model the relationship between the two prevalences.

This means that you meed to do a survey of PLWs. The survey sample size need not be large because (1) there is usually a limited number of PLWs in the program area at any one time so you can apply a finite population correction to sample size calculations (see here), and (2) you can estimate prevalence efficiently using the PROBIT estimator. I think a sample size of about n = 150 would be fine. Using this method with older people works well with n = 192 collected as m = 16 clusters of n = 12 older people).

I hope this is of some help.

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