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Disconnection between CHVs screening and SMART surveys?

This question was posted the Assessment and Surveillance forum area and has 2 replies.

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Tammam Ali Mohammed Ahmed

Nutrition Specialist/ Save the Children

Normal user

3 Mar 2019, 12:08

Dear All,
If we suggest we are working in one district and the CMAM program is for one year. Total Health Facilities (HFs) in the district is 20 and our program is targeting only 10 HFs. Imagine if we conduct nutrition screening (combined MUAC and W/H study) so all children are screened within the 10 HFs catchment population.
For Example :
1. Total number of children under five is 3,124
2. Total SAM is 25
3. Total MAM is 450
4. Total Normal Children is 2,649

As per Prevalence definition (# of people in sample with characteristic/ Total # of people in sample)
so the:
- SAM Prevalence is 0.8
- MAM Prevalence is 14.4

I have compared this to our SMART survey and I found SAM and MAM rates in this district (all the 20 HFs) are 0.6 and 9.4, respectively.
- Do you think our calculation is high because of new cases now (incidence-like cases) not included in the SMART survey (prevalence only based method)?
- Do you see any disconnection between our program data and the SMART survey despite the different population size (in our targeted 10 HFs only 3,124 CU5)
- In terms of impact measurement and study, Do you think is it easy to measure the impact of our program study or of SMART survey results?

Sameh Al-Awlaqi

Public Health and Nutrition Consultant

Normal user

3 Mar 2019, 16:33

Hi Tammam,

You would need a similar comparator (previous SMART surveys) to draw a comparison. In your case, I assume the nutrition screening is not the same as SMART in terms of methodology.

Regarding the SAM/MAM prevalence of SMART, you would need to check the Confidence Interval (C.I.) and design effect to explain the prevalence. If I were a manager of that project, I would not draw conclusions on the impact of your project based on the data you've provided only. To help me do so, I would need a record of programme admission trends and performance indicators over time, and to compare repeated SMART reports. These data, among other indicators, should be analysed within your desired programme impact which was set during the project inception (logical framework).

I am quoting myself below-you might find the comment relevant to your case:

"You can check if there a statistical significance between the prevalence of the two surveys by using the CDC statistical calculator for two surveys. It comes with the SMART training package (managers training), please check the annexes on the SMART methodology website. The difference will be mainly based on the interpretation of the p. value as my colleagues indicated above. C.I. overlap is one quick way to do it as well.

You have to consider other circumstances when you draw comparisons, such as seasonality, sample size, design effect, other nutritional deficiencies, livelihood status or other health interventions in the area, and whether CMAM services have expanded since the last survey or not, or if there was an outbreak of acute watery diarrhoea since the last survey etc. You may wish to talk to health professionals and community members to get insight into your interpretation.

I have worked on SMART surveys and CMAM in Darfur and Yemen, I know sometimes you feel pressured to find and report progress in the nutrition status of children within your programme areas to satisfy donors. SMART reports when they are not consistent over time they may cause confusion and frustration. However, when you look at your programme indicators, admission trends and performance, you should know if your intervention is working or if it needs a bit of improvement. In all cases, interpret your SMART findings based on your context, you and your field team could tell if the nutrition situation is getting worse."

Please check the thread for the full discussion.



Tammam Ali Mohammed Ahmed

Nutrition Specialist/ Save the Children

Normal user

5 Mar 2019, 07:26

Dear Dr.Sameh,
I am appreciating your fruity discussion and analysis. In Yemen context and in the districts where our projects are located SMART surveys are not usually constantly conducted and as partners you cannot do SMART survey for some districts in one governorate. It is only conducted for the whole governorate.
I am suggesting for NGOs to do the assessment (massive screening for CU5 and PLW and linked to Food Consumption Score, FCS) in their targeted district and by this the NGO can have the accurate baseline of affected children/PLW and can monitor the progress easily in this district. I think even the impact can be easily monitored.

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