Estimating the Target Under Five Population for Feeding Programmes in Emergencies
By Anna Taylor
Anna Taylor has been the nutritional advisor for Save the Children UK for a number of years. She has recently taken up a new post of Head of Basic Services in the Policy and Communication Department of SCUK.
Thanks to Kate Sadler and Mary Corbett for discussions on this issue.
This article discusses the problem of accurately estimating the target population for the planning of emergency nutrition programmes and presents a tool developed by Save the Children UK aimed at improving the process.
School feeding recipients in Zimbabwe
The problem of not finding the predicted number of malnourished children when you start a nutrition programme is widely reported. This can often be because programme coverage is poor and outreach systems are weak, because the response is late and malnutrition rates have spontaneously improved or because the target population was overestimated in the first place. This latter problem will be dealt with in this article, drawing on the experience of Save the Children UK's emergency nutrition programmes in Darfur, Sudan (2002) and Gola Oda, Ethiopia (2003).
The accuracy of the estimate of target population size has a knock-on effect on the size of the budget requested in the proposal, the design of the programme (to maximise coverage and speed of operations) the capacity put in place at each distribution point or feeding centre and the morale of staff as they seek to reach all those eligible for the programme.
Estimating the target population in Darfur, Sudan
When Save the Children UK developed proposals for emergency feeding in Darfur, Sudan in 2002, it estimated that the drought-affected population living in the eight rural councils was 476,195 people. The number of direct beneficiaries of the project was estimated to be 43,724 people of whom there were 32,528 moderately malnourished children, 6,434 severely malnourished children and 4,762 pregnant or lactating women.
Mothers and children waiting in Targetted feeding programme.
The proposal was written to cover eight rural councils but due to funding constraints was reduced to the five worst affected. The figures for the numbers of malnourished children for the programme were calculated as follows:
The total population in each rural council was multiplied by 17% to obtain the number of children under five years. The number of children under five years was then multiplied by the percentage of children found to be moderately and severely malnourished in the survey: the figure was different for each rural council because separate surveys were done for each (see Table 1). This number was then doubled as it was anticipated that the project would last for 4 months and would therefore be able to admit two rounds of children in the time it was open. The inbuilt assumptions were that the rate at which children were becoming malnourished would not change, that the proportion of malnourished children at the start of the programme would all be admitted and that admissions would continue throughout the programme as more children became malnourished.
|Table 1: Prevalence of malnutrition in surveys conducted in April / May 2002|
|Food Economy Zone||Goz||Pastoral|
|Prevalence of global malnutrition (<-2 z-score and/or oedema)||35 (31.6-38.4)||25.4 (22.3-28.5)||25.4 (22.3-28.5)||23.7 (20.6-26.7)||-|
|Prevalence of severe malnutrition (<-3 z-score and/or oedema)||6.2 (4.5-7.9)||2.5 (1.1-3.1)||2.5 (1.1-3.1)||2.1 (1.1-3.1)||-|
|Table 2: Predicted beneficiaries and Actual beneficiaries of the Gola Oda nutrition programme 2003|
|Predicted numbers||Actual numbers||
As a percentage of predicted numbers
|Drought-affected population of the district||115,000|
|Direct beneficiaries of the project||6233||2935||47%|
|Moderately malnourished children||4,600||2390||52%|
|Severely malnourished children||460||232||50%|
|Pregnant or lactating malnourished women||1173||313||27%|
Problems with the method of estimation
There were however certain problems with the calculation of numbers of malnourished people resulting in over-estimations of the numbers of beneficiaries expected in both programmes.
- The multiplier (17%) used for children under five includes children <6 months which the programme did not admit (except in very small numbers into the hospital).
- Weight for height z score was used in the surveys to estimate the number of malnourished children while children were actually admitted into the programme using weight for height percent of the median. The latter measure leads to lower rates while the former measure is routinely used for survey reporting.
- It was assumed that the rate of malnutrition would remain constant (at the rates recorded in the April surveys) thereby justifying a doubling of the number of beneficiaries through the life of the programme. In fact, the anthropometric surveys in November (1 month after programme start) showed a significant reduction in the levels of malnutrition compared to those found preprogramme.
Preparing food in Salima
By the end of November (2.5 months into programme implementation) the programme had only reached 368 severely malnourished children, 5590 moderately malnourished children and 3310 pregnant and lactating women.
Lesser degrees of over-estimation were found in Ethiopia where a recent evaluation of Save the Children's emergency nutrition response in Gola Oda showed (Table 2) that only about half of those predicted to be in need of the programme were actually reached even though the programme coverage was estimated by coverage survey to be 80%.
Getting a more accurate estimate
Based on the problems identified in these two evaluations Save the Children has developed a spreadsheet to help programme staff to more accurately estimate the size of the target population for proposals and for planning programme design.
In order to make this calculation the following parameters are needed:
- Size of the population
- Proportion of the population aged < 5 years and > 6 months (aged 6-59 months)
- Prevalence of moderate and severe malnutrition in percentage of the median.
- Coverage expected. The level of coverage which can realistically be achieved will vary according to the context. The Sphere handbook states that, for the standards on malnutrition to be addressed, the coverage of supplementary and therapeutic feeding programmes should be more than 50% in rural areas, more than 70% in urban areas and more than 90% in a camp situation. (The Sphere Project, 2004).
The spreadsheet shown on right presents example data for a total population of 300,000 with 24% moderate malnutrition and 4% severe malnutrition. The expected coverage is 80% for supplementary feeding and 60% for therapeutic feeding because the supplementary feeding programme will have, in this example, a larger number of distribution points. The spreadsheet indicates that the estimated size of the target population is 8640 for targeted supplementary feeding (with a range of 7920-9360) and a target population of 1080 for therapeutic feeding (with a range of 840-1620).
Limitations of the spreadsheet
The spreadsheet does not take into account the incidence of malnutrition i.e. the number of new cases of malnutrition which appear after the start of the programme. The estimated target population calculated only includes those identified as malnourished on the day of the anthropometric survey (the prevalence). It does not take into account any new cases of malnutrition which may develop during the programme implementation. The incidence of malnutrition will depend largely on the extent to which the emergency response prevents new cases from occurring as well as the expected duration of the emergency, e.g. when a new harvest is expected. For example, incidence is likely to be much lower if measures are in place to prevent infection from occurring (e.g. water and sanitation) and to address household food insecurity (such as a general ration, livestock interventions, cash etc). In the current version the spreadsheet does not make an adjustment for programmes which rely on two stage screening as part of the admission process. For example, if a programme relied on community workers to visit house to house and refer children below a certain MUAC cut-off - some of those children eligible for the programme would be automatically excluded thereby affecting the coverage which can ultimately be achieved. This is because MUAC and weight for height do not identify the same children as malnourished. The spreadsheet could be easily adjusted to take this into account.
In addition the spreadsheet relies heavily on the accuracy of the estimates of total population and prevalence of malnutrition. Population estimates are often notoriously inaccurate and often have to be validated in the field through door counts, re-registration etc. Migration complicates this problem further and if the population is mobile or people are being continually displaced, any estimates of the target population will be subject to change.
The accuracy of the prevalence of malnutrition equally relies on a representative sample having been taken over an area where the prevalence of malnutrition is believed to be generally uniform. Standard methodologies should be applied to ensure the prevalence of malnutrition is reliable for programme planning (for example see Save the Children UK, 2004, Emergency nutrition assessment: guidelines for field workers. In press).
For further details or a copy of the freely available spreadsheet contact Anna Taylor, email: email@example.com
The Sphere Project 2004, Humanitarian Charter and Minimum Standards in Disaster Response, 2nd edition
Save the Children UK 2004, Emergency Nutrition Assessment: guidelines for field workers
More like this
Abduljebar Osman Abdulahi and Selamawit Yilma Abduljebar Osman Abdulahi is the Project Nutrition Coordinator for International Medical Corps in Oromia region East Hararghe...
By Anne-Marie Mayer, Mark Myatt, Myriam Ait Aissa and Nuria Salse Anne-Marie Mayer is a technical consultant for this project and carried out the first field test in Mali with...
By Eva Vicent and Núria Salse Eva Vicent has a background in nursing studies in the University of Valencia and is currently working for Action Against Hunger as Nutrition...
By Kate Sadler (Valid International) and Anna Taylor (SC-UK) People waiting at a clinic in Darfur, North Sudan. Child eating plumpynut® in Darfur, North Sudan. North Darfur...
By Victoria Sibson Victoria Sibson has been the emergency nutrition adviser for Save the Children UK since April 2007, with a focus on treatment of acute malnutrition and...
By Pushpa Acharya and Eric Kenefick Pushpa Acharya is currently working as Head of Nutrition for the World Food Programme in Sudan. She has a PhD in Human Nutrition from the...
By Ernest Guevarra, Saul Guerrero, and Mark Myatt Ernest Guevarra leads Valid International's coverage assessment team. He has formal training as a physician and a public...
Glossary ACF Action Contre la Faim CHA Community Health Assistant CHAM Christian Health Association of Malawi CNW Community Nutrition Worker CTC Community Therapeutic...
Terms of Reference Purpose To Design, Implement and Support Capacity Development of Nutrition Coverage Assessment using the SQUEAC Methodology Location Daynile, Dollow,...
by Jane Hanon (Terre Des Hommes, Gaza) The Gaza strip lies on the Mediterranean Coast between Egypt and Israel. It has an area of 360 square kilometres and just under one...
By Saskia van der Kam, MSF Holland, Senior Nutritionist This is the second in a series of pieces published in Field Exchange* which summarises key sections of the newly...
View of the Mandera Camp Lourdes-Vazquez-Garcia worked for MSF Spain in the Mandera feeding centres during the period covered by this article. She subsequently qualified with...
3.1 CTC in Ethiopia- Working from CTC Principles Isolated village in the highlands of South Wollo, Ethiopia. By Kate Golden (Concern Ethiopia) and Tanya Khara (Valid...
By Lily Schofield, Selome Gizaw Lalcha and Terefe Getachew Lily Schofield has worked in many countries in Africa and Asia as a nutrition consultant. She has been involved in...
By Ed Walker (Tearfund) Beneficiaries collecting their general ration in South Sudan. Tearfund has been working in Northern Bahr el Ghazal, southern Sudan, in the nutrition...
By Hassan Taifour Hassan Taifour is the Emergency Response Nutritionist for SC(UK). He graduated from the Faculty of Agriculture, University of Khartoum in 1985 and completed...
By Ruba Ahmad Abu-Taleb Ruba Ahmad Abu-Taleb is Nutrition coordinator at Jordan Health Aid Society (JHAS). She liaises between national and international NGOs and JHAS...
By Simon Kiarie Karanja Simon Karanja is currently the regional nutrition advisor with GOAL in East Africa. Previously he worked as the CTC Coordinator for GOAL Ethiopia and...
FEX: RAM-OP: A rapid assessment method for assessing the nutritional status, vulnerabilities, and needs of older people in emergency and development settings
By Pascale Fritsch (HelpAge International), Katja Siling (VALID International), and Mark Myatt (Brixton Health) Dr Pascale Fritsch is an experienced public health specialist....
by Beth Matthews, Maureen Billiet (Concern field staff Angola) Annalies Borrell (Concern chief nutritionist Dublin). In children the three most commonly used anthropometric...
Reference this page
Anna Taylor (2004). Estimating the Target Under Five Population for Feeding Programmes in Emergencies. Field Exchange 23, November 2004. p17. www.ennonline.net/fex/23/estimating