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Emerging Themes in Epidemiology
Published in: Emerging Themes in Epidemiology 1/2016

Open Access 01-12-2016 | Analytic Perspective

Methods of nutrition surveillance in low-income countries

Authors: Veronica Tuffrey, Andrew Hall

Published in: Emerging Themes in Epidemiology | Issue 1/2016

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Abstract

Background

In 1974 a joint FAO/UNICEF/WHO Expert Committee met to develop methods for nutrition surveillance. There has been much interest and activity in this topic since then, however there is a lack of guidance for practitioners and confusion exists around the terminology of nutrition surveillance. In this paper we propose a classification of data collection activities, consider the technical issues for each category, and examine the potential applications and challenges related to information and communication technology.

Analysis

There are three major approaches used to collect primary data for nutrition surveillance: repeated cross-sectional surveys; community-based sentinel monitoring; and the collection of data in schools. There are three major sources of secondary data for surveillance: from feeding centres, health facilities, and community-based data collection, including mass screening for malnutrition in children. Surveillance systems involving repeated surveys are suitable for monitoring and comparing national trends and for planning and policy development. To plan at a local level, surveys at district level or in programme implementation areas are ideal, but given the usually high cost of primary data collection, data obtained from health systems are more appropriate provided they are interpreted with caution and with contextual information. For early warning, data from health systems and sentinel site assessments may be valuable, if consistent in their methods of collection and any systematic bias is deemed to be steady. For evaluation purposes, surveillance systems can only give plausible evidence of whether a programme is effective. However the implementation of programmes can be monitored as long as data are collected on process indicators such as access to, and use of, services. Surveillance systems also have an important role to provide information that can be used for advocacy and for promoting accountability for actions or lack of actions, including service delivery.

Conclusion

This paper identifies issues that affect the collection of nutrition surveillance data, and proposes definitions of terms to differentiate between diverse sources of data of variable accuracy and validity. Increased interest in nutrition globally has resulted in high level commitments to reduce and prevent undernutrition. This review helps to address the need for accurate and regular data to convert these commitments into practice.
Footnotes
1
Following registration, CMAM report software can be downloaded from http://​www.​cmamreport.​com/​.
 
2
While the SQUEAC, SLEAC and S3M coverage methods undoubtedly provide useful contextual information for refining service delivery approaches, there are outstanding questions on the validity of the quantitative component of these methods. Several agencies and individuals have voiced a need to compare the sampling approach and analysis to other methods.
 
3
In fact often the design of the system is such that the findings are statistically representative of the individual site, but the site is acting as a sentinel site for the larger geographical area. For example repeated surveys can provide representative data of a certain slum area, and the slum area acts a sentinel site for the larger urban area. Thus the application of the term ‘sentinel’ depends on the level at which one can validly claim that the findings are statistically representative.
 
4
The CDC ‘2 surveys’ calculator is helpful as it can be used to examine the effect of different survey designs on the sample size required http://​www.​cdc.​gov/​globalhealth/​healthprotection​/​errb/​researchandsurve​y/​calculators.​htm.
 
5
This pilot surveillance system was short-lived. Despite the system having been designed to be as simple as possible, it proved to be difficult to implement in practice.
 
6
This is true as long as the mean Z score is less than −2. In the exceptional case that the mean Z score is less than −2 (that is, below the threshold to define malnutrition), as variance increases the estimate of prevalence will decrease [38, p. 19]. The proportion of all malnourished children that are severely malnourished also increases.
 
7
For calculations of necessary sample size, it is recommended to seek guidance from a statistician or a nutritionist with extensive experience in survey design.
 
8
Anthropometric data from health systems are most useful for detecting trends rather than estimating prevalence rates, so with respect to deriving an overall score to assess data quality, the size of systematic errors is less important for secondary data than for survey data. It is nonetheless important to monitor systematic errors, since changes in size and direction of bias will impact on comparability of data over time.
 
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Metadata
Title
Methods of nutrition surveillance in low-income countries
Authors
Veronica Tuffrey
Andrew Hall
Publication date
01-12-2016
Publisher
BioMed Central
Published in
Emerging Themes in Epidemiology / Issue 1/2016
Electronic ISSN: 1742-7622
DOI
https://doi.org/10.1186/s12982-016-0045-z

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