↓ Skip to main content

Methods of nutrition surveillance in low-income countries

Overview of attention for article published in Emerging Themes in Epidemiology, March 2016
Altmetric Badge

About this Attention Score

  • Good Attention Score compared to outputs of the same age (70th percentile)

Mentioned by

policy
1 policy source
twitter
3 X users

Citations

dimensions_citation
37 Dimensions

Readers on

mendeley
209 Mendeley
You are seeing a free-to-access but limited selection of the activity Altmetric has collected about this research output. Click here to find out more.
Title
Methods of nutrition surveillance in low-income countries
Published in
Emerging Themes in Epidemiology, March 2016
DOI 10.1186/s12982-016-0045-z
Pubmed ID
Authors

Veronica Tuffrey, Andrew Hall

Abstract

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. 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. 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.

X Demographics

X Demographics

The data shown below were collected from the profiles of 3 X users who shared this research output. Click here to find out more about how the information was compiled.
Mendeley readers

Mendeley readers

The data shown below were compiled from readership statistics for 209 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
South Africa 1 <1%
Unknown 208 100%

Demographic breakdown

Readers by professional status Count As %
Student > Master 47 22%
Student > Bachelor 22 11%
Researcher 21 10%
Student > Ph. D. Student 14 7%
Other 9 4%
Other 34 16%
Unknown 62 30%
Readers by discipline Count As %
Nursing and Health Professions 46 22%
Medicine and Dentistry 27 13%
Social Sciences 20 10%
Agricultural and Biological Sciences 13 6%
Environmental Science 5 2%
Other 30 14%
Unknown 68 33%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 5. This is our high-level measure of the quality and quantity of online attention that it has received. This Attention Score, as well as the ranking and number of research outputs shown below, was calculated when the research output was last mentioned on 19 November 2023.
All research outputs
#6,997,461
of 25,286,324 outputs
Outputs from Emerging Themes in Epidemiology
#65
of 155 outputs
Outputs of similar age
#90,596
of 307,590 outputs
Outputs of similar age from Emerging Themes in Epidemiology
#1
of 2 outputs
Altmetric has tracked 25,286,324 research outputs across all sources so far. This one has received more attention than most of these and is in the 72nd percentile.
So far Altmetric has tracked 155 research outputs from this source. They typically receive a lot more attention than average, with a mean Attention Score of 14.1. This one has gotten more attention than average, scoring higher than 56% of its peers.
Older research outputs will score higher simply because they've had more time to accumulate mentions. To account for age we can compare this Altmetric Attention Score to the 307,590 tracked outputs that were published within six weeks on either side of this one in any source. This one has gotten more attention than average, scoring higher than 70% of its contemporaries.
We're also able to compare this research output to 2 others from the same source and published within six weeks on either side of this one. This one has scored higher than all of them