Evidence map›Paper›PMID 40366099›Full record

ArticlePublic health nutrition2025

Food insecurity, social and behaviour change and distribution model: key considerations for implementation of small quantity lipid-based nutrient supplement programmes.

Akriti Singh, Kali Erickson, Kavita Sethuraman

Abstract read
In one paragraph

Article in Public health nutrition, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.

0numbers the graph read from it
0cells of the map it votes in
2citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

2 citing papers in PubMed.

  1. Trial
  2. Article
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

3 authors.

Akriti SinghHelen Keller International US, New York, NY, USA.
Kali EricksonIndependent Consultant, Guatemala, Guatemala.
Kavita SethuramanUSAID Advancing Nutrition, Arlington, VA, USA.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

objectiveThe objectives of this study were to (1) document factors that promoted or hindered the successful implementation of small quantity lipid-based nutrient supplements (SQ-LNS) for children 6-23 months and pregnant and lactating women (PLW) and (2) gather programme staff perspectives on considerations for expanding SQ-LNS programmes in their context.

designWe used qualitative methods to interview programme staff (

settingThe study was conducted in SQ-LNS programme sites in Honduras, Niger and Somalia.

resultsWe found high acceptability of SQ-LNS among caregivers of children 6-23 months and PLW women. However, caregivers and PLW were dissatisfied with the size of the product in Niger and Somalia and PLW disliked the aftertaste of iron in Honduras. In Somalia, PLW referred to high levels of food insecurity. We also found variation in how the partners designed their SQ-LNS programmes (e.g. enrolment and exit criteria), the level of communication around SQ-LNS and problem-solving to support appropriate use of SQ-LNS. Partners tracked anthropometric measurements in all countries and used the information to assess changes and, in some cases, noted improvements in child anthropometry and vaccination rates.

conclusionsProgrammes need to consider several operational factors during implementation, such as securing household food access in highly food-insecure areas, counselling on the use of SQ-LNS and evidence-based criteria for enrolment, exit and supplementation duration.

Indexed as

Dietary FatsDietary SupplementsFood InsecurityAdultCaregiversFemaleFocus GroupsHondurasHumansInfantInfant Nutritional Physiological PhenomenaLactationMaleNigerPregnancySomaliaDietary FatsChildLactating womenLipid-based nutrient supplementsPregnantSQ-LNS

Identifiers

PMID40366099
PMCPMC12100554

What OpenQuestion holds

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Registered trials

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.