Evidence map›Paper›PMID 30699207›Full record

ArticlePloS one2019

Strengths and limitations of computer assisted telephone interviews (CATI) for nutrition data collection in rural Kenya.

Christine Lamanna, Kusum Hachhethu, Sabrina Chesterman, Gaurav Singhal, Beatrice Mwongela, Mary Ng'endo, Silvia Passeri, Arghanoon Farhikhtah, Suneetha Kadiyala, Jean-Martin Bauer and 1 more

Open access · goldAbstract read
In one paragraph

Article in PloS one, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 18 papers.

0numbers the graph read from it
0cells of the map it votes in
18citing papers in PubMed
7.7field-weighted citation impact, top 3% of its field
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

18 citing papers in PubMed, 39 citations in OpenAlex.

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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

11 authors at 5 institutions in 5 countries.

Christine LamannaWorld Agroforestry Centre, Nairobi, Kenya.ORCID 0000-0002-6773-7352
Kusum HachhethuVulnerability, Analysis, and Mapping Unit, United Nations World Food Programme, Rome, Italy.
Sabrina ChestermanWorld Agroforestry Centre, Nairobi, Kenya.
Gaurav SinghalVulnerability, Analysis, and Mapping Unit, United Nations World Food Programme, Rome, Italy.
Beatrice MwongelaKenya Country Office, United Nations World Food Programme, Nairobi, Kenya.
Mary Ng'endoWorld Agroforestry Centre, Nairobi, Kenya.
Silvia PasseriVulnerability, Analysis, and Mapping Unit, United Nations World Food Programme, Rome, Italy.
Arghanoon FarhikhtahNutrition Division, United Nations World Food Programme, Rome, Italy.
Suneetha KadiyalaDepartment of Population Health, London School of Hygiene and Tropical Medicine, London, United Kingdom.
Jean-Martin BauerVulnerability, Analysis, and Mapping Unit, United Nations World Food Programme, Rome, Italy.
Todd S RosenstockCGIAR Research Program on Climate Change, Agriculture, and Food Security, Kinshasa, Democratic Republic of the Congo.
World Food Programme · ITLondon School of Hygiene & Tropical Medicine · GBWorld Agroforestry Centre · KEUnited Nations Environment Programme · KEUniversity of Kinshasa · CD

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Despite progress in fighting undernutrition, Africa has the highest rates of undernutrition globally, exacerbated by drought and conflict. Mobile phones are emerging as a tool for rapid, cost effective data collection at scale in Africa, as mobile phone subscriptions and phone ownership increase at the highest rates globally. To assess the feasibility and biases of collecting nutrition data via computer assisted telephone interviews (CATI) to mobile phones, we measured Minimum Dietary Diversity for Women (MDD-W) and Minimum Acceptable Diet for Infants and Young Children (MAD) using a one-week test-retest study on 1,821 households in Kenya. Accuracy and bias were assessed by comparing individual scores and population prevalence of undernutrition collected via CATI with data collected via traditional face-to-face (F2F) surveys. We were able to reach 75% (n = 1366) of study participants via CATI. Women's reported nutrition scores did not change with mode for MDD-W, but children's nutrition scores were significantly higher when measured via CATI for both the dietary diversity (mean increase of 0.45 food groups, 95% confidence interval 0.34-0.56) and meal frequency (mean increase of 0.75 meals per day, 95% confidence interval 0.53-0.96) components of MAD. This resulted in a 17% higher inferred prevalence of adequate diets for infants and young children via CATI. Women without mobile-phone access were younger and had fewer assets than women with access, but only marginally lower dietary diversity, resulting in a small non-coverage bias of 1-7% due to exclusion of participants without mobile phones. Thus, collecting nutrition data from rural women in Africa with mobile phones may result in 0% (no change) to as much as 25% higher nutrition estimates than collecting that information in face-to-face interviews.

Indexed as

Cell PhoneNutritional StatusAdolescentAdultChildFemaleHumansInterviews as TopicKenyaMaleMiddle AgedNutrition SurveysReproducibility of ResultsRural PopulationYoung Adult

Identifiers

PMID30699207
PMCPMC6353544
OpenAlexW2914270254

What OpenQuestion holds

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LicenceCC BY
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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.