Evidence map›Paper›PMID 36584156›Full record

ArticlePloS one2022

The prevalence and socio-demographic associations of household food insecurity in seven slum sites across Nigeria, Kenya, Pakistan, and Bangladesh. A cross-sectional study.

Clara Spieker, Anthony A Laverty, Oyinlola Oyebode, Improving Health in Slums Collaborative

Abstract read
In one paragraph

Article in PloS one, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 papers.

0numbers the graph read from it
0cells of the map it votes in
5citing 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

5 citing papers in PubMed.

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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

4 authors.

Clara SpiekerImperial College London, London, United Kingdom.
Anthony A LavertyImperial College London, London, United Kingdom.
Oyinlola OyebodeWolfson Institute of Population Health, Queen Mary University of London, London, United Kingdom.ORCID 0000-0003-0925-9839
Improving Health in Slums Collaborative

Funding

Department of Health
6 · The paper itself

Abstract

Although the proportion of people living in slums is increasing in low- and middle-income countries and food insecurity is considered a severe hazard for health, there is little research on this topic. This study investigated and compared the prevalence and socio-demographic associations of household food insecurity in seven slum settings across Nigeria, Kenya, Pakistan, and Bangladesh. Data were taken from a cross-sectional, household-based, spatially referenced survey conducted between December 2018 and June 2020. Household characteristics and the extent and distribution of food insecurity across sites was established using descriptive statistics. Multivariable logistic regression of data in a pooled model including all slums (adjusting for slum site) and site-specific analyses were conducted. In total, a sample of 6,111 households were included. Forty-one per cent (2,671) of all households reported food insecurity, with varying levels between the different slums (9-69%). Household head working status and national wealth quintiles were consistently found to be associated with household food security in the pooled analysis (OR: 0·82; CI: 0·69-0·98 & OR: 0·65; CI: 0·57-0·75) and in the individual sites. Households which owned agricultural land (OR: 0·80; CI: 0·69-0·94) were less likely to report food insecurity. The association of the household head's migration status with food insecurity varied considerably between sites. We found a high prevalence of household food insecurity which varied across slum sites and household characteristics. Food security in slum settings needs context-specific interventions and further causal clarification.

Indexed as

Food SupplyPoverty AreasBangladeshCross-Sectional StudiesFamily CharacteristicsFood InsecurityHumansKenyaNigeriaPakistanPrevalenceSocioeconomic Factors

Identifiers

PMID36584156
PMCPMC9803099

What OpenQuestion holds

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LicenceCC BY
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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.