Evidence map›Paper›PMID 36721115›Full record

ArticleBMC public health2023

Exploring customers' perceptions of food adulteration at bazaars and supermarkets in Dhaka, Bangladesh; a qualitative exploration.

Dalia Yeasmin, Musa Baker, Abu-Hena Mostofa Kamal, Md Saiful Islam, Mahbubur Rahman, Peter J Winch, Leanne Unicomb

Abstract read
In one paragraph

Article in BMC public health, 2023. 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. Article
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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

7 authors.

Dalia YeasminEnvironmental Interventions Unit, Infectious Diseases Division, International Centre for Diarrhoeal Disease Research (icddr,b), 68 Shaheed Tajuddin Ahmed Sarani, 1212, Dhaka, Bangladesh. daliay@icddrb.org.
Musa BakerEnvironmental Interventions Unit, Infectious Diseases Division, International Centre for Diarrhoeal Disease Research (icddr,b), 68 Shaheed Tajuddin Ahmed Sarani, 1212, Dhaka, Bangladesh.
Abu-Hena Mostofa KamalEnvironmental Interventions Unit, Infectious Diseases Division, International Centre for Diarrhoeal Disease Research (icddr,b), 68 Shaheed Tajuddin Ahmed Sarani, 1212, Dhaka, Bangladesh.
Md Saiful IslamEnvironmental Interventions Unit, Infectious Diseases Division, International Centre for Diarrhoeal Disease Research (icddr,b), 68 Shaheed Tajuddin Ahmed Sarani, 1212, Dhaka, Bangladesh.
Mahbubur RahmanEnvironmental Interventions Unit, Infectious Diseases Division, International Centre for Diarrhoeal Disease Research (icddr,b), 68 Shaheed Tajuddin Ahmed Sarani, 1212, Dhaka, Bangladesh.
Peter J WinchJohns Hopkins Bloomberg School of Public Health, Baltimore, MD, USA.
Leanne UnicombEnvironmental Interventions Unit, Infectious Diseases Division, International Centre for Diarrhoeal Disease Research (icddr,b), 68 Shaheed Tajuddin Ahmed Sarani, 1212, Dhaka, Bangladesh.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundFood adulteration is an increasingly recognized global public health problem. In low- and middle-income countries like Bangladesh, adulteration is difficult to detect and respond to. We explored customers' perceptions on food adulteration, perception of risk and connections between information, participant characteristics and patterns of adulterated food concerns that impact risk perception in urban Bangladesh.

methodsA formative study was conducted in Dhaka, between June and August 2015 at a supermarket and a wet market. We explored community awareness and response to chemical contaminants (adulterants) among participants from a range of socio-economic backgrounds. The team conducted 38 in-depth interviews with 12 customers and 4 staff from a supermarket, and 12 customers and 10 vendors from a wet market. Participants were selected purposively. Audio recorded data were coded based on thematic content and analyzed manually.

resultsWe asked participants how common foods were likely adulterated, and most gave figures of 70% or more. They reported that foods were adulterated with chemicals or artificial colors, especially fish, milk, and vegetables. The supermarket more commonly sold packaged foods with nutritional and expiry information on the label; and offered convenience in terms of building size, layout, and cleanliness. All customers from the wet market thought that foods were cheaper and fresher than from supermarkets. Supermarket customers expressed greater concern about adulterated foods than wet market customers. Most participants from both markets reported that food adulteration is invisible, adulterated foods cannot be avoided, and have long-term negative health impacts including cancer, diabetes, paralysis, heart attack, and others. Nearly half of customers from both markets were concerned about the poor nutritional value of adulterated food. Participants from both settings expressed the need for access to credible information about adulteration to help choose safe foods. The majority expressed the need for government action against those who are responsible for adulteration.

conclusionsFood adulteration was considered a major health threat. The government could act on food adulteration prevention if provided credible population-based data on disease burden, a model food sampling and testing protocol, a model for inspections, organizational strengthening and training, example social and behavioral change communications with estimated costs.

Indexed as

Food MarketsVegetablesAnimalsBangladeshCommunicationCost of IllnessHumansAdulterantsCustomer perceptionsFood qualityFood safetyInformationSupermarketWet market

Identifiers

PMID36721115
PMCPMC9887844

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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.