Evidence map›Paper›PMID 39759536›Full record

ReviewPublic health reviews2024

Food Advertisement and Marketing Policies Aimed at Reducing Childhood Obesity: A Review of Existing Regulations in High-Income Countries.

Rida Khan, L Suzanne Suggs, Afifa Tanweer, Gábor Bányai

Abstract readReview
In one paragraph

Review in Public health reviews, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 8 papers.

0numbers the graph read from it
0cells of the map it votes in
8citing 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

8 citing papers in PubMed.

  1. Trial
  2. Article
  3. Review
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  8. Review
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.

Rida KhanInstitute of Health Sciences, Faculty of Health Sciences, University of Debrecen, Debrecen, Hajdu-Bihar, Hungary.
L Suzanne SuggsInstitute of Communication and Public Policy, Faculty of Communication, Culture and Society, University of Lugano, Lugano, Switzerland.
Afifa TanweerDepartment of Nutrition and Dietetics, School of Health Sciences, University of Management and Technology, Lahore, Punjab, Pakistan.
Gábor BányaiInstitute of Health Economics and Management, Faculty of Economics and Business, University of Debrecen, Debrecen, Hajdu-Bihar, Hungary.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Objectives: To identify and evaluate the difference between voluntary and mandatory food marketing policies and regulations targeting childhood obesity and to study the role of media, the food industry, and private associations in implementing such policies. Methods: A review of policies and legislation about unhealthy food marketing was conducted by searching and extracting relevant grey literature from the websites of international health agencies, food marketing pledge databases, GINA, and NOURISHING policy databases. Statutory laws and self-regulations of high-income countries were compared with each other and with the WHO recommendations. Results: Regulations differ regarding target audience, nutrient profiling, communication media, and marketing techniques. To date, no country has implemented comprehensive regulations restricting all forms of unhealthy food marketing. Statutory laws are more meticulous and rigorous than self-regulatory policies. Conclusion: The goal of reducing childhood obesity through restrictions on unhealthy food advertising has not been met. While not welcomed by all actors, mandatory regulations may be more effective than voluntary measures in reaching this goal. A system for monitoring adherence to regulations and providing both incentives and penalties for violations is warranted.

Indexed as

advertisementchildhoodfoodmarketingobesity

Identifiers

PMID39759536
PMCPMC11695118

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.