Evidence map›Paper›PMID 36319974›Full record

ArticleBMC medicine2022

Added flavors: potential contributors to body weight gain and obesity?

Nathalie Judith Neumann, Mathias Fasshauer

Abstract read
In one paragraph

Article in BMC medicine, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 19 papers.

0numbers the graph read from it
0cells of the map it votes in
19citing 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

19 citing papers in PubMed.

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  18. 360-Degree Perspectives on Obesity.Medicina (Kaunas, Lithuania) · 2023
    Review
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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

2 authors.

Nathalie Judith NeumannInstitute of Nutritional Science, Justus-Liebig-University of Giessen, 35390, Giessen, Germany.
Mathias FasshauerInstitute of Nutritional Science, Justus-Liebig-University of Giessen, 35390, Giessen, Germany. mathias.fasshauer@uni-giessen.de.ORCID 0000-0001-8077-6404

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundAdded flavors are a marker for ultra-processing of food and a strong link exists between the intake of ultra-processed food and the development of obesity. The objective of the present article is to assess animal and human data elucidating the impact of added flavors on the regulation of food intake and body weight gain, as well as to define areas for future research. MAIN TEXT: Mechanistic studies suggest that added flavors induce overeating and body weight gain by two independent mechanisms: Added flavors promote hedonic eating and override homeostatic control of food intake, as well as disrupt flavor-nutrient learning and impair the ability to predict nutrients in food items. Supporting these potential mechanisms, added flavors increase feed intake and body weight as compared to non-flavored control diets in a broad range of animal studies. They are actively promoted by feed additive manufacturers as useful tools to improve palatability, feed intake, and performance parameters. In humans, added flavors are extensively tested concerning toxicity; however, no data exist concerning their impact on food intake and body weight.

conclusionsAdded flavors are potential contributors to the obesity epidemic and further studies focusing on their role in humans are urgently required. These studies include obesity interventions specifically targeting food items with added flavors and cohort studies on independent associations between added flavor intake and metabolic, as well as cardiovascular, morbidity, and mortality.

Indexed as

ObesityWeight GainAnimalsBody WeightEatingFast FoodsHumansAdded flavorsBody weightFlavor-nutrient learningFood intakeHedonic eatingMetabolic syndromeObesityUltra-processed food

Identifiers

PMID36319974
PMCPMC9623908

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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.