Evidence map›Paper›PMID 35804694›Full record

ArticleFoods (Basel, Switzerland)2022

Harnessing Food Product Reviews for Personalizing Sweetness Levels.

Kim Asseo, Masha Y Niv

Abstract read
In one paragraph

Article in Foods (Basel, Switzerland), 2022. 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. Review
  2. Article
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.

Kim AsseoThe Institute of Biochemistry, Food Science and Nutrition, The Robert H. Smith Faculty of Agriculture, Food, and Environment, The Hebrew University of Jerusalem, Rehovot 76100, Israel.
Masha Y NivThe Institute of Biochemistry, Food Science and Nutrition, The Robert H. Smith Faculty of Agriculture, Food, and Environment, The Hebrew University of Jerusalem, Rehovot 76100, Israel.ORCID 0000-0001-8275-8795

Funding

Israel Science Foundation 1129/19
6 · The paper itself

Abstract

Sweet taste is innately appealing, ensuring that mammals are attracted to the sweetness of mother's milk and other sources of carbohydrates and calories. In the modern world, the availability of sugars and sweeteners and the eagerness of the food industry to maximize palatability, result in an abundance of sweet food products, which poses a major health challenge. The aim of the current study is to analyze sweetness levels, liking, and ingredients of online reviews of food products, in order to obtain insights into sensory nutrition and to identify new opportunities for reconciling the palatability-healthiness tension. We collected over 200,000 reviews of ~30,000 products on Amazon dated from 2002 to 2012 and ~350,000 reviews of ~2400 products on iHerb from 2006 to 2021. The reviews were classified and analyzed using manual curation, natural language processing, and machine learning. In total, ~32,000 (Amazon) and ~29,000 (iHerb) of these reviews mention sweetness, with 2200 and 4600 reviews referring to the purchased products as oversweet. Oversweet reviews were dispersed among consumers. Products that included sucralose had more oversweet reviews than average. 26 products had at least 50 reviews for which at least 10% were oversweet. For these products, the average liking by consumers reporting oversweetness was significantly lower (by 0.9 stars on average on a 1 to 5 stars scale) than by the rest of the consumers. In summary, oversweetness appears in 7-16% of the sweetness-related reviews and is less liked, which suggests an opportunity for customized products with reduced sweetness. These products will be simultaneously healthier and tastier for a substantial subgroup of customers and will benefit the manufacturer by expanding the products' target audience. Analysis of consumers' reviews of marketed food products offers new ways to obtain informative sensory data.

Indexed as

healthhedonicNLPnutritionsensorysweetnesstaste

Identifiers

PMID35804694
PMCPMC9266276

What OpenQuestion holds

Textmetadata
LicenceCC BY
Read underepoch 390

Registered trials

None linked

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.