Dataset Information

Artificial sweeteners in food and beverage products at school.

ABSTRACT:

Objective

Experts recommend that products containing artificial sweeteners are not marketed to children or sold at schools. The present study aimed to provide a baseline assessment of the extent to which state laws and local school district wellness policies (LWP) address restrictions on the use of artificial sweeteners in competitive foods and beverages (CF&B) sold at schools.

Design

A descriptive, cross-sectional study of policies in place for the 2014-15 school year.

Setting

Data were collected on laws in all fifty states and Washington, DC. LWP were compiled for 496/518 school food authorities (SFA) for which data were collected as part of the US Department of Agriculture's School Nutrition and Meal Cost Study.

Subjects

State laws and LWP respectively were coded on a 0-3 ordinal scale for the strength of their restrictions on artificial sweeteners in CF&B sold in each of five CF&B venues, separately by grade level. Prevalence of state laws and LWP for SFA nationwide was computed.

Results

Thirteen states addressed the use of artificial sweeteners. Six states addressed the use of artificial sweeteners in both CF&B. District-level artificial sweetener policies were most frequently addressed for beverages in elementary schools' vending machines. District policies also were more likely to address artificial sweeteners in states with laws addressing artificial sweeteners.

Conclusions

Most state laws and LWP do not address artificial sweeteners in CF&B. This is not surprising given the Food and Drug Administration has approved eight artificial sweeteners for consumption and the Smart Snacks regulation does not limit artificial sweeteners for CF&B.

SUBMITTER: Schermbeck RM

PROVIDER: S-EPMC10260501 | biostudies-literature | 2019 Aug

REPOSITORIES: biostudies-literature

ACCESS DATA

Publications

Artificial sweeteners in food and beverage products at school.

Schermbeck Rebecca M RM Leider Julien J Piekarz-Porter Elizabeth E Chriqui Jamie F JF

Public health nutrition 20180910 11

<h4>Objective</h4>Experts recommend that products containing artificial sweeteners are not marketed to children or sold at schools. The present study aimed to provide a baseline assessment of the extent to which state laws and local school district wellness policies (LWP) address restrictions on the use of artificial sweeteners in competitive foods and beverages (CF&B) sold at schools.<h4>Design</h4>A descriptive, cross-sectional study of policies in place for the 2014-15 school year.<h4>Set ...[more]

PMID: 30198458

Similar Datasets

Project description:PurposeThis study investigated the effect of food additives, artificial sweeteners and domestic hygiene products on the gut microbiome and fibre fermentation capacity.MethodsFaecal samples from 13 healthy volunteers were fermented in batch cultures with food additives (maltodextrin, carboxymethyl cellulose, polysorbate-80, carrageenan-kappa, cinnamaldehyde, sodium benzoate, sodium sulphite, titanium dioxide), sweeteners (aspartame-based sweetener, sucralose, stevia) and domestic hygiene products (toothpaste and dishwashing detergent). Short-chain fatty acid production was measured with gas chromatography. Microbiome composition was characterised with 16S rRNA sequencing and quantitative polymerase chain reaction (qPCR).ResultsAcetic acid increased in the presence of maltodextrin and the aspartame-based sweetener and decreased with dishwashing detergent or sodium sulphite. Propionic acid increased with maltodextrin, aspartame-based sweetener, sodium sulphite and polysorbate-80 and butyrate decreased dramatically with cinnamaldehyde and dishwashing detergent. Branched-chain fatty acids decreased with maltodextrin, aspartame-based sweetener, cinnamaldehyde, sodium benzoate and dishwashing detergent. Microbiome Shannon α-diversity increased with stevia and decreased with dishwashing detergent and cinnamaldehyde. Sucralose, cinnamaldehyde, titanium dioxide, polysorbate-80 and dishwashing detergent shifted microbiome community structure; the effects were most profound with dishwashing detergent (R2 = 43.9%, p = 0.008) followed by cinnamaldehyde (R2 = 12.8%, p = 0.016). Addition of dishwashing detergent and cinnamaldehyde increased the abundance of operational taxonomic unit (OTUs) belonging to Escherichia/Shigella and Klebsiella and decreased members of Firmicutes, including OTUs of Faecalibacterium and Subdoligranulum. Addition of sucralose and carrageenan-kappa also increased the abundance of Escherichia/Shigella and sucralose, sodium sulphite and polysorbate-80 did likewise to Bilophila. Polysorbate-80 decreased the abundance of OTUs of Faecalibacterium and Subdoligranulum. Similar effects were observed with the concentration of major bacterial groups using qPCR. In addition, maltodextrin, aspartame-based sweetener and sodium benzoate promoted the growth of Bifidobacterium whereas sodium sulphite, carrageenan-kappa, polysorbate-80 and dishwashing detergent had an inhibitory effect.ConclusionsThis study improves understanding of how additives might affect the gut microbiota composition and its fibre metabolic activity with many possible implications for human health.

Project description:Background: The global obesity pandemic and rates of nutrition-related noncommunicable diseases (NCDs) have increased worldwide, especially in the Latin American and Caribbean region. In an attempt to control this obesity epidemic, the Chilean government has established a comprehensive set of regulatory actions, including beverage taxation, warning labels on foods, and marketing restrictions to children. To improve the effectiveness of actions to prevent obesity, a better understanding of the food environment is needed. Objective: We developed and standardized photographic methods to assess and monitor packaged food and beverage products in supermarkets. Methods: A standardized protocol and food categorization system was used to guide photo collection and data management of photos taken between February and April 2015 in 11 supermarkets, consisting of 5 different supermarket chains, from high- (n = 6) and lower-middle (n = 5)-income neighborhoods in Santiago, Chile. Photos (n = ∼50,000) from nearly 10,000 unique food products from high- and lower-middle-income neighborhoods were used for this study. Results: We developed standardized methods to use photographs to assess and monitor the food environment. A food categorization scheme is essential to guiding the data collection process. Substantial time and human resources are required to assess packaged food and beverage products in supermarkets. Because the number of photos per food product is variable, the organization of the photographs according to the food categorization system, before data entry, is imperative for easy access during data entry and analysis. We identified the information necessary for a photographic registry, which, with the food categorization system, is critical to create unique identifiers that are linked to each food product and its photos. Conclusions: To adequately monitor food environments, standardized methods for food photo collection and management are essential. The information collected on food package photos to monitor food environments is important for guiding and evaluating actions in the context of the ongoing obesity and NCD epidemics.

Project description:BackgroundAs the only place in a store where customers must pass through, checkouts may be especially influential over purchases. Research is needed to understand the healthfulness of checkout environments.ObjectivesThe objective of this study was to classify checkout product facings in California food stores.MethodsIn a cross-sectional study, 102 stores, including chains (dollar stores, drugstores, specialty food stores, supermarkets, and mass merchandisers) and independent supermarkets and grocery stores were sampled from 4 northern California cities. Observational assessments of each checkout product facing were conducted in February 2021 using the Store CheckOUt Tool. Facings were classified by category and healthfulness, defined by meeting Berkeley's Healthy Checkout Ordinance's healthy checkout standards: unsweetened beverages and specific foods containing ≤5 g added sugar and ≤200 mg sodium per serving. Log binomial regressions compared healthfulness by store and checkout characteristics.ResultsOf 26,758 food and beverage checkout facings, the most common categories were candy (31%), gum (18%), sugar-sweetened beverages (SSBs; 11%), salty snacks (9%), mints (7%), and sweets (6%). Water represented only 3% and fruits and vegetables 1% of these facings. Only 30% of food and beverage facings met Berkeley's healthy checkout standards, with 70% not meeting the standards. The percentage of food and beverage facings not meeting the standards was even higher (89%) among snack-sized packages (≤2 servings/package). Compared with chain supermarkets, mass merchandisers, and specialty food stores (34%-36%), dollar and independent grocery stores had a lower percentage of food and beverage facings that met the healthy checkout standards (18%-20%; P < 0.05). Compared with lane and register areas (35%), endcaps and snaking sections within checkouts had fewer food and beverage facings that met the standards (21%-23%; P < 0.001).ConclusionsMost foods and beverages at checkout consisted of candy, SSBs, salty snacks, and sweets and failed to meet the healthy checkout standards.Curr Dev Nutr 2023;xx:xx.

Project description:IntroductionArtificial sweeteners are listed as ingredients of oral nicotine pouches (ONPs), a new product category with rapidly growing market share. The exact sweetener contents of ONPs remain unknown. Artificial sweeteners in ONPs may facilitate initiation and encourage consumption behavior.Aims and methodsArtificial sweetener contents in major US-marketed ONP brands (Zyn, on!, Velo) were determined by Liquid Chromatography-Mass Spectrometry (LC-MS). Sweetener effects during the initiation of ONP consumption were modeled in single- and two-bottle tests, offering mice ONP extracts calibrated to contain nicotine levels similar to saliva of people who use smokeless tobacco. To examine the contribution of sweet taste perception, consumption behavior was compared between wild-type mice and mice deficient in the sweet taste receptor (Tas1r2-/-).ResultsAcesulfame-K was detected in on!, Zyn and Velo ONPs (~0.3-0.9 mg/pouch), including products marketed as "Unflavored" or "Flavor ban approved". In Velo ONPs, sweetened with sucralose (0.6-1.2 mg/pouch), higher nicotine strength products contained higher sucralose levels. Tas1r2-/- mice consumed less ONP extracts than wild-type mice in both sexes. ONP extracts with both higher nicotine and sweetener strengths were tolerated by wild-type mice, but produced stronger aversion in Tas1r2-/- mice.ConclusionsONPs contain significant amounts of artificial sweeteners, with some brands adding more sweetener to ONPs with higher nicotine strengths. Artificial sweeteners, at levels present in ONPs, increase nicotine consumption. Increasing sweetener contents facilitates consumption of ONPs with higher nicotine strengths. Sweetness is a key determinant of ONP use initiation, likely reducing the aversive sensory effects of nicotine and other ONP constituents.ImplicationsArtificial sweeteners such as acesulfame-K or sucralose reduce aversion and facilitate initiation and continued consumption of ONPs. The marketing of some artificially sweetened ONPs as "Unflavored" of "Flavor ban-approved" suggests that the tobacco industry rejects sweet taste as a determinant for the presence of a characterizing flavor. Sweetness as imparted by artificial sweeteners in tobacco products needs to be addressed by regulators as a component of a characterizing flavor, with the aim to reduce product appeal and initiation by never users, and especially youth attracted to sweet flavors.

Dataset Information

Artificial sweeteners in food and beverage products at school.

Objective

Design

Setting

Subjects

Results

Conclusions

Publications

Artificial sweeteners in food and beverage products at school.

Similar Datasets

OmicsDI is part of the ELIXIR infrastructure

Tweets