Dataset Information

Viscosity of Commercial Food-based Formulas and Home-prepared Blenderized Feeds.

ABSTRACT:

Objective

The aim of the study was to quantify the differences in viscosity of over a range of commercial food-based formulas and home-prepared blenderized feeds used for enteral feeding in the clinical management of gastroesophageal reflux and gastroesophageal reflux-related aspiration in children with oropharyngeal dysphagia.

Methods

The viscosity of commercial and home blends was measured using digital rotational viscometer and International Dysphagia Diet Standardization Initiative Syringe Flow Test. Additional testing was performed to determine the impact of added cereal, water flushes, and freezing/thawing on formula viscosity.

Results

There were significant variations in viscosity between commercial blends with values ranging from extremely to mildly thick by Syringe Flow Test. The highest centipoise (cP) value was 13,847 and the lowest 330 and 438 cP. Dilution of 240 mL of commercial blend with 30, 60, and 90 mL of water resulted in a decrease in viscosity of 31%, 62%, and 85%, respectively. Exposure to 1 freeze/thaw cycle decreased viscosity by as much as 59% to 80% depending on the blend. Thickening conventional pediatric formulas with rice or oatmeal did not achieve consistency equivalent to most blenderized feeds.

Conclusions

Commercial food-based formulas and home prepared blends vary greatly in viscosity, ranging from thin to extremely thick liquids, with the majority achieving viscosity greater than thickened formula. Viscosity is reduced by addition of free water and with freezing and thawing. These data can inform the clinical choice of feeding regimen depending on the goals of nutritional therapy.

SUBMITTER: Hron B

PROVIDER: S-EPMC8530412 | biostudies-literature | 2020 Jun

REPOSITORIES: biostudies-literature

ACCESS DATA

Publications

Viscosity of Commercial Food-based Formulas and Home-prepared Blenderized Feeds.

Hron Bridget B Rosen Rachel R

Journal of pediatric gastroenterology and nutrition 20200601 6

<h4>Objective</h4>The aim of the study was to quantify the differences in viscosity of over a range of commercial food-based formulas and home-prepared blenderized feeds used for enteral feeding in the clinical management of gastroesophageal reflux and gastroesophageal reflux-related aspiration in children with oropharyngeal dysphagia.<h4>Methods</h4>The viscosity of commercial and home blends was measured using digital rotational viscometer and International Dysphagia Diet Standardization Initi ...[more]

PMID: 32443040

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Project description:BackgroundHand transcribing nutrient composition data from websites requires extensive human resources and is prone to error. As a result, there are limited nutrient composition data on food prepared out of the home in the United Kingdom. Such data are crucial for understanding and monitoring the out-of-home food environment, which aids policy making. Automated data collection from publicly available sources offers a potential low-resource solution to address this gap.ObjectiveIn this paper, we describe the first UK longitudinal nutritional database of food prepared out of the home, MenuTracker. As large chains will be required to display calorie information on their UK menus from April 2022, we also aimed to identify which chains reported their nutritional information online in November 2021. In a case study to demonstrate the utility of MenuTracker, we estimated the proportions of menu items exceeding recommended energy and nutrient intake (eg, >600 kcal per meal).MethodsWe have collated nutrient composition data of menu items sold by large chain restaurants quarterly since March 2021. Large chains were defined as those with 250 employees or more (those covered by the new calorie labeling policy) or belonging to the top 100 restaurants based on sales volume. We developed scripts in Python to automate the data collection process from business websites. Various techniques were used to harvest web data and extract data from nutritional tables in PDF format.ResultsAutomated Python programs reduced approximately 85% of manual work, totaling 500 hours saved for each wave of data collection. As of January 2022, MenuTracker has 76,405 records from 88 large out-of-home food chains at 4 different time points (ie, March, June, September, and December) in 2021. In constructing the database, we found that one-quarter (24.5%, 256/1043) of large chains, which are likely to be subject to the United Kingdom's calorie menu labeling regulations, provided their nutritional information online in November 2021. Across these chains, 24.7% (16,391/66,295) of menu items exceeded the UK government's recommendation of a maximum of 600 kcal for a single meal. Comparable figures were 46.4% (29,411/63,416) for saturated fat, 34.7% (21,964/63,388) for total fat, 17.6% (11,260/64,051) for carbohydrates, 17.8% (11,434/64,059) for sugar, and 35.2% (22,588/64,086) for salt. Furthermore, 0.7% to 7.1% of the menu items exceeded the maximum daily recommended intake for these nutrients.ConclusionsMenuTracker is a valuable resource that harnesses the power of data science techniques to use publicly available data online. Researchers, policy makers, and consumers can use MenuTracker to understand and assess foods available from out-of-home food outlets. The methods used in development are available online and can be used to establish similar databases elsewhere.

Dataset Information

Viscosity of Commercial Food-based Formulas and Home-prepared Blenderized Feeds.

Objective

Methods

Results

Conclusions

Publications

Viscosity of Commercial Food-based Formulas and Home-prepared Blenderized Feeds.

Similar Datasets

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