Severity: Warning
Message: file_get_contents(https://...@pubfacts.com&api_key=b8daa3ad693db53b1410957c26c9a51b4908&a=1): Failed to open stream: HTTP request failed! HTTP/1.1 429 Too Many Requests
Filename: helpers/my_audit_helper.php
Line Number: 176
Backtrace:
File: /var/www/html/application/helpers/my_audit_helper.php
Line: 176
Function: file_get_contents
File: /var/www/html/application/helpers/my_audit_helper.php
Line: 250
Function: simplexml_load_file_from_url
File: /var/www/html/application/helpers/my_audit_helper.php
Line: 1034
Function: getPubMedXML
File: /var/www/html/application/helpers/my_audit_helper.php
Line: 3152
Function: GetPubMedArticleOutput_2016
File: /var/www/html/application/controllers/Detail.php
Line: 575
Function: pubMedSearch_Global
File: /var/www/html/application/controllers/Detail.php
Line: 489
Function: pubMedGetRelatedKeyword
File: /var/www/html/index.php
Line: 316
Function: require_once
Background: Increasing interest in diets excluding meat and other products of animal origin emphasizes the importance of objective and reliable methods to measure dietary exposure, to evaluate associations and causation between diet and health, and to quantify nutrient intakes in different diets.
Objectives: This study aimed to investigate if NMR analysis of urine samples can serve as an objective method to discriminate vegan, vegetarian with or without fish, and omnivore diets. A secondary aim was to assess the influence of dietary nutrient intake on the metabolomics results.
Methods: Healthy individuals (43 men and 75 women, age 19-57 y) complying with habitual vegan (n = 42), vegetarian (n = 25), vegetarian + fish (n = 13), or omnivore (n = 38) diets were enrolled. Data were collected on clinical phenotype and lifestyle including a 4-d weighed food diary. Urine was analyzed for metabolites by NMR spectroscopy and data normalized using probabilistic quotient normalization and Pareto-scaled before multivariate analysis. Before orthogonal projections to latent structures with discriminant analysis, participants were assigned as meat consumers or nonmeat consumers (vegans and vegetarians), vegans or nonvegans (omnivores, vegetarian, and vegetarian + fish).
Results: The main results showed that it was possible to discriminate meat and nonmeat consumers (91% correctly classified), but discrimination between vegans and nonvegans was less rigorous (75% correctly classified). Secondary outcomes showed that reported intake of protein was higher in omnivores, and saturated fat lower and fiber higher in vegans, compared with the other groups. Discriminating metabolites were mainly related to differences in protein intake.
Conclusions: NMR urine metabolomics appears suitable to objectively identify and predict habitual intake of meat in healthy individuals, but results should be interpreted with caution because not only food groups but also specific foods contribute to the patterns.This trial was registered at clinicaltrials.gov as NCT02039609.
Download full-text PDF |
Source |
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http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7779212 | PMC |
http://dx.doi.org/10.1093/jn/nxaa019 | DOI Listing |
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