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- Title
Discerning animal-sourced food in diet using isotope analysis of human scalp hair and fingernails.
- Authors
Agrawal, Gunjan; Sanyal, Prasanta
- Abstract
Purpose: Diet-related diseases are advancing as the leading cause of death globally. As self-reporting of diet by patients can be associated with errors, stable isotopes of human tissues can be used to diagnose diseases, understand physiology, and detect change in diet. This study investigates the effect of type and amount of food on the nitrogen and carbon concentration (Nconc and Cconc) and isotopic composition (δ15N and δ13C) in human scalp hair and fingernails. Methods: A total of 100 residents participated in the study whereas only 74 individuals provided complete diet history. Sixty-six food items majorly available to them were also collected. The Nconc, Cconc, δ15N and δ13C values of human hair, nails and food items were determined. Results: The Nconc, Cconc, δ15N and δ13C values between plant-sourced and animal-sourced food items, as well as human hair and nail tissue were significantly different (p < 0.05). The δ15N value of human tissues was distinct between lacto-vegetarians and omnivores by 0.9‰. The δ15N and δ13C values of human tissues increased by 0.4–0.5‰ with every 5% increase in the consumption of animal protein. Conclusions: The study helps to demarcate lacto-vegetarians from omnivores, and estimate the percentage of animal protein in diet based on the dual isotope values of human tissues. It also acts as a reference to determine isotopic composition of hair tissue provided the isotope value of nail tissue is known and vice versa.
- Subjects
INDIA; NITROGEN analysis; CARBON analysis; ISOTOPIC analysis; FOOD habits; BIOMARKERS; INFERENTIAL statistics; STATISTICS; KRUSKAL-Wallis Test; NAILS (Anatomy); MEAT; VEGETARIANISM; VEGETABLES; ANALYSIS of variance; POULTRY; CONFIDENCE intervals; FOOD consumption; SCALP; NUTRITIONAL value; MANN Whitney U Test; METABOLISM; PLANT-based diet; FOOD animals; T-test (Statistics); DIETARY sucrose; HAIR; DESCRIPTIVE statistics; GRAIN; ANALYTICAL chemistry techniques; DATA analysis software; DATA analysis; DIETARY proteins; SPECTRUM analysis
- Publication
European Journal of Nutrition, 2024, Vol 63, Issue 2, p409
- ISSN
1436-6207
- Publication type
Article
- DOI
10.1007/s00394-023-03273-y