estimating dietary intake and nutritional status of students

estimating dietary intake and nutritional status of students

;Olga Sergeevna Aminova;Iuliya Eugen’evna Uvarova;Nataliya Nikolaevna Tyatenkova
microsystems and nanoengineering 2017 Vol. 9 pp. 66-77
175
aminova2017vestimating

Abstract

Background: Investigate dietary intake and nutritional status of students on the macronutrients consumption and body mass index. Materials and methods: The study involved 379 students aged 20,1±1,5. The survey was conducted with analyzing the frequency of food consumption. Nutritional status was assessed with body mass index. The results were processed with using a statistical software package Statistica 10.0 and MicrosoftExsel 2010. Results: Survey showed that most of the students ate three or four times a day, disorder of dietary pattern (eat less than 3times a day) was observed in 23% women and 24% men. Estimating distribution of caloric intake during the day showed that 50% girls and 58% boys consumed the greatest amount of food for the evening food ingestion. Estimation of the average daily energy and macronutrients consumption has identified significant differences in sex groups. At the same time the excessive intake of dietary energy, due to the increased consumption of proteins and fats at students of both sexes were pointed. Average BMI values were assessed as normal in 66% students of both sexes. Underweight was registered in 25% women and 17% men. Overweight and obesity were found in 10% women and 18% men. Statistically significant differences in energy ration content among women with underweight and overweight were obtained. Such dependence has not been revealed in men. Conclusion: Study showed that nutrition of 70% students failed to meet hygienic requirements and had protein-fatty tendency.

Citation

ID: 193682
Ref Key: aminova2017vestimating
Use this key to autocite in SciMatic or Thesis Manager

References

Blockchain Verification

Account:
NFT Contract Address:
0x95644003c57E6F55A65596E3D9Eac6813e3566dA
Article ID:
193682
Unique Identifier:
10.12731/wsd-2017-1-66-77
Network:
Scimatic Chain (ID: 481)
Loading...
Blockchain Readiness Checklist
Authors
Abstract
Journal Name
Year
Title
5/5
Creates 1,000,000 NFT tokens for this article
Token Features:
  • ERC-1155 Standard NFT
  • 1 Million Supply per Article
  • Transferable via MetaMask
  • Permanent Blockchain Record
Blockchain QR Code
Scan with Saymatik Web3.0 Wallet

Saymatik Web3.0 Wallet