Food matters: Translating information on what people eat, say they eat, into advice for health

Lara Gallegos, Jose J. (2005) Food matters: Translating information on what people eat, say they eat, into advice for health. PhD thesis, University of Glasgow.

Abstract

The present dissertation deals with broad issues of scientific importance to the field of Dietetics and Human Nutrition, crossing the frontiers which lie between what people say they eat, what they actually eat, what they should eat, and the ultimate effects of diet composition on health, which must be translated into advice and guidelines. Firstly it addresses veracity. Dietary mis-reporting and its relation with psychological and eating behaviour variables were assessed in adult women of varied BMI. A questionnaire, comprising several well-established psychological and eating behaviour tests and two questions to assess inclination to mis-report, was compiled and validated for understandability. The eating habits and dietary practices of subjects involved in food related occupations were then assessed. The fact that these food skilled groups are potentially influential in other people's food choice, including that of their own families, invited the hypothesis that these groups may have healthier diets than other occupational groups. The third study was therefore designed to assess the effects of salmon consumption on vascular parameters of the metabolic syndrome. The opportunity was used to study the effect of salmon on serum leptin as well, following a report of lower leptin concentrations amongst fish-eaters, suggesting increased leptin sensitivity.

• Item Type: Thesis (PhD)
• Qualification Level: Doctoral
• Additional Information: Adviser: Prof. Michael Lean.
• Keywords: Nutrition.
• Colleges/Schools: College of Medical Veterinary and Life Sciences
• Supervisor's Name: Supervisor, not known
• Date of Award: 2005
• Depositing User: Enlighten Team
• Unique ID: glathesis:2005-71459
• Copyright: Copyright of this thesis is held by the author.
• Date Deposited: 17 May 2019 09:31
• Last Modified: 30 Aug 2021 15:46
• Thesis DOI: 10.5525/gla.thesis.71459
• URI: https://theses.gla.ac.uk/id/eprint/71459

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