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      Comparison of Nutritional Quality of the Vegan, Vegetarian, Semi-Vegetarian, Pesco-Vegetarian and Omnivorous Diet

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          Abstract

          The number of studies comparing nutritional quality of restrictive diets is limited. Data on vegan subjects are especially lacking. It was the aim of the present study to compare the quality and the contributing components of vegan, vegetarian, semi-vegetarian, pesco-vegetarian and omnivorous diets. Dietary intake was estimated using a cross-sectional online survey with a 52-items food frequency questionnaire (FFQ). Healthy Eating Index 2010 (HEI-2010) and the Mediterranean Diet Score (MDS) were calculated as indicators for diet quality. After analysis of the diet questionnaire and the FFQ, 1475 participants were classified as vegans ( n = 104), vegetarians ( n = 573), semi-vegetarians ( n = 498), pesco-vegetarians ( n = 145), and omnivores ( n = 155). The most restricted diet, i.e., the vegan diet, had the lowest total energy intake, better fat intake profile, lowest protein and highest dietary fiber intake in contrast to the omnivorous diet. Calcium intake was lowest for the vegans and below national dietary recommendations. The vegan diet received the highest index values and the omnivorous the lowest for HEI-2010 and MDS. Typical aspects of a vegan diet (high fruit and vegetable intake, low sodium intake, and low intake of saturated fat) contributed substantially to the total score, independent of the indexing system used. The score for the more prudent diets (vegetarians, semi-vegetarians and pesco-vegetarians) differed as a function of the used indexing system but they were mostly better in terms of nutrient quality than the omnivores.

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          Diet and body mass index in 38000 EPIC-Oxford meat-eaters, fish-eaters, vegetarians and vegans.

          To compare body mass index (BMI) in four diet groups (meat-eaters, fish-eaters, vegetarians and vegans) in the Oxford cohort of the European Prospective Investigation into Cancer and Nutrition (EPIC-Oxford) and to investigate lifestyle and dietary factors associated with any observed differences. Cross-sectional analysis of self-reported dietary, anthropometric and lifestyle data. A total of 37875 healthy men and women aged 20-97 y participating in EPIC-Oxford. Age-adjusted mean BMI was significantly different between the four diet groups, being highest in the meat-eaters (24.41 kg/m(2) in men, 23.52 kg/m(2) in women) and lowest in the vegans (22.49 kg/m(2) in men, 21.98 kg/m(2) in women). Fish-eaters and vegetarians had similar, intermediate mean BMI. Differences in lifestyle factors including smoking, physical activity and education level accounted for less than 5% of the difference in mean age-adjusted BMI between meat-eaters and vegans, whereas differences in macronutrient intake accounted for about half of the difference. High protein (as percent energy) and low fibre intakes were the dietary factors most strongly and consistently associated with increasing BMI both between and within the diet groups. Fish-eaters, vegetarians and especially vegans had lower BMI than meat-eaters. Differences in macronutrient intakes accounted for about half the difference in mean BMI between vegans and meat-eaters. High protein and low fibre intakes were the factors most strongly associated with increasing BMI.
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            Comparison of self-reported and measured BMI as correlates of disease markers in US adults.

            The purpose of this study is to evaluate the validity of BMI based on self-reported data by comparison with technician-measured BMI and biomarkers of adiposity. We analyzed data from 10,639 National Health and Nutrition Education Study III participants > or =20 years of age to compare BMI calculated from self-reported weight and height with BMI from technician-measured values and body fatness estimated from bioelectrical impedance analysis in relation to systolic blood pressure, fasting blood levels of glucose, high-density lipoprotein-cholesterol, triglycerides, C-reactive protein, and leptin. BMI based on self-reported data (25.07 kg/m2) was lower than BMI based on technician measurements (25.52 kg/m2) because of underreporting weight (-0.56 kg; 95% confidence interval, -0.71, -0.41) and overreporting height (0.76 cm; 95% confidence interval, 0.64, 0.88). However, the correlations between self-reported and measured BMI values were very high (0.95 for whites, 0.93 for blacks, and 0.90 for Mexican Americans). In terms of biomarkers, self-reported and measured BMI values were equally correlated with fasting blood glucose (r = 0.43), high-density lipoprotein-cholesterol (r = -0.53), and systolic blood pressure (r = 0.54). Similar correlations were observed for both measures of BMI with plasma concentrations of triglycerides and leptin. These correlations did not differ appreciably by age, sex, ethnicity, or obesity status. Correlations for percentage body fat estimated through bioelectrical impedance analysis with these biomarkers were similar to those for BMI. The accuracy of self-reported BMI is sufficient for epidemiological studies using disease biomarkers, although inappropriate for precise measures of obesity prevalence.
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              Design characteristics of food frequency questionnaires in relation to their validity.

              The authors investigated the role of food frequency questionnaire (FFQ) design, including length, use of portion-size questions, and FFQ origin, in ranking subjects according to their nutrient intake. They also studied the ability of the FFQ to detect differences in energy intake between subgroups and to assess energy and protein intake. In a meta-analysis of 40 validation studies, FFQs with longer food lists (200 items) were better than shorter FFQs at ranking subjects for most nutrients; results were statistically significant for protein, energy-adjusted total fat, and energy-adjusted vitamin C. The authors found that FFQs that included standard portions had higher correlation coefficients for energy-adjusted vitamin C (0.80 vs. 0.60, p < 0.0001) and protein (0.69 vs. 0.61, p = 0.03) than FFQs with portion-size questions. However, it remained difficult from this review to analyze the effects of using portion-size questions. FFQs slightly underestimated gender differences in energy intake, although level of energy intake was underreported by 23% and level of protein intake by 17%. The authors concluded that FFQs with more items are better able to rank people according to their intake and that they are able to distinguish between subpopulations, even though they underestimated the magnitude of these differences.
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                Author and article information

                Journal
                Nutrients
                Nutrients
                nutrients
                Nutrients
                MDPI
                2072-6643
                24 March 2014
                March 2014
                : 6
                : 3
                : 1318-1332
                Affiliations
                [1 ]Faculty of Physical Education and Physiotherapy, Department of Human Biometrics and Biomechanics, Vrije Universiteit Brussel, Pleinlaan 2, Brussels 1050, Belgium; E-Mails: tom.deliens@ 123456vub.ac.be (T.D.); peter.deriemaeker@ 123456vub.ac.be (P.D.); mhebbel@ 123456vub.ac.be (M.H.); patrick.mullie@ 123456vub.ac.be (P.M.)
                [2 ]Erasmus University College, Laerbeeklaan 121, Brussels 1090, Belgium
                [3 ]International Agency for Research on Cancer (IARC), Dietary Exposure Assessment Group, 150 Cours Albert Thomas, Lyon 69372 CEDEX 08, France; E-Mail: Huybrechtsi@ 123456iarc.fr
                [4 ]Faculty of Medicine and Health Sciences, Department of Public Health, Ghent University, De Pintelaan 185, Ghent 9000, Belgium; E-Mails: inge.huybrechts@ 123456ugent.be (I.H.); Barbara.Vanaelst@ 123456UGent.be (B.V.); willem.dekeyzer@ 123456ugent.be (W.D.K.)
                [5 ]Faculty of Science and Technology, Department of Bio- and food sciences, University College Ghent, Keramiekstraat 80, Ghent 9000, Belgium
                [6 ]International Prevention Research Institute (iPRI), 15 chemin du Saquin, Ecully 69130, France
                Author notes
                [* ]Author to whom correspondence should be addressed; E-Mail: pclarys@ 123456vub.ac.be ; Tel.: +32-26-292-739; Fax: +32-26-292-736.
                Article
                nutrients-06-01318
                10.3390/nu6031318
                3967195
                24667136
                854369c9-e759-42aa-a90e-88fdd9b633ef
                © 2014 by the authors; licensee MDPI, Basel, Switzerland.

                This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution license ( http://creativecommons.org/licenses/by/3.0/).

                History
                : 14 January 2014
                : 06 March 2014
                : 11 March 2014
                Categories
                Article

                Nutrition & Dietetics
                vegan,vegetarian,omnivore,diet quality,dietary pattern analysis
                Nutrition & Dietetics
                vegan, vegetarian, omnivore, diet quality, dietary pattern analysis

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