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Nutrient Profiles of Vegetarian and Non Vegetarian Dietary Patterns - Nico S. Rizzo et al - Journal of the Academy of Nutrition and Dietetics (2013)

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  • Nutrient Profiles of Vegetarian and Non Vegetarian DietaryPatterns

    Nico S. Rizzo,med. Dr., PhD, Asst. Professor, Department of Nutrition, School of Public Health, Loma LindaUniversity, Loma Linda, CA, USA. 24951 North Circle Drive, Loma Linda, CA 92350, USA. Tel:+1 909 558 4300 ext. 47167, Fax: +1 909 558 4095, nrizzo@llu.edu

    Karen Jaceldo-Siegl,DrPH, Asst. Professor, Department of Nutrition, School of Public Health, Loma Linda University,Loma Linda, CA, USA. Tel: +1 909 558 4300 ext. 87580, Fax: +1 909 558 4095,kjaceldo@llu.eduJoan Sabate, andMD, DrPH, Professor, Department of Nutrition, School of Public Health, Loma Linda University,Loma Linda, CA, USA. Tel: +1 909 558 4300, Fax: +1 909 558 4095, kjaceldo@llu.eduGary E. FraserPhD, Professor, Department of Epidemiology, School of Public Health, Loma Linda University,Loma Linda, CA, USA. Tel: +1 909 558 4300, Fax: +1 909 558 4095, efraser@llu.edu

    AbstractBackgroundDifferences in nutrient profiles between vegetarian and non vegetarian dietarypatterns reflect nutritional differences that may contribute to the development of disease.

    ObjectiveTo compare nutrient intakes between dietary patterns characterized by consumptionor exclusion of meat and dairy products.

    DesignCross-sectional study of 71751 subjects (mean age 59 years) from the Adventist-Health-Study-2. Data was collected between 2002 and 2007. Participants completed a 204-itemvalidated semi-quantitative food frequency questionnaire. Dietary patterns compared were: nonvegetarian, semi vegetarian, pesco vegetarian, lacto-ovo vegetarian and strict vegetarian.ANCOVA was used to analyze differences in nutrient intakes by dietary patterns and wereadjusted for age, and sex and race. BMI and other relevant demographic data were reported andcompared by dietary pattern using chi-square tests and ANOVA.

    ResultsMany nutrient intakes varied significantly between dietary patterns. Non vegetarianshad the lowest intakes of plant proteins, fiber, -Carotene, and Mg than those following vegetariandietary patterns and the highest intakes of saturated, trans, arachidonic, and docosahexaenoic fatty

    Correspondence to: Nico S. Rizzo.Publisher's Disclaimer: This is a PDF file of an unedited manuscript that has been accepted for publication. As a service to ourcustomers we are providing this early version of the manuscript. The manuscript will undergo copyediting, typesetting, and review ofthe resulting proof before it is published in its final citable form. Please note that during the production process errors may bediscovered which could affect the content, and all legal disclaimers that apply to the journal pertain.

    NIH Public AccessAuthor ManuscriptJ Acad Nutr Diet. Author manuscript; available in PMC 2014 December 01.

    Published in final edited form as:J Acad Nutr Diet. 2013 December ; 113(12): 16101619. doi:10.1016/j.jand.2013.06.349.

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  • acids. The lower tails of some nutrient distributions in strict vegetarians suggested inadequateintakes by a portion of the subjects. Energy intake was similar among dietary patterns at close to2000 kcal/d with the exception of semi vegetarians that had an intake of 1713 kcal/d. Mean BMIwas highest in non-vegetarians (mean; standard deviation [SD]) (28.7; [6.4]) and lowest in strictvegetarians (24.0; [4.8]).ConclusionsNutrient profiles varied markedly between dietary patterns that were defined bymeat and dairy intakes. These differences can be of interest in the etiology of obesity and chronicdiseases.

    KeywordsDietary Pattern; Nutrient Profile; Vitamins; Minerals; Vegetarian

    INTRODUCTIONAwareness of possible differences in nutrient profiles is of importance when comparingdietary patterns and their associations with disease. Previous studies have shown that dietarypatterns characterized by lower meat intake1 are associated with lower risk of disorders suchas the metabolic syndrome2;3, diabetes3;4, cardiovascular disease57 and certain types ofcancers8;9. Variations in nutrient content may account for these observed differences inhealth outcomes.

    The Adventist Health Study 2 (AHS-2) provides a rich data resource to address thesequestions. With 45% of the 96,335 study subjects being vegetarian, and approximately 8%strict vegetarians, it is presently one of the very few large cohort studies that include a highproportion of vegetarians. Thus associations between vegetarian dietary patterns and healthoutcomes can be addressed with adequate power.

    This report describes the intakes of major nutrients, vitamins and minerals in dietary patternsthat are characterized by varying animal and plant food consumption. Relevant demographicand socioeconomic data such as age, education, marital status and income as well as otherlifestyle factors such as physical activity, alcohol consumption and smoking were includedin this study as they may be of relevance when comparing dietary patterns. To show possibleassociations that differing dietary patterns may have with health relevant outcomes, BMIwas similarly reported and briefly discussed.

    SUBJECTS AND METHODSThe analyses are based on cross-sectional data obtained between 20022007 from a 50-pageself-administered questionnaire10. The number of subjects in the present analysis included71751 U.S. and Canadian participants from the AHS-2 cohort whose dietary data had beenreleased for analysis10. The study was reviewed and approved by the institutional reviewboard of Loma Linda University, Loma Linda, California, and informed consent wasobtained from all participants.

    Race and ethnicity were stratified into black (African American, West Indian/Caribbean,African, or other black) and white (white non-Hispanic, Hispanic, Middle Eastern, Asian,

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    J Acad Nutr Diet. Author manuscript; available in PMC 2014 December 01.

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  • Native Hawaiian/other Pacific Islander, or American Indian) subjects. Education wasstratified into three categories: completed high school diploma or less; some college;bachelors, masters or higher university degrees.

    Participants reported anthropometric data on height (without shoes in feet and inches andweight wearing light clothes) in pounds, that had previously been demonstrated to havegood validity.11 BMI was calculated as weight/length2. Alcohol intake and tobacco use weredefined as never, past or current consumption.

    Assessment of Intake of Nutrients, Vitamins, and MineralsThe FFQ includes more than 204 hard-coded foods and space for approximately 50 writeins,all relating to the diet during the previous one year. It consists of two major sections. Thefirst section includes fruits, vegetables, legumes, grains, nuts, oils, dairy, fish, eggs, meats,and beverages, and the second consists of approximately 70 commercially-preparedproducts, such as dietary supplements, dry cereals, and vegetarian protein products. Picturesof common foods or beverages typically served together were included with thequestionnaire to assist participants in estimating portion sizes. The questionnaire was mailedto each subject, completed at home, and then returned to AHS-2. The FFQ has beenvalidated against 24 hour recall data.12;13 In this report intakes from supplements arecombined with dietary intakes, to form total intakes.

    FFQ data were entered using the Nutrition Data System for Research version 4.06 (NDS-R,Nutrition Coordinating Center, Minneapolis, MN, USA). Nutrient composition of foods wasbased on the NDS-R 2008 database, which contains over 20000 foods that are annuallyupdated while maintaining nutrient profiles true to the version used for data collection14.

    Dietary PatternsDietary patterns were defined by level of animal food intake stratified in five categories 15.Non vegetarians were defined as those consuming some meat (red meat, poultry, at leastonce per month), and the total of meat and fish >1 time/week. Semi vegetarians mayconsume dairy products and/or eggs, eat some meat (red meat and poultry) 1 time/month,and the total of fish and meat 1 time/month but

  • Statistical AnalysisOn average 67% of dietary data were missing for any particular food item and were filledby guided multiple imputation16. Dietary patterns were then compared according to selecteddemographic variables. Chi-square tests (categorical variables) and ANOVA (continuousvariables) were used for these comparisons. Percentiles (5th, 50th and 95th) for nutrientintakes stratified by dietary pattern were reported.

    ANCOVA with Sidaks adjustments for multiple comparisons was used to test nutrient andBMI differences between dietary patterns. Nutrient intakes were logarithmically transformedfor statistical testing. Mean values are reported stratified by dietary pattern and adjusted forage, sex or race. Mean intake values that differed by 20% between dietary patterns weremarked.

    Analyses were carried out using the statistical software packages IBM SPSS Statistics 20.0(SPSS Inc., Chicago, IL, USA) and R 2.13.1: A Language and Environment for StatisticalComputing (R Foundation for Statistical Computing, Vienna, Austria). Type I error rate wasset at 0.05.

    RESULTSBasic demographic information is reported in Table 1. Significant differences by dietarypattern were seen for all variables. Across all dietary patterns 30 to 55 year olds comprisedthe largest group (P

  • 27.6), pesco vegetarians (26.1; CI 26.026.2), lacto-ovo vegetarians (26.1; CI 26.026.2)and strict vegetarians (24.1; CI 24.024.2).

    Table 2 reports 5th, 50th and 95th percentiles for each nutrient. In many cases nutrient intakeswere skewed. For nutrients, values at the 95th percentiles were generall

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