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- Genre: Academic theses
- Genre: Masters Thesis
- Creators: Johnston, Carol
- Creators: Liu, Huan
- Status: Published
Description
In 2002, a scientifically derived food guide pyramid for vegetarians, the Modified Food Guide for Lacto-ovo-vegetarians and Vegans was published and well received. Now that 10 years have passed, new scientific literature regarding the bioavailability of the nutrients of key concern in vegetarian diets has been published, and the graphical format of the nation's food guide has evolved from a pyramid shape into a circular plate. The objective of this research was to examine the post-2002 literature regarding the bioavailability of key nutrients in vegetarian diets; to use this information to update the recommendations made in the 2002 Modified Food Guide Pyramid for Lacto-ovo-vegetarians and Vegans; and to adapt this revised food plan to the new USDA MyPlate format. This process involved reviewing the scientific literature to determine if the DRIs for the nutrients of key concern in vegetarian diets are adequate for the vegetarian population and using this information to develop new recommendations for vegetarians if necessary, analyzing the nutrient content of representative foods in different food groups, reconfiguring the food groups so that foods with like nutrient components were grouped together, determining the number of servings of each food group required to meet vegetarians' nutrient requirements at three caloric levels, and developing sample menus. A circular plate graphic, the Vegetarian Plate, was designed to illustrate the recommendations of this updated food guide. This updated, scientifically derived food guide provides a sound base for diet planning for lacto-ovo-vegetarians and vegans. Further research is needed to assess the Vegetarian Plate's adequacy for children, pregnant and lactating women, athletes, and individuals with medical conditions or chronic diseases.
ContributorsFladell, Lauren (Author) / Johnston, Carol (Thesis advisor) / Vaughan, Linda (Committee member) / Shepard, Christina (Committee member) / Arizona State University (Publisher)
Created2013
Description
This study was designed to influence consumer habits, specifically those relating to purchases of fruits, vegetables, and junk food. Previous studies have clearly shown the ineffectiveness of simply describing the health benefits of eating more fruits and vegetables (F/V). In contrast, this study aimed to change the result by changing the message: providing participants with insight into the hidden agendas of food companies and grocery stores, provide useful tips on how to include children when selecting F/V, and emphasizing the importance of parental modeling in regard to food purchases. Participants of this study were separated into two groups, the tour group and the education group. The tour group was guided through a grocery store where they learned about sales tactics and manipulations used by grocery stores and food companies to influence purchases. Education group participants were provided with an education session focusing on USDA and FDA handouts displaying current educational suggestions for increasing F/V consumption. Grocery store receipts were collected and analyzed to track the progress of both groups. The goal of the study was to identify a method of informing consumers that will produce a significant change in behavior. Increasing F/V consumption, even in relatively small amounts, would be an important step forward in improving the diet and overall health of Americans. This study was the first of its kind to measure purchasing patterns objectively (through analysis of purchase receipts, rather than personal opinion/evaluation surveys) and in a wide-scope retail environment that includes all grocery store purchases by participants. Significant increases or decreases in the amount of money spent on F/V, or the amount (pounds) of F/V purchased were not seen, however a small correlation (r = 0.133) exists when comparing the weight of F/V purchased pre/post intervention. Data from Food Frequency Questionnaires shows participants consuming significantly higher amounts of F/V post intervention (p=0.043). The tour group and education group experienced an average increase of 0.7 servings per day. Future interventions might benefit by extending their scope to include cooking demonstrations, in-home interventions, and education on healthy eating outside of the home.
ContributorsKinsfather, Diana (Author) / Johnston, Carol (Thesis advisor) / Hekler, Eric (Committee member) / Tetreault, Colin (Committee member) / Arizona State University (Publisher)
Created2013
Description
Health knowledge alone does not appear to lead to sustained healthy behavior, suggesting the need for alternative methods for improving diet. Recent research shows a possible role of moral contexts of food production on diet related behaviors; however no studies have been conducted to specifically explore the relationship between moral constructs and food consumption. This study examined the relationship between fast food consumption and two measures of morality, Moral Foundations Questionnaire (MFQ), specifically harm/care and purity/sanctity foundations, and the Ethical Concern in food choice (EC) questionnaire, which includes animal welfare, environment protection, political values, and religion subscales. The study also examined the association between the measures of morality. 739 participants, primarily female (71.4%) and non-Hispanic Whites (76.5%), completed an online survey that included the MFQ, the EC questionnaire, and a brief fast food screener. Participant's morality scores in relation to their fast food consumption were examined first using bivariate ANOVA analysis and then using logistic regression to control for covariates. The MFQ foundations were compared with the EC subscales using Pearson correlation coefficient. Significant bivariate relationships were seen between fast food consumption and the MFQ's purity/sanctity foundation and EC's religion subscales (p<0.05). However these significant bivariate relationships did not hold after controlling for gender, race, university education, and religion in the logistic regression analysis. The foundations of the MFQ were positively correlated with the subscales for the EC questionnaire (r values ranging from .233-.613 (p<0.01). MFQ's purity/sanctity foundation and EC's religion subscale were the two most highly correlated (r=.613, p<0.01) showing that moral intuitions may be associated with eating decision making. The study did not find significant associations between MFQ or EC scores and fast food consumption.
ContributorsMartinelli, Sarah (Author) / Ohri-Vachaspati, Punam (Thesis advisor) / Hekler, Eric B. (Committee member) / Wharton, Christopher (Christopher Mack), 1977- (Committee member) / Johnston, Carol (Committee member) / Arizona State University (Publisher)
Created2013
Description
Background: Previous research suggests a healthy eater schema (i.e., identifying yourself as a healthy eater) may be a useful concept to target in interventions. A "stealth" intervention that discussed the moral issues related to food worked better at promoting healthful eating than an intervention focused on the health benefits. No research has explored the relationship between moral foundations, a theoretical model focused on delineating core "foundations" for making a moral decision, and healthy eater self-identity or self-efficacy. Purpose: We explored the relationship between moral foundations (i.e., harm/care, fairness/reciprocity, in-group/loyalty, authority/respect, & purity/sanctity) and health eater self-identity and fruit and vegetable self-efficacy (FVSE). Methods: 542 participants completed an online cross-sectional survey, which included moral foundations (i.e., MFQ), political views, healthy eater self-identity (i.e., HESS), and FVSE measures. Logistic regression was used to assess the relationship between moral foundations between healthy eater self-identity after controlling for age, gender, major, BMI, and political beliefs. OLS regression was used to explore the relationship between self-efficacy and the moral foundations after controlling for the covariates. Results: 75.6% of the sample were college students, with a mean age of 25.27 (SD=8.61). 25.1% of students were nutrition majors. Harm/care, authority/respect, and ingroup/loyalty were significantly associated with healthy eater schema, (i.e., OR=1.7, p<.001, OR=1.5, p=.009, and OR=1.4, p=.027, respectively). Ingroup/loyalty, authority/respect, and purity/sanctity were related to FVSE (p=.006, p=.002, p=.04, respectively). Conclusion: Among college students, harm/care and authority/respect were associated with a healthy eater schema. Future research should explore possible uses of these moral foundations in interventions (e.g., a plant-based diet based on reduced harm to animals or eating fewer processed views based on "traditional" values).
ContributorsKiser, Sarah (Author) / Hekler, Eric B. (Thesis advisor) / Ohri-Vachaspati, Punam (Committee member) / Wharton, Christopher (Christopher Mack), 1977- (Committee member) / Johnston, Carol (Committee member) / Arizona State University (Publisher)
Created2013
Description
Contemporary online social platforms present individuals with social signals in the form of news feed on their peers' activities. On networks such as Facebook, Quora, network operator decides how that information is shown to an individual. Then the user, with her own interests and resource constraints selectively acts on a subset of items presented to her. The network operator again, shows that activity to a selection of peers, and thus creating a behavioral loop. That mechanism of interaction and information flow raises some very interesting questions such as: can network operator design social signals to promote a particular activity like sustainability, public health care awareness, or to promote a specific product? The focus of my thesis is to answer that question. In this thesis, I develop a framework to personalize social signals for users to guide their activities on an online platform. As the result, we gradually nudge the activity distribution on the platform from the initial distribution p to the target distribution q. My work is particularly applicable to guiding collaborations, guiding collective actions, and online advertising. In particular, I first propose a probabilistic model on how users behave and how information flows on the platform. The main part of this thesis after that discusses the Influence Individuals through Social Signals (IISS) framework. IISS consists of four main components: (1) Learner: it learns users' interests and characteristics from their historical activities using Bayesian model, (2) Calculator: it uses gradient descent method to compute the intermediate activity distributions, (3) Selector: it selects users who can be influenced to adopt or drop specific activities, (4) Designer: it personalizes social signals for each user. I evaluate the performance of IISS framework by simulation on several network topologies such as preferential attachment, small world, and random. I show that the framework gradually nudges users' activities to approach the target distribution. I use both simulation and mathematical method to analyse convergence properties such as how fast and how close we can approach the target distribution. When the number of activities is 3, I show that for about 45% of target distributions, we can achieve KL-divergence as low as 0.05. But for some other distributions KL-divergence can be as large as 0.5.
ContributorsLe, Tien D (Author) / Sundaram, Hari (Thesis advisor) / Davulcu, Hasan (Thesis advisor) / Liu, Huan (Committee member) / Arizona State University (Publisher)
Created2014
Description
Most data cleaning systems aim to go from a given deterministic dirty database to another deterministic but clean database. Such an enterprise pre–supposes that it is in fact possible for the cleaning process to uniquely recover the clean versions of each dirty data tuple. This is not possible in many cases, where the most a cleaning system can do is to generate a (hopefully small) set of clean candidates for each dirty tuple. When the cleaning system is required to output a deterministic database, it is forced to pick one clean candidate (say the "most likely" candidate) per tuple. Such an approach can lead to loss of information. For example, consider a situation where there are three equally likely clean candidates of a dirty tuple. An appealing alternative that avoids such an information loss is to abandon the requirement that the output database be deterministic. In other words, even though the input (dirty) database is deterministic, I allow the reconstructed database to be probabilistic. Although such an approach does avoid the information loss, it also brings forth several challenges. For example, how many alternatives should be kept per tuple in the reconstructed database? Maintaining too many alternatives increases the size of the reconstructed database, and hence the query processing time. Second, while processing queries on the probabilistic database may well increase recall, how would they affect the precision of the query processing? In this thesis, I investigate these questions. My investigation is done in the context of a data cleaning system called BayesWipe that has the capability of producing multiple clean candidates per each dirty tuple, along with the probability that they are the correct cleaned version. I represent these alternatives as tuples in a tuple disjoint probabilistic database, and use the Mystiq system to process queries on it. This probabilistic reconstruction (called BayesWipe–PDB) is compared to a deterministic reconstruction (called BayesWipe–DET)—where the most likely clean candidate for each tuple is chosen, and the rest of the alternatives discarded.
ContributorsRihan, Preet Inder Singh (Author) / Kambhampati, Subbarao (Thesis advisor) / Liu, Huan (Committee member) / Davulcu, Hasan (Committee member) / Arizona State University (Publisher)
Created2013
Description
ABSTRACT Vitamin C plays an important role in fatty acid metabolism because it is required for carnitine synthesis. Vitamin C has been shown to have an inverse relationship with weight and body fat percent in a number of studies. However, there has been limited research exploring the relationship between vitamin C status and fat oxidation. This cross-sectional study investigates the relationship between plasma vitamin C and fat oxidation in 69 participants and between plasma vitamin C and body fatness in 82 participants. Participants were measured for substrate utilization via indirect calorimetry while at rest and measured for body fatness via DEXA scan. Participants provided a single fasting blood draw for analysis of plasma vitamin C. Results did not show a significant association between vitamin C and fat oxidation while at rest, therefore the data do not support the hypothesis that vitamin C status affects fat oxidation in a resting state. However, a significant inverse association was found between vitamin C and both total body fat percent and visceral fat.
ContributorsObermeyer, Lindsay (Author) / Johnston, Carol (Thesis advisor) / Hall, Rick (Committee member) / Swan, Pamela (Committee member) / Arizona State University (Publisher)
Created2014
Description
As the size and scope of valuable datasets has exploded across many industries and fields of research in recent years, an increasingly diverse audience has sought out effective tools for their large-scale data analytics needs. Over this period, machine learning researchers have also been very prolific in designing improved algorithms which are capable of finding the hidden structure within these datasets. As consumers of popular Big Data frameworks have sought to apply and benefit from these improved learning algorithms, the problems encountered with the frameworks have motivated a new generation of Big Data tools to address the shortcomings of the previous generation. One important example of this is the improved performance in the newer tools with the large class of machine learning algorithms which are highly iterative in nature. In this thesis project, I set about to implement a low-rank matrix completion algorithm (as an example of a highly iterative algorithm) within a popular Big Data framework, and to evaluate its performance processing the Netflix Prize dataset. I begin by describing several approaches which I attempted, but which did not perform adequately. These include an implementation of the Singular Value Thresholding (SVT) algorithm within the Apache Mahout framework, which runs on top of the Apache Hadoop MapReduce engine. I then describe an approach which uses the Divide-Factor-Combine (DFC) algorithmic framework to parallelize the state-of-the-art low-rank completion algorithm Orthogoal Rank-One Matrix Pursuit (OR1MP) within the Apache Spark engine. I describe the results of a series of tests running this implementation with the Netflix dataset on clusters of various sizes, with various degrees of parallelism. For these experiments, I utilized the Amazon Elastic Compute Cloud (EC2) web service. In the final analysis, I conclude that the Spark DFC + OR1MP implementation does indeed produce competitive results, in both accuracy and performance. In particular, the Spark implementation performs nearly as well as the MATLAB implementation of OR1MP without any parallelism, and improves performance to a significant degree as the parallelism increases. In addition, the experience demonstrates how Spark's flexible programming model makes it straightforward to implement this parallel and iterative machine learning algorithm.
ContributorsKrouse, Brian (Author) / Ye, Jieping (Thesis advisor) / Liu, Huan (Committee member) / Davulcu, Hasan (Committee member) / Arizona State University (Publisher)
Created2014
Description
ABSTRACT The hormone leptin is an important regulator of body weight and energy balance, while nitric oxide (NO) produced in the blood vessels is beneficial for preventing disease-induced impaired vasodilation and hypertension. Elevations in the free radical superoxide can result in impaired vasodilation through scavenging of NO. Omega 3 is a polyunsaturated fatty acid that is beneficial at reducing body weight and in lowering many cardiovascular risk factors like atherosclerosis. The present study was designed to examine the change in plasma concentrations of leptin, nitric oxide, and the antioxidant superoxide dismutase in addition to examining the association between leptin and NO in healthy normal weight adult female subjects before and following omega 3 intakes. Participants were randomly assigned to either a fish oil group (600 mg per day) or a control group (1000 mg of coconut oil per day) for 8 weeks. Results showed no significant difference in the percent change of leptin over the 8 week supplementation period for either group (15.3±31.9 for fish oil group, 7.83±27 for control group; p=0.763). The percent change in NO was similarly not significantly altered in either group (-1.97±22 decline in fish oil group, 11.8±53.9 in control group; p=0.960). Likewise, the percent change in superoxide dismutase for each group was not significant following 8 weeks of supplementation (fish oil group: 11.94±20.94; control group: 11.8±53.9; p=0.362). The Pearson correlation co-efficient comparing the percent change of both leptin and NO was r2= -0.251 demonstrating a mildly negative, albeit insignificant, relationship between these factors. Together, these findings suggest that daily supplementation with 600 mg omega 3 in healthy females is not beneficial for improving these cardiovascular risk markers. Future studies in this area should include male subjects as well as overweight subjects with larger doses of fish oil that are equivalent to three or more servings per week. The importance of gender cannot be underestimated since estrogen has protective effects in the vasculature of females that may have masked any further protective effects of the fish oil. In addition, overweight individuals are often leptin-resistant and develop impaired vasodilation resulting from superoxide-mediated scavenging of nitric oxide. Therefore, the reported antioxidant and weight loss properties of omega 3 supplementation may greatly benefit overweight individuals.
ContributorsAlanbagy, Samer (Author) / Sweazea, Karen (Thesis advisor) / Johnston, Carol (Committee member) / Shepard, Christina (Committee member) / Lespron, Christy (Committee member) / Arizona State University (Publisher)
Created2014
Description
The omega-3 fatty acids in fatty fish and fish oil, eicosapentanoic acid (EPA) and docosahexanoic acid (DHA), have been associated with a reduction in risk for cardiovascular disease. Blood type is a known contributor to risk for cardiovascular events. This study evaluated the effect of fish oil supplements on cardiovascular risk markers in adults with blood types A or O. An 8-week parallel-arm, randomized, double-blind trial was conducted in healthy adult men and women with either blood type A (BTA) or blood type O (BTO). Participants were randomized to receive fish oil supplements (n=10 [3 BTA/7 BTO]; 2 g [containing 1.2 g EPA+DHA]/d) or a coconut oil supplement (n=7 [3 BTA/4 BTO]; 2 g/d). Markers that were examined included total cholesterol (TC), low-density lipoprotein cholesterol (LDL-C), high-density lipoprotein cholesterol (HDL-C), triglyceride (TG), high-sensitivity C-reactive protein (hsCRP), and hemoglobin A1C (HbA1C). Results indicated that the percent change in LDL cholesterol was significantly greater in the coconut oil group vs the fish oil group (-14.8±12.2% vs +2.8±18.9% respectively, p=0.048). There were no other significant differences between treatment groups, or between blood types A and O, for the other cardiovascular risk markers. Further research with a larger and more diverse sample may yield a more conclusive result.
ContributorsHerring, Dana (Author) / Johnston, Carol (Thesis advisor) / Vega-Lopez, Sonia (Committee member) / Shepard, Christina (Committee member) / Arizona State University (Publisher)
Created2014