Matching Items (3)
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Description
The body is capable of regulating hunger in several ways. Some of these hunger regulation methods are innate, such as genetics, and some, such as the responses to stress and to the smell of food, are innate but can be affected by body conditions such as BMI and physical activity.

The body is capable of regulating hunger in several ways. Some of these hunger regulation methods are innate, such as genetics, and some, such as the responses to stress and to the smell of food, are innate but can be affected by body conditions such as BMI and physical activity. Further, some hunger regulation methods stem from learned behaviors originating from cultural pressures or parenting styles. These latter regulation methods for hunger can be grouped into the categories: emotion, environment, and physical. The factors that regulate hunger can also influence the incidence of disordered eating, such as eating in the absence of hunger (EAH). Eating in the absence of hunger can occur in one of two scenarios, continuous EAH or beginning EAH. College students are at a particularly high risk for EAH and weight gain due to stress, social pressures, and the constant availability of energy dense and nutrient poor food options. The purpose of this study is to validate a modified EAH-C survey in college students and to discover which of the three latent factors (emotion, environment, physical) best predicts continual and beginning EAH. To do so, a modified EAH-C survey, with additional demographic components, was administered to students at a major southwest university. This survey contained two questions, one each for continuing and beginning EAH, regarding 14 factors related to emotional, physical, or environmental reasons that may trigger EAH. The results from this study revealed that the continual and beginning EAH surveys displayed good internal consistency reliability. We found that for beginning and continuing EAH, although emotion is the strongest predictor of EAH, all three latent factors are significant predictors of EAH. In addition, we found that environmental factors had the greatest influence on an individual's likelihood to continue to eat in the absence of hunger. Due to statistical abnormalities and differing numbers of factors in each category, we were unable to determine which of the three factors exerted the greatest influence on an individual's likelihood to begin eating in the absence of hunger. These results can be utilized to develop educational tools aimed at reducing EAH in college students, and ultimately reducing the likelihood for unhealthy weight gain and health complications related to obesity.
ContributorsGoett, Taylor (Author) / Johnston, Carol (Thesis advisor) / Lee, Chong (Committee member) / Lespron, Christy (Committee member) / Arizona State University (Publisher)
Created2013
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Description
The Rapid Eating and Activity Assessment for Participants Short Version (REAP-S), represents a method for rapid diet quality assessment, however, few studies have tested its validity. The Healthy Eating Index-2005 (HEI-2005) and the Diet Quality Index Revised (DQI-R) are tools that effectively assess diet quality, however, both are complex and

The Rapid Eating and Activity Assessment for Participants Short Version (REAP-S), represents a method for rapid diet quality assessment, however, few studies have tested its validity. The Healthy Eating Index-2005 (HEI-2005) and the Diet Quality Index Revised (DQI-R) are tools that effectively assess diet quality, however, both are complex and time consuming. The objective of this study was to evaluate the validity of the REAP-S against the HEI-2005 and the DQI-R. Fifty males, 18 to 33 years of age, completed the REAP-S as well as a 24-hour diet recall. HEI-2005 and DQI-R scores were determined for each 24-hour recall. Scores from the REAP-S were evaluated against the HEI-2005 and DQI-R scores using Spearman rank order correlations and chi square. Modifications were also made to the original method of scoring the REAP-S to evaluate how the correlations transformed when certain questions were removed. The correlation coefficient for REAP-S and the HEI-2005 was 0.367 (P=0.009), and the correlation coefficient for REAP-S and the DQI-R was 0.323 (P=0.022). Chi square determined precision of the REAP-S to the HEI-2005 for overall diet quality at 64% and 62% for the DQI-R and REAP-S. Scores that were considered extreme (n=21) by the HEI-2005 (scores <40 and >60) had 76% precision with REAP-S. The correlation for the modified version of scoring REAP-S with the overall HEI-2005 and DQI-R were 0.395 (P=0.005) and 0.417 (P=0.003) respectively. Chi square statistics revealed the REAP-S accurately captured the diets of high quality versus low quality with 64% precision to the HEI-2005 and 62% of the DQI-R. When evaluating the modified REAP-S scores against the extreme HEI-2005 scores, precision increased to 81%. It appears the REAP-S is an acceptable tool to rapidly assess diet quality. It has a significant, moderate correlation to both the HEI-2005 and the DQI-R, with strong precision as well. Both correlation and precision is strengthened when values are compared to only the extreme scores of the HEI-2005; however, more research studies are needed to evaluate the validity of REAP-S in a more diverse population and to evaluate if changes to select questions can improve its accuracy in assessing diet quality.
ContributorsFawcett, Rachael (Author) / Johnston, Carol (Thesis advisor) / Mayol-Kreiser, Sandra (Committee member) / Wharton, Christopher (Christopher Mack), 1977- (Committee member) / Arizona State University (Publisher)
Created2012
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Description

Due to the COVID-19 pandemic, declared in March of 2020, there have been many lifestyle changes which have likely influenced tobacco smoking behavior. Such lifestyle changes include lockdowns, stay at home orders, reduction in social cues related to smoking, increased stress, and boredom among other things. This study utilized a

Due to the COVID-19 pandemic, declared in March of 2020, there have been many lifestyle changes which have likely influenced tobacco smoking behavior. Such lifestyle changes include lockdowns, stay at home orders, reduction in social cues related to smoking, increased stress, and boredom among other things. This study utilized a cross-sectional survey which looked into these behaviors, primarily perceived risk to COVID-19, and determined if there is an association between perceived risk and education level/race. Education level is a proxy for income and material resources, therefore making it more likely that people with lower levels of education have fewer resources and higher perceived risk to negative effects of COVID-19. Additionally, people of color are often marginalized in the medical community along with being the target of heavy advertising by tobacco companies which have likely impacted risk to COVID-19 as well.

ContributorsLodha, Pratishtha (Author) / Leischow, J. Scott (Thesis director) / Pearson, Jennifer (Committee member) / School of Life Sciences (Contributor) / School of Human Evolution & Social Change (Contributor) / Barrett, The Honors College (Contributor)
Created2021-05