Matching Items (78)
Description
Obesity and related health disparities including type 2 diabetes disproportionately impact Latino youth. These health disparities may be the result of gene-environment interactions, but limited research has examined these interactions in the pediatric age group. Lifestyle intervention is the cornerstone for preventing diabetes among high-risk populations and epigenetic and genetic factors may help explain the biological mechanisms underlying diabetes risk reduction following lifestyle changes. MicroRNAs (miRNAs) are small, non-coding RNA’s that regulate gene expression and have emerged as potential biomarkers for predicting type 2 diabetes risk in adults but have yet to be applied to youth. Therefore, the purpose of this study was to identify changes in miRNA expression among Latino youth with prediabetes (4 female/2 male, ages 14-16, BMI percentile 99 ±.2) who participated in a 12-week lifestyle intervention focused on increasing physical activity and improving nutrition-related behaviors.
ContributorsKarch, Jamie (Co-author) / Day, Samantha (Co-author) / Shaibi, Gabriel (Thesis director) / Coletta, Dawn (Committee member) / Arizona State University. College of Nursing & Healthcare Innovation (Contributor) / College of Integrative Sciences and Arts (Contributor) / Barrett, The Honors College (Contributor)
Created2017-05
Description
Objective: Increasing fruit/vegetable (FV) consumption and decreasing waste during the school lunch is a public health priority. Understanding how serving style of FV impacts FV consumption and waste may be an effective means to changing nutrition behaviors in schools. This study examined whether students were more likely to select, consume, and waste FV when FVs were cut vs. whole. Methods: Baseline data from the ASU School Lunch Study was used to explore associations between cut vs. whole FV serving style and objectively measured FV selection, consumption, and waste and grade level interactions among a random selection of students (n=6804; 47.8% female; 78.8% BIPOC) attending Arizona elementary, middle, and high schools (N=37). Negative binomial regression models evaluated serving style on FV weight (grams) selected, consumed, and wasted, adjusted for sociodemographics and school.
Results: Students were more likely to select cut FVs (IRR=1.11; 95% CI: 1.04, 1.18) and waste cut FVs (IRR=1.20; 95% CI: 1.04, 1.39); however, no differences were observed in the overall consumption of cut vs. whole FVs. Grade-level interactions impacted students’ selection of FVs. Middle school students had a significantly higher effect modification for the selection of cut FVs (IRR=1.18; p=0.006) compared to high school and elementary students. Further, high school students had a significantly lower effect modification for the selection of cut FVs (IRR=0.83; p=0.010) compared to middle and elementary students. No other grade-level interactions were observed.
Discussion: Serving style of FV may impact how much FV is selected and wasted, but further research is needed to determine causality between these variables.
ContributorsJames, Amber Chandarana (Author) / Bruening, Meredith (Thesis advisor) / Adams, Marc (Thesis advisor) / Koskan, Alexis (Committee member) / Arizona State University (Publisher)
Created2021
Description
This work presents a thorough analysis of reconstruction of global wave fields (governed by the inhomogeneous wave equation and the Maxwell vector wave equation) from sensor time series data of the wave field. Three major problems are considered. First, an analysis of circumstances under which wave fields can be fully reconstructed from a network of fixed-location sensors is presented. It is proven that, in many cases, wave fields can be fully reconstructed from a single sensor, but that such reconstructions can be sensitive to small perturbations in sensor placement. Generally, multiple sensors are necessary. The next problem considered is how to obtain a global approximation of an electromagnetic wave field in the presence of an amplifying noisy current density from sensor time series data. This type of noise, described in terms of a cylindrical Wiener process, creates a nonequilibrium system, derived from Maxwell’s equations, where variance increases with time. In this noisy system, longer observation times do not generally provide more accurate estimates of the field coefficients. The mean squared error of the estimates can be decomposed into a sum of the squared bias and the variance. As the observation time $\tau$ increases, the bias decreases as $\mathcal{O}(1/\tau)$ but the variance increases as $\mathcal{O}(\tau)$. The contrasting time scales imply the existence of an ``optimal'' observing time (the bias-variance tradeoff). An iterative algorithm is developed to construct global approximations of the electric field using the optimal observing times. Lastly, the effect of sensor acceleration is considered. When the sensor location is fixed, measurements of wave fields composed of plane waves are almost periodic and so can be written in terms of a standard Fourier basis. When the sensor is accelerating, the resulting time series is no longer almost periodic. This phenomenon is related to the Doppler effect, where a time transformation must be performed to obtain the frequency and amplitude information from the time series data. To obtain frequency and amplitude information from accelerating sensor time series data in a general inhomogeneous medium, a randomized algorithm is presented. The algorithm is analyzed and example wave fields are reconstructed.
ContributorsBarclay, Bryce Matthew (Author) / Mahalov, Alex (Thesis advisor) / Kostelich, Eric J (Thesis advisor) / Moustaoui, Mohamed (Committee member) / Motsch, Sebastien (Committee member) / Platte, Rodrigo (Committee member) / Arizona State University (Publisher)
Created2023
Description
Weight stigma is a prevalent issue that has detrimental effects on health for both adolescents and parents. Adolescents are in a formative stage of life, so it is important to understand how parents may impact adolescents’ own experience with weight stigma. Past research has examined adolescent coping, body image, and associated stigma in the context of the parent-child relationship. This cross-sectional study examined self-reported weight stigma experience and internalization within 42 parent/adolescent dyads to provide greater understanding of how adolescents and parents are experiencing and internalizing weight stigma independently and transversely.
ContributorsMillett, Emma (Author) / McEntee, Mindy (Thesis director) / Adams, Marc (Committee member) / Barrett, The Honors College (Contributor) / College of Health Solutions (Contributor)
Created2022-12
Description
Climate is a critical determinant of agricultural productivity, and the ability to accurately predict this productivity is necessary to provide guidance regarding food security and agricultural management. Previous predictions vary in approach due to the myriad of factors influencing agricultural productivity but generally suggest long-term declines in productivity and agricultural land suitability under climate change. In this paper, I relate predicted climate changes to yield for three major United States crops, namely corn, soybeans, and wheat, using a moderate emissions scenario. By adopting data-driven machine learning approaches, I used the following machine learning methods: random forest (RF), extreme gradient boosting (XGB), and artificial neural networks (ANN) to perform comparative analysis and ensemble methodology. I omitted the western US due to the region's susceptibility to water stress and the prevalence of artificial irrigation as a means to compensate for dry conditions. By considering only climate, the model's results suggest an ensemble mean decline in crop yield of 23.4\% for corn, 19.1\% for soybeans, and 7.8\% for wheat between the years of 2017 and 2100. These results emphasize potential negative impacts of climate change on the current agricultural industry as a result of shifting bio-climactic conditions.
ContributorsSwarup, Shray (Author) / Eikenberry, Steffen (Thesis director) / Mahalov, Alex (Committee member) / Barrett, The Honors College (Contributor) / Computer Science and Engineering Program (Contributor)
Created2023-05
The Association Between Time to Eat and Students Fruit & Vegetable Consumption, Selection, and Waste
Description
Background: Studies have examined student fruit/vegetable (FV) consumption, selection, and waste related to lunch duration and found that longer duration at lunch was associated with greater consumption, selection, and reduced waste. However, few studies have investigated the relationship between time to eat and FVs. The aim of this research is to analyze the relationship between objective time to students took to eat (“time to eat”) as it relates to their fruit and vegetable consumption, selection, and plate waste.in elementary, middle, and high schools. Methods: A secondary analysis of cross-sectional study of 37 Arizona schools to discover the differences in the selection, consumption, and waste of FVs from students (Full N = 2226, Elementary N = 630, Middle School N = 699, High School N = 897) using objective time to eat measures. Zero-inflated negative binomial regressions examined differences in FV grams selected, consumed, and wasted adjusted for sociodemographics including race, ethnicity, eligibility for free or reduced lunch, academic year, and sex and clustering for students within schools. Results are presented across school level (elementary, middle, and high school).
Results: The average time taken to eat ranged from 10-12 minutes for all students. The association of time to eat and lunch duration were not closely related (r=0.03, p = 0.172). In the count model for every additional minute spent, there was a 0.5% greater likelihood of selecting FVs for elementary kids among those who took any FVs. In the zero-inflated model, it was found that there was a statistically significant relationship between time spent eating and the selection of fruits and vegetables. For the total sample and high schoolers, a minute more of eating time was associated with a 4.3% and 8.8% greater odds of selecting FV. This means that longer eating time increased the likelihood of choosing fruits and vegetables. The results indicated that the longer students took to eat, the higher the likelihood of consuming more of FVs. Each 10 more minutes spent eating (i.e., time to eat) is associated with a 5% increase in grams of FV selected relative to mean (for those that chose FV) over 1 week this equates to 32 g increase of FV selected. However, for middle schoolers, the time to eat was not found to be significant in relation to the grams of fruits and vegetables consumed. There was some significance in the sociodemographic factors such as gender (all) and other (middle school). There was a relationship between time taken to eat and waste as a proportion for fruits and vegetables. For example, among those among the students who wasted something (as a proportion of selection), each additional 10 minutes of eating time was associated with a .6% decrease in waste relative to the mean (for those who chose fruits and vegetables) over a week, resulting in a decrease in waste percentage of 16.5%. Among high schoolers, males had a slightly higher odds of wasting a proportion of fruits and vegetables.
Conclusions: This study aimed to examine the association between the time students take to eat during lunch and their fruit and vegetable (FV) consumption, selection, and plate waste. The findings revealed that the time to eat was related to FV consumption, depending on the school level. However, it was not significantly associated with FV selection or waste. The study emphasized the need for further research on time to eat, distinguishing it from the duration of lunch. Longer lunch periods and adequate time could influence better food choices, increased FV consumption, and reduced waste. The study highlighted the importance of interventions and school policies promoting healthier food choices and providing sufficient time for students to eat. Future research should validate these findings and explore the impact of socialization opportunities on promoting healthier eating habits. Understanding the relationship between lunch duration, time to eat, and students' dietary behaviors can contribute to improved health outcomes and inform effective strategies in school settings.
ContributorsDandridge, Christina Marie (Author) / Adams, Marc (Thesis advisor) / Whisner, Corrie (Committee member) / Bruening, Meg (Committee member) / Arizona State University (Publisher)
Created2023
Description
Tools designed to help match people with behaviors they identify as likely to lead to a successful behavioral outcome remain under-researched. This study assessed the effect of a participant-driven behavior-matching intervention on 1) the adoption of a new behavior related to fruit and vegetable (F&V) consumption, 2) study attrition, and 3) changes in F&V consumption. In this two-arm randomized controlled trial, 64 adults who did not meet standard F&V recommendations were allocated to an intervention (n=33) or control group (n=31). Participants in the intervention group ranked 20 F&V-related behaviors according to their perceived likelihood of engagement in the behavior and their perception of the behavior’s efficacy in increasing F&V consumption. Participants in the intervention group were subsequently shown the list of 20 behaviors in order of their provided rankings, with the highest-ranked behaviors at the top, and were asked to choose a behavior they would like to perform daily for 4 weeks. The control group chose from a random-order list of the same 20 behaviors to adopt daily for 4 weeks. During the study period, text messages were sent to all participants 90 minutes before their reported bedtime to collect Yes/No data reflecting successful behavior engagement each day. The binary repeated-measures data collected from the text messages was analyzed using mixed-effects logistic regression, differences in attrition were assessed using log-rank analysis, and change scores in F&V consumption were compared between the two groups using the Man-Whitney U test. P<0.05 indicated significance. The rate of successful behavior adoption did not differ significantly between the two groups (b=0.09, 95%CI= -0.81, 0.98, p=0.85). The log rank test results indicated that there was no significant difference in attrition between the two groups (χ2=2.68, df=1, p=0.10). F&V consumption increased significantly over the 4 weeks in the total sample (Z=-5.86, p<0.001), but no differences in F&V change scores were identified between the control and intervention groups (Z=-0.21, p=0.84). The behavior-matching tool assessed in this study did not significantly improve behavior adoption, study attrition, or F&V intake over 4 weeks.
ContributorsCosgrove, Kelly Sarah (Author) / Wharton, Christopher (Thesis advisor) / Adams, Marc (Committee member) / DesRoches, Tyler (Committee member) / Grebitus, Carola (Committee member) / Johnston, Carol (Committee member) / Arizona State University (Publisher)
Created2023
Description
Earth-system models describe the interacting components of the climate system and
technological systems that affect society, such as communication infrastructures. Data
assimilation addresses the challenge of state specification by incorporating system
observations into the model estimates. In this research, a particular data
assimilation technique called the Local Ensemble Transform Kalman Filter (LETKF) is
applied to the ionosphere, which is a domain of practical interest due to its effects
on infrastructures that depend on satellite communication and remote sensing. This
dissertation consists of three main studies that propose strategies to improve space-
weather specification during ionospheric extreme events, but are generally applicable
to Earth-system models:
Topic I applies the LETKF to estimate ion density with an idealized model of
the ionosphere, given noisy synthetic observations of varying sparsity. Results show
that the LETKF yields accurate estimates of the ion density field and unobserved
components of neutral winds even when the observation density is spatially sparse
(2% of grid points) and there is large levels (40%) of Gaussian observation noise.
Topic II proposes a targeted observing strategy for data assimilation, which uses
the influence matrix diagnostic to target errors in chosen state variables. This
strategy is applied in observing system experiments, in which synthetic electron density
observations are assimilated with the LETKF into the Thermosphere-Ionosphere-
Electrodynamics Global Circulation Model (TIEGCM) during a geomagnetic storm.
Results show that assimilating targeted electron density observations yields on
average about 60%–80% reduction in electron density error within a 600 km radius of
the observed location, compared to 15% reduction obtained with randomly placed
vertical profiles.
Topic III proposes a methodology to account for systematic model bias arising
ifrom errors in parametrized solar and magnetospheric inputs. This strategy is ap-
plied with the TIEGCM during a geomagnetic storm, and is used to estimate the
spatiotemporal variations of bias in electron density predictions during the
transitionary phases of the geomagnetic storm. Results show that this strategy reduces
error in 1-hour predictions of electron density by about 35% and 30% in polar regions
during the main and relaxation phases of the geomagnetic storm, respectively.
technological systems that affect society, such as communication infrastructures. Data
assimilation addresses the challenge of state specification by incorporating system
observations into the model estimates. In this research, a particular data
assimilation technique called the Local Ensemble Transform Kalman Filter (LETKF) is
applied to the ionosphere, which is a domain of practical interest due to its effects
on infrastructures that depend on satellite communication and remote sensing. This
dissertation consists of three main studies that propose strategies to improve space-
weather specification during ionospheric extreme events, but are generally applicable
to Earth-system models:
Topic I applies the LETKF to estimate ion density with an idealized model of
the ionosphere, given noisy synthetic observations of varying sparsity. Results show
that the LETKF yields accurate estimates of the ion density field and unobserved
components of neutral winds even when the observation density is spatially sparse
(2% of grid points) and there is large levels (40%) of Gaussian observation noise.
Topic II proposes a targeted observing strategy for data assimilation, which uses
the influence matrix diagnostic to target errors in chosen state variables. This
strategy is applied in observing system experiments, in which synthetic electron density
observations are assimilated with the LETKF into the Thermosphere-Ionosphere-
Electrodynamics Global Circulation Model (TIEGCM) during a geomagnetic storm.
Results show that assimilating targeted electron density observations yields on
average about 60%–80% reduction in electron density error within a 600 km radius of
the observed location, compared to 15% reduction obtained with randomly placed
vertical profiles.
Topic III proposes a methodology to account for systematic model bias arising
ifrom errors in parametrized solar and magnetospheric inputs. This strategy is ap-
plied with the TIEGCM during a geomagnetic storm, and is used to estimate the
spatiotemporal variations of bias in electron density predictions during the
transitionary phases of the geomagnetic storm. Results show that this strategy reduces
error in 1-hour predictions of electron density by about 35% and 30% in polar regions
during the main and relaxation phases of the geomagnetic storm, respectively.
ContributorsDurazo, Juan, Ph.D (Author) / Kostelich, Eric J. (Thesis advisor) / Mahalov, Alex (Thesis advisor) / Tang, Wenbo (Committee member) / Moustaoui, Mohamed (Committee member) / Platte, Rodrigo (Committee member) / Arizona State University (Publisher)
Created2018
Description
Objective: It’s not well understood how youth perceive existing fruit and vegetable (FV) marketing materials available in schools. This ancillary study sought to assess the acceptability of FV marketing materials freely available to schools among adolescents in grades 6-12.
Methods: Middle and high school adolescents (n=40; 50% female; 52.5% Hispanic) in the Phoenix, AZ area were asked to rank marketing materials (n=35) from favorite to least favorite in four categories: table tents, medium posters, large posters and announcements. Favorites were determined by showing participants two items at a time and having them choose which they preferred; items were displayed to each adolescent in a random order. Adolescents participated in a 20-30 minute interview on their favorite items in each category based on acceptance/attractiveness, comprehension, relevance, motivation and uniqueness of the materials. A content analysis was performed on top rated marketing materials. Top rated marketing materials were determined by the number of times the advertisement was ranked first in its category.
Results: An analysis of the design features of the items indicated that most participants (84%) preferred marketing materials with more than 4 color groups. Participant preference of advertisement length and word count was varied. A total of 5 themes and 20 subthemes emerged when participants discussed their favorite FV advertisements. Themes included: likes (e.g., colors, length, FV shown), dislikes (e.g., length, FV shown), health information (e.g., vitamin shown), comprehension (e.g., doesn’t recognize FV), and social aspects (e.g., peer opinion). Peer opinion often influenced participant opinion on marketing materials. Participants often said peers wouldn’t like the advertisements shown: “…kids my age think that vegetables are not good, and they like food more than vegetables.” Fruits and vegetable pictured as well as the information in the marketing materials also influenced adolescent preference.
Conclusion: Students preferred advertisements with more color and strong visual aspects. Word count had minimal influence on their opinions of the marketing materials, while information mentioned and peer opinion did have a positive effect. Further research needs to be done to determine if there is a link between adolescent preferences on FV marketing materials and FV consumption habits.
Methods: Middle and high school adolescents (n=40; 50% female; 52.5% Hispanic) in the Phoenix, AZ area were asked to rank marketing materials (n=35) from favorite to least favorite in four categories: table tents, medium posters, large posters and announcements. Favorites were determined by showing participants two items at a time and having them choose which they preferred; items were displayed to each adolescent in a random order. Adolescents participated in a 20-30 minute interview on their favorite items in each category based on acceptance/attractiveness, comprehension, relevance, motivation and uniqueness of the materials. A content analysis was performed on top rated marketing materials. Top rated marketing materials were determined by the number of times the advertisement was ranked first in its category.
Results: An analysis of the design features of the items indicated that most participants (84%) preferred marketing materials with more than 4 color groups. Participant preference of advertisement length and word count was varied. A total of 5 themes and 20 subthemes emerged when participants discussed their favorite FV advertisements. Themes included: likes (e.g., colors, length, FV shown), dislikes (e.g., length, FV shown), health information (e.g., vitamin shown), comprehension (e.g., doesn’t recognize FV), and social aspects (e.g., peer opinion). Peer opinion often influenced participant opinion on marketing materials. Participants often said peers wouldn’t like the advertisements shown: “…kids my age think that vegetables are not good, and they like food more than vegetables.” Fruits and vegetable pictured as well as the information in the marketing materials also influenced adolescent preference.
Conclusion: Students preferred advertisements with more color and strong visual aspects. Word count had minimal influence on their opinions of the marketing materials, while information mentioned and peer opinion did have a positive effect. Further research needs to be done to determine if there is a link between adolescent preferences on FV marketing materials and FV consumption habits.
ContributorsPisano, Sydney Alexis (Author) / Bruening, Meg (Thesis advisor) / Adams, Marc (Committee member) / Grgich, Traci (Committee member) / Arizona State University (Publisher)
Created2019
Description
Two urban flows are analyzed, one concerned with pollutant transport in a Phoenix, Arizona neighborhood and the other with windshear detection at the Hong Kong International Airport (HKIA).
Lagrangian measures, identified with finite-time Lyapunov exponents, are first used to characterize transport patterns of inertial pollutant particles. Motivated by actual events the focus is on flows in realistic urban geometry. Both deterministic and stochastic transport patterns are identified, as inertial Lagrangian coherent structures. For the deterministic case, the organizing structures are well defined and are extracted at different hours of a day to reveal the variability of coherent patterns. For the stochastic case, a random displacement model for fluid particles is formulated, and used to derive the governing equations for inertial particles to examine the change in organizing structures due to ``zeroth-order'' random noise. It is found that, (1) the Langevin equation for inertial particles can be reduced to a random displacement model; (2) using random noise based on inhomogeneous turbulence, whose diffusivity is derived from $k$-$\epsilon$ models, major coherent structures survive to organize local flow patterns and weaker structures are smoothed out due to random motion.
A study of three-dimensional Lagrangian coherent structures (LCS) near HKIA is then presented and related to previous developments of two-dimensional (2D) LCS analyses in detecting windshear experienced by landing aircraft. The LCS are contrasted among three independent models and against 2D coherent Doppler light detection and ranging (LIDAR) data. Addition of the velocity information perpendicular to the lidar scanning cone helps solidify flow structures inferred from previous studies; contrast among models reveals the intramodel variability; and comparison with flight data evaluates the performance among models in terms of Lagrangian analyses. It is found that, while the three models and the LIDAR do recover similar features of the windshear experienced by a landing aircraft (along the landing trajectory), their Lagrangian signatures over the entire domain are quite different - a portion of each numerical model captures certain features resembling those LCS extracted from independent 2D LIDAR analyses based on observations. Overall, it was found that the Weather Research and Forecast (WRF) model provides the best agreement with the LIDAR data.
Finally, the three-dimensional variational (3DVAR) data assimilation scheme in WRF is used to incorporate the LIDAR line of sight velocity observations into the WRF model forecast at HKIA. Using two different days as test cases, it is found that the LIDAR data can be successfully and consistently assimilated into WRF. Using the updated model forecast LCS are extracted along the LIDAR scanning cone and compare to onboard flight data. It is found that the LCS generated from the updated WRF forecasts are generally better correlated with the windshear experienced by landing aircraft as compared to the LIDAR extracted LCS alone, which suggests that such a data assimilation scheme could be used for the prediction of windshear events.
Lagrangian measures, identified with finite-time Lyapunov exponents, are first used to characterize transport patterns of inertial pollutant particles. Motivated by actual events the focus is on flows in realistic urban geometry. Both deterministic and stochastic transport patterns are identified, as inertial Lagrangian coherent structures. For the deterministic case, the organizing structures are well defined and are extracted at different hours of a day to reveal the variability of coherent patterns. For the stochastic case, a random displacement model for fluid particles is formulated, and used to derive the governing equations for inertial particles to examine the change in organizing structures due to ``zeroth-order'' random noise. It is found that, (1) the Langevin equation for inertial particles can be reduced to a random displacement model; (2) using random noise based on inhomogeneous turbulence, whose diffusivity is derived from $k$-$\epsilon$ models, major coherent structures survive to organize local flow patterns and weaker structures are smoothed out due to random motion.
A study of three-dimensional Lagrangian coherent structures (LCS) near HKIA is then presented and related to previous developments of two-dimensional (2D) LCS analyses in detecting windshear experienced by landing aircraft. The LCS are contrasted among three independent models and against 2D coherent Doppler light detection and ranging (LIDAR) data. Addition of the velocity information perpendicular to the lidar scanning cone helps solidify flow structures inferred from previous studies; contrast among models reveals the intramodel variability; and comparison with flight data evaluates the performance among models in terms of Lagrangian analyses. It is found that, while the three models and the LIDAR do recover similar features of the windshear experienced by a landing aircraft (along the landing trajectory), their Lagrangian signatures over the entire domain are quite different - a portion of each numerical model captures certain features resembling those LCS extracted from independent 2D LIDAR analyses based on observations. Overall, it was found that the Weather Research and Forecast (WRF) model provides the best agreement with the LIDAR data.
Finally, the three-dimensional variational (3DVAR) data assimilation scheme in WRF is used to incorporate the LIDAR line of sight velocity observations into the WRF model forecast at HKIA. Using two different days as test cases, it is found that the LIDAR data can be successfully and consistently assimilated into WRF. Using the updated model forecast LCS are extracted along the LIDAR scanning cone and compare to onboard flight data. It is found that the LCS generated from the updated WRF forecasts are generally better correlated with the windshear experienced by landing aircraft as compared to the LIDAR extracted LCS alone, which suggests that such a data assimilation scheme could be used for the prediction of windshear events.
ContributorsKnutson, Brent (Author) / Tang, Wenbo (Thesis advisor) / Calhoun, Ronald (Committee member) / Huang, Huei-Ping (Committee member) / Kostelich, Eric (Committee member) / Mahalov, Alex (Committee member) / Arizona State University (Publisher)
Created2018