ASU Regents' Professors Open Access Works
The title “Regents’ Professor” is the highest faculty honor awarded at Arizona State University. It is conferred on ASU faculty who have made pioneering contributions in their areas of expertise, who have achieved a sustained level of distinction, and who enjoy national and international recognition for these accomplishments. This collection contains primarily open access works by ASU Regents' Professors.
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- Creators: Franklin, Janet
- Creators: Buman, Matthew
Description
Aim
The aim of this study was to investigate the potential associations of reallocating 30 minutes sedentary time in long bouts (>60 min) to sedentary time in non-bouts, light intensity physical activity (LPA) and moderate- to vigorous physical activity (MVPA) with cardiometabolic risk factors in a population diagnosed with prediabetes or type 2 diabetes.
Methods
Participants diagnosed with prediabetes and type 2 diabetes (n = 124, 50% men, mean [SD] age = 63.8 [7.5] years) were recruited to the physical activity intervention Sophia Step Study. For this study baseline data was used with a cross-sectional design. Time spent in sedentary behaviors in bouts (>60 min) and non-bouts (accrued in <60 min bouts) and physical activity was measured using the ActiGraph GT1M. Associations of reallocating bouted sedentary time to non-bouted sedentary time, LPA and MVPA with cardiometabolic risk factors were examined using an isotemporal substitution framework with linear regression models.
Results
Reallocating 30 minutes sedentary time in bouts to MVPA was associated with lower waist circumference (b = -4.30 95% CI:-7.23, -1.38 cm), lower BMI (b = -1.46 95% CI:-2.60, -0.33 kg/m2) and higher HDL cholesterol levels (b = 0.11 95% CI: 0.02, 0.21 kg/m[superscript 2]. Similar associations were seen for reallocation of sedentary time in non-bouts to MVPA. Reallocating sedentary time in bouts to LPA was associated only with lower waist circumference.
Conclusion
Reallocation of sedentary time in bouts as well as non-bouts to MVPA, but not to LPA, was beneficially associated with waist circumference, BMI and HDL cholesterol in individuals with prediabetes and type 2 diabetes. The results of this study confirm the importance of reallocation sedentary time to MVPA.
The aim of this study was to investigate the potential associations of reallocating 30 minutes sedentary time in long bouts (>60 min) to sedentary time in non-bouts, light intensity physical activity (LPA) and moderate- to vigorous physical activity (MVPA) with cardiometabolic risk factors in a population diagnosed with prediabetes or type 2 diabetes.
Methods
Participants diagnosed with prediabetes and type 2 diabetes (n = 124, 50% men, mean [SD] age = 63.8 [7.5] years) were recruited to the physical activity intervention Sophia Step Study. For this study baseline data was used with a cross-sectional design. Time spent in sedentary behaviors in bouts (>60 min) and non-bouts (accrued in <60 min bouts) and physical activity was measured using the ActiGraph GT1M. Associations of reallocating bouted sedentary time to non-bouted sedentary time, LPA and MVPA with cardiometabolic risk factors were examined using an isotemporal substitution framework with linear regression models.
Results
Reallocating 30 minutes sedentary time in bouts to MVPA was associated with lower waist circumference (b = -4.30 95% CI:-7.23, -1.38 cm), lower BMI (b = -1.46 95% CI:-2.60, -0.33 kg/m2) and higher HDL cholesterol levels (b = 0.11 95% CI: 0.02, 0.21 kg/m[superscript 2]. Similar associations were seen for reallocation of sedentary time in non-bouts to MVPA. Reallocating sedentary time in bouts to LPA was associated only with lower waist circumference.
Conclusion
Reallocation of sedentary time in bouts as well as non-bouts to MVPA, but not to LPA, was beneficially associated with waist circumference, BMI and HDL cholesterol in individuals with prediabetes and type 2 diabetes. The results of this study confirm the importance of reallocation sedentary time to MVPA.
ContributorsRossen, Jenny (Author) / Buman, Matthew (Author) / Johansson, Unn-Britt (Author) / Yngve, Agneta (Author) / Ainsworth, Barbara (Author) / Brismar, Kerstin (Author) / Hagstromer, Maria (Author) / College of Health Solutions (Contributor) / School of Nutrition and Health Promotion (Contributor)
Created2017-07-28
Description
A species’ response to climate change depends on the interaction of biotic and abiotic factors that define future habitat suitability and species’ ability to migrate or adapt. The interactive effects of processes such as fire, dispersal, and predation have not been thoroughly addressed in the climate change literature. Our objective was to examine how life history traits, short-term global change perturbations, and long-term climate change interact to affect the likely persistence of an oak species - Quercus engelmannii (Engelmann oak). Specifically, we combined dynamic species distribution models, which predict suitable habitat, with stochastic, stage-based metapopulation models, which project population trajectories, to evaluate the effects of three global change factors – climate change, land use change, and altered fire frequency – emphasizing the roles of dispersal and seed predation. Our model predicted dramatic reduction in Q. engelmannii abundance, especially under drier climates and increased fire frequency. When masting lowers seed predation rates, decreased masting frequency leads to large abundance decreases. Current rates of dispersal are not likely to prevent these effects, although increased dispersal could mitigate population declines. The results suggest that habitat suitability predictions by themselves may under-estimate the impact of climate change for other species and locations.
ContributorsConlisk, Erin (Author) / Lawson, Dawn (Author) / Syphard, Alexandra D. (Author) / Franklin, Janet (Author) / Flint, Lorraine (Author) / Flint, Alan (Author) / Regan, Helen M. (Author) / College of Liberal Arts and Sciences (Contributor) / School of Geographical Sciences and Urban Planning (Contributor)
Created2012-05-18
Description
Aim
To establish a chronology for late Quaternary avian extinction, extirpation and persistence in the Bahamas, thereby testing the relative roles of climate change and human impact as causes of extinction.
Location
Great Abaco Island (Abaco), Bahamas, West Indies.
Methods
We analysed the resident bird community as sampled by Pleistocene (> 11.7 ka) and Holocene (< 11.7 ka) fossils. Each species was classified as extinct (lost globally), extirpated (gone from Abaco but persists elsewhere), or extant (still resident on Abaco). We compared patterns of extinction, extirpation and persistence to independent estimates of climate and sea level for glacial (late Pleistocene) and interglacial (Holocene) times.
Results
Of 45 bird species identified in Pleistocene fossils, 25 (56%) no longer occur on Abaco (21 extirpated, 4 extinct). Of 37 species recorded in Holocene deposits, 15 (14 extirpated, 1 extinct; total 41%) no longer exist on Abaco. Of the 30 extant species, 12 were recovered as both Pleistocene and Holocene fossils, as were 9 of the 30 extirpated or extinct species. Most of the extinct or extirpated species that were only recorded from Pleistocene contexts are characteristic of open habitats (pine woodlands or grasslands); several of the extirpated species are currently found only where winters are cooler than in the modern or Pleistocene Bahamas. In contrast, most of the extinct or extirpated species recorded from Holocene contexts are habitat generalists.
Main conclusions
The fossil evidence suggests two main times of late Quaternary avian extirpation and extinction in the Bahamas. The first was during the Pleistocene–Holocene transition (PHT; 15–9 ka) and was fuelled by climate change and associated changes in sea level and island area. The second took place during the late Holocene (< 4 ka, perhaps primarily < 1 ka) and can be attributed to human impact. Although some species lost during the PHT are currently found where climates are cooler and drier than in the Bahamas today, a taxonomically and ecologically diverse set of species persisted through that major climate change but did not survive the past millennium of human presence.
ContributorsSteadman, David W. (Author) / Franklin, Janet (Author) / College of Liberal Arts and Sciences (Contributor) / School of Geographical Sciences and Urban Planning (Contributor)
Created2015-03-01
Description
Estimating and projecting population trends using population viability analysis (PVA) are central to identifying species at risk of extinction and for informing conservation management strategies. Models for PVA generally fall within two categories, scalar (count-based) or matrix (demographic). Model structure, process error, measurement error, and time series length all have known impacts in population risk assessments, but their combined impact has not been thoroughly investigated. We tested the ability of scalar and matrix PVA models to predict percent decline over a ten-year interval, selected to coincide with the IUCN Red List criterion A. 3, using data simulated for a hypothetical, short-lived organism with a simple life-history and for a threatened snail, Tasmaphena lamproides. PVA performance was assessed across different time series lengths, population growth rates, and levels of process and measurement error. We found that the magnitude of effects of measurement error, process error, and time series length, and interactions between these, depended on context. We found that high process and measurement error reduced the reliability of both models in predicted percent decline. Both sources of error contributed strongly to biased predictions, with process error tending to contribute to the spread of predictions more than measurement error. Increasing time series length improved precision and reduced bias of predicted population trends, but gains substantially diminished for time series lengths greater than 10-15 years. The simple parameterization scheme we employed contributed strongly to bias in matrix model predictions when both process and measurement error were high, causing scalar models to exhibit similar or greater precision and lower bias than matrix models. Our study provides evidence that, for short-lived species with structured but simple life histories, short time series and simple models can be sufficient for reasonably reliable conservation decision-making, and may be preferable for population projections when unbiased estimates of vital rates cannot be obtained.
ContributorsRueda-Cediel, Pamela (Author) / Anderson, Kurt E. (Author) / Regan, Tracey J. (Author) / Franklin, Janet (Author) / Regan, Helen M. (Author) / College of Liberal Arts and Sciences (Contributor) / School of Geographical Sciences and Urban Planning (Contributor)
Created2015-07-15
Description
Background
The purpose of this study is to determine the feasibility of three widely used wearable sensors in research settings for 24 h monitoring of sleep, sedentary, and active behaviors in middle-aged women.
Methods
Participants were 21 inactive, overweight (M Body Mass Index (BMI) = 29.27 ± 7.43) women, 30 to 64 years (M = 45.31 ± 9.67). Women were instructed to wear each sensor on the non-dominant hip (ActiGraph GT3X+), wrist (GENEActiv), or upper arm (BodyMedia SenseWear Mini) for 24 h/day and record daily wake and bed times for one week over the course of three consecutive weeks. Women received feedback about their daily physical activity and sleep behaviors. Feasibility (i.e., acceptability and demand) was measured using surveys, interviews, and wear time.
Results
Women felt the GENEActiv (94.7 %) and SenseWear Mini (90.0 %) were easier to wear and preferred the placement (68.4, 80 % respectively) as compared to the ActiGraph (42.9, 47.6 % respectively). Mean wear time on valid days was similar across sensors (ActiGraph: M = 918.8 ± 115.0 min; GENEActiv: M = 949.3 ± 86.6; SenseWear: M = 928.0 ± 101.8) and well above other studies using wake time only protocols. Informational feedback was the biggest motivator, while appearance, comfort, and inconvenience were the biggest barriers to wearing sensors. Wear time was valid on 93.9 % (ActiGraph), 100 % (GENEActiv), and 95.2 % (SenseWear) of eligible days. 61.9, 95.2, and 71.4 % of participants had seven valid days of data for the ActiGraph, GENEActiv, and SenseWear, respectively.
Conclusion
Twenty-four hour monitoring over seven consecutive days is a feasible approach in middle-aged women. Researchers should consider participant acceptability and demand, in addition to validity and reliability, when choosing a wearable sensor. More research is needed across populations and study designs.
The purpose of this study is to determine the feasibility of three widely used wearable sensors in research settings for 24 h monitoring of sleep, sedentary, and active behaviors in middle-aged women.
Methods
Participants were 21 inactive, overweight (M Body Mass Index (BMI) = 29.27 ± 7.43) women, 30 to 64 years (M = 45.31 ± 9.67). Women were instructed to wear each sensor on the non-dominant hip (ActiGraph GT3X+), wrist (GENEActiv), or upper arm (BodyMedia SenseWear Mini) for 24 h/day and record daily wake and bed times for one week over the course of three consecutive weeks. Women received feedback about their daily physical activity and sleep behaviors. Feasibility (i.e., acceptability and demand) was measured using surveys, interviews, and wear time.
Results
Women felt the GENEActiv (94.7 %) and SenseWear Mini (90.0 %) were easier to wear and preferred the placement (68.4, 80 % respectively) as compared to the ActiGraph (42.9, 47.6 % respectively). Mean wear time on valid days was similar across sensors (ActiGraph: M = 918.8 ± 115.0 min; GENEActiv: M = 949.3 ± 86.6; SenseWear: M = 928.0 ± 101.8) and well above other studies using wake time only protocols. Informational feedback was the biggest motivator, while appearance, comfort, and inconvenience were the biggest barriers to wearing sensors. Wear time was valid on 93.9 % (ActiGraph), 100 % (GENEActiv), and 95.2 % (SenseWear) of eligible days. 61.9, 95.2, and 71.4 % of participants had seven valid days of data for the ActiGraph, GENEActiv, and SenseWear, respectively.
Conclusion
Twenty-four hour monitoring over seven consecutive days is a feasible approach in middle-aged women. Researchers should consider participant acceptability and demand, in addition to validity and reliability, when choosing a wearable sensor. More research is needed across populations and study designs.
ContributorsHuberty, Jennifer (Author) / Ehlers, Diane (Author) / Kurka, Jonathan (Author) / Ainsworth, Barbara (Author) / Buman, Matthew (Author) / College of Health Solutions (Contributor) / School of Nutrition and Health Promotion (Contributor)
Created2015-07-30
Validity of the Rapid Eating Assessment for Patients for assessing dietary patterns in NCAA athletes
Description
Background
Athletes may be at risk for developing adverse health outcomes due to poor eating behaviors during college. Due to the complex nature of the diet, it is difficult to include or exclude individual food items and specific food groups from the diet. Eating behaviors may better characterize the complex interactions between individual food items and specific food groups. The purpose was to examine the Rapid Eating Assessment for Patients survey (REAP) as a valid tool for analyzing eating behaviors of NCAA Division-I male and female athletes using pattern identification. Also, to investigate the relationships between derived eating behavior patterns and body mass index (BMI) and waist circumference (WC) while stratifying by sex and aesthetic nature of the sport.
Methods
Two independent samples of male (n = 86; n = 139) and female (n = 64; n = 102) collegiate athletes completed the REAP in June-August 2011 (n = 150) and June-August 2012 (n = 241). Principal component analysis (PCA) determined possible factors using wave-1 athletes. Exploratory (EFA) and confirmatory factor analyses (CFA) determined factors accounting for error and confirmed model fit in wave-2 athletes. Wave-2 athletes' BMI and WC were recorded during a physical exam and sport participation determined classification in aesthetic and non-aesthetic sport. Mean differences in eating behavior pattern score were explored. Regression models examined interactions between pattern scores, participation in aesthetic or non-aesthetic sport, and BMI and waist circumference controlling for age and race.
Results
A 5-factor PCA solution accounting for 60.3% of sample variance determined fourteen questions for EFA and CFA. A confirmed solution revealed patterns of Desserts, Healthy food, Meats, High-fat food, and Dairy. Pattern score (mean ± SE) differences were found, as non-aesthetic sport males had a higher (better) Dessert score than aesthetic sport males (2.16 ± 0.07 vs. 1.93 ± 0.11). Female aesthetic athletes had a higher score compared to non-aesthetic female athletes for the Dessert (2.11 ± 0.11 vs. 1.88 ± 0.08), Meat (1.95 ± 0.10 vs. 1.72 ± 0.07), High-fat food (1.70 ± 0.08 vs. 1.46 ± 0.06), and Dairy (1.70 ± 0.11 vs. 1.43 ± 0.07) patterns.
Conclusions
REAP is a construct valid tool to assess dietary patterns in college athletes. In light of varying dietary patterns, college athletes should be evaluated for healthful and unhealthful eating behaviors.
Athletes may be at risk for developing adverse health outcomes due to poor eating behaviors during college. Due to the complex nature of the diet, it is difficult to include or exclude individual food items and specific food groups from the diet. Eating behaviors may better characterize the complex interactions between individual food items and specific food groups. The purpose was to examine the Rapid Eating Assessment for Patients survey (REAP) as a valid tool for analyzing eating behaviors of NCAA Division-I male and female athletes using pattern identification. Also, to investigate the relationships between derived eating behavior patterns and body mass index (BMI) and waist circumference (WC) while stratifying by sex and aesthetic nature of the sport.
Methods
Two independent samples of male (n = 86; n = 139) and female (n = 64; n = 102) collegiate athletes completed the REAP in June-August 2011 (n = 150) and June-August 2012 (n = 241). Principal component analysis (PCA) determined possible factors using wave-1 athletes. Exploratory (EFA) and confirmatory factor analyses (CFA) determined factors accounting for error and confirmed model fit in wave-2 athletes. Wave-2 athletes' BMI and WC were recorded during a physical exam and sport participation determined classification in aesthetic and non-aesthetic sport. Mean differences in eating behavior pattern score were explored. Regression models examined interactions between pattern scores, participation in aesthetic or non-aesthetic sport, and BMI and waist circumference controlling for age and race.
Results
A 5-factor PCA solution accounting for 60.3% of sample variance determined fourteen questions for EFA and CFA. A confirmed solution revealed patterns of Desserts, Healthy food, Meats, High-fat food, and Dairy. Pattern score (mean ± SE) differences were found, as non-aesthetic sport males had a higher (better) Dessert score than aesthetic sport males (2.16 ± 0.07 vs. 1.93 ± 0.11). Female aesthetic athletes had a higher score compared to non-aesthetic female athletes for the Dessert (2.11 ± 0.11 vs. 1.88 ± 0.08), Meat (1.95 ± 0.10 vs. 1.72 ± 0.07), High-fat food (1.70 ± 0.08 vs. 1.46 ± 0.06), and Dairy (1.70 ± 0.11 vs. 1.43 ± 0.07) patterns.
Conclusions
REAP is a construct valid tool to assess dietary patterns in college athletes. In light of varying dietary patterns, college athletes should be evaluated for healthful and unhealthful eating behaviors.
ContributorsKurka, Jonathan (Author) / Buman, Matthew (Author) / Ainsworth, Barbara (Author) / College of Health Solutions (Contributor) / School of Nutrition and Health Promotion (Contributor)
Created2014-08-15
Description
Tree and shrub abundance has increased in many grasslands causing changes in ecosystem carbon and nitrogen pools that are related to patterns of woody plant distribution. However, with regard to spatial patterns of shrub proliferation, little is known about how they are influenced by grazing or the extent to which they are influenced by intraspecific interactions. We addressed these questions by quantifying changes in the spatial distribution of Prosopis velutina (mesquite) shrubs over 74 years on grazed and protected grasslands. Livestock are effective agents of mesquite dispersal and mesquite plants have lateral roots extending well beyond the canopy. We therefore hypothesized that mesquite distributions would be random on grazed areas mainly due to cattle dispersion and clustered on protected areas due to decreased dispersal and interspecific interference with grasses; and that clustered or random distributions at early stages of encroachment would give way to regular distributions as stands matured and density-dependent interactions intensified. Assessments in 1932, 1948, and 2006 supported the first hypothesis, but we found no support for the second. In fact, clustering intensified with time on the protected area and the pattern remained random on the grazed site. Although shrub density increased on both areas between 1932 and 2006, we saw no progression toward a regular distribution indicative of density-dependent interactions. We propose that processes related to seed dispersal, grass–shrub seedling interactions, and hydrological constraints on shrub size interact to determine vegetation structure in grassland-to-shrubland state changes with implications for ecosystem function and management.
ContributorsBrowning, Dawn M. (Author) / Franklin, Janet (Author) / Archer, Steven R. (Author) / Gillan, Jeffrey K. (Author) / Guertin, D. Phillip (Author) / College of Liberal Arts and Sciences (Contributor) / School of Geographical Sciences and Urban Planning (Contributor)
Created2014-09-01
Description
Species distribution modeling (SDM) is a methodology that has been widely used in the past two decades for developing quantitative, empirical, predictive models of species–environment relationships. SDM methods could be more broadly applied than they currently are to address research questions in archaeology and paleoanthropology. Specifically, SDM can be used to hindcast paleodistributions of species and ecological communities (paleo-SDM) for time periods and locations of prehistoric human occupation. Paleo-SDM may be a powerful tool for understanding human prehistory if used to hindcast the distributions of plants, animals and ecological communities that were key resources for prehistoric humans and to use this information to reconstruct the resource landscapes (paleoscapes) of prehistoric people. Components of the resource paleoscape include species (game animals, food plants), habitats, and geologic features and landforms associated with stone materials for tools, pigments, and so forth. We first review recent advances in SDM as it has been used to hindcast paleodistributions of plants and animals in the field of paleobiology. We then compare the paleo-SDM approach to paleoenvironmental reconstructions modeled from zooarchaeological and archaeobotanical records, widely used in archaeology and paleoanthropology. Next, we describe the less well developed but promising approach of using paleo-SDM methods to reconstruct resource paleoscapes. We argue that paleo-SDM offers an explicitly deductive strategy that generates spatial predictions grounded in strong theoretical understandings of the relation between species, habitat distributions and environment. Because of their limited sampling of space and time, archaeobiological records may be better suited for paleo-SDM validation than directly for paleoenvironmental reconstruction. We conclude by discussing the data requirements, limitations and potential for using predictive modeling to reconstruct resource paleoscapes. There is a need for improved paleoclimate models, improved paleoclimate proxy and species paleodistribution data for model validation, attention to scale issues, and rigorous modeling methods including mechanistic models.
ContributorsFranklin, Janet (Author) / Potts, Alastair (Author) / Fisher, Erich (Author) / Cowling, Richard M. (Author) / Marean, Curtis (Author) / College of Liberal Arts and Sciences (Contributor) / School of Geographical Sciences and Urban Planning (Contributor) / School of Human Evolution and Social Change (Contributor) / Institute of Human Origins (Contributor)
Created2014-12-17