Doyle, Emma E. H.; Mcclure, John; Potter, Sally H.; Becker, Julia S.; Johnston, David M.; Lindell, Michael K.; Johal, Sarbjit; Fraser, Stuart A.; Coomer, Maureen A. (2018). Motivations to Prepare After the 2013 Cook Strait Earthquake, N.Z. International Journal Of Disaster Risk Reduction, 31, 637 – 649.
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Abstract
We investigated responses to the 2013 Cook Strait earthquake sequence, New Zealand. This included two foreshocks (M5.7 and M5.8) and a mainshock doublet pair: M6.5 Cook Strait (CS) earthquake on 21st July and M6.6 Lake Grassmere (LG) earthquake on Friday 16th August. We examined relationships between preparedness, experience and beliefs during the earthquakes, as well as concern and subsequent preparedness actions. Results indicate that earthquake characteristics (e.g., time, location) influence the types of preparedness actions. While there was a reduction in new actions from the first mainshock doublet earthquake (CS) to the second (LG), there were a large number of participants who reviewed or revisited their prior actions, related to their beliefs about impacts, in a form of problem-focused targeted action. Females took more actions than did males, and had a higher rate of immediate aftershock concern. For all participants, concern was greater after the CS earthquake than after the full earthquake sequence, supporting the findings of McClure et al. (2016) that there is a limited window after an event to maximise the opportunity for effective preparedness initiatives. Findings additionally suggest that such post-earthquake preparedness initiatives should consider the impacts that elicited the highest rate of concern in an event, and should tailor messages towards them. While this earthquake sequence resulted in low levels of impact and damage, it presents interesting findings regarding how disruption (in lieu of major damage) influences earthquake preparedness actions, which is particularly important to understand in highly active regions often exposed to smaller impact events.
Keywords
Seismic Hazard Adjustments; Risk Communication; Decision-making; Natural Hazards; Unrealistic Optimism; Different Regions; Volcanic Crisis; Perception; Disaster; Behavior; Earthquakes; Preparedness; Beliefs; Concern; Actions; Gender
Chen, Peng; Hu, Songhua; Shen, Qing; Lin, Hangfei; Xie, Chi. (2019). Estimating Traffic Volume for Local Streets with Imbalanced Data. Transportation Research Record, 2673(3), 598 – 610.
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Abstract
Annual average daily traffic (AADT) is an important measurement used in traffic engineering. Local streets are major components of a road network. However, automatic traffic recorders (ATRs) used to collect AADT are often limited to arterial roads, and such information is, therefore, often unavailable for local streets. Estimating AADT on local streets becomes a necessity as local street traffic continues to grow and the capacity of arterial roads becomes insufficient. A challenge is that an under-represented sample of local street AADT may result in biased estimation. A synthetic minority oversampling technique (SMOTE) is applied to oversample local streets to correct the imbalanced sampling among different road types. A generalized linear mixed model (GLMM) is employed to estimate AADT incorporating various independent variables, including factors of roadway design, socio-demographics, and land use. The model is examined with an AADT dataset from Seattle, WA. Results show that: (1) SMOTE helps to correct imbalanced sampling proportions and improve model performance significantly; (2) the number of lanes and the number of crosswalks are both positively associated with AADT; (3) road segments located in areas with a higher population density or more mixed land use have a higher AADT; (4) distance to the nearest arterial road is negatively correlated with AADT; and (5) AADT creates spatial spillover effects on neighboring road segments. The combination of SMOTE and GLMM improves the estimation accuracy on AADT, which contributes to better data for transportation planning and traffic monitoring, and to cost saving on data collection.
Keywords
Average; Prediction; Network; County
Moudon, Anne Vernez; Huang, Ruizhu; Stewart, Orion T.; Cohen-Cline, Hannah; Noonan, Carolyn; Hurvitz, Philip M.; Duncan, Glen E. (2019). Probabilistic Walking Models Using Built Environment and Sociodemographic Predictors. Population Health Metrics, 17(1).
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Abstract
BackgroundIndividual sociodemographic and home neighborhood built environment (BE) factors influence the probability of engaging in health-enhancing levels of walking or moderate-to-vigorous physical activity (MVPA). Methods are needed to parsimoniously model the associations.MethodsParticipants included 2392 adults drawn from a community-based twin registry living in the Seattle region. Objective BE measures from four domains (regional context, neighborhood composition, destinations, transportation) were taken for neighborhood sizes of 833 and 1666 road network meters from home. Hosmer and Lemeshow's methods served to fit logistic regression models of walking and MVPA outcomes using sociodemographic and BE predictors. Backward elimination identified variables included in final models, and comparison of receiver operating characteristic (ROC) curves determined model fit improvements.ResultsBuilt environment variables associated with physical activity were reduced from 86 to 5 or fewer. Sociodemographic and BE variables from all four BE domains were associated with activity outcomes but differed by activity type and neighborhood size. For the study population, ROC comparisons indicated that adding BE variables to a base model of sociodemographic factors did not improve the ability to predict walking or MVPA.ConclusionsUsing sociodemographic and built environment factors, the proposed approach can guide the estimation of activity prediction models for different activity types, neighborhood sizes, and discrete BE characteristics. Variables associated with walking and MVPA are population and neighborhood BE-specific.
Keywords
Walking; Confidence Intervals; Research Funding; Transportation; Logistic Regression Analysis; Built Environment; Socioeconomic Factors; Predictive Validity; Receiver Operating Characteristic Curves; Data Analysis Software; Descriptive Statistics; Psychology; Washington (state); Active Travel; Home Neighborhood Domains; Physical Activity; Physical-activity; United-states; Life Stage; Adults; Attributes; Health; Associations; Destination; Pitfalls
Buszkiewicz, James; Rose, Chelsea; Gupta, Shilpi; Ko, Linda K.; Mou, Jin; Moudon, Anne, V; Hurvitz, Philip M.; Cook, Andrea; Aggarwal, Anju; Drewnowski, Adam. (2020). A Cross-Sectional Analysis of Physical Activity and Weight Misreporting in Diverse Populations: The Seattle Obesity Study III. Obesity Science & Practice, 6(6), 615 – 627.
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Abstract
Background: In-person assessments of physical activity (PA) and body weight can be burdensome for participants and cost prohibitive for researchers. This study examined self-reported PA and weight accuracy and identified patterns of misreporting in a diverse sample. Methods: King, Pierce and Yakima county residents, aged 21-59 years (n= 728), self-reported their moderate-to-vigorous PA (MVPA) and weight, in kilograms. Self-reports were compared with minutes of bout-level MVPA, from 3 days of accelerometer data, and measured weights. Regression models examined characteristics associated with underreporting and overreporting of MVPA and weight, the potential bias introduced using each measure and the relation between perceived and measured PA and weight. Results: MVPA underreporting was higher among males and college educated participants; however, there was no differential MVPA overreporting. Weight underreporting was higher among males, those age 40-49 years and persons with obesity. Weight overreporting was higher among Hispanic participants and those reporting stress, unhappiness and fair or poor health. The estimated PA-obesity relation was similar using measured and self-reported PA but not self-reported weight. Perceived PA and weight predicted measured values. Conclusion: Self-reported PA and weight may be useful should objective measurement be infeasible; however, though population-specific adjustment for differential reporting should be considered.
Keywords
Self-reported Weight; Sedentary Behavior; Validation; Accuracy; Height; Adults; Health Disparity; Obesity; Physical Activity; Self-reported Outcomes
Rose, Chelsea M.; Gupta, Shilpi; Buszkiewicz, James; Ko, Linda K.; Mou, Jin; Cook, Andrea; Moudon, Anne Vernez; Aggarwal, Anju; Drewnowski, Adam. (2020). Small Increments in Diet Cost Can Improve Compliance with the Dietary Guidelines for Americans. Social Science & Medicine, 266.
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Abstract
Adherence to the Dietary Guidelines for Americans (DGA) may involve higher diet costs. This study assessed the relation between two measures of food spending and diet quality among adult participants (N = 768) in the Seattle Obesity Study (SOS III). All participants completed socio-demographic and food expenditure surveys and the Fred Hutch food frequency questionnaire. Dietary intakes were joined with local supermarket prices to estimate individual-level diet costs. Healthy Eating Index (HEI-2015) scores measured compliance with DGA. Multiple linear regressions using Generalized Estimating Equations with robust standard errors showed that lower food spending was associated with younger age, Hispanic ethnicity, and lower socioeconomic status. Even though higher HEI-2015 scores were associated with higher diet costs per 2000 kcal, much individual variability was observed. A positive curvilinear relationship was observed in adjusted models. At lower cost diets, a $100/ month increase in cost (from $150 to $250) was associated with a 20.6% increase in HEI-2015. For higher levels of diet cost (from $350 to $450) there were diminishing returns (2.8% increase in HEI2015). These findings indicate that increases in food spending at the lower end of the range have the most potential to improve diet quality.
Keywords
Healthy Eating Index; Income Inequality; Quality; Obesity; Adults; Expenditure; Disparities; Strategy; Outcomes; Scores; Food Expenditures; Diet Costs; Food Shopping; Diet Quality; Hei-2015; Ses
Jung, Meen Chel; Dyson, Karen; Alberti, Marina. (2021). Urban Landscape Heterogeneity Influences the Relationship Between Tree Canopy and Land Surface Temperature. Urban Forestry & Urban Greening, 57.
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Abstract
Urban trees play a key role in alleviating elevated summertime land surface temperatures in cities. However, urban landscape influences the capacity of urban trees to mitigate higher temperatures. We propose that both developed land characteristics and tree cover should be considered to accurately estimate the mitigation effects of canopy cover. We subclassified original land cover based on the canopy cover ratio to capture the within-land cover heterogeneity. We selected two coastal cities with different summertime climatic conditions: Seattle, Washington, USA, and Baltimore, Maryland, USA. We used Landsat-based grid cells (30 m x 30 m) as our spatial analytical unit, with corresponding land surface temperature, canopy area, canopy compactness, population size, and National Land Cover Database (NLCD)-based land cover group. We first used grouped boxplots, Kruskal-Wallis H tests, and post-hoc multiple comparison tests to detect the distribution of land surface temperatures by the land cover group. We then introduced statistical models to test the group effects on the relationship between land surface temperatures and canopy cover variables. We found: (1) land surface temperature increases with level of development, (2) land surface temperature decreases with canopy cover level, (3) the magnitude of the mitigation effects from canopy area differs based on development level and current canopy cover, (4) the differing efficacies of canopy area in decreasing land surface temperature follows a nonlinear threshold relationship, and (5) compactness of canopy cover was not significant in reducing the land surface temperature. These findings suggest the importance of considering heterogeneous canopy cover within developed land cover classes in urban heat island research. Tree planting strategies need to consider the nonlinear relationships between tree canopy cover and land surface temperature alongside environmental equity concerns.
Keywords
Extreme Heat Events; Climate-change; Cover Data; Island; Pattern; Cities; Vegetation; Mortality; Phoenix; Impact; Canopy Cover; Environmental Equity; Land Cover; Land Surface Temperature; Mitigation Effect; Area; Canopy; Cells; Climatic Factors; Databases; Heat Island; Landscapes; Multiple Comparison Test; Planting; Population Size; Research; Statistical Models; Summer; Surface Temperature; Testing; Trees; Urban Forestry; Maryland
Zou, Tianqi; Aemmer, Zack; Mackenzie, Don; Laberteaux, Ken. (2022). A Framework for Estimating Commute Accessibility and Adoption of Ridehailing Services Under Functional Improvements from Vehicle Automation. Journal Of Transport Geography, 102.
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Abstract
This paper develops an analytical framework to estimate commute accessibility and adoption of various ridehailing service concepts across the US by synthesizing individual commute trips using national Longitudinal Employer-Household Dynamics Origin-Destination Employment Statistics (LODES) data. Focusing on potential improvements in cost and time that could be enabled by vehicle automation, we use this modeling framework to simulate a lower-price autonomous service (e.g., 50% or 75% lower) with variable wait times and implementation levels (solo, pooled, and first/last mile transit connections services, alone or in combination) to determine how they might affect adoption rates. These results are compared across metrics of accessibility and trip density, as well as socioeconomic factors such as household income. We find - unsurprisingly - that major cities (e.g. New York, Los Angeles, and Chicago) support the highest adoption rates for ridehailing services. Decreases in price tend to increase market share and accessibility. The effect of a decrease in price is more drastic for lower income groups. The proposed method for synthesizing trips using the LODES contributes to current travel demand forecasting methods and the proposed analytic framework can be flexibly implemented with any other mode choice model, extended to non-commute trips, or applied to different levels of geographic aggregation.
Keywords
Choice Of Transportation; Demand Forecasting; Poor People; Adoption; Price Cutting; Metropolis; Employment Statistics; Los Angeles (calif.); New York (state); Chicago (ill.); Accessibility; Autonomous Vehicles; New Mobility Services; Ridehailing; Travel Demand; Preferences
Rowe, Daniel H.; Bae, Chang-hee Christine; Shen, Qing. (2010). Assessing Multifamily Residential Parking Demand and Transit Service. Ite Journal-institute Of Transportation Engineers, 80(12), 20 – 24.
Abstract
This study examined the relationship of multifamily residential parking demand and transit level of service in Two King County, WA, USA, Urban Centers: First Hill/Capitol Hill (FHCH) and redmond. In addition, current parking policies were assessed for their ability to meet the observed parking demand, and an alternative method to collect parking demand data was explored.
Hong, E-Sok Andy; Bae, Christine. (2012). Exposure of Bicyclists to Air Pollution in Seattle, Washington Hybrid Analysis Using Personal Monitoring and Land Use Regression. Transportation Research Record, 2270, 59 – 66.
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Abstract
The increase in urban bicycling facilities, raises public health concerns for potential exposure of bicyclists to traffic emissions. For an assessment of bicyclists' exposure to local traffic emissions, a hybrid approach is presented; it combines personal monitoring and a land use regression (LUR) model. Black carbon, a proxy variable for traffic-related air pollution, was measured with an Aethalometer along the predesignated bicycle route in Seattle, Washington, for 10 days, during a.m. and p.m. peak hours (20 sampling campaigns). Descriptive statistics and three-dimensional pollution maps were used to explore temporal variations and to identify pollution hot spots. The LUR model was developed to quantify the influence of spatial covariates on black carbon concentrations along the designated route. The results indicated that the black carbon concentrations fluctuated throughout the sampling periods and showed statistically significant diurnal and monthly patterns. The hot spot analysis suggests that proximity to traffic and other physical environments have important impacts on bicyclists' exposure and demand further investigation on the localized effects of traffic emissions on exposure levels. The LUR model explains 46% of the variations in black carbon concentrations, and significant relationships are found with types of bicycle route facility, wind speed, length of truck routes, and transportation and utility land uses. This research is the first application of the LUR approach in quantifying bicyclists' exposure to air pollution in transport microenvironments. This study provides a rationale for encouraging municipalities to develop effective strategies to mitigate the health risks of exposure to local traffic emissions in complex urban bicycling environments.
Keywords
Particulate Matter; Diesel Exhaust; Health; Model; Particles; Asthma; City
Perry, Cynthia K.; Herting, Jerald R.; Berke, Ethan M.; Nguyen, Huong Q.; Moudon, Anne Vernez; Beresford, Shirley A. A.; Ockene, Judith K.; Manson, Joann E.; Lacroix, Andrea Z. (2013). Does Neighborhood Walkability Moderate the Effects of Intrapersonal Characteristics on Amount of Walking in Post-Menopausal Women? Health & Place, 21, 39 – 45.
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Abstract
This study identifies factors associated with walking among postmenopausal women and tests whether neighborhood walkability moderates the influence of intrapersonal factors on walking. We used data from the Women's Health Initiative Seattle Center and linear regression models to estimate associations and interactions. Being white and healthy, having a high school education or beyond and greater non-walking exercise were significantly associated with more walking. Neighborhood walkability was not independently associated with greater walking, nor did it moderate influence of intrapersonal factors on walking. Specifying types of walking (e.g., for transportation) can elucidate the relationships among intrapersonal factors, the built environment, and walking. (C) 2013 Elsevier Ltd. All rights reserved.
Keywords
Self-talk; Postmenopause; Walking; Women's Health; Built Environment; Social Interaction; Regression Analysis; Postmenopausal Women; Walkability; Physical-activity; Older-adults; United-states; Us Adults; Exercise; Obesity; Transportation; Association; Attributes