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Research Product Types: Journal Article

peer-reviewed article in academic journal

Physical and Mental Health Impacts of Household Gardens in an Urban Slum in Lima, Peru

Korn, Abigail; Bolton, Susan M.; Spencer, Benjamin; Alarcon, Jorge A.; Andrews, Leann; Voss, Joachim G. (2018). Physical and Mental Health Impacts of Household Gardens in an Urban Slum in Lima, Peru. International Journal Of Environmental Research And Public Health, 15(8).

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Abstract

Rural poverty and lack of access to education has led to urban migration and fed the constant growth of urban slums in Lima, Peru. Inhabitants of these informal settlements lack land rights and access to a public water supply, resulting in poor sanitation, an inability to grow food, and suboptimal health outcomes. A repeated measures longitudinal pilot study utilizing participatory design methods was conducted in Lima between September 2013 and September 2014 to determine the feasibility of implementing household gardens and the subsequent impact of increased green space on well-being. Anthropometric data and a composite of five validated mental health surveys were collected at the baseline, 6-months, and 12-months after garden construction. Significant increases from the baseline in all domains of quality of life, including: physical (p < 0.01), psychological (p = 0.05), social (p = 0.02), environmental (p = 0.02), and overall social capital (p < 0.01) were identified 12 months after garden construction. Life-threatening experiences decreased significantly compared to the baseline (p = 0.02). There were no significant changes in parent or partner empathy (p = 0.21), BMI (p = 0.95), waist circumference (p = 0.18), or blood pressure (p = 0.66) at 6 or 12 months. Improved access to green space in the form of a household garden can significantly improve mental health in an urban slum setting.

Keywords

Of-life Assessment; Psychometric Properties; Threatening Experiences; Vegetable Consumption; Developing-countries; Community Garden; Climate-change; Green Space; Poverty; Participation; Mental Health; Peru; Quality Of Life; Urban Slum; Social Capital

Why Neighborhood Park Proximity Is Not Associated with Total Physical Activity

Stewart, Orion T.; Moudon, Anne Vernez; Littman, Alyson J.; Seto, Edmund; Saelens, Brian E. (2018). Why Neighborhood Park Proximity Is Not Associated with Total Physical Activity. Health & Place, 52, 163 – 169.

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Abstract

This study explored how parks within the home neighborhood contribute to total physical activity (PA) by isolating park-related PA. Seattle-area adults (n = 634) were observed using time-matched accelerometer, Global Positioning System (GPS), and travel diary instruments. Of the average 42.3 min of daily total PA, only 11% was related to parks. Both home neighborhood park count and area were associated with park-based PA, but not with PA that occurred elsewhere, which comprised 89% of total PA. This study demonstrates clear benefits of neighborhood parks for contributing to park-based PA while helping explain why proximity to parks is rarely associated with overall PA.

Keywords

Physical Activity; Parks; Urban Planning; Environmental Health; Global Positioning System; Built Environment; Green Space; Recreation; Social Determinants Of Health; Health Research; Accelerometer Data; Self-selection; United-states; Public Parks; Older Women; Walking; Adults; Facilities

Estimating Traffic Volume for Local Streets with Imbalanced Data

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

Spatial Relationships between Urban Structures and Air Pollution in Korea

Jung, Meen Chel; Park, Jaewoo; Kim, Sunghwan. (2019). Spatial Relationships between Urban Structures and Air Pollution in Korea. Sustainability, 11(2).

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Abstract

Urban structures facilitate human activities and interactions but are also a main source of air pollutants; hence, investigating the relationship between urban structures and air pollution is crucial. The lack of an acceptable general model poses significant challenges to investigations on the underlying mechanisms, and this gap fuels our motivation to analyze the relationships between urban structures and the emissions of four air pollutants, including nitrogen oxides, sulfur oxides, and two types of particulate matter, in Korea. We first conduct exploratory data analysis to detect the global and local spatial dependencies of air pollutants and apply Bayesian spatial regression models to examine the spatial relationship between each air pollutant and urban structure covariates. In particular, we use population, commercial area, industrial area, park area, road length, total land surface, and gross regional domestic product per person as spatial covariates of interest. Except for park area and road length, most covariates have significant positive relationships with air pollutants ranging from 0 to 1, which indicates that urbanization does not result in a one-to-one negative influence on air pollution. Findings suggest that the government should consider the degree of urban structures and air pollutants by region to achieve sustainable development.

Keywords

Land-use Regression; Particulate Matter Concentrations; Nitrogen-dioxide; Temporal Variations; Smart City; Quality; Health; Pm10; Fine; Pollutants; Urban Structure; Air Pollution; Moran's I; Bayesian Spatial Model; Motivation; Population; Urbanization; Nitrogen Oxides; Urban Structures; Emissions; Regression Analysis; Regression Models; Sulfur; Spatial Dependencies; Environmental Impact; Outdoor Air Quality; Metropolitan Areas; Economic Growth; Photochemicals; Industrial Areas; Urban Areas; Industrial Plant Emissions; Particulate Emissions; Particulate Matter; Data Analysis; Bayesian Analysis; Sustainable Development; Sulfur Oxides; Regions; Mathematical Models; Cities; China

A Roadmap for Urban Evolutionary Ecology

Rivkin, L. Ruth; Santangelo, James S.; Alberti, Marina; Aronson, Myla F. J.; De Keyzer, Charlotte W.; Diamond, Sarah E.; Fortin, Marie-josee; Frazee, Lauren J.; Gorton, Amanda J.; Hendry, Andrew P.; Liu, Yang; Losos, Jonathan B.; Macivor, J. Scott; Martin, Ryan A.; Mcdonnell, Mark J.; Miles, Lindsay S.; Munshi-south, Jason; Ness, Robert W.; Newman, Amy E. M.; Stothart, Mason R.; Theodorou, Panagiotis; Thompson, Ken A.; Verrelli, Brian C.; Whitehead, Andrew; Winchell, Kristin M.; Johnson, Marc T. J. (2019). A Roadmap for Urban Evolutionary Ecology. Evolutionary Applications, 12(3), 384 – 398.

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Abstract

Urban ecosystems are rapidly expanding throughout the world, but how urban growth affects the evolutionary ecology of species living in urban areas remains largely unknown. Urban ecology has advanced our understanding of how the development of cities and towns change environmental conditions and alter ecological processes and patterns. However, despite decades of research in urban ecology, the extent to which urbanization influences evolutionary and eco-evolutionary change has received little attention. The nascent field of urban evolutionary ecology seeks to understand how urbanization affects the evolution of populations, and how those evolutionary changes in turn influence the ecological dynamics of populations, communities, and ecosystems. Following a brief history of this emerging field, this Perspective article provides a research agenda and roadmap for future research aimed at advancing our understanding of the interplay between ecology and evolution of urban-dwelling organisms. We identify six key questions that, if addressed, would significantly increase our understanding of how urbanization influences evolutionary processes. These questions consider how urbanization affects nonadaptive evolution, natural selection, and convergent evolution, in addition to the role of urban environmental heterogeneity on species evolution, and the roles of phenotypic plasticity versus adaptation on species' abundance in cities. Our final question examines the impact of urbanization on evolutionary diversification. For each of these six questions, we suggest avenues for future research that will help advance the field of urban evolutionary ecology. Lastly, we highlight the importance of integrating urban evolutionary ecology into urban planning, conservation practice, pest management, and public engagement.

Keywords

Urban Ecology (biology); Climate Change; Urban Growth; Species Diversity; Urbanization; Citizen Science; Community Engagement; Eco-evolutionary Feedback; Gene Flow; Landscape Genetics; Urban Evolution; Urban Socioecology; Mouse Peromyscus-leucopus; Rapid Evolution; Population Genomics; Selection; Habitat; Differentiation; Framework; Environments; Biodiversity; Eco-evolutionary Feedback

Rebaselining Asset Data for Existing Facilities and Infrastructure

Abdirad, Hamid; Dossick, Carrie Sturts. (2020). Rebaselining Asset Data for Existing Facilities and Infrastructure. Journal Of Computing In Civil Engineering, 34(1).

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Abstract

This paper introduces rebaselining as a workflow for collecting reliable and verifiable asset management data for existing facilities and infrastructure. Reporting on two action research case studies with two public owners in the US, this research structures rebaselining in four phases: (1) preparing technology enablers, (2) collecting data from existing documents, (3) conducting field verification, and (4) updating asset management databases. These workflows address some of the common challenges in managing existing assets, including the fast-paced changes in asset data requirements, the inaccuracies in data and documentation of these existing assets portfolios, and the need to update data and documents over their life cycle. The findings set the groundwork for implementing workflow by mapping the rebaselining business processes in each phase, listing the technological requirements for these processes, and explaining the feasibility and examples of customizing building information modeling (BIM) platforms for rebaselining workflows. This customization of BIM platforms aims to offer simplified solutions that reduce the facility management staff's need for advanced BIM software knowledge.

Keywords

Asset Management; Building Management Systems; Business Data Processing; Database Management Systems; Facilities Management; Production Engineering Computing; Project Management; Risk Analysis; Software Tools; Reliable Asset Management Data; Verifiable Asset Management Data; Action Research Case Studies; Public Owners; Research Structures; Technology Enablers; Asset Management Databases; Facility Management Staff; Rebaselining Workflows; Technological Requirements; Rebaselining Business Processes; Existing Assets Portfolios; Documentation; Asset Data Requirements; Managing Existing Assets; Information; Bim; Existing Buildings; Infrastructure; Asset Data; Rebaselining

Dynamic Modal Accessibility Gap: Measurement and Application Using Travel Routes Data.

Guan, Jinping; Zhang, Kai; Shen, Qing; He, Ying. (2020). Dynamic Modal Accessibility Gap: Measurement and Application Using Travel Routes Data. Transportation Research: Part D, 81.

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Abstract

Accessibility is a key concept in transportation research and an important indicator of people's quality of life. With the development of big data analytics, dynamic accessibility that captures the temporal variations of accessibility becomes an important research focus. Few prior studies focus on comparative measures of dynamic accessibility to Points of Interest (POIs) by alternative travel modes. To fill this research gap, we propose a new index called dynamic modal accessibility gap (DMAG), which draws upon available data on residents' real travel routes using different travel modes, as well as the data on POIs. We study the DMAG in the real-travel covered area, assuming POIs are only useful if it is within someone's real-travel covered area. We then apply this DMAG methodology to Shanghai's central city and peripheral area. In both cases, we measure the accessibility for public and private travel modes. As an example, one-week taxi GPS and metro smart card data, and POIs data are used to generate the DMAG index for 30-minute and 60-minute trip durations for weekdays and holidays. Results show that DMAG can reflect the pattern of temporal variations. The proposed DMAG analytical framework, which can be applied at both the user and the system levels, can support urban and transportation planning, and promote social equity and livability.

Keywords

Air Travel; Choice Of Transportation; Urban Transportation; Transportation Planning; Urban Planning; Smart Cards; Inner Cities; Route Choice; Shanghai (china); Dynamic Accessibility; Modal Accessibility Gap (mag); Points Of Interest (pois); Public And Private Travel Modes; Temporal Variations; Scale Residential Areas; Transport; Time; Dimensions; Employment; Indicator; Choice; Boston; Car

Workforce Development: Understanding Task-Level Job Demands-Resources, Burnout, and Performance in Unskilled Construction Workers

Lee, Wonil; Migliaccio, Giovanni C.; Lin, Ken-Yu; Seto, Edmund Y. W. (2020). Workforce Development: Understanding Task-Level Job Demands-Resources, Burnout, and Performance in Unskilled Construction Workers. Safety Science, 123.

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Abstract

This study examines how task demands and personal resources affect unskilled construction worker productivity and safety performance. It extends the job demands-resources (JD-R) burnout model to show how job characteristics interact with burnout to influence performance. A modified model was designed to measure burnout, with exhaustion and disengagement among unskilled construction workers taken into consideration. An observational study was conducted in a laboratory environment to test the research hypotheses and assess the prediction accuracies of outcome constructs. Twenty-two subjects participated in multiple experiments designed to expose them to varying levels of task-demands and to record their personal resources as they performed common construction material-handling tasks. Specifically, both surveys and physiological measurements using wearable sensors were used to operationalize the model constructs. Moreover, partial least squares structural equation modeling was applied to analyze data collected at the task and individual levels. Exhaustion and disengagement exhibited different relationships with productivity and safety performance outcomes as measured by unit rate productivity and ergonomic behavior, respectively. Subjects with high burnout and high engagement showed high productivity but low safety performance. Thus, exhausted workers stand a greater chance of failing to comply with safety. As the sample and the task performed in the experiment do not cover the experience and trade of all construction workers, our findings are limited in their application to entry-level and unskilled workers, whose work is mainly manual material-handling tasks.

Keywords

Construction Workers; Structural Equation Modeling; Job Descriptions; Labor Productivity; Labor Supply; Burnout; Job Demand-resources Model; Partial Least Squares Structural Equation Modeling; Productivity; Safety; Wearable Sensors; Biomechanics; Construction Industry; Ergonomics; Occupational Health; Occupational Safety; Occupational Stress; Personnel; Statistical Analysis; Workforce Development; Understanding Task-level Job Demands-resources; Unskilled Construction Workers; Task Demands; Personal Resources; Unskilled Construction Worker Productivity; Job Demands-resources Burnout Model; Job Characteristics Interact; Exhaustion; Disengagement; Outcome Constructs; Varying Levels; Task-demands; Common Construction Material-handling Tasks; Physiological Measurements; Model Constructs; Individual Levels; Unit Rate Productivity; High Burnout; Low Safety Performance; Exhausted Workers; Entry-level; Unskilled Workers; Manual Material-handling Tasks; Heart-rate-variability; Labor Productivity Trends; Physiological Demands; Emotional Exhaustion; Safety Climate; Role Stress; Engagement; Fatigue; Workload; Task Analysis; Workforce; Level (quantity); Construction Materials; Personnel Management; Materials Handling; Multivariate Statistical Analysis

Impact of Energy Benchmarking and Disclosure Policy on Office Buildings

Shang, Luming; Lee, Hyun Woo; Dermisi, Sofia; Choe, Youngjun. (2020). Impact of Energy Benchmarking and Disclosure Policy on Office Buildings. Journal Of Cleaner Production, 250.

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Abstract

Building energy benchmarking policies require owners to publicly disclose their building's energy performance. In the US, the adoption of such policies is contributing to an increased awareness among tenants and buyers and is expected to motivate the owners of less efficient buildings to invest in energy efficiency improvements. However, there is a lack of studies specifically aimed at investigating the impact of such policies on office buildings among major cities through quantitative analyses. In response, this study evaluated the effectiveness of the benchmarking policy on energy efficiency improvements decision-making and on real estate performances, by applying two interrupted time series analyses to office buildings in downtown Chicago. The initial results indicate a lack of statistically strong evidence that the policy affected the annual vacancy trend of the energy efficient buildings (represented by ENERGY STAR labeled buildings). However, the use of interrupted time series in a more in-depth analysis shows that the policy is associated with a 6.7% decrease in vacancy among energy efficient buildings. The study proposed a method to quantitatively evaluate the impact of energy policies on the real estate performance of office buildings, and the result confirms the positive impact of energy-efficient retrofits on the real estate performance. The study findings support the reasoning behind the owners' decision in implementing energy efficiency improvements in their office buildings to remain competitive in the market. (C) 2019 Elsevier Ltd. All rights reserved.

Keywords

Office Buildings; Building Failures; Time Series Analysis; Real Property; Energy Consumption; Metropolis; Building Performance; Chicago (ill.); Building Energy Benchmarking And Disclosure Policies; Building Energy Efficiency; Time Series Modeling; Energy Star (program); Building Management Systems; Buildings (structures); Decision Making; Energy Conservation; Maintenance Engineering; Time Series; Disclosure Policy; Energy Benchmarking Policies; Building; Benchmarking Policy; Energy Efficiency Improvements Decision-making; Estate Performance; Energy Efficient Buildings; Energy Star; Energy Policies; Energy-efficient Retrofits; Interrupted Time-series; Regression; Behavior; Designs; Building Energy Benchmarking And; Disclosure Policies; Buildings; Cities; Energy Efficiency; Energy Policy; Markets; Quantitative Analysis; United States

Tsunami Preparedness and Resilience in the Cascadia Subduction Zone: A Multistage Model of Expected Evacuation Decisions and Mode Choice

Chen, Chen; Lindell, Michael K.; Wang, Haizhong. (2021). Tsunami Preparedness and Resilience in the Cascadia Subduction Zone: A Multistage Model of Expected Evacuation Decisions and Mode Choice. International Journal Of Disaster Risk Reduction, 59.

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Abstract

Physical scientists have estimated that the Cascadia Subduction Zone (CSZ) has as much as a 25% chance to produce a M9.0 earthquake and tsunami in the next 50 years, but few studies have used survey data to assess household risk perceptions, emergency preparedness, and evacuation intentions. To understand these phenomena, this study conducted a mail-based household questionnaire using the Protective Action Decision Model (PADM) as a guide to collect 483 responses from two coastal communities in the CSZ: Crescent City, CA and Coos Bay, OR. We applied multistage regression models to assess the effects of critical PADM variables. The results showed that three psychological variables (risk perception, perceived hazard knowledge, and evacuation mode efficacy) were associated with some demographic variables and experience variables. Evacuation intention and evacuation mode choice are associated with those psychological variables but not with demographic variables. Contrary to previous studies, location and experience had no direct impact on evacuation intention or mode choice. We also analyzed expected evacuation mode compliance and the potential of using micro-mobility during tsunami response. This study provides empirical evidence of tsunami preparedness and intentions to support interdisciplinary evacuation modeling, tsunami hazard education, community disaster preparedness, and resilience plans.

Keywords

False Discovery Rate; American-samoa; Earthquake; Washington; Behavior; Oregon; Wellington; Responses; Disaster; Tsunami Evacuation; Cascadia Subduction Zone; Risk Perception