Scully, Jason Y.; Moudon, Anne Vernez; Hurvitz, Philip M.; Aggarwal, Anju; Drewnowski, Adam. (2019). A Time-Based Objective Measure of Exposure to the Food Environment. International Journal Of Environmental Research And Public Health, 16(7).
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Abstract
Exposure to food environments has mainly been limited to counting food outlets near participants' homes. This study considers food environment exposures in time and space using global positioning systems (GPS) records and fast food restaurants (FFRs) as the environment of interest. Data came from 412 participants (median participant age of 45) in the Seattle Obesity Study II who completed a survey, wore GPS receivers, and filled out travel logs for seven days. FFR locations were obtained from Public Health Seattle King County and geocoded. Exposure was conceptualized as contact between stressors (FFRs) and receptors (participants' mobility records from GPS data) using four proximities: 21 m, 100 m, 500 m, and 1/2 mile. Measures included count of proximal FFRs, time duration in proximity to 1 FFR, and time duration in proximity to FFRs weighted by FFR counts. Self-reported exposures (FFR visits) were excluded from these measures. Logistic regressions tested associations between one or more reported FFR visits and the three exposure measures at the four proximities. Time spent in proximity to an FFR was associated with significantly higher odds of FFR visits at all proximities. Weighted duration also showed positive associations with FFR visits at 21-m and 100-m proximities. FFR counts were not associated with FFR visits. Duration of exposure helps measure the relationship between the food environment, mobility patterns, and health behaviors. The stronger associations between exposure and outcome found at closer proximities (<100 m) need further research.
Keywords
Global Positioning Systems; Physical-activity; Health Research; Land-use; Neighborhood; Gps; Obesity; Tracking; Validity; Mobility; Fast Food; Spatio-temporal Exposure; Mobility Patterns; Selective Mobility Bias
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
Besser, Lilah M.; Lovasi, Gina S.; Michael, Yvonne L.; Garg, Parveen; Hirsch, Jana A.; Siscovick, David; Hurvitz, Phil; Biggs, Mary L.; Galvin, James E.; Bartz, Traci M.; Longstreth, W. T. (2021). Associations between Neighborhood Greenspace and Brain Imaging Measures in Non-Demented Older Adults: The Cardiovascular Health Study. Social Psychiatry And Psychiatric Epidemiology, 56(9), 1575 – 1585.
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Abstract
Purpose Greater neighborhood greenspace has been associated with brain health, including better cognition and lower odds of Alzheimer's disease in older adults. We investigated associations between neighborhood greenspace and brain-based magnetic resonance imaging (MRI) measures and potential effect modification by sex or apolipoprotein E genotype (APOE), a risk factor for Alzheimer's disease. Methods We obtained a sample of non-demented participants 65 years or older (n = 1125) from the longitudinal, population-based Cardiovascular Health Study (CHS). Greenspace data were derived from the National Land Cover Dataset. Adjusted multivariable linear regression estimated associations between neighborhood greenspace five years prior to the MRI and left and right hippocampal volume and 10-point grades of ventricular size and burden of white matter hyperintensity. Interaction terms tested effect modification by APOE genotype and sex. CHS data (1989-1999) were obtained/analyzed in 2020. Results Participants were on average 79 years old [standard deviation (SD) = 4], 58% were female, and 11% were non-white race. Mean neighborhood greenspace was 38% (SD = 28%). Greater proportion of greenspace in the neighborhood five years before MRI was borderline associated with lower ventricle grade (estimate: - 0.30; 95% confidence interval: - 0.61, 0.00). We observed no associations between greenspace and the other MRI outcome measures and no evidence of effect modification by APOE genotype and sex. Conclusion This study suggests a possible association between greater greenspace and less ventricular enlargement, a measure reflecting global brain atrophy. If confirmed in other longitudinal cohort studies, interventions and policies to improve community greenspaces may help to maintain brain health in older age.
Keywords
Mild Cognitive Impairment; Ventricular Enlargement; Residential Greenness; Hippocampal Atrophy; Volume; Disease; Environment; Progression; Symptoms; Dementia; Neighborhood; Green Space; Mri; Brain Volume; Hippocampal; White Matter
Pataki, Diane E.; Alberti, Marina; Cadenasso, Mary L.; Felson, Alexander J.; McDonnell, Mark J.; Pincetl, Stephanie; Pouyat, Richard V.; Setala, Heikki; Whitlow, Thomas H. (2021). The Benefits and Limits of Urban Tree Planting for Environmental and Human Health. Frontiers In Ecology And Evolution, 9.
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Abstract
Many of the world's major cities have implemented tree planting programs based on assumed environmental and social benefits of urban forests. Recent studies have increasingly tested these assumptions and provide empirical evidence for the contributions of tree planting programs, as well as their feasibility and limits, for solving or mitigating urban environmental and social issues. We propose that current evidence supports local cooling, stormwater absorption, and health benefits of urban trees for local residents. However, the potential for urban trees to appreciably mitigate greenhouse gas emissions and air pollution over a wide array of sites and environmental conditions is limited. Consequently, urban trees appear to be more promising for climate and pollution adaptation strategies than mitigation strategies. In large part, this is due to space constraints limiting the extent of urban tree canopies relative to the current magnitude of emissions. The most promising environmental and health impacts of urban trees are those that can be realized with well-stewarded tree planting and localized design interventions at site to municipal scales. Tree planting at these scales has documented benefits on local climate and health, which can be maximized through targeted site design followed by monitoring, adaptive management, and studies of long-term eco-evolutionary dynamics.
Keywords
Outdoor Thermal Comfort; Improved Public-health; Carbon Storage; Ecosystem Services; Air-quality; Rainfall Interception; Vegetation; Cover; Design; Impact; Urban Ecology; Forestry; Sustainability; Policy; Climate Mitigation; Climate Adaptation; Ecosystem Disservices
Rhew, Isaac C.; Hurvitz, Philip M.; Lyles-riebli, Rose; Lee, Christine M. (2022). Geographic Ecological Momentary Assessment Methods to Examine Spatio-temporal Exposures Associated with Marijuana Use Among Young Adults: A Pilot Study. Spatial And Spatio-temporal Epidemiology, 41.
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Abstract
Background: This study demonstrates the use of geographic ecological momentary assessment (GEMA) methods among young adult marijuana users. Method: Participants were 14 current marijuana users ages 21-27 living in Greater Seattle, Washington. They completed brief surveys four times per day for 14 consecutive days, including measures of marijuana use and desire to use. They also carried a GPS data logger that tracked their spatial movements over time. Results: Participants completed 80.1% of possible EMA surveys. Using the GPS data, we calculated daily number of exposures to (i.e., within 100-m of) marijuana retail outlets (mean = 3.9 times per day; SD = 4.4) and time spent per day in high poverty census tracts (mean = 7.3 h per day in high poverty census tracts; SD = 5.1). Conclusions: GEMA may be a promising approach for studying the role spatio-temporal factors play in marijuana use and related factors.
Keywords
Geographic Ecological Momentary Assessment; Spatio-temporal Factors; Marijuana; Young Adults; Geographic Information System; Poverty; Substance Use; Alcohol; Tracking
El-Anwar, Omar; El-Rayes, Khaled; Elnashai, Amr. (2010). Minimization of Socioeconomic Disruption for Displaced Populations Following Disasters. Disasters, 34(3), 865 – 883.
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Abstract
In the aftermath of catastrophic natural disasters such as hurricanes, tsunamis and earthquakes, emergency management agencies come under intense pressure to provide temporary housing to address the large-scale displacement of the vulnerable population. Temporary housing is essential to enable displaced families to reestablish their normal daily activities until permanent housing solutions can be provided. Temporary housing decisions, however, have often been criticized for their failure to fulfil the socioeconomic needs of the displaced families within acceptable budgets. This paper presents the development of (1) socioeconomic disruption metrics that are capable of quantifying the socioeconomic impacts of temporary housing decisions on displaced populations; and (2) a robust multi-objective optimization model for temporary housing that is capable of simultaneously minimizing socioeconomic disruptions and public expenditures in an effective and efficient manner. A large-scale application example is optimized to illustrate the use of the model and demonstrate its capabilities ingenerating optimal plans for realistic temporary housing problems.
Keywords
Natural Disasters; Hurricanes; Disaster Relief; Temporary Housing; Tsunamis; Multi-objective Optimization; Post-disaster Recovery; Social Welfare; Socioeconomic Disruption
Chi, Nai-wen; Lin, Ken-yu; Hsieh, Shang-hsien. (2014). Using Ontology-based Text Classification To Assist Job Hazard Analysis. Advanced Engineering Informatics, 28(4), 381 – 394.
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Abstract
The dangers of the construction industry due to the risk of fatal hazards, such as falling from extreme heights, being struck by heavy equipment or materials, and the possibility of electrocution, are well known. The concept of Job Hazard Analysis is commonly used to mitigate and control these occupational hazards. This technique analyzes the major tasks in a construction activity, identifies all potential task-related hazards, and suggests safe approaches to reduce or avoid each of these hazards. In this paper, the authors explore the possibility of leveraging existing construction safety resources to assist JHA, aiming to reduce the level of human effort required. Specifically, the authors apply ontology-based text classification (TC) to match safe approaches identified in existing resources with unsafe scenarios. These safe approaches can serve as initial references and enrich the solution space when performing JHA. Various document modification strategies are applied to existing resources in order to achieve superior TC effectiveness. The end result of this research is a construction safety domain ontology and its underlying knowledge base. A user scenario is also discussed to demonstrate how the ontology supports JHA in practice. (C) 2014 Elsevier Ltd. All rights reserved.
Keywords
Construction Industry; Health Hazards; Human Factors; Occupational Safety; Ontologies (artificial Intelligence); Pattern Classification; Text Analysis; Ontology-based Text Classification; Job Hazard Analysis; Fatal Hazards; Task-related Hazard; Construction Safety Resource; Jha; Construction Safety Domain Ontology; Construction; Information; Construction Safety; Information Retrieval; Knowledge Management; Ontology; Text Classification
Chen, Peng. (2015). Built Environment Factors in Explaining the Automobile-Involved Bicycle Crash Frequencies: A Spatial Statistic Approach. Safety Science, 79, 336 – 343.
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Abstract
The objective of this study is to understand the relationship between built environment factors and bicycle crashes with motor vehicles involved in Seattle. The research method employed is a Poisson lognormal random effects model using hierarchal Bayesian estimation. The Traffic Analysis Zone (TAZ) is selected as the unit of analysis to quantify the built environment factors. The assembled dataset provides a rich source of variables, including road network, street elements, traffic controls, travel demand, land use, and socio-demographics. The research questions are twofold: how are the built environment factors associated with the bicycle crashes, and are the TAZ-based bicycle crashes spatially correlated? The findings of this study are: (1) safety improvements should focus on places with more mixed land use; (2) off-arterial bicycle routes are safer than on-arterial bicycle routes; (3) TAZ-based bicycle crashes are spatially correlated; (4) TAZs with more road signals and street parking signs are likely to have more bicycle crashes; and (5) TAZs with more automobile trips have more bicycle crashes. For policy implications, the results suggest that the local authorities should lower the driving speed limits, regulate cycling and driving behaviors in areas with mixed land use, and separate bike lanes from road traffic. (C) 2015 Elsevier Ltd. All rights reserved.
Keywords
Injury Crashes; Risk Analysis; Models; Infrastructure; Dependence; Counts; Level; Bicycle Crash Frequency; Hierarchal Bayesian Estimation; Poisson Lognormal Random Effects Model; Built Environment; Traffic Analysis Zone
Hashemloo, Alireza; Inanici, Mehlika; Meek, Christopher. (2016). Glareshade: A Visual Comfort-Based Approach to Occupant-Centric Shading Systems. Journal Of Building Performance Simulation, 9(4), 351 – 365.
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Abstract
This paper presents a novel method for designing of an occupant-centric shading algorithm that utilizes visual comfort metric as the form-generating criteria. Based on the premise of previous studies that demonstrate glare as the most important factor for operating shading devices, GlareShade is introduced as a simulation-based shading methodology driven by occupant's visual comfort. GlareShade not only responds to changing outdoor conditions such as the movement of the sun and the variation of cloud cover, but it also accounts for building specific local conditions. GlareShade draws its strength and flexibility from an occupant-centric approach that is based on the visual field of view of each occupant as the occupant is performing common visual tasks in a given environment, and the developed shading system is linked to a distributed sensing network of multiple occupants. ShadeFan is demonstrated as a proof-of-concept dynamic shading system utilizing the GlareShade method.
Keywords
Control Strategies; Design Tool; Daylight; Patterns; Offices; Blinds; Model; Occupant-centric Shading System; Glare; Daylighting; Visual Comfort
Doescher, Mark P.; Lee, Chanam; Saelens, Brian E.; Lee, Chunkuen; Berke, Ethan M.; Adachi-mejia, Anna M.; Patterson, Davis G.; Moudon, Anne Vernez. (2017). Utilitarian and Recreational Walking Among Spanish- and English-Speaking Latino Adults in Micropolitan US Towns. Journal Of Immigrant & Minority Health, 19(2), 237 – 245.
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Abstract
Walking among Latinos in US Micropolitan towns may vary by language spoken. In 2011-2012, we collected telephone survey and built environment (BE) data from adults in six towns located within micropolitan counties from two states with sizable Latino populations. We performed mixed-effects logistic regression modeling to examine relationships between ethnicity-language group [Spanish-speaking Latinos (SSLs); English-speaking Latinos (ESLs); and English-speaking non-Latinos (ENLs)] and utilitarian walking and recreational walking, accounting for socio-demographic, lifestyle and BE characteristics. Low-income SSLs reported higher amounts of utilitarian walking than ENLs (p = 0.007), but utilitarian walking in this group decreased as income increased. SSLs reported lower amounts of recreational walking than ENLs (p = 0.004). ESL-ENL differences were not significant. We identified no statistically significant interactions between ethnicity-language group and BE characteristics. Approaches to increase walking in micropolitan towns with sizable SSL populations may need to account for this group's differences in walking behaviors.
Keywords
Walking; Confidence Intervals; Ecology; Ethnic Groups; Hispanic Americans; Income; Language & Languages; Metropolitan Areas; Population; Public Health; Recreation; Rural Conditions; White People; Logistic Regression Analysis; Socioeconomic Factors; Social Context; Body Mass Index; Acquisition Of Data; Physical Activity; Data Analysis Software; Odds Ratio; United States; Environment Design; Ethnicity; Rural Populations; Physical-activity; Built Environment; United-states; Postmenopausal Women; Acculturation; Risk; Transportation; Mortality; Health; Associations; Studies; Demographic Aspects; Telephone Surveys; Minority & Ethnic Groups; Physical Fitness; Low Income Groups; Urban Environments; Demographics; Language; Accounting; Statistical Analysis; Urban Areas; Towns; Populations; Adults; Lifestyles; Latin American Cultural Groups; Sociodemographics; Landscape Architecture; Population Growth; Pediatrics; Leisure; Health Care; Noncitizens; Preventive Medicine; United States--us