Safety & Health & Wellbeing Archives - Page 23 of 29

Minimization of Socioeconomic Disruption for Displaced Populations Following Disasters.

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

Using Ontology-based Text Classification To Assist Job Hazard Analysis

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

Built Environment Factors in Explaining the Automobile-Involved Bicycle Crash Frequencies: A Spatial Statistic Approach

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

Glareshade: A Visual Comfort-Based Approach to Occupant-Centric Shading Systems

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

Utilitarian and Recreational Walking Among Spanish- and English-Speaking Latino Adults in Micropolitan US Towns

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

Medical Facilities in the Neighborhood and Incidence of Sudden Cardiac Arrest

Goh, Charlene E.; Mooney, Stephen J.; Siscovick, David S.; Lemaitre, Rozenn N.; Hurvitz, Philip; Sotoodehnia, Nona; Kaufman, Tanya K.; Zulaika, Garazi; Lovasi, Gina S. (2018). Medical Facilities in the Neighborhood and Incidence of Sudden Cardiac Arrest. Resuscitation, 130, 118 – 123.

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Abstract

Background: Medical establishments in the neighborhood, such as pharmacies and primary care clinics, may play a role in improving access to preventive care and treatment and could explain previously reported neighborhood variations in sudden cardiac arrest (SCA) incidence and survival. Methods: The Cardiac Arrest Blood Study Repository is a population-based repository of data from adult cardiac arrest patients and population-based controls residing in King County, Washington. We examined the association between the availability of medical facilities near home with SCA risk, using adult (age 18-80) Seattle residents experiencing cardiac arrest (n = 446) and matched controls (n = 208) without a history of heart disease. We also analyzed the association of major medical centers near the event location with emergency medical service (EMS) response time and survival among adult cases (age 18+) presenting with ventricular fibrillation from throughout King County (n = 1537). The number of medical facilities per census tract was determined by geocoding business locations from the National Establishment Time-Series longitudinal database 1990-2010. Results: More pharmacies in the home census tract was unexpectedly associated with higher odds of SCA (OR: 1.28, 95% CI: 1.03, 1.59), and similar associations were observed for other medical facility types. The presence of a major medical center in the event census tract was associated with a faster EMS response time (-53 s, 95% CI: -84, -22), but not with short-term survival. Conclusions: We did not observe a protective association between medical facilities in the home census tract and SCA risk, orbetween major medical centers in the event census tract and survival.

Keywords

Cardiac Arrest; Medical Care; Emergency Medical Services; Ventricular Fibrillation; Heart Diseases; Patients; Medical Facilities; Neighborhood; Observational Study; Sudden Cardiac Arrest; Survival; Ambulance Response-times; Socioeconomic-status; Association; Care; Resuscitation; Disparities; Population; Provision; Disease

Identifying High-risk Built Environments for Severe Bicycling Injuries

Chen, Peng; Shen, Qing. (2019). Identifying High-risk Built Environments for Severe Bicycling Injuries. Journal of Safety Research, 68, 1 – 7.

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Abstract

Introduction: This study is aimed at filling part of the knowledge gap on bicycling safety in the built environment by addressing two questions. First, are built environment features and bicyclist injury severity correlated; and if so, what built environment factors most significantly relate to severe bicyclist injuries? Second, are the identified associations varied substantially among cities with different levels of bicycling and different built environments? Methods: The generalized ordered logit model is employed to examine the relationship between built environment features and bicyclist injury severity. Results: Bicyclist injury severity is coded into four types, including no injury (NI), possible injury (PI), evident injury (El), and severe injury and fatality (SIF). The findings include: (a) higher percentages of residential land and green space, and office or mixed use land are correlated with lower probabilities of El and SIF; (b) land use mixture is negatively correlated with El and SIF; (c) steep slopes are positively associated with bicyclist injury severity; (d) in areas with more transit routes, bicyclist injury is less likely to be severe; (e) a higher speed limit is more likely to correlate with SIF; and (f) wearing a helmet is negatively associated with SIF, but positively related to PI and El. Practical applications: To improve bicycle safety, urban planners and policymakers should encourage mixed land use, promote dense street networks, place new bike lanes in residential neighborhoods and green spaces, and office districts, while avoiding steep slopes. To promote bicycling, a process of evaluating the risk of bicyclists involving severe injuries in the local environment should be implemented before encouraging bicycle activities. (C) 2018 National Safety Council and Elsevier Ltd. All rights reserved.

Keywords

Motor Vehicle; Land-use; Crashes; Severities; Facilities; Frameworks; Frequency; Cyclists; Bike; Bicyclist Injury Severity; Built Environments; Generalized Ordered Logit Model; Us Cities; Bicycles; Urban Environments; Injuries; Neighborhoods; Land Use; Urban Areas; Paths; Protective Equipment; Bicycling; Fatalities; Correlation; Residential Areas; Traffic Accidents & Safety; Safety; Logit Models; Ecological Risk Assessment; Slopes; Health Risks; Urban Transportation; Studies; Environments

Busy Businesses and Busy Contexts: The Distribution and Sources of Crime at Commercial Properties.

Tillyer, Marie Skubak; Walter, Rebecca J. (2019). Busy Businesses and Busy Contexts: The Distribution and Sources of Crime at Commercial Properties. Journal Of Research In Crime & Delinquency, 56(6), 816 – 850.

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Abstract

Objective: Examine the distribution and sources of crime across freestanding businesses in San Antonio. We test hypotheses about the main and interactive effects of neighborhood and business characteristics on crime at the business, with a focus on busy contexts and busy businesses. Method: Police crime incident data are spatially joined to study area business parcels. Additional data sources include Infogroup USA Business Data, the American Community Survey, and an Environmental Protection Agency traffic activity indicator. Multilevel negative binomial regression models are estimated to observe the main and interactive effects of census block group and business variables on crime at the parcel. Results: Businesses located in block groups with more commercial property and high levels of vehicular traffic experience more crime. In addition, crime is higher at busy businesses, as indicated by employee size, sales volume, and square footage. Busy contexts and busy businesses do not appear to interact to increase crime at the parcel beyond their main effects. Conclusions: Crime is clustered at relatively few businesses, and this variation cannot be explained by business type alone. Both neighborhood and business characteristics are associated with crime at freestanding businesses, with busy businesses and those within busier block groups experiencing more crime.

Keywords

Business Enterprises; Commercial Real Estate; Crime; Businesses; Busy Places; Crime And Place; Crime Concentration; Infogroup Usa (company); United States. Environmental Protection Agency; Social-disorganization; Routine Activities; Street Segments; Micro Places; High-schools; Hot-spots; Criminology; Neighborhoods; Facilities; Multilevel; Companies; Law Enforcement; Business; Protection; Traffic; Police; Census; Trade; Sales; Environmental Protection; Commercial Property

Evidence-Driven Sound Detection for Prenotification and Identification Of Construction Safety Hazards and Accidents

Lee, Yong-Cheol; Shariatfar, Moeid; Rashidi, Abbas; Lee, Hyun Woo. (2020). Evidence-Driven Sound Detection for Prenotification and Identification Of Construction Safety Hazards and Accidents. Automation In Construction, 113.

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Abstract

As the construction industry experiences a high rate of casualties and significant economic loss associated with accidents, safety has always been a primary concern. In response, several studies have attempted to develop new approaches and state-of-the-art technology for conducting autonomous safety surveillance of construction work zones such as vision-based monitoring. The current and proposed methods including human inspection, however, are limited to consistent and real-time monitoring and rapid event recognition of construction safety issues. In addition, the health and safety risks inherent in construction projects make it challenging for construction workers to be aware of possible safety risks and hazards according to daily planned work activities. To address the urgent demand of the industry to improve worker safety, this study involves the development of an audio-based event detection system to provide daily safety issues to laborers and through the rapid identification of construction accidents. As an evidence-driven approach, the proposed framework incorporates the occupational injury and illness manual data, consisting of historical construction accident data classified by types of sources and events, into an audio-based safety event detection framework. This evidence-driven framework integrated with a daily project schedule can automatically provide construction workers with prenotifications regarding safety hazards at a pertinent work zone as well as consistently contribute to enhanced construction safety monitoring by audio-based event detection. By using a machine learning algorithm, the framework can clearly categorize the narrowed-down sound training data according to a daily project schedule and dynamically restrict sound classification types in advance. The proposed framework is expected to contribute to an emerging knowledge base for integrating an automated safety surveillance system into occupational accident data, significantly improving the accuracy of audio-based event detection.

Keywords

Construction Projects; Occupational Hazards; Construction Workers; Construction; System Safety; Video Surveillance; Work-related Injuries; Audio-based Accident Recognition; Autonomous Safety Surveillance; Construction Safety; Evidence-driven Sound Event Detection; Accident Prevention; Accidents; Audio Acoustics; Classification (of Information); Construction Industry; Health Hazards; Health Risks; Knowledge Based Systems; Learning Algorithms; Losses; Machine Learning; Monitoring; Motion Compensation; Occupational Diseases; Steel Beams And Girders; Audio-based; Construction Accidents; Construction Work Zones; Historical Construction; Sound Event Detection; State-of-the-art Technology; Vision Based Monitoring; Algorithm; System

Use of Health Impact Assessments in the Housing Sector to Promote Health in the United States, 2002-2016

Bever, Emily; Arnold, Kimberly T.; Lindberg, Ruth; Dannenberg, Andrew L.; Morley, Rebecca; Breysse, Jill; Pollack Porter, Keshia M. (2021). Use of Health Impact Assessments in the Housing Sector to Promote Health in the United States, 2002-2016. Journal Of Housing And The Built Environment, 36(3), 1277 – 1297.

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Abstract

Housing affects health, yet health is seldom considered in housing decisions. Health impact assessment (HIA) is a tool that can improve housing-related policies, plans, programs, and projects by bringing together scientific data, health expertise, and stakeholder engagement to identify the potential health effects of proposed decisions. We systematically identified and reviewed HIAs of housing decisions in the United States, yielding 54 HIAs between 2002 and 2016. Two examined federal proposals; the others explored decisions in 20 states. A variety of organizations led the HIAs, including non-profits, public health departments, and academic institutions. The primary decision-makers each HIA sought to inform were housing, planning, and/or elected officials. Eighteen HIAs focused on housing policies, codes, design elements, and utilities in residential structures. The remaining 36 HIAs included housing as one element of broader community development and transportation planning decisions. HIA recommendations changed decisions in some cases, and the assessment process helped strengthen connections between public health and housing decision-makers. To illustrate key characteristics of housing HIAs, we purposefully selected three HIAs and described the decisions they informed in detail: off-campus student housing in Flagstaff, Arizona; a rental housing inspections program in Portland, Oregon; and revitalization plans for a major thoroughfare in a suburb of St. Louis, Missouri. With a few exceptions, federal, state, and local agencies in the U.S. are not required to consider the health impacts of housing decisions, such as where housing is sited, how it is designed and constructed, and policies for ensuring that it is affordable and safe. HIA has emerged as a tool for advocates, health and housing practitioners, and policymakers to fill this gap. However, few studies have examined whether HIAs do in fact change housing decisions, shift the way that decision-makers think, or ultimately shift determinants of health (e.g., housing affordability and quality). This review demonstrates that HIAs can facilitate the consideration of health during housing decision-making. Housing HIAs can also help decision-makers address commonly overlooked effects, such as changes to social cohesion, and improve civic participation by engaging communities in the decisionmaking process.

Keywords

0; Community Development; Decision-making; Healthy Housing; Health Impact Assessment; Housing Policy; Stakeholder Engagement; Health Promotion; Public Health; Exceptions; Impact Analysis; Nonprofit Organizations; Affordability; Suburban Areas; Profits; Housing; Policy Making; Transportation Planning; Decision Making; Rental Housing; Public Officials; Policies; Regeneration; Utilities; Social Cohesion; Inspections; Community Involvement; Decision Makers; Community Participation; United States--us