Safety & Health & Wellbeing Archives - Page 20 of 29

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

Does the Built Environment Have Independent Obesogenic Power? Urban Form and Trajectories of Weight Gain

Buszkiewicz, James H.; Bobb, Jennifer F.; Hurvitz, Philip M.; Arterburn, David; Moudon, Anne Vernez; Cook, Andrea; Mooney, Stephen J.; Cruz, Maricela; Gupta, Shilpi; Lozano, Paula; Rosenberg, Dori E.; Theis, Mary Kay; Anau, Jane; Drewnowski, Adam. (2021). Does the Built Environment Have Independent Obesogenic Power? Urban Form and Trajectories of Weight Gain. International Journal Of Obesity, 45(9), 1914 – 1924.

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Abstract

Objective To determine whether selected features of the built environment can predict weight gain in a large longitudinal cohort of adults. Methods Weight trajectories over a 5-year period were obtained from electronic health records for 115,260 insured patients aged 18-64 years in the Kaiser Permanente Washington health care system. Home addresses were geocoded using ArcGIS. Built environment variables were population, residential unit, and road intersection densities captured using Euclidean-based SmartMaps at 800-m buffers. Counts of area supermarkets and fast food restaurants were obtained using network-based SmartMaps at 1600, and 5000-m buffers. Property values were a measure of socioeconomic status. Linear mixed effects models tested whether built environment variables at baseline were associated with long-term weight gain, adjusting for sex, age, race/ethnicity, Medicaid insurance, body weight, and residential property values. Results Built environment variables at baseline were associated with differences in baseline obesity prevalence and body mass index but had limited impact on weight trajectories. Mean weight gain for the full cohort was 0.06 kg at 1 year (95% CI: 0.03, 0.10); 0.64 kg at 3 years (95% CI: 0.59, 0.68), and 0.95 kg at 5 years (95% CI: 0.90, 1.00). In adjusted regression models, the top tertile of density metrics and frequency counts were associated with lower weight gain at 5-years follow-up compared to the bottom tertiles, though the mean differences in weight change for each follow-up year (1, 3, and 5) did not exceed 0.5 kg. Conclusions Built environment variables that were associated with higher obesity prevalence at baseline had limited independent obesogenic power with respect to weight gain over time. Residential unit density had the strongest negative association with weight gain. Future work on the influence of built environment variables on health should also examine social context, including residential segregation and residential mobility.

Keywords

Body-mass Index; Physical-activity; Food Environment; Structural Racism; Obesity; Neighborhoods; Associations; Health; Walkability; Exposure; Environment Models; Minority & Ethnic Groups; Urban Environments; Regression Analysis; Regression Models; Residential Density; Body Mass Index; Property Values; Body Weight Gain; Government Programs; Body Weight; Electronic Medical Records; Electronic Health Records; Fast Food; Buffers; Real Estate; Body Mass; Body Size; Socioeconomics; Health Care

The Economic Effects of Volcanic Alerts-A Case Study of High-Threat US Volcanoes

Peers, Justin B.; Gregg, Christopher E.; Lindell, Michael K.; Pelletier, Denis; Romerio, Franco; Joyner, Andrew T. (2021). The Economic Effects of Volcanic Alerts-A Case Study of High-Threat US Volcanoes. Risk Analysis, 41(10).

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Abstract

A common concern about volcanic unrest is that the communication of information about increasing volcanic alert levels (VALs) to the public could cause serious social and economic impacts even if an eruption does not occur. To test this statement, this study examined housing prices and business patterns from 1974-2016 in volcanic regions with very-high threat designations from the U.S. Geological Survey (USGS)-Long Valley Caldera (LVC), CA (caldera); Mount St. Helens (MSH), Washington (stratovolcano); and Kilauea, HawaiModified Letter Turned Commai (shield volcano). To compare economic trends in nonvolcanic regions that are economically dependent on tourism, Steamboat Springs, CO, served as a control as it is a ski-tourism community much like Mammoth Lakes in LVC. Autoregressive distributed lag (ARDL) models predicted that housing prices were negatively affected by VALs at LVC from 1982-1983 and 1991-1997. While VALs associated with unrest and eruptions included in this study both had short-term indirect effects on housing prices and business indicators (e.g., number of establishments, employment, and salary), these notifications were not strong predictors of long-term economic trends. Our findings suggest that these indirect effects result from both eruptions with higher level VALs and from unrest involving lower-level VAL notifications that communicate a change in volcanic activity but do not indicate that an eruption is imminent or underway. This provides evidence concerning a systemic issue in disaster resilience. While disaster relief is provided by the U.S. federal government for direct impacts associated with disaster events that result in presidential major disaster declarations, there is limited or no assistance for indirect effects to businesses and homeowners that may follow volcanic unrest with no resulting direct physical losses. The fact that periods of volcanic unrest preceding eruption are often protracted in comparison to precursory periods for other hazardous events (e.g., earthquakes, hurricanes, flooding) makes the issue of indirect effects particularly important in regions susceptible to volcanic activity.

Keywords

Direct Impacts; Econometric Analysis; Indirect Impacts; Risk Assessment; Volcano Alert Levels; Earthquakes; Hurricanes; Threats; Housing Costs; Business Indicators; Disasters; Disaster Relief; Declarations; Volcanoes; Resilience; Tourism; Economics; Flooding; Trends; Calderas; Geological Surveys; Housing Prices; Eruptions; Precursors; Indirect Effects; Business; Disaster Management; Economic Trends; Autoregressive Models; Floods; Employment Status; Prices; Federal Government; Housing; Eruption; Economic Impact; Seismic Activity; Volcanic Activity; Earthquake Prediction; Lakes; Communication; United States--us

The Effect of Luminance Distribution Patterns on Occupant Preference in a Daylit Office Environment

Van Den Wymelenberg, Kevin; Inanici, Mehlika; Johnson, Peter. (2010). The Effect of Luminance Distribution Patterns on Occupant Preference in a Daylit Office Environment. Leukos, 7(2), 103 – 122.

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Abstract

New research in daylighting metrics and developments in validated digital High Dynamic Range (HDR) photography techniques suggest that luminance based lighting controls have the potential to provide occupant satisfaction and energy saving improvements over traditional illuminance based lighting controls. This paper studies occupant preference and acceptance of patterns of luminance using HDR imaging and a repeated measures design methodology in a daylit office environment. Three existing luminance threshold analysis methods [method1: predetermined absolute luminance threshold (for example, 2000 cd/m(2)), method2: scene based mean luminance threshold, and method3: task based mean luminance threshold] were studied along with additional candidate metrics for their ability to explain luminance variability of 18 participant assessments of 'preferred' and 'just disturbing' scenes under daylighting conditions. Per-pixel luminance data from each scene were used to calculate Daylighting Glare Probability (DGP), Daylight Glare Index (DGI), and other candidate metrics using these three luminance threshold analysis methods. Of the established methods, the most consistent and effective metrics to explain variability in subjective responses were found to be; mean luminance of the task (using method3; (adj)r(2) = 0.59), mean luminance of the entire scene (using method2; (adj)r(2) = 0.44), and DGP using 2000 cd/m(2) as a glare source identifier (using method1; (adj)r(2) = 0.41). Of the 150 candidate metrics tested, the most effective was the 'mean luminance of the glare sources', where the glare sources were identified as 7* the mean luminance of the task position ((adj)r(2) = 0.64). Furthermore, DGP consistently performed better than DGI, confirming previous findings. 'Preferred' scenes never had more than similar to 10 percent of the field of view (FOV) that exceeded 2000 cd/m(2). Standard deviation of the entire scene luminance also proved to be a good predictor of satisfaction with general visual appearance.

Keywords

Glare; Daylight Metrics; Luminance Based Lighting Controls; Discomfort Glare; Occupant Preference; High Dynamic Range

Use of Health Impact Assessment for Transportation Planning Importance of Transportation Agency Involvement in the Process

Dannenberg, Andrew L.; Ricklin, Anna; Ross, Catherine L.; Schwartz, Michael; West, Julie; White, Steve; Wier, Megan L. (2014). Use of Health Impact Assessment for Transportation Planning Importance of Transportation Agency Involvement in the Process. Transportation Research Record, 2452, 71 – 80.

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Abstract

A health impact assessment (HIA) is a tool that can be used to inform transportation planners of the potential health consequences of their decisions. Although dozens of transportation-related HIAs have been completed in the United States, the characteristics of these HIAs and the interactions between public health professionals and transportation decision makers in these HIM have not been documented. A master list of completed HIAs was used to identify transportation-related HIAs. Seventy-three transportation-related HIAs conducted in 22 states between 2004 and 2013 were identified. The HIAs were conducted for projects such as road redevelopments, bridge replacements, and development of trails and public transit. Policies such as road pricing, transit service levels, speed limits, complete streets, and safe routes to schools were also assessed. Five HIAs in which substantial interactions between public health and transportation professionals took place during and after the HIA were examined in detail and included HIAs of the road pricing policy in San Francisco, California; a bridge replacement in Seattle, Washington; new transit lines in Baltimore, Maryland, and Portland, Oregon; and the BeltLine transit, trails, and parks project in Atlanta, Georgia. Recommendations from the HIAs led to changes in decisions in some cases and helped to raise awareness of health issues by transportation decision makers in all cases. HIAs are now used for many topics in transportation. The range of involvement of transportation decision makers in the conduct of HIAs varies. These case studies may serve as models for the conduct of future transportation-related HIAs, because the involvement of transportation agencies may increase the likelihood that an HIA will influence subsequent decisions.

Keywords

Policy; Inequalities; Benefits; Justice; Oregon

Associations between Fast-Food Consumption and Body Mass Index: A Cross-sectional Study in Adult Twins

Cohen-Cline, Hannah; Lau, Richard; Moudon, Anne V.; Turkheimer, Eric; Duncan, Glen E. (2015). Associations between Fast-Food Consumption and Body Mass Index: A Cross-sectional Study in Adult Twins. Twin Research & Human Genetics, 18(4), 375 – 382.

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Abstract

Obesity is a substantial health problem in the United States, and is associated with many chronic diseases. Previous studies have linked poor dietary habits to obesity. This cross-sectional study aimed to identify the association between body mass index (BMI) and fast-food consumption among 669 same-sex adult twin pairs residing in the Puget Sound region around Seattle, Washington. We calculated twin-pair correlations for BMI and fast-food consumption. We next regressed BMI on fast-food consumption using generalized estimating equations (GEE), and finally estimated the within-pair difference in BMI associated with a difference in fast-food consumption, which controls for all potential genetic and environment characteristics shared between twins within a pair. Twin-pair correlations for fast-food consumption were similar for identical (monozygotic; MZ) and fraternal (dizygotic; DZ) twins, but were substantially higher in MZ than DZ twins for BMI. In the unadjusted GEE model, greater fast-food consumption was associated with larger BMI. For twin pairs overall, and for MZ twins, there was no association between within-pair differences in fast-food consumption and BMI in any model. In contrast, there was a significant association between within-pair differences in fast-food consumption and BMI among DZ twins, suggesting that genetic factors play a role in the observed association. Thus, although variance in fast-food consumption itself is largely driven by environmental factors, the overall association between this specific eating behavior and BMI is largely due to genetic factors.

Keywords

Diseases In Twins; Obesity; Adults; Diseases; Food Habits; Food Consumption; Body Mass Index; Cross-sectional Method; United States; Fast-food Consumption; Generalized Estimating Equations; Twin Studies; Fto Gene Variants; Physical-activity; Dietary-intake; Weight Status; Environment Interaction; Human Obesity; Young-adults; Zygosity; Patterns; Exercise