102 resultados para 730210 Environmental health


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OBJECTIVE: This paper reviews the epidemiological evidence on the relationship between ambient temperature and morbidity. It assesses the methodological issues in previous studies, and proposes future research directions. DATA SOURCES AND DATA EXTRACTION: We searched the PubMed database for epidemiological studies on ambient temperature and morbidity of non-communicable diseases published in refereed English journals prior to June 2010. 40 relevant studies were identified. Of these, 24 examined the relationship between ambient temperature and morbidity, 15 investigated the short-term effects of heatwave on morbidity, and 1 assessed both temperature and heatwave effects. DATA SYNTHESIS: Descriptive and time-series studies were the two main research designs used to investigate the temperature–morbidity relationship. Measurements of temperature exposure and health outcomes used in these studies differed widely. The majority of studies reported a significant relationship between ambient temperature and total or cause-specific morbidities. However, there were some inconsistencies in the direction and magnitude of non-linear lag effects. The lag effect of hot temperature on morbidity was shorter (several days) compared to that of cold temperature (up to a few weeks). The temperature–morbidity relationship may be confounded and/or modified by socio-demographic factors and air pollution. CONCLUSIONS: There is a significant short-term effect of ambient temperature on total and cause-specific morbidities. However, further research is needed to determine an appropriate temperature measure, consider a diverse range of morbidities, and to use consistent methodology to make different studies more comparable.

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This workshop is a continuation and extension to the successful past workshops exploring the intersection of food, technology, place, and people, namely 2009 OZCHI workshop, Hungry 24/7? HCI Design for Sustainable Food Culture and Sustainable Interaction with Food, Technology, and the City [1] and 2010 CHI panel Making Food, Producing Sustainability [3]. The workshop aims to bring together experts from diverse backgrounds including academia, government, industry, and non-for-profit organisations. It specifically aims to create a space for discussion and design of innovative approaches to understanding and cultivating sustainable food practices via human-computer-interaction (HCI) as well as addressing the wider opportunities for the HCI community to engage with food as a key issue for sustainability The workshop addresses environmental, health, and social domains of sustainability in particular, by looking at various conceptual and design approaches in orchestrating sustainable interaction of people and food in and through dynamic techno-social networks.

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Vacuuming can be a source of indoor exposure to biological and non-biological aerosols, although there is little data that describes the magnitude of emissions from the vacuum cleaner itself. We therefore sought to quantify emission rates of particles and bacteria from a large group of vacuum cleaners and investigate their potential determinants, including temperature, dust bags, exhaust filters, price and age. Emissions of particles between 0.009 and 20 µm and bacteria were measured from 21 vacuums. Ultrafine (<100 nm) particle emission rates ranged from 4.0 × 10^6 to 1.1 × 10^11 particles min-1. Emission of 0.54 to 20 µm particles ranged from 4.0 × 10^4 to 1.2 × 10^9 particles min-1. PM2.5 emissions were between 2.4 × 10-1 and 5.4 × 10^3 µg min-1. Bacteria emissions ranged from 0 to 7.4 × 10^5 bacteria min-1 and were poorly correlated with dust bag bacteria content and particle emissions. Large variability in emission of all parameters was observed across the 21 vacuums we assessed, which was largely not attributable to the range of determinant factors we assessed. Vacuum cleaner emissions contribute to indoor exposure to non-biological and biological aerosols when vacuuming, and this may vary markedly depending on the vacuum used.

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1.1 Background What is renewable energy education and training? A cursory exploration of the International Solar Energy Society website (www.ises.org) reveals numerous references to education and training, referring collectively to concepts of the transfer and exchange of information and good practices, awareness raising and skills development. The purposes of such education and training relate to changing policy, stimulating industry, improving quality control and promoting the wider use of renewable energy sources. The primary objective appears to be to accelerate a transition to a better world for everyone (ISEE), as the greater use of renewable energy is seen as key to climate recovery; world poverty alleviation; advances in energy security, access and equality; improved human and environmental health; and a stabilized society. The Solar Cities project – Habitats of Tomorrow – aims at promoting the greater use of renewable energy within the context of long term planning for sustainable urban development. The focus is on cities or communities as complete systems; each one a unique laboratory allowing for the study of urban sustainability within the context of a low carbon lifestyle. The purpose of this paper is to report on an evaluation of a Solar Community in Australia, focusing specifically on the implications (i) for our understandings and practices in renewable energy education and training and (ii) for sustainability outcomes. 1.2 Methodology The physical context is a residential Ecovillage (a Solar Community) in sub-tropical Queensland, Australia (latitude 28o south). An extensive Architectural and Landscape Code (A&LC) ‘premised on the interconnectedness of all things’ and embracing ‘both local and global concerns’ governs the design and construction of housing in the estate: all houses are constructed off-ground (i.e. on stumps or stilts) and incorporate a hybrid approach to the building envelope (mixed use of thermal mass and light-weight materials). Passive solar design, gas boosted solar water heaters and a minimum 1kWp photovoltaic system (grid connected) are all mandatory, whilst high energy use appliances such as air conditioners and clothes driers are not permitted. Eight families participated in an extended case study that encompassed both quantitative and qualitative approaches to better understand sustainable housing (perceived as a single complex technology) through its phases of design, construction and occupation. 1.3 Results The results revealed that the level of sustainability (i.e. the performance outcomes in terms of a low-carbon lifestyle) was impacted on by numerous ‘players’ in the supply chain, such as architects, engineers and subcontractors, the housing market, the developer, product manufacturers / suppliers / installers and regulators. Three key factors were complicit in the level of success: (i) systems thinking; (ii) informed decision making; and (iii) environmental ethics and business practices. 1.4 Discussion The experiences of these families bring into question our understandings and practices with regard to education and training. Whilst increasing and transferring knowledge and skills is essential, the results appear to indicate that there is a strong need for expanding our education efforts to incorporate foundational skills in complex systems and decision making processes, combined with an understanding of how our individual and collective values and beliefs impact on these systems and processes.

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Objective: To assess the symptoms of heat illness experienced by surface mine workers. Methods: Ninety-one surface mine workers across three mine sites in northern Australia completed a heat stress questionnaire evaluating their symptoms for heat illness. A cohort of 56 underground mine workers also participated for comparative purposes. Participants were allocated into asymptomatic, minor or moderate heat illness categories depending on the number of symptoms they reported. Participants also reported the frequency of symptom experience, as well as their hydration status (average urine colour). Results: Heat illness symptoms were experienced by 87 and 79 % of surface and underground mine workers, respectively (p = 0.189), with 81–82 % of the symptoms reported being experienced by miners on more than one occasion. The majority (56 %) of surface workers were classified as experiencing minor heat illness symptoms, with a further 31 % classed as moderate; 13 % were asymptomatic. A similar distribution of heat illness classification was observed among underground miners (p = 0.420). Only 29 % of surface miners were considered well hydrated, with 61 % minimally dehydrated and 10 % significantly dehydrated, proportions that were similar among underground miners (p = 0.186). Heat illness category was significantly related to hydration status (p = 0.039) among surface mine workers, but only a trend was observed when data from surface and underground miners was pooled (p = 0.073). Compared to asymptomatic surface mine workers, the relative risk of experiencing minor and moderate symptoms of heat illness was 1.5 and 1.6, respectively, when minimally dehydrated. Conclusions: These findings show that surface mine workers routinely experience symptoms of heat illness and highlight that control measures are required to prevent symptoms progressing to medical cases of heat exhaustion or heat stroke.

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In recent years, cities have shown increasing signs of environmental problems due to the negative impacts of urban activities. The degradation and depletion of natural resources, climate change, and development pressure on green areas have become major concerns for cities. In response to these problems, urban planning policies have shifted to a sustainable focus and authorities have begun to develop new strategies for improving the quality of urban ecosystems. An extremely important function of an urban ecosystem is to provide healthy and sustainable environments for both natural systems and communities. Therefore, ecological planning is a functional requirement in the establishment of sustainable built environment. With ecological planning, human needs are supplied while natural resources are used in the most effective and sustainable manner and ecological balance is sustained. Protecting human and environmental health, having healthy ecosystems, reducing environmental pollution and providing green spaces are just a few of the many benefits of ecological planning. In this context, this chapter briefly presents a short overview of the importance of the implementation of ecological planning into sustainable urban development. Furthermore, it presents a conceptual framework for a new methodology for developing sustainable urban ecosystems through ecological planning approach.

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The aim of this paper is to examine the association between a range of objectively measured neighbourhood features and the likelihood of mid-aged adults walking for transport. Increased walking for transport would bring multiple benefits, including improved population and environmental health. As part of the baseline HABITAT study, 10,745 residents of Brisbane, Australia, aged 40–65 years, from 200 neighbourhoods were asked about the time they spent walking for transport. Walking data were collected by mail survey and the physical environmental features of neighbourhoods were compiled using a geographic information systems database. Walking for transport was categorised into four levels and the association between walking and each neighbourhood characteristic was examined using multilevel multinomial models. A number of threshold trends were evident; for example, off-road bikeways were consistently associated with walking between 60 and 150 min per week. Living within 500 m of public transit was also an important predictor but only for those who walked for less than 150 min per week. Interventions targeting these neighbourhood characteristics may lead to improved environmental quality, lower rates of overweight and obesity and associated chromic disease.

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Background: Bicycle commuting in an urban environment of high air pollution is known as a potential health risk, especially for susceptible individuals. While risk management strategies aimed to reduce motorised traffic emissions exposure have been suggested, limited studies have assessed the utility of such strategies in real-world circumstances. Objectives: The potential of reducing exposure to ultrafine particles (UFP; < 0.1 µm) during bicycle commuting by lowering interaction with motorised traffic was investigated with real-time air pollution and acute inflammatory measurements in healthy individuals using their typical, and an alternative to their typical, bicycle commute route. Methods: Thirty-five healthy adults (mean ± SD: age = 39 ± 11 yr; 29% female) each completed two return trips of their typical route (HIGH) and a pre-determined altered route of lower interaction with motorised traffic (LOW; determined by the proportion of on-road cycle paths). Particle number concentration (PNC) and diameter (PD) were monitored in real-time in-commute. Acute inflammatory indices of respiratory symptom incidence, lung function and spontaneous sputum (for inflammatory cell analyses) were collected immediately pre-commute, and one and three hours post-commute. Results: LOW resulted in a significant reduction in mean PNC (1.91 x e4 ± 0.93 x e4 ppcc vs. 2.95 x e4 ± 1.50 x e4 ppcc; p ≤ 0.001). Besides incidence of in-commute offensive odour detection (42 vs. 56 %; p = 0.019), incidence of dust and soot observation (33 vs. 47 %; p = 0.038) and nasopharyngeal irritation (31 vs. 41 %; p = 0.007), acute inflammatory indices were not significantly associated to in-commute PNC, nor were these indices reduced with LOW compared to HIGH. Conclusions: Exposure to PNC, and the incidence of offensive odour and nasopharyngeal irritation, can be significantly reduced when utilising a strategy of lowering interaction with motorised traffic whilst bicycle commuting, which may bring important benefits for both healthy and susceptible individuals.

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Heatwaves are associated with significant health risks particularly among vulnerable groups. To minimize these risks, heat warning systems have been implemented. The question therefore is how effective these systems are in saving lives and reducing heat-related harm. We systematically searched and reviewed 15 studies which examined this. Six studies asserted that fewer people died of excessive heat after the implementation of heat warning systems. Demand for ambulance decreased following the implementation of these systems. One study also estimated the costs of running heat warning systems at US$210,000 compared to the US$468 million benefits of saving 117 lives. The remaining eight studies investigated people?s response to heat warning systems and taking appropriate actions against heat harms. Perceived threat of heat dangers emerged as the main factor related to heeding the warnings and taking proper actions. However, barriers, such as costs of running air-conditioners, were of significant concern, particularly to the poor. The weight of the evidence suggests that heat warning systems are effective in reducing mortality and, potentially, morbidity. However, their effectiveness may be mediated by cognitive, emotive and socio-demographic characteristics. More research is urgently required into the cost-effectiveness of heat warning systems? measures and improving the utilization of the services.

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The health impacts of exposure to ambient temperature have been drawing increasing attention from the environmental health research community, government, society, industries, and the public. Case-crossover and time series models are most commonly used to examine the effects of ambient temperature on mortality. However, some key methodological issues remain to be addressed. For example, few studies have used spatiotemporal models to assess the effects of spatial temperatures on mortality. Few studies have used a case-crossover design to examine the delayed (distributed lag) and non-linear relationship between temperature and mortality. Also, little evidence is available on the effects of temperature changes on mortality, and on differences in heat-related mortality over time. This thesis aimed to address the following research questions: 1. How to combine case-crossover design and distributed lag non-linear models? 2. Is there any significant difference in effect estimates between time series and spatiotemporal models? 3. How to assess the effects of temperature changes between neighbouring days on mortality? 4. Is there any change in temperature effects on mortality over time? To combine the case-crossover design and distributed lag non-linear model, datasets including deaths, and weather conditions (minimum temperature, mean temperature, maximum temperature, and relative humidity), and air pollution were acquired from Tianjin China, for the years 2005 to 2007. I demonstrated how to combine the case-crossover design with a distributed lag non-linear model. This allows the case-crossover design to estimate the non-linear and delayed effects of temperature whilst controlling for seasonality. There was consistent U-shaped relationship between temperature and mortality. Cold effects were delayed by 3 days, and persisted for 10 days. Hot effects were acute and lasted for three days, and were followed by mortality displacement for non-accidental, cardiopulmonary, and cardiovascular deaths. Mean temperature was a better predictor of mortality (based on model fit) than maximum or minimum temperature. It is still unclear whether spatiotemporal models using spatial temperature exposure produce better estimates of mortality risk compared with time series models that use a single site’s temperature or averaged temperature from a network of sites. Daily mortality data were obtained from 163 locations across Brisbane city, Australia from 2000 to 2004. Ordinary kriging was used to interpolate spatial temperatures across the city based on 19 monitoring sites. A spatiotemporal model was used to examine the impact of spatial temperature on mortality. A time series model was used to assess the effects of single site’s temperature, and averaged temperature from 3 monitoring sites on mortality. Squared Pearson scaled residuals were used to check the model fit. The results of this study show that even though spatiotemporal models gave a better model fit than time series models, spatiotemporal and time series models gave similar effect estimates. Time series analyses using temperature recorded from a single monitoring site or average temperature of multiple sites were equally good at estimating the association between temperature and mortality as compared with a spatiotemporal model. A time series Poisson regression model was used to estimate the association between temperature change and mortality in summer in Brisbane, Australia during 1996–2004 and Los Angeles, United States during 1987–2000. Temperature change was calculated by the current day's mean temperature minus the previous day's mean. In Brisbane, a drop of more than 3 �C in temperature between days was associated with relative risks (RRs) of 1.16 (95% confidence interval (CI): 1.02, 1.31) for non-external mortality (NEM), 1.19 (95% CI: 1.00, 1.41) for NEM in females, and 1.44 (95% CI: 1.10, 1.89) for NEM aged 65.74 years. An increase of more than 3 �C was associated with RRs of 1.35 (95% CI: 1.03, 1.77) for cardiovascular mortality and 1.67 (95% CI: 1.15, 2.43) for people aged < 65 years. In Los Angeles, only a drop of more than 3 �C was significantly associated with RRs of 1.13 (95% CI: 1.05, 1.22) for total NEM, 1.25 (95% CI: 1.13, 1.39) for cardiovascular mortality, and 1.25 (95% CI: 1.14, 1.39) for people aged . 75 years. In both cities, there were joint effects of temperature change and mean temperature on NEM. A change in temperature of more than 3 �C, whether positive or negative, has an adverse impact on mortality even after controlling for mean temperature. I examined the variation in the effects of high temperatures on elderly mortality (age . 75 years) by year, city and region for 83 large US cities between 1987 and 2000. High temperature days were defined as two or more consecutive days with temperatures above the 90th percentile for each city during each warm season (May 1 to September 30). The mortality risk for high temperatures was decomposed into: a "main effect" due to high temperatures using a distributed lag non-linear function, and an "added effect" due to consecutive high temperature days. I pooled yearly effects across regions and overall effects at both regional and national levels. The effects of high temperature (both main and added effects) on elderly mortality varied greatly by year, city and region. The years with higher heat-related mortality were often followed by those with relatively lower mortality. Understanding this variability in the effects of high temperatures is important for the development of heat-warning systems. In conclusion, this thesis makes contribution in several aspects. Case-crossover design was combined with distribute lag non-linear model to assess the effects of temperature on mortality in Tianjin. This makes the case-crossover design flexibly estimate the non-linear and delayed effects of temperature. Both extreme cold and high temperatures increased the risk of mortality in Tianjin. Time series model using single site’s temperature or averaged temperature from some sites can be used to examine the effects of temperature on mortality. Temperature change (no matter significant temperature drop or great temperature increase) increases the risk of mortality. The high temperature effect on mortality is highly variable from year to year.

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Background The association between temperature and mortality has been examined mainly in North America and Europe. However, less evidence is available in developing countries, especially in Thailand. In this study, we examined the relationship between temperature and mortality in Chiang Mai city, Thailand, during 1999–2008. Method A time series model was used to examine the effects of temperature on cause-specific mortality (non-external, cardiopulmonary, cardiovascular, and respiratory) and age-specific non-external mortality (<=64, 65–74, 75–84, and > =85 years), while controlling for relative humidity, air pollution, day of the week, season and long-term trend. We used a distributed lag non-linear model to examine the delayed effects of temperature on mortality up to 21 days. Results We found non-linear effects of temperature on all mortality types and age groups. Both hot and cold temperatures resulted in immediate increase in all mortality types and age groups. Generally, the hot effects on all mortality types and age groups were short-term, while the cold effects lasted longer. The relative risk of non-external mortality associated with cold temperature (19.35°C, 1st percentile of temperature) relative to 24.7°C (25th percentile of temperature) was 1.29 (95% confidence interval (CI): 1.16, 1.44) for lags 0–21. The relative risk of non-external mortality associated with high temperature (31.7°C, 99th percentile of temperature) relative to 28°C (75th percentile of temperature) was 1.11 (95% CI: 1.00, 1.24) for lags 0–21. Conclusion This study indicates that exposure to both hot and cold temperatures were related to increased mortality. Both cold and hot effects occurred immediately but cold effects lasted longer than hot effects. This study provides useful data for policy makers to better prepare local responses to manage the impact of hot and cold temperatures on population health.

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Custom designed for display on the Cube Installation situated in the new Science and Engineering Centre (SEC) at QUT, the ECOS project is a playful interface that uses real-time weather data to simulate how a five-star energy building operates in climates all over the world. In collaboration with the SEC building managers, the ECOS Project incorporates energy consumption and generation data of the building into an interactive simulation, which is both engaging to users and highly informative, and which invites play and reflection on the roles of green buildings. ECOS focuses on the principle that humans can have both a positive and negative impact on ecosystems with both local and global consequence. The ECOS project draws on the practice of Eco-Visualisation, a term used to encapsulate the important merging of environmental data visualization with the philosophy of sustainability. Holmes (2007) uses the term Eco-Visualisation (EV) to refer to data visualisations that ‘display the real time consumption statistics of key environmental resources for the goal of promoting ecological literacy’. EVs are commonly artifacts of interaction design, information design, interface design and industrial design, but are informed by various intellectual disciplines that have shared interests in sustainability. As a result of surveying a number of projects, Pierce, Odom and Blevis (2008) outline strategies for designing and evaluating effective EVs, including ‘connecting behavior to material impacts of consumption, encouraging playful engagement and exploration with energy, raising public awareness and facilitating discussion, and stimulating critical reflection.’ Consequently, Froehlich (2010) and his colleagues also use the term ‘Eco-feedback technology’ to describe the same field. ‘Green IT’ is another variation which Tomlinson (2010) describes as a ‘field at the juncture of two trends… the growing concern over environmental issues’ and ‘the use of digital tools and techniques for manipulating information.’ The ECOS Project team is guided by these principles, but more importantly, propose an example for how these principles may be achieved. The ECOS Project presents a simplified interface to the very complex domain of thermodynamic and climate modeling. From a mathematical perspective, the simulation can be divided into two models, which interact and compete for balance – the comfort of ECOS’ virtual denizens and the ecological and environmental health of the virtual world. The comfort model is based on the study of psychometrics, and specifically those relating to human comfort. This provides baseline micro-climatic values for what constitutes a comfortable working environment within the QUT SEC buildings. The difference between the ambient outside temperature (as determined by polling the Google Weather API for live weather data) and the internal thermostat of the building (as set by the user) allows us to estimate the energy required to either heat or cool the building. Once the energy requirements can be ascertained, this is then balanced with the ability of the building to produce enough power from green energy sources (solar, wind and gas) to cover its energy requirements. Calculating the relative amount of energy produced by wind and solar can be done by, in the case of solar for example, considering the size of panel and the amount of solar radiation it is receiving at any given time, which in turn can be estimated based on the temperature and conditions returned by the live weather API. Some of these variables can be altered by the user, allowing them to attempt to optimize the health of the building. The variables that can be changed are the budget allocated to green energy sources such as the Solar Panels, Wind Generator and the Air conditioning to control the internal building temperature. These variables influence the energy input and output variables, modeled on the real energy usage statistics drawn from the SEC data provided by the building managers.