949 resultados para Household Travel Survey


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Few, if any studies, have attempted to identify the specific environmental factors associated with the incidence of diarrheal disease and to rank these by their contribution to the total incidence of diarrheal illness. Potentially those factors with the greatest contribution are the variables on which intervention could be expected to have the greatest impact on the incidence of diarrhea.^ In 317 rural Egyptian households participating in a longitudinal study of diarrheal disease, selected environmental characteristics were observed and recorded on a questionnaire. Characteristics of the environment were classified into seven categories including water usage, proximity of animals to the house, waste management, food preparation area, toilet area, the household structure and hygiene. The variables from each of the seven major groupings most associated with the incidence of diarrhea in infants were selected through the application of stepwise multiple regression. Each area was then ranked by the portion of the incidence of diarrhea in infants that each composite group of area-specific variables alone would explain. The groups of household structure and water usage variables were found to be more associated with the incidence of diarrhea in infants than variables describing the toilet area, proximity to animals or others. It was also found that 24.7% of the total variance in incidence of diarrheal illness was explained by environmental variables. ^

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One of the broad objectives of the Nigerian health service, vigorously being pursued at all levels of government, is to make comprehensive health care available and accessible to the population at the lowest possible cost, within available resources. Some state governments in the federation have already introduced free medical service as a practical way to remove financial barriers to access and in turn to encourage greater utilization of publicly funded care facilities.^ To aid health planners and decision makers in identifying a shorter corridor through which urban dwellers can gain access to comprehensive health care, a health interview survey of the metropolitan Lagos was undertaken. The primary purpose was to ascertain the magnitude of access problems which urban households face in seeking care from existing public facilities at the time of need. Six categories of illness chosen from the 1975 edition of the International Classification of Disease were used as indicators of health need.^ Choice of treatment facilities in response to illness episode was examined in relation to distance, travel time, time of use and transportation experiences. These were graphically described. The overall picture indicated that distance and travel time coexist with transportation problems in preventing a significant segment of those in need of health care from benefitting in the free medical service offered in public health facilities. Within this milieu, traditional medicine and its practitioners became the most preferred alternative. Recommendations were offered for action with regard to decentralization of general practitioner (GP) consultations in general hospitals and integration of traditional medicine and its practitioners into public health service. ^

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Few studies have been conducted on the epidemiology of enteric infectious diseases of public health importance in communities along the United States-Mexico border, and these studies typically focus on bacterial and viral diseases. The epidemiology of intestinal helminth infections along the border has not recently been explored, and there are no published reports for El Paso and Ciudad Juarez, both of which are high traffic urban areas along the Texas-Mexico border. The purpose of this research project was to conduct a cross-sectional epidemiologic survey for enteric helminths of medical importance along the Texas-Mexico border region of El Paso and Ciudad Juarez and to evaluate risk factors for exposure to these parasites. In addition, an emphasis was placed on the zoonotic tapeworm, Taenia solium. This tapeworm is especially important in this region because of the increasing incidence of neurocysticercosis, a severe disease spread by carriers of intestinal T. solium. Fecal samples were collected from individuals of all ages in a population-based cross-sectional household survey and evaluated for the presence of helminth parasites using fecal flotations. In addition, a Taenia coproantigen enzyme linked immunosorbent assay (ELISA) was performed on each stool sample to identify tapeworm carriers. A standardized questionnaire was administered to identify risk factors and routes of exposure for enteric helminth infections with additional questions to assess risk factors specific for taeniasis. The actual prevalence of taeniasis along the Texas-Mexico border was unknown, and this is the first population-based study performed in this region. Flotations were performed on 395 samples and four (1%) were positive for helminths including Ascaris, hookworms and Taenia species. Immunodiagnostic testing demonstrated a prevalence of 2.9% (11/378) for taeniasis. Based on the case definition, a 3% (12/395) prevalence of taeniasis was detected in this area. In addition, statistical analyses indicate that residents of El Paso are 8.5 times more likely to be a tapeworm carrier compared to residents of Juarez (PR=8.5, 95% CI=2.35, 30.81). This finding has important implications in terms of planning effective health education campaigns to decrease the prevalence of enteric helminths in populations along the Texas-Mexico border. ^

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During the summer of 2003, a ground-penetrating radar survey around the North Greenland Icecore Project (NorthGRIP) deep ice-core drilling site (75°06' N, 42°20' W; 2957 m a.s.l.) was carried out using a shielded 250 MHz radar system. The drill site is located on an ice divide, roughly 300 km north-northwest of the summit of the Greenland ice sheet. More than 430 km of profiles were measured, covering a 10 km by 10 km area, with a grid centered on the drilling location, and eight profiles extending beyond this grid. Seven internal horizons within the upper 120 m of the ice sheet were continuously tracked, containing the last 400 years of accumulation history. Based on the age-depth and density-depth distribution of the deep core, the internal layers have been dated and the regional and temporal distribution of accumulation rate in the vicinity of NorthGRIP has been derived. The distribution of accumulation shows a relatively smoothly increasing trend from east to west from 145 kg/m**2/a to 200 kg/m**2/a over a distance of 50 km across the ice divide. The general trend is overlain by small-scale variations on the order of 2.5 kg/m**2/a/km, i.e. around 1.5% of the accumulation mean. The temporal variations of the seven periods defined by the seven tracked isochrones are on the order of +-4% of the mean of the last 400 years, i.e. at NorthGRIP ±7 kg/m**2/a. If the regional accumulation pattern has been stable for the last several thousand years during the Holocene, and ice flow has been comparable to today, advective effects along the particle trajectory upstream of NorthGRIP do not have a significant effect on the interpretation of climatically induced changes in accumulation rates derived from the deep ice core over the last 10 kyr.

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Major findings of the Survey of Living Conditions in the Arctic (SLiCA) are: (1) A combination of traditional activities and cash employment is the prevailing lifestyle of Arctic indigenous peoples; (2) family ties, social support of each other, and traditional activities have a lot to do with why indigenous people choose to remain in Arctic communities; (3) well-being is closely related to job opportunities, locally available fish and game, and a sense of local control. Well-being and depression (and related problems like suicide) are flip sides of the same coin. Improving well-being may reduce social problems; and, (4) health conditions vary widely in the Arctic: three-in-four Greenlandic Inuit self-rate their health as at least very good compared with one-in-two Canadian and Alaska Inuit and one-in-five Chukotka indigenous people. Findings are based on 7,200 interviews in a probability sample of Inupiat settlement regions of Alaska, the four Inuit settlement regions of Canada, all of Greenland, and the Anadyrskij, Anadyr, Shmidtovs, Beringovskij, Chukotskij, Iujl'tinskij, Bilibinskij, Chaunskij, Providenskij, Uel'Kal' districts of Chukotka. Indigenous people and researchers from Greenland, Russia, Canada, the United States, Denmark, Norway, Sweden, and Finland collaborated on all phases of the study.

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La relación entre la estructura urbana y la movilidad ha sido estudiada desde hace más de 70 años. El entorno urbano incluye múltiples dimensiones como por ejemplo: la estructura urbana, los usos de suelo, la distribución de instalaciones diversas (comercios, escuelas y zonas de restauración, parking, etc.). Al realizar una revisión de la literatura existente en este contexto, se encuentran distintos análisis, metodologías, escalas geográficas y dimensiones, tanto de la movilidad como de la estructura urbana. En este sentido, se trata de una relación muy estudiada pero muy compleja, sobre la que no existe hasta el momento un consenso sobre qué dimensión del entorno urbano influye sobre qué dimensión de la movilidad, y cuál es la manera apropiada de representar esta relación. Con el propósito de contestar estas preguntas investigación, la presente tesis tiene los siguientes objetivos generales: (1) Contribuir al mejor entendimiento de la compleja relación estructura urbana y movilidad. y (2) Entender el rol de los atributos latentes en la relación entorno urbano y movilidad. El objetivo específico de la tesis es analizar la influencia del entorno urbano sobre dos dimensiones de la movilidad: número de viajes y tipo de tour. Vista la complejidad de la relación entorno urbano y movilidad, se pretende contribuir al mejor entendimiento de la relación a través de la utilización de 3 escalas geográficas de las variables y del análisis de la influencia de efectos inobservados en la movilidad. Para el análisis se utiliza una base de datos conformada por tres tipos de datos: (1) Una encuesta de movilidad realizada durante los años 2006 y 2007. Se obtuvo un total de 943 encuestas, en 3 barrios de Madrid: Chamberí, Pozuelo y Algete. (2) Información municipal del Instituto Nacional de Estadística: dicha información se encuentra enlazada con los orígenes y destinos de los viajes recogidos en la encuesta. Y (3) Información georeferenciada en Arc-GIS de los hogares participantes en la encuesta: la base de datos contiene información respecto a la estructura de las calles, localización de escuelas, parking, centros médicos y lugares de restauración. Se analizó la correlación entre e intra-grupos y se modelizaron 4 casos de atributos bajo la estructura ordinal logit. Posteriormente se evalúa la auto-selección a través de la estimación conjunta de las elecciones de tipo de barrio y número de viajes. La elección del tipo de barrio consta de 3 alternativas: CBD, Urban y Suburban, según la zona de residencia recogida en las encuestas. Mientras que la elección del número de viajes consta de 4 categorías ordinales: 0 viajes, 1-2 viajes, 3-4 viajes y 5 o más viajes. A partir de la mejor especificación del modelo ordinal logit. Se desarrolló un modelo joint mixed-ordinal conjunto. Los resultados indican que las variables exógenas requieren un análisis exhaustivo de correlaciones con el fin de evitar resultados sesgados. ha determinado que es importante medir los atributos del BE donde se realiza el viaje, pero también la información municipal es muy explicativa de la movilidad individual. Por tanto, la percepción de las zonas de destino a nivel municipal es considerada importante. En el contexto de la Auto-selección (self-selection) es importante modelizar conjuntamente las decisiones. La Auto-selección existe, puesto que los parámetros estimados conjuntamente son significativos. Sin embargo, sólo ciertos atributos del entorno urbano son igualmente importantes sobre la elección de la zona de residencia y frecuencia de viajes. Para analizar la Propensión al Viaje, se desarrolló un modelo híbrido, formado por: una variable latente, un indicador y un modelo de elección discreta. La variable latente se denomina “Propensión al Viaje”, cuyo indicador en ecuación de medida es el número de viajes; la elección discreta es el tipo de tour. El modelo de elección consiste en 5 alternativas, según la jerarquía de actividades establecida en la tesis: HOME, no realiza viajes durante el día de estudio, HWH tour cuya actividad principal es el trabajo o estudios, y no se realizan paradas intermedias; HWHs tour si el individuo reaiza paradas intermedias; HOH tour cuya actividad principal es distinta a trabajo y estudios, y no se realizan paradas intermedias; HOHs donde se realizan paradas intermedias. Para llegar a la mejor especificación del modelo, se realizó un trabajo importante considerando diferentes estructuras de modelos y tres tipos de estimaciones. De tal manera, se obtuvieron parámetros consistentes y eficientes. Los resultados muestran que la modelización de los tours, representa una ventaja sobre la modelización de los viajes, puesto que supera las limitaciones de espacio y tiempo, enlazando los viajes realizados por la misma persona en el día de estudio. La propensión al viaje (PT) existe y es específica para cada tipo de tour. Los parámetros estimados en el modelo híbrido resultaron significativos y distintos para cada alternativa de tipo de tour. Por último, en la tesis se verifica que los modelos híbridos representan una mejora sobre los modelos tradicionales de elección discreta, dando como resultado parámetros consistentes y más robustos. En cuanto a políticas de transporte, se ha demostrado que los atributos del entorno urbano son más importantes que los LOS (Level of Service) en la generación de tours multi-etapas. la presente tesis representa el primer análisis empírico de la relación entre los tipos de tours y la propensión al viaje. El concepto Propensity to Travel ha sido desarrollado exclusivamente para la tesis. Igualmente, el desarrollo de un modelo conjunto RC-Number of trips basado en tres escalas de medida representa innovación en cuanto a la comparación de las escalas geográficas, que no había sido hecha en la modelización de la self-selection. The relationship between built environment (BE) and travel behaviour (TB) has been studied in a number of cases, using several methods - aggregate and disaggregate approaches - and different focuses – trip frequency, automobile use, and vehicle miles travelled and so on. Definitely, travel is generated by the need to undertake activities and obtain services, and there is a general consensus that urban components affect TB. However researches are still needed to better understand which components of the travel behaviour are affected most and by which of the urban components. In order to fill the gap in the research, the present dissertation faced two main objectives: (1) To contribute to the better understanding of the relationship between travel demand and urban environment. And (2) To develop an econometric model for estimating travel demand with urban environment attributes. With this purpose, the present thesis faced an exhaustive research and computation of land-use variables in order to find the best representation of BE for modelling trip frequency. In particular two empirical analyses are carried out: 1. Estimation of three dimensions of travel demand using dimensions of urban environment. We compare different travel dimensions and geographical scales, and we measure self-selection contribution following the joint models. 2. Develop a hybrid model, integrated latent variable and discrete choice model. The implementation of hybrid models is new in the analysis of land-use and travel behaviour. BE and TB explicitly interact and allow richness information about a specific individual decision process For all empirical analysis is used a data-base from a survey conducted in 2006 and 2007 in Madrid. Spatial attributes describing neighbourhood environment are derived from different data sources: National Institute of Statistics-INE (Administrative: municipality and district) and GIS (circular units). INE provides raw data for such spatial units as: municipality and district. The construction of census units is trivial as the census bureau provides tables that readily define districts and municipalities. The construction of circular units requires us to determine the radius and associate the spatial information to our households. The first empirical part analyzes trip frequency by applying an ordered logit model. In this part is studied the effect of socio-economic, transport and land use characteristics on two travel dimensions: trip frequency and type of tour. In particular the land use is defined in terms of type of neighbourhoods and types of dwellers. Three neighbourhood representations are explored, and described three for constructing neighbourhood attributes. In particular administrative units are examined to represent neighbourhood and circular – unit representation. Ordered logit models are applied, while ordinal logit models are well-known, an intensive work for constructing a spatial attributes was carried out. On the other hand, the second empirical analysis consists of the development of an innovative econometric model that considers a latent variable called “propensity to travel”, and choice model is the choice of type of tour. The first two specifications of ordinal models help to estimate this latent variable. The latent variable is unobserved but the manifestation is called “indicators”, then the probability of choosing an alternative of tour is conditional to the probability of latent variable and type of tour. Since latent variable is unknown we fit the integral over its distribution. Four “sets of best variables” are specified, following the specification obtained from the correlation analysis. The results evidence that the relative importance of SE variables versus BE variables depends on how BE variables are measured. We found that each of these three spatial scales has its intangible qualities and drawbacks. Spatial scales play an important role on predicting travel demand due to the variability in measures at trip origin/destinations within the same administrative unit (municipality, district and so on). Larger units will produce less variation in data; but it does not affect certain variables, such as public transport supply, that are more significant at municipality level. By contrast, land-use measures are more efficient at district level. Self-selection in this context, is weak. Thus, the influence of BE attributes is true. The results of the hybrid model show that unobserved factors affect the choice of tour complexity. The latent variable used in this model is propensity to travel that is explained by socioeconomic aspects and neighbourhood attributes. The results show that neighbourhood attributes have indeed a significant impact on the choice of the type of tours either directly and through the propensity to travel. The propensity to travel has a different impact depending on the structure of each tour and increases the probability of choosing more complex tours, such as tours with many intermediate stops. The integration of choice and latent variable model shows that omitting important perception and attitudes leads to inconsistent estimates. The results also indicate that goodness of fit improves by adding the latent variable in both sequential and simultaneous estimation. There are significant differences in the sensitivity to the latent variable across alternatives. In general, as expected, the hybrid models show a major improvement into the goodness of fit of the model, compared to a classical discrete choice model that does not incorporate latent effects. The integrated model leads to a more detailed analysis of the behavioural process. Summarizing, the effect that built environment characteristics on trip frequency studied is deeply analyzed. In particular we tried to better understand how land use characteristics can be defined and measured and which of these measures do have really an impact on trip frequency. We also tried to test the superiority of HCM on this field. We can concluded that HCM shows a major improvement into the goodness of fit of the model, compared to classical discrete choice model that does not incorporate latent effects. And consequently, the application of HCM shows the importance of LV on the decision of tour complexity. People are more elastic to built environment attributes than level of services. Thus, policy implications must take place to develop more mixed areas, work-places in combination with commercial retails.

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During the last years cities around the world have invested important quantities of money in measures for reducing congestion and car-trips. Investments which are nothing but potential solutions for the well-known urban sprawl phenomenon, also called the “development trap” that leads to further congestion and a higher proportion of our time spent in slow moving cars. Over the path of this searching for solutions, the complex relationship between urban environment and travel behaviour has been studied in a number of cases. The main question on discussion is, how to encourage multi-stop tours? Thus, the objective of this paper is to verify whether unobserved factors influence tour complexity. For this purpose, we use a data-base from a survey conducted in 2006-2007 in Madrid, a suitable case study for analyzing urban sprawl due to new urban developments and substantial changes in mobility patterns in the last years. A total of 943 individuals were interviewed from 3 selected neighbourhoods (CBD, urban and suburban). We study the effect of unobserved factors on trip frequency. This paper present the estimation of an hybrid model where the latent variable is called propensity to travel and the discrete choice model is composed by 5 alternatives of tour type. The results show that characteristics of the neighbourhoods in Madrid are important to explain trip frequency. The influence of land use variables on trip generation is clear and in particular the presence of commercial retails. Through estimation of elasticities and forecasting we determine to what extent land-use policy measures modify travel demand. Comparing aggregate elasticities with percentage variations, it can be seen that percentage variations could lead to inconsistent results. The result shows that hybrid models better explain travel behavior than traditional discrete choice models.

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Applications involving travel behavior from the perspective of land use are dating from the 1990s. Usually, four important components are distinguished: density, diversity and design (3D?s of Cervero and Kockelman) and accessibility (introduced by Geurs and van Wee). But there is not a general agreement on how to measure each of those 4 components. Density is used to be measured as population and employment densities, but others authors separate population density between residential and building densities. A lot of measures have been developed to estimate diversity: among others, a dissimilarity index to indicate the degree to which different land uses lie within one another?s surrounding, an entropy index to quantify the degree of balance across various land use types or proximities to commercial-retail uses. Design has been characterized by site design, and dwelling and street characteristics. Lastly, accessibility has become a frequently used concept, but its meaning on travel behavior field always refers to the ability ?to reach activities or locations by means of a travel mode?, measured as accessibility to jobs, to leisure activities, and others. Furthermore, the previous evidence is mainly based on US data or on north European countries. Therefore, this paper adds some new evidence from a Spanish perspective to the research debate. Through a Madrid smartphone-based survey, factor analysis is used to linearly combine variables into the 3D?s and accessibility dimensions of the built environment. At a first step for future investigations, land use variables will be treated to define accurately the previous 4 components.

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This paper explores the potential role of individual trip characteristics and social capital network variables in the choice of transport mode. A sample of around 100 individuals living or working in one suburb of Madrid (i.e. Las Rosas district of Madrid) participated in a smartphone short panel survey, entering travel data for an entire working week. A Mixed Logit model was estimated with this data to analyze shifts to metro as a consequence of the opening of two new stations in the area. Apart from classical explanatory variables, such as travel time and cost, gender, license and car ownership, the model incorporated two “social capital network” variables: participation in voluntary activities and receiving help for various tasks (i.e. child care, housekeeping, etc.). Both variables improved the capacity of the model to explain transport mode shifts. Further, our results confirm that the shift towards metro was higher in the case of people “helped” and lower for those participating in some voluntary activities.

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To combat unsustainable transportation systems characterized by reliance on petroleum, polluting emissions, traffic congestion and suburban sprawl, planners encourage mixed use, densely populated areas that provide individuals with opportunities to live, work, eat and shop without necessarily having to drive private automobiles to accommodate their needs. Despite these attempts, the frequency and duration of automobile trips has consistently increased in the United States throughout past decades. While many studies have focused on how residential proximity to transit influences travel behavior, the effect of workplace location has largely been ignored. This paper asks, does working near a TOD influence the travel behaviors of workers differently than workers living near a TOD? We examine the non-work travel behaviors of workers based upon their commuting mode and proximity to TODs. The data came from a 2009 travel behavior survey by the Denver Regional Council of Governments, which contains 8,000 households, 16,000 individuals, and nearly 80,000 trips. We measure sustainable travel behaviors as reduced mileage, reduced number of trips, and increased use of non-automobile transportation. The results of this study indicate that closer proximity of both households and workplaces to TODs decrease levels of car commuting and that non-car commuting leads to more sustainable personal travel behaviors characterized by more trips made with alternative modes.

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Decades of mixed messages from three federal agencies left many Americans unaware of the hazards associated with the indiscriminate disposal of unwanted or expired medicines. For this Capstone project, a systematic review of state and federal regulations was undertaken to determine how these laws obstruct household pharmaceutical waste collection. In addition, a survey of 654 Atlanta residents was conducted to evaluate unwanted medicine disposal habits, awareness of pharmaceutical compounds being detected in drinking water, surface, and ground waters, and willingness to participate in a household pharmaceutical waste collection program. Survey responses were tabulated to provide overall results and by age group, gender, and race. A household pharmaceutical waste collection plan was developed for the city and included as an appendix.

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Among the different production factors, land is the one that most often limits farm development and one of the most studied. The connection between policy and other context variables and land markets is at the core of the policy debate, including the present reform of the Common Agricultural Policy. The proposal of the latter has been published in October 2011 and in Italy it will include the switch of the payment regime from an historical to a regional basis. The authors’ objective is to simulate the impact of the proposed policy reform on the land market, particularly on land values and propensity to transaction. They combine insights and data from a farm household investment model revised and extended in order to simulate the demand curve for land in different policy scenarios and a survey of farmers stated intention carried out in the province of Bologna (Italy) in 2012. Based on these results, the authors calibrate a mathematical programming model of land market exchanges for the province of Bologna and use this model form simulation. The results of the model largely corroborate the results from the survey and both hint at a relevant reaction of the land demand and supply to the shift from the historical to the regionalised payments. As effect, the regionalisation would result in increased rental prices and in a tendency to the re-allocation of land.

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Federal Highway Administration, Highway Statistics Division, Washington, D.C.

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Federal Highway Administration, Washington, D.C.

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Federal Highway Administration, Washington, D.C.