Acidentes de trabalho em hospital público de alta complexidade no interior paulista: estudo das concepções de segurança

Pós-graduação em Saúde Coletiva - FMB

Mortality from road traffic accidents in Switzerland: longitudinal and spatial analyses

Road traffic accidents (RTA) are an important cause of premature death. We examined socio-demographic and geographical determinants of RTA mortality in Switzerland by linking 2000 census data to RTA mortality records 2000-2005 (ICD-10 codes V00-V99). Data from 5.5 million residents aged 18-94 years, 1744 study areas, and 1620 RTA deaths were analyzed, including 978 deaths (60.4%) in motor vehicle occupants, 254 (15.7%) in motorcyclists, 107 (6.6%) in cyclists, and 259 (16.0%) in pedestrians. Weibull survival models and Bayesian methods were used to calculate hazard ratios (HR), and standardized mortality ratios (SMR) across study areas. Adjusted HR comparing women with men ranged from 0.04 (95% CI 0.02-0.07) in motorcyclists to 0.43 (95% CI 0.32-0.56) in pedestrians. There was a u-shaped relationship with age in motor vehicle occupants and motorcyclists. In cyclists and pedestrians, mortality increased after age 55 years. Mortality was higher in individuals with primary education (HR 1.53; 95% CI 1.29-1.81), and higher in single (HR 1.24; 95% CI 1.05-1.46), widowed (HR 1.31; 95% CI 1.05-1.65) and divorced individuals (HR 1.62; 95% CI 1.33-1.97), compared to persons with tertiary education or married persons. The association with education was particularly strong for pedestrians (HR 1.87; 95% CI 1.20-2.91). RTA mortality increased with decreasing population density of study areas for motor vehicle occupants (test for trend p<0.0001) and motorcyclists (p=0.0021) but not for cyclists (p=0.39) or pedestrians (p=0.29). SMR standardized for socio-demographic and geographical variables ranged from 82 to 190. Prevention efforts should aim to reduce inequities across socio-demographic and educational groups, and across geographical areas, with interventions targeted at high-risk groups and areas, and different traffic users, including pedestrians.

The influence of economic incentives linked to road safety indicators on accidents: The case of toll concessions in Spain

The goal of this paper is to evaluate whether the incentives incorporated in toll highway concession contracts in order to encourage private operators to adopt measures to reduce accidents are actually effective at improving safety. To this end, we implemented negative binomial regression models using information about highway characteristics and accident data from toll highway concessions in Spain from 2007 to 2009. Our results show that even though road safety is highly influenced by variables that are not managed by the contractor, such as the annual average daily traffic (AADT), the percentage of heavy vehicles on the highway, number of lanes, number of intersections and average speed; the implementation of these incentives has a positive influence on the reduction of accidents and injuries. Consequently, this measure seems to be an effective way of improving safety performance in road networks.

Diseño de un modelo para la identificación y análisis de tramos de carreteras sin accidentes : una nueva visión de la seguridad vial

El planteamiento tradicional de análisis de la accidentalidad en carretera pasa por la consideración de herramientas paliativas, como son la identificación y gestión de los puntos negros o tramos de concentración de accidentes, o preventivas, como las auditorías e inspecciones de seguridad vial. En esta tesis doctoral se presenta un planteamiento complementario a estas herramientas, desde una perspectiva novedosa: la consideración de los tramos donde no se producen accidentes; son los denominados Tramos Blancos. La tesis persigue demostrar que existen determinados parámetros del diseño de las carreteras y del tráfico que, bajo características generales similares de las vías, tienen influencia en el hecho de que se produzcan o no accidentes, adicionalmente a la exposición al riesgo, como factor principal, y a otros factores. La propia definición de los Tramos Blancos, entendidos como tramos de carreteras de longitud representativa donde no se han producido accidentes con víctimas mortales o heridos graves durante un periodo largo de tiempo, garantiza que esta situación no se produzca como consecuencia de la aleatoriedad de los accidentes, sino que pudiera deberse a una confluencia específica de determinados parámetros de la geometría de la vía y del tráfico total y de vehículos pesados. Para el desarrollo de esta investigación se han considerado la red de autopistas de peaje y las carreteras convencionales de la Red del Estado de España, que supone un total de 17.000 kilómetros, y los datos de accidentes con víctimas mortales y heridos graves en el periodo 2006-2010, ambos incluidos, en estas redes (un total de 10.000 accidentes). La red viaria objeto de análisis supone el 65% de la longitud de la Red de Carreteras del Estado, por la que circula el 33% de su tráfico; en ella se produjeron en el año 2013 el 47% de los accidentes con víctimas y el 60% de las víctimas mortales de la Red de Carreteras del Estado. Durante la investigación se ha desarrollado una base de datos de 250.130 registros y más de 3.5 millones de datos en el caso de las autopistas de peaje de la Red de Carreteras del Estado y de 935.402 registros y más de 14 millones de datos en el caso de la red convencional del Estado analizada. Tanto las autopistas de peaje como las carreteras convencionales han sido clasificadas según sus características de tráfico, de manera que se valoren vías con nivel de exposición al riesgo similar. Para cada tipología de vía, se ha definido como longitud de referencia para que un tramo se considere Tramo Blanco la longitud igual al percentil 95 de las longitudes de tramos sin accidentes con heridos graves o víctimas mortales durante el periodo 2006-2010. En el caso de las autopistas de peaje, en la tipología que ha sido considerada para la definición del modelo, esta longitud de referencia se estableció en 14.5 kilómetros, mientras que en el caso de las carreteras convencionales, se estableció en 7.75 kilómetros. Para cada uno de los tipos de vía considerados se han construido una base de datos en la que se han incluido las variables de existencia o no de Tramo Blanco, así como las variables de tráfico (intensidad media diaria total, intensidad de vehículos pesados y porcentaje de vehículos pesados ), la velocidad media y las variables de geometría (número de carriles, ancho de carril, ancho de arcén derecho e izquierdo, ancho de calzada y plataforma, radio, peralte, pendiente y visibilidad directa e inversa en los casos disponibles); como variables adicionales, se han incluido el número de accidentes con víctimas, los fallecidos y heridos graves, índices de peligrosidad, índices de mortalidad y exposición al riesgo. Los trabajos desarrollados para explicar la presencia de Tramos Blancos en la red de autopistas de peaje han permitido establecer las diferencias entre los valores medios de las variables de tráfico y diseño geométrico en Tramos Blancos respecto a tramos no blancos y comprobar que estas diferencias son significativas. Así mismo, se ha podido calibrar un modelo de regresión logística que explica parcialmente la existencia de Tramos Blancos, para rangos de tráfico inferiores a 10.000 vehículos diarios y para tráficos entre 10.000 y 15.000 vehículos diarios. Para el primer grupo (menos de 10.000 vehículos al día), las variables que han demostrado tener una mayor influencia en la existencia de Tramo Blanco son la velocidad media de circulación, el ancho de carril, el ancho de arcén izquierdo y el porcentaje de vehículos pesados. Para el segundo grupo (entre 10.000 y 15.000 vehículos al día), las variables independientes más influyentes en la existencia de Tramo Blanco han sido la velocidad de circulación, el ancho de calzada y el porcentaje de vehículos pesados. En el caso de las carreteras convencionales, los diferentes análisis realizados no han permitido identificar un modelo que consiga una buena clasificación de los Tramos Blancos. Aun así, se puede afirmar que los valores medios de las variables de intensidad de tráfico, radio, visibilidad, peralte y pendiente presentan diferencias significativas en los Tramos Blancos respecto a los no blancos, que varían en función de la intensidad de tráfico. Los resultados obtenidos deben considerarse como la conclusión de un análisis preliminar, dado que existen otros parámetros, tanto de diseño de la vía como de la circulación, el entorno, el factor humano o el vehículo que podrían tener una influencia en el hecho que se analiza, y no se han considerado por no disponer de esta información. En esta misma línea, el análisis de las circunstancias que rodean al viaje que el usuario de la vía realiza, su tipología y motivación es una fuente de información de interés de la que no se tienen datos y que permitiría mejorar el análisis de accidentalidad en general, y en particular el de esta investigación. Adicionalmente, se reconocen limitaciones en el desarrollo de esta investigación, en las que sería preciso profundizar en el futuro, reconociendo así nuevas líneas de investigación de interés. The traditional approach to road accidents analysis has been based in the use of palliative tools, such as black spot (or road sections) identification and management, or preventive tools, such as road safety audits and inspections. This thesis shows a complementary approach to the existing tools, from a new perspective: the consideration of road sections where no accidents have occurred; these are the so-called White Road Sections. The aim of this thesis is to show that there are certain design parameters and traffic characteristics which, under similar circumstances for roads, have influence in the fact that accidents occur, in addition to the main factor, which is the risk exposure, and others. White Road Sections, defined as road sections of a representative length, where no fatal accidents or accidents involving serious injured have happened during a long period of time, should not be a product of randomness of accidents; on the contrary, they might be the consequence of a confluence of specific parameters of road geometry, traffic volumes and heavy vehicles traffic volumes. For this research, the toll motorway network and single-carriageway network of the Spanish National Road Network have been considered, which is a total of 17.000 kilometers; fatal accidents and those involving serious injured from the period 2006-2010 have been considered (a total number of 10.000 accidents). The road network covered means 65% of the total length of the National Road Network, which allocates 33% of traffic volume; 47% of accidents with victims and 60% of fatalities happened in these road networks during 2013. During the research, a database of 250.130 registers and more than 3.5 million data for toll motorways and 935.042 registers and more than 14 million data for single carriageways of the National Road Network was developed. Both toll motorways and single-carriageways have been classified according to their traffic characteristics, so that the analysis is performed over roads with similar risk exposure. For each road type, a reference length for White Road Section has been defined, as the 95 percentile of all road sections lengths without accidents (with fatalities or serious injured) for 2006-2010. For toll motorways, this reference length concluded to be 14.5 kilometers, while for single-carriageways, it was defined as 7.75 kilometers. A detailed database was developed for each type of road, including the variable “existence of White Road Section”, as well as variables of traffic (average daily traffic volume, heavy vehicles average daily traffic and percentage of heavy vehicles from the total traffic volume), average speed and geometry variables (number of lanes, width of lane, width of shoulders, carriageway width, platform width, radius, superelevation, slope and visibility); additional variables, such as number of accidents with victims, number of fatalities or serious injured, risk and fatality rates and risk exposure, have also been included. Research conducted for the explanation of the presence of White Road Sections in the toll motorway network have shown statistically significant differences in the average values of variables of traffic and geometric design in White Road Sections compared with other road sections. In addition, a binary logistic model for the partial explanation of the presence of White Road Sections was developed, for traffic volumes lower than 10.000 daily vehicles and for those running from 10.000 to 15.000 daily vehicles. For the first group, the most influent variables for the presence of White Road Sections were the average speed, width of lane, width of left shoulder and percentage of heavy vehicles. For the second group, the most influent variables were found to be average speed, carriageway width and percentage of heavy vehicles. For single-carriageways, the different analysis developed did not reach a proper model for the explanation of White Road Sections. However, it can be assumed that the average values of the variables of traffic volume, radius, visibility, superelevation and slope show significant differences in White Road Sections if compared with others, which also vary with traffic volumes. Results obtained should be considered as a conclusion of a preliminary analysis, as there are other parameters, not only design-related, but also regarding traffic, environment, human factor and vehicle which could have an influence in the fact under research, but this information has not been considered in the analysis, as it was not available. In parallel, the analysis of the circumstances around the trip, including its typology and motivation is an interesting source of information, from which data are not available; the availability of this information would be useful for the improvement of accident analysis, in general, and for this research work, in particular. In addition, there are some limitations in the development of the research work; it would be necessary to develop an in-depth analysis in the future, thus assuming new research lines of interest.

Efficiently computing weighted proximity relationships in spatial databases

Spatial data mining recently emerges from a number of real applications, such as real-estate marketing, urban planning, weather forecasting, medical image analysis, road traffic accident analysis, etc. It demands for efficient solutions for many new, expensive, and complicated problems. In this paper, we investigate the problem of evaluating the top k distinguished “features” for a “cluster” based on weighted proximity relationships between the cluster and features. We measure proximity in an average fashion to address possible nonuniform data distribution in a cluster. Combining a standard multi-step paradigm with new lower and upper proximity bounds, we presented an efficient algorithm to solve the problem. The algorithm is implemented in several different modes. Our experiment results not only give a comparison among them but also illustrate the efficiency of the algorithm.

The effect of age, gender and driver status on pedestrians' intentions to cross the road in risky situations

The theory of planned behaviour (TPB) has been used successfully in the past to account for pedestrians' intentions to cross the road in risky situations. However, accident statistics show age and gender differences in the likelihood of adult pedestrian accidents. This study extends earlier work by examining the relative importance of the model components as predictors of intention to cross for four different adult age groups, men, women, drivers and nondrivers. The groups did not differ in the extent to which they differentiated between two situations of varying perceived risk. The model fit was good, but accounted for less of the variance in intention for the youngest group (17-24) than for other age groups. Differences between the age groups in intention to cross seemed to be due to differences in perceived value of crossing rather than differences in perceived risk. Women were less likely to intend to cross than men and perceived more risk, and there were important age, gender and driver status differences in the importance of the TPB variables as predictors of intention. A key implication of these findings is that road safety interventions need to be designed differently for different groups. © 2006 Elsevier Ltd. All rights reserved.

Gender differences in factors predicting unsafe crossing decisions in adult pedestrians across the lifespan: a simulation study

Adult pedestrian accident data has demonstrated that the risk of being killed or seriously injured varies with age and gender. A range of factors affecting road crossing choices of 218 adults aged 17-90+ were examined in a simulation study using filmed real traffic. With increasing age, women were shown to make more unsafe crossing decisions, to leave small safety margins and to become poorer at estimating their walking speed. However, the age effects on all of these were ameliorated by driving experience. Men differed from women in that age was not a major factor in predicting unsafe crossing decisions. Rather, reduced mobility was the key factor, leading them to make more unsafe crossings and delay longer in leaving the kerb. For men, driving experience did not predict unsafe road crossing decisions. Although male drivers were more likely to look both ways before crossing than male non-drivers, the impact of being a driver had a negative effect in terms of smaller safety margins and delay in leaving the kerb. The implications of the different predictor variables for men and women for unsafe road crossing are discussed and possible reasons for the differences explored.

The effect of age, gender and attitudes on self-regulation in driving

Self-regulation in driving has primarily been studied as a precursor to driving cessation in older people, who minimise driving risk and compensate for physical and cognitive decline by avoiding driving in challenging circumstances, e.g. poor weather conditions, in the dark and at busy times. This research explores whether other demographic groups of drivers adopt self-regulatory behaviours and examines the effects of affective and instrumental attitudes on self-regulation across the lifespan. Quantitative data were collected from 395 drivers. Women were significantly more likely than men to engage in self-regulation, and to be negatively influenced by their emotions (affective attitude). A quadratic effect of age on self-regulation was determined such that younger and older drivers reported higher scores for self-regulation than middle-years' drivers. However, this effect was affected by experience such that when experience was controlled for, self-regulation increased with age. Nevertheless, anxious driving style and negative affective attitude were independent predictors of self-regulation behaviours. Results suggest that self-regulation behaviours are present across the driving lifespan and may occur as a result of driving anxiety or low confidence rather than as an effect of ageing.

Influence of personal mobile phone ringing and usual intention to answer on driver error

Given evidence of effects of mobile phone use on driving, and also legislation, many careful drivers refrain from answering their phones when driving. However, the distracting influence of a call on driving, even in the context of not answering, has not been examined. Furthermore, given that not answering may be contrary to an individual’s normal habits, this study examined whether distraction caused by the ignored call varies according to normal intention to answer whilst driving. That is, determining whether the effect is more than a simple matter of noise distraction. Participants were 27 young drivers (18-29 years), all regular mobile users. A Theory of Planned Behaviour questionnaire examined predictors of intention to refrain from answering calls whilst driving. Participants provided their mobile phone number and were instructed not to answer their phone if it were to ring during a driving simulation. The simulation scenario had seven hazards (e.g. car pulling out, pedestrian crossing) with three being immediately preceded by a call. Infractions (e.g. pedestrian collisions, vehicle collisions, speed exceedances) were significantly greater when distracted by call tones than with no distraction. Lower intention to ignore calls whilst driving correlated with a larger effect of distraction, as was feeling unable to control whether one answered whilst driving (Perceived Behavioural Control). The study suggests that even an ignored call can cause significantly increased infractions in simulator driving, with pedestrian collisions and speed exceedances being striking examples. Results are discussed in relation to cognitive demands of inhibiting normal behaviour and to drivers being advised to switch phones off whilst driving.

Examining links between cognitive markers, movement initiation and change, and pedestrian safety in older adults

Objective: The purpose of this study was to determine the extent to which mobility indices (such as walking speed and postural sway), motor initiation, and cognitive function, specifically executive functions, including spatial planning, visual attention, and within participant variability, differentially predicted collisions in the near and far sides of the road with increasing age. Methods: Adults aged over 45 years participated in cognitive tests measuring executive function and visual attention (using Useful Field of View; UFoV®), mobility assessments (walking speed, sit-to-stand, self-reported mobility, and postural sway assessed using motion capture cameras), and gave road crossing choices in a two-way filmed real traffic pedestrian simulation. Results: A stepwise regression model of walking speed, start-up delay variability, and processing speed) explained 49.4% of the variance in near-side crossing errors. Walking speed, start-up delay measures (average & variability), and spatial planning explained 54.8% of the variance in far-side unsafe crossing errors. Start-up delay was predicted by walking speed only (explained 30.5%). Conclusion: Walking speed and start-up delay measures were consistent predictors of unsafe crossing behaviours. Cognitive measures, however, differentially predicted near-side errors (processing speed), and far-side errors (spatial planning). These findings offer potential contributions for identifying and rehabilitating at-risk older pedestrians.

A road safety performance indicator for vehicle fleet compatibility

This paper discusses the development and the application of a safety performance indicator which measures the intrinsic safety of a country's vehicle fleet related to fleet composition. The indicator takes into account both the ‘relative severity’ of individual collisions between different vehicle types, and the share of those vehicle types within a country's fleet. The relative severity is a measure for the personal damage that can be expected from a collision between two vehicles of any type, relative to that of a collision between passenger cars. It is shown how this number can be calculated using vehicle mass only. A sensitivity analysis is performed to study the dependence of the indicator on parameter values and basic assumptions made. The indicator is easy to apply and satisfies the requirements for appropriate safety performance indicators. It was developed in such a way that it specifically scores the intrinsic safety of a fleet due to its composition, without being influenced by other factors, like helmet wearing. For the sake of simplicity, and since the required data is available throughout Europe, the indicator was applied to the relative share of three of the main vehicle types: passenger cars, heavy goods vehicles and motorcycles. Using the vehicle fleet data from 13 EU Member States and Norway, the indicator was used to rank the countries’ safety performance. The UK was found to perform best in terms of its fleet composition (value is 1.07), while Greece has the worst performance with the highest indicator value (1.41).

Relación entre la calificación de los elementos de un sistema de gestión y los indicadores de accidentalidad en empresas del sector de la construcción en Colombia

El presente estudio tiene como objetivo determinar la relación que existe entre la implementación de un sistema de gestión de seguridad y salud en el trabajo (SGSST), y la frecuencia y la severidad de la accidentalidad en la industria de la construcción en Colombia. Para ello se seleccionaron 35 empresas que realizan actividades relacionadas con la edificación, infraestructura e interventoría, que hubiesen implementado un SGSST para la intervención de los riesgos de accidentes y que contaran con la evaluación del mismo. La evaluación del SGSST está enmarcada en cinco dimensiones o criterios: planeación, política, implementación, manejo integral del accidente y revisión por la gerencia. Cada una evaluada a través de diferentes requisitos y se presentan en una escala de 1 a 10, siendo 10 el nivel más alto del cumplimiento por requisito. Teniendo los resultados de esta calificación, la tasa (proporción entre los accidentes reportados y los trabajadores de cada empresa) y los días de incapacidad (ausentismo por accidente de trabajo), se realizó un análisis de las medidas descriptivas consolidado por las empresas del estudio: tendencia central y dispersión para número de trabajadores, tasa de accidentalidad, días de incapacidad y el resultado de los totales de cada criterio de la evaluación y el gran total. Para estudiar la relación entre los resultados de la evaluación y los indicadores de tasa y días, se llevó a cabo un análisis de correlación y regresión lineal entre los indicadores de accidentalidad y los resultados de las puntuaciones de los criterios. Esta correlación se realizó tanto para la primera evaluación como para la segunda. En las dos mediciones las correlaciones fueron negativas mostrando que existe una disminución en la tasa de accidentalidad y días de incapacidad entre una evaluación y la otra. En el análisis de regresión, en la primera evaluación por cada unidad que aumentó la calificación global, se presentó una reducción de la tasa de frecuencia de 0.140. En la segunda evaluación por cada unidad que aumentó la calificación global, la tasa se redujo en 0.159. Ambos hallazgos soportan la necesidad de implementar un SGSST para ayudar a reducir el número inaceptable de lesiones y enfermedades en la industria de la construcción.

Relación entre estrés y desórdenes músculo esqueléticos en trabajadores de una empresa de transporte terrestre de pasajeros, Bogotá, 2015.

Introducción. Los conductores de transporte terrestre de pasajeros están expuestos a factores de riesgo inherentes a su labor, por lo que la intervención sobre estos factores es un aspecto relevante en las empresas de transporte público dado que dicha actividad afecta la calidad de vida de los mismos. Objetivo: Determinar la prevalencia de estrés en el lugar de trabajo y los factores de riesgo biomecánicos asociados en trabajadores de una empresa de transporte terrestre de pasajeros. Materiales y métodos: Estudio de corte transversal con datos secundarios procedentes de una población de 219 empleados, de los cuales 13 eran administrativos y 206 laboraban en la operación de una empresa de transporte terrestre de pasajeros. Las variables incluidas fueron socio demográficas, laborales, variables relacionadas con la medición de estrés y síntomas osteomusculares. El análisis estadístico incluyó medidas de tendencia central y dispersión y para identificar los factores asociados con el estrés se utilizaron pruebas de asociación Chi2 y prueba exacta de Fisher. Resultados: La edad promedio de los participantes fue de 43 años (DS 10 años), siendo en su mayoría trabajadores de sexo masculino (96,3%). Se presentaron síntomas y factores de riesgo biomecánicos en cuello y espalda en un 55.5%. Se encontró asociación significativa entre estrés con los síntomas en pies (p=0,009), con los factores de riesgo biomecánicos, se encontró relación significativa con el tiempo que permanece adoptando las posturas de inclinación hacia delante (p=0,000) y hacia atrás (p=0,001) de espalda/tronco y las posturas en muñecas, (p=0,000), y a la exposición de los conductores a superficies vibrantes (asientos de vehículo) (p=0,021). No se encontró asociación significativa entre estrés y la postura de sedente. Conclusiones: Con este estudio se encontró una prevalencia de estrés de 78% en el lugar de trabajo y de los factores de riesgo biomecánicos asociados a antigüedad, postura y repetitividad de movimientos, con repercusiones en cuello y espalda lumbar, por lo tanto, se requiere de un seguimiento a las condiciones de salud y trabajo para los empleados del sector transporte.

Accidentes de trabajo e índice de masa corporal en vigilantes atendidos en una I.P.S. de salud ocupacional, Bogotá - Colombia, 2015

INTRODUCCIÓN: Todos los individuos dentro de una sociedad tienen derecho a disfrutar de una integridad física, mental y de sus bienes materiales, que en principio debe ser garantizada por el Estado, sin embargo, debido a la ineficacia y falta de alcance en la disponibilidad de hombres y mujeres para cuidar a cada persona y empresa, la Seguridad Privada ha surgido como actividad económica para garantizar éste servicio de manera individualizada. No obstante a ello, poco se sabe acerca de las características de las personas que desempeñan ésta labor, así como las demandas inherentes a ésta actividad económica; sin embargo, en poblaciones económicamente similares, se documenta a través de la literatura la aparente relación entre la condición física del individuo y la presentación de accidentes de trabajo. OBJETIVO: Establecer la relación entre los accidentes de trabajo y el índice de masa corporal (IMC) en vigilantes atendidos en una I.P.S. de Salud Ocupacional en la ciudad de Bogotá-Colombia, durante el año 2015. MATERIALES Y MÉTODOS: Se llevó a cabo un estudio de corte transversal, con datos secundarios de una base de datos de 76 registros, procedentes de las historias clínicas médico ocupacionales realizadas a una población de trabajadores del sector de la Vigilancia o Seguridad Privada, durante su atención en una Institución Prestadora de Salud (I.P.S.) de Salud Ocupacional. Se incluyeron variables sociodemográficas, ocupacionales, las relacionadas con los accidentes de trabajo y el índice de masa corporal. Se obtuvieron las frecuencias univariadas y para las variables de tipo cuantitativo, medidas de tendencia central y dispersión, además de buscar potenciales asociaciones estadísticas, para conocer las variables que se relacionan con el evento estudiado. RESULTADOS: En éste proyecto se destaca que de los trabajadores que desempeñan la actividad económica de Vigilancia y Seguridad Privada, se encuentran en el grupo de 20 a 39 años (56.5%) y pertenecen al género masculino (84.2%); dichos factores contribuyen a la ocurrencia de los accidentes de trabajo (OR de 1.7 y 2.0 respectivamente). Además el I.M.C. de sobrepeso (OR 1.8), la obesidad (OR 1.4); y en sí el cargo de Vigilante concurren a la accidentalidad laboral (OR de 1.1) y con ello al incremento de incapacidad laboral en un 85.5% de 0 a 60 días. CONCLUSIONES: Se deben establecer medidas encaminadas al emprendimiento de sistemas de vigilancia epidemiológica que mitiguen y minimicen el riesgo, con ello la presencia de eventos no deseados en el ámbito laboral para ésta población y la disminución del ausentismo laboral.

Improving the railway’s understanding of accident causation through an integrated approach to human factors analysis and technical safety data recording

This paper describes a safety data recording and analysis system that has been developed to capture safety occurrences including precursors using high-definition forward-facing video from train cabs and data from other train-borne systems. The paper describes the data processing model and how events detected through data analysis are related to an underlying socio-technical model of accident causation. The integrated approach to safety data recording and analysis insures systemic factors that condition, influence or potentially contribute to an occurrence are captured both for safety occurrences and precursor events, providing a rich tapestry of antecedent causal factors that can significantly improve learning around accident causation. This can ultimately provide benefit to railways through the development of targeted and more effective countermeasures, better risk models and more effective use and prioritization of safety funds. Level crossing occurrences are a key focus in this paper with data analysis scenarios describing causal factors around near-miss occurrences. The paper concludes with a discussion on how the system can also be applied to other types of railway safety occurrences.