Global trend according to estimated number of occupational accidents and fatal work-related diseases at region and country level

Background

Although occupational accidents and work-related diseases have been of interest for a long time, due to lack of proper recording and notification systems the official numbers of occupational accidents and work-related diseases are missing for many countries. Presently, the demand for effectiveness and an interest in the economic aspects of accidents have increased prevention activities at company and country levels.

Methods

Occupational accident data of selected countries and of World Health Organization regional divisions together with the global burden of disease were used in estimating global occupational accidents and fatal work-related diseases. The trend of global occupational accidents and work-related diseases is presented at region and country levels. The years 1998, 2001, and 2003 are compared in the case of occupational accidents and the years 2000 and 2002 in the case of work-related diseases.

Results

The total number of occupational accidents and fatal work-related diseases has increased, but the fatality rates per 100,000 workers have decreased. There were almost 360,000 fatal occupational accidents in 2003 and almost 2 million fatal work-related diseases in 2002. Every day more than 960,000 workers get hurt because of accidents. Each day 5,330 people die because of work-related diseases.

Conclusions

Information on occupational accidents and work-related diseases is needed so that countries may understand better the importance of occupational health and safety at country and company level. Especially companies in developing countries are not familiar with occupational safety and health. Statistical data is essential for accident prevention; it is a starting point for the safety work.     

Acciphilia on the road: An analysis of severe collisions

Introduction

Although prior studies of road traffic accidents have found between-group differences in risk, little attention has been given to the encounter between drivers involved in severe collisions.

Method

The present study empirically evaluates two different possible causes of "social accidents," which are defined as collisions between two or more drivers where some faulty social interaction might be assumed, and which are the most prevalent cause of road injuries. The analyses use merged Israeli collision records from 1983 to 2004 with data from two national censuses, thus providing an unprecedented empirical basis to study the social foundations of car accidents. The data are used to adjudicate between two alternative hypotheses: the heterogeneity hypothesis (socially different drivers tend to collide) versus the homogeneity hypothesis (socially similar drivers tend to collide).

Results

Multivariate analyses provide preliminary support for the latter hypothesis. Given an accident, there are more collisions among drivers from the same broad educational group, and the factors that influence this correlation are independent of geography. The paper thus leads to the idea that severe collisions reflect a sociological or ecological process that is akin to acciphilia.

Impact on Industry

The preliminary findings suggest that variation between drivers may be preferable to similarity, since apparently there is a greater tendency toward collisions between similar drivers.     

A method for simplifying the analysis of traffic accidents injury severity on two-lane highways using Bayesian networks

Introduction

This study describes a method for reducing the number of variables frequently considered in modeling the severity of traffic accidents. The method's efficiency is assessed by constructing Bayesian networks (BN).

Method

It is based on a two stage selection process. Several variable selection algorithms, commonly used in data mining, are applied in order to select subsets of variables. BNs are built using the selected subsets and their performance is compared with the original BN (with all the variables) using five indicators. The BNs that improve the indicators’ values are further analyzed for identifying the most significant variables (accident type, age, atmospheric factors, gender, lighting, number of injured, and occupant involved). A new BN is built using these variables, where the results of the indicators indicate, in most of the cases, a statistically significant improvement with respect to the original BN.

Conclusions

It is possible to reduce the number of variables used to model traffic accidents injury severity through BNs without reducing the performance of the model.

Impact on Industry

The study provides the safety analysts a methodology that could be used to minimize the number of variables used in order to determine efficiently the injury severity of traffic accidents without reducing the performance of the model.     

Random parameter models for accident prediction on two-lane undivided highways in India

Introduction

Generalized linear modeling (GLM), with the assumption of Poisson or negative binomial error structure, has been widely employed in road accident modeling. A number of explanatory variables related to traffic, road geometry, and environment that contribute to accident occurrence have been identified and accident prediction models have been proposed. The accident prediction models reported in literature largely employ the fixed parameter modeling approach, where the magnitude of influence of an explanatory variable is considered to be fixed for any observation in the population. Similar models have been proposed for Indian highways too, which include additional variables representing traffic composition. The mixed traffic on Indian highways comes with a lot of variability within, ranging from difference in vehicle types to variability in driver behavior. This could result in variability in the effect of explanatory variables on accidents across locations. Random parameter models, which can capture some of such variability, are expected to be more appropriate for the Indian situation.

Method

The present study is an attempt to employ random parameter modeling for accident prediction on two-lane undivided rural highways in India. Three years of accident history, from nearly 200 km of highway segments, is used to calibrate and validate the models.

Results

The results of the analysis suggest that the model coefficients for traffic volume, proportion of cars, motorized two-wheelers and trucks in traffic, and driveway density and horizontal and vertical curvatures are randomly distributed across locations.

Conclusions

The paper is concluded with a discussion on modeling results and the limitations of the present study.     

The accident-exposure association: self-reported versus recorded collisions

Problem

It has been claimed that exposure to risk of road traffic accidents (usually conceptualized as mileage) is curvilinearly associated with crashes (i.e., the increase in number of crashes decreases with increased mileage). However, this effect has been criticized as mainly an artifact of self-reported data.

Method

To test the proposition that self-reported accidents create part of the curvilinearity in data by under-reporting by high-accident drivers, self-reported and recorded collisions were plotted against hours of driving for bus drivers.

Results

It was found that the recorded data differed from self-reported information at the high end of exposure, and had a more linear association with the exposure measure as compared to the self-reported data, thus supporting the hypothesis.

Discussion

Part of the previously reported curvilinearity between accidents and exposure is apparently due to biased methods. Also, the interpretation of curvilinearity as an effect of exposure upon accidents was criticized as unfounded, as the causality may just as well go the other way. Impact on industry: The question of how exposure associates with crash involvement is far from resolved, and everyone who uses an exposure metric (mileage, time, induced) should be careful to investigate the exact properties of their variable before using it.     

Injury severity analysis of accidents involving young male drivers in Great Britain

Introduction

Young male drivers are over-represented in traffic accidents; they were involved in 14% of fatal accidents from 1991 to 2003 while holding only 8% of all drivers licenses in the UK. In this study, a subset of the UK national road accident data from 1991 to 2003 has been analyzed. The primary aim is to determine how to best use monetary and progressive resources to understand how road safety measures will reduce the severity of accidents involving young male drivers in both London and Great Britain.

Method

Ordered probit models were used to identify specific accident characteristics that increase the likelihood of one of three categorical outcomes of accident severity: slight, serious, or fatal.

Results

Characteristics found to lead to a higher likelihood of serious and fatal injuries are generally similar across Great Britain and London but are different from those predicted to lead to a higher likelihood of slight injuries. Those characteristics predicted to lead to serious and fatal injuries include driving in darkness, between Friday and Sunday, on roads with a speed limit of 60 mph, on single carriageways, overtaking, skidding, hitting an object off the carriageway, and when passing the site of a previous accident. Characteristics predicted to lead to slight injuries include driving in daylight, between Monday and Thursday, on roads with a speed limit of 30 mph or less, at a roundabout, waiting to move, and when an animal is on the carriageway.

Impact on Industry

These results aid the selection of policy options that are most likely to reduce the severity of accidents involving young male drivers.     

Blood on the coal: The effect of organizational size and differentiation on coal mine accidents

Introduction

Each year, there are at least 100,000,000 occupational accidents and 100,000 occupational deaths in the world. In the United States, one of the safest countries in the world in which to work, there were more than 5,400 workplace fatalities and 5.9 million workplace injuries in 2007. The cost to American industry and taxpayers is estimated to be at least $170 billion per year. Further, as illustrated by accidents such as Three Mile Island and Bhopal, industrial accidents potentially impact a much wider sphere than that of the injured worker and his or her employer. As the repercussions of organizational accidents reverberate through organizations and are felt from human resources to accounting, firms are beginning to incorporate messages of safety in their missions and strategies. As firms organize to achieve safer work environments, they are faced with decisions on how to structure their activities in terms of, among other things, size and differentiation.

Method

This paper explores the impact on accident rates of size and differentiation at the corporate and mine levels of mining companies in an effort to create a framework for thinking about organizational accidents from a structural perspective.

Results

The results suggest that larger mines are safer than smaller mines, and that mines with less task diversity are safer than mines with greater task diversity. The results also suggest that at the corporate level, task diversity decreases mine accidents. These results may help mining executives and engineers structure their corporate activities and individual mines more effectively to help reduce accidents.     

Survival risk factors for fatal injured car and motorcycle drivers in single alcohol-related and alcohol-unrelated vehicle crashes

Introduction

A high percentage of drivers who die as a result of a single vehicle crash are under the influence of alcohol. We aimed to better understand the prevalence of these fatalities and the ratio of death to injuries based on various risk factors. We focused on alcohol-related and -unrelated single-vehicle crashes to investigate the influence of such risk factors on the time until death for car and motorcycle drivers.

Methods

We combined data from national police reports and a vital registration database in Taiwan. Survival analysis using Cox regression models was used to identify the risk factors of time until death.

Results

Overall, nearly 60% of car driver fatalities and 40% of motorcycle driver fatalities involved the consumption of alcohol. Survival analysis of single-vehicle crashes suggested that the traffic island separation between a car moving at a higher speed and motorcycle traffic resulted in a higher risk of death over time for motorcycle drivers who consumed alcohol. The factors attributed to a higher risk of death over time for motorcycle drivers were older age, crashing into trees, night-time driving, driving on curved roads, and driving on local roads. Driving without restraints and driving on roads with higher speed limits attributed to a higher risk of death over time for car drivers.

Conclusions

The factors that influence the risk of death over time in a motor-vehicle accident involving alcohol depended on different elements, which should each be considered when attempting to reduce this risk.

Impact on Industry

More efforts should be made to investigate the various risk factors in areas with large motorcycle populations.     

Differences in urban and rural accident characteristics and medical service utilization for traffic fatalities in less-motorized societies

Introduction

Fatalities from traffic accidents in less-motorized societies are an important global issue. We aimed to characterize the geographic differences of fatalities in such societies to facilitate the development of targeted interventions.

Method

This study linked police reports, hospital data, and vital registration data from Taiwan with special reference to accident factors in pre-hospital deaths and medical care in hospital deaths.

Results

A higher percentage of pre-hospital deaths were observed following rural as compared to urban traffic accidents. The deaths due to rural accidents can be attributed to lower use of restraints (i.e., helmets or seat belts), lower percentage of motorcyclists, and more highway accidents. A higher percentage of victims in rural accidents were transported to distant medical centers rather than to local hospitals.

Conclusion

Specific interventions, such as intelligent emergency medical systems, campaigns for helmets and seat belt usage, enforcement of helmets and seat belt use, and speed control measures should be targeted to rural areas.

Impact on industry

Cooperation between the vehicle industry and emergency medical providers in rural traffic accident rescue teams may decrease the numbers of deaths in these regions.     

Case-control and cross-sectional methods for estimating crash modification factors: comparisons from roadway lighting and lane and shoulder width safety effect studies

Problem

While observational before-after studies are considered the industry standard for developing crash modification factors (CMFs), there are practical limitations that may preclude their use in highway safety analysis. There is a need to explore alternative methods for estimating CMFs.

Method

This paper employs case-control and cross-sectional analyses to estimate CMFs for fixed roadway lighting and the allocation of lane and shoulder widths.

Results

Based on the case-control method, the CMF for intersection lighting is 0.886, while the cross-sectional study indicates a CMF of 0.881. The CMFs developed for lane and shoulder widths are also similar when comparing the two methods.

Conclusions

This paper suggests that case-control and cross-sectional studies produce consistent results if care is taken in the study design and model development.

Impact on industry

Case-control and cross-sectional studies may provide a viable alternative to estimate CMFs when a before-after study is impractical due to data restrictions.     

Needle stick and sharps injuries among health care workers in Gondar city, Ethiopia

Background

All employees in health care settings handling needles or other sharps are at risk for needle stick and sharps injuries (NSSIs). Health care workers in under developed countries are at greater risk of infection from blood borne pathogens because of the lack of safety devices and the high prevalence of these pathogens.

Objectives

The aim of this study was to assess the prevalence of NSSIs and associated factors among health care workers in government health institutions in Gondar city, Ethiopia.

Methods

Institution based cross sectional study was conducted from May-December, 2010. The study included 344 health care workers who were selected from the source population using simple random sampling technique. Data were collected through interviews using structured and pre-tested questionnaire and the collected data were entered and analyzed using SPSS version 16.0.

Results

The prevalence of NSSIs among health care workers in the preceding 12 months was 106 (30.8%), of which 58 (54.7%) was reported by females. Lack of training on occupational health and safety, working more than 48 h/week, dissatisfaction with work environment and work culture, greater than 10 years of work experience and having low and moderate perception of risk were found to be significantly associated with NSSIs.

Conclusion

The study found high prevalence of NSSIs among health care workers. Effective training, ongoing awareness on the risk of hazards, preventive measures such as engineering control, and post-exposure prophylaxis following NSSIs are essential to reduce the risk of such injuries.     

When may road fatalities start to decrease?

Introduction

The comparative analysis of macroscopic trends in road safety has been a popular research topic. The objective of this research is to propose a simple and, at the same time, reliable multiple regime model framework for international road safety comparisons, allowing for the identification of slope changes of personal risk curves and respective breakpoints.

Method

The trends of road traffic fatalities in several EU countries have been examined through the temporal evolution of elementary socioeconomic indicators, namely motorized vehicle fleet and population, at the country level.

Results

Piece-wise linear regression models have been fitted, using a methodology that allows the simultaneous estimation of all slopes and breakpoints. The number and location of breakpoints, as well as the slope of the connecting trends, vary among countries, thus indicating different road safety evolution patterns.

Impact on industry

Macroscopic analysis of road accident trends may be proved beneficial for the identification of best examples and the implementation of appropriate programmes and measures, which will lead to important benefits for the society and the economy through the reduction of road fatalities and injuries. Best performing countries and the related programmes and measures adopted may concern several safety improvements at the processes of the road, the vehicle and the insurance industries.

Conclusions

Lessons from the analysis of the past road safety patterns of developed countries provide some insight into the underlying process that relates motorization levels with personal risk and can prove to be beneficial for predicting the road safety evolution of developing countries that may have not yet reached the same breakpoints. Furthermore, the presented framework may serve as a basis to build more elaborate models, including more reliable exposure indicators (such as vehicle-km driven).     

What is the potential of trauma registry data to be used for road traffic injury surveillance and informing road safety policy?

Introduction

Information from hospital trauma registries is increasingly being used to support injury surveillance efforts. This research examines the potential of using trauma registry data for road traffic injury surveillance for different types of road users in terms of both the information collected and how representative trauma data are compared to two population-based road traffic injury data collections.

Methods

The three data collections were assessed against recommended variables to be collected for injury surveillance purposes and the representativeness of the distribution of road traffic-related injury data from the trauma registry was compared to hospital admission and road traffic authority data collections.

Results

Data from the trauma registry was largely not representative of the distribution of age groups or activities compared to the two population-based collections, but was representative for gender for some road user groups to at least one population-based data collection.

Conclusions

Trauma data could be used to supplement information from population-based data collections to inform road safety efforts.

Impact on Industry

Road safety policy makers should be aware of the potential and the limitations of using trauma registry data for road traffic injury surveillance.     

Comparison of risk factors for falls from height between commercial and residential roofers

Introduction

The purpose of this investigation was to compare commercial roofers and residential roofers in terms of their behaviors, beliefs, working conditions, and attitudes toward the use of fall protection devices, which could lead to fall accidents.

Methods

A cross-sectional sample of 252 roofers participated in the survey in the Midwest (Wisconsin, Illinois, Michigan, Indiana, and Iowa).

Results

Residential roofers were more likely to fall (adjusted prevalence ratio = 1.57, 95% CI = 0.86, 2.27) than commercial roofers. Existence of fall protection programs, enforcement of fall protection device use, actual use of fall protection devices, work type, company size, and race/ethnicity were significantly associated with fall accidents.

Impact on industry

This study adds insight into fall accidents from roofs in the construction industry and provides industry-specific cautions against fall accidents that can be reflected in regulatory agency implementation.     

Project level analysis of special trade contractor fatalities using accident investigation reports

Introduction

Construction is among the most dangerous industries in the United States accounting for thousands of fatalities every year. Although there is data available on high risk work types and areas, the project-level detail is not readily available.

Method

This paper uses the accident investigation reports to categorize project types and presents project level analysis of 350 fatal accidents for special trade contractors.

Results

The results showed that Residential and Commercial projects lead the fatalities where Falls are observed as the leading cause. However, when the fatality causes and project categories are analyzed for each work type, the results showed different fatality cause proportions for each project type.

Impact on Industry

Project level analysis approach has a direct impact on identifying high risk work types and areas for special trade contractors by making it possible to focus the prevention and intervention efforts more accurately, while highlighting training and education needs.     

Nonfatal bathroom injuries among persons aged ≥15 years--United States, 2008

Problem

Information about where nonfatal unintentional injuries occur is limited, but bathrooms commonly are believed to be a hazardous location.

Methods

Data from a nationally representative sample of hospital emergency departments (ED) was used to quantify and characterize nonfatal unintentional bathroom injuries among people aged ≥ 15 years.

Results

In 2008, an estimated 234,094 nonfatal bathroom injuries were treated in EDs. Most injuries (81.1%) were caused by falls and 37.3% of injuries occurred when bathing, showering, or getting out of the tub or shower. Both injury and hospitalization rates increased with age.

Summary

These results suggest that bathrooms tend to be most hazardous for persons in the oldest age groups.

Impact on Industry

Bathroom injuries among all household members might be reduced by increasing awareness about potentially hazardous activities in the bathroom combined with simple environmental changes such as adding grab bars inside and outside the tub or shower.     

The role of production and teamwork practices in construction safety: A cognitive model and an empirical case study

Problem

In construction, the challenge for researchers and practitioners is to develop work systems (production processes and teams) that can achieve high productivity and high safety at the same time. However, construction accident causation models ignore the role of work practices and teamwork. This study investigates the mechanisms by which production and teamwork practices affect the likelihood of accidents.

Method

The paper synthesizes a new model for construction safety based on the cognitive perspective (Fuller's Task-Demand-Capability Interface model, 2005) and then presents an exploratory case study. The case study investigates and compares the work practices of two residential framing crews: a 'High Reliability Crew' (HRC)—that is, a crew with exceptional productivity and safety over several years, and an average performing crew from the same company.

Results

The model explains how the production and teamwork practices generate the work situations that workers face (the task demands) and affect the workers ability to cope (capabilities). The case study indicates that the work practices of the HRC directly influence the task demands and match them with the applied capabilities. These practices were guided by the 'principle' of avoiding errors and rework and included work planning and preparation, work distribution, managing the production pressures, and quality and behavior monitoring.

Summary

The Task Demand-Capability model links construction research to a cognitive model of accident causation and provides a new way to conceptualize safety as an emergent property of the production practices and teamwork processes. The empirical evidence indicates that the crews' work practices and team processes strongly affect the task demands, the applied capabilities, and the match between demands and capabilities.

Impact on Industry

The proposed model and the exploratory case study will guide further discovery of work practices and teamwork processes that can increase both productivity and safety in construction operations. Such understanding will enable training of construction foremen and crews in these practices to systematically develop high reliability crews.     

Age and gender differences in conviction and crash occurrence subsequent to being directed to Iowa's driver improvement program

Introduction

This paper investigates potential gender and age differences in conviction and crash occurrence subsequent to being directed to attend Iowa's Driver Improvement Program (DIP).

Methods

Binary logit models were developed to investigate the factors that influence conviction occurrence after DIP by gender and age. Because of the low crash occurrence subsequent to DIP, association rules were applied to investigate the factors that influence crash occurrence subsequent to DIP, in lieu of econometric models.

Results

There were statistical significant differences by driver gender, age, and conviction history in the likelihood of subsequent convictions. However, this paper found no association between DIP outcome, crash history, and crash occurrence.

Impact on industry

Evaluating the differences in conviction and crash occurrence subsequent to DIP between female and male drivers, and among different age groups can lead to improvements of the effectiveness of DIPs and help to identify low-cost intervention measures, customized based on drivers’ gender and age, for improving driving behaviors.     

Hepatitis B virus infection among health care workers in Public Teaching Hospitals in Khartoum State, Sudan

Background

Hepatitis B virus (HBV) infection is a global public health problem. It is estimated that there are more than 300 million HBV carriers in the world.

Aim

The study aimed to examine the sero-prevalence of hepatitis B virus (HBV) markers among health care workers (HCWs) in Public Teaching Hospitals in Khartoum State, in the year 2004.

Methods

The study is an observational, cross sectional, facility-based study. It was conducted on stratified two-stage cluster random sample of 843 subjects. The study followed non-parametric statistical methods, using Z-test for single proportion.

Results

Among the 843 subjects tested for all HBV markers (Anti-HBc, HBsAg, HBsAb, and HBeAg), the prevalence of Anti-HBc, HBsAg, HBsAb, and HBeAg was found to be 57% (CI 95%:53-60%), 6% (CI 95%:4.0-8.0%), 37% (CI 95%:34-40%) and 9% (CI 95%:7-11%) respectively. P < 0.05.

Conclusion

Seroprevalence of all HBV markers (P < 0.05) was found to be significantly high, while the rate of immunity against HBV infection was low among health care workers In Public Teaching Hospitals in Khartoum State, Sudan.