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«FICHA TÉCNICA Título Segurança e Higiene Ocupacionais - SHO 2012 - Livro de Resumos Autores/Editores Arezes, P., Baptista, J.S., Barroso, M.P., ...»

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Occupational Safety and HygieneInternational Symposium on

ratio show some risk factors as being older than 45 years old, having an experience of more than 6 months, being employed as technicians, reporting mechanical as their main risk or working on average more than 45 hours per week.

Other variables like sex are not significant when occupation and main risks are included in the model. This result implies that female accidents are more related to job assignment in the Andalusian manufacturing sector. Age and tenure have a strong association. We checked two models (I and II), age was significant if tenure was not included. This means that tenure is more important than age in terms of statistical signification but age is a risk factor. Thus, workers with over 45 years old and long tenure would need special re-training and safety motivation. This is the main result provided.

Nationality could not be analysed as none of the foreign workers (13 cases) reported an accident in the last two years.

Future survey sampling should be adjusted to have enough cases of this emergent issue in safety science.

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Further research is needed both to confirm the role of the factors studied and to better understand how these factors influence in the occurrence of accidents. However, there are actions that could already be performed: re-training of longtenured workers and ok workers over 45 years old, avoiding extended working time or, if this is not possible, providing additional preventive measures, especially for those who work more than 45 hours per week.

Main limitations of this study are related to quality of data as it is based on survey data. Besides, the models only considered the existence of accidents but neither its severity nor the type of injury (mechanism are different for traumatic, musculo-skeletal and non-traumatic accidents).

5. REFERENCES Ahonen, E. Q., Benavides, F. G., & Benach, J. (2007). Inmigrant Populations, work and health - a systematic literature review.

Scandinavian Journal of Work Enviromental Health, 33 (2), 96-104.

Benavides, F. G., Benach, J., Muntaner, C., Delclos, G. L., Catot, N., & Amable, M. (2006). Associations between temporary employment and occupational injury: what are the mechanisms? Occupational Enviromental Medicine, 63 (6), 416-421.

Dembe, A. E., Erickson, J. B., & Delbos, R. (2004). Predictors of Work-Related Injuries and Illnesses: National Survey Findings.

Journal of Occupational and Environmental Hygiene, 1 (8), 542-550.

Instituto Andaluz de Prevención de Riesgos Laborales (2009). Retrived November, 11th 2011 from http://www.juntadeandalucia.es/empleo/www/herramientas/biblioteca_virtual/bibliotecaDetalle.php?id=1555 International Labor Organization (1998). Encyclopaedia of International Safety Organization. Retrived November, 11th 2011 from http://www.ilo.org/safework_bookshelf/english?d&nd=170000102&nh=0.

Folkard, S., & Tucker, P. (2003). Shift work, safety and productivity. Occupational Medicine, 53 (2), 95-101.

Islam, S. S., Velilla, A. M., Doyle, E. J., & Ducatman, A. M. (2001). Gender Differences in Work-Related Injury/Illness: Analysis of Workers Compensation Claims. American Journal of Industrial Medicine, 39 (1), 84-91.

Kelsh, M. A., & Sahl, J. D. (1996). Sex differences in Work-related Injury Rates among Electric Utility Workers. American Journal of Epidemiology, 143 (10), 1050-1058.

Salminen, S. (2004). Have young workers more injuries than older ones? An international literature review. Journal of Safety Research, 35 (5), 513-521.

Saloniemi, A., & Salminen, S. (2010). Do fixed-term workers have a higher injury rate? Safety Science, 48 (6), 693-697.

Smith, P. M., & Mustard, C. A. (2004). Examining the associations between physical work demands and work injury rates between men and women in Ontario, 1990–2000. Occupational Enviromental Medicine, 61 (9), 750-756.

Sorensen, O. H., Hasle, P., & Bach, E. (2007). Working in smail enterprises - Is there a special risk? Safety Science, 45 (10), 1044Taiwo, O. A., Cantley, L. F., Slade, M. D., Pollack, K. M., Vegso, S., Fiellin, M. G. (2008). Sex Differences in Injury Patterns Among Workers in Heavy Manufacturing. American Journal of Epidemiology, 169 (2), 161-166.

Severity Factors of Accidents: Analysis of the Manufacturing Sector in Andalusia 2003-2008 Carrillo, Jesusa, Onieva, Luisb a Junta de Andalucía, Avenida Hytasa 14 -1, 41006 Sevilla email: jacarcas@gmail.com ; b Universidad de Sevilla, Camino de los Descubrimientos s/n, Sevilla e-mail: onieva@us.es

1. INTRODUCTION According to Occupational Health & Safety Assessment Series 18001 version 2007, the definition of “risk” is: “the combination of the likelihood of an occurrence of a hazardous event or exposure(s) and the severity of injury or ill health that may be caused by the event or exposure(s)”.

Therefore, severity analysis is a key issue for risk assessment. Several worker individual characteristics can affect occupational safety injuries proneness and in case of injury they also affect severity of injuries. In some cases, worker physical condition can be a protective barrier, in others worker differential behaviour can affect the use of protective measures. Therefore, within the same activities, tasks and jobs, personal characteristics of workers as risk factors can explain differences in the severity of the accidents. Identification of those factors can help to develop better preventive programs and to perform risk assessment.





In this paper, we analyse which worker characteristics are more likely related to severe and fatal accidents in Andalusian Manufacturing Sector from 2003 to 2008. There are previous studies that show that in Spain there are explanatory variables for severe and fatal accidents. These studies are based in a case-control approach comparing worker characteristics of slight accidents and non-slight ones (Bolívar, Daponte, López & Mateo, 2009) (Villanueva & García, 2011). Although mechanism of slight and non-slight accidents could be different, and we can not match if workers with slight and non-slight accidents were exposed to same hazards, we can control for job types (occupations) and physical activities within manufacturing sector in order to identify which personal characteristics of workers are associated with severe and fatal accidents.

Worker occupations, establishment activity and physical activities determine most of hazards at workplace and which injuries are expected. We have used National Occupation Classification (CNO-94), as an indicator of job type and NACE activity classification according to Council Regulation EEC Nº3037/90 (manufacturing sector includes NACE 15 to 37) as an indicator of enterprise’s main activity. Physical activity was also included.

The literature in this topic indicates that young workers have more injuries than older ones, but the injuries reported by young workers are less severe than accidents of senior workers (Salminen, 2004). Besides age, there are other demographic variables such as nationality and gender. Immigrants are supposed to be another risk group, but there are important differences in terms of job assignment for each country and activity (Ahonen, Benavides, & Benach, 2007).

Although female workers show less severe accidents, this can be explained in terms of their different job assignment (Smith & Mustard, 2004) (Taiwo, y otros, 2008). In fact, when analyzed at the company level, female workers have more severe accidents at the same jobs and tasks as their male mates (Kelsh & Sahl, 1996). Other factors related to labour conditions should be considered, such as contract type (Benavides, Benach, Muntaner, Delclos, Catot, & Amable, 2006) or company size (Fabiano, Currò, & Pastorino, 2004) (Sorensen, Hasle, & Bach, 2007). Small and micro companies have more sereve and fatal accidents in comparison with medium and big companies.

2. MATERIALS AND METHODS

2.1 Accident Data We considered accident reports that are collected in “Official Workplace Incident Notification Forms”, electronically collected through Delt@ information system. In Spain, it is mandatory that all accidents that result in an absence from work of one or more days must be notified. For each accident reported, we have information about worker age, months of experience in the company, occupation, and some technical circumstantial information both from workers and companies. Relapses, accidents incurred when travelling to and from work and others that did not cause any absence from work, are excluded from the study. Accident severity is classified as non-severe and severe (serious accident with long recovery decided by physicians based on expected length of absence) or fatal.

2.2 Statistical Analysis Case-control studies are used to identify factors that may contribute to show one of two possible categorical values, cases and controls. In some studies there is a selection of which cases and controls are studied, but we have included all accidents. Cases would be severe and fatal accidents and controls would be slight accidents. Odds ratio are calculated with logistic regression (Agresti, 2002) with severity as dependent variable, both univariate and multivariate. In the multivariate analysis, we adjusted odds ratio for some worker characteristics, controlling possible confounding variables.

As accidents are multicausal, we tried to control as many possible confounding variables as we can. In case-control approach, odds ratio is the ratio of the odds of having a severe accident to the odds of having a slight one. Logistic regression coefficients provide estimation for odds of each categorical value to one of them considered as a reference. If

–  –  –

they are calculated with a multivariate model, those odds are adjusted considering the rest of variables of the model are constant (Sorock & Courtney, 1997).

3. RESULTS

3.1. Univariate analysis of severity The case-control approach can provide a first insight in which worker characteristics affects severity of accidents. As shown in Table 1, severe and fatal accidents are more frequent in male workers, older workers and foreign workers.

Non-permanent workers show less severe accidents. Also we found less severity in accidents of workers in companies with less than 250 employees (small and medium enterprises). Tenure (months in the same position), age and job have no statistically significant relationship with the severity of accidents.

–  –  –

3.2. Multivariate analysis of severity As previous studies have shown, there are possible confounding variables because there are differences in task assignment depending on worker profile, and it should be controlled. We have used job, work type and physical activity to control task assignment in a multivariate analysis. We have used a logistic regression model, where severity is dependent variable with only two categorical values (slight or not slight). The adjusted model is shown in Table 2. Type of contract has no significant relationship in the adjusted model.

4. DISCUSSION As previous studies have noticed, there are many differences in terms of jobs, skills and industries where workers are employed because of the personal characteristics of workers. The purpose of this paper is show which worker characteristics are explanatory of severity of accidents even after adjusting the multivariate model.

Task assignment has been identified with job, company activity, work type and physical activity. As expected, works such as construction, installation and maintenance are hazardous jobs and the most severe accidents occurred in driving and machine operating.

Female workers have less severe accidents. To explain this result, some authors consider that even with the same working place, job and activities there is differential segregation of tasks so heavy work and hazardous activities are assigned to male workers.

Young workers have less severe accidents, possibly because of their stronger physical condition. Elder worker assignment should take into account this result and additional preventive measures should be provided. In our univariate analysis age was not significant, perhaps because of its association with work type. In fact in maintenance and services the percentage of old workers was higher.

Foreign workers are identified as another risk factor for severity. Besides the possibility of assignment segregation, foreign workers have usually worse training and they have a different understanding of safety rules. Preventive activities should focus on foreign workers to assure that they are equally trained.

Safety deals with accident risk. Accident risk depends on probability of accidents and their consequences. Part of preventive activities should be dedicated to protect workers in case of accident. Worker characteristics, according to our research, are important explanatory variables of severity of accidents in Andalusian Manufacturing Sector and preventive plans and protection measures should consider these results.

Some studies consider that slight and fatal accidents do not have the same causation path. Some accidents are more likely severe such as the falling from height or being struck by a machine. Mechanism of traumatic accidents and musculo – skeletal accidents are also different. Further research should be done of differential risk factors for each injury type.

5. ACKNOWLEDGMENTS Authors want to thank to Consejería de Empleo (Andalusia Regional Ministry of Employment), for providing assistance and constructive feedback in this study. Aggregated accident data reports and regression models are available upon request for other researchers.

6. REFERENCES Agresti, Alan (2002). Categorical Data Analysis. New Jersey: Wiley Series in Probability and Statistics.

Ahonen, E. Q., Benavides, F. G., & Benach, J. (2007). Inmigrant Populations, work and health - a systematic literature review.

Scandinavian Journal of Work Enviromental Health, 33 (2), 96-104.

Benavides, F. G., Benach, J., Muntaner, C., Delclos, G. L., Catot, N., & Amable, M. (2006). Associations between temporary employment and occupational injury: what are the mechanisms? Occupational Enviromental Medicine 63 (6), 416-421.



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