Modeling fatal injury rates using Poisson regression: A case study of workers in agriculture, forestry, and fishing
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Cited by (41)
Comparative occupational health risk between tobacco and paddy farming people in Bangladesh
2022, SSM - Mental HealthStatistical Methods
2021, Statistical MethodsHeinrich's pyramid and occupational safety: A statistical validation methodology
2018, Safety ScienceCitation Excerpt :The Poisson model and its extension, the Poisson-gamma model, have been used in different contexts in the literature to represent counting processes. The Poisson regression model has been applied to occupational accidents in the mining industry (Mallick and Mukherjee, 1996) as well as to other industries (Bailer et al., 1997; Boyd and Radson, 1999; Richardson et al., 2004). The Poisson model has also been used to measure the impact of interventions on the safety of working conditions (Frome et al., 1997; Smitha et al., 2001; Wing et al., 1991).
Urban green spaces activities: A preparatory groundwork for a safety management system
2016, Journal of Safety ResearchCitation Excerpt :The current scientific literature about risk taking and accidents frequency among “green operators” is poor in terms of quantitative and qualitative analysis. In most of the cases, data on injuries emerge from agriculture and forestry studies (Bailer, Reed, & Stayner, 1997; Colantoni et al., 2012; Lilley, Feyer, & Kirk, 2002; Lindroos, Aspman, Lidestav, & Neely, 2008; Lindroos & Burström, 2010; Lundqvist & Gustafsson, 1992; Mann, Pouta, Gentin, & Jensen, 2010; Marucci, Pagniello, Monarca, Colantoni, & Biondi, 2012; Monarca et al., 2009; Montorselli et al., 2010; Neely & Wilhelmson, 2006; Potočnik, Pentek, & Poje, 2009; Solomon, Poole, Palmer, & Coggon, 2007; Suchomel & Belanová, 2009; Thelin, 2002). According to Solomon and his work on safety in agriculture in the UK (2002), the most common fatal accidents are those involving machinery, works at height, and electrocution whereas non-fatal injuries are due to manual handling.
Occupational injury and accident research: A comprehensive review
2012, Safety ScienceCitation Excerpt :Such models assume differential injury liability across individuals. Poisson regression models (Bailer et al., 1997) are useful in adjusting injury rates for one or more explanatory variables (for example, age, experience and occupation). Conditional probability-based models capture the risk of injury through three-phase mechanism, namely pre-injury, injury and post-injury phases (Kjellen, 1984b,c).
A methodology for evaluation and monitoring of recurring hazards in underground coal mining
2011, Safety ScienceCitation Excerpt :One of them is that the risk assessment methodology fails to link hazards with risk controls. Several authors have presented statistical modeling of accident/injury data (e.g., Bennett and Passmore, 1984a,b, 1985; Bailer et al., 1997; Boyd and Radson, 1999; Maiti and Bhattacherjee, 1999; Maiti et al., 2001; Cuny and Lejeune, 2003; Bajpayee et al., 2004; Chang, 2004; Duzgun and Einstein, 2004; Sari et al., 2004; Coleman and Kerkering, 2007). The statistical distributions and methods that are predominantly used are Poisson, exponential, Weibull, Gamma, and beta distributions and loglinear, logistic, and Poisson regression models, respectively.
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John Bailer, Ph.D., earned a doctorate in Biostatistics with an area of concentration in environmental health. Since 1988, he has been a professor in the Department of Mathematics and Statistics at Miami University in Oxford, Ohio. Since 1990, he has worked in conjunction with risk assessment researchers at the National Institute for Occupational Safety and Health. Dr. Bailer has published widely in the areas of occupational and environmental risk estimation with special interests in the design and analysis of occupational and environmental research studies.
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Leslie Stayner, Ph.D., received his doctorate in Epidemiology from the University of North Carolina in 1989, and a Masters Degree in Epidemiology from the Harvard School of Public Health in 1980. He has been working with the National Institute for Occupational Safety and Health for approximately 15 years, originally involved in the conduct of industry-wide research projects, and is currently involved in managing their Risk Assessment Program.
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Larry Reed, M.S., earned a Master's degrees in Preventive Medicine and in Industrial and Systems Engineering. He has been employed at the National Institute for Occupational Safety and Health since 1977. In his current position, Mr. Reed manages the development of NIOSH policy statements to regulatory agencies and document development including criteria documents, alerts and hazard controls. Prior to these responsibilities, he worked in the research areas of personal protective equipment, industrial hygiene, and engineering control technology. He also teaches mathematics on a part-time basis in the College of Evening and Continuing Education at the University of Cincinnati.