Elise Lagerstrom1, Sheryl Magzamen2, Lorann Stallones3, David Gilkey4, John Rosecrance2. 1. Department of Environmental and Occupational Health Sciences, Colorado State University, Fort Collins, CO, United States. Electronic address: lagerstrome@gmail.com. 2. Department of Environmental and Occupational Health Sciences, Colorado State University, Fort Collins, CO, United States; Colorado School of Public Health, Colorado State University, Fort Collins, CO, United States. 3. Department of Psychology, Colorado State University, Fort Collins, CO, United States; Colorado School of Public Health, Colorado State University, Fort Collins, CO, United States. 4. Department of Environmental and Occupational Health Sciences, Colorado State University, Fort Collins, CO, United States.
Abstract
INTRODUCTION: Although there are hundreds of ATV-related deaths each year in the United States, contributing factors have not been clearly identified. The purpose of this study was to investigate associations between factors contributing to ATV fatalities using the agent-host-environment epidemiological triangle. METHOD: Incident reports of ATV fatalities occurring between 2011 and 2013 were obtained from the United States Consumer Product Safety Commission (CPSC). Narrative reports included details of the decedent and a description of the ATV crash. A chi-square automatic interaction detector (CHAID) analysis was performed for three major risk factors representing each facet of the epidemiologic triangle: helmet use (host), type of crash (agent), and location where death occurred (environment). The output of the CHAID analysis is a classification tree that models the relationship between the predictor variables and a single outcome variable. RESULTS: A total of 1193 ATV fatalities were reported to the CPSC during the 3-year study period. In cases with known helmet and/or drug and alcohol use status, descriptive statistics indicated helmets were not worn in 88% of fatalities and use of alcohol or drugs was present in 84% of fatalities. Reoccurring factors within the CHAID analysis included age, helmet use, geographic region of the country, and location (e.g., farm, street, home, etc.) at the time of death. Within the three CHAID models, there were seven significant partitions related to host, one related to agent, and eight related to the environment. CONCLUSIONS: This research provides a model for understanding the relationship between risk factors and fatalities. The combination of the CHAID analysis method and the epidemiologic triangle allows for visualization of the interaction between host-agent-environment factors and fatalities. PRACTICAL APPLICATIONS: By modeling and characterizing risk factors associated with ATV fatalities, future work can focus on developing solutions targeted to specific factions of ATV users.
INTRODUCTION: Although there are hundreds of ATV-related deaths each year in the United States, contributing factors have not been clearly identified. The purpose of this study was to investigate associations between factors contributing to ATV fatalities using the agent-host-environment epidemiological triangle. METHOD: Incident reports of ATV fatalities occurring between 2011 and 2013 were obtained from the United States Consumer Product Safety Commission (CPSC). Narrative reports included details of the decedent and a description of the ATV crash. A chi-square automatic interaction detector (CHAID) analysis was performed for three major risk factors representing each facet of the epidemiologic triangle: helmet use (host), type of crash (agent), and location where death occurred (environment). The output of the CHAID analysis is a classification tree that models the relationship between the predictor variables and a single outcome variable. RESULTS: A total of 1193 ATV fatalities were reported to the CPSC during the 3-year study period. In cases with known helmet and/or drug and alcohol use status, descriptive statistics indicated helmets were not worn in 88% of fatalities and use of alcohol or drugs was present in 84% of fatalities. Reoccurring factors within the CHAID analysis included age, helmet use, geographic region of the country, and location (e.g., farm, street, home, etc.) at the time of death. Within the three CHAID models, there were seven significant partitions related to host, one related to agent, and eight related to the environment. CONCLUSIONS: This research provides a model for understanding the relationship between risk factors and fatalities. The combination of the CHAID analysis method and the epidemiologic triangle allows for visualization of the interaction between host-agent-environment factors and fatalities. PRACTICAL APPLICATIONS: By modeling and characterizing risk factors associated with ATV fatalities, future work can focus on developing solutions targeted to specific factions of ATV users.
Authors: Preetha Menon; Mohamed El-Sadig; Moien AB Khan; Linda Östlundh; Marwan El-Deyarbi; Rami H Al-Rifai; Michal Grivna Journal: BMJ Open Date: 2021-04-05 Impact factor: 2.692
Authors: Kelly L Vittetoe; Jackson H Allen; Purnima Unni; Katlyn G McKay; Aaron M Yengo-Kahn; Owais Ghani; Pradeep Mummidi; Amber L Greeno; Christopher M Bonfield; Harold N Bo Lovvorn Journal: Trauma Surg Acute Care Open Date: 2022-03-16