Recurrent injury event-time analysis.

Public health decision making based on data sources that are characterized by a lack of independence and other complicating factors requires the development of innovative statistical techniques. Studies of injuries in occupational cohorts require methods to account for recurrent injuries to workers over time and the temporary removal of workers from the 'risk set' while recuperating. In this study, the times until injury events are modelled in an occupational cohort of employees in a large power utility company where employees are susceptible to recurrent events. The injury history over a ten-year period is used to compare the hazards of specific jobs, adjusted for age when first hired, and race/ethnicity differences. Subject-specific random effects and multiple event-times are accommodated through the application of frailty models which characterize the dependence of recurrent events over time. The counting process formulation of the proportional hazards regression model is used to estimate the effects of covariates for subjects with discontinuous intervals of risk. In this application, subjects are not at risk of injury during recovery periods or other illness, changes in jobs, or other reasons. Previous applications of proportional hazards regression in frailty models have not needed to account for the changing composition of the risk set which is required to adequately model occupational injury data. Published in 1999 by John Wiley & Sons, Ltd. This article is a US Government work and is in the public domain in the United States.

Fatal occupational injuries associated with forklifts, United States, 1980-1994.

BACKGROUND: This paper describes deaths of American workers involving forklifts during the 15-year period from January 1, 1980 to December 31, 1994. METHODS: Death certificate data were obtained from the National Institute for Occupational Safety and Health's (NIOSH's) National Traumatic Occupational Fatality (NTOF) surveillance system. The narrative fields on the death certificate were searched for keywords indicating that a powered industrial vehicle (PIV) or forklift was involved in the death. This study examined the circumstances of the forklift-related deaths, the nature of the injury, and the decedent's age, gender, race, occupation, and industry. Average annual employment data from the Bureau of the Census were used to calculate civilian fatality rates by age, gender, industry, and occupation. RESULTS: A total of 1,021 deaths were identified. The average age of the fatally injured worker was 38 years; the 1,021 forklift-related deaths resulted in a total of 27,505 years of productive life lost. The three most common circumstances of the fatalities were forklift overturns (22%), pedestrian struck by forklifts (20%), and worker crushed by forklift (16%). The greatest proportion of the fatalities (37%) occurred to workers in Manufacturing, followed by Transportation, Communication, and Public Utilities, (TCPU), (17%), Construction (16%), Wholesale Trade (8%), and Agriculture, Forestry, and Fishing (AFF) (7%). The highest forklift-related fatality rates per ten million workers occurred among transport operatives (34.0) and laborers (32.0). CONCLUSIONS: Many of the fatalities resulting from forklift "overturns" might have been prevented if the operator had been restrained with a lap/shoulder belt. Careful consideration should be given to separating pedestrian and forklift traffic, and restricting the use of forklifts near time clocks, exits, and other areas where large numbers of pedestrians pass through an area in a short time. Additionally, systematic traffic control, including rules for pedestrian and forklift traffic, will be necessary to reduce the enormous injury and death toll associated with forklifts. Am. J. Ind. Med. 36:504-512, 1999. Published 1999 Wiley-Liss, Inc.

A descriptive analysis of nonfatal occupational injuries to older workers, using a national probability sample of hospital emergency departments.

An estimated 136,985 nonfatal, work-related injuries to workers 55 years of age and older were presented for treatment in hospital emergency departments across the United States during 1993. Men accounted for 63.7% of the injuries and had an injury rate of 1.06 per 100 workers, compared with a rate of 0.76 among women. Among the oldest workers (65+ years), injuries were more likely to be fractures or dislocations, to result from falls on the same level, or to involve hospitalization. The services industry had the largest number of injuries (31.9%), whereas the highest injury rate occurred in the agriculture/forestry/fishing industry (1.50 per 100 workers). The types of injuries most frequently requiring hospitalization were fractures or dislocations that resulted from a fall. Because older workers' employment demographics and injury patterns differ from the remainder of the labor force, interventions need to be developed which are specific to the workplace for this older working population.

Effect of recall on reporting of at-work injuries.

Difficulty with recall of injuries can result in underestimates of injury incidence and bias in risk estimates in surveys based on self-reports. This study examined the effect of recall on estimates of at-work injury obtained from the 1988 Occupational Health Supplement of the National Health Interview Survey, which used a 12-month reference period for injury reporting. Estimates of annual injury incidence were obtained from recall intervals of increasing time between injury date and interview date. A linear model was fitted to these data to estimate the incidence rate expected if all respondents had been interviewed within 4 weeks of injury. The incidence rate for all at-work injuries adjusted for recall was 32 percent higher than the unadjusted rate. The percent increase in the estimates differed among demographic groups and by injury severity. Rate ratios comparing risk of injury between some demographic groups were also affected by adjustment for recall. A 12-month or longer reference period is frequently used in injury surveys in order to obtain an adequate number of injuries for analysis. A shorter reference period is desirable to provide more accurate estimates; however this necessitates increasing the size of the sample used in the survey. This increased cost must be balanced against the need for accurate information on injury.

Occupational injury deaths of 16- and 17-year-olds in the United States.

Data from the National Traumatic Occupational Fatalities surveillance system were used to analyze occupational injury deaths of civilian 16- and 17-year-olds during 1980 through 1989. There were 670 deaths; the rate was 5.11 per 100,000 full-time equivalent workers. The leading causes of death were incidents involving motor vehicles and machines, electrocution, and homicide. Workers 16 and 17 years old appear to be at greater risk than adults for occupational death by electrocution, suffocation, drowning, poisoning, and natural and environmental factors. Improved enforcement of and compliance with federal child labor laws, evaluation of the appropriateness of currently permitted activities, and education are encouraged.

Occupational injury deaths in Alaska's fishing industry, 1980 through 1988.

OBJECTIVES: Studies from other countries have identified fishing as a hazardous industry, but little is known about occupational injury mortality related to fishing in the United States. Alaska was chosen for this study because approximately 45,000 people annually participate in Alaska's fishing industry and fishing is thought to be a major contributor to occupational injury mortality in the state. METHODS: Work-related injury deaths in Alaska's fishing industry were identified by means of death certificates and US Coast Guard mortality data. Fatality rates were calculated by using average annual fishing industry employment estimates. RESULTS: The 5-year average annual fishing-related fatality rate was 414.6 per 100,000 fishermen. The majority of the decedents were Caucasian men who drowned while fishing. CONCLUSIONS: This study emphasizes that fishing is a dangerous industry in Alaska and demonstrates the benefit of using multiple data sources to identify fishing-related deaths in the state.