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APHA Scientific Session and Event Listing

Recorded presentation

Roni Neff, SM¹, Thomas A. Burke, MPH, PhD¹, and Frank C. Curriero, PhD². (1) Department of Health Policy and Management, Johns Hopkins Bloomberg School of Public Health, 624 North Broadway, Room 511A, Baltimore, MD 21205, 443-287-6533, rneff@jhsph.edu, (2) Department of Environmental Health Sciences and Department of Biostatistics, Johns Hopkins Bloomberg School of Public Health, 615 North Wolfe Street, Baltimore, MD 21205

BACKGROUND: Across US counties there is a diverse landscape of economic, demographic, policy, social, and health conditions, and of industry. These local conditions may in turn affect business and worker risks, incentives, and capacity for safe work. This study builds on previous descriptive work by the authors to present results from a national multivariate regression analysis of county-level predictors of occupational injury and illness. METHODS: Occupational injury/illness rates are drawn from the OSHA Data Initiative, 1997-2001, and social risk factors are from the US Census 2000 and other sources. Data were mapped and described at the county level, and geographic and multilevel regression analytic tools were used. RESULTS: Preliminary findings suggest that rates were especially low in counties with high percent African American. After controlling for race, other positively associated variables included segregation, unemployment, household income, and percent English-speaking. DISCUSSION: These potentially counterintuitive findings are discussed, and interpretations including underreporting are discussed. Geographic analysis has moved into the mainstream of public health and environmental tools, but few studies have examined geographic risk factors for occupational injury/illness. This national study helps enrich understanding of contextual contributions to risk, and supports the need for further geographic analysis in occupational injury and illness surveillance and research.

Learning Objectives: At the conclusion of the session, the participant in this session will be able to

• Discuss county-level predictors of occupational injury and illness.
• Discuss the benefits of going beyond the individual and workplace level to consider contextual risk factors.
• Recognize tools for geographic analysis.
• Discuss some strengths and limitations of the OSHA Data Initiative data set.

Keywords: Geographic Information Systems, Workplace Safety

Presenting author's disclosure statement:

Any relevant financial relationships? No

Recorded presentation