IN THE WRONG PLACE?: GEOGRAPHIC VARIATION IN U.S. OCCUPATIONAL INJURY / ILLNESS RATES
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Date
2007-05-07T17:35:49Z
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Johns Hopkins University
Abstract
BACKGROUND: Around the world and across U.S. counties, workers and businesses
operate in a diverse landscape of demographics, economy, culture, policy and industry.
This dissertation presents four papers exploring geographic variation in U.S. occupational
injury/illness rates.
METHODS: The literature on geographic variation in occupational injury/illness is
reviewed and categorized. Three papers examine geographic variation in the OSHA Data
Initiative (ODI), 1997-2001, a database of high injury/illness industries. The first presents
surveillance tools including mapping, spatial statistics, and ranking. The second uses
multilevel regression to examine social determinants of county-level variation in lost
workday injury/illness rates (LWDII). Finally, a case study of the meat processing
industry uses mapping and regression to explore risk factors associated with both
establishment location and high-LWDII establishments.
RESULTS: 1) There is a small, uncoordinated literature using geographic methods to
examine occupational injury/illness. 2) There is geographic variation in occupational
injury/illness rates. The sample mean LWDII was 7.22 per 100 workers (county range: 0,
25.2). The five highest rate states were Vermont (9.77), West Virginia (9.76), Michigan
(9.67), Maine (9.54) and Kentucky (8.99). Rates were low throughout the South.
3) Geographic variation was associated with social risk factors. In regressions, high rates
were positively associated with county poverty, percent Caucasian, unionization, strong
safety net, and industry hazard. Meat establishment locations were associated with county
percent African American, non-college educated, longterm job gain, and urbanicity, plus
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state-level anti-union policy, medium union membership, and slightly reduced OSHA
inspections. By contrast, high-LWDII meat establishments were associated with county
percent Caucasian, low income, high school education, and longterm job loss. 4) There is
suggestive evidence of substantial, biased underreporting in the ODI.
CONCLUSIONS: Explanations for the findings are discussed. Recommendations focus
on addressing underreporting, generating more county-level occupational injury/illness
data, promoting county-level surveillance, increasing geographic research in occupational
injury/illness, piloting programs for geographic targeting, and changing business and
worker incentives and capacity for prevention.
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Keywords
Public health, Occupational health, Surveillance, Geography, Health policy, Meat industry