Just in the wrong place...? Geographic tools for occupational injury/illness surveillance

Research output: Contribution to journalArticle

Abstract

Background: Geographic analysis is now integral to public health surveillance, but has been underused for occupational injury/illness. Methods: Mapping and spatial statistics are used to examine national county-level mean establishment Lost Workday Injury/Illness (LWDII) rates in the Occupational Safety and Health Administration (OSHA) Data Initiative (ODI), 1997-2001. The following questions are explored: Does occupational injury/illness vary geographically at the county level?; Does variation remain after accounting for industry hazard?; Where are rates higher or lower than expected? Results: The methods provide evidence of geographic variation in nonfatal occupational injury/illness rates, including after adjusting for industry hazard. Conclusions: Geographic analyses can improve intervention targeting, suggest risk factors for investigation, and make the case for targeting resources to prevention in hard-hit areas, as well as improving ongoing surveillance.

Original languageEnglish (US)
Pages (from-to)680-690
Number of pages11
JournalAmerican Journal of Industrial Medicine
Volume51
Issue number9
DOIs
StatePublished - Sep 2008

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Occupational Injuries
Occupational Diseases
Industry
Public Health Surveillance
United States Occupational Safety and Health Administration
Wounds and Injuries

Keywords

  • County-level
  • Geographic information systems
  • Geography
  • Mapping
  • Occupational health
  • Occupational injury
  • Occupational safety
  • Ranking
  • Spatial
  • Surveillance

ASJC Scopus subject areas

  • Public Health, Environmental and Occupational Health

Cite this

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title = "Just in the wrong place...?: Geographic tools for occupational injury/illness surveillance",
abstract = "Background: Geographic analysis is now integral to public health surveillance, but has been underused for occupational injury/illness. Methods: Mapping and spatial statistics are used to examine national county-level mean establishment Lost Workday Injury/Illness (LWDII) rates in the Occupational Safety and Health Administration (OSHA) Data Initiative (ODI), 1997-2001. The following questions are explored: Does occupational injury/illness vary geographically at the county level?; Does variation remain after accounting for industry hazard?; Where are rates higher or lower than expected? Results: The methods provide evidence of geographic variation in nonfatal occupational injury/illness rates, including after adjusting for industry hazard. Conclusions: Geographic analyses can improve intervention targeting, suggest risk factors for investigation, and make the case for targeting resources to prevention in hard-hit areas, as well as improving ongoing surveillance.",
keywords = "County-level, Geographic information systems, Geography, Mapping, Occupational health, Occupational injury, Occupational safety, Ranking, Spatial, Surveillance",
author = "Roni Neff and Curriero, {Frank C} and Thomas Burke",
year = "2008",
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doi = "10.1002/ajim.20611",
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volume = "51",
pages = "680--690",
journal = "American Journal of Industrial Medicine",
issn = "0271-3586",
publisher = "Wiley-Liss Inc.",
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N2 - Background: Geographic analysis is now integral to public health surveillance, but has been underused for occupational injury/illness. Methods: Mapping and spatial statistics are used to examine national county-level mean establishment Lost Workday Injury/Illness (LWDII) rates in the Occupational Safety and Health Administration (OSHA) Data Initiative (ODI), 1997-2001. The following questions are explored: Does occupational injury/illness vary geographically at the county level?; Does variation remain after accounting for industry hazard?; Where are rates higher or lower than expected? Results: The methods provide evidence of geographic variation in nonfatal occupational injury/illness rates, including after adjusting for industry hazard. Conclusions: Geographic analyses can improve intervention targeting, suggest risk factors for investigation, and make the case for targeting resources to prevention in hard-hit areas, as well as improving ongoing surveillance.

AB - Background: Geographic analysis is now integral to public health surveillance, but has been underused for occupational injury/illness. Methods: Mapping and spatial statistics are used to examine national county-level mean establishment Lost Workday Injury/Illness (LWDII) rates in the Occupational Safety and Health Administration (OSHA) Data Initiative (ODI), 1997-2001. The following questions are explored: Does occupational injury/illness vary geographically at the county level?; Does variation remain after accounting for industry hazard?; Where are rates higher or lower than expected? Results: The methods provide evidence of geographic variation in nonfatal occupational injury/illness rates, including after adjusting for industry hazard. Conclusions: Geographic analyses can improve intervention targeting, suggest risk factors for investigation, and make the case for targeting resources to prevention in hard-hit areas, as well as improving ongoing surveillance.

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