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Examining Agricultural Workplace Micro and Macroclimate Data Using Decision Tree Analysis to Determine Heat Illness Risk
  • Published Date:
    Feb 2019
  • Source:
    J Occup Environ Med. 61(2):107-114
  • Language:
    English


Public Access Version Available on: February 01, 2020 information icon
Please check back on the date listed above.
Details:
  • Personal Authors:
  • Keywords:
  • Pubmed ID:
    30335678
  • Pubmed Central ID:
    PMC6367045
  • Description:
    This study was designed to examine the associations between regional weather data and agricultural worksite temperatures in Florida.|Florida farmworkers (n = 105) were each monitored using iButton technology paired with simultaneous data from regional weather stations. Conditional inference tree models were developed for (1) regional environmental temperatures and iButton (worksite) temperatures, and (2) regional heat index (HI) and iButton HI.|Worksite temperatures were partitioned by regional temperature at the primary node of 29.1°C. Worksite HI was partitioned at nodes of 33.0°C, 36.0°C, 37.0°C, and 40.0°C. The nodes at 33.0°C and 40.0°C mirror the National Weather Service's category entry points for "extreme caution" and "danger" regarding the risk of developing heat-related illness.|Regional weather data have the potential to provide estimations of worksite environmental conditions allowing employers to quickly implement strategies to protect workers.

  • Document Type:
    Journal Article
  • Collection(s):
    CDC Public Access
  • Funding:
    R01 OH010657/OH/NIOSH CDC HHS/United States
    T32 NR012715/NR/NINR NIH HHS/United States
  • Main Document Checksum:
  • Supporting Files:
    No Additional Files
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