Literature DB >> 32725891

Health and safety in the Maine woods: Assemblage and baseline characteristics of a longitudinal cohort of logging workers.

Erika Scott1, Liane Hirabayashi1, Judy Graham1, Katherine Franck1, Nicole Krupa2, Paul Jenkins2.   

Abstract

BACKGROUND: Logging remains one of the most hazardous industries in the United States, despite many safety improvements made in the last decades. Currently, we know little about regional trends in health conditions of logging workers, especially in the Northeast. However, the forest products industry is a critical component of the Northeast's economy, especially in the State of Maine.
METHODS: This paper reports on the baseline data of a longitudinal cohort study involving Maine loggers, aimed to assess the health and safety of the industry.
RESULTS: Three hundred twenty-five are included in these analyses, 246 mechanized loggers, and 79 conventional. On average mechanized loggers worked longer days (11.8 vs 9.7 hours) and had longer commutes from home to the woodlot (72.6 vs 40.7 minutes) than conventional loggers. For health factors, mechanized and conventional loggers had similar responses. Nearly two-thirds of both mechanized and conventional loggers had an annual physical in the previous year, and 36.3% had seen a health specialist during that same time period. The overall work-related injury and illness rate is 6.8 of 100 workers for this cohort.
CONCLUSIONS: These factors contribute to a need to work with the community on transforming logging into a safer and healthier profession for the current workforce, as well as the workforce of the future. This study provides the basis for an appropriate intervention, in collaboration with the loggers and industry stakeholders, to improve the lives of these vital workers.
© 2020 Wiley Periodicals LLC.

Entities:  

Keywords:  Maine; forestry; health; logging; longitudinal cohort; occupational epidemiology; safety

Year:  2020        PMID: 32725891     DOI: 10.1002/ajim.23165

Source DB:  PubMed          Journal:  Am J Ind Med        ISSN: 0271-3586            Impact factor:   2.214


  2 in total

1.  The development of a machine learning algorithm to identify occupational injuries in agriculture using pre-hospital care reports.

Authors:  Erika Scott; Liane Hirabayashi; Alex Levenstein; Nicole Krupa; Paul Jenkins
Journal:  Health Inf Sci Syst       Date:  2021-07-29

2.  Using hospitalization data for injury surveillance in agriculture, forestry and fishing: a crosswalk between ICD10CM external cause of injury coding and The Occupational Injury and Illness Classification System.

Authors:  Erika Scott; Liane Hirabayashi; Judy Graham; Nicole Krupa; Paul Jenkins
Journal:  Inj Epidemiol       Date:  2021-02-15
  2 in total

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