Characterizing the Distribution of Shift Domains by Demographics and Shift Schedule in the American Manufacturing Cohort

Details

• Personal Author:
  Bradshaw PT ; Costello S ; Cullen MR ; Eisen EA ; Ferguson JM
• Description:
  Introduction: The American Manufacturing Cohort is the largest source of time-registry data on American workers available for research. In this cohort of 23,096 workers with over 23 million shifts, between 2003-2013, we describe the distribution of shift work domains relevant for circadian rhythm disruption by demographics and shift schedules. Methods: We defined the prevalence of shift domains using algorithms for shift type (e.g. day vs. night), shift duration (e.g. shift >/=13 hours), shift intensity (e.g. quick return (<11 hours between shifts) and consecutive work), rotational direction (forward, backward, flipped), and social aspects (e.g. weekend work). Person-years with >/=150 shifts/year were classified into shift schedules by combinations of permanent and rotating day, evening, and night. Shift domains distributions were examined by shift schedules and demographics, and were cross-classified in a matrix to examine co-occurrence. Results: Shifts were classified into morning (6%), day (50%), evening (16%), and night (28%). Approximately 60% of shifts may cause circadian rhythm disruption as they were non-day shifts or day shifts with a quick return, a rotation, or were 13 hours or longer. One third of quick returns were due to a backwards rotation while 42% were attributable to a long shift. Approximately 48% of person-years were non-rotating: day (32%), night (12%), evening (4%), day/evening (11%), day/night (24%), evening/night (4%) and day/evening/night (13%). Men were more likely to work rotational schedules (54.9% vs. 41.4%). White workers worked permanent day shifts most often, while racial minorities worked more day/night schedules. Older workers worked more permanent day and fewer day/evening/night schedules. Distribution of shift domains such as quick returns, shift length, and rotations varied by schedule type.Conclusions: We identified variations in the joint distributions of shift domains by shift schedules, demographics, and schedule type. These shift domains are important to identify, as they may impact circadian rhythm disruption. [Description provided by NIOSH]
• Subjects:
  Circadian Rhythm Demography Manufacturing And Industrial Facilities Occupational Health Safety Shift Work Schedule
• Keywords:
  Biological Rhythms Circadian Rhythms Demographic Characteristics Manufacturing Shift Work Shift Workers Work Schedules
• ISSN:
  1984-0063
• Document Type:
  Text
• Funding:
  Grant
• Genre:
  Abstract or Summary
• Place as Subject:
  California ; Idaho ; OSHA Region 10 ; OSHA Region 9
• CIO:
  National Institute for Occupational Safety and Health (NIOSH)
• Topic:
  Workplace Safety & Health
• Location:
  North America
• Pages in Document:
  10
• Volume:
  12
• NIOSHTIC Number:
  nn:20057985
• Citation:
  Sleep Sci 2019 Aug; 12(Suppl 3):10
• Federal Fiscal Year:
  2019
• NORA Priority Area:
  Manufacturing
• Performing Organization:
  Stanford University
• Peer Reviewed:
  True
• Start Date:
  20110901
• Source Full Name:
  Sleep Science
• Supplement:
  3
• End Date:
  20200831
• Collection(s):
  National Institute for Occupational Safety and Health
• Main Document Checksum:
  urn:sha-512:360b76439ee050b3072321473fa0615f96e7b7bb8338fbe35fd89bf2801ee74970fc134d35c718932555320e0824fdef143d15455e9873685f7f8a031e57dc4b
• Download URL:
  https://stacks.cdc.gov/view/cdc/215179/cdc_215179_DS1.pdf
• File Type:
  [PDF - 179.85 KB ]