Data Bulletin: Musculoskeletal Disorder (MSD) Trends in Construction

Details

• Personal Author:
  Harris, William ; Dufoe, Derek ; Brooks, Raina D. ; Trueblood, Amber B.
• Description:
  This issue examines musculoskeletal disorders (MSDs) in construction, including MSDs by industry, self-reported pain, prescription analgesic and/ or opioid use by industry, demographics, and other characteristics. Musculoskeletal disorders (MSDs) are a collection of injuries and/or sources of pain that occur in joints, ligaments, muscles, nerves, tendons and other parts of the body, particularly in the limbs, neck, or back. Construction workers are often exposed to tasks and work environments that leave them at greater risk of these injuries than workers in general. These injuries can reduce workers' productivity, shorten their careers, and diminish their quality of life. They also create a financial burden for employers, workers, and their families, costing the U.S. construction industry over $700 million in 2023. Prior research has shown declines in the number and rate of MSDs over time, but construction still has rates higher than all industries combined. Additionally, the presence of an MSD is associated with increased opioid use among construction workers, a major concern given the industry has one of the highest overdose rates. This issue examines musculoskeletal disorders (MSDs) in construction, including the number and impact of these injuries, self-reported pain, prescription analgesic and/or opioid use by industry, demographics, and other characteristics. MSD injury data include nonfatal injuries resulting in days away from work (DAFW) and comes from the U.S. Bureau of Labor Statistics (BLS) Survey of Occupational Injuries and Illnesses (SOII). Due to SOII data changing from annual to biennial estimates in 2021, data is shown for two-year periods. It is important to note that SOII data has been found to underreport nonfatal injuries, affecting the accuracy of the count of MSDs. Data on self-reported worker pain and injury come from the Centers for Disease Control (CDC) National Health Interview Survey (NHIS), while data for prescription analgesic use come from the Medical Expenditure Panel Survey (MEPS) downloaded through IPUMS. Data for rate calculations shown were obtained using the Current Population Survey (CPS) and were calculated per 10,000 full-time equivalents (FTEs) for chart 1; chart 4 uses rates provided by BLS. Description provided by NIOSH
• Subjects:
  • Construction
  • Musculoskeletal Diseases
  • Musculoskeletal System
  • Occupational Health
  • Safety
• Keywords:
  • Construction workers
  • Injuries
  • Musculoskeletal disorders
  • MSD
  • Costs
  • Opioids
  • Lost work days
  • Repetitive strain injury
  • RSI
  • Health care
• Series:
  CPWR - Center for Construction Research and Training Publications
• Subseries:
  Data Bulletin
• Document Type:
  Text
• Funding:
  Cooperative Agreement
• Genre:
  Report
• Place as Subject:
  Maryland ; Philadelphia Region OSHA
• CIO:
  National Institute for Occupational Safety and Health (NIOSH)
• Topic:
  Workplace Safety & Health
• Location:
  North America
• Pages in Document:
  7 pdf pages
• NIOSHTIC Number:
  nn:20071790
• Citation:
  CPWR Data Bulletin. Silver Spring, MD: CPWR-The Center for Construction Research and Training, 2025 Jun; :1-7
• Contact Point Address:
  Data Center, CPWR-The Center for Construction Research and Training, 8484 Georgia Avenue, Suite 1000, Silver Spring, MD 20910
• Email:
  datacenter@cpwr.com
• Federal Fiscal Year:
  2025
• NORA Priority Area:
  Construction
• Performing Organization:
  CPWR - The Center for Construction Research and Training, Silver Spring, Maryland
• Peer Reviewed:
  False
• Start Date:
  2024/09/01
• End Date:
  2029/08/31
• Download URL:
  https://stacks.cdc.gov/view/cdc/260014/cdc_260014_DS1.pdf
• File Type:
  [PDF - 870.77 KB]
• Collection(s):
  National Institute for Occupational Safety and Health
• Main Document Checksum:
  urn:sha-512:b5a23cc228afdb0ac0ad54712feec1e2fd59cdcbab81c22bfcd80fbb2d6155c56557685e077b844d4a3935e8eb635a16e735de4ab45f785204c94925c80df2fa