Length of time spent working on a commercial construction site and the associations with worker characteristics

Am J Ind Med. 2015 Sep;58(9):964-73. doi: 10.1002/ajim.22461. Epub 2015 Jun 29.

Abstract

Background: Construction workers move frequently from jobsite to jobsite, yet little is documented about length of stay on-site and associations with worker characteristics.

Method: Using cross-sectional data, we investigated associations between worker characteristics (including trade and musculoskeletal pain) and length of stay on-site (dichotomized as < 1 month, n = 554, and ≥ 1 month, n = 435).

Results: Approximately, 56% of workers remained on the worksite for at least 1 month. Length of stay was significantly associated with workers' race/ethnicity, union status, title, trade, and musculoskeletal pain (P-values < 0.05). Trades associated with longer length of stay included pipefitters and plumbers. Trades associated with shorter length of stay included operators and piledrivers. Workers with single-location pain had 2.21 times (95%CI: 1.52, 3.19) the odds of being short-term versus long-term, adjusting for trade, title, and race/ethnicity.

Conclusion: The length of stay and associated characteristics provide important insight into how workers come and go on construction sites and the methodological challenges associated with traditional intervention evaluations.

Keywords: construction; dynamic work environment; length of time on-site; worker characteristics.

Publication types

  • Research Support, N.I.H., Extramural
  • Research Support, Non-U.S. Gov't
  • Research Support, U.S. Gov't, P.H.S.

MeSH terms

  • Adult
  • Construction Industry / statistics & numerical data*
  • Cross-Sectional Studies
  • Employment / statistics & numerical data*
  • Ethnicity / statistics & numerical data
  • Female
  • Humans
  • Labor Unions / statistics & numerical data
  • Male
  • Middle Aged
  • Musculoskeletal Pain / epidemiology
  • Musculoskeletal Pain / etiology
  • Occupational Diseases / epidemiology
  • Occupational Diseases / etiology
  • Odds Ratio
  • Racial Groups / statistics & numerical data
  • Time Factors
  • Work
  • Workplace / statistics & numerical data*