Updating the "Risk Index": A systematic review and meta-analysis of occupational injuries and work schedule characteristics. (26th November 2017)

• Record Type: Journal Article
• Authors: Fischer, Dorothee; Lombardi, David A.; Folkard, Simon; Willetts, Joanna; Christiani, David C.
• Is Part Of: Chronobiology international. Volume 34:Number 10(2017)
• Page Start: 1423
• Page End: 1438
• Publication Date: 2017-11-26
• Subjects: Occupational safety -- shift work -- injury risk -- accidents; Chronobiology -- Periodicals; Biological rhythms -- Periodicals; Circadian rhythms -- Periodicals; 571.77
• DOI: 10.1080/07420528.2017.1367305
• Languages: English
• ISSNs: 0742-0528

Abstract

ABSTRACT: Fatigue is a major risk factor for occupational 'accidents' and injuries, and involves dimensions of physical, mental, and muscular fatigue. These dimensions are largely influenced by temporal aspects of work schedules. The "Risk Index" combines four fatigue-related components of work schedules to estimate occupational 'accident' and injury risk based on empirical trends: shift type (morning, afternoon/evening, night), length and consecutive number, and on-shift rest breaks. Since its first introduction in 2004, several additional studies have been published that allow the opportunity to improve the internal and external validity of the "Risk Index". Thus, we updated the model's estimates by systematically reviewing the literature and synthesizing study results using meta-analysis. Cochrane Collaboration directives and MOOSE guidelines were followed. We conducted systematic literature searches on each model component in Medline. An inverse variance approach to meta-analysis was used to synthesize study effect sizes and estimate between-studies variance ('heterogeneity'). Meta-regression models were conducted to explain the heterogeneity using several effect modifiers, including the sample age and sex ratio. Among 3, 183 initially identified abstracts, after screening by two independent raters (95–98% agreement), 29 high-quality studies were included in the meta-analysis. The following trends were observed: Shift type . Compared to morning shifts, injury risk significantly increased on night shifts (RR = 1.36 [95%CI = 1.15–1.60], n = 14 studies), while risk was slightly elevated on afternoon/evening shifts, although non-significantly (RR = 1.12 [0.76–1.64], n = 9 studies). Meta-regressions revealed worker's age as a significant effect modifier: adolescent workers (≤ 20 y) showed a decreased risk on the afternoon/evening shift compared to both morning shifts and adult workers ( p < 0.05). Number of consecutive shifts . Compared to the first shift in a block of consecutive shifts, risk increased exponentially for morning shifts ( e.g ., 4th: RR = 1.09 [0.90–1.32]; n = 6 studies) and night shifts ( e.g ., 4th: RR = 1.36 [1.14–1.62]; n = 8 studies), while risk on afternoon/evening shifts appeared unsystematic. Shift length . Injury risk rose substantially beyond the 9th hour on duty, a trend that was mirrored when looking at shift lengths ( e.g., >12 h: RR = 1.34 [1.04–1.51], n = 3 studies). Rest breaks . Risk decreased for any rest break duration (e.g., 31–60 min: RR = 0.35 [0.29–0.43], n = 2 studies). With regards to time between breaks, risk increased with every additional half hour spent on the work task compared to the first 30 min (e.g., 90–119 min: RR = 1.62 [1.00–2.62], n = 3 studies). Rest break duration and interval seem to interact such that with increasing duration, the time between breaks becomes irrelevant. The updated "Risk Index" . All four components were combined to form the updated model and the relative risk values estimated for a variety of work schedules. The resulting "Risk Map" shows regions of highest risk when rest breaks are not taken frequently enough ( i.e . <4 h) or are too short ( i.e . <30 min), when shift length exceeds 11 h, and when work takes place during the night (particularly for >3 consecutive night shifts). The "Risk Index" is proposed as an empirical model to predict occupational 'accident' and injury risk based on the most recent data in the field, and can serve as a tool to evaluate hazards and maximize safety across different work schedules.