Fatigue risk index for shift work: how the numbers add up
Updated October 8, 2026 · 3 min read
A fatigue risk index scores a work schedule by the extra injury risk its features carry. In a 2006 index built from pooled industrial studies, a night shift carried 27.9% more risk than a morning shift, the 4th night in a row 36% more than the 1st, and a 12-hour shift 27.5% more than an 8-hour shift.
The trends behind the index
The 2006 paper pooled studies of injuries and accidents at work that could be compared fairly across shifts. It found four consistent trends.
- Morning
- 1.00
- Afternoon
- 1.152
- Night
- 1.279
Time of day: risk was 15.2% higher on afternoon shifts and 27.9% higher on night shifts than on morning shifts.
Successive night shifts
- 1st night
- 1.00
- 2nd night
- 1.06
- 3rd night
- 1.17
- 4th night
- 1.36
Successive day shifts
- 1st day
- 1.00
- 2nd day
- 1.02
- 3rd day
- 1.07
- 4th day
- 1.17
Shifts in a row: risk was 6% higher on the 2nd night, 17% on the 3rd and 36% on the 4th. Over day shifts the rise was smaller and less consistent: 2%, 7% and 17%.
- 8 hours
- 1.00
- 10 hours
- 1.13
- 12 hours
- 1.275
Shift length: little change between about 4 and 9 hours, then 13.0% higher for 10 hours and 27.5% higher for 12. A 2006 trade article rounded the 12-hour figure to "almost 30 percent".
Breaks matter too. In the one study of breaks the paper found, injury risk doubled from the first to the last 30 minutes of a 2-hour stretch between breaks.
Worked example: four ways to work 48 hours
The paper adds up the changes in risk and compares whole weeks with a standard week of five 8-hour day shifts. Its estimates for 48 hours a week:
| Shifts | Length | Type | Risk vs standard week |
|---|---|---|---|
| 6 | 8 h | Day | +3% |
| 4 | 12 h | Day | +25% |
| 6 | 8 h | Night | +41% |
| 4 | 12 h | Night | +55% |
All four weeks have the same hours. The gap holds at 60 hours a week: six 10-hour shifts come out 16% higher on days and 54% on nights, and five 12-hour shifts 28% and 62%.
The per-shift version in Capillary
Capillary's risk calculator and Analytics score each shift instead of each week, with the paper's own parts added the way its formula adds them: the first shift of its type (day 1.00, night 1.06), the change for its place in the run and the change for its length, against a first 8-hour day shift (1.00). The 4th 12-hour night in a row scores 1.06 + 0.36 + 0.275 = 1.70. Shifts at 1.30 or more are marked.
Limits
- The data on shift timing and runs come from industrial sites such as mines, steel mills, docks and engineering plants, and most incidents were minor.
- Its authors said the index needed more validation and could not yet be recommended for general use.
- Rest between shifts is not in it. Check quick returns separately.
- Few studies ran past four nights in a row, so the 5th and later nights are uncertain. Capillary continues the trend in a straight line for them, as the paper does.
Common questions
- Is a risk index the same as a fatigue risk management system?
- No. An index is one tool. Airlines use sleepiness models such as the three-process model to assess rosters inside wider fatigue risk management systems.
- Does 1.30 mean a 30% chance of injury?
- No. It means about 30% more injuries and accidents than on the reference shift in the pooled studies. It is a relative rate, not a probability for one person or one shift.
- Why do nights get worse across a run?
- Short day sleep is a likely part of it. The 2006 paper links night-shift risk partly to the short day sleeps between nights, and the alertness model predicts lower lows on the 2nd and 3rd nights when day sleep lasts 4.5 hours.
See your own shifts this way.
Bring in your schedule from any scheduling app with its calendar link. Capillary charts your hours, nights, quick returns and hardest shifts. Only you can see it.
Sources
- Folkard S, Lombardi DA. Modeling the impact of the components of long work hours on injuries and "accidents". Am J Ind Med 2006
- Brogmus G, Maynard W. Safer shift work through more effective scheduling. Occupational Health & Safety, December 2006
- Åkerstedt T, Folkard S, Portin C. Predictions from the three-process model of alertness. Aviat Space Environ Med 2004
- Ingre M, et al. Validating and extending the three process model of alertness in airline operations. PLoS One 2014