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Impact of Sleep Deprivation on Agricultural Injury Incidents

Impact of Sleep Deprivation on Agricultural Injury Incidents. James M. Gregory Professor Civil Engineering Texas Tech University Retiring and moving to Shreveport, LA in May 2007. Education Objectives. Overview the general nature of sleep. Learn how age affects sleep need.

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Impact of Sleep Deprivation on Agricultural Injury Incidents

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  1. Impact of Sleep Deprivation on Agricultural Injury Incidents James M. Gregory Professor Civil Engineering Texas Tech University Retiring and moving to Shreveport, LA in May 2007

  2. Education Objectives • Overview the general nature of sleep. • Learn how age affects sleep need. • Present a mathematical model to understand the nature of risks for accidents. • Illustrate the use of SLEEP Model to evaluate risk and countermeasures for risk associated with sleep management.

  3. Sleep • Are you getting enough? • Do you know the consequences of poor sleep management? • Do your employees understand sleep management well enough to work safely?

  4. How much sleep do you need?

  5. Nature of Sleep REM Sleep 2 1 3/4 http://www.holistic-online.com/Remedies/Sleep/sleep_stages-1-4NREM.htm

  6. Importance of Sleep Switch to deeper sleep Delta: deep sleep (Stage 3 and Stage 4) REM (Rapid Eye Movement) Sleep Reference for waves http://www.holistic-online.com/Remedies/Sleep/sleep_stages-1-4NREM.htm

  7. Health • REM sleep associates with mental activity. • Delta sleep associates with growth, growth hormone, and exercise. • Loss of REM sleep reduces mental alertness and makes people irritable! • Loss of either REM or Delta results in insulin response similar to an old person even when the person is young! • Insulin response relates to diabetes and heart disease!

  8. Conclusion and Warning • Sleep management affects short-term body functions • Too little or too much sleep over a period of time leads to increased medical risks • Time of day and build up of sleep debt affects the time before one falls asleep.

  9. Injury Risk Theory where R = increased risk of injury, C = calibration coefficient (injuries/time), effi = efficiency of performance during time period i, i = a counter of time periods, di = duration of time period, N = total number of time periods at which efficiency is below normal, and effni = efficiency of normal performance without alcohol or sleep debt. If effi = effni, then R=0 Risk calculation depends on reference as well as current activity.

  10. Injury Risk Theory Increase fraction = Odds ratio – 1 SLEEP Model is not designed to compare risks for different activities. If you drive a tractor for 8 hours instead of 4 hours, it does not increase the risk or odds ratio. It only computes the increase in risk or odds ratio associated with the reduced performance due to use of alcohol or loss in performance because of sleep debt.

  11. Measurement Problems: Alcohol • Duration goes up with number of drinks. • Impairment goes up with number of drinks. • Risk generally goes up with square of number of drinks. • Can usually survey number of drinks. • Rate of drinking, however, complicates results. • Body weight affects blood alcohol level. • Can measure blood alcohol level either dead or alive. • Timing of measurement does affect results, especially early in process. • Gender in addition to body mass has minor effects. • Interactions can affect results: sleep, medications, etc.

  12. Measurement Problems: Sleep • Duration of sleep debt can be as long as 4 to 6 weeks. • Impairment depends on time of day as well as amount of sleep debt. • Impairment depends on amount of sleep night before as well as total sleep debt. • Impairment depends on use of counter measures, such as caffeine. • Impairment depends on external stimulation: talking, radio, cold air, type of activity. • Pilots stayed awake during dog fights in WW2 and fell asleep and crashed on the flight back to base. • Students stay awake during tests and fall asleep during next lecture. • Impairment depends on interactions with food and medications. • Difficult to measure impairment when subject is alive. • Impossible to measure impairment when subject is dead. • Nearly impossible to measure all the variables to obtain good data to relate accidents to sleep in a precise way.

  13. Measurements • Risks analysis tend to be for individual machines. • Risks analysis tend to be for specific activity, such as skiing, driving, flying. • Driving has more risk than flying and both have more risk than sleeping. • Both driving and flying have highly elevated risk when performance is impaired than when normal. • Impairment due to sleep debt is more complicated than with alcohol because of difficulty in measurement of sleep debt and use of counter measures, such as caffeine. • It is difficult to obtain reliable data for increased risk associated with sleep management for driving and nearly impossible to obtain good data for agricultural machines and activities. • Good theory and well-calibrated and robust mathematical models become an essential tools to develop management and safety alternatives.

  14. Simulation Tool • SLEEP Model (Started 1997, public use 2002) • SLEEP Model 2 • http://eddev.coe.ttu.edu/development/schenck/sleep/ • Developed at Texas Tech University. • One of seven sleep models. • Only one that includes alcohol and caffeine as of 2004. • Only one that predicts performance accurately for both total and partial sleep loss.

  15. Performance

  16. Process • SLEEP Model evaluates the performance of the person not the activity. • Calibrated from alcohol data collect at Boone County Hospital in Columbia, Missouri—a rural community. • Because risk in model is calculated based on performance, once calibrated for one effect on performance, it is by default calibrated for other effects on performance.

  17. Data: Vinson et al. (2003) Comparison includes Average Upper 95% confidence Lower 95 % confidence Simulation includes Average drinking rate Binge drinking rate Drinking distributed over 6 hr

  18. Rough Test for Non-Professional Drivers in Finland • No information on caffeine. • Fatal accidents. • Survey of family members after accident. • Accidents with alcohol eliminated. • Predicted is average of simulation with and without caffeine. • Average over three and six-hour durations. • Accepted calibration from alcohol and theory as correct model.

  19. Applications to Agriculture • Infinite possibilities. • General patterns can be obtained. • Age has mixed and often hidden effects. • Older people generally need less sleep. • Older people generally have more fat and more problems of sleep difficulties. • Older people may think and log sufficient sleep time but not get REM and delta sleep. • Young people have more rapid response times but are more likely to misjudge their impairment. • We will work through an example simulation.

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